Ignite Creation Date:
2024-05-06 @ 8:10 PM
Last Modification Date:
2024-10-26 @ 3:22 PM
Study NCT ID:
NCT06286267
Status:
RECRUITING
Last Update Posted:
2024-02-29
First Post:
2024-02-22
Brief Title:
AI-Assisted System for Accurate Diagnosis and Prognosis of Breast Phyllodes Tumors
Sponsor:
Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
Organization:
Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
Study Overview
Official Title:
Development of an Artificial Intelligence-Based System for Precise Diagnosis and Prognosis of Breast Phyllodes Tumors
Status:
RECRUITING
Status Verified Date:
2024-02
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief Summary:
Breast phyllodes tumor PT is a rare fibroepithelial tumor accounting for 1 to 3 of all breast tumors categorized by the WHO into benign borderline and malignant based on histopathology features such as tumor border stromal cellularity stromal atypia mitotic activity and stromal overgrowth Malignant PTs account for 18-25 with high local recurrence up to 65 and distant metastasis rates 16-25 Benign PT could progress to malignancy after multiple recurrences Therefore Early accurate diagnosis and identification of therapeutic targets are crucial for improving outcomes and survival rates
In recent years there has been growing interest in the application of artificial intelligence AI in medical diagnostics AI can integrate clinical information histopathological images and multi-omics data to assist in pathological and clinical diagnosis prognosis prediction and molecular profilingAI has shown promising results in various areas including the diagnosis of different cancers such as colorectal cancer breast cancer and prostate cancer However PT differs from breast cancer in diagnosis and treatment approach Therefore establishing an AI-based system for the precise diagnosis and prognosis assessment of PT is crucial for personalized medicine
The research team led by Dr Nie Yan is one of the few in Guangdong Province and even nationally specializing in PT research Their team has been conducting research on the malignant progression metastasis mechanisms and molecular markers for PT The team has identified key mechanisms such as fibroblast-to-myofibroblast differentiation and the role of tumor-associated macrophages in promoting this differentiation They have also identified molecular markers including miR-21 α-SMA CCL18 and CCL5 which are more accurate in predicting tumor recurrence risk compared to traditional histopathological grading
The project has collected high-quality data from nearly a thousand breast PT patients including imaging histopathology and survival data and has performed transcriptome gene sequencing on tissue samples They aim to build a comprehensive multi-omics database for breast PT and create an AI-based model for early diagnosis and prognosis prediction This research has the potential to improve the diagnosis and treatment of breast PT address the disparities in breast PT care across different regions in China and contribute to the development of new therapeutic targets
In recent years there has been growing interest in the application of artificial intelligence AI in medical diagnostics AI can integrate clinical information histopathological images and multi-omics data to assist in pathological and clinical diagnosis prognosis prediction and molecular profilingAI has shown promising results in various areas including the diagnosis of different cancers such as colorectal cancer breast cancer and prostate cancer However PT differs from breast cancer in diagnosis and treatment approach Therefore establishing an AI-based system for the precise diagnosis and prognosis assessment of PT is crucial for personalized medicine
The research team led by Dr Nie Yan is one of the few in Guangdong Province and even nationally specializing in PT research Their team has been conducting research on the malignant progression metastasis mechanisms and molecular markers for PT The team has identified key mechanisms such as fibroblast-to-myofibroblast differentiation and the role of tumor-associated macrophages in promoting this differentiation They have also identified molecular markers including miR-21 α-SMA CCL18 and CCL5 which are more accurate in predicting tumor recurrence risk compared to traditional histopathological grading
The project has collected high-quality data from nearly a thousand breast PT patients including imaging histopathology and survival data and has performed transcriptome gene sequencing on tissue samples They aim to build a comprehensive multi-omics database for breast PT and create an AI-based model for early diagnosis and prognosis prediction This research has the potential to improve the diagnosis and treatment of breast PT address the disparities in breast PT care across different regions in China and contribute to the development of new therapeutic targets
Detailed Description:
None
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None