Clinical trial · Observational
The Clinical Value of an Artificial Intelligence System Using Abbreviated Protocol of Breast MRI Facilitates Classification of Breast Lessions
NCT05892380CI-TRIAL-00066968unknownClinicalTrials.gov clinicaltrialsProvenance
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
This study aims to use a combination of abbreviated protocol and artificial intelligence to automatically identify lesions and make diagnosis without decreasing the diagnostic accuracy of breast cancer, thus enhancing the comfort of patient examination, accelerating the flow of examination and reducing the load of clinical work.
Conditions
Conditions (1)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Breast Cancer | Malignant Breast Neoplasm | CURATED_EXACT | 0.92 |
Interventions
Interventions (0)
Data not yet available
No intervention recorded.
Design
Arms and outcomes
Arms (0)
[]Primary outcomes (1)
- measure
- Comparison between the diagnostic performance of【AP breast MRI + AI】 vs. 【Radiologist】, using the pathological results as golden standard,
- timeFrame
- 2 years
- description
- Comparison of AUC, sensitivity, specificity, Positive Predictive Value (PPV) and Negative Predictive Value (NPV) between【AP breast MRI + AI】 vs. 【Radiologist】, using the pathological results as golden standard,
Secondary outcomes (2)
- measure
- Comparison of the scan time of abbreviated and full protocol
- timeFrame
- 2 years
- description
- Comparison of the scan time of abbreviated and full protocol
- measure
- Comparison of the interpretation time of abbreviated and full protocol
- timeFrame
- 2 years
- description
- Comparison of the interpretation time of abbreviated and full protocol. Although abbreviated saves scan time, the interpretation time may increase because the usage of AI.
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 18 Years
Show eligibility criteria text
Inclusion Criteria: 1. Patients with breast lesions detected by ultrasound and mammography that cannot be characterized 2. Patients who were consecutively included in our hospital for breast MRI without treatment 3. Underwent preoperative full-protocol breast MRI 4. Pathological results are available, of which benign lesions can be determined by follow-up Exclusion Criteria: 1. Poor MRI image quality 2. Patients who have been received the biopsy
References
Publications (0)
Data not yet available
No reference posted for this study.