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Prostatic Neoplasms

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Automated prostate gland segmentation in challenging clinical cases: comparison of three artificial intelligence methods.

Abdominal radiology (New York)
OBJECTIVE: Automated methods for prostate segmentation on MRI are typically developed under ideal scanning and anatomical conditions. This study evaluates three different prostate segmentation AI algorithms in a challenging population of patients wit...

Extended pelvic lymph node dissection during robotic prostatectomy: antegrade versus retrograde technique.

BMC urology
BACKGROUND: Robot-assisted radical prostatectomy (RARP) with extended lymphadenectomy (ePLND) is the gold standard for surgical treatment of prostate cancer (PCa). Recently, the en-bloc ePLND has been proposed but no studies reported on the standardi...

DiagSet: a dataset for prostate cancer histopathological image classification.

Scientific reports
Cancer diseases constitute one of the most significant societal challenges. In this paper, we introduce a novel histopathological dataset for prostate cancer detection. The proposed dataset, consisting of over 2.6 million tissue patches extracted fro...

Can we predict pathology without surgery? Weighing the added value of multiparametric MRI and whole prostate radiomics in integrative machine learning models.

European radiology
OBJECTIVE: To test the ability of high-performance machine learning (ML) models employing clinical, radiological, and radiomic variables to improve non-invasive prediction of the pathological status of prostate cancer (PCa) in a large, single-institu...

Modified Retzius-sparing robot-assisted radical prostatectomy for cases with anterior tumor: a propensity score-matched analysis.

World journal of urology
OBJECTIVE: To compare the outcomes between a modified Retzius-sparing robot-assisted radical prostatectomy (mRS-RARP) technique and conventional robot-assisted radical prostatectomy (Con-RARP) technique for cases with anterior prostate cancer (PCa), ...

RAPHIA: A deep learning pipeline for the registration of MRI and whole-mount histopathology images of the prostate.

Computers in biology and medicine
Image registration can map the ground truth extent of prostate cancer from histopathology images onto MRI, facilitating the development of machine learning methods for early prostate cancer detection. Here, we present RAdiology PatHology Image Alignm...

Men's sociotechnical imaginaries of artificial intelligence for prostate cancer diagnostics - A focus group study.

Social science & medicine (1982)
Artificial intelligence (AI) is increasingly used for diagnostic purposes in cancer care. Prostate cancer is one of the most prevalent cancers affecting men worldwide, but current diagnostic approaches have limitations in terms of specificity and sen...

High-dose-rate Brachytherapy Monotherapy in Patients With Localised Prostate Cancer: Dose Modelling and Optimisation Using Computer Algorithms.

Clinical oncology (Royal College of Radiologists (Great Britain))
AIMS: Interstitial high-dose-rate brachytherapy (HDR-BT) is an effective therapy modality for patients with localized prostate carcinoma. The objectives of the study were to optimise the therapy regime variables using two models: response surface met...

Prognostic factors among patients with pathological Grade Group 5 prostate cancer based on robot-associated radical prostatectomy specimens from a large Japanese cohort (MSUG94).

World journal of urology
PURPOSE: There are no definitive prognostic factors for patients with pathological Grade Group 5 (pGG 5) prostate cancer (PCa) undergoing robot-associated radical prostatectomy (RARP). This study aimed to explore the prognostic factors among patients...

Using a deep learning prior for accelerating hyperpolarized C MRSI on synthetic cancer datasets.

Magnetic resonance in medicine
PURPOSE: We aimed to incorporate a deep learning prior with k-space data fidelity for accelerating hyperpolarized carbon-13 MRSI, demonstrated on synthetic cancer datasets.