Tumors represented by breast cancer
Conditions
Interventions
(1)Research on the development and clinical application of artificial intelligence diagnosis system for multimodal imaging:NA
(2) Expert review test:Clinical Expert Group:NA
(3) Concordance study of AI decision making and clinical practice: clinical practice group:NA
Sponsors
The First Affiliated Hospital of Anhui Medical University
Eligibility
Sex/Gender
All
Age
18 Years to 90 Years
Inclusion criteria
Inclusion criteria: (I) Research on the development and clinical application of artificial intelligence diagnosis system for multimodal imaging (1) Patients with breast masses on examinations such as ultrasound, mammography, or MRI of any kind, especially BI-RADS category 3 and 4 patients; (2) Informed of this study and signed an informed consent form. Voluntary shear wave elastography examination; (3) Agreed and combined with puncture biopsy, rotary biopsy, or surgical treatment, and finally obtained the pathological diagnosis. (II) Construction of "AI+" intelligent medical ecosystem and clinical applicability research (1) Patients with pathologically confirmed breast cancer. (2) Complete treatment and pathology data.
Exclusion criteria
Exclusion criteria: (I) Research on the development and clinical application of artificial intelligence diagnosis system for multimodal imaging (1) Pregnancy or lactation; (2) Implants in the breast; (3) History of surgery on the affected side; (4) History of malignant tumor and other cachexia. (II) Construction of "AI+" intelligent medical ecosystem and clinical applicability research (1) Male breast cancer. (2) Breast cancer during pregnancy. (3) Two or more primary repeat cancers.
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| age;Menstrual status;Personal Cancer History;Family history of cancer;Location;Distance to nipple;Mass size;Echo;Boundary of the mass;Mass pattern;Calcification;BI-RADS;PSV;EDV;RI;S/D;Emax;Emin;Emean;SD;Eratio;Area;Berg' color scoring;Tozaki M four-color model;Radiomic features;assess the breast cancer risk via deep-learning based AI system;Mammogram breast density types;Biopsy Method;Histological type;WHO histological grading;Vessel carcinoma embolus;Nerve Violation;Molecular subtypes;Lymph node biopsy results;cTNM;Neoadjuvant treatment programs;Surgical method;Number of positive SLN by intraoperative cryopreservation;Number of positive SLN by postoperative paraffin examination;Number of NSLN positives;pTNM;Concordance of biopsy and postoperative molecular subtypes;Whether or not pCR;Adjunctive therapy programs;AI treatment decision recommendations;Expert independent review recommendations;Expert + AI integrated decision-making advice;Expert + AI + Guide Integrated Decision Advice;Guide Decision Advice;Consistency between clinical practice protocols and AI recommendations;Consistency between clinical practice protocols and guideline recommendations;Consistency between AI recommendations and guideline recommendations;Consistency between expert independent review recommendations and AI recommendations;Expert independent review of consistency between recommendations and guideline recommendations;Concordance between expert + AI integrated decision recommendations and guideline recommendations;Concordance between expert + AI + guideline integrated decision recommendations and guideline recommendations;Rate of change in treatment decisions;Guideline compliance rate improvement rate;Prognosis Information;Pathogenomic features; | — |
Countries
Chian
Contacts
Public ContactPei Jing
The First Affiliated Hospital of Anhui Medical University
Outcome results
None listed