S. Broggi
Vita-Salute San Raffaele University
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Publication
Featured researches published by S. Broggi.
Physics in Medicine and Biology | 2011
E Faggiano; C. Fiorino; Elisa Scalco; S. Broggi; Mauro Cattaneo; E. Maggiulli; I. Dell’Oca; N. Di Muzio; R. Calandrino; Giovanna Rizzo
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.
Radiotherapy and Oncology | 2009
S. Broggi; C. Fiorino; I. Dell'Oca; N. Dinapoli; M. Paiusco; A Muraglia; E. Maggiulli; F. Ricchetti; Vincenzo Valentini; Gaetano Sanguineti; Gm Cattaneo; N. Di Muzio; R. Calandrino
PURPOSE To assess anatomical, clinical and dosimetric pre-treatment parameters, possibly predictors of parotid shrinkage during radiotherapy of head and neck cancer (HNC). MATERIALS Data of 174 parotids from four institutions were analysed; patients were treated with IMRT, with radical and adjuvant intent. Parotid shrinkage was evaluated by the volumetric difference (DeltaV) between parotid volumes at the end and those at the start of the therapy, as assessed by CT images (MVCT for 40 patients, KVCT for 47 patients). Correlation between DeltaVcc/% and a number of dosimetric, clinical and geometrical parameters was assessed. Univariate as well as stepwise logistic multivariate (MVA) analyses were performed by considering as an end-point a DeltaVcc/% larger than the median value. Linear models of DeltaV (continuous variable) based on the most predictive variables found at the MVA were developed. RESULTS Median DeltaVcc/% were 6.95 cc and 26%, respectively. The most predictive independent variables of DeltaVcc at MVA were the initial parotid volume (IPV, OR: 1.100; p=0.0002) and Dmean (OR: 1.059; p=0.038). The main independent predictors of DeltaV% at MVA were age (OR: 0.968; p=0.041) and V40 (OR: 1.0338; p=0.013). DeltaVcc and DeltaV% may be well described by the equations: DeltaVcc=-2.44+0.076 Dmean (Gy)+0.279 IPV (cc) and DeltaV%=34.23+0.192 V40 (%)-0.2203 age (year). The predictive power of the DeltaVcc model is higher than that of the DeltaV% model. CONCLUSIONS IPV/age and Dmean/V40 are the major dosimetric and clinical/anatomic predictors of DeltaVcc and DeltaV%. DeltaVcc and DeltaV% may be well described by bi-linear models including the above-mentioned variables.
Technology in Cancer Research & Treatment | 2015
S. Broggi; Elisa Scalco; C. Fiorino; M.L. Belli; Giuseppe Sanguineti; F. Ricchetti; I. Dell'Oca; N. Dinapoli; Vincenzo Valentini; N. Di Muzio; Giovanni Mauro Cattaneo; G. Rizzo
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 fist 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.
Physica Medica | 2017
M. Branchini; C. Fiorino; I. Dell'Oca; M.L. Belli; L. Perna; N. Di Muzio; R. Calandrino; S. Broggi
PURPOSE The aim of this study was to test the feasibility and dosimetric accuracy of a method that employs planning CT-to-MVCT deformable image registration (DIR) for calculation of the daily dose for head and neck (HN) patients treated with Helical Tomotherapy (HT). METHODS For each patient, the planning kVCT (CTplan) was deformably registered to the MVCT acquired at the 15th therapy session (MV15) with a B-Spline Free Form algorithm using Mattes mutual information (open-source software 3D Slicer), resulting in a deformed CT (CTdef). On the same day as MVCT15, a kVCT was acquired with the patient in the same treatment position (CT15). The original HT plans were recalculated both on CTdef and CT15, and the corresponding dose distributions were compared; local dose differences <2% of the prescribed dose (DD2%) and 2D/3D gamma-index values (2%-2mm) were assessed respectively with Mapcheck SNC Patient software (Sun Nuclear) and with 3D-Slicer. RESULTS On average, 87.9%±1.2% of voxels were found for DD2% (on average 27 slices available for each patient) and 94.6%±0.8% of points passed the 2D gamma analysis test while the 3D gamma test was satisfied in 94.8%±0.8% of bodys voxels. CONCLUSIONS This study represents the first demonstration of the dosimetric accuracy of kVCT-to-MVCT DIR for dose of the day computations. The suggested method is sufficiently fast and reliable to be used for daily delivered dose evaluations in clinical strategies for adaptive Tomotherapy of HN cancer.
Radiotherapy and Oncology | 2016
S. Broggi; I. Dell'Oca; C. Fiorino; Elena Incerti; Maria Picchio; M.L. Belli; Paola Mapelli; A. Chiara; N. Di Muzio; Giovanni Mauro Cattaneo; R. Calandrino
S871 ________________________________________________________________________________ patients with high-risk extremity soft tissue sarcoma. A twotier registration was used to align the tumor VOI within each dynamic frame at TP1 and align the volumes at TP2 to the volumes at TP1. After registration, the voxel-wise transfer constant K within a VOI covering the whole tumor normalized to a reference region of normal tissue area closed to the tumor was calculated. The responder threshold was determined by linear regression via evaluating the 95% confidence interval [-T, T] in the residuals from the reference region. The difference of the voxel-wise ΔK within the tumor between TP1 and TP2 was calculated. Three classes of voxels within the tumor VOI were determined: voxels having ΔK value exceed threshold T were designated in red, below -T were designated in blue, and otherwise designated in green indicating no significant change. The volume fractions with respect to three subvolumes of the tumor VOI were computed as F+ (red voxels), F-(blue voxels) and F0 (green voxels).
Radiotherapy and Oncology | 2016
M. Branchini; S. Broggi; M.L. Belli; C. Fiorino; Giovanni Mauro Cattaneo; L. Perna; R. Calandrino
S851 ________________________________________________________________________________ Conclusion: A method has been developed to assist the adaptive planning process for lung patients receiving FFF VMAT radiotherapy. This provides a means of assessing the dosimetric effect of tumour changes to determine whether a new treatment plan is necessary. It showed that for 25% of patients who received full treatment replans no replan was necessary, as the dosimetric effect of tumour shrinkage was insignificant in terms of both target coverage and OAR doses. Therefore it allows significant time savings in the treatment replanning process. Use of the technique is limited to patients who display tumour volume changes with no other significant changes to internal/external anatomy.
Radiotherapy and Oncology | 2013
S. Garelli; R. Raso; Elisa Scalco; S. Vagge; A. Bacigalupo; C. Salvetti; P. Passoni; S. Broggi; G. Rizzo; C. Fiorino
Conclusions: Delivery of IMRT plans with IE provided sufficient photon fluence extending beyond the breast skin surface proving the sufficiency of the 8mm margin in the AL direction. However, comparing the IMRT plans with against without IE increased all the SR and PTV doses for uncorrected setup errors. Moreover, for the plans with extended fluence, the maximum values near the skin were found to increase, especially for higher setup errors >8mm. Therefore, daily image guidance and consistent patient repositioning was warranted for not increasing the superficial dose.
Clinical Oncology | 2016
N. Di Muzio; A. Fodor; B. Noris Chiorda; S. Broggi; P. Mangili; Riccardo Valdagni; I. Dell'Oca; M. Pasetti; C. Deantoni; A. Chiara; G. Berardi; A. Briganti; R. Calandrino; C. Cozzarini; C. Fiorino
Physica Medica | 2016
Roberta Castriconi; Paolo Russo; Giovanni Mettivier; F. Di Lillo; Antonio Sarno; M. Ciocca; A. Mirandola; C. Sini; S. Broggi
International Journal of Radiation Oncology Biology Physics | 2009
C. Cozzarini; C. Fiorino; F. Alongi; G. Berardi; Angelo Bolognesi; S. Broggi; A.M. Deli; M. Pasetti; Patrizio Rigatti; N. Di Muzio