NCT04721444

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

Optimising Cancer Therapy And Identifying Causes of Pneumonitis USing Artificial Intelligence

• Status: Completed
• Phase: —
• Study type: Observational
• Enrollment: 1,211 (actual)
• Sponsor: Royal Marsden NHS Foundation Trust · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: —

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

• Lung Cancer
• Covid19
• Pneumonitis

Interventions

Type	Name	Description
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

Timeline

• Start date: 2021-01-27
• Primary completion: 2022-03-01
• Completion: 2022-03-01
• First posted: 2021-01-22
• Last updated: 2022-06-29

Locations

3 sites across 1 country: United Kingdom