Search

The treatment of head and neck cancer (HNC) patients is one of the widest applications of radiation treatment. One of the main organs involved in dose delivery and playing a relevant role in the quality of life of patients treated for HNC is the parotid gland, the major salivary gland, whose damage causes a pathologic condition called xerostomia. During the treatment, HNC patients may undergo significant anatomical changes; it was generally reported that parotids shrink during RT with a shift of the center of mass (COM) toward the midline. These modifications cause a translation of the glands into the high dose region, thus the effective delivered dose on parotids is significantly higher than that planned. Therefore, the study of local changes in parotid glands due to irradiation is still an open challenge, and the exploitation of the information content in medical images acquired during the radiation treatment is of practical interest for the non-invasiveness of these techniques. The aim of this work was thus the evaluation of morphological and structural modifications induced by RT on parotid glands using image-based indices extracted from CT images acquired during the treatment. In particular, in this PhD project it was proposed to estimate morphological changes by the deformation of the glands, evaluated by applying a non-rigid registration method expressly optimized and validated on CT images of the HN district. Secondly, a method of image analysis based on textural feature extraction was proposed to characterize structural variations of parotid tissue. All these methods were evaluated and optimized for the clinical problem and all these parameters were studied in relation to dosimetric and clinical indices and to the clinical outcome, in order to better assess their contribution in this research field. Parotid deformation was here estimated through an image registration and contour propagation method, based on Free Form Deformation and Mutual Information. A de

To quantitatively assess the predictive power of early variations of parotid gland volume and density on final changes at the end of therapy and, possibly, on acute xerostomia during IMRT for head-neck cancer.

The Jacobian of the deformation field of the registration between images taken during Radiotherapy is a measure of compression/expansion of the voxels within an organ. The Jacobian mean value was applied to investigate possible correlations between parotid deformation and anatomical, clinical and dosimetric parameters. Data of 84 patients were analyzed. Parotid deformation was evaluated through Jacobian maps of images taken at the start and at the end of the treatment. Several clinical, geometrical and dosimetric factors were considered. Correlation between Jacobian mean value and these parameters was assessed through Spearman's test. Univariate and multivariate logistic analyses were performed by considering as the end point the first quartile value of the Jacobian mean value. Parotid dose volume histograms were stratified according to gland deformation, assessing the most predictive dose-volume combination. At multivariate analysis, age (p = 0.02), overlap between tumor volume and parotid gland (p = 0.0006) and the parotid volume receiving more than 10 Gy (p = 0.02) were found as the best independent predictors, by considering Jacobian mean value first quartile, the parotid volume receiving more than 10 Gy and 40 Gy were found as the most predictive dosimetric parameters. Parotid glands were divided in three different sub-groups (bad-, medium- and good dose volume histogram). The risk to have Jacobian means value lower than first quartile was 39.6% versus 19.6% versus 11.3% in these three groups. By including in the multivariate analysis this "dose volume grouping" parameter, age and bad dose volume histogram were found as the most predictive parameters for large shrinkage. The pattern of parotid deformation may be well predicted by some pre-treatment variables; a bad dose volume histogram seems the most important predictor.

We developed an automatic method for regional analysis of femoral neck images acquired by peripheral quantitative computed tomography (pQCT), based on automatic spatial re-alignment and segmentation; the segmentation method, based on a morphological approach, explicitly accounts for the presence of three different bone compartments: cortical region, trabecular region, and transition zone between cortical and trabecular compartments. The proposed method was applied on 13 femoral neck sections derived from female donors who were undergoing hip replacement surgery for primary degenerative arthritis or fracture, and a typical densitometric and structural analysis was performed both globally and regionally. The proposed segmentation method was quantitatively evaluated by comparing automatic contour and the corresponding manual contours delineated by three operators using metrics based on surface distance (average symmetric distance, ASD) and volumetric overlapping (dice similarity coefficient, DSC). The same approach was used to validate the automatic spatial orientation, considering as metric the difference between manual and automatic angle orientation. Results confirm a satisfactory agreement between automatic and manual performances (ASD < 0.41 mm, DSC > 0.91, orientation difference = 3.61°) and show that globally our algorithm performs very well. Concerning regional analysis application, from our results we can observe that significant differences are present among the four bone quadrants. © 2010 Biomedical Engineering Society.

We developed an efficient technique to auto-propagate parotid gland contours from planning kVCT to daily MVCT images of head-and-neck cancer patients treated with helical tomotherapy. The method deformed a 3D surface mesh constructed from manual kVCT contours by B-spline free-form deformation to generate optimal and smooth contours. Deformation was calculated by elastic image registration between kVCT and MVCT images. Data from ten head-and-neck cancer patients were considered and manual contours by three observers were included in both kVCT and MVCT images. A preliminary inter-observer variability analysis demonstrated the importance of contour propagation in tomotherapy application: a high variability was reported in MVCT parotid volume estimation (p = 0.0176, ANOVA test) and a larger uncertainty of MVCT contouring compared with kVCT was demonstrated by DICE and volume variability indices (Wilcoxon signed rank test, p < 10-4 for both indices). The performance analysis of our method showed no significant differences between automatic and manual contours in terms of volumes (p > 0.05, in a multiple comparison Tukey test), center-of-mass distances (p = 0.3043, ANOVA test), DICE values (p = 0.1672, Wilcoxon signed rank test) and average and maximum symmetric distances (p = 0.2043, p = 0.8228 Wilcoxon signed rank tests). Results suggested that our contour propagation method could successfully substitute human contouring on MVCT images. © 2011 Institute of Physics and Engineering in Medicine.