ultralow-dose abdominal computed tomography

ORIGINAL ARTICLE

Ultralow-Dose Abdominal Computed Tomography:Comparison of 2 Iterative Reconstruction Techniques

in a Prospective Clinical Study
Ranish Deedar Ali Khawaja, MD,* Sarabjeet Singh, MD, MMST,* Michael Blake, MD,†
Mukesh Harisinghani, MD,† Gary Choy, MD,† Ali Karosmanoglu, MD,† Atul Padole, MD,*Saravenaz Pourjabbar, MD,* Synho Do, PhD,* and Mannudeep K. Kalra, MD*

Purpose: To assess lesion detection and image quality of ultralow-dose(ULD) abdominal computed tomography (CT) reconstructed with filteredback projection (FBP) and 2 iterative reconstruction techniques: hybrid-based iDose, and image-based SafeCT.Materials and Methods: In this institutional review board–approvedongoing prospective clinical study, 41 adult patients provided written in-formed consent for an additional ULD abdominal CT examination imme-diately after standard dose (SD) CT exam on a 256-slice multidetectorcomputed tomography (iCT, Philips-Healthcare). The SD examination(size-specific dose estimate, 10 ± 3 mGy) was performed at 120 kV withautomatic exposure control, and reconstructed with FBP. The ULD examina-tion (1.5 ± 0.4 mGy) was performed at 120 kVand fixed tube current of 17 to20 mAs/slice to achieve ULD radiation dose, with the rest of the scan param-eters same as SD examination. The ULD data were reconstructed with(a) FBP, (b) iDose, and (c) SafeCT. Lesionswere detected onULDFBP seriesand compared to SD FBP “reference-standard” series. True lesions, pseu-dolesions, and missed lesions were recorded. Four abdominal radiologistsindependently blindly performed subjective image quality. Objective imagequality included image noise calculation and noise spectral density plots.Results: All true lesions (n, 52: liver metastases, renal cysts, diverticulo-sis) in SD FBP images were detected in ULD images. Although there wereno missed or pseudolesions on ULD iDose and ULD SafeCT images, ap-pearance of small low-contrast hepatic lesions was suboptimal. The ULDFBP images were unacceptable across all patients for both lesion detectionand image quality. In patients with a bodymass index (BMI) of 25 kg/m2 orless, ULD iDose and ULD SafeCT images were acceptable for image qual-ity that was close to SD FBP for both normal and abnormal abdominal andpelvic structures. With increasing BMI, the image quality of ULD imageswas deemed unacceptable due to photo starvation. Evaluation of kidneystones with ULD iDose/SafeCT images was found acceptable regardlessof patient size. Image noise levels were significantly lower in ULD iDoseand ULD SafeCT images compared to ULD FBP (P < 0.01).Conclusions: Preliminary results show that ULD abdominal CT recon-structed with iterative reconstruction techniques is achievable in smallerpatients (BMI≤ 25 kg/m2) but remains a challenge for overweight to obesepatients. Lesion detection is similar in full-dose SD FBP and ULD iDose/SafeCT images, with suboptimal visibility of low-contrast lesions inULD images.

Key Words: CT dose reduction, abdominal CT, iterative reconstructiontechniques

(J Comput Assist Tomogr 2015;39: 489–498)

From the *MGH Imaging, and †Division of Abdominal Imaging, MassachusettsGeneral Hospital and Harvard Medical School, Boston, MA.Received for publication September 29, 2014; accepted February 24, 2015.Reprints: Ranish Deedar Ali Khawaja, MD, 25 New Chardon Street, 4th Floor,

Boston, MA 02114 (e‐mail: [email protected]).S.S. received research grant from GE Healthcare, Philips Healthcare and the

Radiological Society of North America (RSNA). S.D. received research grantfrom Philips Healthcare. The other authors declare no conflict of interest.

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J Comput Assist Tomogr • Volume 39, Number 4, July/August 2015

Copyright © 2015 Wolters Kluwer

C omputed tomography (CT) radiation dose is considered oneof themost important safety concernswithmodernmedicine.1–4

A goal of ultralow-dose (ULD) radiation dose has been advo-cated by several federal agencies and national institutes becausethis would be below the average annual dose from backgroundradiation.5–7 The Biologic Effects of Ionizing Radiation reportno. 7 and linear-no-threshold model supported that “population”risk of cancer incidence decreases as the radiation dose to the pa-tient decreases.7 Recent National Institute of Biomedical Imagingand Bioengineering meeting has also advocated the goal ofachieving ULD radiation dose.5,6 In addition, several studies havealready shown dose reduction to less than 1 mSv, especially car-diac and limited high-contrast clinical indications, such as Crohndisease, lung nodules evaluation, and scoliosis.8–13

Consequently, several efforts have been made to decrease thenecessary radiation dose with CT scanning. Iterative reconstruc-tion techniques (IRTs) have enabled dose reduction by reducingimage noise while preserving image quality compared to conven-tional filtered back projection (FBP)–based image reconstruc-tion.4,14,15 Potentially, to this end, several different types of IRThave recently become available. The hybrid IRT works with ablending function that consists of FBP, whereas model-basedIRT involves the system optics of the scanner hardware. Thesetechniques work either in the image space or the raw data space.Examples include iterative reconstruction in image space, iDose(Philips Healthcare), sinogram-affirmed iterative reconstruction(SAFIRE) (Siemens Healthcare), adaptive iterative dose reduction3-dimensional (Toshiba Healthcare), adaptive statistical iterativereconstruction (ASIR) (GEHealthcare), andmodel-based iterativereconstruction (MBIR) (GE Healthcare).16–30 These IRTs haveshown dose reductions of 29% to 66% in abdominal multidetectorCT, and many of them have been accepted as standard reconstruc-tion algorithms in clinical practice for low-dose protocols.16–30

Although these techniques have demonstrated dose reduction po-tential, the smoothening artifacts and therefore, the artificial lookaffect the overall diagnostic image quality at low dose.21 Addition-ally, none of the previous studies have assessed abdominal CT atULD radiation doses.

Hence, the purpose of our study was to assess lesion detec-tion and image quality of ULD abdominal CT reconstructed withFBP and 2 iterative reconstruction techniques: hybrid-based iDose,and image-based SafeCT.

MATERIALS AND METHODS

Patients and Study DesignThis ongoing prospective clinical study was approved by our

institutional review board, and was Human Insurance PortabilityAnd Accountability Act compliant. The inclusion criteria for ourstudy were (a) aged 19 years or greater; (b) scheduled for a routineabdominal CT; (c) ability to provide written informed consent;

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Khawaja et al J Comput Assist Tomogr • Volume 39, Number 4, July/August 2015

(d) hemodynamically stable (conscious, oriented, regular respira-tions of 12–40 breaths/min, pulse rate of 50–90, and systolicblood pressure of 100–140 mm Hg); (e) able to score 18 or morein mini mental state examination; and (f ) ability to hold breath for10 seconds. Patients whowere hemodynamically unstable, unableto provide written informed consent, unable to understand orspeak English, undergoing emergent or stat CT, and womenwho were pregnant or were trying to get pregnant were excludedfrom this study. Subjects with any contrast reaction or extravasa-tions during initial CT image acquisition, as well as patients withbody mass index (BMI) of 33 kg/m2 or higher were excluded.

A study coauthor (R.D.A.K.) used our department's radiol-ogy information system to identify eligible patients. The patientsincluded in our study underwent abdominal CT scanning for clin-ical indications including staging of known or suspected malig-nancy (n, 18 patients), change of bowel habits or abdominalpain (n, 15), and hematuria (n, 08). Forty-one patients (meanage, 62 ± 12 years; F:M, 26:13; mean body weight, 76 ± 16 kg;mean BMI, 27.6 ± 4.7 kg/m2; Fig. 1) gave written informed con-sent for participation in this study. We report the initial resultsbased on data collected on these patients in this ongoing prospec-tive clinical study.

Radiation DosesSize-specific dose estimates were retrieved from each CT

examination from an automatic dose monitoring software usedby our institution (Xposure, Bayer, Toronto). The CT dose in-dex volume (CTDIvol, mGy) and dose length product (DLP,mGy/cm) were recorded from the dose information page.

The mean (± standard deviation) radiation doses for standard-of-care abdominal CT were CTDIvol, 9.0 ± 3.0 mGy; DLP,434.0 ± 196.0 mGy/cm, and size-specific dose estimate,10.0 ± 3.0 mGy). Respective doses for ULD abdominal CTwere 1.2 ± 0.2 mGy, 61.0 ± 2.0 mGy/cm, and 1.5 ± 0.4 mGy(~0.9 mSv). Compared to standard-of-care CT, mean dose reduc-tion was 85% (9.0 vs 1.2 mGy) in ULD abdominal CT.

Therewas no significant difference betweenmale and femalepatients, across mean age (60 ± 11 and 62 ± 13 years, respectively;P = 0.6), mean body weight (83 ± 18 and 73 ± 14 kg; P = 0.06),mean BMI (27.9 ± 4 and 27.4 ± 5 kg/m2; P = 0.7), and meaneffective diameter (29.2 ± 5.9 and 30.4 ± 5.3 cm; P = 0.5).

Scanning TechniquesAll patients were scanned on a 256-slice multidetector CT

scanner (iCT; Philips Healthcare) with (n, 37) or without (n, 02)administration of an intravenous contrast medium (80–100 mLof Iopamidol 370 mg%; Bracco Diagnostic, Princeton, NJ). After

FIGURE 1. Flowchart shows CT image acquisitions at standard andultralow-dose radiation doses with 3 different imagereconstruction algorithms (FBP, SD, ULD).

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centering the patient in the gantry isocenter, 2 orthogonal localizerradiographs were acquired. Standard-of-care CTwas planned onthe localizer radiograph extending from the dome of the dia-phragm to the pubic symphysis. Next, the standard-of-care CT se-ries was duplicated to plan the ULD CT image series over theexact same scan region and range. All scan parameters, with ex-ception of tube current, were kept constant between the 2 imageseries. For the ULD image series, we used a low fixed tube currentof 17 to 20 mAs/slice (mA� gantry rotation time/pitch) to obtaina targeted DLP of under 65 mGy/cm which corresponds to anestimated effective dose of just under 1 mSv (65 mGy/cm �0.015 = 0.98 mSv).31 Therefore, automatic exposure control(AEC) could not be enabled on ULD CT image series whichwas enabled on standard-of-care CT. The remaining scan parame-ters were kept constant between the 2 image series and includedtube potential of 120 kV, 0.985 pitch, helical acquisition mode,128� 0.625mm detector configuration, 0.5 second gantry rotationtime, 5 mm reconstructed section thickness, 2.5 mm reconstruc-tion section interval, and reconstruction filter A. No additionalcontrast was injected for ULD CT series.

Image ReconstructionRaw data of ULD examinations were reconstructed with a

hybrid IRT, iDose4 (Philips Healthcare). Digital Imaging andCommunications in Medicine (DICOM) images of ULD serieswere used to generate SafeCT images (image based-vendor neu-tral IR technique; MedicVision, Israel, Fig. 1). The raw data werereconstructed with conventional FBPmethod to serve as the refer-ence standard, standard dose (SD) FBP. Additionally, ULD FBPwas reconstructed for comparison with ULD IRT image data sets.

Four IRT image series were generated for each patient ULDdata set: (i) iDose (iDosea and iDoseb), and (ii) SafeCT (SCTa andSCTb). iDoseb setting (corresponds to level 4 of iDose algorithm)has a higher noise reduction than iDosea setting (corresponds tolevel 2 of iDose algorithm). Likewise, SCTb setting (correspondsto SafeCT-1 as per manufacturer) has a higher noise reductionpotential compared to SCTa setting (corresponds to SafeCT-0).Hence, for each patient, there were 6 image data sets: SD-FBP,ULD FBP, ULD iDosea, ULD iDoseb, ULD SCTa, and ULDSCTb. SafeCT and iDose images were reconstructed in less than1 minute on a research workstation.

To enable double blinded evaluation, each image data set wascoded, deidentified and randomized by a study coauthor (R.D.A.K.).

Task-Based Evaluation for Subjective ImageQualityAll randomized CT image data sets were reviewed on a

DICOM compliant 55-inch screen with 2 mega pixel resolutionfor assessment of subjective image quality. All image data setswere presented to 4 experienced abdominal radiologists (M.H.with 15 years, M.B. with 12 years, G.C. with 5 years, and A.K.with 4 years of experience) for independent assessment of imagequality. All radiologists were trained on 2 image data sets forassessing evaluation system for subjective image quality, lesiondetection, and to improve interobserver agreement. The 2 train-ing image data sets were not used in the subsequent statisticalanalyses (Fig. 1).

For evaluation of subjective image quality, a 5-point gradingsystem was used to score the contour, margin, and wall of normalabdominal structures as well as identified lesions (grade 1, imagequality better than clinically needed; grade 2, image quality equalto clinical need; grade 3, image quality slightly below the clinicalneed but with sufficient clinical diagnostic performance; grade 4,image quality mostly below the clinical need; and grade 5, unac-ceptable clinical diagnostic performance) was used. We considered

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J Comput Assist Tomogr • Volume 39, Number 4, July/August 2015 Ultralow Dose Abdominal Computed Tomography

grades 1 to 3 as “acceptable or optimal” and grades 4 to 5 as“nonacceptable or suboptimal.” Training cases used the same5-point grading scale and method as above. Table 1 demon-strates the assessed structures using a task-based evaluationmethod that was used to assess radiologists' performance fora specific diagnostic task.

All 4 radiologists assessed the images in a blinded indepen-dent manner. All images from patients, consisting of a randommix of image data sets were sequentially read in 2 separate indi-vidual sessions by each reader. Each radiologist completed the

TABLE 1. Task-Based Evaluation System: An Aggregate Listfor Normal Abdominal Structures Assessed by 4Abdominal Radiologists

(A) Assessment of normal anatomy(a) Liver

Liver marginLiver parenchymaArtifact (s) ± pseudolesion

(b) Adrenal glandContour

(c) PancreasContour

(d) Gall bladder (if present)Wall

(e) KidneyMarginPelvis

(f ) RetroperitoneumLymph node (s) conspicuity, subcentimeter

(g) PeritoneumBlood vessels and soft-tissue

(h) Urinary bladderWall

(i) BowelWall

(B) Assessment of lesions(a) Liver

Low attenuation lesion (s)(b) Adrenal Gland

Nodule(c) Pancreas

Lesion(d) Gall bladder (if present)

Lesion(e) Kidney

Stone(s)Cyst(s)Solid lesion(s)Indeterminate lesion(s)

(f ) RetroperitoneumLymph node(s) conspicuity, enlarged

(g) Urinary bladderLesion

(h) BowelAbnormality (diverticula)

All structures were assessed on soft tissue windows.

Soft tissue window (window width, 400; window length, 40).



evaluation in 2 study sessions, which were separated by a periodof 1 week.

Reference Standard for Lesion Presence andMatching of Reader Markings

Lesion detection was performed independently on ULD FBPimages without showing SD FBP images. After lesion detection,the coauthor (R.D.A.K.) noted a list of all lesions for that particu-lar patient. After detection of lesions, radiologists were shown all6-image series (SD-FBP, ULD FBP, ULD iDosea, ULD iDoseb,ULD SCTa, and ULD SCTb) all together, all side by side for com-parison. At this point, reader was blinded to the arrangement ofULD image series on the screen. However, they were made awareof the SD-FBP images that were always located on the top right ofthe screen. At this step, lesions were assessed in all ULD imagesall together and compared to reference standard SD FBP for anymissed and/or false positive lesions. All true lesions were thencompared across ULD images with SD FBP for their image qual-ity on the grading scale as mentioned above.

For presence or absence of lesions, SD-FBP images wereconsidered as the “reference standard.” All the lesions detected inthe SD FBP images were considered as the “true lesions.”Any le-sions seen in the ULD FBP images and not seen in SD-FBP wereconsidered as false positive or pseudolesions. Any lesions thatwere not seen in ULD FBP images but seen in SD-FBP imageswere considered as missed lesions.

Note that detection of abnormal findings was performed onULD FBP images only. After that, if any lesions were seen duringside-by-side comparison on SD-FBP images, those were recordedas “missed lesions” as mentioned above.

Evaluation of Objective Image QualityCircular regions of interest (ROI, 20–30 mm) were drawn in

the homogenous liver parenchyma, anterior abdominal fat, andabdominal aorta at the level of porta hepatis to cover at least twothirds of its lumen. Mean attenuation values (Hounsfield Units[HU]) and image noise (standard deviation) were measured foreach ROI. The size and position of each ROI were kept constantthroughout the entire study performed on a DICOM image work-station (ClearCanvas, Toronto). The pattern of noise distribu-tion and spectrum (noise spectral density) was assessed inMATLAB program for SD-FBP, ULD FBP, and ULD IRT andwas reported graphically.

Statistical AnalysisAll statistical analyses were performed on SPSS software

(version 21.0, SPSS Chicago, IL) and spreadsheet software(Microsoft Excel 2010; Microsoft, Richmond, VA). Differencesbetween objective image noise and patient characteristics were an-alyzed with 1-way analysis of variance. Differences between sub-jective image quality for reconstruction algorithms (ULD FBP,iDose, and SafeCT) were assessed with Friedman test (nonpara-metric for repeated measures of analysis of variance) for a statis-tically significant difference among the image sets. Post hocanalysis was performed with Dunn multiple comparison test.Wilcoxon signed-rank test was performed to assess the performancefor all assessed settings of reconstruction algorithms. Rank-sumdifference was calculated and compared for each assessed indi-vidual abdominal-pelvis structure and lesions.

Intraclass correlations in addition to 95% confidence intervalswere used to determine interobserver agreement whose interpreta-tion was based as follows, 0 = no agreement; 1 = full agreement;0 to 1 = agreement declines as correlation moves toward 0. AP value of 0.05 or less was considered statistically significant.

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RESULTS

Lesion Detection (True, Pseudo, andMissed Lesions)

All lesions (seen in ULD FBP, n = 104) were also detected inULD image series. Therefore, no lesionswere missed in our study.Additionally, no lesions were described by readers in ULD imageseries that were not present in the SD FBP series. Hence, nopseudolesions were reported in this preliminary phase of study.To note, although lesions were detected in all ULD image series,their image quality was not similar across FBP, iDose, and SafeCTtechniques. Lesions characterized to individual organs have beenreported in the subsequent sections.

Subjective Image QualityThere was substantial interobserver agreement between the

4 radiologists (intraclass correlation, 0.69; P < 0.001).Liver margins were suboptimally visualized in 38 of 39 patients

on ULD FBP images and optimal across all ULD iDose (38/39)and ULD SafeCT (38/39) images. Visualization of liver paren-chyma in ULD IRT images was significantly better than ULDFBP (P < 0.001). Among ULD IRT images, ULD STb had signif-icantly higher rank sum score compared to ULD iDosea images(P < 0.05; Fig. 2).

FIGURE 2. A 62-year-old woman (BMI, 20 kg/m2) with abdominal pain8 mGy; ultralow-dose scan, 1.2 mGy) showed multiple liver metastatic leultralow-dose images and unacceptable with ULD FBP method.

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Overall, only 21 of 52 lesions (size range, 8–20 mm; mainlyliver cysts, hypoattenuated liver masses) were deemed acceptablefor conspicuity in ULD FBP images compared to ULD iDose(38–39/52) andULDSafeCT (39–40/52 images;P< 0.0001; Fig. 3).

The visibility of gall bladder, adrenal glands, pancreatic con-tours, kidneys, and bowel wall were significantly better with ULDiDose andULDSafeCT images compared toULDFBP (P< 0.01,Table 2). All adrenal nodules (n, 04 size range, 10–20 mm) weredeemed optimal with ULD IRT images and suboptimal on ULDFBP images. All 4 pancreatic lesions (solid masses, size rangeof 15–40 mm was deemed acceptable with ULD IRT images andsuboptimal on ULD FBP images (P > 0.05).

A total of 52 renal cysts (size range, 5–30 mm) were assessed.Overall, only 32 of 52 cysts were deemed acceptable in ULDFBP images compared to ULD iDose (49–50/52) andULDSafeCT(46–49/52) images (Fig. 4). Compared to ULD FBP, renal cystswere seen significantly better with ULD iDose (both settings) im-ages (P < 0.001, and P < 0.05, respectively; Fig. 4). Renal stoneswere seen in 3 patients, and their appearance did not change inULD images irrespective of reconstruction algorithm.

Ring artifacts (related to photon starvation) in liver were seenin 12 of 39 patients at ULD dose (BMI ≤ 25 kg/m2, 0/10 patients;25.1–29.9 kg/m2, 3/11; and ≥30 kg/m2, 9/18). No pseudolesionswere reported in the presence of above ring artifacts.

For scores for individual organs and lesions type, subjectiveimage quality grading has been summarized in Tables 2 and 3.

and distention underwent abdominal CT (standard of care, CTDIvolsions. Both liver parenchyma and lesions were acceptable for all



FIGURE 3. A 64-year-old woman (BMI, 29 kg/m2) with known Hodgkin disease underwent abdominal CT (standard of care, CTDIvol 6 mGy;ultralow-dose scan, 1.2 mGy) showed a low attenuation liver lesion (arrow). Both liver parenchyma and lesion were acceptable for allultralow-dose images and unacceptable with ULD FBP (too noisy).

TABLE 2. Subjective Image Quality Grading* (Median Scores With Interquartile Range in the Parenthesis) for NormalAbdominal Structures

Normal StructuresSD

FBP† SS FBP‡ iDoseaRank-Sum

Score iDosebRank-Sum

Score STaRank-Sum

Score STbRank-Sum

Score

Liver margin 2 4 (3–5) 3 (2–4) 137 3 (2–4) 142 3 (2–4) 137 3 (2–4) 195Liver parenchyma 2 4.5 (3–5) 3 (3–5) 135 3 (3–4) 150 3 (2–4) 164 3 (2–4) 213Adrenal gland contour 2 4 (3–5) 3 (2–5) 138 3 (2–5) 138 3 (3–5) 118 3 (2–5) 162Pancreatic contour 2 4 (3–5) 3 (2–4) 130 3 (2–4) 148 3 (3–4) 135 3 (2–4) 159Gall bladder wall 2 4 (3–5) 3 (2–5) 97 3 (2–5) 97 3 (2–5) 106 3 (2–5) 126Renal margin 2 4 (3–5) 3 (2–3) 147 3 (2–4) 143 3 (2–4) 151 2 (2–3) 199Renal pelvis 2 4 (2–5) 3 (2–5) 124 3 (2–5) 123 3 (2–5) 118 3 (2–5) 148Peritoneum 2 4 (4–5) 3 (2–5) 145 3 (2–5) 150 3 (2–5) 150 3 (2–5) 187Bowel wall 2 4 (2–5) 3 (2–4) 141 3 (2–4) 141 3 (2–4) 137 3 (2–4) 153Urinary bladder wall 2 4 (3–5) 3 (2–5) 113 3 (2–5) 109 3 (2–5) 118 3 (2–5) 142

Rank sum difference scores were calculated for each setting of IR technique and compared to SS-FBP.

*Five-point grading scale: grade 1, image quality better than clinically needed and supraclinical diagnostic performance; grade 2, image quality equal toclinical need and sufficient clinical diagnostic performance; grade 3, image quality slightly below the clinical need but with sufficient clinical diagnosticperformance; grade 4, image quality mostly below the clinical need and suboptimal clinical diagnostic performance; and grade 5, unacceptable clinical di-agnostic performance). We considered grades 1 to 3 as “acceptable or optimal” and grades 4 to 5 as “nonacceptable or suboptimal.”

†SD-FBP was the reference standard and was automatically given a score of 2 during evaluation.

‡The rank-sum score was calculated for ULD IRT images compared to ULD FBP images (and hence, no rank sum was reported for SS-FBP).


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FIGURE 4. A 78-year-old man (BMI, 21 kg/m2) with known primary hepatocellular carcinoma underwent abdominal CT (standard of care,CTDIvol 6 mGy; ultralow-dose scan, 1.2 mGy) showed a low attenuation renal lesion in right kidney (arrow). Both renal margins and lesionwere acceptable for all ultralow-dose images and unacceptable with ULD FBP (too noisy) images.


Objective Image Quality

Objective Noise MeasurementsThe mean CT number (HU) values and image noise (standard

deviations of attenuation values) are summarized in Table 4. Over-all, mean objective noise was lower in ULD iDoseb images com-pared to other IR settings (29 ± 5 HU, P < 0.001). Objective noisewas 39% to 59% (P < 0.001) lower for ULD iDose and 34% to52% (P < 0.001) lower for ULD SafeCT compared to ULD FBP(71 ± 26 HU).

Noise Spectral DensityThe iDose and SafeCT techniques improved image noise in

medium and high-frequency range. Noise spectral density graphsfor the studied reconstruction algorithms are plotted in Figure 5.

TABLE 3. Subjective Image Quality Grading (Median Scores With InAbdominal Structures

Abnormal Structures SD-FBP*ULDFBP† iDosea

Rank SumScore

Liver lesions 2 4 (3–5) 3 (2–5) 38Renal cysts 2 4.5 (3–5) 3 (2–5) 52Colonic diverticula 2 4 (3–5) 3 (2–3) 55Retroperitoneal lymph nodes 2 4 (4) 2 (2–3) 27

Rank sum difference scores were calculated for each setting of IR technique

*SD-FBP was the reference standard and was automatically given a score o

†The rank sum score was calculated for ULD IRT images compared to ULD

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DISCUSSION

We found that ultralow-dose abdominal CTexaminations re-constructed with traditional FBP method demonstrated unaccept-able diagnostic image quality. This may be due to excessive noisein FBP images at ULD doses. Compared to ULD FBP images,data sets reconstructed with hybrid-IRT iDose and image-basedIRT SafeCT had 34% to 59% lower image noise, which enabledacceptable lesion evaluation. Additionally, ULD IRT images pre-served image quality of small structures in abdomen and pelvis(such as liver and renal margins, gall bladder wall, and adrenalglands) close to SD-FBP images particularly in smaller patientswith BMI of 25 kg/m2 or lower. On the other hand, abdominalCT examinations in patients with BMI greater than 25 kg/m2

scanned at ULD radiation doses were deemed unacceptable forevaluation with both assessed IRTs. For selective clinical situations,

terquartile Range in the Parenthesis) for Abnormal

iDosebRank Sum

Score STaRank Sum

Score STbRank Sum

Score

3 (2–5) 38 3 (2–5) 33 3 (2–5) 543 (2–5) 52 3 (3–5) 41 3 (2–5) 433 (2–3) 55 3 (2–4) 51 3 (2–4) 552 (2–3) 27 2 (2–3) 27 3 (2–3) 31

and compared to SS-FBP.

f 2 during evaluation.

FBP images (and hence, no rank sum was reported for ULD FBP).



TABLE 4. Objective Image Noise

Soft Tissue SD FBP ULD FBP ULD iDosea ULD iDoseb ULD STa ULD STb

Attenuation (HU)*Liver 101.9 ± 26.7 109.1 ± 24.4 102.2 ± 25.1 102.1 ± 24.2 108.8 ± 24.8 109.5 ± 23.8Fat tissue −92.7 ± 34.5 −92 ± 26.7 90.1 ± 34.6 89.5 ± 34.6 93.5 ± 36.6 93.5 ± 35.9Aorta 178.6 ± 68.7 140.9 ± 39.7 130.3 ± 39.8 130.1 ± 38.3 140.6 ± 40.5 140.9 ± 39.7

Noise†Liver 26.2 ± 6.7 70.7 ± 26.1 34.2 ± 5.8 29.3 ± 5.2 46.7 ± 24.8 33.7 ± 12.5Fat tissue 16.6 ± 3 .4 43.1 ± 18.5 26.4 ± 4.2 23.1 ± 4.2 28.3 ± 10.8 21.0 ± 8.5Aorta 28.9 ± 8.4 79.2 ± 28.2 36.6 ± 6.2 31.7 ± 6.3 51.8 ± 17.6 38.3 ± 14.9

*Data are means ± standard deviation. No significant differences were found (P values of 0.99 for liver, 0.993 for fat, 0.983 for aorta; ANOVA test).

†Data are means ± standard deviation. Data were significantly different (P values of 0.001 for liver, fat, and aorta).

ANOVA indicates analysis of variance.


such as evaluation of colonic diverticular disease, kidney stones,and kidney cysts, however, ULD images reconstructed with iDoseand/or SafeCTwere found to be acceptable regardless of patientsize. Iterative reconstruction techniques (SafeCT and iDose) en-abled ULD abdominal CTwith acceptable image quality and le-sion detection in patients with body mass indices of less than orequal to 25 kg/m2.

At ULD radiation dose, patients with BMI of 30 kg/m2 orhigher had higher-dose reduction relative to the standard-of-careCT compared to patients with BMI of 25 kg/m2 or lower (91% vs83%; P < 0.0001). SafeCT outperformed other IR algorithms andULD FBP in larger patients (BMI ≥30 kg/m2) for visualization ofmost normal structures and some abnormal findings in abdomen

FIGURE 5. NSDplots for 2 patients with different BMI (A: 67 kg, BMI 22 kand ULD iDoseb) show consistent spectral suppression for both patients.patients. Notice the spectral density profiles of 2 different settings of ULDand no overlap was seen in patient A. NSD indicates noise spectral dens



and pelvis. This was likely a result of significantly lower imagenoise in SafeCT images as compared to iDose and ULD FBP(64–84% lower noise than ULD FBP; P < 0.001). Unfortunately,despite the improved visibility of certain structures and lower im-age noise, SafeCT images were not diagnostically acceptable atULD dose in patients with BMI greater than 25 kg/m2.

Margins of abdominal viscera (liver and kidneys) were ac-ceptably seen at ULD radiation doses independent of IR algo-rithms and BMI subgroups. However, radiologists had differentopinions about appearance of organ parenchyma with IRTs. TheULD SafeCT images with greater image noise retained the ex-pected liver texture in most cases, which may have been responsi-ble for its higher acceptability for evaluation of liver parenchyma

g/m2 and B: 133 kg, BMI 32 kg/m2). NSDplots of iDose (ULD iDosea

Spectral plots of SafeCT technique show different trends for bothSafeCT overlap in patient B without showing significant differences

ity. Figure 5 can be viewed online in color at www.jcat.org.

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(suboptimal for only 4–9/39 patients). As has been reported inprevious studies,21,32 change in appearance of liver parenchymaand altered image texture with the IR techniques did not compro-mise detection of focal liver lesions in our study.

Previous studies have assessed the feasibility of coronary CTangiography, lumbar spine CT, Crohn disease, and whole spineCT at ULD radiation doses.8–12 However, to our knowledge,ULD doses for CTof abdomen and pelvis have not been assessedwith IR algorithms. Recent publications have expounded the ben-efits of ULD radiation dose for CTexaminations to ignite investi-gations and technology development for targeting substantial dosereduction which is below the average annual dose from back-ground radiation.5,6 Abdominal CT is the most commonly per-formed CT examination in the body and perhaps the mostchallenging region in the body for ULD radiation dose levelsdue to presence of low-contrast structures and lesions as well pre-ponderance of this body region to accumulate excess adipose tis-sue in larger subjects.

Previous studies have assessed the role of single vendor IRalgorithms in abdominal CT at higher radiation doses comparedto our study (ranging from 4.2 mGy to 17 mGy compared to1.2 mGy in our study).16–30 Deak et al33 noted significantly im-proved image quality, low-contrast resolution, and decreasedimage noise with MBIR images compared to that of ASIR in ab-dominal CT performed at 9 ± 4.1mGy. However, these doses weresubstantially higher compared to our study (about 2- to 5-folds).Likewise, Singh et al19 have reported improved diagnostic confi-dence for abdominal CT examinations reconstructed with ASIRat 4.2 mGy radiation dose (about 2-fold higher radiationdoses compared to our study). In another study, Kataria andSmedby34 reported improved image quality with SAFIRE(Siemens Healthcare) technique for abdominal CT examina-tions performed at 2.5 ± 0.6 mGy (52% higher radiation dosethan our study).

Ring artifacts in ULD images (particularly in patients withBMI > 25 kg/m2) regardless of reconstruction techniques were amajor cause of unacceptable performance of both ULD FBP andULD IRT techniques. We believe they were seen because of pho-ton starvation at this low radiation dose. To note, these artifactswere also seen ULD FBP images that explains the problem rootedduring acquisition of data during scan. Other clinical studies havealso reported different types of artifacts in low-dose abdominalCT. For example, Deak et al33 reported consistent pattern of subtlestaircase effect on bony interfaces in addition to blacked-out arti-facts on skin to air interface withMBIR technique (at 9 mGy) thatnegatively affected the image quality. Kataria and Smedby34 re-ported ring artifacts for low-dose CT images reconstructed withSAFIRE at 2.5 mGy radiation dose.

The most important implication of our study is that ULD ab-dominal CT is feasible with the use of iterative reconstruction al-gorithms in patients with BMI of 25 kg/m2 or lower. We believethat further improvements in CT hardware and/or iterative recon-struction technologies may enable ULD abdominal CT in largerpatients. In addition to the known and assessed complications oflarge body habitus, patients should also understand the limitationsof radiation dose reduction with obesity. Our study also describesand uses a comprehensive task-based evaluation method for eval-uation of normal structures and abnormal findings when assessinglow radiation dose CT. Currently, many physical metrics, such asnoise power spectrum, noise measurements, and modulationtransfer function are used to quantify CT image quality.35 How-ever, these metrics do not describe the image quality and do notcorrelate the diagnostic performance of radiologists for a givenclinical task—which is the eventual measure of image quality.To our knowledge, this is the first time this type of evaluation

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has been used for the evaluation of low-dose abdominal CTexam-inations. It refers to a system that requires grading individual diag-nostic tasks (such as organs and their related abnormalities). Thisallows a comprehensive and detailed assessment for a specificbody region under consideration for dose reduction potential.We also believe that CT scan manufacturers should also improvesignal detection at ULD radiation dose and invest in creating iter-ative reconstruction algorithms to reduce artifacts related to pho-ton starvation. From standpoint of image reconstruction times,both IR algorithms assessed in our study (iDose and SafeCT) tookless than 5 minutes on an offline reconstruction box, which is con-siderably shorter on the CTuser interface.

Our study had several limitations. First, the qualitative anal-ysis scoring system was subjective in nature. However, subjectiv-ity is difficult to prevent in qualitative analysis. We tried tominimize subjectivity by having multiple readers and by adoptinga comprehensive task-based evaluation of multiple normal and ab-normal anatomical levels in abdomen and pelvis. Additionally, le-sion detection with characterization (true, pseudo, and missed)added a more objective perspective to our study and helped toovercome the subjectivity. Second, there was about a 10-seconddelay between standard-of-care and low-dose image series thatmay have changed the appearance of contrast enhancement inthe 2 image series. Third, patients with a BMI greater than32 kg/m2 were not recruited because we doubted that IRTs couldprovide acceptable image quality in these larger patients. Weaimed to keep a dose limit of under 1 mSv for the entire abdomi-nal multidetector computed tomography (MDCT) using a ULDprotocol. To approach under 1 mSv radiation dose (or a dose-length product of less than 65 mGy.cm), we reduced the mA onthe protocol. This resulted into scans that were under 1 mSv radia-tion dose. We believe that using AEC approach for less than 1-mSvscans would not have been useful. Therefore, we used a fixed-mAapproach. This has limited the generalizability of the results. Futurestudies may enable AEC technique that may overcome limited im-age quality for larger patients. Finally, we observed variability inscores for subjective image quality across 4 radiologists, whichmade our results difficult to generalize. At this time, we would liketo highlight the role of using reference phantoms and modeledreader performance to evaluate the performance of low-dose scansusing different vendors' equipment and techniques.

Although there were no missed or pseudolesions in this on-going study yet, we believe that a higher number of low-contrastlesions in a larger cohort of patients is definitely required to vali-date our initial results. Various studies have assessed the role ofIRTs for detection of lesions in low-dose MDCT.36–42 Also, stud-ies have shown decreased low-contrast object detection at lowerradiation doses. Hence, our initial results with ultralow-doseMDCT require validation in a larger sample size.

In conclusion, ultralow-dose abdominal CT is feasible withiterative reconstruction algorithms in smaller patients (BMI ≤25 kg/m2) with acceptable image quality, similar diagnostic accu-racy, and a mean 85% dose reduction compared to standard-of-care abdominal CT examinations. In patients with BMI greaterthan 25 kg/m2, IR algorithms do not provide acceptable diagnosticinformation. This enables the radiation dose from abdominal-pelvic CT to be cut down to less than 1 mSv in the former cohortthat is only one third of the average annual dose from backgroundradiation sources.

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