Faculty Bibliography

PURPOSE/OBJECTIVE:Active surveillance is increasingly recommended for older men with low risk prostate cancer. Although older men have higher all cause mortality, they also have higher prostate cancer specific mortality. We hypothesized that older age is associated with an increased risk of Gleason score upgrading at confirmatory biopsy when controlling for prostate volume. MATERIALS AND METHODS/METHODS:We retrospectively reviewed data on 1,130 patients with prostate cancer who were treated with active surveillance from 1991 through 2011. We included 646 patients with clinical Gleason 6 or less, stage T2a or less prostate cancer, a confirmatory biopsy within 2 years of diagnostic biopsy and prostate magnetic resonance imaging before confirmatory biopsy. The primary outcome was Gleason score upgrading to 7 or greater on confirmatory biopsy. We used logistic regression to estimate the effect of age on upgrading, adjusting for magnetic resonance imaging prostate volume and other potential confounders. RESULTS:Median age was 66 years (IQR 61-72) and median magnetic resonance imaging prostate volume was 41 ml (IQR 29-55). At confirmatory biopsy disease was upgraded in 55 of 646 patients (9%) and unchanged in 290 (45%) and biopsy was negative in 297 (46%). Older age was associated with higher odds of upgrading (adjusted OR 1.05, 95% CI 1.01-1.09, p=0.009). Larger prostate volume was associated with lower odds of upgrading (adjusted OR 0.80/10 ml increase, 95% CI 0.7-0.9, p=0.012). CONCLUSIONS:Our findings suggest that older age is associated with an increased risk of misclassification on diagnostic biopsy. Older men who are interested in active surveillance should be counseled about the risks and benefits of confirmatory biopsy.

OBJECTIVE:The role of imaging in patients with suspected gynecologic malignancies is to provide an accurate diagnosis to achieve the best and most tailored treatment plan. Uncommon cancers pose a distinct challenge, because current knowledge of these diseases is still limited. Our purpose is to highlight the role of cross-sectional imaging techniques, including ultrasound, CT, MRI, and PET/CT, in the diagnosis and pretreatment stratification of patients with rare gynecologic cancers. CONCLUSION/CONCLUSIONS:This review shows the relevance of imaging findings for diagnosis, staging, and treatment planning in patients with uncommon uterine, cervical, vaginal, vulvar, and ovarian cancers.

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.

OBJECTIVE:Our aim was to evaluate the associations between quantitative (18)F-fluorodeoxyglucose positron-emission tomography (FDG-PET) uptake metrics, optimal debulking (OD) and progression-free survival (PFS) in patients with recurrent ovarian cancer undergoing secondary cytoreductive surgery. METHODS:Fifty-five patients with recurrent ovarian cancer underwent FDG-PET/CT within 90 days prior to surgery. Standardized uptake values (SUVmax), metabolically active tumour volumes (MTV), and total lesion glycolysis (TLG) were measured on PET. Exact logistic regression, Kaplan-Meier curves and the log-rank test were used to assess associations between imaging metrics, OD and PFS. RESULTS:MTV (p = 0.0025) and TLG (p = 0.0043) were associated with OD; however, there was no significant association between SUVmax and debulking status (p = 0.83). Patients with an MTV above 7.52 mL and/or a TLG above 35.94 g had significantly shorter PFS (p = 0.0191 for MTV and p = 0.0069 for TLG). SUVmax was not significantly related to PFS (p = 0.10). PFS estimates at 3.5 years after surgery were 0.42 for patients with an MTV ≤ 7.52 mL and 0.19 for patients with an MTV > 7.52 mL; 0.46 for patients with a TLG ≤ 35.94 g and 0.15 for patients with a TLG > 35.94 g. CONCLUSION/CONCLUSIONS:FDG-PET metrics that reflect metabolic tumour burden are associated with optimal secondary cytoreductive surgery and progression-free survival in patients with recurrent ovarian cancer. KEY POINTS/CONCLUSIONS:• Both TLG and MTV were associated with optimal tumour debulking. • There was no significant association between SUVmax and tumour debulking status. • Patients with higher MTV and/or TLG had significantly shorter PFS. • SUVmax was not significantly related to PFS.

OBJECTIVES/OBJECTIVE:To investigate Haralick texture analysis of prostate MRI for cancer detection and differentiating Gleason scores (GS). METHODS:One hundred and forty-seven patients underwent T2- weighted (T2WI) and diffusion-weighted prostate MRI. Cancers ≥0.5 ml and non-cancerous peripheral (PZ) and transition (TZ) zone tissue were identified on T2WI and apparent diffusion coefficient (ADC) maps, using whole-mount pathology as reference. Texture features (Energy, Entropy, Correlation, Homogeneity, Inertia) were extracted and analysed using generalized estimating equations. RESULTS:PZ cancers (n = 143) showed higher Entropy and Inertia and lower Energy, Correlation and Homogeneity compared to non-cancerous tissue on T2WI and ADC maps (p-values: <.0001-0.008). In TZ cancers (n = 43) we observed significant differences for all five texture features on the ADC map (all p-values: <.0001) and for Correlation (p = 0.041) and Inertia (p = 0.001) on T2WI. On ADC maps, GS was associated with higher Entropy (GS 6 vs. 7: p = 0.0225; 6 vs. >7: p = 0.0069) and lower Energy (GS 6 vs. 7: p = 0.0116, 6 vs. >7: p = 0.0039). ADC map Energy (p = 0.0102) and Entropy (p = 0.0019) were significantly different in GS ≤3 + 4 versus ≥4 + 3 cancers; ADC map Entropy remained significant after controlling for the median ADC (p = 0.0291). CONCLUSION/CONCLUSIONS:Several Haralick-based texture features appear useful for prostate cancer detection and GS assessment. KEY POINTS/CONCLUSIONS:• Several Haralick texture features may differentiate non-cancerous and cancerous prostate tissue. • Tumour Energy and Entropy on ADC maps correlate with Gleason score. • T2w-image-derived texture features are not associated with the Gleason score.

OBJECTIVE:The aim of this study was to evaluate the incremental prognostic value of pelvic magnetic resonance imaging (MRI) and whole-body F-fluorodeoxyglucose positron emission tomography/computed tomography (PET/CT) findings compared with clinical-histopathologic factors in patients with newly diagnosed cervical cancer. METHODS:The institutional review board approved this retrospective study of 114 patients (median age, 40.6 years) with International Federation of Gynecology and Obstetrics (FIGO) stage I-IVB cervical cancer who underwent pretreatment MRI and PET/CT. All scans were reviewed for locoregional tumor extent, pelvic or/and para-aortic lymphadenopathy, and distant metastases. Univariate Cox proportional hazard regression was performed to evaluate associations between clinical-histopathologic factors, imaging findings, and progression-free survival (PFS). Multivariate models were built using independent predictors for PFS. Harrell C was used to measure concordance (C index). RESULTS:Forty patients progressed within a median time of 10.4 months (range, 0.4-40.3 months). At univariate analysis, age, FIGO stage, tumor histology, tumor grade, and all MRI and PET/CT features were significantly associated with PFS (P < 0.0001 to P = 0.0474). A multivariate model including clinical and imaging parameters (parametrial invasion on MRI and para-aortic lymphadenopathy/distant metastases on PET/CT) had significantly higher concordance for predicting PFS than a model including clinical parameters only (C index: 0.81 [95% confidence interval, 0.75-0.87] vs 0.68 [95% confidence interval, 0.59-0.78]; P < 0.001). The comparison of C indices for the combined clinical and imaging model approached significance when compared with a FIGO stage model (C index: 0.81 [95% confidence interval, 0.75-0.87] vs 0.75 [95% confidence interval, 0.69-0.82]; P = 0.058). CONCLUSIONS:In patients with newly diagnosed cervical cancer, a prognostic model including combined MRI and PET/CT findings provides information that complements clinical and histopathologic factors.