External beam radiotherapy is commonly prescribed for @entity263 . Although new radiation techniques allow high doses to be delivered to the target, the surrounding healthy organs (rectum and bladder) may suffer from irradiation, which might produce undesirable side-effects. Hence, the understanding of the complex @entity137 dose-volume effect relationships is crucial to adapt the treatment, thereby decreasing the risk of @entity137 . In this paper, we introduce a novel method to classify @entity1 at risk of presenting @entity548 based on a Deterministic Multi-way Analysis (DMA) of three-dimensional planned dose distributions across a population. After a non-rigid spatial alignment of the anatomies applied to the dose distributions, the proposed method seeks for two bases of vectors representing @entity548 and non @entity548 @entity1 by using the Canonical Polyadic (CP) decomposition of two fourth order arrays of the planned doses. A @entity1 is then classified according to its distance to the subspaces spanned by both bases. A total of 99 @entity1 treated for @entity263 were used to analyze and test the performance of the proposed approach, named CP-DMA, in a leave-one-out cross validation scheme. Results were compared with supervised (linear discriminant analysis, support vector machine, K-means, K-nearest neighbor) and unsupervised (recent principal component analysis-based algorithm, and multidimensional classification method) approaches based on the registered dose distribution. Moreover, CP-DMA was also compared with the Normal Tissue Complication Probability (NTCP) model. The CP- @entity3496 method allowed @entity548 @entity1 to be classified with good specificity and sensitivity values, outperforming the classical approaches.

On feature extraction and classification in XXXX radiotherapy using tensor decompositions.

@entity1 :: ('9606', 'Species') :: ['patients', 'patient'] @entity137 :: ('MESH:D064420', 'Disease') :: ['toxicity'] @entity263 :: ('MESH:D011471', 'Disease') :: ['prostate cancer'] @entity3496 :: ('MESH:C405765', 'Chemical') :: ['DMA'] @entity548 :: ('MESH:D006470', 'Disease') :: ['rectal bleeding', 'bleeding']
@entity263 :: (MESH:D011471,Disease) :: ['prostate cancer']
