Clinical Validation of Radiomics Artificial Intelligence: Application to Breast Cancer Treatment Planning

Recruiting

• Conditions: Breast Cancer
• Interventions: Other: The development of new clinical AI solutions to predict treatment response to neoadjuvant chemotherapy (NAC) in breast cancer

• Registration Number: NCT05070884
• Lead Sponsor: Instituto de Investigacion Sanitaria La Fe

Brief Summary

RadioVal will develop and implement interoperable solutions for clinical deployment of the radiomics tools, including information, training, and communication packages for clinicians and patients, as well as standard operating procedures for the integration of radiomics in clinical oncology. With this study, we will clinically validate these solutions, by looking at their reliability for precise breast cancer diagnosis, treatment recommendation and prognosis estimate, treatment response, evaluation of residual disease and outcome prediction.

Detailed Description

Not available

Study Timeline

• Study First Submitted: 2021-09-20
• Study First Submitted QC: 2021-10-04
• Study First Posted: 2021-10-07
• Status Verified: 2022-09
• Last Update Submitted: 2023-02-01
• Last Update Posted: 2023-02-03
• Study Start: 2023-06-01
• Primary Completion: 2025-08
• Study Completion: 2025-12

Recruitment & Eligibility

• Status: RECRUITING
• Sex: Female
• Target Recruitment: 5000

Inclusion Criteria

• Females ≥ 18 years up to 85 years old
• Individuals referred to hospitals for diagnosis of breast cancer
• Availability of radiological images: 2D mammography or 2D synthetic digital tomosynthesis, ultrasound, or magnetic resonance
• Availability of pathological report (surgical specimen)
• Availability of (Neoadjuvant) treatment allocation (scheme, duration, benefit)
• Availability of treatment response

Exclusion Criteria

• Patient with incomplete or low-quality data (radiological, pathological or clinical)

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Arm && Interventions

Group	Intervention	Description
non respondants of neo treatment	The development of new clinical AI solutions to predict treatment response to neoadjuvant chemotherapy (NAC) in breast cancer	those patients with no response or partial response when administered with Chemotherapy prior to sugery

Primary Outcome Measures

Name	Time	Method
Percentage of patients non-respondents vs respondents in neoadjuvant breast cancer treatment (Estimate tumor aggressiveness)	Baseline and after neoadjuvant treatment (4-6 months)	Proportion of patients who have complete response evaluating the target lesion according to Miller/Payne Grading system \[Ogston et al., 2003\]: 1A. Evaluation of target Tumor: G5 as pathological complete response, no tumor left; G4:more than 90% loss of tumor cells; G3: between 30-90% reduction in tumor cells; G2: loss of tumor \<30%; G1: no reduction. 1B: Evaluating the lymph nodes: A: negative; B: lymph nodes with metastasis and without changes by chemotherapy; C: lymph nodes with metastasis with evidence of partial response, D: lymph nodes with changes attributed to response without residual infiltration. 1C: Using images to evaluated radiological response: Size and diameter in millimeters of the target lesion using RM and TC or PET/CT for extension analysis (lymph nodes and metastasis).

Trial Locations

Locations (8)

University of Zagreb School of Medicine; 🇭🇷 Zagreb, Croatia

Ain Shams University; 🇪🇬 El Cairo, Egypt

Medical University of Gdansk; 🇵🇱 Gdańsk, Poland

Hospital Universitario y Politécnico La Fe de Valencia; 🇪🇸 Valencia, Spain

Karolinska Institute; 🇸🇪 Stockholm, Sweden

Hacettepe University; 🇹🇷 Ankara, Turkey

Alexander Fleming; 🇦🇷 Buenos Aires, Argentina

Medical University of Vienna; 🇦🇹 Vienna, Austria