Publications (3)1.45 Total impact
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Article: A Decision Support System for the assisted diagnosis of brain tumors: A feasibility study for (18)F-FDG PET preclinical studies.
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ABSTRACT: Decision support systems for the assisted medical diagnosis offer the main feature of giving assessments which are poorly affected from arbitrary clinical reasoning. Aim of this work was to assess the feasibility of a decision support system for the assisted diagnosis of brain cancer, such approach presenting potential for early diagnosis of tumors and for the classification of the degree of the disease progression. For this purpose, a supervised learning algorithm combined with a pattern recognition method was developed and cross-validated in (18)F-FDG PET studies of a model of a brain tumour implantation.Conference proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference 08/2012; 2012:6255-8. -
Article: PVE Correction in PET-CT Whole-Body Oncological Studies From PVE-Affected Images
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ABSTRACT: Partial Volume Effect (PVE) in PET-CT oncological studies affects the estimation of quantitative parameters useful for lesion malignancy differentiation and for monitoring disease and response to therapy. The aim of this work was to investigate the clinical feasibility and accuracy of PVE correction methods based on Recovery Coefficients (RC) as function of measured Lesion-to-Background ratio (L/B)<sub>m</sub> and measured lesion volume (V<sub>m</sub>). PET-CT measurements were performed. The radioactivity concentration (C<sub>m</sub>) and V<sub>m</sub> were measured from images using Operator-Dependent and Operator-Independent (OI) techniques. RC curves were obtained combining RC from NEMA 2001 IQ phantom measurements as function of Sphere-to-Background ratio (S/B)<sub>m</sub> and sphere V<sub>m</sub>. PVE correction was applied to PET-CT studies of anthropomorphic oncological phantoms and to PET-CT oncological studies (basal and follow up). The underestimation of C<sub>m</sub> due to PVE in the NEMA IQ spheres (up to 80%) confirmed the severity of the error. The more feasible (always applicable, noise insensitive, reproducible) way to measure radioactivity was found by the use of an OI threshold technique. Our results showed that this measurement technique allows to achieve a PVE correction accuracy >; 87% (error in radioactivity estimate <; 13%) for a sphere diameter >; 1 cm. In patient studies the PVE correction was found to modify both SUV and SUV variations during patient follow up and our analysis showed that a PVE corrected SUV quantification increases the diagnostic confidence of oncological PET-CT studies.IEEE Transactions on Nuclear Science 07/2011; · 1.45 Impact Factor -
Chapter: Partial Volume Correction Methods Based on Measured Lesion-to-Background Ratio in PET-CT Oncological Studies
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ABSTRACT: This study evaluates Operator-Dependent (OD) and Operator-Independent (OI) methods for Partial Volume effect Correction (PVC) in PET-CT oncological studies. The proposed PVC methods are based on curves of Recovery Coefficients (RC) versus Measured Lesion-to-Background ratios (M-L/B). NEMA IQ phantom PET-CT measurements were performed for RC curves estimation, for M-L/B from 2 to 30. Validation of the PVC methods was performed by 18F-FDG PET-CT studies of a Breast Oncological Phantom, miming from 1cm to 1.56 cm lesions in breasts, for prepared L/B from 14 to 54. An OI PVC method based on a threshold-technique for the estimation of lesion uptake was found the most accurate method (accuracy >80%). PVC methods were applied to the SUV quantification of 11 18F-FDG PET-CT oncological studies. Results prove PV strongly affects lesion quantification and needs to be corrected. When a decrement in the PET lesion volume is observed, PVC-SUV always decreased well fitting the clinical assessment, as from diagnostic report. When an increment in the PET lesion volume is observed, results suggest PVC-SUV should be used together with the PET lesion volume for a better characterization or therapy response of oncological lesions. KeywordsPET-CT-quantification-PV-RC01/2010: pages 360-363;
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Institutions
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2010
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Università degli Studi di Milano-Bicocca
Monza, Lombardy, Italy
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