A5081218733- Prostate Cancer Diagnosis and Treatment
- Prostate Cancer Treatment and Research
- MRI in cancer diagnosis
- Advanced MRI Techniques and Applications
- Medical Image Segmentation Techniques
- Radiomics and Machine Learning in Medical Imaging
- Cardiovascular Health and Disease Prevention
- Urinary Bladder and Prostate Research
- Renal and Vascular Pathologies
University of Bergen
2020
Haukeland University Hospital
2008-2020
To investigate whether magnetic resonance (MR) radiomic features combined with machine learning may aid in predicting extraprostatic extension (EPE) high- and non-favorable intermediate-risk patients prostate cancer.To the diagnostic performance of radiomics to detect EPE.MR were extracted from 228 patients, whom 86 diagnosed EPE, using lesion segmentations. Prediction models built Random Forest. Further, EPE was also predicted a clinical nomogram routine radiological interpretation assessed...
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 Urogenital Radiology (ESUR) published guidelines for mpMRI introduced Prostate Imaging Reporting Data System (PI-RADS) scoring different parameters. Purpose To evaluate reliability diagnostic performance endorectal 1.5-T using PI-RADS index tumor patients undergoing prostatectomy. Material Methods This institutional...
Purpose To validate the MRI grading system proposed by Mehralivand et al in 2019 (the "extraprostatic extension [EPE] grade") an independent cohort and to compare EPE with interpretation on basis of a five-point Likert score ("EPE Likert"). Materials Methods A total 310 consecutive patients underwent multiparametric according standardized institutional protocol before radical prostatectomy was performed using same 1.5-T unit at single institution between 2010 2012. Two radiologists blinded...
To improve preoperative risk stratification for prostate cancer (PCa) by incorporating multiparametric MRI (mpMRI) features into tools PCa, CAPRA and D'Amico.807 consecutive patients operated on robot-assisted radical prostatectomy at our institution during the period 2010-2015 were followed to identify biochemical recurrence (BCR). 591 eligible final analysis. We employed stepwise backward likelihood methodology penalised Cox cross-validation most significant predictors of BCR including...
Chronic kidney disease (CKD) is a serious medical condition characterized by gradual loss of function. Early detection and diagnosis mandatory for adequate therapy prognostic improvement. Hence, in the current pilot study we explore use image registration methods detecting renal morphologic changes patients with CKD.Ten healthy volunteers nine presumed CKD underwent dynamic T1 weighted imaging without contrast agent. From real simulated time series, deformation fields were estimated using...