Prostate Cancer Detection Rate of Freehand versus 3-Dimensional Template Mapping Biopsy Using a Magnetic Resonance Imaging-Ultrasound Fusion Device in Biopsy Naïve Men.

PURPOSE: Targeted prostate biopsy devices include a 3-dimensional digital template grid to guide systematic biopsy locations. Following a template could better ensure uniform and well distributed sampling of the prostate compared to the traditional freehand biopsy approach, possibly decreasing the chance of false-negative biopsy. Thus, we determined cancer detection rates obtained by conventional freehand systematic sampling vs template mapping sampling using a magnetic resonance imaging-ultrasound fusion device. MATERIALS AND METHODS: Men who underwent first line conventional or image guided prostate biopsy were identified retrospectively in an institutional review board approved protocol. Excluded from study were men with prior biopsy or treatment or fewer than 10 cores taken. Targeted cores obtained by image guided biopsy were censored from analysis to simulate systematic template biopsy. The resulting cancer detection rate was compared to that of conventional biopsy. RESULTS: We identified 1,582 patients between 2006 and 2014 who met the criteria for analysis, including 1,052 who underwent conventional biopsy and 530 who underwent template biopsy with a magnetic resonance imaging-ultrasound fusion device. Patient age, prostate specific antigen and the number of systematic cores were the same in the 2 groups. Template biopsy detected any prostate cancer in 257 of 530 men (48.5%) and clinically significant cancer in 196 (37.0%) while conventional biopsy detected any cancer in 432 of 1,052 (41.0%) (p=0.005) and clinically significant cancer in 308 (29.2%) (p=0.002). CONCLUSIONS: Template mapping systematic biopsy detected more prostate cancer than conventional sampling in biopsy naïve men. It is a promising cost-effective alternative to magnetic resonance imaging-ultrasound fusion biopsy as an upfront screening tool.

Using spatial tracking with magnetic resonance imaging/ultrasound-guided biopsy to identify unilateral prostate cancer.

OBJECTIVES: To create reliable predictive metrics of unilateral disease using spatial tracking from a fusion device, thereby improving patient selection for hemi-gland ablation of prostate cancer. PATIENTS AND METHODS: We identified patients who received magnetic resonance imaging (MRI)/ultrasound-guided biopsy and radical prostatectomy at a single institution between 2011 and 2018. In addition to standard clinical features, we extracted quantitative features related to biopsy core and MRI target locations predictive of tumour unilaterality. Classification and Regression Tree (CART) analysis was used to create a decision tree (DT) for identifying cancer laterality. We evaluated concordance of model-determined laterality with final surgical pathology. RESULTS: A total of 173 patients were identified with biopsy coordinates and surgical pathology available. Based on CART analysis, in addition to biopsy- and MRI-confirmed disease unilaterality, patients should be further screened for cancer detected within 7 mm of midline in a 40 mL prostate, which equates to the central third of any-sized prostate by radius. The area under the curve for this DT was 0.82. Standard diagnostics and the DT correctly identified disease laterality in 73% and 80% of patients, respectively (P = 0.13). Of the patients identified as unilateral by standard diagnostics, 47% had undetected contralateral disease or were otherwise incorrectly identified. This error rate was reduced to 17% (P = 0.01) with the DT. CONCLUSION: Using spatial tracking from fusion devices, a DT was more reliable for identifying laterality of prostate cancer compared to standard diagnostics. Patients with cancer detected within the central third of the prostate by radius are poor hemi-gland ablation candidates due to the risk of midline extension of tumour.

Bladder Cancer and Artificial Intelligence: Emerging Applications.

Bladder cancer is a common and heterogeneous disease that poses a significant burden to the patient and health care system. Major unmet needs include effective early detection strategy, imprecision of risk stratification, and treatment-associated morbidities. The existing clinical paradigm is imprecise, which results in missed tumors, suboptimal therapy, and disease progression. Artificial intelligence holds immense potential to address many unmet needs in bladder cancer, including early detection, risk stratification, treatment planning, quality assessment, and outcome prediction. Despite recent advances, extensive work remains to affirm the efficacy of artificial intelligence as a decision-making tool for bladder cancer management.

Optimizing cystoscopy and TURBT: enhanced imaging and artificial intelligence.

Diagnostic cystoscopy in combination with transurethral resection of the bladder tumour are the standard for the diagnosis, surgical treatment and surveillance of bladder cancer. The ability to inspect the bladder in its current form stems from a long chain of advances in imaging science and endoscopy. Despite these advances, bladder cancer recurrence and progression rates remain high after endoscopic resection. This stagnation is a result of the heterogeneity of cancer biology as well as limitations in surgical techniques and tools, as incomplete resection and provider-specific differences affect cancer persistence and early recurrence. An unmet clinical need remains for solutions that can improve tumour delineation and resection. Translational advances in enhanced cystoscopy technologies and artificial intelligence offer promising avenues to overcoming the progress plateau.

Inter-reader Agreement for Prostate Cancer Detection Using Micro-ultrasound: A Multi-institutional Study.

Background and objective: Micro-ultrasound (MUS) uses a high-frequency transducer with superior resolution to conventional ultrasound, which may differentiate prostate cancer from normal tissue and thereby allow targeted biopsy. Preliminary evidence has shown comparable sensitivity to magnetic resonance imaging (MRI), but consistency between users has yet to be described. Our objective was to assess agreement of MUS interpretation across multiple readers. Methods: After institutional review board approval, we prospectively collected MUS images for 57 patients referred for prostate biopsy after multiparametric MRI from 2022 to 2023. MUS images were interpreted by six urologists at four institutions with varying experience (range 2-6 yr). Readers were blinded to MRI results and clinical data. The primary outcome was reader agreement on the locations of suspicious lesions, measured in terms of Light's κ and positive percent agreement (PPA). Reader sensitivity for identification of grade group (GG) ≥2 prostate cancer was a secondary outcome. Key findings and limitations: Analysis revealed a κ value of 0.30 (95% confidence interval [CI] 0.21-0.39). PPA was 33% (95% CI 25-42%). The mean patient-level sensitivity for GG ≥2 cancer was 0.66 ± 0.05 overall and 0.87 ± 0.09 when cases with anterior lesions were excluded. Readers were 12 times more likely to detect higher-grade cancers (GG ≥3), with higher levels of agreement for this subgroup (κ 0.41, PPA 45%). Key limitations include the inability to prospectively biopsy reader-delineated targets and the inability of readers to perform live transducer maneuvers. Conclusions and clinical implications: Inter-reader agreement on the location of suspicious lesions on MUS is lower than rates previously reported for MRI. MUS sensitivity for cancer in the anterior gland is lacking. Patient summary: The ability to find cancer on imaging scans can vary between doctors. We found that there was frequent disagreement on the location of prostate cancer when doctors were using a new high-resolution scan method called micro-ultrasound. This suggests that the performance of micro-ultrasound is not yet consistent enough to replace MRI (magnetic resonance imaging) for diagnosis of prostate cancer.

The stanford prostate cancer calculator: Development and external validation of online nomograms incorporating PIRADS scores to predict clinically significant prostate cancer.

BACKGROUND: While multiparametric MRI (mpMRI) has high sensitivity for detection of clinically significant prostate cancer (CSC), false positives and negatives remain common. Calculators that combine mpMRI with clinical variables can improve cancer risk assessment, while providing more accurate predictions for individual patients. We sought to create and externally validate nomograms incorporating Prostate Imaging Reporting and Data System (PIRADS) scores and clinical data to predict the presence of CSC in men of all biopsy backgrounds. METHODS: Data from 2125 men undergoing mpMRI and MR fusion biopsy from 2014 to 2018 at Stanford, Yale, and UAB were prospectively collected. Clinical data included age, race, PSA, biopsy status, PIRADS scores, and prostate volume. A nomogram predicting detection of CSC on targeted or systematic biopsy was created. RESULTS: Biopsy history, Prostate Specific Antigen (PSA) density, PIRADS score of 4 or 5, Caucasian race, and age were significant independent predictors. Our nomogram-the Stanford Prostate Cancer Calculator (SPCC)-combined these factors in a logistic regression to provide stronger predictive accuracy than PSA density or PIRADS alone. Validation of the SPCC using data from Yale and UAB yielded robust AUC values. CONCLUSIONS: The SPCC combines pre-biopsy mpMRI with clinical data to more accurately predict the probability of CSC in men of all biopsy backgrounds. The SPCC demonstrates strong external generalizability with successful validation in two separate institutions. The calculator is available as a free web-based tool that can direct real-time clinical decision-making.

Use of MRI-Guided Biopsy for Selection and Follow-up of Men Undergoing Hemi-gland Cryoablation of Prostate Cancer.

OBJECTIVE: To investigate safety, efficacy, and quality of life impact of hemi-gland cryotherapy for clinically-significant prostate cancer (CaP), when patient selection and follow-up includes MRI-guided biopsy. METHODS: Twenty-nine men with unilateral CaP (all clinically significant with prostate volume <60 cc) were enrolled in a prospective observational trial of hemi-gland cryotherapy. Mean patient age was 68.7 years. Median prostate-specific antigen (PSA) was 6.6 ng/mL. MRI-guided biopsy (3T-MRI, Artemis US fusion) was used for diagnosis and repeated at 6-month follow-up in all men. Treatment was under general anesthesia using the BTG/Galil system. Validated questionnaires were used to determine effects of treatment on urinary and sexual function and quality of life. RESULTS: Cryotherapy was completed satisfactorily in all 29 cases in <60 minutes with no intraoperative complications. Significant decreases in PSA (median decrease 5.6 ng/mL) and PSA density (median decrease 0.14 ng/mL/cc) were observed (P < .01). At 6 months, 23 patients (79%) demonstrated no residual cancer on follow-up MRI-guided biopsy of the treated side. Three patients (10%) revealed micro-residual disease. Three patients (10%) had residual cancer and underwent further treatment. Ipsilateral MRI lesions were present before treatment in 26 patients and after treatment in only 2, reflecting the gross ablative effect; however, MRI showed disappearance of lesions in 4 patients with residual tumor on biopsy. The single complication was 1 case of transient urinary retention; 85% of men who were sexually active continued without change after treatment. Voiding function was unchanged. CONCLUSION: Hemi-gland cryoablation for clinically-significant CaP is well-tolerated, and when patients are selected and followed by MRI/US fusion biopsy, cancer control appears promising at 6 months.