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Prostatic Neoplasms

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Performance of an ultra-fast deep-learning accelerated MRI screening protocol for prostate cancer compared to a standard multiparametric protocol.

European radiology
OBJECTIVES: To establish and evaluate an ultra-fast MRI screening protocol for prostate cancer (PCa) in comparison to the standard multiparametric (mp) protocol, reducing scan time and maintaining adequate diagnostic performance.

Stacked neural network for predicting polygenic risk score.

Scientific reports
In recent years, the utility of polygenic risk scores (PRS) in forecasting disease susceptibility from genome-wide association studies (GWAS) results has been widely recognised. Yet, these models face limitations due to overfitting and the potential ...

Perception of cure in prostate cancer: human-led and artificial intelligence-assisted landscape review and linguistic analysis of literature, social media and policy documents.

ESMO open
BACKGROUND: Understanding stakeholders' perception of cure in prostate cancer (PC) is essential to preparing for effective communication about emerging treatments with curative intent. This study used artificial intelligence (AI) for landscape review...

Robust prostate disease classification using transformers with discrete representations.

International journal of computer assisted radiology and surgery
PURPOSE: Automated prostate disease classification on multi-parametric MRI has recently shown promising results with the use of convolutional neural networks (CNNs). The vision transformer (ViT) is a convolutional free architecture which only exploit...

Application of Natural Language Processing in Electronic Health Record Data Extraction for Navigating Prostate Cancer Care: A Narrative Review.

Journal of endourology
Natural language processing (NLP)-based data extraction from electronic health records (EHRs) holds significant potential to simplify clinical management and aid research. This review aims to evaluate the current landscape of NLP-based data extracti...

Assessing deep learning reconstruction for faster prostate MRI: visual vs. diagnostic performance metrics.

European radiology
OBJECTIVE: Deep learning (DL) MRI reconstruction enables fast scan acquisition with good visual quality, but the diagnostic impact is often not assessed because of large reader study requirements. This study used existing diagnostic DL to assess the ...

Rapid multi-catheter segmentation for magnetic resonance image-guided catheter-based interventions.

Medical physics
BACKGROUND: Magnetic resonance imaging (MRI) is the gold standard for delineating cancerous lesions in soft tissue. Catheter-based interventions require the accurate placement of multiple long, flexible catheters at the target site. The manual segmen...

Novel dosimetric validation of a commercial CT scanner based deep learning automated contour solution for prostate radiotherapy.

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: OAR delineation accuracy influences: (i) a patient's optimised dose distribution (PD), (ii) the reported doses (RD) presented at approval, which represent plan quality. This study utilised a novel dosimetric validation methodology, comprehen...

Deep learning-based whole-body PSMA PET/CT attenuation correction utilizing Pix-2-Pix GAN.

Oncotarget
PURPOSE: Sequential PET/CT studies oncology patients can undergo during their treatment follow-up course is limited by radiation dosage. We propose an artificial intelligence (AI) tool to produce attenuation-corrected PET (AC-PET) images from non-att...