The Application of Radiomics and AI to Molecular Imaging for Prostate Cancer.

Molecular imaging is a key tool in the diagnosis and treatment of prostate cancer (PCa). Magnetic Resonance (MR) plays a major role in this respect with nuclear medicine imaging, particularly, Prostate-Specific Membrane Antigen-based, (PSMA-based) positron emission tomography with computed tomography (PET/CT) also playing a major role of rapidly increasing importance. Another key technology finding growing application across medicine and specifically in molecular imaging is the use of machine learning (ML) and artificial intelligence (AI). Several authoritative reviews are available of the role of MR-based molecular imaging with a sparsity of reviews of the role of PET/CT. This review will focus on the use of AI for molecular imaging for PCa. It will aim to achieve two goals: firstly, to give the reader an introduction to the AI technologies available, and secondly, to provide an overview of AI applied to PET/CT in PCa. The clinical applications include diagnosis, staging, target volume definition for treatment planning, outcome prediction and outcome monitoring. ML and AL techniques discussed include radiomics, convolutional neural networks (CNN), generative adversarial networks (GAN) and training methods: supervised, unsupervised and semi-supervised learning.

Net survival of men with localized prostate cancer after LDR brachytherapy.

OBJECTIVES: To compare survival of patients who received LDR prostate brachytherapy relative to that of peers in the general population of England, UK. PATIENTS AND METHODS: Net survival was estimated for 2472 cases treated between 2002 and 2016 using population-based analysis guidelines. Life tables adjusted for social deprivation in England from the Office for National Statistics were used to match patients by affluence based on their postcode. RESULTS: The median (range) age at time of brachytherapy was 66 (55-84) years, 84% resided in Southeast England, 51% under an index of deprivation quintile 5 (most affluent), 55% were clinical stage T1 and the remainder T2. Death from any cause occurred in 270 patients at a median (range) of 7 (1-17) years postimplant. Five and 10-year estimates (95% CI) of overall survival were 96% (95-97) and 90% (89-92), and net survival 103% (102-104) and 109% (107-110) respectively. The net survival remained above 100% in all age-at-treatment and clinical stage groups. CONCLUSION: Net survival above 100% indicates patients survive longer than the matched general population. The study shows for the first time the net survival of patients treated with a radical therapy for localized prostate cancer in England. The impact of treatment choice on the long-term net survival advantage requires further investigation.