Cancer treatment needs refinement. Any method aimed at treating a tumor, from extirpation to radiotherapy, requires a precise knowledge of the cancerous tumor margins so that the intervention on it may be performed in such a way that the possibilities of healing are maximised and the effects on surrounding healthy tissues are minimised. A group of researchers from the Department of Mathematics at the Universitat Jaume I in Castelló have implemented a mathematical method that is applied to medical imaging analysis, which enables to determine the margins of a tumor in the prostate, lung or bladder.
In most cases, the task of delimitating the contour of a tumor is carried out manually by a specialist. According to his or her experience, the doctor draws the perimeter within which he or she locates the cancerous tissue on an image obtained by computerised axial tomography (CAT) or magnetic resonance (MR) images. This perimeter may vary slightly depending on the professional who traces it. The method developed by the mathematicians at the UJI does away with such a great subjective variability, and enables a single, more objective and standardised confidence interval to be obtained for each tumor type and patient depending on his or her characteristics.
“What we have done is to define an average and most adjusted confidence interval possible from a series of contours delineated by various professionals on one same tumor, in such a way that it only surrounds the tissue that is considered cancerous and leaves any surrounding tissue which is not to be submitted to treatment unharmed”, as Ximo Gual, the person in charge of the research, explains.
Hugo Cerdà | alfa
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