Publications by authors named "Satheesh Krishna"

56 Publications

The Renal Vasculature: What the Radiologist Needs to Know.

Radiographics 2021 Sep-Oct;41(5):1531-1548. Epub 2021 Jul 30.

From the Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital, and Women's College Hospital, University of Toronto, 200 Elizabeth St, Toronto, ON, Canada M5G 2C4 (A.L., M.J.T., K.K., S.K.); Department of Radiology, University of Iowa, Iowa City, Iowa (S.N.); and Department of Medical Imaging, Ottawa Hospital, University of Ottawa, Ottawa, Ont, Canada (N.S.).

The physiologic role of the kidneys is dependent on the normal structure and functioning of the renal vasculature. Knowledge and understanding of the embryologic basis of the renal vasculature are necessary for the radiologist. Common anatomic variants involving the renal artery (supernumerary arteries and prehilar branching) and renal vein (supernumerary veins, delayed venous confluence, retroaortic or circumaortic vein) may affect procedures like renal transplantation, percutaneous biopsy, and aortic aneurysm repair. Venous compression syndromes (anterior and posterior nutcracker syndrome) can be symptomatic and can be diagnosed with a combination of radiologic features. Renal artery stenosis is commonly atherosclerotic and is diagnosed with Doppler US, CT angiography, or MR angiography. Fibromuscular dysplasia, the second most common cause of renal artery narrowing, has a characteristic string-of-beads appearance resulting from multifocal stenoses and dilatations. Manifestations of renal vasculitis differ depending on whether the affected vessels are large, medium, or small. Renal vascular injury is graded according to the American Association for the Surgery of Trauma (AAST) renal injury scale, which defines and in renal injuries. Both renal arteries and veins are affected by primary neoplasms or secondarily by neoplasms from adjacent structures. Differentiation between bland thrombus and tumor thrombus and the extent of involvement dictate management in malignancies, especially renal cell carcinoma. Aneurysms, pseudoaneurysms, arteriovenous malformations, and arteriovenous fistulas can affect renal vessels and can be diagnosed with specific imaging features. The radiologist has a critical role in identification of specific imaging characteristics and establishing the diagnosis in the varied pathologic conditions affecting the renal vasculature, which is critical for directing management. Thus, the renal vasculature should be an integral part of radiologists' checklist. RSNA, 2021.
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http://dx.doi.org/10.1148/rg.2021200174DOI Listing
July 2021

Bosniak Classification of Cystic Renal Masses, Version 2019: A Pictorial Guide to Clinical Use.

Radiographics 2021 May-Jun;41(3):814-828. Epub 2021 Apr 16.

From the Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, 1053 Carling Ave, Ottawa, ON, Canada K1H 1H6 (N.S.); Departments of Radiology (M.S.D., N.E.C.) and Urology (M.S.D.), Michigan Medicine, University of Michigan, Ann Arbor, Mich; Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital and Women's College Hospital, University of Toronto, Toronto, ON, Canada (S.K.); Department of Radiology, University of Nebraska Medical Center, Omaha, Neb (E.A.E.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (I.P.); Department of Radiology, New York University Langone Medical Center, New York, NY (N.H.); Department of Radiology and Diagnostic Imaging, Hospital Israelita Albert Einstein, São Paulo, Brazil (R.H.B.); Department of Radiology, Brigham and Women's Hospital/Dana-Farber Cancer Institute, Harvard Medical School, Boston, Mass (A.S.); and Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (S.G.S.).

Cystic renal masses are commonly encountered in clinical practice. In 2019, the Bosniak classification of cystic renal masses, originally developed for CT, underwent a major revision to incorporate MRI and is referred to as the Bosniak Classification, version 2019. The proposed changes attempt to define renal masses (ie, cystic tumors with less than 25% enhancing tissue) to which the classification should be applied; emphasize specificity for diagnosis of cystic renal cancers, thereby decreasing the number of benign and indolent cystic masses that are unnecessarily treated or imaged further; improve interobserver agreement by defining imaging features, terms, and classes of cystic renal masses; reduce variation in reported malignancy rates for each of the Bosniak classes; incorporate MRI and to some extent US; and be applicable to all cystic renal masses encountered in clinical practice, including those that had been considered indeterminate with the original classification. The authors instruct how, using CT, MRI, and to some extent US, the revised classification can be applied, with representative clinical examples and images. Practical tips, pitfalls to avoid, and decision tree rules are included to help radiologists and other physicians apply the Bosniak Classification, version 2019 and better manage cystic renal masses. An online resource and mobile application are also available for clinical assistance. RSNA, 2021.
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http://dx.doi.org/10.1148/rg.2021200160DOI Listing
April 2021

Pharmacokinetic modeling of dynamic contrast-enhanced (DCE)-MRI in PI-RADS category 3 peripheral zone lesions: preliminary study evaluating DCE-MRI as an imaging biomarker for detection of clinically significant prostate cancers.

Abdom Radiol (NY) 2021 09 5;46(9):4370-4380. Epub 2021 Apr 5.

Department of Radiology, The Ottawa Hospital, University of Ottawa, Ottawa, Canada.

Purpose: To determine if pharmacokinetic modeling of DCE-MRI can diagnose CS-PCa in PI-RADS category 3 PZ lesions with subjective negative DCE-MRI.

Materials And Methods: In the present IRB approved, bi-institutional, retrospective, case-control study, we identified 73 men with 73 PZ PI-RADS version 2.1 category 3 lesions with MRI-directed-TRUS-guided targeted biopsy yielding: 12 PZ CS-PCa (ISUP Grade Group 2; N = 9, ISUP 3; N = 3), 27 ISUP 1 PCa and 34 benign lesions. An expert blinded radiologist segmented lesions on ADC and DCE images; segmentations were overlayed onto pharmacokinetic DCE-MRI maps. Mean values were compared between groups using univariate analysis. Diagnostic accuracy was assessed by ROC.

Results: There were no differences in age, PSA, PSAD or clinical stage between groups (p = 0.265-0.645). Mean and 10th percentile ADC did not differ comparing CS-PCa to ISUP 1 PCa and benign lesions (p = 0.376 and 0.598) but was lower comparing ISUP ≥ 1 PCa to benign lesions (p < 0.001). Mean Ktrans (p = 0.003), Ve (p = 0.003) but not Kep (p = 0.387) were higher in CS-PCa compared to ISUP 1 PCa and benign lesions. There were no differences in DCE-MRI metrics comparing ISUP ≥ 1 PCa and benign lesions (p > 0.05). AUC for diagnosis of CS-PCa using Ktrans and Ve were: 0.69 (95% CI 0.52-0.87) and 0.69 (0.49-0.88).

Conclusion: Pharmacokinetic modeling of DCE-MRI parameters in PI-RADS category 3 lesions with subjectively negative DCE-MRI show significant differences comparing CS-PCa to ISUP 1 PCa and benign lesions, in this study outperforming ADC. Studies are required to further evaluate these parameters to determine which patients should undergo targeted biopsy for PI-RADS 3 lesions.
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http://dx.doi.org/10.1007/s00261-021-03035-6DOI Listing
September 2021

Bosniak classification of cystic renal masses, version 2019: interpretation pitfalls and recommendations to avoid misclassification.

Abdom Radiol (NY) 2021 06 23;46(6):2699-2711. Epub 2021 Jan 23.

Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX, USA.

The purpose of this review is to describe the potential sources of variability or discrepancy in interpretation of cystic renal masses under the Bosniak v2019 classification system. Strategies to avoid these pitfalls and clinical examples of diagnostic approaches are also presented. Potential pitfalls in the application of Bosniak v2019 are divided into three categories: interpretative, technical, and mass related. An organized, comprehensive review of possible discrepancies in interpreting Bosniak v2019 cystic masses is presented with pictorial examples of difficult clinical cases and proposed solutions. The scheme provided can guide readers to consistent, precise application of the classification system. Radiologists should be aware of the possible sources of misinterpretation of cystic renal masses when applying Bosniak v2019. Knowing which features and types of cystic masses are prone to interpretive errors, in addition to the inherent trade-offs between the CT and MR techniques used to characterize them, can help radiologists avoid these pitfalls.
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http://dx.doi.org/10.1007/s00261-020-02906-8DOI Listing
June 2021

Evaluation of Crohn Disease Activity Using a Potential Abbreviated MRE Protocol Consisting of Balanced Steady-State Free Precession MRI Only Versus Full-Protocol MRE.

AJR Am J Roentgenol 2021 02 9;216(2):384-392. Epub 2020 Dec 9.

Department of Biostatistics, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.

The purpose of the present study was to compare the diagnostic performance of an abbreviated MR enterography (MRE) protocol consisting of balanced steady-state free-precession (b-SSFP) imaging only versus standard full-protocol MRE for the evaluation of Crohn disease activity. This single-center retrospective study included 112 patients with Crohn disease (66 women and 46 men; age range, 18-84 years) who underwent MRE between January 2017 and March 2018. Utilizing binary and 5-point Likert confidence scales, two blinded readers independently interpreted and scored disease activity on b-SSFP sequences only and on full-protocol MRE images. Interreader and intrareader agreement on confidence regarding disease activity were calculated using weighted kappa indexes. Correlation between MRE findings of Crohn disease and the Harvey-Bradshaw index was also performed. Perfect intrareader agreement and strong interreader agreement on disease activity were observed (intrareader agreement: κ = 0.97, 0.96, and 0.96 for reader A, reader B, and both readers combined; interreader agreement: κ = 0.82 for b-SSFP imaging only and κ = 0.81 for MRE). For detecting active Crohn disease, b-SSFP sequences had a sensitivity and specificity of 97% and 100%, respectively, for reader A and 98% and 86%, respectively, for reader B. Strong-to-perfect intrareader agreement was achieved between b-SSFP imaging only and MRE for identification of penetrating disease (κ = 0.80 and 0.97) and stenosing disease (κ = 0.87 and 0.95). Perfect intrareader agreement was also obtained between b-SSFP imaging only and MRE for detecting abnormal bowel segments (κ = 0.91 for reader A; κ = 0.98 for reader B). Weak agreement was noted between both b-SSFP imaging only and MRE versus the Harvey-Bradshaw index (κ = 0.08 of reader A; κ = 0.04 for reader B). Robust agreement was observed between b-SSFP imaging only and full-protocol MRE for the assessment of Crohn disease activity and complications. An abbreviated MRE protocol that exclusively uses b-SSFP sequences appears feasible and has significant implications for health care resources.
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http://dx.doi.org/10.2214/AJR.20.22856DOI Listing
February 2021

Update on MRI of Cystic Renal Masses Including Bosniak Version 2019.

J Magn Reson Imaging 2021 08 2;54(2):341-356. Epub 2020 Oct 2.

Departments of Radiology and Urology, Michigan Medicine, University of Michigan, Ann Arbor, Michigan, USA.

Incidental cystic renal masses are common, usually benign, and almost always indolent. Since 1986, the Bosniak classification has been used to express the risk of malignancy in a cystic renal mass detected at imaging. Historically, magnetic resonance imaging (MRI) was not included in that classification. The proposed Bosniak v.2019 update has formally incorporated MRI, included definitions of imaging terms designed to improve interobserver agreement and specificity for malignancy, and incorporated a variety of masses that were incompletely defined or not included in the original classification. For example, at unenhanced MRI, homogeneous masses markedly hyperintense at T -weighted imaging (similar to cerebrospinal fluid) and homogeneous masses markedly hyperintense at fat suppressed T -weighted imaging (approximately ≥2.5 times more intense than adjacent renal parenchyma) are classified as Bosniak II and may be safely ignored, even when they have not been imaged with a complete renal mass MRI protocol. MRI has specific advantages and is recommended to evaluate masses that at computed tomography (CT) 1) have abundant thick or nodular calcifications; 2) are homogeneous, hyperattenuating, ≥3 cm, and nonenhancing; or 3) are heterogeneous and nonenhancing. Although MRI is generally excellent for characterizing cystic renal masses, there are unique weaknesses of MRI that bear consideration. These details and others related to MRI of cystic renal masses are described in this review, with an emphasis on Bosniak v.2019. A website (https://bosniak-calculator.herokuapp.com/) and mobile phone apps named "Bosniak Calculator" have been developed for ease of assignment of Bosniak classes. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY STAGE: 3.
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http://dx.doi.org/10.1002/jmri.27364DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8017011PMC
August 2021

Use of Oral Contrast in Abdominal/Pelvic CT Scans.

Can Assoc Radiol J 2021 Aug 16;72(3):339-340. Epub 2020 Sep 16.

Joint Department of Medical Imaging, University Health Network, 7938University of Toronto, Ontario, Canada.

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http://dx.doi.org/10.1177/0846537120957322DOI Listing
August 2021

Imaging spectrum of traumatic urinary bladder and urethral injuries.

Abdom Radiol (NY) 2021 02 28;46(2):681-691. Epub 2020 Jul 28.

Depertment of Medical Imaging, The Ottawa Hospital, Ottawa, ON, Canada.

Urinary bladder and urethral injuries usually occur as part of multiple injuries in polytrauma patients. These injuries are easily overlooked because the initial evaluation is focused on other life-threatening injuries such as traumatic brain injury, hemopneumothorax or hemoperitoneum. Although the urinary bladder and urethral injuries are not life-threatening, they pose the risk of long-term morbidity which can be burdensome. These complications include urinary incontinence, voiding dysfunction, urethrocutaneous fistula, urethral stricture and erectile dysfunction. Computed tomography (CT) findings of urinary bladder and urethral injuries are usually subtle. Retrograde fluoroscopic/CT cystography and urethrography remain the mainstay imaging techniques for complete evaluation, diagnosis, staging, and follow-up of these traumatic injuries. In this review, we discuss the pathophysiology and imaging spectrum of urinary bladder and urethral injuries with an emphasis on the classification schemes. Familiarity with the pelvic anatomy and the injury pattern leads to the prompt diagnosis, accurate classification and appropriate management, which have been associated with better prognosis.
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http://dx.doi.org/10.1007/s00261-020-02679-0DOI Listing
February 2021

Imaging of Renal Cancer.

Semin Ultrasound CT MR 2020 Apr 10;41(2):152-169. Epub 2019 Dec 10.

Mayo Clinic, Rochester, MN. Electronic address:

Renal masses are common incidental findings on cross-sectional imaging. Accurate characterization of renal masses is essential to guide management. Renal mass CT protocol comprises of a good quality noncontrast, corticomedullary and nephrographic phases, with each phase providing complementary information for diagnosis. Attenuation measurements in different phases are central to the 'golden-rules' in renal mass imaging in the characterization of renal masses. Newer modalities like dual energy CT scan obviate need for repeat imaging by generation of iodine-overlay image and also help in eliminating artifactual pseudoenhancement which can be problematic, especially in small endophytic cysts. Contrast- enhanced ultrasound (CEUS) is extremely sensitive in identification of enhancing components in indeterminate masses, especially in the setting of renal failure as the microbubbles are not excreted via the renal route. The Bosniak classification for renal cystic masses has been revised in 2019 to standardize terminology and further improve upon the original version. The current version includes CT and MRI, although CEUS is yet to be included. Image- guided biopsy of renal mass helps confirm the diagnosis and also gives information regarding the subtype and grading and is useful in avoiding overtreatment of benign entities, and in active surveillance. Multiparametric MRI can potentially help avoid needle biopsy in a subset of patients by accurate characterization through a previously validated algorithm.
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http://dx.doi.org/10.1053/j.sult.2019.12.004DOI Listing
April 2020

Imaging and Management of Liver Cancer.

Semin Ultrasound CT MR 2020 Apr 14;41(2):122-138. Epub 2019 Dec 14.

University of Toronto, University of Ottawa, Ottawa, Canada. Electronic address:

Imaging of primary hepatic neoplasms in patients at risk for hepatocellular carcinoma (HCC) and in patients with otherwise normal livers relies on proper multiphase image acquisition technique, with emphasis on a high-quality, late arterial phase, using either CT or MRI for accurate image interpretation. The introduction of liver imaging reporting and data system in 2011, with subsequent multiple updates, the most recent in 2018, has provided standardization of image interpretation, reporting and management recommendations for liver observations in patients at risk for HCC. This review article will emphasize key points of imaging primary liver tumors with emphasis on liver imaging reporting and data system, including strengths of this system. We will also review imaging of less common primary liver tumors such as cholangiocarcinoma and angiosarcomas. Imaging pitfall associated with primary liver malignancies will be demonstrated as well as ways to mitigate them. Finally, imaging and reporting of findings following locoregional treatment of HCC will be reviewed.
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http://dx.doi.org/10.1053/j.sult.2019.12.002DOI Listing
April 2020

Quantitative Prostate MRI.

J Magn Reson Imaging 2021 06 15;53(6):1632-1645. Epub 2020 May 15.

Molecular Imaging Program, National Cancer Institute NIH, Bethesda, Maryland, USA.

Prostate MRI is reported in clinical practice using the Prostate Imaging and Data Reporting System (PI-RADS). PI-RADS aims to standardize, as much as possible, the acquisition, interpretation, reporting, and ultimately the performance of prostate MRI. PI-RADS relies upon mainly subjective analysis of MR imaging findings, with very few incorporated quantitative features. The shortcomings of PI-RADS are mainly: low-to-moderate interobserver agreement and modest accuracy for detection of clinically significant tumors in the transition zone. The use of a more quantitative analysis of prostate MR imaging findings is therefore of interest. Quantitative MR imaging features including: tumor size and volume, tumor length of capsular contact, tumor apparent diffusion coefficient (ADC) metrics, tumor T and T relaxation times, tumor shape, and texture analyses have all shown value for improving characterization of observations detected on prostate MRI and for differentiating between tumors by their pathological grade and stage. Quantitative analysis may therefore improve diagnostic accuracy for detection of cancer and could be a noninvasive means to predict patient prognosis and guide management. Since quantitative analysis of prostate MRI is less dependent on an individual users' assessment, it could also improve interobserver agreement. Semi- and fully automated analysis of quantitative (radiomic) MRI features using artificial neural networks represent the next step in quantitative prostate MRI and are now being actively studied. Validation, through high-quality multicenter studies assessing diagnostic accuracy for clinically significant prostate cancer detection, in the domain of quantitative prostate MRI is needed. This article reviews advances in quantitative prostate MRI, highlighting the strengths and limitations of existing and emerging techniques, as well as discussing opportunities and challenges for evaluation of prostate MRI in clinical practice when using quantitative assessment. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 2.
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http://dx.doi.org/10.1002/jmri.27191DOI Listing
June 2021

Automated classification of solid renal masses on contrast-enhanced computed tomography images using convolutional neural network with decision fusion.

Eur Radiol 2020 Sep 29;30(9):5183-5190. Epub 2020 Apr 29.

School of Engineering, University of Guelph, Guelph, ON, Canada.

Objectives: To develop a deep learning-based method for automated classification of renal cell carcinoma (RCC) from benign solid renal masses using contrast-enhanced computed tomography (CECT) images.

Methods: This institutional review board-approved retrospective study evaluated CECT in 315 patients with 77 benign (57 oncocytomas, and 20 fat-poor angiomyolipoma) and 238 malignant (RCC: 123 clear cell, 69 papillary, and 46 chromophobe subtypes) tumors identified consecutively between 2015 and 2017. We employed a decision fusion-based model to aggregate slice level predictions determined by convolutional neural network (CNN) via a majority voting system to evaluate renal masses on CECT. The CNN-based model was trained using 7023 slices with renal masses manually extracted from CECT images of 155 patients, cropped automatically around kidneys, and augmented artificially. We also examined the fully automated approach for renal mass evaluation on CECT. Moreover, a 3D CNN was trained and tested using the same datasets and the obtained results were compared with those acquired from slice-wise algorithms.

Results: For differentiation of RCC versus benign solid masses, the semi-automated majority voting-based CNN algorithm achieved accuracy, precision, and recall of 83.75%, 89.05%, and 91.73% using 160 test cases, respectively. Fully automated pipeline yielded accuracy, precision, and recall of 77.36%, 85.92%, and 87.22% on the same test cases, respectively. 3D CNN reported accuracy, precision, and recall of 79.24%, 90.32%, and 84.21% using 160 test cases, respectively.

Conclusions: A semi-automated majority voting CNN-based methodology enabled accurate classification of RCC from benign neoplasms among solid renal masses on CECT.

Key Points: • Our proposed semi-automated majority voting CNN-based algorithm achieved accuracy of 83.75% for the diagnosis of RCC from benign solid renal masses on CECT images. • A fully automated CNN-based methodology classified solid renal masses with moderate accuracy of 77.36% using the same test images. • Employing 3D CNN-based methodology yielded slightly lower accuracy for renal mass classification compared with the semi- automated 2D CNN-based algorithm (79.24%).
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http://dx.doi.org/10.1007/s00330-020-06787-9DOI Listing
September 2020

Fournier gangrene: pictorial review.

Abdom Radiol (NY) 2020 11;45(11):3838-3848

Department of Medical Imaging, The Ottawa Hospital, Ottawa, Ontario, Canada.

Fournier gangrene is an emergency condition that is associated with a high mortality rate. It is defined as a rapidly progressing infective necrotizing fasciitis of the perineal, perianal, and genital regions. Early diagnosis, broad-spectrum antibiotic coverage, and adequate surgical debridement are crucial and lead to better prognosis and patient survival. There is increasing utilization of computed tomography (CT) in the initial evaluation of Fournier gangrene. CT can confirm the diagnosis in equivocal cases, determine the source of infection, and evaluate the disease extent. In this pictorial review, we discuss the pathogenesis of Fournier gangrene and display the imaging spectrum with an emphasis on CT findings, including asymmetrical fascial thickening, soft tissue stranding, soft tissue gas, collection, and abscess formation. The infection originating from colorectal pathology, the affected anatomy, and the involvement of the abdominal wall are important predictors of mortality. The familiarity of the varied imaging appearance of Fournier gangrene is necessary to provide an accurate diagnosis, and evaluation of disease extent is crucial for optimal surgical debridement.
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http://dx.doi.org/10.1007/s00261-020-02549-9DOI Listing
November 2020

Clinicians and surgeon survey regarding current and future versions of CT/MRI LI-RADS.

Abdom Radiol (NY) 2020 08;45(8):2603-2611

Joint Department of Medical Imaging, University of Toronto, Ontario, Canada.

Purpose: To determine preferences of clinicians and surgeons regarding radiology reporting of liver observations in patients at risk for hepatocellular carcinoma (HCC).

Methods: Members of the American College of Radiology Liver Imaging and Data Reporting System (LI-RADS) Outreach & Education Group (30 members) as well as Society of Abdominal Radiology Disease-Focused Panel on HCC diagnosis (27 members) created and distributed an 18-question survey to clinicians and surgeons, with focus on preferences regarding radiology reporting of liver observations in patients. The survey questions were directed to physician demographics, current use of LI-RADS by their local radiologists, their opinions about current LI-RADS and potential improvements.

Results: A total of 152 physicians responded, 66.4% (101/152) from North America, including 42 surgeons, 81 physicians and 29 interventional radiologists. Participants were predominantly from academic centers 83% (126/152), while 13.8% (21/152) worked in private/community centers and 3.2% (5/152) worked in a hybrid practice. Almost 90% (136/152) of participants preferred the use of LI-RADS (compared to nothing or other standardized reporting systems; OPTN and AASLD) to communicate liver-related observations. However, only 28.5% (43/152) of participants input was sought at the time of implementing LI-RADS in their institutions. Fifty-eight percent (88/152) of all participants found standardized LI-RADS management recommendations in radiology reports to be clinically helpful. However, a subgroup analysis of surgeons in academic centers showed that 61.8% (21/34) prefer not to receive standardized LI-RADS recommendations.

Conclusions: Most participants preferred the use LI-RADS in reporting CT and MRI examination. When considering inclusion of management recommendations, radiologists should consult with their referring physicians, as preference may differ.
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http://dx.doi.org/10.1007/s00261-020-02544-0DOI Listing
August 2020

Ensemble U-net-based method for fully automated detection and segmentation of renal masses on computed tomography images.

Med Phys 2020 Sep 28;47(9):4032-4044. Epub 2020 Jul 28.

School of Engineering, University of Guelph, Guelph, ON, Canada.

Purpose: Detection and accurate localization of renal masses (RM) are important steps toward future potential classification of benign vs malignant RM. A fully automated algorithm for detection and localization of RM may eliminate the observer variability in the clinical workflow.

Method: In this paper, we describe a fully automated methodology for accurate detection and segmentation of RM from contrast-enhanced computed tomography (CECT) images. We first determine the boundaries of the kidneys on the CECT images utilizing a convolutional neural network-based method to be used as a region of interest to search for RM. We then employ a homogenous U-Net-based ensemble learning model to identify and delineate RM. We used an institutional dataset comprised of CECT images in 315 patients to train and evaluate the proposed method. We compared results of our method to those of three-dimensional (3D) U-Net for RM localization and further evaluated our algorithm using the kidney tumor segmentation (KiTS19) challenge dataset.

Results: The developed algorithm reported a Dice similarity coefficient (DSC) of 95.79% ± 5.16% and 96.25 ± 3.37 (mean ± standard deviation) for segmentation accuracy of kidney boundary from 125 and 60 test images from institutional and KiTS19 datasets, respectively. Using our method, RM were detected in 125 and 52 test cases, which corresponds to 100% and 86.67% sensitivity at patient level in institutional and KiTS19 test images. Our ensemble method for RM localization yielded a mean DSC of 88.65% ± 7.31% and 87.91% ± 6.82% on the institutional and KiTS19 test datasets, respectively. The mean DSC for RM delineation from CECT institutional test images using 3D U-Net was 85.95% ± 1.46%.

Conclusion: We describe a method for automated localization of RM using CECT images. Our results are important in terms of clinical perspective as fully automated detection of RM is a fundamental step for further diagnosis of cystic vs solid RM and eventually benign vs malignant solid RM, that has not been reported previously.
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http://dx.doi.org/10.1002/mp.14193DOI Listing
September 2020

Editorial for "Quantitative MRCP Imaging: Accuracy, Repeatability, Reproducibility, and Cohort-Derived Normative Ranges.

J Magn Reson Imaging 2020 09 2;52(3):821-822. Epub 2020 Mar 2.

Department of Medical Imaging, The Ottawa Hospital Clinical Epidemiology Program, OHRI Professor of Radiology and Epidemiology, University of Ottawa, Ottawa, Ontario, Canada.

Level Of Evidence: 5.

Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;52:821-822.
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http://dx.doi.org/10.1002/jmri.27110DOI Listing
September 2020

Multidetector Computed Tomography in Traumatic and Nontraumatic Aortic Emergencies: Emphasis on Acute Aortic Syndromes.

Can Assoc Radiol J 2020 Aug 28;71(3):322-334. Epub 2020 Feb 28.

Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, Ontario, Canada.

Aortic emergencies comprise of a list of conditions which are uncommon but are potentially fatal. Prognosis is usually determined by emergent diagnosis and treatment and hence radiology plays a key role in patient management. In this article, we aim to review the various causes of aortic emergencies and the relevant imaging findings placing special emphasis on acute aortic syndromes.
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http://dx.doi.org/10.1177/0846537120902069DOI Listing
August 2020

Role of MRI in Staging of Penile Cancer.

J Magn Reson Imaging 2020 06 24;51(6):1612-1629. Epub 2020 Jan 24.

Department of Diagnostic Imaging, Sao Paulo, Hospital Israelita Albert Einstein, São Paulo, Brazil.

Penile cancer is one of the male-specific cancers. Accurate pretreatment staging is crucial due to a plethora of treatment options currently available. The 8 edition American Joint Committee on Cancer-Tumor Node and Metastasis (AJCC-TNM) revised the staging for penile cancers, with invasion of corpora cavernosa upstaged from T2 to T3 and invasion of urethra downstaged from T3 to being not separately relevant. With this revision, MRI is more relevant in local staging because MRI is accurate in identifying invasion of corpora cavernosa, while the accuracy is lower for detection of urethral involvement. The recent European Urology Association (EAU) guidelines recommend MRI to exclude invasion of the corpora cavernosa, especially if penis preservation is planned. Identification of satellite lesions and measurement of residual-penile-length help in surgical planning. When nonsurgical treatment modalities of the primary tumor are being considered, accurate local staging helps in decision-making regarding upfront inguinal lymph node dissection as against surveillance. MRI helps in detection and extent of inguinal and pelvic lymphadenopathy and is superior to clinical palpation, which continues to be the current approach recommended by National Comprehensive Cancer Network (NCCN) treatment guidelines. MRI helps the detection of "bulky" lymph nodes that warrant neoadjuvant chemotherapy and potentially identify extranodal extension. However, tumor involvement in small lymph nodes and differentiation of reactive vs. malignant lymphadenopathy in large lymph nodes continue to be challenging and the utilization of alternative contrast agents (superparamagnetic iron oxide), positron emission tomography (PET)-MRI along with texture analysis is promising. In locally recurrent tumors, MRI is invaluable in identification of deep invasion, which forms the basis of treatment. Multiparametric MRI, especially diffusion-weighted-imaging, may allow for quantitative noninvasive assessment of tumor grade and histologic subtyping to avoid biopsy undersampling. Further research is required for incorporation of MRI with deep learning and artificial intelligence algorithms for effective staging in penile cancer. Level of Evidence: 5 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2020;51:1612-1629.
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http://dx.doi.org/10.1002/jmri.27060DOI Listing
June 2020

Characterization of clear cell renal cell carcinoma and other renal tumors: evaluation of dual-energy CT using material-specific iodine and fat imaging.

Eur Radiol 2020 Apr 19;30(4):2091-2102. Epub 2019 Dec 19.

Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, 1053 Carling Avenue, Ottawa, ON, K1Y 4E9, Canada.

Objective: This study aimed to assess material-specific iodine and fat images for diagnosis of clear cell renal cell carcinoma (cc-RCC) compared to papillary RCC (p-RCC) and other renal masses.

Materials And Methods: With IRB approval, we identified histologically confirmed solid renal masses that underwent rapid-kVp-switch DECT between 2016 and 2018: 25 cc-RCC (7 low grade versus 18 high grade), 11 p-RCC, and 6 other tumors (2 clear cell papillary RCC, 2 chromophobe RCC, 1 oncocytoma, 1 renal angiomyomatous tumor). A blinded radiologist measured iodine and fat concentration on material-specific iodine-water and fat-water basis pair images. Comparisons were performed between groups using univariate analysis and diagnostic accuracy calculated by ROC.

Results: Iodine concentration was higher in cc-RCC (6.14 ± 1.79 mg/mL) compared to p-RCC (1.40 ± 0.54 mg/mL, p < 0.001), but not compared to other tumors (5.0 ± 2.2 mg/mL, p = 0.370). Intratumoral fat was seen in 36.0% (9/25) cc-RCC (309.6 ± 234.3 mg/mL [71.1-762.3 ng/mL]), 9.1% (1/11) papillary RCC (97.11 mg/mL), and no other tumors (p = 0.036). Iodine concentration ≥ 3.99 mg/mL achieved AUC and sensitivity/specificity of 0.88 (CI 0.76-1.00) and 92.31%/82.40% to diagnose cc-RCC. To diagnose p-RCC, iodine concentration ≤ 2.5 mg/mL achieved AUC and sensitivity/specificity of 0.99 (0.98-1.00) and 100%/100%. The presence of intratumoral fat had AUC 0.64 (CI 0.53-0.75) and sensitivity/specificity of 34.6%/93.8% to diagnose cc-RCC. A logistic regression model combining iodine concentration and presence of fat increased AUC to 0.91 (CI 0.81-1.0) with sensitivity/specificity of 80.8%/93.8% to diagnose cc-RCC.

Conclusion: Iodine concentration values are highly accurate to differentiate clear cell RCC from papillary RCC; however, they overlap with other tumors. Fat-specific images may improve differentiation of clear cell RCC from other avidly enhancing tumors.

Key Points: • Clear cell renal cell carcinoma (RCC) has significantly higher iodine concentration than papillary RCC, but there is an overlap in values comparing clear cell RCC to other renal tumors. • Iodine concentration ≤ 2.5 mg/mL is highly accurate to differentiate papillary RCC from clear cell RCC and other renal tumors. • The presence of microscopic fat on material-specific fat images was specific for clear cell RCC, helping to differentiate clear cell RCC from other avidly enhancing renal tumors.
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http://dx.doi.org/10.1007/s00330-019-06590-1DOI Listing
April 2020

Imaging Manifestations of Acute and Chronic Renal Infection That Mimics Malignancy: How to Make the Diagnosis Using Computed Tomography and Magnetic Resonance Imaging.

Can Assoc Radiol J 2019 Nov 17;70(4):424-433. Epub 2019 Sep 17.

Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, Ottawa, Ontario, Canada. Electronic address:

Purpose: To review the computed tomography and magnetic resonance imaging manifestations of acute and chronic renal infections that may mimic malignancy and to provide useful tips to establish an imaging diagnosis.

Conclusion: Acute and chronic bacterial pyelonephritis are usually readily diagnosed clinically and on imaging when the diagnosis is suspected based upon clinical presentation. When unsuspected, focal, extensive or mass-like, acute and chronic bacterial pyelonephritis may mimic infiltrative tumours such as urothelial cell carcinoma (UCC), lymphoma, and metastatic disease. Infection may be suspected when patients are young and otherwise healthy when there is marked associated perinephric changes and in the absence of metastatic adenopathy or disease elsewhere in the abdomen and pelvis. Renal abscesses, from bacterial or atypical microbial agents, can appear as complex cystic renal masses mimicking cystic renal cell carcinoma. Associated inflammatory changes in and around the kidney and local invasion favour infection. Emphysematous pyelonephritis can mimic necrotic or fistulizing tumour; however, infection is more likely and should always be considered first. Xanthogranulomatous pyelonephritis can mimic malignancy when focal or multifocal and in cases without associated renal calculi. Malacoplakia is an inflammatory process that may mimic malignancy and should be considered in patients with chronic infection. Bacillus Calmette-Guerin (BCG)-induced pyelonephritis is rare but can mimic renal malignancy and should be considered in patients presenting with a renal mass when being treated with BCG for urinary bladder UCC.
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http://dx.doi.org/10.1016/j.carj.2019.07.002DOI Listing
November 2019

Fully automated localization of prostate peripheral zone tumors on apparent diffusion coefficient map MR images using an ensemble learning method.

J Magn Reson Imaging 2020 04 28;51(4):1223-1234. Epub 2019 Aug 28.

Department of Radiology, University of Ottawa, Ottawa, Ontario, Canada.

Background: Accurate detection and localization of prostate cancer (PCa) in men undergoing prostate MRI is a fundamental step for future targeted prostate biopsies and treatment planning. Fully automated localization of peripheral zone (PZ) PCa using the apparent diffusion coefficient (ADC) map might be clinically useful.

Purpose/hypothesis: To describe automated localization of PCa in the PZ on ADC map MR images using an ensemble U-Net-based model.

Study Type: Retrospective, case-control.

Population: In all, 226 patients (154 and 72 patients with and without clinically significant PZ PCa, respectively), training, and testing was performed using dataset images of 146 and 80 patients, respectively.

Field Strength: 3T, ADC maps.

Sequence: ADC map.

Assessment: The ground truth was established by manual delineation of the prostate and prostate PZ tumors on ADC maps by dedicated radiologists using MRI-radical prostatectomy maps as a reference standard. Statistical Tests: Performance of the ensemble model was evaluated using Dice similarity coefficient (DSC), sensitivity, and specificity metrics on a per-slice basis. Receiver operating characteristic (ROC) curve and area under the curve (AUC) were employed as well. The paired t-test was used to test the differences between the performances of constituent networks of the ensemble model.

Results: Our developed algorithm yielded DSC, sensitivity, and specificity of 86.72% ± 9.93%, 85.76% ± 23.33%, and 76.44% ± 23.70%, respectively (mean ± standard deviation) on 80 test cases consisting of 41 and 39 instances from patients with and without clinically significant tumors including 660 extracted 2D slices. AUC was reported as 0.779.

Data Conclusion: An ensemble U-Net-based approach can accurately detect and segment PCa in the PZ from ADC map MR prostate images.

Level Of Evidence: 4 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2020;51:1223-1234.
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http://dx.doi.org/10.1002/jmri.26913DOI Listing
April 2020

Diagnostic Accuracy of Attenuation Difference and Iodine Concentration Thresholds at Rapid-Kilovoltage-Switching Dual-Energy CT for Detection of Enhancement in Renal Masses.

AJR Am J Roentgenol 2019 09 23;213(3):619-625. Epub 2019 May 23.

Department of Medical Imaging, The Ottawa Hospital, The University of Ottawa, 1053 Carling Ave, Ottawa, ON K1Y 4E9, Canada.

The objective of our study was to evaluate iodine concentration and attenuation change in Hounsfield unit (ΔHU) thresholds to diagnose enhancement in renal masses at rapid-kilovoltage-switching dual-energy CT (DECT). We evaluated 30 consecutive histologically confirmed solid renal masses (including nine papillary renal cell carcinomas [RCCs]) and 27 benign cysts (17 simple and 10 hemorrhagic or proteinaceous cysts) with DECT December 2016 and May 2018. A blinded radiologist measured iodine concentration (in milligrams per milliliter) and ΔHU (attenuation on enhanced CT - attenuation on unenhanced CT) using 70-keV corticomedullary (CM) phase virtual monochromatic and 120-kVp nephrographic (NG) phase images. The accuracies of previously described enhancement thresholds were compared by ROC curve analysis. An iodine concentration of ≥ 2.0 mg/mL and an iodine concentration of ≥ 1.2 mg/mL achieved sensitivity, specificity, and the area under the ROC curve (AUC) of 73.3%, 100.0%, and 0.87 and 86.7%, 100.0%, and 0.93, respectively. On 70-keV CM phase images, ΔHU ≥ 20 HU and ΔHU ≥ 15 HU yielded sensitivity, specificity, and AUC of 80.0%, 100.0%, and 0.90 and 90.0%, 100.0%, and 0.95, respectively. The numbers of incorrectly classified papillary RCCs were as follows: iodine concentration of ≥ 2.0 mg/mL, 77.8% (7/9; range, 0.7-1.6 mg/mL); iodine concentration of ≥ 1.2 mg/mL, 44.4% (4/9; range, 0.7-0.9 mg/mL); ΔHU ≥ 20 HU on 70-keV CM phase images, 66.7% (6/9; range, 4-17 HU); and ΔHU ≥ 15 HU on 70-keV DECT images, 33.3% (3/9; 4-12 HU). No cyst pseudoenhancement occurred on DECT. For 120-kVp NG phase DECT, ΔHU ≥ 20 HU and ΔHU ≥ 15 HU yielded sensitivity, specificity, and AUC of 93.3%, 96.3%, and 0.95 and 100.0%, 88.9%, and 0.94, respectively. With ΔHU ≥ 20 HU, 22.2% (2/9) (range, 15-18 HU) of papillary RCCs were misclassified and there was one pseudoenhancing cyst. With ΔHU ≥ 15 HU, no papillary RCCs were misclassified but 11.1% (3/27) of cysts showed pseudoenhancement. Only an iodine concentration of ≥ 2.0 mg/mL showed significantly lower accuracy than other measures ( = 0.031-0.045). DECT applied in the CM phase performed best using an iodine concentration of ≥ 1.2 mg/mL or a 70-keV ΔHU ≥ 15 HU; these parameters improved sensitivity for the detection of enhancement in renal masses without instances of cyst pseudoenhancement.
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http://dx.doi.org/10.2214/AJR.18.20990DOI Listing
September 2019

Dynamic Contrast-Enhanced MRI-Upgraded Prostate Imaging Reporting and Data System Version 2 Category 3 Peripheral Zone Observations Stratified by a Size Threshold of 15 mm.

AJR Am J Roentgenol 2019 10 23;213(4):836-843. Epub 2019 May 23.

Department of Medical Imaging, The Ottawa Hospital, 1053 Carling Ave, Rm C159, Ottawa, ON K1Y 4E9, Canada.

The purpose of this study is to evaluate dynamic contrast-enhanced (DCE) MRI (DCE-MRI)-upgraded Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) peripheral zone (PZ) observations stratified by a size threshold of 15 mm. Two blinded radiologists independently assessed 301 patients with 326 clinically significant tumors (Gleason score [GS] ≥ 7) using multiparametric MRI performed before radical prostatectomy (RP) between 2012 and 2017 and then assigned PI-RADSv2 scores for the tumors. PI-RADSv2 category 3 PZ observations upgraded on the basis of abnormal DCE-MRI findings were tabulated, agreement was calculated, and discrepancies were resolved by consensus. The rate of detection of clinically significant cancer among upgraded observations was calculated. Size was measured at consensus review and was compared with pathologic outcomes on the basis of the PI-RADSv2 size threshold of 15 mm or more, with the use of chi-square tests. Reader 1 identified 5.2% (17/326) of DCE-MRI-upgraded PZ observations, and reader 2 identified 8.3% (27/326) of such observations. Interobserver agreement for PI-RADSv2 scoring was moderate (κ = 0.42) overall, but it was fair (κ = 0.23) when only DCE-MRI-upgraded observations were considered. Of the upgraded observations, which had a mean (± SD) size of 14 ± 6 mm (range, 6-29 mm), 10.4% (34/326) were agreed on after consensus review. Size smaller than 15 mm was noted for 61.8% (21/34) of observations. Among DCE-MRI-upgraded PZ observations, true- and false-positive detection rates for significant cancer were 91.2% (31/34) and 8.8% (3/34), respectively. Observations 15 mm or larger had no false-positive diagnoses and higher rates of extraprostatic extension (84.6% [11/13] vs 38.1% [8/21]; = 0.016); however, there was no difference in GS ( = 0.354) compared with observations less than 15 mm in size. PZ observations upgraded on the basis of abnormal DCE-MRI findings have a high likelihood of being clinically significant cancer; however, agreement between readers was low. DCE-MRI-upgraded tumors of 15 mm or larger had no false-positive diagnoses and higher rates of extraprostatic extension, suggesting that they could be assigned to PI-RADSv2 assessment category 5.
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http://dx.doi.org/10.2214/AJR.18.21005DOI Listing
October 2019

Can MRI be used to diagnose histologic grade in T1a (< 4 cm) clear cell renal cell carcinomas?

Abdom Radiol (NY) 2019 08;44(8):2841-2851

Department of Medical Imaging, The Ottawa Hospital, Ottawa, ON, Canada.

Objective: To assess whether MRI can differentiate low-grade from high-grade T1a cc-RCC.

Materials And Methods: With IRB approval, 49 consecutive solid < 4 cm cc-RCC (low grade [Grade 1 or 2] N = 38, high grade [Grade 3] N = 11) with pre-operative MRI before nephrectomy were identified between 2013 and 2018. Tumor size, apparent diffusion coefficient (ADC) histogram analysis, enhancement wash-in and wash-out rates, and chemical shift signal intensity index (SI index) were assessed by a blinded radiologist. Subjectively, two blinded Radiologists also assessed for (1) microscopic fat, (2) homogeneity (5-point Likert scale), and (3) ADC signal (relative to renal cortex); discrepancies were resolved by consensus. Outcomes were studied using Chi square, multivariate analysis, logistic regression modeling, and ROC. Inter-observer agreement was assessed using Cohen's kappa.

Results: Tumor size was 24 ± 7 (13-39) mm with no association to grade (p = 0.45). Among quantitative features studied, corticomedullary phase wash-in index (p = 0.015), SI index (p = 0.137), and tenth-centile ADC (p = 0.049) were higher in low-grade tumors. 36.8% (14/38) low-grade tumors versus zero high-grade tumors demonstrated microscopic fat (p = 0.015; Kappa = 0.67). Microscopic fat was specific for low-grade disease (100.0% [71.5-100.0]) with low sensitivity (36.8% [21.8-54.6]). Other subjective features did not differ between groups (p > 0.05). A logistic regression model combining microscopic fat + wash-in index + tenth-centile-ADC yielded area under ROC curve 0.98 (Confidence Intervals 0.94-1.0) with sensitivity/specificity 87.5%/100%.

Conclusion: The combination of microscopic fat, higher corticomedullary phase wash-in and higher tenth-centile ADC is highly accurate for diagnosis of low-grade disease among T1a clear cell RCC.
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http://dx.doi.org/10.1007/s00261-019-02018-yDOI Listing
August 2019

Update on Gadolinium-Based Contrast Agent-Enhanced Imaging in the Genitourinary System.

AJR Am J Roentgenol 2019 Apr 11:1-11. Epub 2019 Apr 11.

3 Department of Radiology, The University of Michigan, Ann Arbor, MI.

Objective: The purpose of this article is to review gadolinium-based contrast agent (GBCA)-enhanced MRI applications in the genitourinary system.

Conclusion: Nephrogenic systemic fibrosis is rare or nonexistent with standard dosing of group II GBCAs. Gadolinium retention, cost, and examination times are emerging considerations affecting GBCA use. GBCA is unnecessary to diagnose adrenal adenomas, simple cysts, and some Bosniak category II cysts; however, it is required to determine solid or septal renal mass enhancement. Biparametric prostate MRI requires high-quality and reproducible DWI; therefore, dynamic contrast-enhanced MRI remains valuable in selected prostate MRI examinations.
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http://dx.doi.org/10.2214/AJR.19.21137DOI Listing
April 2019

Transition zone prostate cancer: Logistic regression and machine-learning models of quantitative ADC, shape and texture features are highly accurate for diagnosis.

J Magn Reson Imaging 2019 09 30;50(3):940-950. Epub 2019 Jan 30.

Department of Medical Imaging, Ottawa Hospital, University of Ottawa, Ontario, Canada.

Background: The limitation of diagnosis of transition zone (TZ) prostate cancer (PCa) using subjective assessment of multiparametric (mp) MRI with PI-RADS v2 is related to overlapping features between cancers and stromal benign prostatic hyperplasia (BPH) nodules, particularly in small lesions.

Purpose: To evaluate modeling of quantitative apparent diffusion coefficient (ADC), texture, and shape features using logistic regression (LR) and support vector machine (SVM) models for the diagnosis of transition zone PCa.

Study Type: Retrospective.

Population: Ninety patients; 44 consecutive TZ PCa were compared with 61 consecutive BPH nodules (26 glandular/35 stromal).

Field Strength/sequence: 3 T/T -weighted (T W) fast spin-echo, diffusion weighted imaging.

Assessment: A radiologist manually segmented lesions on axial images for quantitative ADC (mean, 10 , 25 -centile-ADC), T W-shape (circularity, convexity) and T W-texture (kurtosis, skewness, entropy, run-length nonuniformity [RLNU], gray-level nonuniformity [GLNU]) analysis. A second radiologist segmented one-fifth of randomly selected lesions to determine the reproducibility of measurements. The reference standard was histopathology for all lesions.

Statistical Tests: Quantitative features were selected a priori and were compared using univariate and multivariate analysis. LR and SVM models of statistically significant features were constructed and evaluated using receiver operator characteristic (ROC) analysis. Subgroup analysis of TZ PCa vs. only stromal BPH and in lesions measuring <15 mm was performed. Agreement in measurements was assessed using the Dice similarity coefficient (DSC).

Results: Mean, 25 and 10 -centile ADC, circularity, and texture (entropy, RLNU, GLNU) features differed between groups (P < 0.0001-0.0058); however, at multivariate analysis only circularity and ADC metrics (P < 0.001) remained significant. LR and SVM models were highly accurate for the diagnosis of TZ PCa (sensitivity/specificity/AUC): 93.2%/98.4%/0.989 and 93.2%/96.7%/0.949, respectively, with no significance difference between the LR and SVM models (P = 0.2271). Reproducibility of segmentation was excellent (DSC 0.84 tumors and 0.87 BPH). Subgroup analyses of TZ PCa vs. stromal BPH (AUC = 0.976) and in <15 mm lesions (AUC = 0.990) remained highly accurate.

Data Conclusion: LR and SVM models incorporating previously described quantitative ADC, shape and texture analysis features are highly accurate for the diagnosis of TZ PCa and remained accurate when comparing TZ PCa with stromal BPH and in smaller lesions.

Level Of Evidence: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:940-950.
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http://dx.doi.org/10.1002/jmri.26674DOI Listing
September 2019

Diagnostic Accuracy of MRI for Detecting Inferior Vena Cava Wall Invasion in Renal Cell Carcinoma Tumor Thrombus Using Quantitative and Subjective Analysis.

AJR Am J Roentgenol 2019 03 27;212(3):562-569. Epub 2018 Dec 27.

1 Department of Medical Imaging, The Ottawa Hospital, 1053 Carling Ave, Rm C159, Ottawa, ON K1Y 4E9, Canada.

Objective: The purpose of this study is to evaluate MRI in inferior vena cava (IVC) renal cell carcinoma (RCC) tumor thrombus for the diagnosis of caval wall invasion.

Materials And Methods: This retrospective case-control study evaluated 24 consecutive patients who underwent thrombectomy for RCC IVC tumor thrombus (11 [45.8%] with invasion) seen at preoperative MRI. A blinded radiologist segmented tumor thrombus on apparent diffusion coefficient (ADC) maps and T2-weighted images for texture analysis, measured the diameter of the renal vein and IVC at the level of the renal vein ostium, and measured the craniocaudal extent and volume of the tumor thrombus. Two blinded radiologists independently evaluated the margin of the tumor thrombus (smooth vs irregular), thinning or thickening and abnormal T2-weighted signal or enhancement of the IVC wall, and overall impression of invasion. Comparisons were performed using logistic regression models and chi-square with accuracy calculated using ROC.

Results: Subjective features were associated with invasion (p = 0.001-0.045) with moderate-to-substantial agreement (κ = 0.49-0.66). The overall impression of invasion had a sensitivity of 63.6% (95% CI, 30.8-89.1%) and a specificity of 92.3% (95% CI, 64.0-99.8%) with perfect agreement (κ = 1.0). Tumor thrombus with invasion had larger diameters of renal vein (28 ± 8 vs 15 ± 6 mm; p = 0.031) and IVC (41 ± 9 vs 19 ± 6 mm; p = 0.003), greater craniocaudal extent (87 ± 34 vs 51 ± 31 mm; p = 0.0239), and greater volume (77.4 ± 57.6 vs 17.7 ± 17.4 cm; p = 0.003) than did thrombi without invasion. The ROC AUC ranged from 0.78 to 0.83. ADC and texture parameters were not significantly different between groups (p = 0.208-0.503); however, larger entropy in invasive tumor thrombus trended toward significance (p = 0.061). A model combining volume, entropy, and overall impression achieved an AUC of 0.91 (95% CI, 0.77-1.0).

Conclusion: The combination of tumor thrombus volume with entropy and subjective overall impression of IVC wall invasion achieved the highest accuracy for diagnosis.
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http://dx.doi.org/10.2214/AJR.18.20209DOI Listing
March 2019

Intraductal carcinoma of the prostate (IDC-P) lowers apparent diffusion coefficient (ADC) values among intermediate risk prostate cancers.

J Magn Reson Imaging 2019 07 25;50(1):279-287. Epub 2018 Dec 25.

Department of Medical Imaging, Ottawa Hospital, Ottawa, Ontario, Canada.

Background: Prostatic intraductal carcinoma (IDC-P) is an aggressive variant of prostate cancer (PCa) characterized by proliferation of malignant cells within prostatic ducts/acini and nucleomegaly.

Purpose/hypothesis: To compare apparent diffusion coefficient (ADC) values and Prostate Imaging and Data Reporting System (PI-RADS) v. 2 scores in intermediate risk (International Society of Urological Pathology [ISUP] Grade Group [GG] 2 and 3) PCa with/without IDC-P to determine if IDC-P alters the MRI appearance of PCa.

Study Type: Retrospective, case-control.

Population: Fifteen consecutive men with ISUP GG 2/3 (Gleason score 3+4 = 7 [N = 4], 4+3 = 7 [N = 11]) PCa with IDC-P diagnosed at radical prostatectomy were compared with: 1) ISUP GG 2/3 PCa without IDC-P (matched for percentage Gleason pattern 4), and 2) ISUP GG 4 and 5 (Gleason score 8/9) PCa without IDC-P.

Field Strength/sequence: 3T multiparametric MRI.

Assessment: Two blinded radiologists (R1/R2) measured mean ADC, ADC.ratio (ADC.tumor/ADC.normal peripheral zone) and assigned PI-RADS v2 scores. Statistical Tests: Chi-square and analysis of variance (ANOVA).

Results: There were no differences in age, prostate serum antigen, tumor size, or stage between groups (P = 0.063-0.912). Tumors with IDC-P had lower mean ADC and ADC.ratio (0.741 ± 0.152 mm /sec and 0.44 ± 0.07) compared with ISUP GG 2/3 tumors without IDC-P (0.888 ± 0.167 mm /sec and 0.62 ± 0.14), P = 0.012 and <0.001; and did not differ compared with ISUP GG 4/5 tumors (0.705 ± 0.141 mm /sec and 0.44 ± 0.08), P = 0.509 and 0.868. Tumors with IDC-P were nearly all PI-RADS v2 score 5 (14/15) compared with ISUP GG 2/3 tumors without IDC-P (10/15 R1, 8/15 R2) and GG 4/5 tumors (9/15), (P = 0.040 = 0.092). Agreement in PI-RADS v2 scoring was moderate (K = 0.68).

Data Conclusion: ISUP GG 2 and 3 (intermediate risk, Gleason score 7) PCa with IDC-P have lower ADC compared with tumors without IDC-P with a similar percentage of Gleason pattern 4 and resemble ISUP GG 4 and 5 high risk tumors on MRI. IDC-P lowers ADC values among intermediate risk prostate cancers.

Level Of Evidence: 3 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019;50:279-287.
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http://dx.doi.org/10.1002/jmri.26594DOI Listing
July 2019

Encapsulating Peritoneal Sclerosis: The Abdominal Cocoon.

Radiographics 2019 Jan-Feb;39(1):62-77. Epub 2018 Dec 7.

From the Departments of Radiology (M.S., A.L., N.K.), Histopathology (A.B.), General Surgery (T.D.Y.), and Gastroenterology (R.K., S.K.S.), PGIMER, Chandigarh, India; and the Abdominal Imaging Section, Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, Ottawa, Ont, Canada (S.K., S.N., A.M.S.).

Encapsulating peritoneal sclerosis (EPS) is a rare but serious condition that results in (a) encapsulation of bowel within a thickened fibrocollagenous peritoneal membrane and (b) recurrent episodes of bowel obstruction. Although described by various names in the literature, the preferred term is encapsulating peritoneal sclerosis because it best describes the morphologic and histologic changes in this disorder. The etiology of EPS is multifactorial, with a wide variety of implicated predisposing factors that disrupt the normal physiologic function of the peritoneal membrane-prime among these factors being long-term peritoneal dialysis and bacterial peritoneal infections, especially tuberculosis. The clinical features of EPS are usually nonspecific, and knowledge of the radiologic features is necessary to make a specific diagnosis. The findings on radiographs are usually normal. Images from small-bowel follow-through studies show the bowel loops conglomerated in a concertina-like fashion with a serpentine arrangement in a fixed U-shaped configuration. US demonstrates a "cauliflower" appearance of bowel with a narrow base, as well as a "trilaminar" appearance depicted especially with use of high-resolution US probes. CT is the imaging modality of choice and allows identification of the thickened contrast material-enhanced abnormal peritoneal membrane and the encapsulated clumped bowel loops. In addition, CT can potentially help identify the cause of EPS (omental granuloma in tuberculosis), as well as the complications of EPS (bowel obstruction). Conservative medical treatment and surgical therapy early in the course of EPS have been used for management of the condition. The purpose of this article is to review the nomenclature and etiopathogenesis of EPS, describe the multimodality imaging appearances of EPS, including differentiating its features from those of other conditions mimicking EPS, and give an overview of management options. Online DICOM image stacks are available for this article. RSNA, 2018.
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http://dx.doi.org/10.1148/rg.2019180108DOI Listing
March 2020
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