Clinical trial NCT04060706: Heuristics, Algorithms and Machine Learning: Evaluation & Testing in Radiation Therapy
Official title: Hamlet-RT: Heuristics, Algorithms and Machine Learning: Evaluation & Testing in Radiation Therapy
Study type: OBSERVATIONAL
Overall status: RECRUITING
Conditions: Cancer
Keywords: Radiotherapy
Image-guided
Head & Neck
Brain
Lung
Prostate
Adults
Lead sponsor: Cambridge University Hospitals NHS Foundation Trust
Sponsor class: OTHER
Collaborators: name: University of Cambridge
name: Microsoft Research
First posted: 2019-08-19
Enrollment: 310
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Adults suitable for radical image-guided radiotherapy with Prostate, Head \& Neck, Brain, or Lung Cancer. The variation in conditions is based on the requirements of Machine Learning algorithms requiring high levels of clinical applicability, which depends on the quality and quantity of the input data available. The input data set therefore should adequately encompass the variation in anatomy encountered in the population.

Brief summary: The Hamlet.rt study is a prospective data collection and patient questionnaire study for patients undergoing image-guided radiotherapy with curative intent.

The aim of the study is to use novel machine learning and mathematical techniques to build a model that can predict the risk of significant side effects from radiotherapy treatment for an individual patient: using calculations of normal tissue dose from radiotherapy treatment planning and patient baseline characteristics derived from image and non-image data, continuously updated as the patient is reviewed both during and after treatment.

A secondary goal of the project is to facilitate research in machine learning and medical image processing for radiation therapy through the creation of a discoverable and shared data resource for research use.


Eligibility criteria: Inclusion Criteria:

* Participant is willing and able to give informed consent for participation in the study
* Male or Female
* Aged 18 years or older
* Diagnosed with primary prostate cancer, head and neck cancer, lung cancer, or brain tumour
* Treated with curative intent
* Suitable for radical image guided radiotherapy
* WHO ECOG performance status 0 or 1
* Expected survival of 18 months or more

Exclusion Criteria:

* Participant is not willing or able to complete the protocol-stated requirements of the study, e.g. accessing \& completing web-based long-term follow-up questionnaires.

Primary outcomes:
measure: Machine Learning Modelling
timeFrame: 8 years from FPFV
measure: Predictive Modelling
timeFrame: 8 years from FPFV
measure: Clinical Toxicity Evaluation
timeFrame: 8 years from FPFV
Secondary outcomes:
Other outcomes:
Locations:
city: Cambridge
country: United Kingdom
facility: Cambridge University Hospitals NHS Foundation Trust
state: Cambridgeshire
Study officials:
affiliation: Cambridge University Hospitals NHS Foundation Trust & the University of Cambridge
name: Raj Dr. Jena
role: PRINCIPAL_INVESTIGATOR
affiliation: Cambridge University Hospitals NHS Foundation Trust
name: Suzanne Miller
role: PRINCIPAL_INVESTIGATOR
affiliation: Cambridge University Hospitals NHS Foundation Trust
name: Amy Bates
role: PRINCIPAL_INVESTIGATOR
References: