AI Medical Compendium Topic:
Prostatic Neoplasms

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Characterizing CDK12-Mutated Prostate Cancers.

Clinical cancer research : an official journal of the American Association for Cancer Research
PURPOSE: Cyclin-dependent kinase 12 (CDK12) aberrations have been reported as a biomarker of response to immunotherapy for metastatic castration-resistant prostate cancer (mCRPC). Herein, we characterize CDK12-mutated mCRPC, presenting clinical, geno...

Periprostatic fat thickness quantified by preoperative magnetic resonance imaging is an independent risk factor for upstaging from cT1/2 to pT3 in robot-assisted radical prostatectomy.

International journal of urology : official journal of the Japanese Urological Association
OBJECTIVES: To analyze the correlation between periprostatic fat thickness on multiparametric magnetic resonance imaging and upstaging from cT1/2 to pT3 in robot-assisted radical prostatectomy.

The utility of a deep learning-based algorithm for bone scintigraphy in patient with prostate cancer.

Annals of nuclear medicine
OBJECTIVE: Bone scintigraphy has often been used to evaluate bone metastases. Its functionality is evident in detecting bone metastasis in patients with malignant tumor including prostate cancer, as appropriate treatment and prognosis are dependent o...

Radiomics for Gleason Score Detection through Deep Learning.

Sensors (Basel, Switzerland)
Prostate cancer is classified into different stages, each stage is related to a different Gleason score. The labeling of a diagnosed prostate cancer is a task usually performed by radiologists. In this paper we propose a deep architecture, based on s...

Digital Biopsy with Fluorescence Confocal Microscope for Effective Real-time Diagnosis of Prostate Cancer: A Prospective, Comparative Study.

European urology oncology
BACKGROUND: A microscopic analysis of tissue is the gold standard for cancer detection. Hematoxylin-eosin (HE) for the reporting of prostate biopsy (PB) is conventionally based on fixation, processing, acquisition of glass slides, and analysis with a...

Simple low-cost approaches to semantic segmentation in radiation therapy planning for prostate cancer using deep learning with non-contrast planning CT images.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: Deep learning has shown great efficacy for semantic segmentation. However, there are difficulties in the collection, labeling and management of medical imaging data, because of ethical complications and the limited number of imaging studies ...

Patient reported outcome measures concerning urinary incontinence after robot assisted radical prostatectomy: development and validation of an online prediction model using clinical parameters, lower urinary tract symptoms and surgical experience.

Journal of robotic surgery
The prediction of post-prostatectomy incontinence (PPI) after robot-assisted radical prostatectomy (RARP) depends on multiple clinical, anatomical and surgical factors. There are only few risk formulas, tables or nomograms predicting PPI that may ass...

Application of hierarchical clustering to multi-parametric MR in prostate: Differentiation of tumor and normal tissue with high accuracy.

Magnetic resonance imaging
PURPOSE: Hierarchical clustering (HC), an unsupervised machine learning (ML) technique, was applied to multi-parametric MR (mp-MR) for prostate cancer (PCa). The aim of this study is to demonstrate HC can diagnose PCa in a straightforward interpretab...

Automated detection of cribriform growth patterns in prostate histology images.

Scientific reports
Cribriform growth patterns in prostate carcinoma are associated with poor prognosis. We aimed to introduce a deep learning method to detect such patterns automatically. To do so, convolutional neural network was trained to detect cribriform growth pa...