MedTrace Logo

AI & Radiomics for Stratification of Lung Nodules After Radically Treated Cancer

NCT05375591 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 1000

Last updated 2022-05-24

No results posted yet for this study

Summary

This study will assess the utility of radiomics and artificial intelligence approaches to new lung nodules in patients who have undergone radical treatment for a previous cancer.

Conditions

  • Indeterminate Pulmonary Nodules
  • Lung Metastases
  • Second Primary Cancer
  • Lung Cancer

Interventions

OTHER

Non-Interventional Study

First nodule detection CT scans as per eligibility criteria will be used as input into in-house software to extract multiple radiomic features and used to develop a machine learning based classifier to differentiate nodule aetiology. Scans will also be used as input in to a deep learning/convolutional neural network models to perform automated imaging classification.

Sponsors & Collaborators

  • Institute of Cancer Research, United Kingdom

    collaborator OTHER

  • National Institute for Health Research, United Kingdom

    collaborator OTHER_GOV

  • Royal Brompton & Harefield NHS Foundation Trust

    collaborator OTHER

  • Royal Marsden Partners Cancer Alliance

    collaborator UNKNOWN

  • Imperial College London

    collaborator OTHER

  • Oxford University Hospitals NHS Trust

    collaborator OTHER

  • National Heart and Lung Institute

    collaborator OTHER

  • Royal Marsden NHS Foundation Trust

    lead OTHER

Principal Investigators

  • Richard Lee · The Royal Marsden Hospitals NHS Trust

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2021-10-13
Primary Completion
2022-11-01
Completion
2026-11-01

Countries

  • United Kingdom

Study Locations

More Related Trials

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 NCT05375591 on ClinicalTrials.gov