Ovarian cancer reporting lexicon for computed tomography (CT) and magnetic resonance (MR) imaging developed by the SAR Uterine and Ovarian Cancer Disease-Focused Panel and the ESUR Female Pelvic Imaging Working Group.

OBJECTIVES: Imaging evaluation is an essential part of treatment planning for patients with ovarian cancer. Variation in the terminology used for describing ovarian cancer on computed tomography (CT) and magnetic resonance (MR) imaging can lead to ambiguity and inconsistency in clinical radiology reports. The aim of this collaborative project between Society of Abdominal Radiology (SAR) Uterine and Ovarian Cancer (UOC) Disease-focused Panel (DFP) and the European Society of Uroradiology (ESUR) Female Pelvic Imaging (FPI) Working Group was to develop an ovarian cancer reporting lexicon for CT and MR imaging. METHODS: Twenty-one members of the SAR UOC DFP and ESUR FPI working group, one radiology clinical fellow, and two gynecologic oncology surgeons formed the Ovarian Cancer Reporting Lexicon Committee. Two attending radiologist members of the committee prepared a preliminary list of imaging terms that was sent as an online survey to 173 radiologists and gynecologic oncologic physicians, of whom 67 responded to the survey. The committee reviewed these responses to create a final consensus list of lexicon terms. RESULTS: An ovarian cancer reporting lexicon was created for CT and MR Imaging. This consensus-based lexicon has 6 major categories of terms: general, adnexal lesion-specific, peritoneal carcinomatosis-specific, lymph node-specific, metastatic disease -specific, and fluid-specific. CONCLUSIONS: This lexicon for CT and MR imaging evaluation of ovarian cancer patients has the capacity to improve the clarity and consistency of reporting disease sites seen on imaging. KEY POINTS: • This reporting lexicon for CT and MR imaging provides a list of consensus-based, standardized terms and definitions for reporting sites of ovarian cancer on imaging at initial diagnosis or follow-up. • Use of standardized terms and morphologic imaging descriptors can help improve interdisciplinary communication of disease extent and facilitate optimal patient management. • The radiologists should identify and communicate areas of disease, including difficult to resect or potentially unresectable disease that may limit the ability to achieve optimal resection.

Is possible to rule out clinically significant prostate cancer using PI-RADS v2 for the assessment of prostate MRI?

OBJECTIVES: To evaluate the diagnostic performance and interobserver agreement of PI-RADS v2. MATERIALS AND METHODS: In this Institutional Review Board approved single-center retrospective study, 98 patients with clinically suspected PCa who underwent 3-T multiparametric MRI followed by MRI/TRUS fusion-guided prostate biopsy were included from June 2013 to February 2015. Two radiologists (R1 and R2) with 8 and 1 years of experience in abdominal radiology reviewed the MRI scans and assigned PI-RADS v2 scores in all prostate zones. PI-RADS v2 were compared to MRI/TRUS fusion-guided biopsy results, which were classified as negative, PCa, and significant PCa (sPCa). RESULTS: Sensitivity, specificity, NPV, PPV and accuracy for PCa was 85.7% (same for all metrics) for R1 and 81.6%, 79.6%, 81.2%, 80.0% and 80.6% for R2. For detecting sPCa, the corresponding values were 95.3%, 85.4%, 95.9%, 83.7% and 89.8% for R1 and 93.0%, 81.8%, 93.7%, 86.7% and 86.7% for R2. There was substantial interobserver agreement in assigning PI-RADS v2 score as negative (1, 2, 3) or positive (4, 5) (Kappa=0.78). On multivariate analysis, PI-RADS v2 (p <0.001) was the only independent predictor of sPCa compared with age, abnormal DRE, prostate volume, PSA and PSA density. CONCLUSIONS: Our study population demonstrated that PI-RADS v2 had high diagnostic accuracy, substantial interobserver agreement, and it was the only independent predictor of sPCa.

Automatic classification of prostate cancer Gleason scores from multiparametric magnetic resonance images.

Noninvasive, radiological image-based detection and stratification of Gleason patterns can impact clinical outcomes, treatment selection, and the determination of disease status at diagnosis without subjecting patients to surgical biopsies. We present machine learning-based automatic classification of prostate cancer aggressiveness by combining apparent diffusion coefficient (ADC) and T2-weighted (T2-w) MRI-based texture features. Our approach achieved reasonably accurate classification of Gleason scores (GS) 6(3 + 3) vs. ≥7 and 7(3 + 4) vs. 7(4 + 3) despite the presence of highly unbalanced samples by using two different sample augmentation techniques followed by feature selection-based classification. Our method distinguished between GS 6(3 + 3) and ≥7 cancers with 93% accuracy for cancers occurring in both peripheral (PZ) and transition (TZ) zones and 92% for cancers occurring in the PZ alone. Our approach distinguished the GS 7(3 + 4) from GS 7(4 + 3) with 92% accuracy for cancers occurring in both the PZ and TZ and with 93% for cancers occurring in the PZ alone. In comparison, a classifier using only the ADC mean achieved a top accuracy of 58% for distinguishing GS 6(3 + 3) vs. GS ≥7 for cancers occurring in PZ and TZ and 63% for cancers occurring in PZ alone. The same classifier achieved an accuracy of 59% for distinguishing GS 7(3 + 4) from GS 7(4 + 3) occurring in the PZ and TZ and 60% for cancers occurring in PZ alone. Separate analysis of the cancers occurring in TZ alone was not performed owing to the limited number of samples. Our results suggest that texture features derived from ADC and T2-w MRI together with sample augmentation can help to obtain reasonably accurate classification of Gleason patterns.

Convergent evolution of BRCA2 reversion mutations under therapeutic pressure by PARP inhibition and platinum chemotherapy.

Reversion mutations that restore wild-type function of the BRCA gene have been described as a key mechanism of resistance to Poly(ADP-ribose) polymerase (PARP) inhibitor therapy in BRCA-associated cancers. Here, we report a case of a patient with metastatic castration-resistant prostate cancer (mCRPC) with a germline BRCA2 mutation who developed acquired resistance to PARP inhibition. Extensive genomic interrogation of cell-free DNA (cfDNA) and tissue at baseline, post-progression, and postmortem revealed ten unique BRCA2 reversion mutations across ten sites. While several of the reversion mutations were private to a specific site, nine out of ten tumors contained at least one mutation, suggesting a powerful clonal selection for reversion mutations in the presence of therapeutic pressure by PARP inhibition. Variable cfDNA shed was seen across tumor sites, emphasizing a potential shortcoming of cfDNA monitoring for PARPi resistance. This report provides a genomic portrait of the temporal and spatial heterogeneity of prostate cancer under the selective pressure of a PARP inhibition and exposes limitations in the current strategies for detection of reversion mutations.

Plasmacytoid urothelial carcinoma of the bladder: MRI features and their association with survival.

OBJECTIVES: Plasmacytoid urothelial carcinomas (PUC) of the bladder are rare variants known for diffuse and infiltrative spread, however their magnetic resonance imaging (MRI) features are not well established. We aimed to evaluate MRI features of PUC of the bladder and their association with survival. METHODS AND MATERIALS: This retrospective single-center study included 41 patients with pathologically-proven bladder PUC of the bladder that underwent pre-treatment MRI between January 2000 and March 2020. Two radiologists reviewed MRIs independently followed by consensus with a third radiologist. On MRI, tumor extent, size, Vesical Imaging-Reporting and Data System (VI-RADS) scores (≥4, muscle-invasive; 5, extravesical extension [EVE]), pelvic peritoneal spread (PPS), hydronephrosis, pelvic adenopathy and clinicopathological factors of age, gender, pathological stage, and treatment type were extracted. Kaplan-Meier curves and Cox proportional-hazards models were used to evaluate association with survival. RESULTS: Thirty-two men and 9 women (median age 70 years, IQR 64-76) were included. Most were muscle-invasive (n = 30 [73.2%]). On MRI, most tumors were diffuse (n = 28 [68.3%]), >5 cm (n = 30 [73.2%]), VI-RADS 4 to 5 (n = 36 [87.8%]) with features of EVE and (n = 31 [75.6%]) and PPS (n = 25 [61.0%]). Variables associated with survival were: Larger tumors (>5 cm; hazard ratio [HR] = 5.0; 95% confidence interval [CI] 1.6-15.5; P < 0.01), diffuse extent (HR = 4.0; 95% CI 1.4-11.2; P = 0.01), EVE (HR = 4.5; 95% CI 1.5-13.6; P < 0.01), PPS (HR = 3.0; 95% CI 1.2-7.4; P = 0.01), hydronephrosis (HR = 13.7; 95% CI 3.1-60.9; P < 0.01), pathologic stage (≥pT3 vs. pT1; HR = 5.6; 95% CI 1.3-22.0; P = 0.02), and margin positivity (HR = 4.4 [95% CI 1.2-16.4], P = 0.03). CONCLUSION: PUCs of the bladder are commonly large, diffuse VI-RADS score 4 to 5 tumors with MRI features of EVE and PPS. These features and pathological stage were associated with survival.

Integrated Multi-Tumor Radio-Genomic Marker of Outcomes in Patients with High Serous Ovarian Carcinoma.

Purpose: Develop an integrated intra-site and inter-site radiomics-clinical-genomic marker of high grade serous ovarian cancer (HGSOC) outcomes and explore the biological basis of radiomics with respect to molecular signaling pathways and the tumor microenvironment (TME). Method: Seventy-five stage III-IV HGSOC patients from internal (N = 40) and external factors via the Cancer Imaging Archive (TCGA) (N = 35) with pre-operative contrast enhanced CT, attempted primary cytoreduction, at least two disease sites, and molecular analysis performed within TCGA were retrospectively analyzed. An intra-site and inter-site radiomics (cluDiss) measure was combined with clinical-genomic variables (iRCG) and compared against conventional (volume and number of sites) and average radiomics (N = 75) for prognosticating progression-free survival (PFS) and platinum resistance. Correlation with molecular signaling and TME derived using a single sample gene set enrichment that was measured. Results: The iRCG model had the best platinum resistance classification accuracy (AUROC of 0.78 [95% CI 0.77 to 0.80]). CluDiss was associated with PFS (HR 1.03 [95% CI: 1.01 to 1.05], p = 0.002), negatively correlated with Wnt signaling, and positively to immune TME. Conclusions: CluDiss and the iRCG prognosticated HGSOC outcomes better than conventional and average radiomic measures and could better stratify patient outcomes if validated on larger multi-center trials.

How clinical imaging can assess cancer biology.

Human cancers represent complex structures, which display substantial inter- and intratumor heterogeneity in their genetic expression and phenotypic features. However, cancers usually exhibit characteristic structural, physiologic, and molecular features and display specific biological capabilities named hallmarks. Many of these tumor traits are imageable through different imaging techniques. Imaging is able to spatially map key cancer features and tumor heterogeneity improving tumor diagnosis, characterization, and management. This paper aims to summarize the current and emerging applications of imaging in tumor biology assessment.

Is possible to rule out clinically significant prostate cancer using PI-RADS v2 for the assessment of prostate MRI?

ABSTRACT Objectives To evaluate the diagnostic performance and interobserver agreement of PI-RADS v2. Materials and Methods In this Institutional Review Board approved single-center retrospective study, 98 patients with clinically suspected PCa who underwent 3-T multiparametric MRI followed by MRI/TRUS fusion-guided prostate biopsy were included from June 2013 to February 2015. Two radiologists (R1 and R2) with 8 and 1 years of experience in abdominal radiology reviewed the MRI scans and assigned PI-RADS v2 scores in all prostate zones. PI-RADS v2 were compared to MRI/TRUS fusion-guided biopsy results, which were classified as negative, PCa, and significant PCa (sPCa). Results Sensitivity, specificity, NPV, PPV and accuracy for PCa was 85.7% (same for all metrics) for R1 and 81.6%, 79.6%, 81.2%, 80.0% and 80.6% for R2. For detecting sPCa, the corresponding values were 95.3%, 85.4%, 95.9%, 83.7% and 89.8% for R1 and 93.0%, 81.8%, 93.7%, 86.7% and 86.7% for R2. There was substantial interobserver agreement in assigning PI-RADS v2 score as negative (1, 2, 3) or positive (4, 5) (Kappa=0.78). On multivariate analysis, PI-RADS v2 (p <0.001) was the only independent predictor of sPCa compared with age, abnormal DRE, prostate volume, PSA and PSA density. Conclusions Our study population demonstrated that PI-RADS v2 had high diagnostic accuracy, substantial interobserver agreement, and it was the only independent predictor of sPCa.

Ipilimumab-induced colitis on FDG PET/CT.

A 52-year-old woman with metastatic melanoma was treated with ipilimumab. After 2 cycles of treatment, she developed watery diarrhea, sweats, and chills. An FDG PET/CT study demonstrated new FDG-avid (maximum standardized uptake value 15.6) diffuse colonic wall thickening, suggestive of ipilimumab-induced colitis. The patient was treated with systemic steroids, with subsequent resolution of her symptoms. Based on the response to steroids, the diagnosis of ipilimumab-induced enterocolitis was made. Ipilimumab may cause several immune-mediated toxicities, the most common of which is enterocolitis. Physicians interpreting FDG PET/CT examinations of patients treated with ipilimumab should be aware of these FDG-avid immune-mediated toxicities.