Viewing Study NCT06588569



Ignite Creation Date: 2024-10-26 @ 3:39 PM
Last Modification Date: 2024-10-26 @ 3:39 PM
Study NCT ID: NCT06588569
Status: ACTIVE_NOT_RECRUITING
Last Update Posted: None
First Post: 2024-09-04

Brief Title: Multi-mode Ablation and Molecular Imaging Multi-omics Study for Digestive-Origin Malignant Liver Tumors
Sponsor: None
Organization: None

Study Overview

Official Title: Construction of a Multi-mode Ablation Treatment System and Molecular Imaging Multi-omics Study for Malignant Liver Tumors of Digestive System Origin
Status: ACTIVE_NOT_RECRUITING
Status Verified Date: 2024-09
Last Known Status: None
Delayed Posting: No
If Stopped, Why?: Not Stopped
Has Expanded Access: No
If Expanded Access, NCT#: N/A
Has Expanded Access, NCT# Status: N/A
Acronym: None
Brief Summary: This single-center parallel-controlled clinical trial aims to establish a multi-mode ablation system for liver malignant tumors originating from the digestive system The study will evaluate the safety and efficacy of multi-mode tumor ablation utilizing a multi-mode imaging platform for ablation planning and immediate evaluation of intraoperative ablation effects Additionally the study will employ multi-omics and multi-mode imaging techniques to explore the spatiotemporal heterogeneity and immune escape mechanisms of liver metastases from gastrointestinal tumors providing guidance for treatment strategy formulation and prognostic evaluation
Detailed Description: This is a single-center parallel-controlled clinical trial The study includes a total enrollment of 20 subjects 10 patients with primary liver cancer will be divided into an experimental group and a control group 5 cases per group 10 patients with Colorectal Cancer Liver Metastases will also be divided into the experimental group and the control group 5 cases per group The purpose is to validate the safety and efficacy of multi-mode tumor ablation for liver malignant tumors aiming to establish a multi-mode tumor treatment system and obtain multi-dimensional biomedical information from patients before during and after ablation

The study will employ an interdisciplinary approach integrating statistics machine learning and artificial intelligence to establish a new technical system for rapid efficacy evaluation Additionally it will establish a multi-omics artificial intelligence-assisted diagnostic and evaluation system based on radiomics The system will use artificial intelligence algorithms to automatically locate and identify lesions based on imaging guidance information and accurately predict individual prognoses and anti-tumor immune states through comprehensive preoperative intraoperative and postoperative evaluations providing an important basis for treatment planning intraoperative dose adjustment and subsequent treatment strategies

Study Oversight

Has Oversight DMC: None
Is a FDA Regulated Drug?: None
Is a FDA Regulated Device?: None
Is an Unapproved Device?: None
Is a PPSD?: None
Is a US Export?: None
Is an FDA AA801 Violation?: None