Adrenal Mass Biopsy in Patients Without Extraadrenal Primary Malignancy: A Multicenter Study.

BACKGROUND. Adrenal washout CT is not useful for evaluating incidental adrenal masses in patients without known or suspected primary extraadrenal malignancy. OBJECTIVE. The purpose of our study was to evaluate the diagnostic utility of adrenal mass biopsy in patients without known or suspected extraadrenal primary malignancy. METHODS. This retrospective six-center study included 69 patients (mean age, 56 years; 32 men, 37 women) without known or suspected extraadrenal primary malignancy who underwent image-guided core needle biopsy between January 2004 and June 2021 of a mass suspected to be arising from the adrenal gland. Biopsy results were classified as diagnostic or nondiagnostic. For masses resected after biopsy, histopathologic concordance was assessed between diagnoses from biopsy and resection. Masses were classified as benign or malignant by resection or imaging follow-up, and all nondi-agnostic biopsies were classified as false results. RESULTS. The median mass size was 7.4 cm (range, 1.9-19.2 cm). Adrenal mass biopsy had a diagnostic yield of 64% (44/69; 95% CI, 51-75%). After biopsy, 25 masses were resected, and 44 had imaging follow-up. Of the masses that were resected after diagnostic biopsy, diagnosis was concordant between biopsy and resection in 100% (12/12). Of the 13 masses that were resected after nondiagnostic biopsy, the diagnosis from re-section was benign in eight masses and malignant in five masses. The 44 masses with imaging follow-up included one mass with diagnostic biopsy yielding benign adenoma and two masses with nondiagnostic biopsy results that were classified as malignant by imaging follow-up. Biopsy had overall sensitivity and specificity for malignancy of 73% (22/30) and 54% (21/39), respectively; diagnostic biopsies had sensitivity and specificity for malignancy of 96% (22/23) and 100% (21/21), respectively. Among nine nondi-agnostic biopsies reported as adrenocortical neoplasm, six were classified as malignant by the reference standard (resection showing adrenocortical carcinoma in four, resection showing adrenocortical neoplasm of uncertain malignant potential in one, imaging follow-up consistent with malignancy in one). CONCLUSION. Adrenal mass biopsy had low diagnostic yield, with low sensitivity and low specificity for malignancy. A biopsy result of adrenocortical neoplasm did not reliably differentiate benign and malignant adrenal masses. CLINICAL IMPACT. Biopsy appears to have limited utility for the evaluation of incidental adrenal masses in patients without primary extraadrenal malignancy.

Utility of machine learning of apparent diffusion coefficient (ADC) and T2-weighted (T2W) radiomic features in PI-RADS version 2.1 category 3 lesions to predict prostate cancer diagnosis.

PURPOSE: To evaluate if machine learning (ML) of radiomic features extracted from apparent diffusion coefficient (ADC) and T2-weighted (T2W) MRI can predict prostate cancer (PCa) diagnosis in Prostate Imaging-Reporting and Data System (PI-RADS) version 2.1 category 3 lesions. METHODS: This multi-institutional review board-approved retrospective case-control study evaluated 158 men with 160 PI-RADS category 3 lesions (79 peripheral zone, 81 transition zone) diagnosed at 3-Tesla MRI with histopathology diagnosis by MRI-TRUS-guided targeted biopsy. A blinded radiologist confirmed PI-RADS v2.1 score and segmented lesions on axial T2W and ADC images using 3D Slicer, extracting radiomic features with an open-source software (Pyradiomics). Diagnostic accuracy for (1) any PCa and (2) clinically significant (CS; International Society of Urogenital Pathology Grade Group ≥ 2) PCa was assessed using XGBoost with tenfold cross -validation. RESULTS: From 160 PI-RADS 3 lesions, there were 50.0% (80/160) PCa, including 36.3% (29/80) CS-PCa (63.8% [51/80] ISUP 1, 23.8% [19/80] ISUP 2, 8.8% [7/80] ISUP 3, 3.8% [3/80] ISUP 4). The remaining 50.0% (80/160) lesions were benign. ML of all radiomic features from T2W and ADC achieved area under receiver operating characteristic curve (AUC) for diagnosis of (1) CS-PCa 0.547 (95% Confidence Intervals 0.510-0.584) for T2W and 0.684 (CI 0.652-0.715) for ADC and (2) any PCa 0.608 (CI 0.579-0.636) for T2W and 0.642 (CI 0.614-0.0.670) for ADC. CONCLUSION: Our results indicate ML of radiomic features extracted from T2W and ADC achieved at best moderate accuracy for determining which PI-RADS category 3 lesions represent PCa.

Prevalence of prostate cancer in PI-RADS version 2.1 T2-weighted transition zone 'nodule in nodule' and 'homogeneous mildly hypointense area between nodules' criteria: MRI-radical prostatectomy histopathological evaluation.

OBJECTIVES: To evaluate the prevalence of prostate cancer (PCa) of two PI-RADS version (v) 2.1 transition zone (TZ) features (PI-RADS 1 ['nodule in nodule'] and 2 ['homogeneous mildly hypointense area between nodules']). METHODS: With an institutional review board approval, from a 5-year cohort between 2012 and 2017, we retrospectively identified 53 consecutive men with radical prostatectomy (RP) confirmed TZ tumors and MRI. Three blinded radiologists (R1/2/3) independently evaluated T2-weighted and diffusion-weighted imaging (DWI) using PI-RADS v2.1 for the presence of (1) 'nodule in nodule' (recording 'cystic change', inner nodule encapsulation, size, and DWI score) and (2) 'homogeneous mildly hypointense area between nodules' (also recording size and DWI score). MRI-RP maps established ground truth. Primary tumor was evaluated assessing PI-RADS v2.1 category, size, and presence of imaging variants. RESULTS: R1/2/3 identified 26/18/22 'nodule in nodule' respectively with 7.7% (2/26; 95% confidence interval [95% CI]: 0.1-17.9%), 5.6% (1/18; 95% CI: 0.01-16.1%), and 4.5% (1/22; 95% CI: 0.01-13.3%) PCa (both Gleason score 3 + 4 = 7). Agreement was fair-to-substantial, kappa = 0.222-0.696. 'Cystic change', inner nodule absent/incomplete encapsulation and DWI score ≥ 4 for R1/R2/R2 were present in 80.8% (21/26), 46.2% (12/26), 7.7% (2/26); 94.4% (17/18), 33.3% (6/18), 5.6% (1/18); and 59.1% (13/22), 63.6% (14/22), 9.1% (2/22). Both PCa had inner nodule absent/incomplete encapsulation and DWI score ≥ 4. No other TZ tumors demonstrated 'nodule in nodule', nodule 'cystic change', or 'homogeneous mildly hypointense area between nodules'. R1/2/3 identified 5/6/13 'homogeneous mildly hypointense area between nodules' with zero PCa for any reader (upper bound 95% CI: 24.7-52.2%). Interobserver agreement was fair-to-substantial, kappa = 0.104-0.779. CONCLUSION: The proportion of cancers in PI-RADS v2.1 'nodule in nodule' was low (~5-8%) with zero cancers detected in 'homogeneous mildly hypointense area between nodules'. When 'nodule in nodule' inner nodule shows absent or incomplete encapsulation with marked restricted diffusion, PCa may be considered; however, this warrants further studies. KEY POINTS: • The prevalence of clinically significant prostate cancers in PI-RADS v2.1 'nodule in nodule' was low (5-8%, 95% CI: 0.1-17.9%). • Clinically significant prostate cancer was only detected in the 'nodule in nodule' variant when the inner nodule showed absent or incomplete encapsulation ('atypical nodule') with marked restricted diffusion. • 'Homogeneous mildly hypointense area between nodules' is likely benign with no cancers identified in the current study, however, with a wide 95% CI due to low prevalence.

Prevalence of Prostate Cancer in PI-RADS Version 2.1 Transition Zone Atypical Nodules Upgraded by Abnormal DWI: Correlation With MRI-Directed TRUS-Guided Targeted Biopsy.

BACKGROUND. In PI-RADS version 2.1 (v2.1), atypical transition zone (TZ) nodules (homogeneous circumscribed nodules without full encapsulation) assigned category 2 can be upgraded to category 3 when showing markedly restricted diffusion. The prevalence of prostate cancer (PCa) in DWI-upgraded atypical nodules is unknown. OBJECTIVE. The purpose of this study was to evaluate the prevalence of PCa in DWI-upgraded TZ atypical nodules and compare PCa diagnosis rate with that for conventional score 3 TZ nodules. METHODS. We retrospectively identified 104 consecutive cases of men who underwent MRI-directed transrectal ultrasound-guided targeted biopsy of 109 TZ category 3 or lower nodules performed between January 2015 and July 2018. Three radiologists who were blinded to the scores independently rescored lesions using PI-RADS v2.1. Agreement was assessed by Cohen kappa score. Consensus diagnosis was established by a second-round joint review. The number of TZ atypical nodules with or without DWI-upgraded and conventional score 3 TZ nodules were recorded and compared with targeted biopsy results including any PCa or clinically significant PCa (csPCa, defined as International Society of Urological Pathology [ISUP] grade group ≥ 2) using chi-square analysis. RESULTS. There were 95 PI-RADS v2.1 category 3 (55 conventional T2-weighted MRI score 3 and 40 DWI-upgraded atypical nodules) and 14 category 2 or 1 nodules at consensus review with patient mean age of 64.8 ± 8.4 (SD) years, PSA of 10.6 ± 7.2 ng/mL, and nodule size of 15.1 ± 5.5 mm. Interobserver agreement ranged from slight to substantial for radiologists 1 and 2 (κ = 0.329), radiologists 1 and 3 (κ = 0.548), and radiologists 2 and 3 (κ = 0.652). From the 40 upgraded atypical nodules, 27.5% (11/40) had PCa and 7.5% (3/40) had csPCa (8 ISUP grade 1, 2 ISUP grade 2, 1 ISUP grade 3), compared with 43.6% (24/55) PCa and 20.0% (11/55) csPCa (13 ISUP grade 1, 6 ISUP grade 2, 3 ISUP grade 3, 2 ISUP grade 4) diagnosed in conventional T2-weighted score 3 nodules (p = .09 for csPCA and p = .11 for PCa). PCa was not diagnosed in any atypical nodule that was not upgraded on DWI. CONCLUSION. The prevalence of PCa in DWI-upgraded TZ atypical nodules was low (≈ 28% for any PCa and ≈ 8% for csPCa) and compared favorably to csPCa diagnosis rates in conventional TZ score 3 nodules. CLINICAL IMPACT. This study validates the DWI upgrade rule introduced in PI-RADS v2.1 for atypical nodules, which showed significant prostate cancer detection rates at targeted biopsy similar to those of conventional T2-weighted MRI TZ score 3 nodules.

Quantitative Prostate MRI.

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 T1 and T2 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.

When to biopsy Prostate Imaging and Data Reporting System version 2 (PI-RADSv2) assessment category 3 lesions? Use of clinical and imaging variables to predict cancer diagnosis at targeted biopsy.

INTRODUCTION: We aimed to determine if clinical and imaging features can stratify men at higher risk for clinically significant (CS, International Society of Urological Pathology [ISUP] grade group ≥2) prostate cancer (PCa) in equivocal Prostate Imaging and Data Reporting System (PI-RADS) category 3 lesions on magnetic resonance imaging (MRI). METHODS: Approved by the institutional review board, this retrospective study involved 184 men with 198 lesions who underwent 3T-MRI and MRI-directed transrectal ultrasound biopsy for PI-RADS 3 lesions. Men were evaluated including clinical stage, prostate-specific antigen density (PSAD), indication, and MRI lesion size. Diagnoses for all men and by indication (no cancer, any PCa, CSPCa) were compared using multivariate logistic regression, including stage, PSAD, and lesion size. RESULTS: We found an overall PCa rate of 31.8% (63/198) and 10.1% (20/198) CSPCa (13 grade group 2, five group 3, and two group 4). Higher stage (p=0.001), PSAD (p=0.007), and lesion size (p=0.015) were associated with CSPCa, with no association between CSPCa and age, PSA, or prostate volume (p>0.05). PSAD modestly predicted CSPCa area under the curve (AUC) 0.66 (95% confidence interval [CI] 0.518-0.794) in all men and 0.64 (0.487-0.799) for those on active surveillance (AS). Model combining clinical stage, PSAD, and lesion size improved accuracy for all men and AS (AUC 0.82 [0.736-0.910], p<0.001 and 0.785 [0.666-0.904], p<0.001). In men with prior negative biopsy and persistent suspicion, PSAD (0.90 [0.767-1.000]) was not different from the model (p>0.05), with optimal cutpoint of ≥0.215 ng/mL/cc achieving sensitivity/specificity of 85.7/84.4%. CONCLUSIONS: PI-RADSv2 category 3 lesions are often not CSPCa. PSAD predicted CSPCa in men with a prior negative biopsy; however, PSAD alone had limited value, and accuracy improved when using a model incorporating PSAD with clinical stage and MRI lesion size.

Necrotic Excluded Gastric Remnant Post Gastric Bypass: A Rare Fatal Complication.

We report an unusual case of a 76-year-old woman with a necrotic perforated excluded gastric pouch who had stomach partitioning gastrojejunostomy 20 years earlier for morbid obesity. The necrotic mucosa of the excluded gastric pouch was seen on gastroscopy with retrograde cannulation from the pylorus. Laparotomy revealed a distended excluded stomach with full-thickness ischaemia of the posterior wall with perforation into the lesser sac. Partial gastrectomy with Roux-en-Y gastrojejunostomy was performed. We strongly suggest early surgical exploration for these patients when they are hemodynamically unstable or do not have a precise diagnosis despite imaging to prevent potentially life-threatening gastric pouch necrosis. We advocate for avoiding risk factors like alcohol, nicotine, and nonsteroidal anti-inflammatory drugs (NSAIDs) and implement preoperative Helicobacter pylori testing and its eradication to reduce the incidence of perforation in the excluded pouch.

Update on Indications for Percutaneous Renal Mass Biopsy in the Era of Advanced CT and MRI.

OBJECTIVE. The objective of this article is to review the burgeoning role of percutaneous renal mass biopsy (RMB). CONCLUSION. Percutaneous RMB is safe, accurate, and indicated for an expanded list of clinical scenarios. The chief scenarios among them are to prevent treatment of benign masses and help select patients for active surveillance (AS). Imaging characterization of renal masses has improved; however, management decisions often depend on a histologic diagnosis and an assessment of biologic behavior of renal cancers, both of which are currently best achieved with RMB.

Use of Quantitative T2-Weighted and Apparent Diffusion Coefficient Texture Features of Bladder Cancer and Extravesical Fat for Local Tumor Staging After Transurethral Resection.

OBJECTIVE. The purpose of this study was to determine whether quantitative T2-weighted imaging and apparent diffusion coefficient (ADC) texture features of bladder cancer and extravesical fat are predictive of muscle invasive bladder cancer (category ≥ T2) and extravesical (category ≥ T3) disease after transurethral resection of a bladder tumor (TURBT). MATERIALS AND METHODS. In this retrospective study, 36 patients (27 men, nine women; mean age, 71 years) were identified who underwent post-TURBT MRI followed by cystectomy without intervening treatment from August 2011 through October 2016. Texture features of bladder cancer and extravesical fat adjacent to the tumor on T2-weighted and ADC images were extracted and compared between category ≤ T2 versus ≥ T3 and category T1 versus ≥ T2 tumors by means of Kruskal-Wallis or Mann-Whitney U test. Multivariate logistic regression analysis was performed, and ROC curves were calculated. RESULTS. Twenty-six of the 36 (72%) tumors were ≥ T2, and 53% (19/36) were ≥ T3. In multivariate analysis, bladder cancer entropy on T2-weighted images (p = 0.006; odds ratio [OR], 4.56; 95% CI, 1.49-20.41; AUC, 0.85) and ADC maps (p = 0.019; OR, 2.24; 95% CI, 1.13-5.31; AUC, 0.80) and extravesical fat entropy on T2-weighted images (p = 0.005; OR, 17.50; 95% CI, 3.01-200.80; AUC, 0.84) and ADC maps (p = 0.002; OR, 6.54; 95% CI, 1.90-32.40; AUC, 0.82) remained greater for ≥ T3 than for ≤ T2 tumors. In multivariate analysis, bladder cancer entropy on ADC maps (p = 0.027; OR, 2.11; 95% CI, 1.08-5.03; AUC, 0.76) and extravesical fat entropy on T2-weighted images (p = 0.010; OR, 5.33; 95% CI, 1.25-3.79; AUC, 0.78) and ADC maps (p = 0.029; OR, 3.80; 95% CI, 1.25-16.97; AUC, 0.74) remained greater for category ≥ T2 compared with category T1 tumors. CONCLUSION. Greater entropy of primary bladder cancers and extravesicular fat was observed in category ≥ T3 than in category ≤ T2 and in category ≥ T2 than in category T1 tumors. MRI texture analysis can help with local bladder cancer staging in patients who have undergone TURBT and may serve as a biomarker for higher local category bladder cancers.

LI-RADS: a conceptual and historical review from its beginning to its recent integration into AASLD clinical practice guidance.

The Liver Imaging Reporting and Data System (LI-RADS®) is a comprehensive system for standardizing the terminology, technique, interpretation, reporting, and data collection of liver observations in individuals at high risk for hepatocellular carcinoma (HCC). LI-RADS is supported and endorsed by the American College of Radiology (ACR). Upon its initial release in 2011, LI-RADS applied only to liver observations identified at CT or MRI. It has since been refined and expanded over multiple updates to now also address ultrasound-based surveillance, contrast-enhanced ultrasound for HCC diagnosis, and CT/MRI for assessing treatment response after locoregional therapy. The LI-RADS 2018 version was integrated into the HCC diagnosis, staging, and management practice guidance of the American Association for the Study of Liver Diseases (AASLD). This article reviews the major LI-RADS updates since its 2011 inception and provides an overview of the currently published LI-RADS algorithms.

Accuracy of the Liver Imaging Reporting and Data System in Computed Tomography and Magnetic Resonance Image Analysis of Hepatocellular Carcinoma or Overall Malignancy-A Systematic Review.

BACKGROUND & AIMS: The Liver Imaging Reporting and Data System (LI-RADS) categorizes observations from imaging analyses of high-risk patients based on the level of suspicion for hepatocellular carcinoma (HCC) and overall malignancy. The categories range from definitely benign (LR-1) to definitely HCC (LR-5), malignancy (LR-M), or tumor in vein (LR-TIV) based on findings from computed tomography or magnetic resonance imaging. However, the actual percentage of HCC and overall malignancy within each LI-RADS category is not known. We performed a systematic review to determine the percentage of observations in each LI-RADS category for computed tomography and magnetic resonance imaging that are HCCs or malignancies. METHODS: We searched the MEDLINE, Embase, Cochrane CENTRAL, and Scopus databases from 2014 through 2018 for studies that reported the percentage of observations in each LI-RADS v2014 and v2017 category that were confirmed as HCCs or other malignancies based on pathology, follow-up imaging analyses, or response to treatment (reference standard). Data were assessed on a per-observation basis. Random-effects models were used to determine the pooled percentages of HCC and overall malignancy for each LI-RADS category. Differences between categories were compared by analysis of variance of logit-transformed percentage of HCC and overall malignancy. Risk of bias and concerns about applicability were assessed with the Quality Assessment of Diagnostic Accuracy Studies 2 tool. RESULTS: Of 454 studies identified, 17 (all retrospective studies) were included in the final analysis, consisting of 2760 patients, 3556 observations, and 2482 HCCs. The pooled percentages of observations confirmed as HCC and overall malignancy, respectively, were 94% (95% confidence interval [CI] 92%-96%) and 97% (95% CI 95%-99%) for LR-5, 74% (95% CI 67%-80%) and 80% (95% CI 75%-85%) for LR-4, 38% (95% CI 31%-45%) and 40% (95% CI 31%-50%) for LR-3, 13% (95% CI 8%-22%) and 14% (95% CI 9%-21%) for LR-2, 79% (95% CI 63%-89%) and 92% (95% CI 77%-98%) for LR-TIV, and 36% (95% CI 26%-48%) and 93% (95% CI 87%-97%) for LR-M. No malignancies were found in the LR-1 group. The percentage of HCCs and overall malignancies confirmed differed significantly among LR groups 2-5 (P < .00001). Patient selection was the most frequent factor that affected bias risk, because of verification bias and case-control study design. CONCLUSIONS: In a systematic review, we found that increasing LI-RADS categories contained increasing percentages of HCCs and overall malignancy based on reference standard confirmation. Of observations categorized as LR-M, 93% were malignancies and 36% were confirmed as HCCs. The percentage of HCCs found in the LR-2 and LR-3 categories indicate the need for a more active management strategy than currently recommended. Prospective studies are needed to validate these findings. PROSPERO number CRD42018087441.

Evaluation of MRI for diagnosis of extraprostatic extension in prostate cancer.

PURPOSE: To assess the ability of magnetic resonance imaging (MRI) to diagnose extraprostatic extension (EPE) in prostate cancer. MATERIALS AND METHODS: With Institutional Review Board (IRB) approval, 149 men with 170 ≥0.5 mL tumors underwent preoperative 3T MRI followed by radical prostatectomy (RP) between 2012-2015. Two blinded radiologists (R1/R2) assessed tumors using Prostate Imaging Reporting and Data System (PI-RADS) v2, subjectively evaluated for the presence of EPE, measured tumor size, and length of capsular contact (LCC). A third blinded radiologist, using MRI-RP-maps, measured whole-lesion: apparent diffusion coefficient (ADC) mean/centile and histogram features. Comparisons were performed using chi-square, logistic regression, and receiver operator characteristic (ROC) analysis. RESULTS: The subjective EPE assessment showed high specificity (SPEC = 75.4/91.3% [R1/R2]), low sensitivity (SENS = 43.3/43.6% [R1/R2]), and area-under (AU) ROC curve = 0.67 (confidence interval [CI] 0.61-0.73) R1 and 0.61 (CI 0.53-0.70) R2; (k = 0.33). PI-RADS v2 scores were strongly associated with EPE (P < 0.001 / P = 0.008; R1/R2) with AU-ROC curve = 0.72 (0.64-0.79) R1 and 0.61 (0.53-0.70) R2; (k = 0.44). Tumors with EPE were larger (18.8 ± 7.8 [median 17, range 6-51] vs. 18.8 ± 4.9 [12, 6-28] mm) and had greater LCC (21.1 ± 14.9 [16, 1-85] vs. 13.6 ± 6.1 [11.5, 4-30] mm); P < 0.001 and 0.002, respectively. AU-ROC for size was 0.73 (0.64-0.80) and LCC was 0.69 (0.60-0.76), respectively. Optimal SENS/SPEC for diagnosis of EPE were: size ≥15 mm = 67.7/66.7% and LCC ≥11 mm = 84.9/44.8%. 10th -centile ADC and ADC entropy were both associated with EPE (P = 0.02 and < 0.001), with AU-ROC = 0.56 (0.47-0.65) and 0.76 (0.69-0.83), respectively. Optimal SENS/SPEC for diagnosis of EPE with entropy ≥6.99 was 63.3/75.0%. 25th -centile ADC trended towards being significantly lower with EPE (P = 0.06) with no difference in other ADC metrics (P = 0.25-0.88). Size, LCC, and ADC entropy improved sensitivity but reduced specificity compared with subjective analysis with no difference in overall accuracy (P = 0.38). CONCLUSION: Measurements of tumor size, capsular contact, and ADC entropy improve sensitivity but reduce specificity for diagnosis of EPE compared to subjective assessment. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:176-185.

Prostate Imaging Reporting and Data System, Version 2, Assessment Categories and Pathologic Outcomes in Patients With Gleason Score 3 + 4 = 7 Prostate Cancer Diagnosed at Biopsy.

OBJECTIVE: The purpose of this study is to assess associations between Prostate Imaging Reporting and Data System, version 2 (PI-RADSv2), categories and the presence of a tumor with a Gleason score (GS) of 4 + 3 = 7 or greater or the presence of extraprostatic extension (EPE) at radical prostatectomy (RP) in patients with a GS 3 + 4 = 7 tumor at biopsy. MATERIALS AND METHODS: A total of 81 men with GS 3 + 4 = 7 prostate cancer diagnosed by transrectal ultrasound-guided biopsy underwent multiparametric MRI and RP between 2012 and 2015. Two blinded radiologists assessed multiparametric MR images and assigned PI-RADSv2 assessment categories (categories 1-5) with the use of sector maps, which were compared with regard to the location of the tumor, the GS, and the presence of EPE at RP. Comparisons were performed between groups with the use of chi-square and multivariate analysis. Diagnostic accuracy was assessed using ROC curve analysis, and localization was compared using the Fisher exact test. RESULTS: A total of 53.1% of men (43/81) had EPE, and 21.0% (17/81) had GS 4 + 3 = 7 prostate cancer after RP, whereas 2.5% of men (2/81) had their tumors downgraded to GS 3 + 3 = 6. No statistically significant difference in patient age, prostate specific antigen level, or clinical stage existed between groups (p > 0.05). PI-RADSv2 assessment categories were significantly higher for GS 4 + 3 = 7 tumors (p = 0.03). PI-RADSv2 showed moderate accuracy for the diagnosis of GS 4 + 3 = 7 tumors (AUC, 0.65; 95% CI, 0.54-0.77), with a category of 4 or higher having a sensitivity and specificity for diagnosis of 94.1% and 23.4%, respectively. No patient with a PI-RADSv2 category lower than 3 had a GS 4 + 3 = 7 tumor. Accuracy of tumor localization ranged from 86.4% to 92.6%, with 88.2% of errors (15/17) occurring in GS 3 + 3 = 6 or GS 3 + 4 = 7 tumors (p = 0.30). PI-RADSv2 categories were noted to be higher when EPE was present (p < 0.001). Interobserver agreement was moderate (κ = 0.43). CONCLUSION: For GS 3 + 4 = 7 cancers detected at transrectal ultrasound-guided biopsy, higher PI-RADSv2 assessment categories are associated with upgrading to GS 4 + 3 = 7 cancer and with the presence of EPE after RP. A PI-RADSv2 score of 3 or higher was 100% sensitive for diagnosing GS 4 + 3 = 7 tumors.

MRI assessment of pathological stage and surgical margins in anterior prostate cancer (APC) using subjective and quantitative analysis.

PURPOSE: To evaluate magnetic resonance imaging (MRI) for assessment of extraprostatic extension (EPE) and positive surgical margins (PSM) in anterior prostate cancer (APC). MATERIALS AND METHODS: With Institutional Review Board approval, 25 APC (>2/3 of tumor anterior to urethra) were assessed using 3T MRI by two blinded radiologists for: size and maximal leading edge of tumor (relative to anterior fibromuscular stroma [AFMS]) on b ≥1000 sec/mm2 echo-planar-MRI fused onto T2 -weighted-MRI, invasion of AFMS and EPE. Comparisons were performed between APCs by EPE/PSM using chi-square, multivariable analysis, and receiver operator characteristic (ROC) analysis. RESULTS: The prevalence of EPE and PSM were 52% (13/25) and 36% (9/25). Tumor sizes were larger with EPE (22.5 ± 8.4 vs. 14.7 ± 6.3, P = 0.02) and PSM (23.0 ± 9.3 vs. 16.4 ± 7.0, P = 0.06). Area under ROC curve (AUC-ROC) for the diagnosis of EPE by tumor size was 0.77 (95% confidence interval [CI] 0.58-0.95); ≥16 mm size = sensitivity/specificity 69.2/66.7%. Maximal leading edge of tumor was greater with EPE (2.4 ± 2.2 vs. -0.2 ± 3.0) and PSM (2.8 ± 2.3 vs. -0.3 ± 2.5), (P = 0.023, 0.031). AUC-ROC for diagnosis of EPE/PSM by leading edge was 0.78 (CI 0.57-0.97) and 0.75 (CI 0.56-0.94). A ≥1 mm leading edge yielded sensitivity/specificity of 76.9/75.0% and 77.8/62.5% for diagnosis of EPE/PSM. 60-72% (15-18/25) tumors invaded AFMS (k = 0.74), which was not associated with EPE/PSM (P = 0.12-0.14). Radiologists' assessment of EPE had sensitivity/specificity of 61.5-69.2/50.0-75.0% (k = 0.53). CONCLUSION: Tumor size and leading edge of tumor relative to AFMS may enable diagnosis of EPE and positive surgical margins in APC. LEVEL OF EVIDENCE: 2 J. MAGN. RESON. IMAGING 2017;45:1296-1303.

Prognostic value of Prostate Imaging and Data Reporting System (PI-RADS) v. 2 assessment categories 4 and 5 compared to histopathological outcomes after radical prostatectomy.

PURPOSE: To assess Prostate Imaging and Data Reporting System (PI-RADS) v. 2 score 4/5 lesions compared to Gleason score (GS) and stage after radical prostatectomy (RP) and to validate the proposed 15-mm size threshold that differentiates category 4 versus 5 lesions. MATERIALS AND METHODS: With Institutional Review Board (IRB) approval, 140 men underwent 3T magnetic resonance imaging (MRI) and RP between 2012-2015. Two blinded radiologists: 1) assigned PI-RADS v. 2 scores, 2) measured tumor size on axial T2 -weighted-MRI, and 3) assessed for extraprostatic extension (EPE). Interobserver agreement was calculated and consensus diagnoses achieved through reference standard (MRI-RP maps). PI-RADS v. 2 scores and tumor size were compared to GS and stage using chi-square, analysis of variance (ANOVA), and receiver operating characteristic (ROC) curve analysis. RESULTS: In all, 80.7% (113/140) of tumors were category 4 (n = 45) or 5 (n = 68) lesions (κ = 0.45). Overall tumor size was 18.2 ± 7.7 mm and category 5 lesions were larger (22.6 ± 6.8 versus 11.5 ± 1.9 mm, P < 0.001). High-risk (GS ≥8) tumors were larger than low- and intermediate-risk tumors (P = 0.016) and were more frequently, but not significantly so, category 5 lesions (78.9% [15/19] vs. 22.1% [4/10], P = 0.18). 67.3% (76/113) of patients had EPE. Category 5 lesions were strongly associated with EPE (P < 0.0001). Area under the ROC curve for diagnosis of EPE by size was 0.74 (confidence interval 0.64-0.83), with size ≥15 mm yielding a sensitivity/specificity of 72.4/64.9%. Size improved sensitivity for diagnosis of EPE compared to subjective assessment (sensitivity/specificity ranging from 46.1-48.7%/70.3-86.5%, κ = 0.29) (P = 0.028). CONCLUSION: PI-RADS v. 2 category 5 lesions are associated with higher Gleason scores and EPE. A 15-mm size threshold is reasonably accurate for diagnosis of EPE with increased sensitivity compared to subjective assessment. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:257-266.