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Artificial intelligence-assisted multi-temporal multimodal imaging and pathology images for the evaluation of breast masses

Artificial intelligence-assisted multi-temporal multimodal imaging and pathology images for the evaluation of breast masses - Artificial intelligence-assisted multi-temporal multimodal imaging and pathology images for the evaluation of breast masses

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600116028
Enrollment
Unknown
Registered
2026-01-04
Start date
2023-10-11
Completion date
Unknown
Last updated
2026-01-05

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Breast tumor

Interventions

Case group:None

Sponsors

Guangdong Provincial Hospital of Traditional Chinese Medicine
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 80 Years

Inclusion criteria

Inclusion criteria: Model 1: Early diagnosis of breast cancer and differentiation of benign and malignant breast masses: Inclusion criteria were as follows: 1. Patients admitted for puncture or surgical excision of breast masses found in our outpatient clinic or outside hospital, with routine preoperative breast ultrasound examination 2. Good quality of ultrasound images 3. confirmed by puncture or surgical pathological biopsy 4. age > 18 years, and 18 years, and 18 years, and< 80 years

Exclusion criteria

Exclusion criteria: Model 1: Early diagnosis of breast cancer and differentiation of benign and malignant breast masses Nullification criteria: The exclusion criteria are as follows: 1. Poor image quality, unable to extract features 3. No puncture biopsy or surgical histology results were obtained Model 2: Prediction of the efficacy of neoadjuvant chemotherapy NAC for breast cancer Exclusion criteria are as follows 1. Patients who did not complete the NAC regimen or received non-standard treatment (mainly HER-2 positive patients who did not receive trastuzumab) 2. Poor image quality and inability to extract features 3, lack of ultrasound images of a particular phase or incomplete multimodality ultrasound images of a particular phase 4Patients with multicentric or multifocal cancer with uncertain correlation between the lesion on the ultrasound image and postoperative pathological analysis 5. distant metastases Model III: Prognostic assessment after breast cancer surgery Exclusion criteria: 1. NAC patients who have not completed the NAC protocol or who are receiving non-standard treatment (mainly HER-2 positive patients who are not receiving trastuzumab) 2. Poor image quality and inability to extract features 3. Lack of ultrasound images of a particular stage or incomplete multimodality ultrasound images of a particular stage 4. Preoperative distant metastases 5. Incomplete clinically relevant information

Design outcomes

Primary

MeasureTime frame
Multi-temporal multimodal ultrasound images;Pre-operative puncture pathology images;Integration of ultrasound and pathology image multimodality;Type of puncture or surgical pathology mass;Complete remission of neoadjuvant chemotherapy pathology;Disease-free survival;

Secondary

MeasureTime frame
Size of primary focus;Age at first diagnosis;Menopausal state;Hormone receptor;Human epidermal growth factor receptor-2;Ki-67;Molecular subtype;Histologic typing;Types of breast cancer;Neoadjuvant chemotherapy treatment protocols;Tumor staging;

Countries

China

Contacts

Public ContactShi Jiayao

Guangdong Provincial Hospital of Traditional Chinese Medicine

295423432@qq.com+86 132 6501 1638

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026