Development of Clinically High Efficient Platforms for Individualised Treatment of Cervix Cancer

NCT05102240 | Recruiting

• 2 other identifiers: TMC IRB 900787CTRI/2021/08/035810
• Study Type: observational
• Target: 1,800
• Locations: 1 country
• Sites: 1

Brief Summary

Retrospective study utilizing patient data to develop and validate Machine Learning application. Available imaging data sets of patients who have completed treatment will be used to develop Normal tissue complication probability and Tumour control probability Hypothesis Integrating existing radiation treatment information, quantitative imaging and patient outcome data from completed and ongoing clinical trials will allow development of knowledge based systems for efficient treatment delivery and allow selection of patients for intensified treatment approaches in cervix cancer.

Conditions

Cervix Cancer

Keywords

Advanced Radiation Technology; Quantitative Imaging; Molecular Biology; Machine Learning

Outcome Measures

Primary Outcomes (3)

• Generation of software for automated target delineation for cervix cancer

  1\. To develop and validate automated platforms for target delineation and planning for cervix cancer in time efficient manner through a. Machine learning based detection of abnormal cancerous tissues in multimodality medical diagnostic images. b . To train machine base systems for automated planning of external radiation and brachytherapy for gynaecological cancers.

  3 years

• Development and validation of Normal Tissue Complication Plots

  2\. To use existing databases and radiation dose maps, imaging texture features and adverse events data for machine learning to develop "normal tissue complication plots "and to identify cervix cancer patient subgroups that may benefit from advanced radiation techniques (like proton treatment)

  3 years

• Identify "high risk patient population" that may benefit from intensification of treatment in future

  3\. To use advanced image texture analysis within ongoing institutional and collaborative clinical trials to identify "high risk patient population" that may benefit from intensification of treatment in future

  3 years

Eligibility Criteria

• Age: 18 Years - 90 Years
• Gender Eligibility Details: This study is about cervical cancer.
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Cervical cancer patients treated within ongoing and completed clinical trials of chemoradiation and brachytherapy for cervix cancer at our institute with access to MRI/CT images at time of diagnosis and brachytherapy, undergoing postoperative or definitive radiotherapy and treated within trials of postoperative or definitive RT.

You may qualify if:

• For Aim 1 and Aim 3:
• Patients treated within ongoing and completed clinical trials of chemoradiation and brachytherapy for cervix cancer with access to MRI/CT images at the time of diagnosis and brachytherapy For Aim 2
• Patients undergoing postoperative or definitive radiotherapy and treated within trials of postoperative or definitive RT.

You may not qualify if:

• Lack of disease or toxicity outcomes.
• Lack of images in the hospital database.

Sponsors & Collaborators

• Tata Memorial Hospital: lead
• Bhabha Atomic Research Centre and Indian Institute of Technology, Mumbai.: collaborator
• Erasmus Medical Center: collaborator

Study Sites (1)

Advanced Centre of Treatment Research and Education In Cancer,Tata Memorial Centre

Navi Mumbai, Maharashtra, 410210, India

RECRUITING

MeSH Terms

Conditions

Uterine Cervical Neoplasms

Condition Hierarchy (Ancestors)

Uterine Neoplasms; Genital Neoplasms, Female; Urogenital Neoplasms; Neoplasms by Site; Neoplasms; Uterine Cervical Diseases; Uterine Diseases; Genital Diseases, Female; Female Urogenital Diseases; Female Urogenital Diseases and Pregnancy Complications; Urogenital Diseases; Genital Diseases

Study Officials

• Supriya Sastri (nee Chopra), MD

  Tata Memorial Centre, The Advanced Centre for Treatment, Research and Education in Cancer (ACTREC)

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Supriya Sastri (nee Chopra), MD

CONTACT

02227405000; supriyasastri@gmail.com

Supriya Sastri (nee Chopra), MD

CONTACT

02227405000; schopra@actrec.gov.in

Study Design

• Study Type: observational
• Observational Model: OTHER
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER GOV
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Professor, Radiation Oncology

Study Record Dates

• First Submitted: October 20, 2021
• First Posted: November 1, 2021
• Study Start: February 24, 2022
• Primary Completion (Estimated): June 30, 2026
• Study Completion (Estimated): June 30, 2026
• Last Updated: February 20, 2026

Record last verified: 2026-02

Locations

IN (1)