Development of Clinically High Efficient Platforms for Individualised Treatment of Cervix Cancer

Summary

Retrospective study utilizing patient data to develop and validate Machine Learning application. Available imaging data sets of patients who have completed treatment will be used to develop Normal tissue complication probability and Tumour control probability Hypothesis Integrating existing radiation treatment information, quantitative imaging and patient outcome data from completed and ongoing clinical trials will allow development of knowledge based systems for efficient treatment delivery and allow selection of patients for intensified treatment approaches in cervix cancer.

Eligibility

Inclusion Criteria:

For Aim 1 and Aim 3:

* Patients treated within ongoing and completed clinical trials of chemoradiation and brachytherapy for cervix cancer with access to MRI/CT images at the time of diagnosis and brachytherapy For Aim 2
* Patients undergoing postoperative or definitive radiotherapy and treated within trials of postoperative or definitive RT.

Exclusion Criteria:

1. Lack of disease or toxicity outcomes.
2. Lack of images in the hospital database.

Conditions2

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