review article towards multidimensional radiotherapy: key...

Review ArticleTowards Multidimensional Radiotherapy Key Challenges forTreatment Individualisation

Iuliana Toma-Dasu1 and Alexandru Dasu2

1Medical Radiation Physics Stockholm University and Karolinska Institutet PO Box 260 171 76 Stockholm Sweden2Department of Radiation Physics and Department of Medical and Health Sciences Linkoping University 581 83 Linkoping Sweden

Correspondence should be addressed to Iuliana Toma-Dasu iulianaliviadasukise

Received 4 July 2014 Accepted 3 September 2014

Academic Editor Eva Bezak

Copyright copy 2015 I Toma-Dasu and A Dasu This is an open access article distributed under the Creative Commons AttributionLicense which permits unrestricted use distribution and reproduction in any medium provided the original work is properlycited

Functional and molecular imaging of tumours have offered the possibility of redefining the target in cancer therapy andindividualising the treatment with a multidimensional approach that aims to target the adverse processes known to impactnegatively upon treatment result Following the first theoretical attempts to include imaging information into treatment planningit became clear that the biological features of interest for targeting exhibit considerable heterogeneity with respect to magnitudespatial and temporal distribution both within one patient and between patients which require more advanced solutions for theway the treatment is planned and adapted Combiningmultiparameter information from imagingwith predictive information frombiopsies and molecular analyses as well as in treatment monitoring of tumour responsiveness appears to be the key approach tomaximise the individualisation of treatment This review paper aims to discuss some of the key challenges for incorporating intotreatment planning and optimisation the radiobiological features of the tumour derived from pretreatment PET imaging of tumourmetabolism proliferation and hypoxia and combining them with intreatment monitoring of responsiveness and other predictivefactors with the ultimate aim of individualising the treatment towards the maximisation of response

1 Introduction

The progress and technological development of functionaland molecular techniques for imaging tumours have offeredthe possibility of redefining the target in radiation therapyand devising the treatment in an innovative manner Four-teen years have passed since Ling et al [1] introduced theconcept of biological target volume (BTV) encompassing themultidimensional physiological and functional informationprovided by the new imaging techniques At the end of theirseminal paper onmultidimensional radiotherapy the authorschallenged the research and clinical communities to definea biological target volume and apply it by the year 2010moving towards evidence-based multidimensional radiationtherapy by conforming the physical dose distribution to theradiobiological features of the target that may be derivedfrom molecular and functional imaging Research has beenconducted towards this aim but the current practice inradiation therapy is still at its best based on the physi-cal optimisation of the dose distribution according to the

anatomical information regarding the localisation and theextent of the tumour and the normal tissue The routineplanning in clinical radiation treatment does not generallytake into account the particular radiation sensitivity of thetumour of an individual patient or the spatial and temporalheterogeneity of tumour resistance However it is well knownthat these aspects may be the causes for treatment failurefor a considerable fraction of the nonresponding patients asthe standard dose prescription does not ensure sufficientlycurative doses to counteract the radiation resistance of thetumour Among these adverse factors one has to count thevariations in cellular density from tumour to tumour theproliferation characteristics of the tumour cells and thedistinct microenvironmental characteristics of the tumours

A broad array of techniques could now be used to deter-mine the morphologic functional and molecular features oftumours and normal tissues Among these positron emissiontomography (PET) has the advantage of being almost nonin-vasive as it uses tracers that are usually metabolic substitutes

Hindawi Publishing CorporationComputational and Mathematical Methods in MedicineVolume 2015 Article ID 934380 8 pageshttpdxdoiorg1011552015934380

2 Computational and Mathematical Methods in Medicine

and is quite sensitive since quite low concentrations of tracersare required for imaging Furthermore several tracers arealready available for investigating various processes [2] Themost quoted tumour phenotypes that could be integratedwith the CT-defined gross tumour volume (GTV) to obtainthe BTV are the tumour metabolism proliferation hypoxiaand angiogenesis Consequently several methods have beenproposed for providing the relevant biological information onmetabolic biochemical and physiological factors resulting ina new approach for the way the treatment is planned [3 4]However it became clear that tumours do not contain onebiological target volume to which a homogeneous dose couldbe prescribed but instead the biological features of interestfor targeting exhibit considerable heterogeneity with respectto magnitude spatial and temporal distribution both withinone patient and between patients

This review paper aims to add to these conceptual solu-tions by discussing some of the key challenges for incorporat-ing the radiobiological features of the tumour into themodelsfor predicting the treatment outcome or for counteractingthe adverse tumour control factors based on PET imaging oftumour metabolism proliferation and hypoxia

2 PET Imaging of Key TumourPhenotypes and Corresponding Models forDose Painting

Several modelling studies have presented various approacheswith different degrees of complexity to include the imaginginformation into treatment planning Although in some casesmore than one type of PET image was available to thebest of our knowledge the models currently proposed in theliterature did not focus on more than one of the adversetumour control factors at a time for determining the BTVand its subregions and for addressing the radiation resistanceassociated with them With very large extent the majorityof the models focused on tumour hypoxia since it is one ofthe most important factors that determine the response ofthe tumour to radiation therapy [5ndash8] A common approachis to delineate a hypoxic subtarget in the tumour based onPET tracers specifically designed for imaging the tumouroxygenation such as [18F]Fluoromisonidazole ([18F]FMISO)[18F]Fluoroetanidazole ([18F]FETA) [18F]Fluoroazomycin-arabinofuranoside ([18F]FAZA) or the nonimidazoles com-pound Cu(II)-diacetyl-bis-N-(4)-methylthiosemicarbazone(Cu-ATSM) and prescribe an escalation of the dose accordingto available radiation therapy techniques and consideringthe tolerance of the normal tissues around the tumour [9ndash11] However the risk of using such an empirical approachis that the prescribed dose might not be large enough tocounteract the hypoxic radiation resistance and thereforethe method might fail to bring the expected results inclinical settings Other approaches recommended highlyheterogeneous dose distributions based on a linear increaseof the prescribed dose according to the signal intensity inthe PET image [12 13] or as a result of redistributing thedose to the target by increasing the dose to the hypoxicvoxels while decreasing the prescribed dose to the remaining

voxels in the tumour [14 15] More complex approaches forheterogeneous dose prescription make use of dynamic PETinformation [16] However heterogeneous dose distributionsare at risk of failing to provide the expected results forcases of dynamic hypoxia as have indeed been seen inclinical patients [17] since changes in the spatial distributionof hypoxia could easily lead to mismatches between thehypoxic subregions and the planned hotspots in the dosedistribution Alternative approaches in which the impact oflocal changes in the oxygenation of the tumour were alsotheoretically explored and subsequently tested for feasibility[18 19]

Another factor that reduces treatment effectivenessamong the physiological factors that influence the responseto treatment is tumour cell proliferation Cell prolifera-tion and especially accelerated repopulation that is seen inrapidly growing tumours like head-and-neck carcinomas areregarded as adverse factors for the success of radiotherapybecause they increase the population of cells that couldregrow the tumour and therefore need to be sterilised withradiation [20] This warrants the noninvasive investigationof tumour proliferation as a potential target to increaselocal control Proliferation andormetabolic PET tracers maybe used to image and quantify the tumour regions withincreased proliferation They can also be used to predict andevaluate the response to treatment and if necessary to adaptor improve the therapy

Many tumours also have an increased glycolytic metab-olism compared to normal tissues [21] This means that aradioactive analogue of glucose will be easily taken up intumours and the tumour burden could be detected throughthe difference in activity concentration This is the case of[18F]Fluorodeoxyglucose ([18F]FDG) that led to PET beinglargely used for improving the detection and staging ofcancers as well as for target delineation and the evaluationof treatment [22ndash24] Other tracers like 11C-acetate wouldhave to be considered for non-FDG-avid tumours offeringyet another facet of tumour metabolism [25ndash28]

Furthermore some studies showed that the uptake ofFDG in slowly proliferating tumours is generally lower thanin rapidly growing poorly differentiated tumours [2] sug-gesting an indirect correlationwith the proliferating potentialof the tumours However FDG is not a dedicated tracerfor tumour proliferation and therefore some regions withincreased glycolytic metabolism such as inflammations willalso show a high FDG uptake and will be imaged decreasingthe quality of the information provided by FDG-PET Due tothese limitations other biomarkers have been proposed forspecifically characterising tumour proliferation [2] such as[18F]31015840-deoxy-31015840-fluorotymidine ([18F]FLT) In comparisonto hypoxia little attention has been paid to developingmodelsfor the inclusion of proliferation information into treatmentplanning To the best of our knowledge there is only onestudy in which the possibility of including quantitativeimaging of tumour proliferation and cell density into theradiobiological evaluation and optimisation of treatmentplanning was theoretically explored [29]

Computational and Mathematical Methods in Medicine 3

3 Multitracer Spatial and TemporalDistributions and TCP Models

The most common hypotheses on which a dose paint-ing approach is generally based are the following localrecurrence is related to resistant foci not eradicated by thecurrently prescribed and delivered uniform doses nonin-vasive functional and molecular imaging allows mappingthe target in terms of radiation resistance and progress intreatment planning and radiation delivery allows nonho-mogeneous target irradiation while the irradiation of thenormal tissue and organs-at-risk (OARs) is kept below thetolerance levels The subsequent steps that are taken whenproposing a strategy for dose painting are to determine whatfunctional noninvasive methods can be used for imagingspecific tumour phenotypes related to local control or risk ofrelapse after (chemo)radiotherapy to determine the responsefunction(s) that would allow the quantitative interpretationof the image or images translated into a painting strategy andfinally to determine how to prescribe and deliver the dose asdose boosting or as in the manner generally known as dosepainting by numbers

The larger variability in the known approaches for per-forming treatment planning based on functional imaging isrelated to the interpretation of the images and their trans-lation into dose prescription Furthermore for the case ofcombined information regarding the key factors that shouldbe accounted for when attempting dose painting based onfunctional PET imaging tumour metabolism proliferationand hypoxia the complexity of the problem has prevented upto the present date the proposal of quantitative radiobiologi-cal models to simultaneously account for them

The most general approach for modelling the tumourresponse if information about the key features regardingtumour resistance to radiation is available as derived fromfunctional imaging is to calculate the tumour control prob-ability (TCP) at voxel level and then to integrate the responseover the whole target structure Thus assuming an initialdistribution of cell density 119899

0(r) and a distribution of cell

survival following the treatment 119878119865(r) the probability ofcontrolling the tumour is given by the following expression[18]

TCP = exp [minusintr1198990(r) sdot 119878119865 (r) 119889r] (1)

If the linear quadratic (LQ) model [30ndash32] adapted forproliferation [33] is used for describing the cellular survivalthe fraction of cells surviving in a voxel r in the tumour isgiven by

119878119865 (r) =119899

prod

119894=1

exp [minus120572 (r) sdot 119889119894(r) minus 120573 (r) sdot 1198892

119894(r)]

sdot exp [119879 ln (2)TD (r)]

(2)

where 119899 is the number of fractions119889119894(r) is the dose in fraction

119894 in voxel r 120572(r) and 120573(r) are the LQ parameters describingthe radiosensitivity in voxel r119879 is the treatment duration and

TD(r) is the cell doubling time in the voxel r If the variationin radiation sensitivity is related to the oxygenation of thecells 120572(r) and 120573(r) could be expressed as functions of the 120572and 120573 parameters relevant for well oxygenated cells and theoxygen tension-dependent modification factors OMF andthus (2) becomes

119878119865 (r) =119899

prod

119894=1

exp[minus 120572

OMF (1199011198742(r))sdot 119889119894(r)

minus

120573

OMF2 (1199011198742(r))sdot 1198892

119894(r)]


(3)

OMF (1199011198742(r)) is given by the following expression

OMF (1199011198742(r)) = OMFmax

119896 + 1199011198742(r)

119896 +OMFmax1199011198742 (r) (4)

where OMFmax is the maximum protection achieved in theabsence of oxygen and 119896 is a reaction constant as describedby Alper and Howard-Flanders [34]

In these conditions the probability for controlling thetumour could be written as

TCP

= expminusintr1198990(r) sdot119899

prod

119894=1

exp[minus 120572

OMF (1199011198742(r))sdot 119889119894(r)

minus

120573

OMF2 (1199011198742(r))sdot 1198892

119894(r)]

sdot exp [119879 ln (2)TD (r)] 119889r

(5)

Several proposals exist in the literature regarding the way theparameters 119899

0(r) TD(r) and OMF(119901119874

2(r)) could be derived

from PET images Thus the density of the clonogenic cellsin the beginning of the treatment could be derived from aFDG PET image based on the assumption that the enhancedFDG uptake should correspond to areas of higher densityof glucose-avid clonogens [35] As FLT is a marker takenup by the cells and phosphorylated by thymidine kinase 1(TK1)which is an enzyme closely tied to cellular proliferationit has been postulated that the retention of FLT within thecells provides a measure of cellular proliferation [36 37] Theparameters used for describing the relationship between radi-ation sensitivity and tumour oxygenation could be derivedbased on the relative uptake of hypoxia-specific PETmarkersfor various oxygen tensions as proposed by Toma-Dasu et al[38 39] and subsequently tested with respect to its feasibilitybased on FMISO PET [19] Thus if FDG FLT and FMISOimages of the tumour would be available before the startof the treatment and the relationships between the tracersuptake and 119899

0(r) TD(r) and OMF(119901119874

2(r)) would also be


known (5) could be used to determine the heterogeneousdose distribution that should be delivered for achieving adefined level of TCP

Nevertheless the practical implementation of thisapproach towards the complex BTV concept proposed byLing et al [1] is faced with several potential problems thatmay not be easily solved Thus one key problem is the factthat the required information about the biological parametersof interest would in fact be derived from PET images takenat different time points extending over several days to allowfor the clearance of the different tracers Therefore assumingfor example that the FDG PET image is taken at the timepoint 119905

1before the start of the treatment while FMISO and

FLT images are taken at 1199052and 1199053 respectively (5) should be

rewritten as

TCP

= exp minus intr1198990(r 1199051)

sdot

119899

prod

119894=1

exp[minus 120572

OMF (1199011198742(r 1199052))

sdot 119889119894(r)

minus

120573

OMF2 (1199011198742(r 1199052))

sdot 1198892

119894(r)]

sdot exp[ 119879 ln (2)TD (r 119905

3)

] 119889r

(6)

The expression in (6) shows that in reality it is quite difficultto speak about a time-independent BTV given the spatialand temporal heterogeneity of the parameters determiningthe tumour control probability Furthermore the differentbiological processes that have to be incorporated are seldomcoinciding in space [40 41] meaning that several boostvolumes would have to be defined possibly with differentboost levels

The temporal stability and the reproducibility of thesignal in the images before the start of the treatment givenby the technical limitations of the imaging method butmoreover by the dynamics of the biological system that isimaged may add yet another layer of complication to thealready challenging task of multiparameter mapping of thetarget with respect to the radiobiological tumour featuresrelated to adverse response to (chemo)radiotherapy

Last but not least the intrinsic radiosensitivity of thepatients would have to be accounted for Radiosensitivityparameters could be derived from clinical dose-responsecurves but these are considered relevant for populationsof patients which often exhibit considerable interpatientheterogeneity [42] Instead one could use for example patient-specific parameters derived in vitro from biopsy materialsas these were shown to better describe the response totreatment than generic or average parameters [43] In thefuture such information may also be combined with pre-dictive molecular assays providing quantitative informationon the responsiveness of individuals to various forms of

treatment Therefore the true individualisation of treatmentwould have to determine the right prescription levels not onlyfor the BTV or its equivalents but also for the CTV and theGTV

4 Integrated Biological DosePrescription and Treatment AdaptationBased on Functional Imaging Is It Time fora New Paradigm Shift

Given the inherent limitations in defining the BTV anddetermining the dose prescription that should overcomethe radioresistent foci within the BTV the implementationof simple dose painting approaches might lead to disap-pointing results in clinical settings Therefore the presentpaper proposes a paradigm shift from focusing on the radio-biological dose prescription towards biologically adaptedradiation therapy BIOART based on tumour responsivenessassessed with functional imaging The BIOART concept in amuch wider acceptation was introduced by Brahme in 2003as Biologically Optimized in vivo Predictive Assay-BasedAdaptive RadiationTherapy [3]The original paper proposedthat combining accurate knowledge about the delivered doseacquired with a PET camera based on the nuclear reactionsinduced in the patient by ions or high energy photonstogether with information regarding the density of tumourclonogens at some early point during the treatment derivedfrom two successive PET images one taken before the startof the treatment and one after about one week could be usedto assess the responsiveness of the tumour to the treatmentand consequently to adapt the treatment Although veryappealing the monitoring of the dose delivery or ratherof the production of positron emitting isotopes inside thepatient following nuclear reactions in case of ion therapyor photonuclear reactions in case of photon irradiation withhigh energy photons is not yet possible as a routine clinicalprocedure [44 45] the accurate dose determination beingachieved at its best through deformable dose registrationbased on repeated CBCT images during the course of thetreatment The effectiveness of this approach has howeverbeen debated on the grounds of the associated uncertainties[46]

The second component of the generic BIOART approachmonitoring of the tumour response by repeated PET imagesearly during the treatment is actually currently feasibleIndeed several studies have explored qualitatively the cor-relations between variations in PET tracer uptake and treat-ment outcome [47ndash53] Nevertheless a very recent studyon NSCLC imaged with FDG-PET before the start of(chemo)radiotherapy and during the second week of radia-tion therapy showed that it is feasible to determine a thresholdvalue for the effective radiosensitivity of the patients thatcould be used quantitatively to divide the patients into goodand poor responders to treatment as assessed by overallsurvival at 2 years after treatment [54]These results thereforesupport the high potential of early assessment of treatmentresponsiveness and subsequent treatment individualisationby identifying the likely candidates for more aggressive


Diagnostic imaging(morphological images)

Diagnostic imaging(functional image)

FDG 1

FDG 2


FMISOandor

FLT

Biologically optimised treatment planning

Dosedeliveryand in vivodosimetry

On board image acquisition

Treatment evaluation

Replanning Responsiveness evaluation


Andor

Figure 1 Schematic illustration of customised adaptive radiation therapy accounting for tumour hypoxia andor proliferation

strategies like dose escalation or combined therapies neededto increase the rate of local control

This approach also provides another advantage asrepeated examinations in the same patient ensure that eachpatient is its own reference and does not require spe-cific assumptions regarding the radiosensitivity In fact theapproach opens the possibility of deriving effective radiore-sistance parameters that could eventually be used for treat-ment adaptationThus assuming that the FDG images give ameasure of the tumour burden variations in signal intensitiesin individual voxels in the same patent would reflect changesin the density of functional clonogenic cells due to cell killor proliferation These and the dose distributions could thenbe used together with (2) or a simplified version of it todetermine effective parameters for radiosensitivity [3 54]Other investigations of biologically adverse processes likehypoxia and proliferation could offer additional informationthat could be used for fine-tuning the parameters or includedin the treatment optimisation process provided that theirintrinsic heterogeneity and dynamics are accounted for Aschematic illustration of the currently proposed approachfor individualising the treatment and adapting it based onfunctional PET imaging is shown in Figure 1

Several papers have shown that pretreatment FDGFMISO and FLT PET imaging might have not only prog-nostic values for indicating the likely course of the diseasein the untreated individual but also more importantly inthis setting predictive values that might allow the selectionof patients that would benefit from the chosen treatment[55ndash59] However proper patient selection and subsequentdose painting approaches for prescribing and delivering thedose do not guarantee the success of the treatment dueto the large interpatient variability in response [56] andtherefore they should be integrated in complex strategies for

the management of the tumour which include early monitor-ing of the response and treatment adaptation

Central to responsiveness evaluation and treatment adap-tation is the registration of images containing anatomicfunctional and dosimetric information This is the resultof a mathematical optimisation process using algorithmsaimed at aligning the images through rigid or deformabletransformations [60] Several sources of uncertainties existin this process some intrinsic to the algorithms used andother originating in uncertainties or noise in the analysedimages As there is the risk that these uncertainties mightinterfere with the analysis of the information in the imagesit is important to include them in a sensitivity analysis aimedat testing the robustness of the results or predictions as donefor example by Tilly et al [61] It has to be highlighted thatbest results are probably obtained when the assessment of theresponse has to take place not later than two weeks from thestart of the treatment This not only prevents the inflamma-tory response from dominating the information that couldbe retrieved from repeated FDG images but also minimisesthe morphological changes that may be caused for exampleby tumour shrinkage or progression and whichmight requiredeformable registration algorithms that are more error proneand therefore more of a source of uncertainties

The proposal above has mainly been concerned withusing functional information from PET images for treatmentmonitoring and adaptation Nevertheless similar consider-ation might also apply for functional magnetic resonanceimaging (MRI) that allows both qualitative and quantitativecharacterisation of clinical tumours and the subsequentmap-ping of the tumour response Thus parameters derived fromdiffusion-weighted MRI (DW-MRI) could offer informationon tissue cellularity and may therefore be used for treatmentresponse monitoring [62] Other methods like dynamic


contrast-enhanced (DCE) imaging may be useful to obtaininformation on tissue vasculature [63] although it has beenargued that tumour oxygenation might have a more complexdependence [64] Proposals also exist for imaging lactateor choline levels in tumours as surrogates for hypoxia andproliferation [2]

5 Conclusions

There is no doubt that functional and molecular imaginghave the potential to provide a paradigm shift in treat-ment planning and optimisation in cancer therapy thatextends well beyond target definition While multiparameterexaminations will nevertheless provide valuable prognosticinformation for each patient it is in unleashing the pre-dictive power of the tracers that the true value of PET liesin modern radiotherapy Thus pretreatment investigationspossibly combined with predictive molecular informationon the intrinsic features of each patient will provide initialinformation on the dose levels needed to be included inthe individual treatment plan and the likely therapeuticapproaches Subsequent examinations early during the treat-ment would then provide information on tumour responsive-ness that may subsequently be used to determine the need fortreatment adaptation taking into account the delivered dosedistributions as well as adjuvant therapies the effectivenessof which could also be assessed with this proposed approachThis may therefore be a simple and quite straightforwardway to individualise treatment considering not only thepretreatment condition of the patient but also its intrinsicresponsiveness and individual dose distributions that deter-mine the need for later treatment adaptation This is in factthe ultimate aim towards true individualisation of moderncancer treatment

Conflict of Interests

The authors report no conflict of interests concerning thematerials or methods used in this study or the findings in thispaper

Acknowledgments

Financial support from the Cancer Research Funds of Radi-umhemmet EU FP7 ARTFORCE Linkoping University andthe County Council of Ostergotland is gratefully acknowl-edged

References

[1] C C Ling J Humm S Larson et al ldquoTowards multidimen-sional radiotherapy (MD-CRT) biological imaging and biolog-ical conformalityrdquo International Journal of Radiation OncologyBiology Physics vol 47 no 3 pp 551ndash560 2000

[2] S Apisarnthanarax and K S C Chao ldquoCurrent imagingparadigms in radiation oncologyrdquo Radiation Research vol 163no 1 pp 1ndash25 2005

[3] A Brahme ldquoBiologically optimized 3-dimensional in vivo pre-dictive assay-based radiation therapy using positron emission

tomography-computerized tomography imagingrdquo Acta Onco-logica vol 42 no 2 pp 123ndash136 2003

[4] S M Bentzen ldquoTheragnostic imaging for radiation oncologydose-painting by numbersrdquo The Lancet Oncology vol 6 no 2pp 112ndash117 2005

[5] M Nordsmark M Overgaard and J Overgaard ldquoPretreatmentoxygenation predicts radiation response in advanced squamouscell carcinoma of the head and neckrdquo Radiotherapy and Oncol-ogy vol 41 no 1 pp 31ndash39 1996

[6] D M Brizel G S Sibley L R Prosnitz R L Scher and MW Dewhirst ldquoTumor hypoxia adversely affects the prognosisof carcinoma of the head and neckrdquo International Journal ofRadiation Oncology Biology Physics vol 38 no 2 pp 285ndash2891997

[7] J Overgaard ldquoClinical evaluation of nitroimidazoles as modi-fiers of hypoxia in solid tumorsrdquo Oncology Research vol 6 no10-11 pp 509ndash518 1994

[8] P Vaupel and A Mayer ldquoHypoxia in cancer significance andimpact on clinical outcomerdquo Cancer and Metastasis Reviewsvol 26 no 2 pp 225ndash239 2007

[9] K S C Chao W R Bosch S Mutic et al ldquoA novelapproach to overcome hypoxic tumor resistance Cu-ATSM-guided intensity-modulated radiation therapyrdquo InternationalJournal of Radiation Oncology Biology Physics vol 49 no 4 pp1171ndash1182 2001

[10] A-L Grosu M Souvatzoglou B Roper et al ldquoHypoxiaimaging with FAZA-PET and theoretical considerations withregard to dose painting for individualization of radiotherapyin patients with head and neck cancerrdquo International Journal ofRadiation Oncology Biology Physics vol 69 no 2 pp 541ndash5512007

[11] S T Lee and AM Scott ldquoHypoxia positron emission tomogra-phy imaging with 18F-fluoromisonidazolerdquo Seminars in NuclearMedicine vol 37 no 6 pp 451ndash461 2007

[12] M Alber F Paulsen S M Eschmann and H J MachullaldquoOn biologically conformal boost dose optimizationrdquo Physics inMedicine and Biology vol 48 no 2 pp N31ndashN35 2003

[13] S K Das M M Miften S Zhou et al ldquoFeasebility of opti-mizing the dose distribution in lung tumors using fluorine-18-fluorodeoxyglucose positron emission tomography and singlephoton emission computed tomography guided dose prescrip-tionsrdquoMedical Physics vol 31 no 6 pp 1452ndash1461 2004

[14] E Malinen A Soslashvik D Hristov O S Bruland and D ROlsen ldquoAdapting radiotherapy to hypoxic tumoursrdquo Physics inMedicine and Biology vol 51 no 19 pp 4903ndash4921 2006

[15] R T Flynn S R Bowen S M Bentzen T R Mackie andR Jeraj ldquoIntensity-modulated X-ray (IMXT) versus proton(IMPT) therapy for theragnostic hypoxia-based dose paintingrdquoPhysics in Medicine and Biology vol 53 no 15 pp 4153ndash41672008

[16] D Thorwarth S-M Eschmann F Paulsen and M AlberldquoHypoxia dose painting by numbers a planning studyrdquo Inter-national Journal of Radiation Oncology Biology Physics vol 68no 1 pp 291ndash300 2007

[17] S Roels P Slagmolen J Nuyts et al ldquoBiological image-guidedradiotherapy in rectal cancer is there a role for FMISO or FLTnext to FDGrdquo Acta Oncologica vol 47 no 7 pp 1237ndash12482008

[18] I Toma-Dasu A Dasu and A Brahme ldquoDose prescription andoptimisation based on tumour hypoxiardquo Acta Oncologica vol48 no 8 pp 1181ndash1192 2009


[19] I Toma-Dasu J Uhrdin L Antonovic et al ldquoDose prescriptionand treatment planning based on FMISO-PET hypoxiardquo ActaOncologica vol 51 no 2 pp 222ndash230 2012

[20] H R Whithers J M G Taylor and B Maciejewski ldquoThehazard of accelerated tumor clonogen repopulation duringradiotherapyrdquo Acta Oncologica vol 27 no 2 pp 131ndash146 1988

[21] P Vaupel F Kallinowski and P Okunieff ldquoBlood flow oxy-gen and nutrient supply and metabolic microenvironment ofhuman tumors a reviewrdquo Cancer Research vol 49 no 23 pp6449ndash6465 1989

[22] V Gregoire ldquoIs there any future in radiotherapy planningwithout the use of PET unraveling themythrdquo Radiotherapy andOncology vol 73 no 3 pp 261ndash263 2004

[23] D L Schwartz E C Ford J Rajendran et al ldquoFDG-PETCT-guided intensity modulated head and neck radiotherapy a pilotinvestigationrdquo Head and Neck vol 27 no 6 pp 478ndash487 2005

[24] V Gregoire and A Chiti ldquoMolecular imaging in radiother-apy planning for head and neck tumorsrdquo Journal of NuclearMedicine vol 52 no 3 pp 331ndash334 2011

[25] C L Ho S C H Yu and D W Yeung ldquo11C-acetate PETimaging in hepatocellular carcinoma and other liver massesrdquoJournal of Nuclear Medicine vol 44 no 2 pp 213ndash221 2003

[26] G Sandblom J Sorensen N Lundin M Haggman and P-UMalmstrom ldquoPositron emission tomography with C11-acetatefor tumor detection and localization in patients with prostate-specific antigen relapse after radical prostatectomyrdquo Urologyvol 67 no 5 pp 996ndash1000 2006

[27] A Sun J Sorensen M Karlsson et al ldquo1-[11C]-acetate PETimaging in head and neck cancermdasha comparison with 18F-FDG-PET implications for staging and radiotherapy planningrdquoEuropean Journal of Nuclear Medicine and Molecular Imagingvol 34 no 5 pp 651ndash657 2007

[28] A Sun S Johansson I Turesson A Dau and J SorensenldquoImaging tumor perfusion and oxidativemetabolism in patientswith head-and-neck cancer using 1-[11C]-acetate PET dur-ing radiotherapy preliminary resultsrdquo International Journal ofRadiation Oncology Biology Physics vol 82 no 2 pp 554ndash5602012

[29] A Dasu ldquoTreatment planning optimisation based on imagingtumour proliferation and cell densityrdquo Acta Oncologica vol 47no 7 pp 1221ndash1228 2008

[30] K H Chadwick and H P Leenhouts ldquoA molecular theory ofcell survivalrdquo Physics in Medicine and Biology vol 18 no 1 pp78ndash87 1973

[31] B G Douglas and J F Fowler ldquoFractionation schedules and aquadratic dose effect relationshiprdquo British Journal of Radiologyvol 48 no 570 pp 502ndash504 1975

[32] G W Barendsen ldquoDose fraction dose rate and iso-effectrelationships for normal tissue responsesrdquo International Journalof Radiation Oncology Biology Physics vol 8 no 11 pp 1981ndash1997 1982

[33] J F Fowler ldquoThe linear-quadratic formula and progress infractionated radiotherapyrdquo British Journal of Radiology vol 62no 740 pp 679ndash694 1989

[34] T Alper and P Howard-Flanders ldquoRole of oxygen inmodifyingthe radiosensitivity of E coli Brdquo Nature vol 178 no 4540 pp978ndash979 1956

[35] GMeijer J SteenhuijsenM Bal K De Jaeger D Schuring andJ Theuws ldquoDose painting by contours versus dose painting bynumbers for stage IIIII lung cancer practical implications ofusing a broad or sharp brushrdquo Radiotherapy and Oncology vol100 no 3 pp 396ndash401 2011

[36] AK BuckGHalterH Schirrmeister et al ldquoImaging prolifera-tion in lung tumors with PET 18F-FLT versus 18F-FDGrdquo Journalof Nuclear Medicine vol 44 no 9 pp 1426ndash1431 2003

[37] D L Francis A Freeman D Visvikis et al ldquoIn vivo imagingof cellular proliferation in colorectal cancer using positronemission tomographyrdquo Gut vol 52 no 11 pp 1602ndash1606 2003

[38] I Toma-Dasu J Uhrdin A Dasu and A Brahme ldquoTherapyoptimization based on non-linear uptake of PET tracers versuslsquolinear dose paintingrsquordquo IFMBE Proceedings I vol 25 pp 221ndash2242009

[39] I Toma-Dasu and A Dasu ldquoBiologically-optimised IMRTbased on molecular imaging of tumour hypoxia-the impact ofthe tracer usedrdquo IFMBEProceedings vol 39 pp 1742ndash1745 2013

[40] P Vera P Bohn A Edet-Sanson et al ldquoSimultaneous positronemission tomography (PET) assessment of metabolism with18F-fluoro-2-deoxy-d-glucose (FDG) proliferation with 18F-fluoro-thymidine (FLT) and hypoxia with 18F-fluoro-mison-idazole (F-miso) before and during radiotherapy in patientswith non-small-cell lung cancer (NSCLC) a pilot studyrdquo Radio-therapy and Oncology vol 98 no 1 pp 109ndash116 2011

[41] T J Bradshaw S Yip N Jallow L J Forrest and R Jeraj ldquoSpa-tiotemporal stability of Cu-ATSM and FLT positron emissiontomography distributions during radiation therapyrdquo Interna-tional Journal of Radiation Oncology Biology Physics vol 89 no2 pp 399ndash405 2014

[42] A Dasu I Toma-Dasu and J F Fowler ldquoShould single ordistributed parameters be used to explain the steepness oftumour control probability curvesrdquo Physics in Medicine andBiology vol 48 no 3 pp 387ndash397 2003

[43] M Hedman T Bjork-Eriksson O Brodin and I Toma-DasuldquoPredictive value of modelled tumour control probability basedon individual measurements of in vitro radiosensitivity andpotential doubling timerdquo British Journal of Radiology vol 86no 1025 Article ID 20130015 2013

[44] J Bauer D Unholtz F Sommerer et al ldquoImplementation andinitial clinical experience of offline PETCT-based verificationof scanned carbon ion treatmentrdquo Radiotherapy and Oncologyvol 107 no 2 pp 218ndash226 2013

[45] K Frey J Bauer D Unholtz et al ldquoTPS(PET) a TPS-basedapproach for in vivo dose verification with PET in protontherapyrdquo Physics in Medicine and Biology vol 59 no 1 pp 1ndash21 2014

[46] T E Schultheiss W A Tome and C G Orton ldquoPointcoun-terpoint it is not appropriate to ldquodeformrdquo dose along withdeformable image registration in adaptive radiotherapyrdquoMedi-cal Physics vol 39 no 11 pp 6531ndash6533 2012

[47] E Brun E Kjellen J Tennvall et al ldquoFDG pet studies duringtreatment prediction of therapy outcome in head and necksquamous cell carcinomardquo Head and Neck vol 24 no 2 pp127ndash135 2002

[48] A van Baardwijk G Bosmans A Dekker et al ldquoTime trendsin the maximal uptake of FDG on PET scan during thoracicradiotherapy A prospective study in locally advanced non-small cell lung cancer (NSCLC) patientsrdquo Radiotherapy andOncology vol 82 no 2 pp 145ndash152 2007

[49] M Hentschel S Appold A Schreiber et al ldquoEarly FDG PETat 10 or 20 Gy under chemoradiotherapy is prognostic forlocoregional control and overall survival in patients with headand neck cancerrdquo European Journal of Nuclear Medicine andMolecular Imaging vol 38 no 7 pp 1203ndash1211 2011

[50] M Massaccesi M L Calcagni M G Spitilli et al ldquo18F-FDGPET-CTduring chemo-radiotherapy in patients with non-small


cell lung cancer the earlymetabolic response correlates with thedelivered radiation doserdquo Radiation Oncology vol 7 article 1062012

[51] W van Elmpt M Ollers A-M C Dingemans P Lambin andD de Ruysscher ldquoResponse assessment using 18F-FDG PETearly in the course of radiotherapy correlates with survival inadvanced-stage non-small cell lung cancerrdquo Journal of NuclearMedicine vol 53 no 10 pp 1514ndash1520 2012

[52] J K Hoang S K Das K R Choudhury D S Yoo and D MBrizel ldquoUsing FDG-PET tomeasure early treatment response inhead and neck squamous cell carcinoma quantifying intrinsicvariability in order to understand treatment-induced changerdquoTheAmerican Journal of Neuroradiology vol 34 no 7 pp 1428ndash1433 2013

[53] E A Usmanij L F deGeus-Oei E G C Troost et al ldquo18F-FDGPET early response evaluation of locally advanced non-smallcell lung cancer treated with concomitant chemoradiotherapyrdquoJournal of Nuclear Medicine vol 54 no 9 pp 1528ndash1534 2013

[54] I Toma-Dasu J Uhrdin A Dasu S Carvalo W van Elmptand P Lambin ldquoEvaluating tumour response ofNSCLCpatientswith FDG-PET potential for treatment individualisationrdquoRadiotherapy and Oncology vol 111 supplement 1 p 364 2014

[55] J G Rajendran D L Schwartz J OrsquoSullivan et al ldquoTumorhypoxia imaging with [F-18] fluoromisonidazole positron emis-sion tomography in head and neck cancerrdquo Clinical CancerResearch vol 12 no 18 pp 5435ndash5441 2006

[56] J van Loon A van Baardwijk L BoersmaM Ollers P Lambinand D de Ruysscher ldquoTherapeutic implications of molecularimaging with PET in the combined modality treatment of lungcancerrdquo Cancer Treatment Reviews vol 37 no 5 pp 331ndash3432011

[57] H Quon and D M Brizel ldquoPredictive and prognostic role offunctional imaging of head and neck squamous cell carcino-masrdquo Seminars in Radiation Oncology vol 22 no 3 pp 220ndash232 2012

[58] H JW L Aerts J BussinkW J GOyen et al ldquoIdentification ofresidual metabolic-active areas within NSCLC tumours using apre-radiotherapy FDG-PET-CT scan a prospective validationrdquoLung Cancer vol 75 no 1 pp 73ndash76 2012

[59] M Inubushi T Saga M Koizumi et al ldquoPredictive value of31015840-deoxy-31015840-[18F]fluorothymidine positron emission tomogra-phycomputed tomography for outcome of carbon ion radio-therapy in patients with head and neck mucosal malignantmelanomardquo Annals of Nuclear Medicine vol 27 no 1 pp 1ndash102013

[60] D L Hill P G Batchelor M Holden and D J HawkesldquoMedical image registrationrdquo Physics in Medicine and Biologyvol 46 no 3 pp R1ndash45 2001

[61] D Tilly N Tilly and A Ahnesjo ldquoDose mapping sensitivityto deformable registration uncertainties in fractionated radio-therapy applied to prostate proton treatmentsrdquo BMC MedicalPhysics vol 13 article 2 no 1 2013

[62] HCThoeny andBD Ross ldquoPredicting andmonitoring cancertreatment response with diffusion-weighted MRIrdquo Journal ofMagnetic Resonance Imaging vol 32 no 1 pp 2ndash16 2010

[63] T Nielsen T Wittenborn and M R Horsman ldquoDynamiccontrast-enhancedmagnetic resonance imaging (DCE-MRI) inpreclinical studies of antivascular treatmentsrdquo Pharmaceuticsvol 4 no 4 pp 563ndash589 2012

[64] A Dasu and I Toma-Dasu ldquoVascular oxygen content and thetissue oxygenation a theoretical analysisrdquoMedical Physics vol35 no 2 pp 539ndash545 2008

Submit your manuscripts athttpwwwhindawicom

Stem CellsInternational

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014


MEDIATORSINFLAMMATION

of


Behavioural Neurology

EndocrinologyInternational Journal of



Disease Markers


BioMed Research International

OncologyJournal of



Oxidative Medicine and Cellular Longevity


PPAR Research

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Immunology ResearchHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal of

ObesityJournal of



Computational and Mathematical Methods in Medicine

OphthalmologyJournal of


Diabetes ResearchJournal of



Research and TreatmentAIDS


Gastroenterology Research and Practice


Parkinsonrsquos Disease

Evidence-Based Complementary and Alternative Medicine

Volume 2014Hindawi Publishing Corporationhttpwwwhindawicom


and is quite sensitive since quite low concentrations of tracersare required for imaging Furthermore several tracers arealready available for investigating various processes [2] Themost quoted tumour phenotypes that could be integratedwith the CT-defined gross tumour volume (GTV) to obtainthe BTV are the tumour metabolism proliferation hypoxiaand angiogenesis Consequently several methods have beenproposed for providing the relevant biological information onmetabolic biochemical and physiological factors resulting ina new approach for the way the treatment is planned [3 4]However it became clear that tumours do not contain onebiological target volume to which a homogeneous dose couldbe prescribed but instead the biological features of interestfor targeting exhibit considerable heterogeneity with respectto magnitude spatial and temporal distribution both withinone patient and between patients

This review paper aims to add to these conceptual solu-tions by discussing some of the key challenges for incorporat-ing the radiobiological features of the tumour into themodelsfor predicting the treatment outcome or for counteractingthe adverse tumour control factors based on PET imaging oftumour metabolism proliferation and hypoxia

2 PET Imaging of Key TumourPhenotypes and Corresponding Models forDose Painting

Several modelling studies have presented various approacheswith different degrees of complexity to include the imaginginformation into treatment planning Although in some casesmore than one type of PET image was available to thebest of our knowledge the models currently proposed in theliterature did not focus on more than one of the adversetumour control factors at a time for determining the BTVand its subregions and for addressing the radiation resistanceassociated with them With very large extent the majorityof the models focused on tumour hypoxia since it is one ofthe most important factors that determine the response ofthe tumour to radiation therapy [5ndash8] A common approachis to delineate a hypoxic subtarget in the tumour based onPET tracers specifically designed for imaging the tumouroxygenation such as [18F]Fluoromisonidazole ([18F]FMISO)[18F]Fluoroetanidazole ([18F]FETA) [18F]Fluoroazomycin-arabinofuranoside ([18F]FAZA) or the nonimidazoles com-pound Cu(II)-diacetyl-bis-N-(4)-methylthiosemicarbazone(Cu-ATSM) and prescribe an escalation of the dose accordingto available radiation therapy techniques and consideringthe tolerance of the normal tissues around the tumour [9ndash11] However the risk of using such an empirical approachis that the prescribed dose might not be large enough tocounteract the hypoxic radiation resistance and thereforethe method might fail to bring the expected results inclinical settings Other approaches recommended highlyheterogeneous dose distributions based on a linear increaseof the prescribed dose according to the signal intensity inthe PET image [12 13] or as a result of redistributing thedose to the target by increasing the dose to the hypoxicvoxels while decreasing the prescribed dose to the remaining

voxels in the tumour [14 15] More complex approaches forheterogeneous dose prescription make use of dynamic PETinformation [16] However heterogeneous dose distributionsare at risk of failing to provide the expected results forcases of dynamic hypoxia as have indeed been seen inclinical patients [17] since changes in the spatial distributionof hypoxia could easily lead to mismatches between thehypoxic subregions and the planned hotspots in the dosedistribution Alternative approaches in which the impact oflocal changes in the oxygenation of the tumour were alsotheoretically explored and subsequently tested for feasibility[18 19]

Another factor that reduces treatment effectivenessamong the physiological factors that influence the responseto treatment is tumour cell proliferation Cell prolifera-tion and especially accelerated repopulation that is seen inrapidly growing tumours like head-and-neck carcinomas areregarded as adverse factors for the success of radiotherapybecause they increase the population of cells that couldregrow the tumour and therefore need to be sterilised withradiation [20] This warrants the noninvasive investigationof tumour proliferation as a potential target to increaselocal control Proliferation andormetabolic PET tracers maybe used to image and quantify the tumour regions withincreased proliferation They can also be used to predict andevaluate the response to treatment and if necessary to adaptor improve the therapy

Many tumours also have an increased glycolytic metab-olism compared to normal tissues [21] This means that aradioactive analogue of glucose will be easily taken up intumours and the tumour burden could be detected throughthe difference in activity concentration This is the case of[18F]Fluorodeoxyglucose ([18F]FDG) that led to PET beinglargely used for improving the detection and staging ofcancers as well as for target delineation and the evaluationof treatment [22ndash24] Other tracers like 11C-acetate wouldhave to be considered for non-FDG-avid tumours offeringyet another facet of tumour metabolism [25ndash28]

Furthermore some studies showed that the uptake ofFDG in slowly proliferating tumours is generally lower thanin rapidly growing poorly differentiated tumours [2] sug-gesting an indirect correlationwith the proliferating potentialof the tumours However FDG is not a dedicated tracerfor tumour proliferation and therefore some regions withincreased glycolytic metabolism such as inflammations willalso show a high FDG uptake and will be imaged decreasingthe quality of the information provided by FDG-PET Due tothese limitations other biomarkers have been proposed forspecifically characterising tumour proliferation [2] such as[18F]31015840-deoxy-31015840-fluorotymidine ([18F]FLT) In comparisonto hypoxia little attention has been paid to developingmodelsfor the inclusion of proliferation information into treatmentplanning To the best of our knowledge there is only onestudy in which the possibility of including quantitativeimaging of tumour proliferation and cell density into theradiobiological evaluation and optimisation of treatmentplanning was theoretically explored [29]










119878119865 (r) =119899

prod

119894=1


119894(r)]


(2)




119878119865 (r) =119899

prod

119894=1

exp[minus 120572

OMF (1199011198742(r))sdot 119889119894(r)

minus

120573

OMF2 (1199011198742(r))sdot 1198892

119894(r)]


(3)


OMF (1199011198742(r)) = OMFmax

119896 + 1199011198742(r)

119896 +OMFmax1199011198742 (r) (4)



TCP


prod

119894=1

exp[minus 120572

OMF (1199011198742(r))sdot 119889119894(r)

minus

120573

OMF2 (1199011198742(r))sdot 1198892

119894(r)]

sdot exp [119879 ln (2)TD (r)] 119889r

(5)


0(r) TD(r) and OMF(119901119874



0(r) TD(r) and OMF(119901119874

2(r)) would also be






rewritten as

TCP

= exp minus intr1198990(r 1199051)

sdot

119899

prod

119894=1

exp[minus 120572

OMF (1199011198742(r 1199052))

sdot 119889119894(r)

minus

120573

OMF2 (1199011198742(r 1199052))

sdot 1198892

119894(r)]

sdot exp[ 119879 ln (2)TD (r 119905

3)

] 119889r

(6)











FDG 1

FDG 2


FMISOandor

FLT







Andor










5 Conclusions




Acknowledgments


References










































































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of

























119878119865 (r) =119899

prod

119894=1


119894(r)]


(2)




119878119865 (r) =119899

prod

119894=1

exp[minus 120572

OMF (1199011198742(r))sdot 119889119894(r)

minus

120573

OMF2 (1199011198742(r))sdot 1198892

119894(r)]


(3)


OMF (1199011198742(r)) = OMFmax

119896 + 1199011198742(r)

119896 +OMFmax1199011198742 (r) (4)



TCP


prod

119894=1

exp[minus 120572

OMF (1199011198742(r))sdot 119889119894(r)

minus

120573

OMF2 (1199011198742(r))sdot 1198892

119894(r)]

sdot exp [119879 ln (2)TD (r)] 119889r

(5)


0(r) TD(r) and OMF(119901119874



0(r) TD(r) and OMF(119901119874

2(r)) would also be






rewritten as

TCP

= exp minus intr1198990(r 1199051)

sdot

119899

prod

119894=1

exp[minus 120572

OMF (1199011198742(r 1199052))

sdot 119889119894(r)

minus

120573

OMF2 (1199011198742(r 1199052))

sdot 1198892

119894(r)]

sdot exp[ 119879 ln (2)TD (r 119905

3)

] 119889r

(6)











FDG 1

FDG 2


FMISOandor

FLT







Andor










5 Conclusions




Acknowledgments


References










































































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of





















rewritten as

TCP

= exp minus intr1198990(r 1199051)

sdot

119899

prod

119894=1

exp[minus 120572

OMF (1199011198742(r 1199052))

sdot 119889119894(r)

minus

120573

OMF2 (1199011198742(r 1199052))

sdot 1198892

119894(r)]

sdot exp[ 119879 ln (2)TD (r 119905

3)

] 119889r

(6)











FDG 1

FDG 2


FMISOandor

FLT







Andor










5 Conclusions




Acknowledgments


References










































































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of



















FDG 1

FDG 2


FMISOandor

FLT







Andor










5 Conclusions




Acknowledgments


References










































































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of


















5 Conclusions




Acknowledgments


References










































































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of






































































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of
















review article towards multidimensional radiotherapy: key...

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