1. Apparent Diffusion Coefficient and Other Preoperative Magnetic Resonance Imaging Features for the Prediction of Positive Surgical Margins in Prostate Cancer Patients Undergoing Radical Prostatectomy
- Author
-
Barbara Alicja Jereczek-Fossa, Giulia Saia, Stefano Luzzago, Roberta Maggioni, Massimo Bellomi, Giulia Marvaso, Paola Pricolo, Paul Summers, Sarah Alessi, Giuseppe Renne, Ottavio De Cobelli, Alberto Colombo, Marco Federico Manzoni, and Giuseppe Petralia
- Subjects
Male ,medicine.medical_specialty ,Urology ,medicine.medical_treatment ,Youden's J statistic ,030232 urology & nephrology ,03 medical and health sciences ,Prostate cancer ,0302 clinical medicine ,Prostate ,medicine ,Humans ,Effective diffusion coefficient ,Retrospective Studies ,Prostatectomy ,medicine.diagnostic_test ,Index Lesion ,business.industry ,Margins of Excision ,Prostatic Neoplasms ,Magnetic resonance imaging ,medicine.disease ,Magnetic Resonance Imaging ,body regions ,Diffusion Magnetic Resonance Imaging ,medicine.anatomical_structure ,Oncology ,030220 oncology & carcinogenesis ,Radiology ,Neoplasm Grading ,Positive Surgical Margin ,business - Abstract
Purpose : To investigate the use of apparent diffusion coefficient (ADC) values and other MRI features for the prediction of positive surgical margins (PSMs) in patients undergoing radical prostatectomy. Materials and methods : 400 consecutive patients who underwent surgery for prostate cancer between January 2015 and June 2016 were retrospectively identified. ADC values of the index lesion and other preoperative MRI features, including tumor site, laterality and level, Prostate Imaging Reporting and Data System (PI-RADS) category, European Society of Urogenital Radiology (ESUR) extra-capsular extension score (ECE 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), and 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 : A total of 105 out of the 400 patients (26.2%) had PSMs after radical prostatectomy. ADC values, PI-RADS category, ECE score, tumor site and laterality were significantly associated with PSMs (p Conclusions : ADC values and preoperative MRI features can help estimate the risk of PSMs after radical prostatectomy. Micro Abstract : We retrospectively analysed 400 consecutive patients who underwent surgery for prostate cancer to investigate the use of apparent diffusion coefficient (ADC) values and other MRI features for the prediction of positive surgical margins (PSMs). ADC values, PI-RADS category, extra-capsular extension score, site, and laterality were significantly associated with PSMs; ADC performed well in PSM prediction, both in the univariate or multivariable analyses, with lower ADC values being present in patients with PSMs.
- Published
- 2021