Clinical Trials Logo
  1. Home
  2. Predictive Cancer Model
  3. NCT04511481
  4. Details
NCT04511481 Clinical Trial

Deep Learning Magnetic Resonance Imaging Radiomic Predict Platinum-sensitive in Patients With Epithelial Ovarian Cancer

Predictive Cancer Model Clinical Trial

Official title:
Deep Learning Magnetic Resonance Imaging Radiomic Predict Platinum-sensitive in Patients With Epithelial Ovarian Cancer

Clinical Trial Details — Status: Recruiting

Administrative data
NCT number NCT04511481
Other study ID # SYSEC-KY-KS-2020-072
Secondary ID
Status Recruiting
Phase
First received
Last updated
Start date April 15, 2020
Est. completion date January 1, 2021

Study information
Verified date August 2020
Source Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
Contact Ruilin Lei, phD
Phone +8618898325866
Email leiruilin1988@163.com
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial Summary

Platinum-sensitive is an important basis for the treatment of recurrent epithelial ovarian cancer (EOC) without effective methods to predict.We aimed to develop and validate the EOC deep learning system to predict the platinum-sensitive of EOC patients through analysis of enhanced magnetic resonance imaging (MRI) images before initial treatment.Ninety-three EOC patients received platinum-based chemotherapy (>= 4 cycles) and debulking surgery from Sun Yat-sen Memorial Hospitalin China from January 2011 to January 2020 were enrolled. This deep-learning EOC signature achieved a high predictive power for platinum-sensitive, and the signature based on MRI whole volume is better than that on primary tumor area only.

Recruitment information / eligibility
Status Recruiting
Enrollment 93
Est. completion date January 1, 2021
Est. primary completion date August 3, 2020
Accepts healthy volunteers No
Gender Female
Age group 22 Years to 99 Years
Eligibility Inclusion Criteria:

- (1)Patients with epithelial ovarian cancer (2 )Patients received platinum-based chemotherapy (>= 4 cycles) and debulking surgery

Exclusion Criteria:

- Patients with epithelial ovarian cancer received less than 4 cycles platinum-based chemotherapy or no debulking surgery

Study Design

Related Conditions & MeSH terms

Intervention

Other:
• Radiomic Algorithm
Different radiomic and machine learning strategies for radiomic features extraction, sorting features and model constriction

Locations
Country Name City State
China Sun Yat-Sen Memorial Hospital of Sun Yat-sen University Guangzhou Guangdong

Sponsors (1)
Lead Sponsor Collaborator
Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

Country where clinical trial is conducted

China, 

Outcome
Type Measure Description Time frame Safety issue
Primary Platinum sensitivity Platinum sensitivity 9 years
See also
  Status Clinical Trial Phase
Recruiting NCT06023966 - A Clinical Prospective Study to Validate a Risk Scoring Model for the HMGC After Curative Surgery
Recruiting NCT04535466 - Diagnosis Predictive Modle for Dense Density Breast Tissue Based on Radiomics
Recruiting NCT03280134 - A Prospective Validation Cohort Study of a Prediction System on nSLN Metastasis in Early Breast Cancer N/A
Recruiting NCT03253107 - Predicting Biomarker of Gastric Cancer Chemotherapy Response
Recruiting NCT06364371 - Dynamic Multi-omics Integration Model to Predict Neoadjuvant Therapy Response in Locally Advanced Rectal Cancer
Recruiting NCT05997147 - A Preoperative Model to Predict the Lymphovascular Invasion in Pancreatic Ductal Adenocarcinoma
Recruiting NCT05929365 - Innovative Approach to Detect Recurrent Colorectal Lesions With Surveillance Via Mutation Analysis & Clinical Phenotype
Active, not recruiting NCT05973331 - Prospective Validation of an EHR-based Pancreatic Cancer Risk Model
Recruiting NCT05338073 - KM3D Multicenter Cancer Consortium: Predicting Patient Response Using 3D Cell Culture Models
Recruiting NCT06391892 - Liquid Biopsy (ctDNA) Guided Treatment in Localized Pancreatic Cancer: Neoadjuvant CTX vs. Upfront Surgery Phase 3
Recruiting NCT06202404 - Predicting Tumor Metastasis by Employing a Target Organ/Primary Lesion Fusion Radiomics Model
Completed NCT06411015 - Prognostic Evaluation Prediction Model Survival Spinal Epidural Metastases
Completed NCT04079283 - Radiomics of Immunotherapeutics Response Evaluation and Prediction
Completed NCT06092918 - Generation and Validation of Predictive Models for Localized Prostate Cancer Treated With External Radiotherapy.
Recruiting NCT06339307 - A Prospective Clinical Study to Validate a Preoperative Risk Scoring Model for LNM in GC Patients
Recruiting NCT04185779 - COLO-COHORT (Colorectal Cancer Cohort) Study
Active, not recruiting NCT06074029 - Exploratory Study on the Therapeutic Effect Prediction Model of Advanced BTC Immunotherapy Phase 1/Phase 2
Recruiting NCT05741944 - The Value of a Risk Prediction Tool (PERSARC) for Effective Treatment Decisions of Soft-tissue Sarcomas Patients N/A
Recruiting NCT04452058 - CT-based Radiomic Algorithm for Assisting Surgery Decision and Predicting Immunotherapy Response of NSCLC
Active, not recruiting NCT06140823 - Prospective Validation of Liver Cancer Risk Computation (LIRIC) Models