SynthesisEuropean radiology experimental2022
Radiomics and artificial intelligence in prostate cancer: new tools for molecular hybrid imaging and theragnostics.
Synthesis in European radiology experimental, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
What it found
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Who cites it
26 citing papers in PubMed.
- Cascaded deep learning for automated lung cancer tumour burden quantification on [Quantitative imaging in medicine and surgery · 2026Article
- Enhancing PET/CT Radiomics Robustness Through Graph Signal Processing.Diagnostics (Basel, Switzerland) · 2026Article
- Radiological and Biological Dictionary of Radiomics Features: Addressing Understandable AI Issues in Personalized Prostate Cancer, Dictionary Version PM1.0.Journal of imaging informatics in medicine · 2026Article
- Impact of partial volume correction on radiomics reproducibility in theranostic SPECT/CT imaging.Medical physics · 2026Article
- PICO-based assessment and categorization of evidence for digital health interventions: an inductive framework development.Frontiers in digital health · 2026Review
- Article
- The evolving role of positron emission tomography in precision prostate cancer biopsy.European journal of clinical investigation · 2025Review
- Multivariate Framework of Metabolism in Advanced Prostate Cancer Using Whole Abdominal and Pelvic HyperpolarizedCancers · 2025Article
- Article
- Preclinical Implementation of matRadiomics: A Case Study for Early Malformation Prediction in Zebrafish Model.Journal of imaging · 2024Article
- Application of Photoactive Compounds in Cancer Theranostics: Review on Recent Trends from Photoactive Chemistry to Artificial Intelligence.Molecules (Basel, Switzerland) · 2024Review
- CT and MRI radiomic features of lung cancer (NSCLC): comparison and software consistency.European radiology experimental · 2024Article
- Deep Learning-Based Detection and Classification of Bone Lesions on Staging Computed Tomography in Prostate Cancer: A Development Study.Academic radiology · 2024Article
- Review
- Radiomics and Artificial Intelligence in Radiotheranostics: A Review of Applications for Radioligands Targeting Somatostatin Receptors and Prostate-Specific Membrane Antigens.Diagnostics (Basel, Switzerland) · 2024Review
- Application of Advanced Imaging to Prostate Cancer Diagnosis and Management: A Narrative Review of Current Practice and Unanswered Questions.Journal of clinical medicine · 2024Review
- Theranostics and artificial intelligence: new frontiers in personalized medicine.Theranostics · 2024Review
- A Critical Analysis of the Robustness of Radiomics to Variations in Segmentation Methods inDiagnostics (Basel, Switzerland) · 2023Article
- A novel method for assessing cardiac function in patients with coronary heart disease based on wrist pulse analysis.Irish journal of medical science · 2023Article
- Machine Learning and Radiomics of Bone Scintigraphy: Their Role in Predicting Recurrence of Localized or Locally Advanced Prostate Cancer.Diagnostics (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
16 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In prostate cancer (PCa), the use of new radiopharmaceuticals has improved the accuracy of diagnosis and staging, refined surveillance strategies, and introduced specific and personalized radioreceptor therapies. Nuclear medicine, therefore, holds great promise for improving the quality of life of PCa patients, through managing and processing a vast amount of molecular imaging data and beyond, using a multi-omics approach and improving patients' risk-stratification for tailored medicine. Artificial intelligence (AI) and radiomics may allow clinicians to improve the overall efficiency and accuracy of using these "big data" in both the diagnostic and theragnostic field: from technical aspects (such as semi-automatization of tumor segmentation, image reconstruction, and interpretation) to clinical outcomes, improving a deeper understanding of the molecular environment of PCa, refining personalized treatment strategies, and increasing the ability to predict the outcome. This systematic review aims to describe the current literature on AI and radiomics applied to molecular imaging of prostate cancer.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.