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Progress in Neurobiology 67 (2002) 393420

MR microscopy and high resolution small animal MRI:applications in neuroscience research

Helene Benveniste a,b,, Steve Blackband c,d

a Medical Department, Brookhaven National Laboratory, Building 490, 30 Bell Avenue, Upton, NY 11793, USAb Department of Anesthesiology, SUNY-SB Stony Brook, New York, NY, USA

c McKnight Brain Institute, University of Florida, Gainesville, FL, USAd The National High Magnetic Field Laboratory, Tallahassee, FL, USA

Received 13 February 2002; accepted 7 June 2002

Abstract

The application of magnetic resonance (MR) imaging in the study of human disease using small animals has steadily evolved over

the past two decades and strongly established the fields of small animal MR imaging and MR microscopy. An increasing number

of neuroscience related investigations now implement MR microscopy in their experiments. Research areas of growth pertaining to MR

microscopy studies are focused on (1) phenotyping of genetically engineered mice models of human neurological diseases and (2) rodent

brain atlases. MR microscopy can be performed in vitro on tissue specimens, ex vivo on brain slice preparations and in vivo (typically

on rodents). Like most new imaging technologies, MR microscopy is technologically demanding and requires broad expertise. Uniform

guidelines or standards of a given MR microscopy experiment are non-existent. The main focus therefore of this review will be on

biological applications of MR microscopy and the experimental requirements. We also take a critical look at the biological information

that small animal (rodent) MR imaging has provided in neuroscience research.

2002 Published by Elsevier Science Ltd.

Contents

1. Introduction . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . .. . . . 394

2. Physical considerations in MRI . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . .. . . . 394

2.1. Spatial resolution and signal-to-noise ratio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 394

2.2. Morphology and image contrast . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . 395

2.3. Temporal resolution and function . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . 396

2.4. When does MRI become MR microscopy? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 396

2.5. Summary . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . .. . . 396

3. Structural neurobiology. . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . 397

3.1. Neuroanatomy . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . 397

3.1.1. In vitro versus in vivo imaging . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . 397

3.1.2. In vitro experimentsformalin-fixed specimens . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 398

3.1.3. Contrast agents for in vitro MR microscopy studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4023.1.4. In vivo MR microscopypractical aspects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 403

3.2. Brain atlases and neuroinformatics . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . 404

3.2.1. Mouse brain atlases by MR microscopy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 404

3.3. Anatomical phenotyping by MR microscopy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 405

3.3.1. Morphometry. . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . 406

Abbreviations: MRI, magnetic resonance imaging; rf, radio frequency; SNR, signal-to-noise ratio; CNR, contrast-to-noise ratio; BMAP, Brain Molecular

Anatomy Project; MAP, map atlas project; LONI, laboratory of neuroimaging; MCA, middle cerebral artery; CBF, cerebral blood flow; ADC, apparent

diffusion coefficient; ApoE, apolipoprotein E; MS, multiple sclerosis; EAE, experimental allergic encephalomyelitis; LPC, lysophospahtidylcholine; AD,

Alzheimers disease; fMRI, functional magnetic resonance imaging; BOLD, blood oxygen level-dependent Corresponding author. Tel.: +1-631-344-7006; fax: +1-631-344-2540.

E-mail address: [email protected] (H. Benveniste).

0301-0082/02/$ see front matter 2002 Published by Elsevier Science Ltd.

PII: S 0 3 0 1 - 0 0 8 2 (0 2 )0 0 0 2 0 -5


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394 H. Benveniste, S. Blackband / Progress in Neurobiology 67 (2002) 393420

4. Pathology visualized by MR microscopy . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . 407

4.1. Stroke . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . .. . . 407

4.1.1. Diagnostic studies . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . .. . . . . 407

4.1.2. MR microscopy studies related to stroke pathophysiology . . . . . . . . . . . . . . . . . . . . . . . . . . 408

4.1.3. Therapeutic stroke studies . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . 410

4.2. Head injury . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . 410

4.3. Demyelinating diseases . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . .. . . . . . . 410

4.4. Aging and dementia . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . 411

4.5. MR microscopy of brain tumors in rodents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 412

4.6. Functional imaging studies in the rodent brain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 413

5. Bridging in vitro and in vivo studies. . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . 414

6. Conclusions . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . .. . . . . 414

Acknowledgements . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . 415

References . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . .. . . . . . . 415

1. Introduction

The application of magnetic resonance (MR) imaging in

the study of human disease using small animals began withthe inception of MR more than 25 years ago. Hansen et al.

published the first anatomically interpretable MR images of

a normal living rat body (Hansen et al., 1980) in 1980 and

thus laid the groundwork for the many MR applications in

small animals soon to follow. The earliest MR applications

using small animals in the study of human disease focused on

tumors (Damadian et al., 1976; Crooks et al., 1980; Hansen

et al., 1980; Davis et al., 1981; Henkelman et al., 198 7)

and sterile abscesses (Herfkens et al., 1981). This effort

was soon followed by studies on MR visualization of acute

stroke, stroke maturation and the testing of various inter-

ventions (Buonanno et al., 1982, 1983; Naruse et al., 1986;Sauter and Rudin, 1986, 1987; Sauter et al., 1988, 1989).

When reviewing the literature over the last two decades

it is clear that physicists, bioengineers and computer scien-

tists continuously improved imaging capabilities of the MR

instruments, which in turn drove bio-application studies for-

ward. On the other hand, biologists increasing demand for

non-invasive imaging technologies suitable to follow pro-

gression and/or regression of disease in small animals and

tissue specimens undoubtedly enforced the fields of small

animal MR imaging and MR microscopy. In the liter-

ature, the term small animal MR imaging is often used

interchangeably with MR microscopy, although strictly

speaking the two fields operate within different spatial res-

olution ranges. However, in the following we will continue

to use the term MR microscopy for all high resolution

MR imaging, although this particular expression usually

refers to images acquired with a resolution of less than

100m in at least one dimension.

Many excellent review articles have been written describ-

ing the evolving MR technology, MR physics and hard-

ware design for MR microscopy (Budinger and Lauterbur,

1984; Chance, 1989; Johnson et al., 1993; Blackband et al.,

1999). This review is not meant to copy or supplement this

plentiful literature. Instead we intend to focus on biological

applications of MRI using small animals such as rodents in

the study of human disease. As it would be impossible to

cover all disease processes thoroughly we choose to con-

centrate on diseases afflicting the central nervous system.We will take a critical look at the biological information

that small animal (rodent) MR imaging has provided in neu-

roscience research. The literature on neuroscience related

investigations involving small animal MR imaging spans a

wide range of research fields, however, a large part of the

review will be dedicated to discussing current and future ap-

plications in transgenic mice, targeted mutations (knockout

mice) and chemically induced mutations in mice. It is this

new research direction that now occupies many MR imaging

laboratories all over the world.

2. Physical considerations in MRI

2.1. Spatial resolution and signal-to-noise ratio

The spatial resolution in MRI depends on multiple factors

(Back et al., 1991; Callaghan et al., 1994) but a good first

approximation, appropriate for the context of this review,

depends primarily on (1) the magnetic field strength used, (2)

the size of the radio frequency (rf) detector coil, (3) the total

signal averaging time, (4) the abundance of the nuclei under

investigation, and (5) the contrast mechanism employed in

the image (Mansfield and Morris, 1982). In the following,it is assumed that signals from the hydrogen nuclei in water

are used to form the images. Following this, a few general

comments can be made:

(A) The signal-to-noise ratio (SNR) increases more than

linearly with magnetic field strength (Mansfield and

Morris, 1982), hence the continuing development of

stronger magnets for MRI. Compromising this SNR

improvement is the cost of the magnets, increased rf

power requirements, potential adverse effects of high

rf power and stronger fields on biological organisms

and increases in image distortions arising from inhomo-


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H. Benveniste, S. Blackband / Progress in Neurobiology 67 (2002) 393420 395

Fig. 1. MR microimages of brain slices showing the tradeoff between spatial resolution and acquisition time. The left image has a resolution of

15m 15m 300m but took 14 h to obtain. The right image has a lower resolution of 120m 230m 300m giving improved SNR that

was traded for a reduction in acquisition time to 4.3 min. Figure reproduced with permission from Bui et al. (1998).

geneities. For the most part a particular user will have

access to a particular magnet and the field strength will

then be fixed.

(B) The SNR increases linearly as the coil size decreases

(Mansfield and Morris, 1982). For this reason, thespatial resolution achieved in a given imaging time is

increased on smaller samples (or at least using smaller

coils to image parts of large samples). Thus resolutions

of hundreds of microns achieved on objects the size of

humans can be improved to a few microns or at least

tens of microns on samples a few millimeters in size.

(C) For the most part, improving contrast in an image

results in a loss of SNR. For example, increasing TE to

obtain more T2 weighting results in signal loss since the

signal decays exponentially with increasing TE. In or-

der to maintain adequate SNR when contrast is required

thus requires ways of regaining the SNR loss and is

most often achieved by reducing the spatial resolution

a little.

Given these issues, once the magnet system has been

chosen and rf coil has been selected (usually optimized

to span the region of interest), then the spatial resolution

obtained using a particular contrast mechanism (imaging

sequence) is mainly determined by the total data acquisition

time. However, SNR only increases as the square root of

the imaging time, while the SNR decreases as cube root of

the isotropic spatial resolution. Fig. 1 illustrates the tradeoff

that can be made between imaging time and spatial reso-

lution in images of a hippocampal rat brain slice. Bear in

mind that increasing the averaging time is thus an expen-

sive way of improving the SNR. For example, halving the

isotropic resolution reduces the SNR by a factor of 8, and

thus to regain the SNR of the lower resolution will require

a 64-fold increase in the imaging time (i.e. to maintain a

constant SNR, then t 1/x6, where x is the linear dimension

of an isotropic voxel and t the imaging time).

Thus a 1 min image would take an hour at half the reso-

lution, and nearly 3 days to halve the resolution again, and

so on. These considerations are obviously important when

considering imaging studies on pathological samples where

scan times can be long or in vivo studies where short scan

times are desirable. Fine details in images require both spa-

tial resolution and sufficient SNR in order to discern them.

2.2. Morphology and image contrast

A MR image can be manipulated to yield either morpho-

logical or functional information. To assess morphology,

SNR and resolution are not enough if signal differences

do not exist between different structureswithout these

the image will be flat and featureless. Thus an adequate

contrast-to-noise ratio (CNR) is required to separate struc-

tures of interest. MR techniques are unique in that several

contrast mechanisms (e.g. T1, T2, diffusion, etc.) may be

employed by using different imaging sequences that con-

trol the degree of contrast that can be achieved (referred to

as the image weighting). Since the contrast mechanisms

arise from distinct physical processes they may be used to

elicit different kinds of contrast that may aid in the resolu-

tion of different features of the sample under examination.

The significance of CNR is illustrated in Fig. 2. The spatial

resolution of all images is 0.00024 mm3 and SNR is 60:1.

On the T2 and T2 images the hippocampus mold can be

clearly outlined while the granule cell layer is barely appre-

ciated as a faint bright v-shaped structure.1 In comparison,

the CNR of the diffusion image is superior to both T2 and

T2 images and several additional hippocampal substructures

are apparent.

On a given MR system, two different sets of MR parame-

ters might display the same anatomical structures differently

or visualize different structures all together. For example, inthe T2 image in Fig. 2, the granule cell layer is visible as

a bright v-shaped line. On the other hand on the diffusion

image a dark line is present in a location corresponding to

the mossy fiber pathway (Fig. 2). Varying the weighting in

an image controls the contrast, but to do so usually requires

a reduction in the SNRthe heavily weighted image may

offer better contrast but requires a reduction in the spatial

resolution to maintain adequate SNR. Often a combination

1 It is here assumed that the bright line represents the granule cell

layer. However, strictly speaking this can only be confirmed by means of

histopathological studies.


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Fig. 2. Three MR microimages of the dorsal hippocampus from a formalin-perfusion fixed C57BL6/J mouse brain acquired at a spatial resolution

of 0.00024 mm3 (9.4T MR instrument, Duke Center for In vivo Microscopy). Three different MR contrast parameters have been used (T2, T2 and

diffusion). The SNR of the three images are 60:1. Note that the display of anatomical structures is dependent on MR contrast used. For example, the

granule cell layer can be appreciated as a faint brighter v-shaped line on T2- and T2-weighted images whereas the mossy fiber pathway is apparent

only on the diffusion image as a dark appearing band.

of MR images using different MR contrast will yield more

anatomical information than either one alone and an imag-

ing protocol often involves the collection of several image

types.

2.3. Temporal resolution and function

As described above, SNR, spatial resolution and CNR are

very important considerations for optimal imaging of tissue

morphology. However, as indicated by Fig. 1, this must be

tempered by the temporal requirements of the study. Aside

from consideration of the cost and access to the scanner

time, studies on pathological tissues can be relatively long,

and tens of hours are not uncommon. However, for in vivo

studies, or studies of dynamic processes and function, the

temporal resolution becomes a major constraint. Sick ani-mals may not tolerate prolonged (or multiple) anesthesia.

Studies of changes in the genesis of a variety of lesion types

will require differing temporal resolutions from minutes

to days. Some dynamic or functional processes (such as

contrast agent uptake or blood flow measures) may require

imaging on the second or subsecond timescale. Cardiac

imaging may also require subsecond imaging techniques.

In all cases, the SNR requirements are exacting and usually

maintained by reducing the spatial resolution.

2.4. When does MRI become MR microscopy?

The delineation between high resolution MRI, small

animal MR imaging and MR microscopy is somewhat

unclear. Definitions for MR microscopy being images with

a resolution of less than 40100 m have been suggested

(Aiken et al., 1995) but are confounded by the number of

dimensions this refers to. For example, the slice width in

MR images is often considerably larger than the in-plane

resolution in order to improve SNR with little compromise

in image quality, taking advantage of some degree (Aiken

et al., 1995) of at least 1D symmetry in many samples (an

analogous situation occurs with optical techniques where

the slice width is the thickness of the section and often

much greater than the in-plane resolution). As suggested by

Aiken et al. (1995), we shall loosely refer to imaging with a

resolution of less than 100m in at least one dimension as

MR microscopy, and imaging above that as high resolu-tion MRI. Generally, the SNR in small animal MR images is

high enough to support the microscopy regime, making MR

microscopy and small animal imaging generally accepted

as synonymous. As indicated in the earlier sections, it is im-

portant not to become fixated with spatial resolution since

SNR, contrast and temporal resolution are as important in

terms of how useful the information content of the study

will be, and thus we consider the term MR microscopy as

indicative of microscopic resolutions, but more a matter of

semantics.

2.5. Summary

Multiple factors control the spatial resolution, SNR and

CNR in MR imaging, and in the above a few of the ma-

jor ones were discussed. Clearly, tradeoffs between spatial

resolution and imaging time are required to obtain the re-

quired contrast and/or functional information. In particular,

the size of the sample and whether the sample is in vivo or

ex vivo are major issues with respect to brain imaging. At

the extremes of present techniques and technology, resolu-

tions of tens of microns can be obtained on small samples

(millimeters to a few centimeters at most) with small coils

in many hours, while resolution of over hundreds of mi-

crons can be obtained in vivo on larger samples in minutes.

Between these extremes are a range of resolutions (spatial

and temporal) mediated by contrast and dynamic/functional

requirements. Many other factors contribute to the appear-

ance of MR images and will not be discussed in detail

here. For example, MR physical variables, such as T2 and

T1 are magnetic field dependent, and thus a given set of

MR parameters used on a low field MR system might yield

different CNR compared to that obtained on a high-field

MR system. Some of these will be alluded to in the rest

of this review and we must leave the reader to further

investigate.


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3. Structural neurobiology

The term structural neurobiology covers several topics.

First, the ability to visualize normal as well as abnormal

neuroanatomy appears to be one of the most prominent and

important applications of the MR microscopy technology

in neuroscience research. Interestingly, research focusedon optimizing the visualization of rodent neuroanatomy

by MR microscopy has developed into separate fields of

brain atlas generation, neuroinformatics and associated

morphometry. Another newly evolving imaging concept is

anatomical phenotyping, which specifically focuses on how

MR microscopy can be used to anatomically characterize or

even screen for relevant pathology in genetically engineered

mice models of disease.

3.1. Neuroanatomy

From a neurobiologist point of view, MR microscopy

images of the rodent brain should capture structural infor-mation suitable to answer the questions of interest. Thus,

for some studies gross anatomical (surface, shape) infor-

mation will suffice while again others will require spatial

resolution at micro-anatomical (tissue architecture) or at the

single cell level. It is fair to conclude that gross anatomical

resolution can be routinely achieved by MR microscopy

in vivo as well as in vitro. However, in regards to tissue

architectural information in vivo data provide insufficient

anatomical information in most brain regions in spite of

technological advances. For example, in 1980 when Hansen

et al. first published in vivo images of the rat brain at a spa-

tial resolution of 0.33mm0.33mm8.4 mm, it appearedas a white homogeneous structure with no anatomical detail

(Hansen et al., 1980). Some years later, Johnson et al. im-

plemented improved MRI hardware for microscopy and

more efficient pulse sequences and produced high-quality

images of a living rat brain at a spatial resolution of

0.05mm 0.05mm 1 m m (Johnson et al., 1987). On

these images several subregional brain structures, such as

the corpus callosum, hippocampus and caudate nucleus

could be identified, however, cell layers could not be clearly

recognized (Johnson et al., 1987, 1986; Rudin, 1987). Sim-

ilar anatomical results were obtained in the living mouse

brain at a spatial resolution of 0.1 mm 0.2 mm 0.9 mm

(Munasinghe et al., 1995) and 0.058mm 0.058mm

0.469mm (McDaniel et al., 2001). In vivo images of the

canary brain were recently acquired at an even higher spa-

tial resolution of 0.078 mm 0.078mm 0.058mm (Van

der Linden et al., 1998). Interestingly, several brainstem

nuclei could be identified on the proton density-weighted

MR images (Van der Linden et al., 1998).

MR microscopy performed on formalin-fixed brain spec-

imens yields far more anatomical information compared

to in vivo for a number of reasons (to be discussed in the

Section 3.1.1). Fig. 3 shows a volume-rendered diffusion-

weighted 3D MRI data set acquired at a spatial resolution

of 2.4 104 mm3. The specimen is a formalin-perfusion

fixed C57BL6/J mouse brain. The 3D rendered forebrain

can be seen in the upper left corner (A) as well as tissue

architectural detail at three different levels (cf. Fig. 3EG).

Although several subregions within the hippocampus can

be appreciated, the spatial resolution, SNR and CNR of the

images presented in Fig. 3 clearly do not support visualiza-tion of single cells within individual cell layers. Structural

information in large single L7 neuronal cells from the ab-

dominal ganglia of sea hares (diameter of 300400 m) has

been obtained using specialized microcoils (Schoeninger

et al., 1994; Grant et al., 2001). However, at present this

has not been achieved in the intact animal or body organ

where the sample is larger and the cells within it smaller.

3.1.1. In vitro versus in vivo imaging

When assessing anatomical MR imaging data, it is im-

portant to distinguish between data acquired in vitro and

in vivo. For example, imaging of tissue specimens, that is,

formalin-perfusion fixed whole brains, fresh brain tissue orimmersion fixed brain tissue confers the experimenter sev-

eral advantages when compared to in vivo imaging. First,

overall scan times can be much longer in vitro (1050 h)

than in vivo (typically 30 min to 4 h per scan), which results

in better SNR for any given voxel size due to more signal

averaging as discussed previously (cf. Section 2). Second, in

vitro samples are obviously motionless, which also enhances

SNR for any given imaging protocol compared to in vivo

imaging; breathing and cardiac activity in the living animal

cause pulsatile physical excursions of up to several mil-

limeters in the brain, which significantly reduces the SNR

if not controlled for during the image acquisition (Hedlundet al., 1986, 2000a). Thirdly, the formalin-perfusion process

chemically alters tissue characteristics so that the CNR in

the MR images changes compared to that of living tissue

(vide infra). Additionally, the sample may often be shaped

(cut down) to fit optimally within the rf coils for optimal

SNR.

To begin to understand differences between in vitro and

in vivo MR imaging one must first compare an image ob-

tained in a living animal with one obtained post-mortem

using the exact same imaging parameters. Fig. 4 shows

two diffusion-weighted MR images of a C57BL6/J mouse

brain acquired at a spatial resolution of 0.058 mm

0.058mm0.46875 mm and a scan time of 2 h and 43 min.

Image A was acquired while the C57 mouse was alive and

B is a post-mortem acquisition of the same mouse (same

body temperature as A). The SNR of image B obtained

post-mortem has improved by 30% compared to image A

secondary to the arrest of physiological motion (breathing,

cardiac activity and/or cerebro-spinal fluid convective flow)

and ischemia-induced increases in the diffusion-signal (cf.

Section 4.1). The first question to ask is whether the SNR

improvement of image B also enhances its CNR (more accu-

rately referred to as a signal difference to noise (SNR))

when compared to image Ai.e. are more structures visible


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Fig. 3. A volume-rendered diffusion-weighted 3D MR data set acquired at a spatial resolution of 2.4 104 mm3 on a 9.4T MR instrument (Duke

Center for In vivo Microscopy). The specimen is a formalin-perfusion fixed C57BL6/J mouse brain. (A) 3D rendered forebrain with three attachedsegmentation planes (BD). (B) Coronal diffusion-weighted MR image at the level of the caudate putamen and globus pallidus. The two nuclei are clearly

visible because the globus pallidus appears darker (see details in (E)). (C and D) Coronal images at the level of the hippocampus. Several hippocampus

subregions are apparent (see details in (F) and (G)).

in image B? Clearly, the most striking difference between

image A and B is the partial obliteration of the lateral and

third ventricle spaces post-mortem secondary to swelling

of the tissue. The black appearing ventricle system actually

confers contrast-to-noise ratios in the in vivo image A facil-

itating definition of several subregions compared to image

B. Thus, in this particular example, the increase in SNR

did not provide significantly more anatomical information

because the CNR did not improve in parallel.

3.1.2. In vitro experimentsformalin-fixed specimens

The advantage of imaging formalin-fixed specimens are

several-fold: (1) the specimens do not undergo autolysis over

time, can be preserved for years and scanned repeatedly; (2)


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Fig. 4. Diffusion-weighted MR microimages (horizontal imaging plane, spatial resolution: 58 m58m470m, 7.1 T MR instrument, Duke Center for

In vivo Microscopy) from a C57Bl6/J mouse brain acquired in vivo (A) and post-mortem (B). The signal-to-noise ratio has increased by 30% in image

B secondary to arrest of physiological motion and ischemia-induced increases in the overall signal intensity. The SNR improvement in B compared

to A does not automatically lead to enhanced visualization of anatomical structures because the contrast-to-noise ratio has not improved in parallel.


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Fig. 5. The effect of air entrapment within the imbedding material used for MR microscopy of tissue specimens is shown. Three large air bubbles have

formed on the dorsal surface of the tissue specimen, which can be seen as dark circular objects in the volume-rendered image (A). The air bubbles cause

large susceptibility artifacts, which obscure anatomical structures and therefore destroys the MR image (B).

etc.) and are affordable. Drawbacks include processing time

and the potential for entrapment of air within the medium,

which causes image artifacts. Further, samples immersed

in agarose gels need to be quickly removed after imaging,

cleaned and restored in formalin to prevent dehydration as

the gelling agars tends to dry out over time. Polyethylene

film and soaked gauzes are easy to use techniques that will

prevent dehydration of specimens at least for shorter periods

of time (probably 24h). However, a given specimen will eventually dry out if stored for

long period of times in Fomblin.


10/28


from the producers (Ausimont USA) and the consequent

considerable expenditure involved. Fluorocarbon (Fluo-

rinert) is another less expensive option, which seems to be

working just as well (Dhenain et al., 2001).

3.1.3. Contrast agents for in vitro MR microscopy studies

Paramagnetic contrast agents can be used to improvetissue discrimination in MR images when intrinsic CNR be-

tween structures is lacking. Contrast agents include chelates

of paramagnetic ions, both ionic and non-ionic, which gen-

erate both T1 and T2 effects (Brasch, 1983, 1992). Short-

ening the T1 results in an increase and shortening the T2

in a decrease of signal intensity (see review by Kroft and

de Roos, 1999). For example, intravenous administration

of gadolinium diethylenetriaminepentaacetic acid complex

(Gd-DTPA) will cause intact vessels to appear bright on

T1-weighted MR images. Several different paramagnetic

contrast agents exist, each characterized by their molec-

ular weights, viscosity, pharmacodynamic parameters and

Fig. 6. The effect of adding a contrast agent (Gd-DTPA) to the formalin fixation medium is shown. Without contrast enhancement the T2-weighted

MR microimage displays a limited number of anatomical structures (top image). The contrast-enhanced MR T2-weighted image provides superior

visualization of several hippocampal subregions (bottom image).

pharmacokinetic parameters (Runge, 1999; Kuriashkin and

Losonsky, 2000; Torchilin, 2000).

In vivo, the available contrast agents will not pass the

intact blood brain barrier (BBB); however, this problem

can be circumvented by administering them (a) intrathe-

cally, (b) into areas/structures without a BBB or (c) directly

into the brain parenchyma. For example, a 1:40 dilutionof Gd-DTPA:0. 9% NaCl administered intrathecally was

used to visualize positioning of spinal catheters in live rats

(Benveniste et al., 1999) and also enhanced visualization of

individual nerve roots (Benveniste et al., 1998). In another

study, a dilution of MnCl2 was administered into the olfac-

tory epithelium in living anesthetized rats via the naris and

directly into the aqueous humor of the eye (Pautler et al.,

1998). Twenty-four hours later, the presence of Mn2+ was

demonstrated in the olfactory pathway or the optic tract on

T1-weighted MR images indicating anterograde transport

of the tracer (Pautler et al., 1998). Jacobs and Fraser (1994)

injected single frog blastomeres with a covalent conjugate


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of dextran with diethylenetriaminepentaacetic acid chelated

to Gd to follow embryogenesis. By means of repetitive

imaging, they were able to follow over time the migration

of contrast-enhanced cell clusters in the developing blas-

tomeres during gastrulation and neurulation (Jacobs and

Fraser, 1994; Ahrens et al., 1998b).

To enhance the CNR in high resolution MR images oftissue specimens and isolated body organs, paramagnetic

contrast agents have been added to the formalin fixation

medium (Johnson et al., 1993; Mellin et al., 1994; Smith

et al., 1994, 1996; Benveniste et al., 2000). For example,

Smith et al. injected bovine serum albumin coupled to

DTPA-Gd dissolved in 1% gelatin into the umbilical vein of

mouse embryos to augment anatomical visualization (Smith

et al., 1994). Using this technique, Smith et al. completed

a digital atlas that contains magnetic resonance images

of normal mouse embryos from 9.5 days after conception

to the newborn (Mellin et al., 1994; Smith et al., 1999);

http://embryo.soad.umich.edu/animal/bradresearch / bradre-

search.html). The digital MR microscopy embryology atlasseries include surface views as well as cross-sectional views

from the transverse, coronal, and sagittal planes for each

embryo and are also organized as a reference for researchers

studying embryological anatomy.

The addition of gelatin to the macromolecular contrast

agent fixation media allowed for greater than normal image

contrast due to intravascular retention of the contrast agent

(Smith et al., 1994). Without the addition of gelatin, the

contrast/formalin solution diffuses out of the intravascular

compartment into the interstitial and intracellular compart-

ments and reduces the CNR in the image (Benveniste et al.,

2000).The addition of Gd-DTPA to formalin-perfusion fixation

media has also been used to enhance visualization of tissue

architecture in the C57BL6/J mouse brain (Benveniste et al.,

2000). Figs. 6 and 7 show the effect of 1:40 (v/v) Gd-DTPA:

formalin on the CNR in the T2-weighted image. Without

contrast enhancement only the hippocampal outline and the

granule cell layer can be seen within the hippocampus region

(Fig. 6A); however, several hippocampal subregions are re-

vealed by the addition of contrast probably due to regional

differences in vessel density (Benveniste et al., 2000).

3.1.4. In vivo MR microscopypractical aspects

For the reader to truly appreciate the multidisciplinary

expertise involved in small animal in vivo MR microscopy

studies (Section 4), we will briefly review some of the tech-

nical requirements involved. First, the successful outcome

of any MRI experiment involving live animals is dependent

on a team of investigators. The MR physicist, bioengineers,

computer scientists, and MR instrument operator, together

with the biologist/physiologist must carefully plan all prac-

tical aspects of the experiment. The anesthesia, physiolog-

ical monitoring and gating requirements, that is, image

acquisition triggered by cardiac and/or ventilation (Hedlund

et al., 1986, 2000a,b; Johnson et al., 1993) must be addressed

Fig. 7. MR microimage of a single neural cell, the L7 cell from the ab-

dominal ganglia of the sea slug Aplysia californica. The spatial resolution

is 20m 20m 100m. The image shows a bright central nucleus

surrounded by dark cytoplasm, in turn surrounded by artificial seawater.

Reprinted by permission from Schoeniger and Blackband (1994).

as well as the expected length of the imaging sequence.3

The latter is important in regards to choice of anesthesia,

hydration requirements, and propensity for animal survival.

Table 2 presents a list of anesthetic agents, which have been

and continue to be used in various in vivo MR studies on

rodents. There is no right or wrong in regards to selec-

tion of anesthetic agents as long as (1) the compounds ful-

fill their main goal, that is, provide the animal relief of pain

and discomfort during the procedures and (2) the anesthetic

agent does not interfere with the goals of the study. The

latter has proven to be a problem in certain functional MR

imaging studies (Prichard et al., 1995; Yang et al., 1996).

For example, in two studies involving somatosensory activa-

tion, inhalational anesthesia (enflurane and halothane) was

replaced with -chloralose during this particular part of the

study (Gyngell et al., 1996; Yang et al., 1996). In a recent

study, it was also shown that anesthetic agents often used

in MR microscopy studies affect cerebral perfusion differ-ently (Hendrich et al., 2001). Another concern is the choice

of anesthetic agent for survival studies. Although relatively

few longitudinal rodent MR microscopy studies have been

published, it appears that inhalational agents are preferred

probably because they are easy to administer, rapidly ad-

justable and inexpensive (Wood et al., 2001).

3 The quantitative impact of cardiac gating and scan-synchronous venti-

lation on SNR and CNR in brain studies is not known. In most live animal

brain studies a stereotaxic frame immobilizes the head of the rodent and

images are not routinely acquired with cardiac and/or scan-synchronous

ventilation.
http://embryo.soad.umich.edu/animal/bradresearchprotect%20kern%20+.1667emelax%20/protect%20kern%20+.1667emelax%20bradre-search.htmlhttp://embryo.soad.umich.edu/animal/bradresearchprotect%20kern%20+.1667emelax%20/protect%20kern%20+.1667emelax%20bradre-search.htmlhttp://embryo.soad.umich.edu/animal/bradresearchprotect%20kern%20+.1667emelax%20/protect%20kern%20+.1667emelax%20bradre-search.html


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Table 2

Anesthetic agents used in MR imaging studies on rodents

Species Agent Route of administration Reference

Mice Halothane and N2O Inhalational Zaharchuk et al. (1997)

Pentobarbital Intraperitoneal Atlas et al. (1990), Huang et al. (1996)

Isoflurane Inhalational van Bruggen et al. (1999)

Rats Halothane Inhalational Benveniste et al. (1991), MacFall et al. (1991), Benveniste et al.,1992, van Bruggen et al., 1992, Beaulieu et al. (1993), Verheul et al.

(1993), Jiang et al. (1994), Lo et al. (1994), Roussel et al. (1994),

Busch et al. (1996), Rother et al. (1996), Jiang et al. (1997)

Isoflurane Inhalational Minematsu et al. (1992), Latour et al. (1994), Hasegawa et al.

(1995), Mancuso et al. (1995), Hall et al., 1996, Porszasz et al.

(1997), Qiu et al. (1997), Benveniste et al. (1999, 2000),

Miyasaka et al. (2000)

Chloralose Intravenous, intraperitoneal Gyngell et al. (1996), Yang et al. (1996)

Ketamine and pentobarbital Intramuscular, intraperitoneal Buonanno et al. (1983)

Diazepam fluanisone and fentanyl Intraperitoneal, intramuscular Verheul et al. (1992)

Pentobarbital urethane Intraperitoneal, subcutaneously Takahashi et al. (1993)

Pentobarbital Intravenous, intraperitoneal van Nesselrooij et al. (1989), Ford et al. (1990), Ogawa et al.

(1990), Hanstock et al. (1994)

N2O/O2 MSO4 Inhalational, subcutaneously Prichard et al. (1995)

Xylazine and ketamine Intravenously van de Vyver and Peersman (1990), Ford et al. (1990)

Gerbils Pentobarbital Not reported Kato et al. (1986)

The requirement for physiological monitoring and manip-

ulation of physiological parameters is obviously dependent

on study design. However, as a minimum requirement body

temperature, heart rate/ECG and respiratory rate of the ani-

mal need to be continuously monitored while the animal is

unapproachable in the magnet bore. Heart and respiratory

rates are essential to monitor in order to indirectly assess and

adjust anesthetic depth and for experiments requiring venti-

lation synchronous scanning and cardiac gating. Obviously,maintaining a normal body temperature is important for all

in vivo studies unless hypothermia is a requirement (Jiang

et al., 1994). For survival studies it is probably better to ad-

here to minimally invasive monitoring devices so as to assure

the lowest morbidity and mortality of the study groups. Lim-

ited information is currently available on the subject of mor-

tality in live animal MR studies as this parameter is rarely

reported in the literature. However, with the increase in use

of sick, immune deficient and overall physically fragile ge-

netically engineered mice in MR imaging studies, it will be

important to gather more general knowledge in this area.

3.2. Brain atlases and neuroinformatics

The Brain Molecular Anatomy Project (BMAP) is an

ongoing multi-institute NIH initiative that supports research

on the genomics of the nervous system with an initial effort

dedicated towards the study of gene expression patterns in

mouse and human brains (for more information, see http://

www.nimh.hih.gov/research/brainatlas.cfm). In lieu of this

initiative, a demand for interoperable databases and as-

sociated data management capable of extracting, storing,

fitting and displaying spatially distributed gene ex-

pression patterns into the human and rodent brain have

developed. Within the neuroinformatics community, such

multi-dimensional databases are often broadly referred to as

brain atlases or multi-dimensional atlases (Ghosh et al.,

1994; Dhenain et al., 2001; see also http://embryo.soad.

umich.edu/animal/bradResearch/bradResearch.html). The

ideal brain atlas database would not only serve as an

anatomical standard against which data can be compared

but also function as a management system of data. Thus, the

atlas needs to be digitally manipulative and freely availableon the World Wide Web. To function properly it should be

equipped with (1) a common coordinate system, (2) anatom-

ical labels for all the atlas elements (defined by the spatial

resolution of the images), (3) computational tools/algorithms

to allow the user to spatially map any given type of data

into the normalized atlas reference space, graphic interfaces

and querying approaches, (4) provided with systems for

information retrieval, biological modeling and simulation

and (5) links to all other relevant databases (for more detail,

see http://www.nimh.nih.gov/neuroinformatics/).

3.2.1. Mouse brain atlases by MR microscopy

As discussed, MR microscopy certainly has the capa-

bility to visualize mouse brain anatomy in sufficient detail

to be used to produce atlas templates for standardization,

mapping of histological data, gene expression patterns,

and functional imaging activation studies and for general

data retrieval. For this particular purpose, non-invasive MR

imaging data would seem superior to both cryo- and con-

ventional histological technologies because the data output

is naturally 3D. Further, the 3D MR data can be acquired

in an isotropic format so that any given slice plane can

be obtained without loss of structural information due to

zero-filling. The latter is important for general accuracy of
http://www.nimh.hih.gov/research/brainatlas.cfmhttp://www.nimh.hih.gov/research/brainatlas.cfmhttp://www.nimh.nih.gov/neuroinformaticshttp://www.nimh.nih.gov/neuroinformaticshttp://embryo.soad.umich.edu/animal/bradResearch/bradResearch.htmlhttp://embryo.soad.umich.edu/animal/bradResearch/bradResearch.htmlhttp://www.nimh.hih.gov/research/brainatlas.cfmhttp://www.nimh.hih.gov/research/brainatlas.cfm


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computational algorithms because it is important to preserve

as many landmarks (including accurate surface reconstruc-

tion) as possible when mapping, fitting and warping

other modality images into the atlas template.

Traditionally rodent brain atlases are made from histo-

logical processed brain sections, i.e. Nissl-stained sections

or cryo sections (Sidman et al., 1971; Slotnik and Leonard,1975; Pellegrino et al., 1979; Paxinos and Watson, 1982;

Franklin and Paxinos, 1997). Although this type of data

is 2D, it is actually possible to reconstruct 3D atlases

from cryo data because the input data from post-mortem

cryosectioning are digital images of the cryo-planed spec-

imen block face and are therefore already registered data

(Toga et al., 1994a,b). Nevertheless, cryo data does not

yield much anatomical information as the cryosections are

unstained and therefore do not serve as an ideal template to

use in regards to mapping and retrieval of anatomical in-

formation. Conventional stained histological brain sections

by definition provide the best visualization of neuroanatom-

ical structures. However, attempts to utilize histologicalmaterial for digital 3D reconstructions have often failed

due to (a) non-contiguous slice data sampling, (b) spatial

inconsistencies, and (c) artifacts caused by the histologi-

cal processing (staining and slide mounting). Nevertheless,

several initiatives are underway, which appear promising

(http://www.hms.harvard.edu/research/brain/).

A 3D digital MR microscopy atlas of a neonate mouse

lemur (primate Microcebus Mimurinus) cadaver head at

60m cubic voxel was produced in 1994 (Ghosh et al.,

1994). The images from this atlas display gross anatom-

ical structures as well as some micro-anatomy. This MR

microscopy atlas, however, has not been attached to a ref-erence space and coordinates for brain structures cannot

be obtained (Ghosh et al., 1994). Currently, there are only

two digital web based digital mouse brain atlases that are

based on MR microscopy data. The mouse atlas project

(MAP) out of the laboratory of neuroimaging (LONI) dis-

plays adult C57Bl6/J mouse brain anatomy and consists

of four different image modalitiesNissl-stained brain

sections, MR microscopy data, cryo data and labeled sec-

tions (http://www.loni.ucla.edu/MAP). Although this atlas

is still under development, it already has multiple elegant

functions. The interactive 2D viewer allows the user to

examine mouse brain data (four different modalities) in

three different imaging planes. Each of the data modali-

ties provides alternate anatomical information, that is, the

MR data sets display white matter particularly well while

the Nissl-stained brain data shows cell bodies/cell layers.

Several desirable functions are still under development

for example, labeling of structures when activating voxels

on individual images, links to same structures on other

modality images, etc. However, other MAP tools are avail-

able and include the 3D viewer and segmentation software,

which can be downloaded, explored and utilized. Proba-

bly the LONI MAP project is the most advanced digital

web based neuroinformatics tool available for mice data.

Another mouse brain atlas website is the atlas of the devel-

oping mouse brain (http://mouseatlas.caltech.edu/13.5dpc/)

produced by Dhenain, Ruffins and Jacobs out of the Bio-

logical Imaging Center at CalTech (Dhenain et al., 2001).

This atlas also has an interactive 2D viewer and addition-

ally provides the user with access to 3D rendered models of

labeled segmented structures produced from the single 2Dslices (segmentation routines can be reviewed on the 2D

viewer). Anatomical information and links to other relevant

web sites are also provided.

The current MR microscopy brain atlases are based on

a single brain specimen, and a probabilistic mouse brain

atlas is not yet available. Further, only one mouse strain is

represented (C57BL6/J). Obviously, multiple mice strains

exist each of which might express subtle unique anatomical

features. Another issue is whether the atlas template should

be produced from in vivo or in vitro specimens. Probably,

the best solution will be to have available in vivo as well

as in vitro templates as histologically processed brain sec-

tions are best mapped into an in vitro template, while otherdata requires in vivo templates. There is no doubt that web

based neuroinformatics tools for mice brain data are rapidly

developing. Several multi-disciplinary research groups are

currently working on different parts of the neuroinformatics

puzzlethe anatomists and neuroimagers are focusing on

the atlas templates and the computer scientists on the map-

ping algorithms, data bases and query mechanisms. Thus, in

the near future it will unquestionably be possible to routinely

access web based rodent brain atlases in a fully functional

neuroinformatics format as defined in the original mission

statement (http://www.nimh.nih.gov/neuroinformatics/).

3.3. Anatomical phenotyping by MR microscopy

The term anatomical phenotyping refers here to a char-

acterization of the observable anatomy in a given structure

or organism. Lately, there has been an ongoing and fo-

cused debate on the topic of how to develop high resolu-

tion imaging technologies into phenotypic screening tools of

transgenic and knockout mice models (NIH, 1999; see also

http://birn.ncrr.nih.gov/birn/). For the MR microscopy tech-

nology, the general idea is to acquire 3D data sets of a given

transgenic or knockout mouse and rapidly determine if the

genetic manipulation has caused any anatomical changes.

The scientific desire to streamline high resolution imaging

technologies for this particular purpose has high priority for

many reasons. First, when a given transgenic mouse, targeted

mutation or chemically induced mutation in mice are engi-

neered, the purpose most often is to create an animal model

of a given human disease or to find out what phenotype a

particular gene is responsible for. Conventional phenotypic

studies can take a long time, and it is not unusual that a given

mutation does not alter the phenotype. For the molecular bi-

ologists and bioengineers, therefore, it becomes important to

have available screening tools to rapidly determine whether

the desired pathologyor any pathology for that matter
http://www.hms.harvard.edu/research/brainhttp://mouseatlas.caltech.edu/http://birn.ncrr.nih.gov/birnhttp://www.nimh.nih.gov/neuroinformaticshttp://mouseatlas.caltech.edu/http://www.loni.ucla.edu/http://www.hms.harvard.edu/research/brain


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is present in the mouse model. Current screening tools in-

clude behavioral testing and conventional histology. Behav-

ioral testing is probably one of the most frequently used

modalities for defining phenotypes in genetically engineered

animals. By defining abnormal behaviors in transgenic or

knockout mice scientists have a measure of the phenotype

towards which a given hypothesis can be tested. Behavioraltesting requires expertise and considerable experience. In a

recent book on behavioral phenotyping of transgenic and

knockout mice it was stated that scientists are best advised

to seek training or collaboration with a good behavioral

neuroscience laboratory rather than set up the behavioral

tasks independently (Crawley, 2000). Thus, there are mul-

tiple pitfalls and false negatives/positives in behavioral as-

says and some scientists, therefore, view behavioral testing

to be too complex and/or time-consuming. The latter issue

is obviously essential to the pharmaceutical and biotechnol-

ogy industry. Conventional histological techniques are inva-

sive, often cumbersome and do not allow the investigator to

follow the onset, progression and/or regression of relevantpathology over time in the same animal. Regardless, in the

ideal world behavioral testing should routinely be combined

with a non-invasive measure of structure (and/or function) in

order to characterize a given phenotype in depth (as exam-

ples, see studies by Virley et al., 2000; Reese et al., 2000).

For any high resolution imaging technology to become

the perfect tool for anatomical screening, it needs to fulfill

the following criteria: (a) provide superior anatomical de-

tail of any given structure at least at the micro-anatomical

resolution range, (b) fast data acquisitions, (c) efficient

and low-risk animal throughput (many animals need to be

screened within a given time period with minimal morbidity

Table 3

Examples of morphological phenotyping in rodents by MR microscopy

Species/strain Magnetic

field (T)

Spatial

resolution (mm3)

Disease model Pathology detected Reference

Rattus/SpragueDawley 4.7 0.027 (in vivo) Prolactinoma Pituitary hypertrophy Rudin et al. (1999),

van Nesselrooij et al.

(1989)

Rattus/Lewis 7 8 104 (in vitro) Experimental allergic

encephalomyelitis

MS lesions Lanens et al. (1994)

Cheirogaleids/dwarf

and mouse lemurs

11.7 3 105 (in vitro) Aging Iron accumulation Gilissen et al. (1998)

Homozygous,

heterozygous AGA

and C57Bl6/J mice

1.5 6 103 (In vivo) Lysosomal storage disease:

Aspartylglucosaminuria

Enlarged ventricle

system; cerebral

atrophy

Tenhunen et al. (1998)

11.7 3 105 (in vitro) Experimental allergic

encephalomyelitis/multiple

sclerosis

MS lesions Ahrens et al. (1998a)

AnkyrinB(/) and

AnkyrinB (+/+) mice

7.1 1.2 104 (in vitro) Mental retardation,

hydrocephalus

Enlarged ventr.,

stenosis of the

aqueduct

Scotland et al. (1998)

Mouse/C57Bl6/J/male 7.1 1.6 103 (in vivo) Transient global

cerebral ischemia

Enlarged ventr.,

hippocampal atrophy

McDaniel et al. (2001)

Mouse/SJL/NBOM 1.5 ? (in vivo) Herpes simplex virus

encephalitis

Contrast-enhanced

lesions on T1-

weighted MRIs

Meyding-Lamade et al.

(1998)

and mortality) and (d) the user needs to be able to rapidly

extract relevant information from the data. Clearly, MR

microscopy is able to visualize an abundance of anatomi-

cal structures within any given organism/body organ albeit

not all. MR hardware (e.g. high-field magnets, rf coils)

(Hurlston et al., 1999; Miller et al., 1999) and development

of time-efficient pulse sequences have enabled rapid acqui-sition of 3D data sets at high spatial resolution (Suddarth

and Johnson, 1991). In the future, special hardware will be

designed that enable high-quality MR imaging of several ro-

dents at a time (Henkelman et al., 1987). We will soon learn

whether such efforts will provide consistent high-quality

data output. Another important issue to be solved in regards

to multi-animal imaging is the implementation of physi-

ological monitoring, cardiac gating and scan-synchronous

ventilation. Finally, the access to computational tools and

algorithms that allows the user to extract relevant data from

the 3D data sets is far from being available.

Although the literature is still sparse with reports on

the use of MR microscopy for anatomical phenotyping, itis nevertheless increasing (cf. Table 3). Fig. 8 shows how

MR microscopy was used to anatomically phenotype the

AnkyrinB/ neonatal mice brain in vitro (Scotland et al.,

1998).

3.3.1. Morphometry

In Section 3.3, we reviewed the literature on anatomical

phenotyping by MRI in animal models of human diseases.

In most of these studies (cf. Table 3), the discovered pathol-

ogy on the MR images was converted into a quantitative

measurefor example, an enlarged ventricle system, hy-

pertrophy or atrophy. The techniques used in these studies


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Fig. 8. An example of anatomical phenotyping using in vitro MR microscopy is demonstrated. Volume-rendered 3D diffusion-weighted images of a

formalin-perfusion fixed normal brain (EF5 +/+) and a knockout mouse brain (AnkyrinB/, EF8/) are shown. Several anatomical structures can be

identified (yellow arrows). The presence of hydrocephalus (enlarged lateral ventricles) can be observed in the 3D image of the knockout mouse brain.

for measurement of the size and shape of biological struc-

tures was based primarily on manual segmentation. By

segmentation we mean the operation whereby contours

are constructed to partition, for example, the rodent brain

into structures of interest. These regions are typically con-structed manually according to quasi-objective criteria re-

lating to signal intensity transitions, which can be difficult

particularly in three dimensions. The concept of automated

segmentation has become increasingly important with the

now large volume of MR microscopy data being generated

from genetically engineered animals. It is now essential that

this type of data be both rapidly and accurately analyzed.

The accuracy becomes even more of an issue given the fact

that anatomical changes in genetically engineered mice can

be extremely subtle and barely detectable with less sensitive

techniques such as manual segmentation. Improved SNR

and CNR in MR microscopy images will enable possible

use of automated segmentation software in the future.

4. Pathology visualized by MR microscopy

4.1. Stroke

The use of MR microscopy, or at least high resolution

MRI, for detection of stroke was an obvious research appli-

cation given the ability of the technology to visualize the

high concentration of proton-rich water . . . in biological

systems (Buonanno et al., 1982, 1983; Levy et al., 1983;

Mano et al., 1983; Brant-Zawadzki et al., 1985). Thus due

to a higher than normal water content within ischemic brain

tissue secondary to the presence of vasogenic edema the

infarct would theoretically be apparent on, for example,

proton density-weighted MR images. Buonanno et al. werethe first to provide the proof of principle in regards to ac-

tually demonstrating ischemic brain tissue non-invasively

by MR imaging (Buonanno et al., 1982, 1983). In one of

the earliest experiments, serial proton density-weighted MR

images were acquired in gerbils after unilateral occlusion of

the common carotid artery and areas of increased signal in-

tensity were demonstrated within the occluded hemisphere

as early as 2 h after ischemia onset (Buonanno et al., 1983).

Corresponding spectroscopy data on the excised ischemic

tissue revealed elevated T1 and T2 relaxation times when

compared to non-ischemic control tissue (Buonanno et al.,

1983). Over the last two decades, numerous scientific re-

ports have appeared on the topic of MRI and stroke. In an

attempt to briefly review this plentiful literature in a sys-

tematic fashion, we have divided it into three major topics:

(a) diagnostic studies, (b) pathophysiological studies and

(c) studies testing therapeutic interventions.

4.1.1. Diagnostic studies

MR microscopy provided researchers with a mean to

non-invasively detect the presence of an ischemic infarct

or stroke in the brain of the living animal. This capabil-

ity was a unique revelation to neuroscientists because for

the first time it was possible to study the phenomenon of


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stroke maturation as it occurred andat least theoretically

follow the effect of therapeutic interventions in a much more

aggressive manner than was permitted by neurological ex-

ams alone. The first efforts used proton density, T1- and

T2-weighted MR microscopy, to detect and characterize the

progression of focal ischemic lesions (Buonanno et al., 1982,

1983; Levy et al., 1983; Mano et al., 1983; Brant-Zawadzkiet al., 1985; Horikawa et al., 1986; Kato et al., 1986; Naruse

et al., 1986) and global transient cerebral ischemia (Iwama

et al., 1992). Major conclusions from these first studies were

as follows: (1) ischemic brain tissue could be visualized on

T1- and T2-weighted MR images 24h after onset of stroke

(Buonanno et al., 1983; Levy et al., 1983; Mano et al., 1983;

Brant-Zawadzki et al., 1985), (2) signal changes on T1- or

T2-weighted images and significant increases in T1 and T2

relaxation times occurred only in neurologically affected

animals suggesting diagnostic specificity (Buonanno et al.,

1983; Levy et al., 1983) and (3) the area of signal change on

T1- and T2-weighted MR images induced by ischemia cor-

related with histological evidence of necrosis at late (>16 h)post-ischemic time points (Buonanno et al., 1983; Levy

et al., 1983; Brant-Zawadzki et al., 1985).

Diagnostic stroke studies took another step for-

ward in 1990 when Moseley et al. discovered that

diffusion-weighted MR imaging was far more sensitive

than T1- and T2-weighted MR imaging in detection of

ischemic brain tissue (Moseley et al., 1990a,b). Thus,

diffusion-weighted images displayed a significant hyperin-

tensity in ischemic brain regions as early as 45 min after

onset of the stroke in cat brains (Moseley et al., 1990a).

This result was later confirmed in experimental focal is-

chemia models in rats (Knight et al., 1991, 1994; MacFallet al., 1991; Mintorovitch et al., 1991; Benveniste et al.,

1992; Minematsu et al., 1992; van Bruggen et al., 1992;

Verheul et al., 1992; Lo et al., 1994) and mice (Zaharchuk

et al., 1997; Hata et al., 1998; van Bruggen et al., 1999). In

contrast to the rapid demarcation of the ischemic territory

in stroke models, it apparently takes several days for signal

changes to appear on diffusion-weighted MR brain images

after transient cerebral global ischemia in rats (Kawahara

et al., 2000). Similarly, in C57BL6/J mice exposed to tran-

sient global forebrain ischemia signal intensity changes

on diffusion-weighted MRIs were observed three days

post-ischemia, but only in areas with profound necrosis

(McDaniel et al., 2001). Interestingly, the ischemia-induced

signal increases on diffusion-weighted MR images seemed

to be specific for brain tissue because it did not occur simul-

taneously in the adjacent temporal muscle (MacFall et al.,

1991).

In the focal ischemia models, it was noted that the lesion

expanded over time (Lo et al., 1994; Roussel et al., 1994;

Hall et al., 1996) and that the growth was caused by

peri-infarct depolarizations (Hasegawa et al., 1995; Busch

et al., 1996; Rother et al., 1996). Fig. 9 shows expansion

of a stroke lesion in rat brain following occlusion of the

middle cerebral artery (MCA). The diffusion-weighted im-

ages shown in Fig. 9 were acquired at 6 and 21 h following

MCA occlusion, and it is clear that the high signal intensity

area has enlarged over the 13 h ischemia time period. Again

other studies have shown that signal changes induced by is-

chemia on diffusion-weighted MR images can be reversed if

the ischemic episode is limited (Mintorovitch et al., 1991).

However, reversal of ischemia-induced diffusion changesdoes not necessarily signify that histologic normalization

has occurred (Miyasaka et al., 2000).

A series of T2- and diffusion-weighted MR microscopy

experiments were performed in rats at various times after

stroke onset and correlated with histopathology (Jiang et al.,

1997). From these and other studies, a model of dual pa-

rameter MRI analysis was developed, which could be used

to predict the state of tissue damagetheoretically at any

given time point following stroke onset (Welch et al., 1995;

Jiang et al., 1997; Virley et al., 2000). Further refine-

ment of the multi-parameter MRI analysis in predict-

ing tissue damage also referred to as tissue signature

modeling for classification of ischemic tissue damagewas recently undertaken by Jacobs et al. who imple-

mented an unsupervised segmentation method cluster

analysis algorithm (Jacobs et al., 2000). This tech-

nique was shown to accurately identify ischemic cell

damage both early and later after stroke onset (Jacobs

et al., 2000).

4.1.2. MR microscopy studies related to stroke

pathophysiology

What exactly do ischemia-induced signal changes on

T1-, T2- and diffusion-weighted MR images reflect in

pathophysiological terms? For neuroscientists and neurol-ogists this is obviously an extremely important question to

address in order to successfully implement the diagnostic

capabilities of MRI in the treatment of stroke in humans.

How else can clinicians correctly interpret signal changes

in the course of therapy? By understanding in detail the un-

derlying pathophysiology for a given MR parameter change

in the course of stroke evolution, we will learn how and

when it is possible to intervene and when it is too late.

The mechanism of stroke detection by proton density-

weighted MR imaging was straightforwardly explained as a

consequence of a higher than normal water content within

the infarcted area (Buonanno et al., 1983; Levy et al., 1983;

Horikawa et al., 1986; Naruse et al., 1986). However, the

pathophysiological mechanisms underlying corresponding

changes in T1 and T2 relaxation times were more diffi-

cult to define. It became clear that T1 and T2 changes in

ischemic tissue were delayed by 24 h after stroke onset

(Buonanno et al., 1983; Horikawa et al., 1986; Kato et al.,

1986) and corresponded to the lag in vasogenic edema for-

mation (Horikawa et al., 1986). It was also demonstrated

that T2 relaxation times increased quantitatively more

than T1 relaxation times after ischemia onset (Kato et al.,

1986), and T2-weighted imaging sequences were, there-

fore, more time sensitive to detection of ischemic tissue


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Fig. 9. Diffusion-weighted MR images from rat brain acquired in vivo at 6 h (top) and 21 h (bottom) following occlusion of the middle cerebral artery. The

stroke can be recognized as a high signal intensity area (arrows) located in the frontal and parietal cortices at 6 h. It is clear that the ischemia-induced

high signal intensity area has enlarged and intensified over the 12 h period.

(Kato et al., 1986). Kato et al. found superior quantitative

correspondence between ischemia-induced areas of high

signal intensity on T1- and T2-weighted MR images and

areas of potassium depletion but not with areas of ATPase

reductions (Kato et al., 1986). Interestingly, when T1 and

T2 relaxation times measured in ischemic brain tissue were

plotted against corresponding values of tissue water con-

tent, T1 was found to be linearly dependent on it whereas

T2 values were not (Kato et al., 1986; Kamman et al.,

1988; Venkatesan et al., 2000). Thus, the increase in T2 by

ischemia could not be explained on the basis of water con-

tent alone (Kato et al., 1986) and it was suggested to be an

effect of protein content alterations (Kamman et al., 1988).

A more extensive analysis of relaxation times in edematous

tissue by Naruse et al. further revealed that the T2 decay con-

sisted of two time components in ischemic tissuea fast and

a slow componentand only one in normal tissue (Naruse

and Hirakawa, 1986; Naruse et al., 1986). The fast compo-

nent presumably reflected the intracellular fraction and

the slow component the extracellular fraction (Naruse

and Hirakawa, 1986; Naruse et al., 1986). In ischemic tis-

sue, the T2 values of the extracellular fraction were lower

than that of the intracellular fraction because of accumula-

tion of protein-rich edema fluid, which over time restricted

movement of water molecules in this compartment (Naruse

and Hirakawa, 1986; Naruse et al., 1986).

In regards to diffusion-weighted imaging, the pathophys-

iological mechanisms behind stroke detection are more ap-

parent. First, significant correlation was found between the

early ischemia-induced diffusion-weighted signal intensity

changes and alterations in Pii:PCr and lactate:NAA peak

area ratios (Moseley et al., 1990a,b). It was suggested, there-

fore, that the hyperintensity on diffusion images represented

disturbances of the intracellular energy metabolism and thus

could possibly serve as a more specific diagnostic tool of

the ischemia process itself (Moseley et al., 1990a,b). In sup-

port of this statement, it was shown that the signal started to

increase on diffusion-weighted images when cerebral blood

flow (CBF) was reduced to 1520 cm3/(100 g min) in gerbil

brains (Busza et al., 1992; Mancuso et al., 1995).


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Moseley et al. also suggested that the ischemia-induced

apparent diffusion coefficient (ADC) decrease was due to

intracellular swelling (cytotoxic edema) during which wa-

ter protons originally in the faster-diffusing extracellular

space migrate into a more diffusion-restricted intracellu-

lar compartment (Moseley et al., 1990a,b). In favor of

this hypothesis, it was later shown that cytotoxic edemainduced in the living brain with ouabain known to arrest

Na+K+ ATPase also produced a decrease in the ADC

similarly to that induced by ischemia (Benveniste et al.,

1992). This was also observed under more controlled con-

ditions in the isolated perfused rat hippocampal brain slice

(Buckley et al., 1999b). Similarly, other pathophysiological

processes known to cause cytotoxic cell swelling, such as

excitotoxins (King et al., 1991; Benveniste et al., 1992;

Verheul et al., 1993, 1994; Dijkhuizen et al., 1996; Black-

band et al., 1999), cortical spreading depressions (Latour

et al., 1994; Hasegawa et al., 1995; Busch et al., 1996)

and cardiac-arrest induced anoxic depolarizations (Davis

et al., 1994; de Crespigny et al., 2001) also reduce theADC. Interestingly, within 1020 s of cardiac arrest there

is an immediate 5% ADC decrease, which is attributed to

the cessation of vascular spin motion (de Crespigny et al.,

2001). All the above mentioned diffusion imaging experi-

ments have served to partly clarify the diagnostic potential

of diffusion-weighted MRI and made it clear that if used

for stroke diagnostic purposes diffusion imaging needs to

be combined with other imaging modalities (e.g. perfusion,

spectroscopy) in order to obtain adequate information.4

4.1.3. Therapeutic stroke studies

Therapeutic interventional studies with various com-pounds in experimental stroke models have been performed

using diffusion- and T2-weighted MR microscopy (recently

reviewed by Rudin et al., 1999). The strength of these stud-

ies in comparison with those using conventional histology

as an endpoint are (1) the animals can be used as their own

control and (2) progression and/or regression of stroke mat-

uration can be followed over time in the same animal. Both

of these features increase statistical power and theoretically

reduce the number of animals used in a given study (Hall

et al., 1996). For example, Shi et al. have demonstrated the

neuroprotective effect of estrogen in a rat model of stroke

as evidenced by a reduction in the infarct volume (Shi et al.,

2001). For further information on therapeutic intervention

studies, the reader is referred to a recent review article

(Rudin et al., 1999).

4 Several alternate hypotheses underlying the ischemia-induced ADC

decrease have been proposed, tested and partly rejected. For instance,

early ADC reductions in ischemic tissue were attributed to cell membrane

permeability changes, restricted diffusion and/or increased tortuosity in

the extracellular space (for in-depth reviews on these topic the reader is

referred to recent review articles (Blackband et al., 1999; Duong et al.,

2001; Gass et al., 2001).

4.2. Head injury

Diffusion-weighted MR microscopy has been used to

follow the progression of acute and chronic head injury in ro-

dents (Hanstock et al., 1994; Assaf et al., 1997, 1999; Barzo

et al., 1997). Similar to ischemia, signal intensity increases

acutely within the injured brain area on diffusion- (Hanstocket al., 1994; Assaf et al., 1997, 1999) and T2-weighted MR

images indicating the presence of both vasogenic and cyto-

toxic edema (Assaf et al., 1997). However, 7 days following

closed head injury the signal becomes hypointense and the

ADC quantitatively approaches that of free water probably

reflecting tissues in which a large population of cells have

been disrupted (Assaf et al., 1997). In a recent study, closed

head injury was induced in 30 g mice and a neuroprotective

agent (NAPSVIPQ, a femtomolar-acting peptide) was ad-

ministered subcutaneously after the insult (Beni-Adani et al.,

2001). T2-weighted MR microscopy demonstrated signif-

icant brain-tissue recovery in the treated mice at 2 weeks

and also reduced overall mortality (Beni-Adani et al.,

2001).

To investigate the role of endogenous apolipoprotein E

(ApoE) in closed head injury MR microscopy was performed

on ApoE knockout mice (ApoE/) and control 24 h after

the insult (Lynch et al., 2002). The degree of lateral ventri-

cle effacement was used as an indirect measure of edema

(cf. Fig. 10) and quantitative analysis demonstrated that

ApoE/ mice developed more edema than C57BL6/J mice

(Lynch et al., 2002). Interestingly, the amount of edema also

correlated with increased brain production of tumor necro-

sis factor-, a pro-inflammatory cytokine believed to play

an important role in mediating BBB breakdown and devel-opment of cerebral edema (Lynch et al., 2002).

4.3. Demyelinating diseases

No naturally occurring disease of the central nervous sys-

tem in animals is known that corresponds to multiple scle-

rosis (MS). However, experimental animal models, which

result in demyelination and formation of plaque-like areas

of inflammation, are instead available to researchers study-

ing MS. The most frequently used animal model is the

so-called experimental allergic encephalomyelitis (EAE)

induced in animals by sensitizing them to components of

central myelin. EAE lesions have been demonstrated in vitro

in the rat spinal cord at a spatial resolution of 8104 mm3

(Lanens et al., 1994) and in mice spinal cords at 2.7 105 mm3 (Ahrens et al., 1998a). EAE-induced plaque-like

lesions were also demonstrated in vivo in a EAE SJL mouse

model at a spatial resolution of 3.4 103 mm3 by in-

jecting contrast (monocrystalline iron oxide nanoparticle,

MION-46) intravenously (Xu et al., 1998). In this study,

EAE lesions were visualized as a central punctuate area

of hypointensity surrounded by hyperintensity (Xu et al.,

1998). The hypointensity was interpreted as an effect of ex-

travasation of the contrast agent due to blood brain barrier


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Fig. 10. Volume-rendered 3D diffusion-weighted MR image from a C57Bl6/J mouse acquired in vivo 24 h following closed head injury. The closed head

injury impact area can be recognized as a high signal intensity zone (arrow), which has caused effacement of the ipsi-lateral ventricle.

breakdown in the area of the EAE lesion (Xu et al., 1998).

It is clear that the use of contrast agents facilitates visualiza-tion of EAE lesions at least acutely and several experimen-

tal contrast agents are being tested for this purpose (see also

Sipkins et al., 2000). In another experimental animal model,

lysophospahtidylcholine (LPC) was injected directly into the

internal capsule in rats to produce localized demyelinating

lesions, which were visible 48 h after the injection on both

T1- and T2-weighted MR microscopy images at a spatial

resolution of 0.16 mm3 (Ford et al., 1990).

Interestingly, the process of myelination has also been

studied using MR microscopy (Bulte et al., 1999). Rat

oligodendrocyte progenitor cells were first labeled with

MION-46L nanoparticles using specific transferrin receptor

targeting techniques (see, for detailed reviews, Bogdanov

et al., 2000; Weissleder et al., 2000; Wunderbaldinger et al.,

2000). The labeled cells were subsequently grafted in to the

spinal cord of neonatal myelin-deficient rats (Bulte et al.,

1999). Ten days later, the spinal cord was removed and

imaged in vitro. The MR microscopy images demonstrated

extensive migration of the grafted cells, particularly in the

area of the dorsal column (Bulte et al., 1999). This study

introduces MR microscopy as a technique to track the

migratory capacity of magnetically labeled cells after trans-

plantation and holds promise for future studies involving

the general processing involved in neurografting.

4.4. Aging and dementia

One of the hallmarks of aging in the brain is atrophy ( Esiri

et al., 1997). Development of cerebral atrophy in brains of

mouse lemur primates (Dhenain et al., 2000), C57BL6/J

mice and ApoE/ mice (McDaniel et al., 2001) can be

tracked non-invasively by MR microscopy. In Dhenains

study, mouse lemur primates were followed for up to 2 years

and T2-weighted images (spatial resolution of 0.05 mm3)

were acquired two to three times in each animal at various

time points (Dhenain et al., 2000). Global atrophy was es-

timated by measuring total CSF volume and in most of the

animals it increased with aging. Interestingly, four out of the

seven oldest animals did not display atrophy even at very

advanced ages (Dhenain et al., 2000).

In mice brains, development of forebrain atrophy was

indirectly assessed by measuring the ventricle volumes

on diffusion-weighted MR microscopy images before and

30 days after exposure to transient forebrain ischemia

(McDaniel et al., 2001). Thus, the animals served as their

own control, and the analysis showed that ventricle vol-

ume increased significantly in both C57BL6/J and ApoE

deficient mice (McDaniel et al., 2001). Fig. 11 displays the

significant volume increase particularly in the lateral ven-

tricles, which occurs following transient cerebral ischemia

in the C57BL6/J mouse brain.


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Fig. 11. Brain atrophy can be tracked in the mouse brain by in vivo MR microscopy. Two volume-rendered diffusion-weighted MR images from a

C57Bl/6 mouse brain are shown acquired before and 30 days after a 10-min period of transient cerebral ischemia. The ventricles are outlined (filled-in

space) on the volume-rendered images and it is evident that the lateral ventricles have enlarged as a consequence of ischemia-induced brain atrophy.

In another study, brains of very old (15 years old) and

younger mouse lemurs were examined using T2-weighted

MR microscopy and compared with subsequent histologi-

cal processing for iron content (Gilissen et al., 1998). The

T2-weighted images revealed dark regions in the areas of

the globus pallidus, the substantia nigra and the corpus cal-

losum, which corresponded to areas with high iron content(Gilissen et al., 1998). The findings of this study supported

the hypothesis that brain iron (ferritin) is the primary de-

terminant of MRI contrast and that iron accumulates in the

normal aging brain (Gilissen et al., 1998).

Until now, only preliminary reports are available on the

characterization of neuropathology in genetically engineered

mouse models of Alzheimers disease (AD) (Helpern et al.,

2001; Zhang et al., 2001). Preliminary data suggest that brain

atrophy does not develop over time neither in the PDAPP

transgenic AD mouse model (Zhang et al., 2001) nor in the

PS-APP transgenic AD mouse model (Helpern et al., 2001).

Additionally, the ventricle system in PDAPP mice appears

highly abnormal compared to normal control mice (Zhang

et al., 2001). More information on MRI characteriza-

tions of genetically engineered mouse models of AD

will undoubtedly appear in the literature in the very near

future and clarify the significance of using these mod-

els in the study of the equivalent clinical condition in

humans.

4.5. MR microscopy of brain tumors in rodents

The non-invasive approach to detection and the capabil-

ity of obtaining volumetric quantitative information makes

MRI an obvious tool for a broad range of experimental

cancer studies. Thus, MR microscopy has been used to

(1) characterize the appearance of tumors using various

MR parameters, (2) follow tumor growth in small animals

(Damadian et al., 1976; Crooks et al., 1980; Hansen et al.,

1980; Davis et al., 1981; Henkelman et al., 1987; Rajan

et al., 1990; Lemaire et al., 2000) and (3) follow the effectof treatment (Benedetti et al., 2000; Roy et al., 2000).

Contrast agents are known to enhance MR visualization

of various types of intracranial tumors secondary to the pres-

ence of abnormal vessels within the tumor tissue (Runge

et al., 1988; Norman et al., 1989; Bockhorst et al., 1990;

Wilmes et al., 1993; Hoehn-Berlage and Bockhorst, 1994;

Moore et al., 2000; Fonchy et al., 2001). Fig. 12 shows

how administration of a contrast agent can enhance the

definition of tumor tissue on T1-weighted MR microscopy

images. Some contrast agents when given intravenously or

intraperitoneally will provide enhanced tumor visualization

on T1- and T2-weighted MR images for several hours fol-

lowing administration (Wilmes et al., 1993; Ikezaki et al.,

1994a,b; Moore et al., 2000), while others only provide

enhancement for brief, transient intervals (Hoehn-Berlage

and Bockhorst, 1994). For example, in tumor-bearing ro-

dents an intra-peritoneal injection of Gd-DTPA caused

various tumor-associated tissue compartments to appear

transiently on T1-weighted MR images in a characteristic

time-dependent manner (Hoehn-Berlage and Bockhorst,

1994): first the tumor became apparent, later centrally lo-

cated cysts and peritumoral edema (Hoehn-Berlage and

microscopic mri

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