Predictive modelling of head and neck cancer tumour based on statistical analysis. (1st March 2013)

• Record Type: Journal Article
• Authors: Azimi, Maryam
• Is Part Of: International journal of collaborative enterprise. Volume 3:Number 1(2012)
• Page Start: 60
• Page End: 71
• Publication Date: 2013-03-01
• Subjects: H&N cancer -- prediction model -- regression analysis -- tumour deformation; 338.805
• Languages: English
• ISSNs: 1740-2085

Abstract

Most of the cancer patients receive radiation therapy each year, either alone or in conjunction with surgery, chemotherapy or other forms of cancer therapy. The primary objective of radiotherapy is to deliver the correct dose of radiation to cancerous region with minimum damage to surrounding normal tissues in head and neck. Based on pre-treatment computer tomography (CT) images, a master plan for the treatment is developed. Most of the current radiation therapy planning systems assumes that the tumour geometry will not change during the course of treatment. However, there is a critical flaw in this assumption, because tumour geometry is shown to be changing over time. Accordingly, there is a critical need to track the changes in tumour geometry over time during the radiotherapy treatment. We proposed a methodology in order to monitor and predict daily (fraction day) tumour volume and surface changes of head and neck cancer tumours during the entire radiation therapy period. Tumour volume and surface values are calculated using patients' CT scan data. Statistical analyses are applied in order to generate the predictive models and validation. The main goal of the proposed methodology is increasing the accuracy of each therapy and quality of life for patients.