Response Prediction to Neoadjuvant Chemoradiation in Esophageal Cancer Using Artificial Intelligence & Machine Learning (QARC)

December 25, 2022 updated by: Dr Kundan Singh Chufal

Pathological Response Prediction to Neo-adjuvant Chemoradiotherapy in Esophageal Carcinoma and Comparison of Engineered Features Versus Deep Learning Models

In esophageal carcinoma, neoadjuvant concurrent chemo-radiotherapy (NA-CCRT) followed by surgery is the current standard of care and ample evidence has accumulated supporting the view that complete pathological response (pCR) is a positive prognostic marker for improved outcomes. Predicting the probability of achieving pCR prior to neoadjuvant treatment could permit modification of treatment protocols for those patients unlikely to achieve pCR.

Radiomics is a new entrant in the field of imaging where specific features are derived from the intensity and distribution pattern of pixels based on a region-of-interest (ROI). The features thus extracted can then be used for prediction modelling similar to other -omics datasets. Preliminary investigations examining its utility have been performed and its applications have thus far focused on screening and survival prediction after treatment. Due to the multi-dimensional nature of data extracted using radiomics, Artificial Intelligence (AI) methods are ideally suited for analysing and modelling radiomic features.

Machine Learning (ML) and Deep Learning (DL)[utilising Convolutional Neural Networks (CNN)] are both part of the AI framework. In contrast to ML, DL is a new entrant and has been utilised by some medical researchers for modelling using prediction-type algorithms. Besides significantly reducing the workflow associated with Radiomics-based research, feature engineering and modelling using DL are immune to the effects of incorrect ROI delineation. However, the main limitation of DL is the 'blackbox' effect, in which the underlying basis of a CNN is not known. This has been mitigated in part by the visualisation of activation maps directly on the image dataset to prove biological plausibility of predictions. The comparative performance of both types of modelling is also not known.

Our objective is to investigate pCR probability in our study population using radiomics-based ML and AI-based modelling. We will also investigate the comparative performance of both modelling techniques. For DL based prediction modelling, we will attempt to provide biological plausibility on the basis of activation maps.

Study Overview

Study Type

Observational

Enrollment (Anticipated)

150

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

      • Wollongong, Australia, 2500
        • Illawarra Cancer Care Centre
    • Delhi
      • New Delhi, Delhi, India, 110019
        • Rajiv Gandhi Cancer Institute & Research Center

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

18 years and older (Adult, Older Adult)

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Sampling Method

Non-Probability Sample

Study Population

Patient records in each participating research center from January 2011 to 1st May 2020

Description

Inclusion Criteria:

  • ECOG Performance Status: 0-2
  • Patients with histopathological or cytopathological confirmed malignancy of the esophagus
  • Histology: Squamous Cell Carcinoma and Adenocarcinoma
  • Patients should have received NeoAdjuvant Concurrent Chemoradiation (NACCRT) followed by Surgery
  • All therapeutic interventions (Radiotherapy, Chemotherapy & Surgery) delivered within participating institutions
  • At least one pre-NACCRT DICOM imaging dataset (HRCT/ 18-FDG PET-CT/ Radiotherapy planning CT) for each patient

Exclusion Criteria:

  • Patients with any metallic implants in the region of interest
  • Patient with locally advanced disease or metastatic disease (T4 disease, Fistula, metastases)
  • Patients with prior history of radiotherapy in the same region
  • Patients developing a second malignancy in the esophagus

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Observational Models: Cohort
  • Time Perspectives: Other

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
Study Group
Patients undergoing NA-CCRT followed by Surgery
Neo-Adjuvant Radiotherapy via any technique, delivered concurrently with Neo-Adjuvant Chemotherapy.
Neo-Adjuvant Chemotherapy, delivered concurrently with Neo-Adjuvant Radiotherapy.
Esophagectomy, performed 4-6 weeks after completion of Neo-Adjuvant Concurrent ChemoRadiation

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Time Frame
Develop models to predict pCR based on pre-neoadjuvant imaging modalities
Time Frame: August 2021
August 2021
Perform a clinical audit of patient outcomes (OS, RFS, pCR rate) after new-adjuvant chemoradiation and esophagectomy
Time Frame: January 2020
January 2020

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Investigators

  • Principal Investigator: Kundan S Chufal, MD, Rajiv Gandhi Cancer Institute & Research Center

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

January 16, 2020

Primary Completion (Anticipated)

July 1, 2023

Study Completion (Anticipated)

July 1, 2023

Study Registration Dates

First Submitted

July 23, 2020

First Submitted That Met QC Criteria

July 23, 2020

First Posted (Actual)

July 28, 2020

Study Record Updates

Last Update Posted (Estimate)

December 28, 2022

Last Update Submitted That Met QC Criteria

December 25, 2022

Last Verified

December 1, 2022

More Information

Terms related to this study

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

No

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

Clinical Trials on Esophageal Neoplasm

Clinical Trials on Neo-Adjuvant Radiotherapy

3
Subscribe