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Optimising Cancer Therapy And Identifying Causes of Pneumonitis USing Artificial Intelligence (COVID-19)

NCT04721444 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 1211

Last updated 2022-06-29

No results posted yet for this study

Summary

Distinguishing changes on patients that have received thoracic radiotherapy and patients that are currently receiving or have recently received IO and presenting lung changes which will be identified using AI.

Conditions

Interventions

DIAGNOSTIC_TEST

Machine Learning Classification of parenchymal lung change cause

Arms A \& B: Radiomics and deep-learning approaches will be used on patient's imaging to develop a feature vector that can distinguish parenchymal lung changes, e.g. infection from drug-toxicity.

DIAGNOSTIC_TEST

Machine Learning Classification of recurrence and non-recurrence

Arm C: Radiomics and deep-learning approaches will be used on patient's imaging to develop a risk-signature for recurrence of malignancy following radical treatment

Sponsors & Collaborators

  • Royal Marsden NHS Foundation Trust

    lead OTHER

Principal Investigators

  • Richard Lee · Royal Marsden NHS Foundation Trust

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2021-01-27
Primary Completion
2022-03-01
Completion
2022-03-01

Countries

  • United Kingdom

Study Locations

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Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT04721444 on ClinicalTrials.gov