Neoplasms

Respiratory Tract (Lung and Bronchial) Diseases

All Conditions

Infections

Symptoms and General Pathology

Lung Neoplasms

COVID-19

Pneumonia

Pneumonia, Viral

Communicable Diseases

Respiratory Tract Infections

Virus Diseases

Coronavirus Infections

Coronaviridae Infections

Nidovirales Infections

RNA Virus Infections

Lung Diseases

Respiratory Tract Diseases

Training set: Pneumonitis in the context of IO therapy and negative for infectious pneumonia (including COVID-19)

Training set B1: IO and RT naive and pneumonia (without COVID-19)

Training set B2: IO and RT naive and confirmed COVID-19 positive with pneumonia

Training set: Pneumonitis in the context of thoracic RT and negative for infectious pneumonia (including COVID-19)

Test set C1: Patients on IO and with possible toxicity versus COVID-19 or other infective pneumonitis

Test set C2: Patients with pneumonitis in context of thoracic RT with possible toxicity versus COVID-19 or other infective pneumonitis.

Patients with radiotherapy planning CT scans and post-treatment surveillance CT scans at 3, 6 and 12-months post treatment

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.

Machine Learning Classification of parenchymal lung change cause

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

Machine Learning Classification of recurrence and non-recurrence

Richard Lee

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.

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

Optimising Cancer Therapy And Identifying Causes of Pneumonitis USing Artificial Intelligence

The development and validation of an ML/radiomic classifier to distinguish between Infective/COVID-19 pneumonia and cancer therapy induced lung changes

to develop a prognostic AI/radiomic signature for NSCLC recurrence after radical RT (Conventional fractionated RT +/- chemotherapy or stereotactic body RT (SBRT)) to stratify appropriate surveillance and onward care, thus minimising unnecessary hospital visits and resource use.

Study title	NCT ID	Conditions	Interventions	Eligibility	Organization	Link
Optimising Cancer Therapy And Identifying Causes of Pneumonitis USing Artificial Intelligence (COVID-19)	NCT04721444	Lung Cancer Covid19 Pneumonitis	Machine Learnin... Machine Learnin...	18 Years -	Royal Marsden NHS Foundation Trust
Optimising Cancer Therapy And Identifying Causes of Pneumonitis USing Artificial Intelligence (COVID-19)	NCT04721444	Lung Cancer Covid19 Pneumonitis	Machine Learnin... Machine Learnin...	18 Years -	Royal Marsden NHS Foundation Trust

Spots Global Cancer Trial Database for machine learning classification of parenchymal lung change cause