Vincenzo Patera
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Vincenzo Patera has a total of 6 co-authors. Here are the top co-authors by number of shared publications:
- Edoardo D’andrea
Postgraduate School of Medical Physics, Azienda Ospedaliero-Universitaria Policlinico Umberto I, 00161 Rome, Italy
2 shared publications - Marta Cremonesi
Medical Physics Unit, IEO, European Institute of Oncology IRCCS, 20141 Milan, Italy
2 shared publications - Massimiliano Pacilio
Department of Medical Physics, Azienda Ospedaliero-Universitaria Policlinico Umberto I, 00161 Rome, Italy
2 shared publications - Nico Lanconelli
Department of Physics and Astronomy, Università di Bologna, 40126 Bologna, Italy
2 shared publications - Andrea Politano
Postgraduate School of Medical Physics, Azienda Ospedaliero-Universitaria Policlinico Umberto I, 00161 Rome, Italy
1 shared publication - Bartolomeo Cassano
Department of Research, Diagnosis and Innovative Technologies, Medical Physics Unit, IRCCS Regina Elena National Cancer Institute, 00144 Rome, Italy
1 shared publication
Latest Publications
- Open Access
- 19 January 2025
- Published by MDPI AG in Applied Sciences
- Vol. 15 (2) , 958
The Essential Role of Monte Carlo Simulations for Lung Dosimetry in Liver Radioembolization—Part B: 166Ho Microspheres
This study compares dosimetric approaches for lung dosimetry in 166 radioembolization (Ho-TARE) with direct Monte Carlo (MC) simulations on a voxelized anthropomorphic phantom derived from a real patient’s CT scan, preserving the patient’s lung density distribution. Lung dosimetry was assessed for five lung shunt (LS) scenarios with conventional methods: the mono-compartmental organ-level approach (MIRD), voxel S-value convolution for soft tissue (kST, ICRU soft tissue with 1.04 g/cm3) and lung tissue (kLT, ICRU lung tissue with 0.296 g/cm3), local density rescaling (kSTL and kLTL, respectively, for soft tissue and lung tissue), or global rescaling for a lung mean density of 0.221 g/cm3 (kLT221). Significant underestimations in the mean absorbed dose (AD) were observed, with relative differences with respect to the reference (MC) of −64% for MIRD, −93% for kST, −56% for kSTL, −76% for kLT, −68% for kLT221, and −60% for kLTL. Given the high heterogeneity of lung tissue, standard dosimetric approaches cannot accurately estimate the AD. Additionally, MC results for 166Ho showed notable spatial absorbed dose inhomogeneity, highlighting the need for tailored lung dosimetry in Ho-TARE accounting for the patient-specific lung density distribution. MC-based dosimetry thus proves to be essential for safe and effective radioembolization treatment planning in the presence of LS.
- 19 January 2025
- Published by MDPI AG in Applied Sciences
- Vol. 15 (2) , 958
Open AccessThe Essential Role of Monte Carlo Simulations for Lung Dosimetry in Liver Radioembolization—Part B: 166Ho Microspheres
This study compares dosimetric approaches for lung dosimetry in 166 radioembolization (Ho-TARE) with direct Monte Carlo (MC) simulations on a voxelized anthropomorphic phantom derived from a real patient’s CT scan, preserving the patient’s lung density distribution. Lung dosimetry was assessed for five lung shunt (LS) scenarios with conventional methods: the mono-compartmental organ-level approach (MIRD), voxel S-value convolution for soft tissue (kST, ICRU soft tissue with 1.04 g/cm3) and lung tissue (kLT, ICRU lung tissue with 0.296 g/cm3), local density rescaling (kSTL and kLTL, respectively, for soft tissue and lung tissue), or global rescaling for a lung mean density of 0.221 g/cm3 (kLT221). Significant underestimations in the mean absorbed dose (AD) were observed, with relative differences with respect to the reference (MC) of −64% for MIRD, −93% for kST, −56% for kSTL, −76% for kLT, −68% for kLT221, and −60% for kLTL. Given the high heterogeneity of lung tissue, standard dosimetric approaches cannot accurately estimate the AD. Additionally, MC results for 166Ho showed notable spatial absorbed dose inhomogeneity, highlighting the need for tailored lung dosimetry in Ho-TARE accounting for the patient-specific lung density distribution. MC-based dosimetry thus proves to be essential for safe and effective radioembolization treatment planning in the presence of LS.
- Open Access
- 30 August 2024
- Published by MDPI AG in Applied Sciences
- Vol. 14 (17) , 7684
The Essential Role of Monte Carlo Simulations for Lung Dosimetry in Liver Radioembolization with 90Y Microspheres
This study compares various methodologies for lung dosimetry in radioembolization using Monte Carlo (MC) simulations. A voxelized anthropomorphic phantom, created from a real patient’s CT scan, preserved the actual density distribution of the lungs. Lung dosimetry was evaluated for five lung-shunt (LS) cases using traditional methods: the mono-compartmental organ-level approach (MIRD), local energy deposition (LED), and convolution with voxel S-values, either with local density corrections (SVOX_L) or without (SVOX_ST). Additionally, a novel voxel S-value (VSV) kernel for lung tissue with an ICRU density of was developed. Calculations were performed using either the ICRU lung density (Lung_296), the average lung density of the phantom (Lung_221), or the local density (Lung_L). The comparison revealed significant underestimations in the mean absorbed dose (AD) for the classical approaches: approximately − for MIRD, − for LED, − for SVOX_L, and − for SVOX_ST. Similarly, calculations with the lung VSV kernel showed underestimations of about − for Lung_296, − for Lung_221, and − for Lung_L. Given the high heterogeneity of lung tissue, traditional dosimetric methods fail to provide accurate estimates of the mean AD for the lungs. Therefore, MC dosimetry based on patient images is recommended as the preferred method for precise assessment of lung AD during radioembolization.- 30 August 2024
- Published by MDPI AG in Applied Sciences
- Vol. 14 (17) , 7684
Open AccessThe Essential Role of Monte Carlo Simulations for Lung Dosimetry in Liver Radioembolization with 90Y Microspheres
This study compares various methodologies for lung dosimetry in radioembolization using Monte Carlo (MC) simulations. A voxelized anthropomorphic phantom, created from a real patient’s CT scan, preserved the actual density distribution of the lungs. Lung dosimetry was evaluated for five lung-shunt (LS) cases using traditional methods: the mono-compartmental organ-level approach (MIRD), local energy deposition (LED), and convolution with voxel S-values, either with local density corrections (SVOX_L) or without (SVOX_ST). Additionally, a novel voxel S-value (VSV) kernel for lung tissue with an ICRU density of was developed. Calculations were performed using either the ICRU lung density (Lung_296), the average lung density of the phantom (Lung_221), or the local density (Lung_L). The comparison revealed significant underestimations in the mean absorbed dose (AD) for the classical approaches: approximately − for MIRD, − for LED, − for SVOX_L, and − for SVOX_ST. Similarly, calculations with the lung VSV kernel showed underestimations of about − for Lung_296, − for Lung_221, and − for Lung_L. Given the high heterogeneity of lung tissue, traditional dosimetric methods fail to provide accurate estimates of the mean AD for the lungs. Therefore, MC dosimetry based on patient images is recommended as the preferred method for precise assessment of lung AD during radioembolization.