Faculty Bibliography

PURPOSE:Accurate identification of the source of a detectable serum prostate-specific antigen (PSA) in the postprostatectomy setting is a major challenge among the urologic community. The aim of this study was to assess positivity rates of imaging examinations performed in patients with early PSA rise after prostatectomy and to summarize the management strategies adopted in this clinical scenario. METHODS:F-sodium fluoride-PET/CT at a single tertiary cancer center. Imaging results were summarized per modality and compared with pathology findings. RESULTS:Pelvic MRI was positive in 15/142 (11%) patients (14 patients with local recurrence in the surgical bed and 1 patient with pelvic osseous metastases). Of these 15, 10 patients underwent additional imaging examinations; none revealed positive findings. Of the 127 patients with negative pelvic MRI, 54 (43%) underwent additional imaging examinations; only 1/54 had positive findings (false-positive T8 lesion on bone scintigraphy and FDG-PET/CT; biopsy was negative for cancer). Overall, 12/16 patients with positive imaging findings and 75/126 (60%) patients with negative imaging received treatment (radiation, hormones or chemotherapy). CONCLUSION:The conventional imaging identified sites of disease, almost always in the form of local recurrence, in a minority of patients with early PSA rise postprostatectomy.

OBJECTIVE:To investigate the multiparametric prostate magnetic resonance imaging (mpMRI) findings in patients treated with testosterone replacement therapy (TRT) while on active surveillance for low-risk prostate cancer. METHODS:We retrospectively reviewed 12 patients who underwent mpMRI before and after TRT while on active surveillance. Changes in serum testosterone level, prostate-specific antigen (PSA), prostate biopsy findings, prostate volume, and Prostate Imaging Reporting and Data System Version 2 (PI-RADSv2) score before and after TRT were summarized. RESULTS:). In total, 2 patients had biopsy progression during the study period. The PI-RADSv2 scores before and after TRT were unchanged in 10/12 patients; none of these demonstrated biopsy progression on post-TRT. The PI-RADSv2 scores increased after TRT in 2/12 patients; both showed Gleason score upgrade on follow-up biopsy. Of these 2 patients, 1 patient underwent radical treatment due to clinical progression. The area under the curve for detecting biopsy progression calculated from PI-RADSv2 score after TRT was 0.90, which was better than that calculated from post-TRT PSA level (0.48). CONCLUSIONS:After TRT, mpMRI findings remained stable in patients without biopsy progression, whereas PI-RADSv2 score increase was identified in patients with Gleason score upgrade on follow-up biopsy.

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.

OBJECTIVES/OBJECTIVE:To evaluate if computed tomographic (CT) features of intradiverticular bladder cancer can predict clinical outcome. METHODS:Retrospective study of 34 patients with intradiverticular bladder cancer. Two radiologists independently evaluated all CT exams. RESULTS:CT tumor length and width were significantly associated with survival for both readers [hazard ratios (HRs) 1.31-1.62, P<.001-.043]. No other tumor features were significantly associated with survival. The interreader agreement for the assessment of CT features was fair to substantial (k=0.34-0.78, concordance correlation coefficient=0.56-0.66). There was no association between transurethral resection pathology stage and survival (HR 2.10, P=.21). CONCLUSIONS:In patients with intradiverticular bladder cancer, the tumor length and width measured on the pretreatment CT predicted survival.

PURPOSE/OBJECTIVE:To develop a preoperative CT-based nomogram for predicting overall survival (OS) in patients with non-endometrioid carcinomas of the uterine corpus. METHODS:Waiving informed consent, the institutional review board approved this HIPAA-compliant, retrospective study of 193 women with histopathologically proven uterine papillary serous carcinomas (UPSC), uterine clear cell carcinomas (UCCC), and uterine carcinosarcomas (UCS) who underwent primary surgical resection between May 1998 and December 2011, and had a preoperative CT ≤ 6 weeks before surgery. All CT scans were reviewed for local or/and regional tumor extent, presence of pelvic or/and para-aortic adenopathy, and presence of distant metastases. Univariate survival analysis was performed using log-rank test and Cox regression. Variables shown significant by the univariate analysis were evaluated with the multivariable Cox regression analysis and the results were used to create a nomogram for predicting OS. The predictive accuracy of the nomogram was assessed with the concordance probability index (c-index) and a 3-year calibration plot. RESULTS:Mean patient age was 67.2 years (range 49.0-85.9); histologies included UPSC (n = 116), UCCC (n = 27), and UCS (n = 50). Median follow-up was 38.1 months (0.9-168.5 months). At multivariate analysis, patient age, ascites, and omental implants on CT were significant adverse predictors of OS and were used to build the nomogram. Concordance index for the nomogram was 0.640 ± 0.028. CONCLUSION/CONCLUSIONS:We developed a nomogram with a good concordance probability at predicting OS based on readily available pretreatment clinical and imaging characteristics. This preoperative nomogram has the potential to improve initial treatment planning and patient counseling.

UNLABELLED:The epidemiology of prostate cancer has dramatically changed since the introduction of prostate-specific antigen (PSA) screening in the 1980's. Most prostate cancers today are detected at early stages of the disease and are considered 'indolent'; however, some patients' prostate cancers demonstrate a more aggressive behaviour which leads to rapid progression and death. Increasing understanding of the biology underlying the heterogeneity that characterises this disease has led to a continuously evolving role of imaging in the management of prostate cancer. Functional and metabolic imaging techniques are gaining importance as the impact on the therapeutic paradigm has shifted from structural tumour detection alone to distinguishing patients with indolent tumours that can be managed conservatively (e.g., by active surveillance) from patients with more aggressive tumours that may require definitive treatment with surgery or radiation. In this review, we discuss advanced imaging techniques that allow direct visualisation of molecular interactions relevant to prostate cancer and their potential for translation to the clinical setting in the near future. The potential use of imaging to follow molecular events during drug therapy as well as the use of imaging agents for therapeutic purposes will also be discussed. KEY POINTS/CONCLUSIONS:• Advanced imaging techniques allow direct visualisation of molecular interactions in prostate cancer. • MRI/PET, optical and Cerenkov imaging facilitate the translation of molecular biology. • Multiple compounds targeting PSMA expression are currently undergoing clinical translation. • Other targets (e.g., PSA, prostate-stem cell antigen, GRPR) are in development.

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.

PURPOSE/OBJECTIVE:The use of multivariable clinical models to assess postoperative prognosis in ovarian cancer increased. All published models incorporate surgical debulking. However, postoperative CT can detect residual disease (CT-RD) in 40% of optimally resected patients. The aim of our study was to investigate the added value of incorporating CT-RD evaluation into clinical models for assessment of overall survival (OS) and progression free survival (PFS) in patients after primary cytoreductive surgery (PCS). METHODS:212 women with PCS for advanced ovarian cancer between 01/1997 and 12/2011, and a contrast enhanced abdominal CT 1-7 weeks after surgery were included in this IRB approved retrospective study. Two radiologists blinded to clinical data, evaluated all CT for the presence of CT-RD, and Cohen's kappa assessed agreement. Cox proportional hazards regression with stepwise selection was used to develop OS and PFS models, with CT-RD incorporated afterwards. Model fit was assessed with bootstrapped Concordance Probability Estimates (CPE), accounting for over-fitting bias by correcting the initial estimate after repeated subsampling. RESULTS:Readers agreed on the majority of cases (179/212, k=0.68). For OS and PFS, CT-RD was significant after adjusting for clinical factors with a CPE 0.663 (p=0.0264) and 0.649 (p=0.0008). CT-RD was detected in 37% of patients assessed as optimally debulked (RD<1cm) and increased the risk of death (HR: 1.58, 95% CI: 1.06-2.37%). CONCLUSION/CONCLUSIONS:CT-RD is a significant predictor after adjusting for clinical factors for both OS and PFS. Incorporating CT-RD into the clinical model improved the prediction of OS and PFS in patients after PCS for advanced ovarian cancer.