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NCT Number: NCT04060706

Heuristics, Algorithms and Machine Learning: Evaluation & Testing in Radiation Therapy

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.

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Key information

Conditions

Cancer Neoplasms

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Cambridge University Hospitals NHS Foundation Trust

Cambridge, Cambridgeshire, CB2 0QQ, United Kingdom

Location status: Recruiting

Location contact

Amy Bates

CONTACT

[email protected]

01223 256296 ext. 256296

Raj Dr. Jena

PRINCIPAL_INVESTIGATOR

Who can participate

Only the study team can determine whether someone qualifies for participation.

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.

Treatment and study plan

Radical Image-Guided Radiotherapy

Radiation

Questionnaires administered will monitor the clinical toxicity experienced by each patient up to 5 years post radiotherapy

Primary outcomes

  1. Machine Learning Modelling

    Time frame: 8 years from FPFV

    Characterise machine learning models for the four disease sites. Developing machine learning algorithms for autosegmentation of normal tissue anatomy, and to extend machine learning algorithms to identify and segment normal tissue structures in cone beam CT images, and to utilise the ML segmentations to evaluate image signatures correlated with treatment toxicity

  2. Predictive Modelling

    Time frame: 8 years from FPFV

    Predict performance matches with published techniques. Combining the machine learning models in outcome 1, with pre-treatment assessment data and on-treatment quantitative assessments in outcome 3 for the construction and evaluation of a predictive mathematical model

  3. Clinical Toxicity Evaluation

    Time frame: 8 years from FPFV

    Evaluation of the clinical toxicity experienced by each patient up to 5 years post radiotherapy to inform the predictive models in outcome 2

Study contacts

Contact information is provided by the study sponsor or research team.

CCTU Cancer

CONTACT

[email protected]

01223 216038 ext. 216038

Meena Murthy

CONTACT

[email protected]

01223 349707 ext. 349707

Sponsors and collaborators

Lead sponsor

CCTU- Cancer Theme

Other

Collaborators

  • Microsoft Research
  • University of Cambridge

Registry information

Official study title

Hamlet-RT: Heuristics, Algorithms and Machine Learning: Evaluation & Testing in Radiation Therapy

Acronym: Hamlet rt

Important dates

Study start
2019
Primary completion
2023
Study completion
2028
First posted
Aug 19, 2019
Registry last updated
Aug 2, 2021

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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