Radiomics breakthrough could spark the head and neck cancer radiotherapy revolution
Publication Date : 08/02/2023
Artificial intelligence (AI), defined as machine capability of imitating human intelligence, has already been implemented on a large scale in oncology and radiotherapy. One of the two main branches (the virtual one) of machine learning depending on the application, artificial intelligence is involved both in the diagnostics processes as well as treatment planning, - dose delivery and radiotherapy quality assurance (QA). Head and neck cancer (HNC), although it is the 6th malignancy in incidence worldwide, is redoubtable due to the high rate of therapeutic failures, especially of loco-regional recurrence. Although intensity-modulated treatment techniques have brought benefits especially in limiting the toxicities associated with irradiation, AI and especially radiomics, due the possibility to extract data from high-resolution medical imaging in order to build predictive diagnostic and prognostic models, could upgrade the technological revolution in HNC radiotherapy at a higher level. Beyond the already intensively studied diagnostic applications, radiomics could be useful for predicting the response to radio-chemotherapy, anticipating treatment related toxicities and for pre-therapeutic evaluation of the need for adaptive radiotherapy (ART). Clinical-radiomic models have superior predictive power and the delta variation of radiomic features could be a biomarker still less evaluated. Due to characteristics of modern radiotherapy which includes as standard the image guided radiotherapy (IGRT) concept using the computer tomography (CT) simulator and Cone Beam CT (CBCT) to ensure the accuracy of the patient's positioning during the treatment, radiomics in radiotherapy could be the spearhead of the translation radiomics in daily clinical routine and of the HNC RGRT concept development.
No. of Downloads :