Stephanie Harmon

A Magnetic Resonance Imaging–Based Prediction Model for Prostate Biopsy Risk Stratification

Importance Multiparametric magnetic resonance imaging (MRI) in conjunction with MRI–transrectal ultrasound (TRUS) fusion-guided biopsies have improved the detection of prostate cancer. It is unclear whether MRI itself adds additional value to multivariable prediction models based on clinical parameters. Objective To determine whether an MRI-based prediction model can reduce unnecessary biopsies in patients with suspected prostate cancer. Design, Setting, and Participants Patients underwent MRI, MRI-TRUS fusion-guided biopsy, and 12-core systematic biopsy in 1 session. The development cohort used to derive the prediction model consisted of 400 patients from 1 institution enrolled between May 14, 2015, and August 31, 2016, and the validation cohort included 251 patients from 2 independent institutions who underwent biopsies between April 1, 2013, and June 30, 2016, at 1 institution and between July 1, 2015, and October 31, 2016, at the other institution. The MRI model included MRI-derived parameters in addition to clinical variables. Area under the curve of receiver operating characteristic curves and decision curve analysis were performed. Main Outcomes and Measures Risk of clinically significant prostate cancer on biopsy, defined as a Gleason score of 3u2009+u20094 or higher in at least 1 biopsy core. Results Overall, 193 (48.3%) of the 400 patients in the development cohort (mean [SD] age at biopsy, 64.3 [7.1] years) and 96 (38.2%) of the 251 patients in the validation cohort (mean [SD] age at biopsy, 64.9 [7.2] years) had clinically significant prostate cancer, defined as a Gleason score greater than or equal to 3u2009+u20094. By applying the model to the external validation cohort, the area under the curve increased from 64% to 84% compared with the baseline model (Pu2009<u2009.001). At a risk threshold of 20%, the MRI model had a lower false-positive rate than the baseline model (46% [95% CI, 32%-66%] vs 92% [95% CI, 70%-100%]), with only a small reduction in the true-positive rate (89% [95% CI, 85%-96%] vs 99% [95% CI, 89%-100%]). Eighteen of 100 fewer biopsies could have been performed, with no increase in the number of patients with missed clinically significant prostate cancers. Conclusions and Relevance The inclusion of MRI-derived parameters in a risk model could reduce the number of unnecessary biopsies while maintaining a high rate of diagnosis of clinically significant prostate cancers.

A Prospective Comparison of 18F-Sodium Fluoride PET/CT and PSMA-targeted 18F-DCFBC PET/CT in Metastatic Prostate Cancer

The purpose of this study was to compare the diagnostic performance of 18F-DCFBC PET/CT, a first-generation 18F-labeled prostate-specific membrane antigen (PSMA)–targeted agent, and 18F-NaF PET/CT, a sensitive marker of osteoblastic activity, in a prospective cohort of patients with metastatic prostate cancer. Methods: Twenty-eight prostate cancer patients with metastatic disease on conventional imaging prospectively received up to 4 PET/CT scans. All patients completed baseline 18F-DCFBC PET/CT and 18F-NaF PET/CT scans, and 23 patients completed follow-up imaging, with a median follow-up interval of 5.7 mo (range, 4.2–12.6 mo). Lesion detection was compared across the 2 PET/CT agents at each time point. Detection and SUV characteristics of each PET/CT agent were compared with serum prostate-specific antigen (PSA) levels and treatment status at the time of baseline imaging using nonparametric statistical testing (Spearman correlation, Wilcoxon rank). Results: Twenty-six patients had metastatic disease detected on 18F-NaF or 18F-DCFBC at baseline, and 2 patients were negative on both scans. Three patients demonstrated soft tissue–only disease. Of 241 lesions detected at baseline, 56 were soft-tissue lesions identified by 18F-DCFBC only and 185 bone lesions detected on 18F-NaF or 18F-DCFBC. 18F-NaF detected significantly more bone lesions than 18F-DCFBC (P < 0.001). Correlation of PSA with patient-level SUV metrics was strong in 18F-DCFBC (ρ > 0.5, P < 0.01) and poor in 18F-NaF (ρ < 0.3, P > 0.1). When PSA levels were combined with treatment status, patients with below-median levels of PSA (<2 ng/mL) on androgen deprivation therapy (n = 11) demonstrated more lesions on 18F-NaF than 18F-DCFBC (P = 0.02). In PSA greater than 2 ng/mL, patients on androgen deprivation therapy (n = 8) showed equal to or more lesions on 18F-DCFBC than on 18F-NaF. Conclusion: The utility of PSMA-targeting imaging in metastatic prostate cancer appears to depend on patient disease course and treatment status. Compared with 18F-NaF PET/CT, 18F-DCFBC PET/CT detected significantly fewer bone lesions in the setting of early or metastatic castrate-sensitive disease on treatment. However, in advanced metastatic castrate-resistant prostate cancer, 18F-DCFBC PET/CT shows good concordance with NaF PET/CT.

Clinical impact of PSMA-based 18F–DCFBC PET/CT imaging in patients with biochemically recurrent prostate cancer after primary local therapy

PurposeThe purpose of our study was to assess 18F–DCFBC PET/CT, a PSMA targeted PET agent, for lesion detection and clinical management of biochemical relapse in prostate cancer patients after primary treatment.MethodsThis is a prospective IRB-approved study of 68 patients with documented biochemical recurrence after primary local therapy consisting of radical prostatectomy (nxa0=xa050), post radiation therapy (nxa0=xa09) or both (nxa0=xa09), with negative conventional imaging. All 68 patients underwent whole-body 18F–DCFBC PET/CT, and 62 also underwent mpMRI within one month. Lesion detection with 18F–DCFBC was correlated with mpMRI findings and pre-scan PSA levels. The impact of 18F–DCFBC PET/CT on clinical management and treatment decisions was established after 6xa0months’ patient clinical follow-up.ResultsForty-one patients (60.3%) showed at least one positive 18F–DCFBC lesion, for a total of 79 lesions, 30 in the prostate bed, 39 in lymph nodes, and ten in distant sites. Tumor recurrence was confirmed by either biopsy (13/41 pts), serial CT/MRI (8/41) or clinical follow-up (15/41); there was no confirmation in five patients, who continue to be observed. The 18F–DCFBC and mpMRI findings were concordant in 39 lesions (49.4%), and discordant in 40 lesions (50.6%); the majority (nxa0=xa032/40) of the latter occurring because the recurrence was located outside the mpMRI field of view. 18F–DCFBC PET positivity rates correlated with PSA values and 15%, 46%, 83%, and 77% were seen in patients with PSA values <0.5, 0.5 to <1.0, 1.0 to <2.0, and ≥2.0xa0ng/mL, respectively. The optimal cut-off PSA value to predict a positive 18F–DCFBC scan was 0.78xa0ng/mL (AUCxa0=xa00.764). A change in clinical management occurred in 51.2% (21/41) of patients with a positive 18F–DCFBC result, generally characterized by starting a new treatment in 19 patients or changing the treatment plan in two patients.Conclusions18F–DCFBC detects recurrences in 60.3% of a population of patients with biochemical recurrence, but results are dependent on PSA levels. Above a threshold PSA value of 0.78xa0ng/mL, 18F–DCFBC was able to identify recurrence with high reliability. Positive 18F–DCFBC PET imaging led clinicians to change treatment strategy in 51.2% of patients.

Prospective comparison of PI-RADS version 2 and qualitative in-house categorization system in detection of prostate cancer: Prospective Comparison of PI-RADSv2

Prostate Imaging‐Reporting and Data System v. 2 (PI‐RADSv2) provides standardized nomenclature for interpretation of prostate multiparametric MRI (mpMRI). Inclusion of additional features for categorization may provide benefit to stratification of disease.

Can Apparent Diffusion Coefficient Values Assist PI-RADS Version 2 DWI Scoring? A Correlation Study Using the PI-RADSv2 and International Society of Urological Pathology Systems

OBJECTIVEnThe purposes of this study were to assess correlation of apparent diffusion coefficient (ADC) and normalized ADC (ratio of tumor to nontumor tissue) with the Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) and updated International Society of Urological Pathology (ISUP) categories and to determine how to optimally use ADC metrics for objective assistance in categorizing lesions within PI-RADSv2 guidelines.nnnMATERIALS AND METHODSnIn this retrospective study, 100 patients (median age, 62 years; range, 44-75 years; prostate-specific antigen level, 7.18 ng/mL; range, 1.70-84.56 ng/mL) underwent 3-T multiparametric MRI of the prostate with an endorectal coil. Mean ADC was extracted from ROIs based on subsequent prostatectomy specimens. Histopathologic analysis revealed 172 lesions (113 peripheral, 59 transition zone). Two radiologists blinded to histopathologic outcome assigned PI-RADSv2 categories. Kendall tau was used to correlate ADC metrics with PI-RADSv2 and ISUP categories. ROC curves were used to assess the utility of ADC metrics in differentiating each readers PI-RADSv2 DWI category 4 or 5 assessment in the whole prostate and by zone.nnnRESULTSnADC metrics negatively correlated with ISUP category in the whole prostate (ADC, τ = -0.21, p = 0.0002; normalized ADC, τ = -0.21, p = 0.0001). Moderate negative correlation was found in expert PI-RADSv2 DWI categories (ADC, τ = -0.34; normalized ADC, τ = -0.31; each p < 0.0001) maintained across zones. In the whole prostate, AUCs of ADC and normalized ADC were 87% and 82% for predicting expert PI-RADSv2 DWI category 4 or 5. A derived optimal cutoff ADC less than 1061 and normalized ADC less than 0.65 achieved positive predictive values of 83% and 84% for correct classification of PI-RADSv2 DWI category 4 or 5 by an expert reader. Consistent relations and predictive values were found by an independent novice reader.nnnCONCLUSIONnADC and normalized ADC inversely correlate with PI-RADSv2 and ISUP categories and can serve as quantitative metrics to assist with assigning PI-RADSv2 DWI category 4 or 5.

A Multireader Exploratory Evaluation of Individual Pulse Sequence Cancer Detection on Prostate Multiparametric Magnetic Resonance Imaging (MRI)

RATIONALE AND OBJECTIVESnTo determine independent contribution of each prostate multiparametric magnetic resonance imaging (mpMRI) sequence to cancer detection when read in isolation.nnnMATERIALS AND METHODSnProstate mpMRI at 3-Tesla with endorectal coil from 45 patients (nu2009=u200930 prostatectomy cases, nu2009=u200915 controls with negative magnetic resonance imaging [MRI] or biopsy) were retrospectively interpreted. Sequences (T2-weighted [T2W] MRI, diffusion-weighted imaging [DWI], and dynamic contrast-enhanced [DCE] MRI; Nu2009=u2009135) were separately distributed to three radiologists at different institutions. Readers evaluated each sequence blinded to other mpMRI sequences. Findings were correlated to whole-mount pathology. Cancer detection sensitivity, positive predictive value for whole prostate (WP), transition zone, and peripheral zone were evaluated per sequence by reader, with reader concordance measured by index of specific agreement. Cancer detection rates (CDRs) were calculated for combinations of independently read sequences.nnnRESULTSn44 patients were evaluable (cases median prostate-specific antigen 6.83 [ range 1.95-51.13] ng/mL, age 62 [45-71] years; controls prostate-specific antigen 6.85 [2.4-10.87] ng/mL, age 65.5 [47-71] years). Readers had highest sensitivity on DWI (59%) vs T2W MRI (48%) and DCE (23%) in WP. DWI-only positivity (DWI+/T2W-/DCE-) achieved highest CDR in WP (38%), compared to T2W-only (CDR 24%) and DCE-only (CDR 8%). DWI+/T2W+/DCE- achieved CDR 80%, an added benefit of 56.4% from T2W-only and of 42% from DWI-only (Pu2009<u2009.0001). All three sequences interpreted independently positive gave highest CDR of 90%. Reader agreement was moderate (index of specific agreement: T2Wu2009=u200954%, DWIu2009=u200958%, DCEu2009=u200933%).nnnCONCLUSIONSnWhen prostate mpMRI sequences are interpreted independently by multiple observers, DWI achieves highest sensitivity and CDR in transition zone and peripheral zone. T2W and DCE MRI both add value to detection; mpMRI achieves highest detection sensitivity when all three mpMRI sequences are positive.

Radiomics and radiogenomics of prostate cancer

Radiomics and radiogenomics are attractive research topics in prostate cancer. Radiomics mainly focuses on extraction of quantitative information from medical imaging, whereas radiogenomics aims to correlate these imaging features to genomic data. The purpose of this review is to provide a brief overview summarizing recent progress in the application of radiomics-based approaches in prostate cancer and to discuss the potential role of radiogenomics in prostate cancer.

Evaluating the size criterion for PI-RADSv2 category 5 upgrade: is 15 mm the best threshold?

PurposeThe purpose of the study was to determine if theu2009≥u200915xa0mm threshold currently used to define PIRADS 5 lesions is the optimal size threshold for predicting high likelihood of clinically significant (CS) cancers.MaterialsThree hundred and fifty-eight lesions that may be changed from category 4 to 5 or vice versa on the basis of the size criterion (category 4: nu2009=u2009288, category 5: nu2009=u200970) from 255 patients were evaluated. Kendall’s tau-b statistic accounting for inter-lesion correlation, generalized estimation equation logistic regression, and receiver operating curve analysis evaluated two lesion size-metrics (lesion diameter and relative lesion diameter—defined as lesion diameter/prostate volume) for ability to identify CS (Gleason gradeu2009≥u20093u2009+u20094) cancer at targeted biopsy. Optimal cut-points were identified using the Youden index. Analyses were performed for the whole prostate (WP) and zone-specific sub-cohorts of lesions in the peripheral and transition zones (PZ and TZ).ResultsLesion diameter showed a modest correlation with Gleason grade (WP: τBu2009=u20090.21, pu2009<u20090.0001; PZ: τBu2009=u20090.13, pu2009=u20090.02; TZ: τBu2009=u20090.32, pu2009=u20090.001), and association with CS cancer detection (WP: AUCu2009=u20090.63, PZ: AUCu2009=u20090.59, TZ: AUCu2009=u20090.74). Empirically derived thresholds (WP: 14xa0mm, PZ: 13xa0mm, TZ: 16xa0mm) performed similarly to the currentu2009≥u200915xa0mm standard. Lesion relative lesion diameter improved identification of CS cancers compared to lesion diameter alone (WP: τBu2009=u20090.30, PZ: τBu2009=u20090.24, TZ: τBu2009=u20090.42, all pu2009<u20090.0001). AUC also improved for WP and PZ lesions (WP: AUCu2009=u20090.70, PZ: AUCu2009=u20090.68, and TZ: AUCu2009=u20090.74).ConclusionsThe currentu2009≥u200915xa0mm diameter threshold is a reasonable delineator of PI-RADS category 4 and category 5 lesions in the absence of extraprostatic extension to predict CS cancers. Additionally, relative lesion diameter can improve identification of CS cancers and may serve as another option for distinguishing category 4 and 5 lesions.