Background: PSMA PET radiomics is a promising tool for primary prostate cancer (PCa) characterisation. However, small single-centre studies and lack of external validation hinder definitive conclusions on the potential of PSMA PET radiomics in the initial workup of PCa. We aimed to validate a radiomics signature in a larger internal cohort and in an external cohort from a separate centre. Methods: One hundred and twenty-seven PCa patients were retrospectively enrolled across two independent hospitals. The first centre (IRCCS San Raffaele Scientific Institute, Centre 1) contributed 62 [68Ga]Ga-PSMA-11 PET scans, 20 patients classified as low-grade (ISUP grade < 4), and 42 as high-grade (ISUP grade ≥ 4). The second centre (Stanford University Hospital, Centre 2) provided 65 [68Ga]Ga-PSMA-11 PET scans, and 49 low-grade and 16 high-grade patients. A radiomics model previously generated in Centre 1 was tested on the two cohorts separately and afterward on the entire dataset. Then, we evaluated whether the radiomics features selected in the previous investigation could generalise to new data. Several machine learning (ML) models underwent training and testing using 100-fold Monte Carlo cross-validation, independently at both Centre 1 and Centre 2, with a 70–30% train–test split. Additionally, models were trained in one centre and tested in the other, and vice versa. Furthermore, data from both centres were combined for training and testing using Monte Carlo cross-validation. Finally, a new radiomics signature built on this bicentric dataset was proposed. Several performance metrics were computed. Results: The previously generated radiomics signature resulted in an area under the receiver operating characteristic curve (AUC) of 80.4% when tested on Centre 1, while it generalised poorly to Centre 2, where it reached an AUC of 62.7%. When the whole cohort was considered, AUC was 72.5%. Similarly, new ML models trained on the previously selected features yielded, at best, an AUC of 80.9% for Centre 1 and performed at chance for Centre 2 (AUC of 49.3%). A new signature built on this bicentric dataset reached, at best, an average AUC of 91.4% in the test set. Conclusions: The satisfying performance of radiomics models when used in the original development settings, paired with the poor performance otherwise observed, emphasises the need to consider centre-specific factors and dataset characteristics when developing radiomics models. Combining radiomics datasets is a viable strategy to reduce such centre-specific biases, but external validation is still needed.

You have accessJournal of UrologyBladder Cancer: Non-invasive IV (MP71)1 May 2024MP71-19 ULTRASENSITIVE URINARY LIQUID BIOPSY ANALYSIS FOR BCG RESPONSE ASSESSMENT IN HIGH-RISK NON-MUSCLE INVASIVE BLADDER CANCER William Y. Shi, Kevin J. Liu, Mohammad S. Esfahani, Joseph G. Schroers-Martin, Monica Nesselbush, Simon B. Chen, Stefan K. Alig, Patrick Mullane, Kathleen E. Mach, Ludimila Trabanino, Timothy J. Lee, Ihna Yoo, Vinh La, Gabriela Rodriguez, Zachary Kornberg, Eugene Shkolyar, Harcharan Gill, Alan Thong, Jay B. Shah, Kris Prado, Eila C. Skinner, Ash A. Alizadeh, Joseph C. Liao, and Maximilian Diehn William Y. ShiWilliam Y. Shi , Kevin J. LiuKevin J. Liu , Mohammad S. EsfahaniMohammad S. Esfahani , Joseph G. Schroers-MartinJoseph G. Schroers-Martin , Monica NesselbushMonica Nesselbush , Simon B. ChenSimon B. Chen , Stefan K. AligStefan K. Alig , Patrick MullanePatrick Mullane , Kathleen E. MachKathleen E. Mach , Ludimila TrabaninoLudimila Trabanino , Timothy J. LeeTimothy J. Lee , Ihna YooIhna Yoo , Vinh LaVinh La , Gabriela RodriguezGabriela Rodriguez , Zachary KornbergZachary Kornberg , Eugene ShkolyarEugene Shkolyar , Harcharan GillHarcharan Gill , Alan ThongAlan Thong , Jay B. ShahJay B. Shah , Kris PradoKris Prado , Eila C. SkinnerEila C. Skinner , Ash A. AlizadehAsh A. Alizadeh , Joseph C. LiaoJoseph C. Liao , and Maximilian DiehnMaximilian Diehn View All Author Informationhttps://doi.org/10.1097/01.JU.0001009548.76580.ba.19AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Standard-of-care treatment for high-risk non-muscle invasive bladder cancer (NMIBC) is transurethral resection of bladder tumor (TURBT) followed by adjuvant Bacillus Calmette-Guérin (BCG), yet monitoring response is challenging. Noninvasive biomarkers such as urinary tumor DNA (utDNA) could improve assessment of NMIBC recurrence after BCG. We have developed a liquid biopsy assay called urinary Cancer Personalized Profiling by Deep Sequencing (uCAPP-Seq) which has a limit of detection of∼1 part per 10,000 (0.01%). Here, we investigated if uCAPP-Seq utDNA detection can identify responses to BCG in NMIBC. METHODS: We applied tumor-informed uCAPP-Seq to 120 urine specimens from 45 prospectively enrolled high-risk NMIBC patients undergoing BCG induction. GU pathologists annotated tumor and adjacent normal tissue, and DNA was extracted from 1 mm biopsy cores from FFPE blocks. Urine samples were collected prior to TURBT (n=30) and BCG induction (n=45), and at first follow-up after BCG (n=45). The primary endpoint was high-grade recurrence-free survival (HGRFS). RESULTS: uCAPP-Seq analysis identified three major categories of utDNA molecular responses to BCG immunotherapy: 1) utDNA complete response to TURBT (51%; n=23/45 patients), 2) utDNA response to BCG (22%; n=10/45), and 3) no utDNA response (27%; n=12/45) (Fig 1A). Levels of utDNA following BCG were significantly higher in patients with high-grade recurrence (p<0.0001) (Fig 1B). On Kaplan-Meier analysis, patients with persistent utDNA had significantly worse HGRFS compared to patients with responses to TURBT (HR 5.13, 95% CI 1.7-16.5, p=0.0005), and patients with responses to BCG (HR 13.25, 95% CI 4.0-43.7, p=0.0023) (Fig 1C). In patients with utDNA response to BCG, only 10% (n=1/10 patients) experienced high-grade recurrence (Fig 1D). CONCLUSIONS: Detection of utDNA via uCAPP-Seq identifies three types of molecular responses to TURBT and BCG in NMIBC. Molecular response to TURBT and BCG were strongly associated with freedom from high-grade recurrence. About half of patients had complete molecular responses to TURBT, suggesting a significant subset may have been cured by surgery alone. Liquid biopsy detection of utDNA is therefore a promising biomarker for developing personalized treatment strategies for NMIBC. Download PPT Source of Funding: This work is supported by the National Institutes of Health/National Cancer Institute (1R01CA244526) © 2024 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 211Issue 5SMay 2024Page: e1169 Advertisement Copyright & Permissions© 2024 by American Urological Association Education and Research, Inc.Metrics Author Information William Y. Shi More articles by this author Kevin J. Liu More articles by this author Mohammad S. Esfahani More articles by this author Joseph G. Schroers-Martin More articles by this author Monica Nesselbush More articles by this author Simon B. Chen More articles by this author Stefan K. Alig More articles by this author Patrick Mullane More articles by this author Kathleen E. Mach More articles by this author Ludimila Trabanino More articles by this author Timothy J. Lee More articles by this author Ihna Yoo More articles by this author Vinh La More articles by this author Gabriela Rodriguez More articles by this author Zachary Kornberg More articles by this author Eugene Shkolyar More articles by this author Harcharan Gill More articles by this author Alan Thong More articles by this author Jay B. Shah More articles by this author Kris Prado More articles by this author Eila C. Skinner More articles by this author Ash A. Alizadeh More articles by this author Joseph C. Liao More articles by this author Maximilian Diehn More articles by this author Expand All Advertisement PDF downloadLoading ...

Purpose:Patients treated with radical cystectomy experience a high rate of postoperative complications and frequent hospital readmissions. We sought to explore the utility of the Care Assessment Need (CAN) score, derived from electronic health data, to estimate the risk of these adverse clinical outcomes, thereby aiding patient counseling and informed treatment decision-making.Materials and Methods:We retrospectively examined data from 982 patients with bladder cancer who underwent radical cystectomy between 2013 and 2018 within the national Veterans Health Administration system. We tested for associations between the preoperative CAN score and length of stay, discharge location, and readmission rates.Results:We observed a correlation between higher CAN scores and longer hospital stays (adjusted relative risk = 1.03 [95% CI: 1.02-1.05]). An increased CAN score was also linked to greater odds of discharge to a skilled nursing facility or death (adjusted odds ratio = 1.16 [95% CI: 1.06-1.26]). Furthermore, the score was associated with hospital readmission at both 30 and 90 days postdischarge (adjusted HR = 1.03 [95% CI: 1.00-1.07] and 1.04 [95% CI: 1.00-1.07], respectively).Conclusions:The CAN score is associated with length of hospital stay, discharge to a skilled nursing facility, and readmission within 30 and 90 days after radical cystectomy. These findings highlight the potential of health care systems leveraging electronic health records for automatically calculating multidimensional tools, such as the CAN score, to identify patients at risk of adverse clinical outcomes after radical cystectomy.

Visual Abstract Prostate-specific membrane antigen (PSMA) PET offers an accuracy superior to other imaging modalities in initial staging of prostate cancer and is more likely to affect management. We examined the prognostic value of 68Ga-PSMA-11 uptake in the primary lesion and presence of metastatic disease on PET in newly diagnosed prostate cancer patients before initial therapy. Methods: In a prospective study from April 2016 to December 2020, 68Ga-PSMA-11 PET/MRI was performed in men with a new diagnosis of intermediate- or high-grade prostate cancer who were candidates for prostatectomy. Patients were followed up after initial therapy for up to 5 y. We examined the Kendall correlation between PET (intense uptake in the primary lesion and presence of metastatic disease) and clinical and pathologic findings (grade group, extraprostatic extension, nodal involvement) relevant for risk stratification, and examined the relationship between PET findings and outcome using Kaplan–Meier analysis. Results: Seventy-three men (age, 64.0 ± 6.3 y) were imaged. Seventy-two had focal uptake in the prostate, and in 20 (27%) PSMA-avid metastatic disease was identified. Uptake correlated with grade group and prostate-specific antigen (PSA). Presence of PSMA metastasis correlated with grade group and pathologic nodal stage. PSMA PET had higher per-patient positivity than nodal dissection in patients with only 5–15 nodes removed (8/41 vs. 3/41) but lower positivity if more than 15 nodes were removed (13/21 vs. 10/21). High uptake in the primary lesion (SUVmax > 12.5, P = 0.008) and presence of PSMA metastasis (P = 0.013) were associated with biochemical failure, and corresponding hazard ratios for recurrence within 2 y (4.93 and 3.95, respectively) were similar to or higher than other clinicopathologic prognostic factors. Conclusion: 68Ga-PSMA-11 PET can risk-stratify patients with intermediate- or high-grade prostate cancer before prostatectomy based on degree of uptake in the prostate and presence of metastatic disease.

BACKGROUND:Patients with chronic kidney disease (CKD) are poor candidates for standard treatments for muscle-invasive bladder cancer (MIBC) and may be more likely to experience adverse outcomes when diagnosed with MIBC. OBJECTIVE:To investigate factors associated with the development of advanced CKD following radical cystectomy. DESIGN SETTING AND PARTICIPANTS:Using national Veterans Health Administration utilization files, we identified 3360 patients who underwent radical cystectomy for MIBC between 2004 and 2018. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS:We examined factors associated with the development of advanced CKD (estimated glomerular filtration rate [eGFR] of <30 ml/min/1.73 m2) after radical cystectomy using multivariable logistic and proportional hazard regression, with and without consideration of competing risks. We examined survival using Kaplan-Meier product limit estimates and proportional hazard regression. RESULTS AND LIMITATIONS:The median age at surgery was 67 yr and the mean preoperative eGFR was 69.1 ± 20.3 ml/min/1.73 m2. Approximately three out of ten patients (n = 962, 29%) progressed to advanced CKD within 12 mo. Older age (hazard ratio [HR] per 5-yr increase 1.15, 95% confidence interval [CI] 1.10-1.20), preoperative hydronephrosis (HR 1.50, 95% CI 1.29-1.76), adjuvant chemotherapy (HR 1.19, 95% CI 1.00-1.41), higher comorbidity index (HR 1.13, 95% CI 1.11-1.16 per point), and lower baseline kidney function (HR 0.75, 95% CI 0.73-0.78) were associated with the development of advanced CKD. Baseline kidney function at the time of surgery was associated with survival. Generalizability is limited due to the predominantly male cohort. CONCLUSIONS:Impaired kidney function at baseline is associated with progression to advanced CKD and mortality after radical cystectomy. Preoperative kidney function should be incorporated into risk stratification algorithms for patients undergoing radical cystectomy. PATIENT SUMMARY:Impaired kidney function at baseline is associated with progression to advanced chronic kidney disease and mortality after radical cystectomy.

Visual Abstract Targeting of lesions seen on multiparametric MRI (mpMRI) improves prostate cancer (PC) detection at biopsy. However, 20%–65% of highly suspicious lesions on mpMRI (PI-RADS [Prostate Imaging-Reporting and Data System] 4 or 5) are false-positives (FPs), while 5%–10% of clinically significant PC (csPC) are missed. Prostate-specific membrane antigen (PSMA) and gastrin-releasing peptide receptors (GRPRs) are both overexpressed in PC. We therefore aimed to evaluate the potential of 68Ga-PSMA11 and 68Ga-RM2 PET/MRI for biopsy guidance in patients with suspected PC. Methods: A highly selective cohort of 13 men, aged 58.0 ± 7.1 y, with suspected PC (persistently high prostate-specific antigen [PSA] and PSA density) but negative or equivocal mpMRI results or negative biopsy were prospectively enrolled to undergo 68Ga-PSMA11 and 68Ga-RM2 PET/MRI. PET/MRI included whole-body and dedicated pelvic imaging after a delay of 20 min. All patients had targeted biopsy of any lesions seen on PET followed by standard 12-core biopsy. The SUVmax of suspected PC lesions was collected and compared with gold standard biopsy. Results: PSA and PSA density at enrollment were 9.8 ± 6.0 (range, 1.5–25.5) ng/mL and 0.20 ± 0.18 (range, 0.06–0.68) ng/mL2, respectively. Standardized systematic biopsy revealed a total of 14 PCs in 8 participants: 7 were csPC and 7 were nonclinically significant PC (ncsPC). 68Ga-PSMA11 identified 25 lesions, of which 11 (44%) were true-positive (TP) (5 csPC). 68Ga-RM2 showed 27 lesions, of which 14 (52%) were TP, identifying all 7 csPC and also 7 ncsPC. There were 17 concordant lesions in 11 patients versus 14 discordant lesions in 7 patients between 68Ga-PSMA11 and 68Ga-RM2 PET. Incongruent lesions had the highest rate of FP (12 FP vs. 2 TP). SUVmax was significantly higher for TP than FP lesions in delayed pelvic imaging for 68Ga-PSMA11 (6.49 ± 4.14 vs. 4.05 ± 1.55, P = 0.023) but not for whole-body images, nor for 68Ga-RM2. Conclusion: Our results show that 68Ga-PSMA11 and 68Ga-RM2 PET/MRI are feasible for biopsy guidance in suspected PC. Both radiopharmaceuticals detected additional clinically significant cancers not seen on mpMRI in this selective cohort. 68Ga-RM2 PET/MRI identified all csPC confirmed at biopsy.

68Ga-RM2 targets gastrin-releasing peptide receptors (GRPRs), which are overexpressed in prostate cancer (PC). Here, we compared preop-erative 68Ga-RM2 PET to postsurgery histopathology in patients with newly diagnosed intermediate-or high-risk PC.Methods: Forty-one men, 64.0 +/- 6.7 y old, were prospectively enrolled. PET images were acquired 42-72 min (median +/- SD, 52.5 +/- 6.5 min) after injection of 118.4-247.9 MBq (median +/- SD, 138.0 +/- 22.2 MBq) of 68Ga-RM2. PET findings were compared with preoperative multiparametric MRI (mpMRI) (n = 36) and 68Ga-PSMA11 PET (n = 17) and correlated to postprostatectomy whole-mount histopathology (n = 32) and time to biochemical recurrence. Nine participants decided to undergo radiation therapy after study enrollment.Results: All participants had inter- mediate-(n = 17) or high-risk (n = 24) PC and were scheduled for prostatectomy. Prostate-specific antigen was 8.8 +/- 77.4 (range, 2.5-504) and 7.6 +/- 5.3 ng/mL (range, 2.5-28.0 ng/mL) when partici-pants who ultimately underwent radiation treatment were excluded. Preoperative 68Ga-RM2 PET identified 70 intraprostatic foci of uptake in 40 of 41 patients. Postprostatectomy histopathology was available in 32 patients in which 68Ga-RM2 PET identified 50 of 54 intraprostatic lesions (detection rate = 93%). 68Ga-RM2 uptake was recorded in 19 nonenlarged pelvic lymph nodes in 6 patients. Pathology confirmed lymph node metastases in 16 lesions, and follow-up imaging con-firmed nodal metastases in 2 lesions. 68Ga-PSMA11 and 68Ga-RM2 PET identified 27 and 26 intraprostatic lesions, respectively, and 5 pel-vic lymph nodes each in 17 patients. Concordance between 68Ga-RM2 and 68Ga-PSMA11 PET was found in 18 prostatic lesions in 11 patients and 4 lymph nodes in 2 patients. Noncongruent findings were observed in 6 patients (intraprostatic lesions in 4 patients and nodal lesions in 2 patients). Sensitivity and accuracy rates for 68Ga-RM2 and 68Ga-PSMA11 (98% and 89% for 68Ga-RM2 and 95% and 89% for 68Ga-PSMA11) were higher than those for mpMRI (77% and 77%, respectively). Specificity was highest for mpMRI with 75% followed by 68Ga-PSMA11 (67%) and 68Ga-RM2 (65%).Conclusion: 68Ga-RM2 PET accurately detects intermediate-and high-risk primary PC, with a detection rate of 93%. In addition, 68Ga-RM2 PET showed signifi-cantly higher specificity and accuracy than mpMRI and a performance similar to 68Ga-PSMA11 PET. These findings need to be confirmed in larger studies to identify which patients will benefit from one or the other or both radiopharmaceuticals.

You have accessJournal of UrologyProstate Cancer: Detection & Screening IV (MP43)1 Sep 2021MP43-02 LESSONS LEARNED IN APPLYING DEEP LEARNING TO FACILITATE PROSTATE MR-US FUSION BIOPSY WORKFLOW Simon John Christoph Soerensen, Richard E. Fan, Wei Shao, Indrani Bhattacharya, Arun Seetharaman, Michael Borre, Alan Thong, Katherine To’o, Mirabela Rusu, and Geoffrey A. Sonn Simon John Christoph SoerensenSimon John Christoph Soerensen More articles by this author , Richard E. FanRichard E. Fan More articles by this author , Wei ShaoWei Shao More articles by this author , Indrani BhattacharyaIndrani Bhattacharya More articles by this author , Arun SeetharamanArun Seetharaman More articles by this author , Michael BorreMichael Borre More articles by this author , Alan ThongAlan Thong More articles by this author , Katherine To’oKatherine To’o More articles by this author , Mirabela RusuMirabela Rusu More articles by this author , and Geoffrey A. SonnGeoffrey A. Sonn More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002064.02AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Targeted biopsy improves prostate cancer diagnosis. Accurate prostate gland segmentation on MRI is critical for accurate biopsy. Manual gland segmentation performed by urologists or radiologists is tedious and time-consuming. To address this clinical problem, we sought to develop a deep learning model to rapidly and accurately segment the prostate on MRI and to implement it as part of routine MR-US fusion biopsy in the clinic. METHODS: 905 subjects underwent multiparametric MRI at 29 institutions, followed by MR-US fusion biopsy at one institution. A urologic oncology expert segmented the prostate on axial T2-weighted MRI scans for all cases. We trained a deep learning model, ProGNet, on 805 cases. We retrospectively tested ProGNet on 100 independent internal and 56 external cases. We then prospectively implemented ProGNet as part of the fusion biopsy workflow for 11 patients. We compared ProGNet performance to two deep learning networks (U-Net and HED) and radiology technicians. The Dice similarity coefficient (DSC) was used to measure overlap with expert segmentations. The DSC is widely used to evaluate overlap in segmentation tasks; its value ranges from 0 to 1. A DSC of 1 indicates perfect overlap between segmentations, while 0 indicates no overlap. DSCs were compared using paired t-tests. We are expanding our model's use to provide gland segmentations for all biopsy cases as an initial step in the fusion biopsy workflow. RESULTS: ProGNet (DSC=0.92) outperformed U-Net (DSC=0.85, p<0.0001), HED (DSC=0.80, p<0.0001), and radiology technicians (DSC=0.89, p<0.0001) in the retrospective internal test set. In the prospective cohort, ProGNet (DSC=0.93) outperformed radiology technicians (DSC=0.90, p<0.0001). ProGNet took just 35 seconds per case (vs. 10 minutes for radiology technicians) to yield a clinically utilizable segmentation file. Figure 1 illustrates the step-by-step segmentation workflow at our institution. CONCLUSIONS: This is the first study to employ a deep learning model for prostate gland segmentation for targeted biopsy in routine urologic clinical practice, while reporting results and releasing the code online. Prospective and retrospective evaluations revealed increased speed and accuracy. Source of Funding: This work was supported by Stanford University (Departments of Radiology and Urology) and by the generous philanthropic support of donors to the Urologic Cancer Innovation Laboratory © 2021 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 206Issue Supplement 3September 2021Page: e781-e781 Advertisement Copyright & Permissions© 2021 by American Urological Association Education and Research, Inc.MetricsAuthor Information Simon John Christoph Soerensen More articles by this author Richard E. Fan More articles by this author Wei Shao More articles by this author Indrani Bhattacharya More articles by this author Arun Seetharaman More articles by this author Michael Borre More articles by this author Alan Thong More articles by this author Katherine To’o More articles by this author Mirabela Rusu More articles by this author Geoffrey A. Sonn More articles by this author Expand All Advertisement Loading ...

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. Published by Elsevier Inc.

You have accessJournal of UrologyBladder Cancer: Epidemiology & Evaluation II (PD47)1 Sep 2021PD47-12 THE CARE ASSESSMENT NEED (CAN) SCORE TO ESTIMATE LIFE EXPECTANCY IN PATIENTS DIAGNOSED WITH BLADDER CANCER IN THE VETERANS HEALTH ADMINISTRATION Bogdana Schmidt, Simon John Christoph Soerensen, I-Chun Thomas, Alan Thong, Brian Dietrich, Joseph Liao, Thomas F. Osborne, and John T. Leppert Bogdana SchmidtBogdana Schmidt More articles by this author , Simon John Christoph SoerensenSimon John Christoph Soerensen More articles by this author , I-Chun ThomasI-Chun Thomas More articles by this author , Alan ThongAlan Thong More articles by this author , Brian DietrichBrian Dietrich More articles by this author , Joseph LiaoJoseph Liao More articles by this author , Thomas F. OsborneThomas F. Osborne More articles by this author , and John T. LeppertJohn T. Leppert More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002069.12AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Patients with muscle invasive bladder cancer are often older and present with comorbid conditions and tools that estimate life expectancy can guide clinical decision making for patients considering cystectomy. The Care Assessment Needs (CAN) score is an existing risk assessment tool that utilizes a variety of variables from electronic health records (EHR) and is automatically calculated for individual patients receiving care in the Veterans Health Administration (VHA). The CAN score produces a percentile score (0 to 99) that incorporates patient age, diagnoses, laboratory data, vital signs, medication use, and services utilization. We sought to investigate the utility of the CAN score to estimate 5-year life expectancy in patients with bladder cancer undergoing radical cystectomy. METHODS: We identified all patients diagnosed with bladder cancer who underwent radical cystectomy between 2013 and 2018 in the VHA. We utilized the CAN 1-year mortality model version 2.5, with score recorded within one month prior to surgery. We visualized unadjusted survival using Kaplan-Meier plots. We fit unadjusted and multivariable Cox proportional hazards models to determine the association between the CAN score and overall survival. RESULTS: We identified 1,192 patients with bladder cancer that were treated with radical cystectomy and had an available CAN score in the month prior to diagnosis. Median age at surgery was 68.2 (IQR 63.9, 72.6), 1,180 (99%) patients were male, 112 (9.4%) had neobladder urinary diversion, 680 (57%) had T2 or greater stage disease, 387 (32.5%) received neoadjuvant chemotherapy. Median Charlson comorbidity index (CCI) was 2.0 (IQR 0.0 ,4.0). Median CAN score was 60 (IQR 40, 75). In models adjusted for age, race, chemotherapy, and diversion type, the CAN score was independently associated with survival (HR per 5-unit change=1.08, 95%CI 1.06,1.10). CONCLUSIONS: The CAN score is a readily available EHR score that is automatically calculated for individual patients receiving care in the VHA. The CAN score is strongly associated with survival following radical cystectomy for bladder cancer. Incorporating the CAN score into clinical practice can help clinicians efficiently risk-stratify patients to provide patient-centered bladder cancer care. Source of Funding: None © 2021 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 206Issue Supplement 3September 2021Page: e837-e837 Advertisement Copyright & Permissions© 2021 by American Urological Association Education and Research, Inc.MetricsAuthor Information Bogdana Schmidt More articles by this author Simon John Christoph Soerensen More articles by this author I-Chun Thomas More articles by this author Alan Thong More articles by this author Brian Dietrich More articles by this author Joseph Liao More articles by this author Thomas F. Osborne More articles by this author John T. Leppert More articles by this author Expand All Advertisement Loading ...

Introduction: Reduction of opioids is an important goal in the care of patients undergoing radical cystectomy (RC). Liposomal bupivacaine (LB) has been shown to be a safe and effective pain reliever in the immediate postoperative period and has been reported to reduce postoperative opioid requirements. Since the liposomal formulation is predicated on slow systemic absorption, the amount of bupivacaine administered is notably higher than that typically used with standard bupivacaine (SB) formulations. In addition, LB is costly, not universally available, and studies comparing this formulation to SB are lacking. We sought to determine if there is a difference in postoperative opioid requirements in patients who receive LB vs. high dose SB at the time of RC. Methods: In May 2019 we transitioned to administration of high-volume SB injected intraoperatively at the time of RC. This prospective cohort was compared to a historical cohort of patients who received injection of LB at the time of surgery. Primary endpoints included postsurgical opioid use measured in morphine equivalent dose (MED) and patient-reported Numeric Rating Scale (NRS) pain scores and length of stay. All patients were managed using principles of enhanced recovery after surgery (ERAS). Results: From May 2019 through August 2019, 28 patients underwent RC and met eligibility criteria to receive SB at the time of surgery. They were compared to a historical cohort of 34 patients who received LB between November 2017 and July 2018. There was no difference in MED exposure either in the postanesthesia care unit (SB 9.0 +/- 8.9 MED vs. LB 6.5 +/- 9.4 MED, P= 0.29) or during the remainder of the hospital stay (SB 36.8 +/- 56.9 MED vs. LB 42.1 +/- 102.5 MED, P= 0.81), no difference in NRS pain scores on postoperative day 1 (SB 2.6 +/- 1.6 vs. LB 2.1 +/- 1.7, P= 0.23), day 2 (SB 2.4 +/- 1.8 vs. LB 1.9 +/- 1.6, P= 0.19), or day 3 (SB 1.9 +/- 1.8 vs. LB 1.7 +/- 1.7, P= 0.69) and no difference in length of stay (SB 5.0 +/- 1.7 days, LB 4.9 +/- 3.3 days, P= 0.93). Subgroup analysis of open RC and robotic-assisted RC showed no significant difference in MED or pain scores between LB and SB patients. Conclusions: Among patients undergoing RC under ERAS protocol there was no significant difference in postoperative opioid consumption, NRS pain scores, or length of stay among patients receiving SB compared to LB. (C) 2020 Elsevier Inc. All rights reserved.

You have accessJournal of UrologyProstate Cancer: Detection & Screening VII (PD60)1 Apr 2019PD60-05 AUTOMATED DETECTION OF PROSTATE CANCER ON MULTIPARAMETRIC MRI USING DEEP NEURAL NETWORKS TRAINED ON SPATIAL COORDINATES AND PATHOLOGY OF BIOPSY CORES Leo Chen*, Nicholas Bien, Richard Fan, Robin Cheong, Pranav Rajpurkar, Alan Thong, Nancy Wang, Sarir Ahmadi, Mirabela Rusu, James Brooks, Andrew Ng, and Geoffrey Sonn Leo Chen*Leo Chen* More articles by this author , Nicholas BienNicholas Bien More articles by this author , Richard FanRichard Fan More articles by this author , Robin CheongRobin Cheong More articles by this author , Pranav RajpurkarPranav Rajpurkar More articles by this author , Alan ThongAlan Thong More articles by this author , Nancy WangNancy Wang More articles by this author , Sarir AhmadiSarir Ahmadi More articles by this author , Mirabela RusuMirabela Rusu More articles by this author , James BrooksJames Brooks More articles by this author , Andrew NgAndrew Ng More articles by this author , and Geoffrey SonnGeoffrey Sonn More articles by this author View All Author Informationhttps://doi.org/10.1097/01.JU.0000557214.92207.3fAboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVES: The role of multiparametric MRI in clinical care is rapidly expanding due to its ability to improve prostate cancer detection. However, MRI interpretation suffers from a false negative rate of around 5-7% and high interobserver variability even among experts, thereby limiting its predictive value. Advances in machine learning and artificial intelligence have the potential to improve and standardize prostate cancer detection on MRI, though studies have relied on radiologist interpretations such as PIRADS scores of segmented lesions as ground truth. We sought to improve over existing methods by directly training on the 3D location and pathology of biopsy cores. METHODS: MR-ultrasound fusion biopsies were performed at a single institution using a robotic fusion biopsy device (Artemis, Eigen) for patients that had multiparametric prostate MRIs. Patients underwent both targeted and standard template biopsies. Core level pathology was prospectively collected into a database. The spatial coordinates of both targeted and standard template cores were calculated and plotted onto the MR images. A weakly supervised convolutional neural network model was trained to predict cancer on MR images, using the spatial geometry and pathology of the biopsy core tracts as ground truth. Implementation was done using the Python programming language. RESULTS: Over 10,000 MRI-US fusion biopsy cores were collected from over 600 patients in 2015-2018, yielding over 40,000 data points. A preliminary binary classification model based on T2 sequences alone correctly predicted benign versus cancerous cores with an AUROC of 0.78. There is ongoing work on incorporating DWI and ADC sequences to improve the accuracy of the deep learning model. CONCLUSIONS: We present a deep neural network model to predict prostate cancer on MRI that is trained on spatial coordinates and pathology of biopsy cores as ground truth. To our knowledge, this dataset is the largest that has been reported. Our model is blind to radiologist interpretation and lesion segmentation: it thereby aims to eliminate the interobserver variability of radiologist interpretations and improve the detection of cancer in patients with false negative MRIs. Ultimately, our goal is the automated generation of probabilistic heat maps of clinically significant prostate cancer based on automated processing of MRIs, improving the speed and accuracy of detecting clinically significant cancer, while reducing overdetection of clinically insignificant cancer. Source of Funding: None Stanford, CA© 2019 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 201Issue Supplement 4April 2019Page: e1098-e1098 Advertisement Copyright & Permissions© 2019 by American Urological Association Education and Research, Inc.MetricsAuthor Information Leo Chen* More articles by this author Nicholas Bien More articles by this author Richard Fan More articles by this author Robin Cheong More articles by this author Pranav Rajpurkar More articles by this author Alan Thong More articles by this author Nancy Wang More articles by this author Sarir Ahmadi More articles by this author Mirabela Rusu More articles by this author James Brooks More articles by this author Andrew Ng More articles by this author Geoffrey Sonn More articles by this author Expand All Advertisement PDF downloadLoading ...

Magnetic resonance imaging (MRI)-ultrasound fusion targeted biopsy (TB) is increasingly used to diagnose prostate cancer. When TB is used, it is common practice to also perform a transrectal ultrasound-guided systematic biopsy (SB). We hypothesize that a patient's National Comprehensive Cancer Network (NCCN) risk-group would not significantly change with the omission of SB when TB is used. In this IRB-approved prospective study, 594 patients underwent SB and TB for any MRI-visible lesion for the diagnosis of prostate cancer. A single urologist performed TB with a robotic biopsy device according to a standard protocol. The biopsy device selected SB locations independent of TB locations, and TB lesions were hidden during SB. Tissue cores were sent for histopathologic evaluation, and biopsy results were used as the standard for assessment of the presence of cancer. The proportion of patients in the NCCN (v 4.2018) very low/low (VL/L)*, favorable-intermediate (FI), unfavorable intermediate (UI), and high/very-high (H/VH)* risk groups were determined for TB and TB+SB groups (*combined due to small numbers). The Kappa statistic (0 = no agreement, 1 = perfect agreement) was used to measure agreement in NCCN risk groups between TB and TB+SB. Four hundred and twenty-five patients with adequate information for NCCN risk-stratification were analyzed. As expected, ISUP Grade Group with TB tended to be higher than SB (p<0.0001). There was almost perfect agreement in NCCN risk-group using TB with or without SB (Table 1), weighted kappa=0.92 (95% CI = 0.0.88-0.96). Only 18 patients (4%) had a lower NCCN risk-group with the omission of SB. Specifically, 11 patients (2.6%) were VL/L as opposed to FI, 5 patients (1.2%) were VL/L as opposed to UI, no patients were FI as opposed to UI, and 2 patients (0.5%) were UI as opposed to H/VH. There were no instances where the percentage of positive cores led to a change in risk group. Based on these results, the number needed to undergo SB in order to prevent one underestimation of the risk group is 25 patients. In this large study, underestimation of the NCCN risk-group with the omission of SB was highly improbable (4%). In light of the very large number of patients needed to undergo SB to prevent one underestimation of risk-group (25 patients), routine use of SB for risk categorization should be considered carefully. Without personalized factors that increase the baseline risk of higher-grade disease or otherwise support the need for SB, we propose that TB alone be an accepted practice standard for prostate cancer treatment decision-making.Abstract 2603; Table 1NCCN Risk Group calculated using TB+SB versus TB alone. Weighted kappa=0.92 (95% CI = 0.0.88-0.96).TB+SB NCCN Risk Group n (%)TB Alone NCCN Risk Group n (%)VL/LFIUIH/VHTotalVL/L46 (10.82%)00046 (10.82%)FI11 (2.59%)11 (2.59%)0022 (5.18%)UI5 (1.18%)0217 (51.06%)0222 (52.24%)H/VH002 (0.47%)133 (31.29%)135 (31.76%)Total62 (14.59%)11 (2.59%)219 (51.53%)133 (31.29%)425 (100%) Open table in a new tab

Purpose: Accurately tracking health-related quality-of-life after radical prostatectomy is critical to counseling patients and improving technique. Physicians consistently overestimate functional recovery. We measured concordance between surgeon-assessed and patient-reported outcomes and evaluated a novel method to provide feedback to surgeons. Materials and methods: Men treated with radical prostatectomy self-completed the International Index of Erectile Function-6 questionnaire at each postoperative visit. Separately, physicians graded sexual function on a 5-point scale. International Index of Erectile Function -6 score<22 and grade >= 3 defined patient-reported and physician-assessed erectile dysfunction (ED), respectively. Feedback on concordance was given to physicians starting in May 2013 with the implementation of the Amplio feedback system. Chi-square tests were used to assess agreement proportions and linear regression to evaluate changes in agreement after implementation. Results: From 2009 to 2015, 3,053 men completed at least 1 postprostatectomy questionnaire and had a concurrent independent physician-reported outcome. Prior to implementation of feedback in 2013, patients and physicians were consistent as to ED 83% of the time; in 10% of cases, physicians overestimated function; in 7% of cases, physicians, but not patients reported ED. Agreement increased after implementation of feedback but this was not statistically significant, likely owing to a ceiling effect. Supporting this hypothesis, increase in agreement postfeedback was greater during late follow-up (>= 12mo), where baseline agreement was lower compared to earlier follow-up. Conclusions: Agreement was higher than expected at baseline; implementation of feedback regarding discrepancies between patient-reported and physician-assessed outcomes did not further improve agreement significantly. Our observed high rate of agreement may be partly attributed to our institutional practice of systematically capturing patient-reported outcomes as part of normal clinical care. Copyright (C) 2018 Elsevier Inc. All rights reserved.

You have accessJournal of UrologyStone Disease: Epidemiology & Evaluation I1 Apr 2017MP01-18 PRECIPITATION (AND NOT TEMPERATURE) IS ASSOCIATED WITH URINARY STONE DISEASE IN CALIFORNIA Kai Dallas, Simon Conti, John Leppert, Christopher Elliott, Mario Sofer, and Alan Thong Kai DallasKai Dallas More articles by this author , Simon ContiSimon Conti More articles by this author , John LeppertJohn Leppert More articles by this author , Christopher ElliottChristopher Elliott More articles by this author , Mario SoferMario Sofer More articles by this author , and Alan ThongAlan Thong More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2017.02.093AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES It is commonly accepted that increased temperatures are associated with increased prevalence of kidney stone disease. When examining stone mapping studies of the United States, while some regions with high annual temperatures (the southeast) have higher kidney stone prevalence, other warm regions such as the southwest do not. One major climate difference between these two regions is annual precipitation and humidity. We sought to explore the associations among, temperature, precipitation and urinary stone disease. METHODS We identified all patients who underwent ureteroscopy, percutaneous nephrolithotomy, or shock wave lithotripsy using data from the Office of Statewide Health Planning and Development (OSHPD) for the state of California (2010-2012). We calculated the rate of operative stone disease for each county based on the patient's home zipcode. We obtained climate data for each county in California from the National Oceanic and Atmospheric Administration. We compared the rate of urinary stone surgeries, adjusted for county population, mean annual temperature, total number of days over 90 degrees, and the total annual precipitation. RESULTS A total of 63,994 unique patients underwent stone procedures in California between 2010-2012. The mean county stone surgery rate was 1.77 cases per 1000 persons (range 0.05-3.16). In the lowest quartile of rainfall (less than 21 inches per year), the average stone surgery rate was 1.5 per 1000 persons. This was significantly less than 2.2 per 1000 persons in the regions with the highest quartile of rainfall (44 inches per year) (p<0.01). In fully-adjusted models, precipitation (0.019 increase in surgeries per 1000 persons per inch, p<0.01) and higher mean temperature (0.029 increase in surgeries per 1000 persons per degree, p<0.01) were associated with an increased rate of stone surgery (Figure 1). The effect of temperature was not significant unless precipitation was controlled for. CONCLUSIONS In the state of California, temperature alone is not associated with the county-level rate of stone surgery until precipitation is included in models. Our results appear to agree with the larger trends seen through the United States where the areas of highest stone prevalence have warm humid climates, and not warm arid, climates. © 2017FiguresReferencesRelatedDetails Volume 197Issue 4SApril 2017Page: e8 Advertisement Copyright & Permissions© 2017MetricsAuthor Information Kai Dallas More articles by this author Simon Conti More articles by this author John Leppert More articles by this author Christopher Elliott More articles by this author Mario Sofer More articles by this author Alan Thong More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...