Faculty Bibliography

PURPOSE/OBJECTIVE:To review the diagnostic performance of ≥1.5-T MRI for local staging of bladder cancer. METHODS:MEDLINE and EMBASE were searched up to February 21, 2017. We included diagnostic accuracy studies published since 2000 that used ≥1.5-T MRI for local staging (≥T2 [muscle-invasive]) in patients with bladder cancer, using pathology as the reference standard. The methodological quality was assessed using Quality Assessment of Diagnostic Accuracy Studies-2. Sensitivity and specificity were pooled and plotted in a hierarchical summary receiver operating characteristics plot. Sensitivity analyses using several clinically relevant covariates were performed. RESULTS:24 studies (1774 patients) were included. Pooled sensitivity was 0.92 (95% CI 0.88-0.95) with specificity of 0.87 (95% CI 0.78-0.93). Sensitivity analyses showed that sensitivity estimates were comparable and consistently high across all subgroups, but specificity estimates were variable. Studies using 3-T scanners had higher specificity (0.93 [95% CI 0.86-0.98]) than those using 1.5-T scanners (0.83 [95% CI 0.74-0.98]). Studies using multiparametric MRI (conventional+≥2 functional sequences) showed the highest accuracy with sensitivity and specificity of 0.94 (95% CI 0.89-1.00) and 0.95 (95% CI 0.89-0.98), respectively. CONCLUSIONS:MRI shows good diagnostic performance for predicting muscle-invasiveness of bladder cancer. Multiparametric 3-T MRI seems to improve both sensitivity and specificity.

CONTEXT:In 2015, the updated Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) for the detection of prostate cancer (PCa) was established. Since then, several studies assessing the value of PI-RADSv2 have been published. OBJECTIVE:To review the diagnostic performance of PI-RADSv2 for the detection of PCa. EVIDENCE ACQUISITION:MEDLINE and EMBASE databases were searched up to December 7, 2016. We included diagnostic accuracy studies that used PI-RADSv2 for PCa detection, using prostatectomy or biopsy as the reference standard. The methodological quality was assessed by two independent reviewers using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Sensitivity and specificity of all studies were calculated. Results were pooled and plotted in a hierarchical summary receiver operating characteristic plot with further exploration using meta-regression and multiple subgroup analyses. Head-to-head comparison between PI-RADSv1 and PI-RADSv2 was performed for available studies. EVIDENCE SYNTHESIS:Twenty-one studies (3857 patients) were included. The pooled sensitivity was 0.89 (95% confidence interval [CI] 0.86-0.92) with specificity of 0.73 (95% CI 0.60-0.83) for PCa detection. Proportion of patients with PCa, magnetic field strength, and reference standard were significant factors affecting heterogeneity (p<0.01). Multiple subgroup analyses showed consistent results. In six studies performing head-to-head comparison, PI-RADSv2 demonstrated higher pooled sensitivity of 0.95 (95% CI 0.85-0.98) compared with 0.88 (95% CI 0.80-0.93) for PI-RADSv1 (p=0.04). However, the pooled specificity was not significantly different (0.73 [95% CI 0.47-0.89] vs 0.75 [95% CI 0.36-0.94], respectively; p=0.90). CONCLUSIONS:PI-RADSv2 shows good performance for the detection of PCa. PI-RADSv2 has higher pooled sensitivity than PI-RADSv1 without significantly different specificity. PATIENT SUMMARY:We reviewed all previous studies using Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) for prostate cancer detection. We found that the updated PI-RADSv2 shows significant improvement compared with the original PI-RADSv1.

OBJECTIVE:To investigate the added value of secondary reports issued by radiologists subspecializing in gynaecologic imaging for determining deep myometrial invasion of endometrial cancer on MRI. METHODS:Initial (from referring institutions) and secondary (by subspecialized radiologists) interpretations of MRI of 55 patients with endometrial cancer were retrospectively reviewed. A radiologist blinded to clinicopathological information assessed both reports for the presence of deep myometrial invasion. Reference standard was based on hysterectomy specimens. Kappa coefficients (k) were used to measure their concordance. McNemar testing and receiver operating characteristic (ROC) analysis was used to compare sensitivities, specificities and areas under the curves (AUCs). RESULTS:Deep myometrial invasion was present in 25 (45.5 %) patients. Among 27.3 % (15/55; k = 0.458) patients with discrepant results, secondary interpretations were correct in 10 (66.7 %) cases. Sensitivity was higher in secondary than in initial reports (76.0 % vs. 48.0 %, p = 0.039) while no significant difference was seen in specificity (70.0 % vs. 76.7 %, p = 0.668). At ROC analysis, there was a tendency for higher AUCs in secondary reports (0.785 vs 0.669, p = 0.096). CONCLUSION/CONCLUSIONS:Secondary readings of MRI by subspecialized gynaecologic oncologic radiologists may provide incremental value in determining deep myometrial invasion of endometrial cancer. KEY POINTS/CONCLUSIONS:• Deep myometrial invasion is an important prognostic factor in endometrial cancer. • Assessment of deep myometrial invasion is often discrepant between initial and secondary reports. • Secondary reports showed higher sensitivity and accuracy. • Secondary review of MRI may provide incremental value in endometrial cancer patients.

Background Length of capsular contact (LCC) is a promising biomarker for predicting extracapsular extension (ECE), but the most optimal magnetic resonance imaging (MRI) sequence for measuring LCC is yet to be determined. Purpose To evaluate LCC using different MRI sequences for determining ECE in prostate cancer. Material and Methods A total of 185 patients underwent prostate MRI followed by radical prostatectomy. LCC was measured separately on T2-weighted (T2W) images, apparent diffusion coefficient (ADC) maps, and dynamic contrast-enhanced (DCE) MRI. LCCs (LCC_T2, LCC_ADC, LCC_DCE, and LCC_max [greatest value of 3 LCCs]) were compared between sequences using Wilcoxon signed rank test and was tested for determining ECE using the Mann-Whitney U test, ROC curve analysis, and logistic regression analysis. Results There were no significant differences among LCCs ( P = 0.333-0.837). All LCCs were significantly greater in patients with ECE ( P < 0.001). The optimal threshold value for predicting ECE was >14, >13, >12, and >14 mm for LCC_T2, LCC_ADC, LCC_DCE, and LCC_max, respectively. LCC_max yielded the highest area under the curve (0.895) which was significantly greater than that by LCC_ADC (0.858, P = 0.030). Otherwise, there were no significant difference between LCCs ( P = 0.052-0.985). At univariate analysis, age, clinical stage, PSA, Gleason score, and all LCCs were significantly associated with ECE ( P < 0.001-0.040). At multivariate analysis, GS ( P ≤ 0.008) and all LCCs ( P < 0.001) were independently predictive factors. Conclusion LCC measured on any sequence was significantly different in patients with and without ECE and was independently associated with the presence of ECE. Although LCC_max showed the greatest ability to predict ECE, there was relatively equivalent performance among different MRI sequences.

PURPOSE:To evaluate the diagnostic value of integrated positron emission tomography/magnetic resonance imaging (PET/MRI) compared with conventional multiparametric MRI and PET/computed tomography (CT) for the detailed and accurate segmental detection/localization of prostate cancer. MATERIALS AND METHODS:F-FDG PET/CT). Sensitivity, specificity, accuracy, positive and negative predictive values, likelihood ratios, and diagnostic performance based on the DOR (diagnostic odds ratio) and NNM (number needed to misdiagnose) were evaluated for each interpretation modality, using the pathologic result as the reference standard. Detection rates of seminal vesicle invasion and extracapsular invasion were also evaluated. RESULTS:F-FDG PET/MRI (as DOR, 6.917 in total patients, 15.143 in high Gleason score patients, 3.175 in low Gleason score groups) in all three patient groups. CONCLUSION:F-FDG PET/CT. LEVEL OF EVIDENCE:2 J. Magn. Reson. Imaging 2017;45:597-609.

The incidence of small renal masses (SRMs) has shown significant increase owing to more widespread use of cross-sectional imaging. These SRMs include various subtypes of renal cell carcinomas (RCCs) and several types of benign tumors including angiomyolipomas. Differentiation between RCC and benign SRMs is crucial for a patient to receive optimal management. Therefore, it is important for the radiologist to recognize imaging patterns that are characteristic of or diffferentiate between RCCs and benign SRMs, when confronting a SRM. This article describes several well-known imaging patterns of SRMs reported in the literature.

BACKGROUND:Although magnetic resonance imaging (MRI) is currently indispensable in the management of cervical cancer, its role in determining residual tumor in patients with cervical cancer after conization is not well known. PURPOSE/OBJECTIVE:To evaluate the value of MRI after conization in determining residual tumor in patients with FIGO stage IA-IB1 cervical cancer. MATERIAL AND METHODS/METHODS:In this retrospective study, 55 patients underwent conization followed by preoperative MRI and definitive surgery. Two radiologists evaluated the presence of residual tumor on MRI. MRI and preoperative clinical variables were compared between patients with and without residual tumor at final pathology using Student's t-test or Chi-square test. Association between variables and the presence of residual tumor was assessed using logistic regression analyses and receiver operating characteristic (ROC) curves. RESULTS:Residual tumor at final pathology was found in 30 (54.5%) patients. Patients with residual tumor were older, had greater SCC antigen, and more frequently had positive conization margins and identifiable tumor on MRI (P < 0.008). Multivariate analysis showed that age (P = 0.008; odds ratio [OR] = 1.140), positive conization margin (P = 0.016; OR = 11.919), and identifiable tumor on MRI (P = 0.038; OR = 6.926) were independently predictive of residual tumor. Areas under the curve (AUCs) calculated with age (0.693), SCC antigen (0.755), and identifiable tumor on MRI (0.727) were greater than lymphovascular space invasion (0.517) and histological subtype (0.520, P ≤ 0.049). Otherwise, there were no significant differences in the AUCs derived from different variables (P = 0.053-0.970). CONCLUSION/CONCLUSIONS:Identifiable tumor on MRI after conization in patients with early stage cervical cancer was an independent predictor of residual tumor at final pathology.

OBJECTIVES/OBJECTIVE:To evaluate PI-RADSv2 for predicting pathological downgrading after radical prostatectomy (RP) in patients with biopsy-proven Gleason score (GS) 7(3+4) PC. METHODS:A total of 105 patients with biopsy-proven GS 7(3+4) PC who underwent multiparametric prostate MRI followed by RP were included. Two radiologists assigned PI-RADSv2 scores for each patient. Preoperative clinicopathological variables and PI-RADSv2 scores were compared between patients with and without downgrading after RP using the Wilcoxon rank sum test or Fisher's exact test. Logistic regression analyses with Firth's bias correction were performed to assess their association with downgrading. RESULTS:Pathological downgrading was identified in ten (9.5 %) patients. Prostate-specific antigen (PSA), PSA density, percentage of cores with GS 7(3+4), and greatest percentage of core length (GPCL) with GS 7(3+4) were significantly lower in patients with downgrading (p = 0.002-0.037). There was no significant difference in age and clinical stage (p = 0.537-0.755). PI-RADSv2 scores were significantly lower in patients with downgrading (3.8 versus 4.4, p = 0.012). At univariate logistic regression analysis, PSA, PSA density, and PI-RADSv2 scores were significant predictors of downgrading (p = 0.003-0.022). Multivariate analysis revealed only PSA density and PI-RADSv2 scores as independent predictors of downgrading (p = 0.014-0.042). CONCLUSIONS:The PI-RADSv2 scoring system was an independent predictor of pathological downgrading after RP in patients with biopsy-proven GS 7(3+4) PC. KEY POINTS/CONCLUSIONS:• PI-RADSv2 was an independent predictor of downgrading in biopsy-proven GS 7(3+4) PC • PSA density was also an independent predictor of downgrading • MRI may assist in identifying AS candidates in biopsy-proven GS 7(3+4) PC patients.

BACKGROUND:Angiomyolipoma (AML) with minimal fat may mimic renal cell carcinoma (RCC) and is difficult to distinguish from RCC with imaging studies alone. Precise diagnostic strategies have been explored to discern AML with minimal fat from RCC. PURPOSE/OBJECTIVE:To compare the morphological and enhancement features of AML with minimal fat with those of size-matched RCC on computed tomography (CT). MATERIAL AND METHODS/METHODS:Our study included 143 pathologically proved renal tumors (29 AML with minimal fat: mean diameter, 2.5 cm; range, 1.2-4 cm; 114 RCC: mean diameter, 2.8 cm; range, 1.3-4 cm). All patients underwent biphasic helical CTs. Two radiologists retrospectively evaluated the morphological (i.e. non-round and round appearances, with or without capsule) and enhancement features (i.e., wash-out, gradual, or prolonged). For the parameters that had statistically significance between the two groups, we calculated the positive and negative predictive values by using the univariate χ(2) test. P < 0.05 indicated a significant difference. RESULTS:AML with minimal fat showed a non-round appearance without a capsule (n = 24, 83%) and prolonged enhancement (n = 20, 69%). The positive and negative predictive values of the non-round appearance without capsule for differentiating AML with minimal fat from RCC were 82.8% and 95.6%, respectively. The positive and negative predictive values of prolonged enhancement were 62.5% and 90.8%, respectively. These features were valuable predictors for AML with minimal fat from RCC. CONCLUSION/CONCLUSIONS:CT images with non-round shape without capsule and prolonged enhancements may be used to differentiate AML with minimal fat from RCC.

BACKGROUND:Although magnetic resonance imaging (MRI) is currently indispensable in the preoperative setting of biopsy-proven prostate cancer, the value of preoperative MRI for predicting prostate cancer-specific mortality (PCSM) is not well known. PURPOSE/OBJECTIVE:To evaluate the value of MRI for predicting PCSM in patients who underwent radical prostatectomy (RP) for localized prostate cancer. MATERIAL AND METHODS/METHODS:A total of 318 patients underwent MRI followed by RP. MRI was assessed for the presence of clinically significant cancer using a five-point Likert scale, where ≥4 was considered positive. Cox proportional hazards regression analyses was used to determine the relationship of preoperative factors with PCSM. PCSM was calculated using the Kaplan-Meier method and compared between factors using the log-rank test. RESULTS:After a median follow-up of 104 months, 11 (3.5%) patients died of prostate cancer. One hundred and four (32.7%) patients had clinically significant prostate cancer on MRI. Univariate analysis revealed that Gleason grade, greatest percentage of involved core length (GPCL), and clinically significant cancer on MRI were significantly related to PCSM (P = 0.001-0.003). Multivariate analysis showed that GPCL (hazard ratio [HR], 1.028; 95% confidence interval [CI], 1.000-1.057; P = 0.048) and clinically significant cancer on MRI (HR, 10.903; 95% CI, 1.287-92.374; P = 0.028) were independent predictors of PCSM. The 5 - and 10-year PCSM rates were 0.6% and 1.3% in patients with GPCL <50% and 5.1% and 8.6% in those with GPCL ≥50% (P = 0.012). Patients without clinically significant cancer on MRI showed 5 - and 10-year PCSM rates of 0% and 0.5%, respectively, whereas those with clinically significant cancer on MRI showed rates of 8% and 14.2%, respectively (P < 0.001). CONCLUSION/CONCLUSIONS:Preoperative MRI and GPCL may be used to predict PCSM after RP.