Sarah Alessi1, Roberta Maggioni2, Stefano Luzzago3, Alberto Colombo4, Paola Pricolo4, Paul E Summers4, Giulia Saia4, Marco Manzoni5, Giuseppe Renne5, Giulia Marvaso6, Ottavio De Cobelli7, Massimo Bellomi8, Barbara A Jereczek-Fossa6, Giuseppe Petralia9. 1. Postgraduate School in Radiodiagnostics, University of Milan. Electronic address: sarah.alessi@ieo.it. 2. Postgraduate School in Radiodiagnostics, University of Milan. 3. Department of Urology, IEO European Institute of Oncology IRCCS. 4. Division of Radiology, IEO European Institute of Oncology IRCCS. 5. Uropathology and Intraoperative Diagnostic Division, IEO European Institute of Oncology IRCCS. 6. Division of Radiotherapy, IEO European Institute of Oncology IRCCS; Department of Oncology and Hemato-Oncology, University of Milan. 7. Postgraduate School in Radiodiagnostics, University of Milan; Department of Oncology and Hemato-Oncology, University of Milan. 8. Department of Urology, IEO European Institute of Oncology IRCCS; Department of Oncology and Hemato-Oncology, University of Milan. 9. Department of Oncology and Hemato-Oncology, University of Milan; Precision Imaging and Research Unit - Department of Medical Imaging and Radiation Sciences, IEO European Institute of Oncology IRCCS Milan Italy.
Abstract
PURPOSE: To investigate the use of apparent diffusion coefficient (ADC) values and other MRI features for predicting positive surgical margins (PSMs) in patients undergoing radical prostatectomy. MATERIALS AND METHODS: We retrospectively identified 400 consecutive patients who underwent surgery for prostate cancer between January 2015 and June 2016. ADC values of the index lesion and other preoperative magnetic resonance imaging features, including tumor site, laterality, level, Prostate Imaging Reporting and Data System category, European Society of Urogenital Radiology extracapsular extension score, and prostate volume, were assessed. Univariate and multivariable logistic regression were performed. Performance in predicting the occurrence of PSMs was measured using the area under the curve (AUC). AUC differences were evaluated with the DeLong method. The Youden index was calculated to identify the ADC threshold to best discriminate patients with PSMs. RESULTS: Of the 400 patients, 105 (26.2%) had PSMs after radical prostatectomy. ADC values, Prostate Imaging Reporting and Data System category, extracapsular extension score, tumor site, and laterality were significantly associated with PSMs (P < .001) in univariate analysis. The AUC of the predictive model based on ADC alone was 68.2% (95% confidence interval, 62.2-74.2%) and did not significantly differ from the best multivariable predictive model which combined laterality, and site with ADC to attain an AUC of 70.0% (95% confidence interval, 64.2-75.8%; DeLong P = .318). The ADC threshold that maximized the Youden index was 960.3 µm2/s. CONCLUSION: ADC values and preoperative magnetic resonance imaging features can help estimate the risk of PSMs after radical prostatectomy.
PURPOSE: To investigate the use of apparent diffusion coefficient (ADC) values and other MRI features for predicting positive surgical margins (PSMs) in patients undergoing radical prostatectomy. MATERIALS AND METHODS: We retrospectively identified 400 consecutive patients who underwent surgery for prostate cancer between January 2015 and June 2016. ADC values of the index lesion and other preoperative magnetic resonance imaging features, including tumor site, laterality, level, Prostate Imaging Reporting and Data System category, European Society of Urogenital Radiology extracapsular extension score, and prostate volume, were assessed. Univariate and multivariable logistic regression were performed. Performance in predicting the occurrence of PSMs was measured using the area under the curve (AUC). AUC differences were evaluated with the DeLong method. The Youden index was calculated to identify the ADC threshold to best discriminate patients with PSMs. RESULTS: Of the 400 patients, 105 (26.2%) had PSMs after radical prostatectomy. ADC values, Prostate Imaging Reporting and Data System category, extracapsular extension score, tumor site, and laterality were significantly associated with PSMs (P < .001) in univariate analysis. The AUC of the predictive model based on ADC alone was 68.2% (95% confidence interval, 62.2-74.2%) and did not significantly differ from the best multivariable predictive model which combined laterality, and site with ADC to attain an AUC of 70.0% (95% confidence interval, 64.2-75.8%; DeLong P = .318). The ADC threshold that maximized the Youden index was 960.3 µm2/s. CONCLUSION: ADC values and preoperative magnetic resonance imaging features can help estimate the risk of PSMs after radical prostatectomy.