Luca Brunese1, Maria Chiara Brunese1, Mattia Carbone2, Vincenzo Ciccone2, Francesco Mercaldo3, Antonella Santone1. 1. Department of Medicine and Health Sciences "Vincenzo Tiberio", University of Molise, Campobasso, Italy. 2. Dipartimento Diagnostico per Immagini U.O.C. di Radiologia, Ospedale San Giovanni di Dio e Ruggi d'Aragona, Salerno, Italy. 3. Department of Medicine and Health Sciences "Vincenzo Tiberio", University of Molise, Campobasso, Italy. francesco.mercaldo@unimol.it.
Abstract
INTRODUCTION AND OBJECTIVES: The Prostate Imaging Reporting and Data System (PI-RADS) version 2 emerged as standard in prostate magnetic resonance imaging examination. The Pi-RADS scores are assigned by radiologists and indicate the likelihood of a clinically significant cancer. The aim of this paper is to propose a methodology to automatically mark a magnetic resonance imaging with its related PI-RADS. MATERIALS AND METHODS: We collected a dataset from two different institutions composed by DWI ADC MRI for 91 patients marked by expert radiologists with different PI-RADS score. A formal model is generated starting from a prostate magnetic resonance imaging, and a set of properties related to the different PI-RADS scores are formulated with the help of expert radiologists and pathologists. RESULTS: Our methodology relies on the adoption of formal methods and radiomic features, and in the experimental analysis, we obtain a specificity and sensitivity equal to 1. Q CONCLUSIONS: The proposed methodology is able to assign the PI-RADS score by analyzing prostate magnetic resonance imaging with a very high accuracy.
INTRODUCTION AND OBJECTIVES: The Prostate Imaging Reporting and Data System (PI-RADS) version 2 emerged as standard in prostate magnetic resonance imaging examination. The Pi-RADS scores are assigned by radiologists and indicate the likelihood of a clinically significant cancer. The aim of this paper is to propose a methodology to automatically mark a magnetic resonance imaging with its related PI-RADS. MATERIALS AND METHODS: We collected a dataset from two different institutions composed by DWI ADC MRI for 91 patients marked by expert radiologists with different PI-RADS score. A formal model is generated starting from a prostate magnetic resonance imaging, and a set of properties related to the different PI-RADS scores are formulated with the help of expert radiologists and pathologists. RESULTS: Our methodology relies on the adoption of formal methods and radiomic features, and in the experimental analysis, we obtain a specificity and sensitivity equal to 1. Q CONCLUSIONS: The proposed methodology is able to assign the PI-RADS score by analyzing prostate magnetic resonance imaging with a very high accuracy.