Faculty Bibliography

BACKGROUND:Patient-specific 3D models are being used increasingly in medicine for many applications including surgical planning, procedure rehearsal, trainee education, and patient education. To date, experiences on the use of 3D models to facilitate patient understanding of their disease and surgical plan are limited. The purpose of this study was to investigate in the context of renal and prostate cancer the impact of using 3D printed and augmented reality models for patient education. METHODS:Patients with MRI-visible prostate cancer undergoing either robotic assisted radical prostatectomy or focal ablative therapy or patients with renal masses undergoing partial nephrectomy were prospectively enrolled in this IRB approved study (n = 200). Patients underwent routine clinical imaging protocols and were randomized to receive pre-operative planning with imaging alone or imaging plus a patient-specific 3D model which was either 3D printed, visualized in AR, or viewed in 3D on a 2D computer monitor. 3D uro-oncologic models were created from the medical imaging data. A 5-point Likert scale survey was administered to patients prior to the surgical procedure to determine understanding of the cancer and treatment plan. If randomized to receive a pre-operative 3D model, the survey was completed twice, before and after viewing the 3D model. In addition, the cohort that received 3D models completed additional questions to compare usefulness of the different forms of visualization of the 3D models. Survey responses for each of the 3D model groups were compared using the Mann-Whitney and Wilcoxan rank-sum tests. RESULTS:All 200 patients completed the survey after reviewing their cases with their surgeons using imaging only. 127 patients completed the 5-point Likert scale survey regarding understanding of disease and surgical procedure twice, once with imaging and again after reviewing imaging plus a 3D model. Patients had a greater understanding using 3D printed models versus imaging for all measures including comprehension of disease, cancer size, cancer location, treatment plan, and the comfort level regarding the treatment plan (range 4.60-4.78/5 vs. 4.06-4.49/5, p < 0.05). CONCLUSIONS:All types of patient-specific 3D models were reported to be valuable for patient education. Out of the three advanced imaging methods, the 3D printed models helped patients to have the greatest understanding of their anatomy, disease, tumor characteristics, and surgical procedure.

PURPOSE/OBJECTIVE:To determine whether the presence of an ultrasound hypoechoic region at the site of a MRI region of interest (ROI) results in improved prostate cancer (PCa) detection and predicts clinically significant PCa on MRI - ultrasound fusion targeted prostate biopsy (MRF-TB). MATERIALS AND METHODS/METHODS:Between July 2011 and June 2017, 1058 men who underwent MRF-TB and systematic biopsy by a single surgeon were prospectively entered into an IRB-approved database. MRI ROI were identified and scored for suspicion by a single radiologist. Each MRI ROI was prospectively evaluated for presence of a hypoechoic region at the site (ROI-HyR) by the surgeon and graded as 0,1,2 representing none, poorly demarcated, or well demarcated, respectively. Interaction of MRI suspicion score (mSS) and US grade (USG), and prediction of cancer detection rate (CDR) by USG, was evaluated by univariate and multivariate analysis. RESULTS:For 672 men, overall and Gleason Score (GS)≥7 CDR were 61.2% and 39.6%, respectively. CDR for USG 0,1,2 were 46.2%, 58.6%, 76.0% (p<0.001) for any cancer and 18.7%, 35.2%, 61.1% (p<0.001) for GS≥7, respectively. For MRF-TB only, GS≥7 CDR for USG 0,1,2 was 12.8%, 25.7%, 52.0% (p<0.001), respectively. On univariate analysis, among mSS 2-4, USG was predictive of GS≥7 CDR. Multivariable regression analysis revealed USG, PSAD, and mSS were predictive of GS≥7 PCa on MRF-TB. CONCLUSIONS:Ultrasound findings at the site of MRI ROI independently predict the likelihood of GS≥7 PCa, as men with a well demarcated ROI-HyR at the time of MRF-TB have a higher risk than men without.

INTRODUCTION/BACKGROUND:Penectomy for PC is useful in staging, disease prognosis, and treatment. Limited studies have evaluated its surgical complications. We sought to assess these complications and determine predictive models to create a novel risk score for penectomy complications. PATIENTS AND METHODS/METHODS:A retrospective review of patients undergoing PC surgical management from the 2005-2016 American College of Surgeons National Surgical Quality Improvement Program was performed. Data were queried for partial and total penectomy among those with PC. To develop predictive models of complications, we fit LASSO logistic, random forest, and stepwise logistic models to training data using cross-validation, demographic, comorbidity, laboratory, and wound characteristics as candidate predictors. Each model was evaluated on the test data using receiver operating characteristic curves. A novel risk score was created by rounding coefficients from the LASSO logistic model. RESULTS:A total of 304 cases met the inclusion criteria. Overall incidence of penectomy complications was 19.7%, where urinary tract infection (3.0%), superficial surgical site infection (3.0%), and bleeding requiring transfusion (3.9%) were most common. LASSO logistic, random forest, and stepwise logistic models for predicting complications had area under the curve (AUC) [95% confidence interval] values of 0.66 [0.52-0.81], 0.73 [0.63-0.83], and 0.59 [0.45-0.74], respectively. Eleven variables were included in the risk score. The LASSO model-derived risk score had moderately good performance (area under the curve [95% confidence interval] 0.74 [0.66-0.82]). Using a cutoff point of 6, the score attains sensitivity 0.58, specificity 0.74, and kappa 0.26. CONCLUSION/CONCLUSIONS:PC management through penectomy is associated with appreciable complications rates. Predictive models of penectomy complications performed moderately well. Our novel prognostic risk score may allow for improved preoperative counseling and risk stratification of men undergoing surgical management of PC.