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Prostatic Neoplasms

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High-throughput precision MRI assessment with integrated stack-ensemble deep learning can enhance the preoperative prediction of prostate cancer Gleason grade.

British journal of cancer
BACKGROUND: To develop and test a Prostate Imaging Stratification Risk (PRISK) tool for precisely assessing the International Society of Urological Pathology Gleason grade (ISUP-GG) of prostate cancer (PCa).

Automated deep-learning system in the assessment of MRI-visible prostate cancer: comparison of advanced zoomed diffusion-weighted imaging and conventional technique.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: Deep-learning-based computer-aided diagnosis (DL-CAD) systems using MRI for prostate cancer (PCa) detection have demonstrated good performance. Nevertheless, DL-CAD systems are vulnerable to high heterogeneities in DWI, which can interfer...

Retzius-sparing robot-assisted radical prostatectomy in a medium size oncological center holds adequate oncological and functional outcomes.

Journal of robotic surgery
Retzius-sparing robot-assisted radical prostatectomy (RS-RARP) has emerged as a surgical option for patients with prostatic cancer in high-volume centers. The objective is to assess oncological and functional outcomes when implementing RS-RARP in a m...

Port-Site Metastasis Identified on Prostate-Specific Membrane Antigen-Targeted 18 F-DCFPyL PET/CT After Robot-Assisted Laparoscopic Radical Prostatectomy.

Clinical nuclear medicine
Port-site metastasis is an extremely rare complication following minimally invasive oncologic surgery for prostate cancer. We present the case of a 74-year-old man who underwent robot-assisted laparoscopic radical prostatectomy followed by salvage ra...

Applications of artificial intelligence in prostate cancer histopathology.

Urologic oncology
The diagnosis of prostate cancer (PCa) depends on the evaluation of core needle biopsies by trained pathologists. Artificial intelligence (AI) derived models have been created to address the challenges posed by pathologists' increasing workload, work...

Deep Learning on Multimodal Chemical and Whole Slide Imaging Data for Predicting Prostate Cancer Directly from Tissue Images.

Journal of the American Society for Mass Spectrometry
Prostate cancer is one of the most common cancers globally and is the second most common cancer in the male population in the US. Here we develop a study based on correlating the hematoxylin and eosin (H&E)-stained biopsy data with MALDI mass-spectro...

Sustainable functional urethral reconstruction improves early urinary continence after robot-assisted radical prostatectomy: a randomised controlled trial.

BJU international
OBJECTIVE: To evaluate the impact of sustainable functional urethral reconstruction (SFUR) on early recovery of urinary continence (UC) after robot-assisted radical prostatectomy.

Feasibility, Safety, and Functional Outcomes of Pelvic Hypothermia Induced Using a Rectal Cooling Device During Robot-Assisted Radical Prostatectomy: A Phase I/II Trial.

Journal of endourology
Radical prostatectomy (RP) is one of the standard treatments for localized prostate cancer. However, in terms of functional outcomes, there are aspects that still need improvements. We designed this prospective phase I/II clinical trial to assess th...

Differential diagnosis of prostate cancer and benign prostatic hyperplasia based on DCE-MRI using bi-directional CLSTM deep learning and radiomics.

Medical & biological engineering & computing
Dynamic contrast-enhanced MRI (DCE-MRI) is routinely included in the prostate MRI protocol for a long time; its role has been questioned. It provides rich spatial and temporal information. However, the contained information cannot be fully extracted ...

Radiomic-based machine learning model for the accurate prediction of prostate cancer risk stratification.

The British journal of radiology
OBJECTIVES: To precisely predict prostate cancer (PCa) risk stratification, we constructed a machine learning (ML) model based on magnetic resonance imaging (MRI) radiomic features.