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NCT06662708
Artificial Intelligence Models for Precision Prediction and Treatment of Prostate Cancer
NA trial testing Accurate Prediction Artificial Intelligence Models in Prostate Cancer in 200 participants. Not yet recruiting.
1 January 2030
Quick facts
| Lead sponsor | Shao Pengfei |
|---|---|
| Phase | NA |
| Status | Not yet recruiting |
| Study type | INTERVENTIONAL |
| Allocation | randomized |
| Design | parallel |
| Masking | triple |
| Primary purpose | diagnostic |
| Enrollment | 200 |
| Start date | 1 December 2024 |
| Primary completion | 1 January 2030 |
| Estimated completion | 31 December 2030 |
| Sites | 1 location across China |
Drugs / interventions tested
- Accurate Prediction Artificial Intelligence Models
Conditions studied
- Prostate Cancer — all drugs for Prostate Cancer →
- Prostate Intraductal Carcinoma — all drugs for Prostate Intraductal Carcinoma →
- Prostate Cancer Aggressiveness — all drugs for Prostate Cancer Aggressiveness →
- Prostate Cancer Stage — all drugs for Prostate Cancer Stage →
Sponsor
Shao Pengfei
Who can join
30 and older, male only, with Prostate Cancer or Prostate Intraductal Carcinoma. Patients with the condition only — healthy volunteers not accepted.
Sponsor's own description
The aim of this clinical trial is whether artificial intelligence models can be used for accurate clinical preoperative diagnosis and postoperative diagnosis of pathological findings, and will also measure the accuracy of the predictions made by the artificial intelligence models.The main target questions addressed by the model building are: 1. whether the AI model can learn from preoperative MRI and postoperative Whole Slide Images so as to accurately predict information such as benignness or malignancy, aggressiveness, grading, subtypes, genes, etc. for participants suspected of having prostate cancer preoperatively/puncturally. 2. whether the AI model is capable of learning postoperative macropathology slides to enable outcome diagnosis of surgical pathology slides in new participants. Participants will: 1. complete an MRI examination and have their MRI images analysed by the established AI model to make an accurate diagnosis of them. 2. Based on the diagnosis, if prostate cancer is predicted, they will undergo radical prostate cancer surgery and refine their surgical pathology.
Publications & conference data
No peer-reviewed publications indexed yet for this trial.
Verify or expand the search:
- PubMed search for NCT06662708
- Europe PMC full search
- ASCO Meeting Library
- ESMO Meeting Library
- bioRxiv preprints
- medRxiv preprints
- Google Scholar
Related trials
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Currently open trials in the same condition.
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- NCT07234981 — PSMA-PET Guided De-escalation of Salvage Radiation Treatment in Recurrent Prostate Cancer · Phase 2 · recruiting
- NCT07027124 — Neoadjuvant ADT + Darolutamide With Pembrolizumab, Followed by Adjuvant Pembrolizumab in Molecularly Stratified High-Ris · Phase 2 · recruiting
- NCT07426094 — PRO-BOOST-N: Prostate-First Versus Combined Prostate and Nodal Dose Escalation in PSMA PET-Staged Node-Positive Prostate · Phase 2, PHASE3 · recruiting
Other Shao Pengfei trials
Trials by the same sponsor.
- NCT07141225 — Application of the "Off-Clamp And Sutureless" Technique in Robot-Assisted Partial Nephrectomy · NA · recruiting
- NCT07020169 — Using 3D Kidney Model Based on Artificial Intelligence to Assist Partial Nephrectomy: A Prospective Validation Study · NA · recruiting
- NCT06714916 — Optimising Renal Tumour Management Through Artificial Intelligence Modules · recruiting
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Verify against primary sources
- ClinicalTrials.gov — authoritative US registry record
- WHO ICTRP — international registry index
- EU Clinical Trials Register
- Sponsor press releases (Google)
- Trial protocol + status: ClinicalTrials.gov NCT06662708 (US National Library of Medicine, public domain)
- Drug + disease cross-links: matched in real time against Drug Landscape's normalised drug + company + condition tables
- Sponsor: as reported to ClinicalTrials.gov by Shao Pengfei
- Last refreshed: 29 October 2024
Drug Landscape aggregates and links these public records for informational use only. Always verify against the primary source before clinical or regulatory decisions. Canonical URL: https://druglandscape.com/trial/NCT06662708.
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