AI Medical Compendium Topic:
Prostatic Neoplasms

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Concurrent robot-assisted radical prostatectomy and robot-assisted partial nephrectomy for patients with synchronous prostate cancer and small renal tumor: A case series of five patients.

Asian journal of endoscopic surgery
Robotic surgery has become widely used in the field of urology. We experienced concurrent robot-assisted radical prostatectomy (RARP) and robot-assisted partial nephrectomy (RAPN) for the complex cases of synchronous primary cancers. Concurrent RARP ...

Medical image diagnosis of prostate tumor based on PSP-Net+VGG16 deep learning network.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Prostate cancer is the most common cancer of the male reproductive system. With the development of medical imaging technology, magnetic resonance images (MRI) have been used in the diagnosis and treatment of prostate cancer ...

The role of MRI in prostate cancer: current and future directions.

Magma (New York, N.Y.)
There has been an increasing role of magnetic resonance imaging (MRI) in the management of prostate cancer. MRI already plays an essential role in the detection and staging, with the introduction of functional MRI sequences. Recent advancements in ra...

Robot-assisted laparoscopic abdominoperineal resection with en bloc prostatectomy using the Retzius-sparing robot-assisted radical prostatectomy technique.

Asian journal of endoscopic surgery
INTRODUCTION: The best surgical technique for rectal cancer invading the prostate remains controversial. Rectal resection with en bloc prostatectomy using a standard retropubic approach is an option but has disadvantages. We report a new surgical pro...

A feasibility study on the development and use of a deep learning model to automate real-time monitoring of tumor position and assessment of interfraction fiducial marker migration in prostate radiotherapy patients.

Biomedical physics & engineering express
. The aim of this study was to assess the feasibility of the development and training of a deep learning object detection model for automating the assessment of fiducial marker migration and tracking of the prostate in radiotherapy patients.. A fiduc...

Optimal Deep Learning Enabled Prostate Cancer Detection Using Microarray Gene Expression.

Journal of healthcare engineering
Prostate cancer is the main cause of death over the globe. Earlier detection and classification of cancer is highly important to improve patient health. Previous studies utilized statistical and machine learning (ML) techniques for prostate cancer de...

Leveraging 5G technology for robotic surgery and cancer care.

Cancer reports (Hoboken, N.J.)
BACKGROUND: The field of robotic surgery has seen significant advancements in the past few years and it has been adopted in many large hospitals in the United States and worldwide as a standard for various procedures in recent years. However, the loc...

The association between perineural invasion in mpMRI-targeted and/or systematic prostate biopsy and adverse pathological outcomes in robot-assisted radical prostatectomy.

Actas urologicas espanolas
INTRODUCTION AND OBJECTIVES: This study aims to investigate the relationship between perineural invasion (PNI) in targeted (TBx) and/or systematic (SBx) prostate needle biopsy and adverse pathological features of prostate cancer (PCa) in prostatectom...

Robot-Assisted Prostate-Specific Membrane Antigen-Radioguided Surgery in Primary Diagnosed Prostate Cancer.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
The objective of this study was to evaluate the safety and feasibility of Tc-based prostate-specific membrane antigen (PSMA) robot-assisted-radioguided surgery to aid or improve the intraoperative detection of lymph node metastases during primary rob...

A deep learning system for prostate cancer diagnosis and grading in whole slide images of core needle biopsies.

Scientific reports
Gleason grading, a risk stratification method for prostate cancer, is subjective and dependent on experience and expertise of the reporting pathologist. Deep Learning (DL) systems have shown promise in enhancing the objectivity and efficiency of Glea...