| Prospective validation of pathology-based artificial intelligence diagnostic model for lymph node metastasis in prostate cancer |
Patients with prostate cancer undergoing radical prostatectomy and pelvic lymph node dissection |
AI-based diagnostic model analyzing the whole-slide images |
Assess the diagnostic accuracy and clinical utility of a pre-existing AI system for prostate cancer lymph node metastasis detection |
[111] |
| AI based measurements of tumor burden in PSMA PET-CT |
Patients referred to a clinically indicated 18F-PSMA-1007 PET-CT scan at Skåne University Hospital, Lund or Malmö, Sweden |
AI-based detection and quantification of suspected tumour/metastases in PSMA PET/CT scans |
Evaluate how the total tumor burden (cm3) predicts overall survival |
[112] |
| Imperial Prostate 6 - Cancer Histology Artificial Intelligence Reliability Study. (IP6-CHAIROS) |
Adults with a prostate (either cis-male gender or trans-female gender with no prior hormone use at all) undergoing prostate biopsy because of an elevated serum PSA or abnormal digital rectal exam, who have undergone a pre-biopsy mp-MRI and advised to undergo prostate biopsies |
Biopsy & imaging |
To evaluate the diagnostic accuracy and health economic value of the Galen Prostate AI system for triaging pathology slides within the NHS context. |
[113] |
| Artificial Intelligence and Radiologists at Prostate Cancer Detection in MRI: The PI-CAI Challenge |
Men suspected of harboring clinically significant prostate cancer (csPCa) with elevated PSA levels (≥ 3 ng/ml) or abnormal digital rectal exam findings. Patients must not have a history of prior prostate treatment or positive histopathology findings (ISUP ≥ 2) |
Histopathology and MRI |
Validate the diagnostic performance of AI algorithms and radiologists in detecting and diagnosing csPCa in MRI, comparing their efficacy and identifying the optimal AI model and the effects of imaging techniques and reader experience on diagnostic accuracy |
[114] |
| Accelerated Body Diffusion-Weighted MRI Using Artificial Intelligence (CeleScan-R) |
Cancer patients aged 18 and older who have undergone one of the following MRI examinations: whole-body for multiple myeloma, metastatic prostate cancer, metastatic breast cancer; stacked abdomen/pelvis for liver metastases, pancreatic cancer, gynecological cancers, gastrointestinal cancers; multiparametric prostate exam for primary prostate cancers |
Whole-body diffusion-weighted MRI (WBDWI) using quickDWI, an accelerated technique with DL denoising filters, reducing acquisition times by up to 50% |
To evaluate the clinical quality of quickDWI images compared to conventional MRI, aiming to facilitate wider adoption, reduce costs, and improve patient experience |
[115, 116] |
