Soheila Koopaei - Quantitative MR Imaging and Spectroscopy Group, Research Center for Molecular and Cellular Imaging, Institute for Advanced Medical Technologies, Imam Hospital, Tehran, Iran
Anahita Fathi Kazerooni - Department of Medical Physics and Biomedical Engineering, School of Medicine, Tehran University of Medical Science Tehran, Iran
Mahyar Ghafoori - Department of Radiology, Hazrat Rasoul Akram University Hospital, Tehran, Iran
Mohammadreza Alviri - Department of Medical Physics and Biomedical Engineering, School of Medicine, Tehran University of Medical Science Tehran, Iran
Fakhereh Pashaei - Quantitative MR Imaging and Spectroscopy Group, Research Center for Molecular and Cellular Imaging, Institute for Advanced Medical Technologies, Imam Hospital, Tehran, Iran
Hamidreza Saligheh Rad - Quantitative MR Imaging and Spectroscopy Group, Research Center for Molecular and Cellular Imaging, Institute for Advanced Medical Technologies, Imam Hospital, Tehran, Iran

Background: The most common cancer (non-cutaneous) malignancy among men is prostate cancer. Management of prostate cancer, including staging and treatment, playing an important role in decreasing mortality rates. Among all current diagnostic tools, multiparametric MRI (mp-MRI) has shown high potential in localizing and staging prostate cancer. Quantification of mp-MRI helps to decrease the dependency of diagnosis on readers’ opinions.Objective: The aim of this research is to set a method based on quantification of mp-MRI images for discrimination between benign and malignant prostatic lesions with fusion-guided MR imaging/transrectal ultrasonography biopsy as a pathology validation reference.Material and Methods: It is an analytical research that ۲۷ patients underwent the mp-MRI examination, including T۱- and T۲- weighted and diffusion weighted imaging (DWI). Quantification was done by calculating radiomic features from mp-MRI images. Receiver-operating-characteristic curve was done for each feature to evaluate the discriminatory capacity and linear discriminant analysis (LDA) and leave-one-out cross-validation for feature filtering to estimate the sensitivity, specificity and accuracy of the benign and malignant lesion differentiation process is used.Results: An accuracy, sensitivity and specificity of ۹۲.۶%, ۹۵.۲% and ۸۳.۳%, respectively, were achieved from a subset of radiomics features obtained from T۲-weighted images and apparent diffusion coefficient (ADC) maps for distinguishing benign and malignant prostate lesions. Conclusion: Quantification of mp-MRI (T۲-weighted images and ADC-maps) based on radiomics feature has potential to distinguish benign with appropriate accuracy from malignant prostate lesions. This technique is helpful in preventing needless biopsies in patients and provides an assisted diagnosis for classifications of prostate lesions.

Prostatic Neoplasms, Multiparametric Magnetic Resonance Imaging, Radiomics Fatures, Quantification analysis