Magnetic resonance radiomics for prediction of extraprostatic extension in non-favorable intermediate- and high-risk prostate cancer patients.

Background: To investigate whether magnetic resonance (MR) radiomic features combined with machine learning may aid in predicting extraprostatic extension (EPE) in high- and non-favorable intermediate-risk patients with prostate cancer.

Purpose: To investigate the diagnostic performance of radiomics to detect EPE.

Material And Methods: MR radiomic features were extracted from 228 patients, of whom 86 were diagnosed with EPE, using prostate and lesion segmentations.

In Vivo Detection of Chronic Kidney Disease Using Tissue Deformation Fields From Dynamic MR Imaging.

Objective: Chronic kidney disease (CKD) is a serious medical condition characterized by gradual loss of kidney function. Early detection and diagnosis is mandatory for adequate therapy and prognostic improvement. Hence, in the current pilot study we explore the use of image registration methods for detecting renal morphologic changes in patients with CKD.

1.5-T multiparametric MRI using PI-RADS: a region by region analysis to localize the index-tumor of prostate cancer in patients undergoing prostatectomy.

Background: The use of multiparametric magnetic resonance imaging (mpMRI) to detect and localize prostate cancer has increased in recent years. In 2010, the European Society of Urogenital Radiology (ESUR) published guidelines for mpMRI and introduced the Prostate Imaging Reporting and Data System (PI-RADS) for scoring the different parameters.

Purpose: To evaluate the reliability and diagnostic performance of endorectal 1.

Blood flow quantification from 2D phase contrast MRI in renal arteries using an unsupervised data driven approach.

We present a clustering approach to segment the renal artery from 2D PC Cine MR images to measure arterial blood velocity and flow. Such information is important in grading renal artery stenosis and to support the decision on surgical interventions like percutaneous transluminal angioplasty. Results from 20 data sets (3 volunteers, 7 patients) show that the renal arteries could be extracted automatically and the corresponding velocity profiles were close (r = 0.