10 results on '"Torelli, Nathan"'
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2. Spatiotemporal Fractionation in Radiotherapy
- Author
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Torelli, Nathan and Torelli, Nathan
- Abstract
In current clinical practice, radiotherapy treatments are often fractionated, i.e. the total radiation dose is equally divided into small fractions to be delivered daily over a period of few days or weeks. It has recently been shown in silico that spatiotemporal fractionation schemes, i.e. delivering distinct dose distributions in different fractions, can potentially improve the treatment. This is possible if these dose distributions are designed such that different fractions deliver similar doses to normal tissues (i.e. exploit the fractionation effect), but each fraction delivers high single-fraction doses to alternating parts of the tumor (i.e. achieve partial hypofractionation in the tumor). Thereby, the ratio of biological dose in the tumor versus the normal tissue can be improved. In this project, we further developed this innovative and novel concept. In particular, we focused on: 1. Developing new treatment planning algorithms for spatiotemporal fractionation 2. Identifying potential clinical applications of spatiotemporal fractionation with the aim of bringing spatiotemporal fractionation towards the design and implementation of a phase I clinical trial. Spatiotemporal fractionation is associated with higher complexity in treatment planning and delivery. Different plans with distinct dose distributions for different fractions must be designed such that all fractions together deliver the prescribed biological dose to the tumor. To that end, novel mathematical optimization methods for treatment planning have been developed, which are based on the cumulative biological dose rather than the physical dose. In particular, we developed robust treatment planning methods to account for geometric uncertainty in the patient setup and biological uncertainty in the fractionation sensitivity, which may lead to a degradation of the resulting treatment if not accounted for. It was shown that spatiotemporally fractionated treatments can be obtained which are robust against
- Published
- 2024
3. Evaluation of the hoof centre-of-pressure path in horses affected by chronic osteoarthritic pain
- Author
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Buser, Larissa Irina, primary, Torelli, Nathan, additional, Andreis, Sabrina, additional, Witte, Stefan, additional, and Spadavecchia, Claudia, additional
- Published
- 2023
- Full Text
- View/download PDF
4. 2739: Dosimetrically motivated collimator angle optimization for SRS of multiple brain metastases
- Author
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Torelli, Nathan, Gao, Liming, and Unkelbach, Jan
- Published
- 2024
- Full Text
- View/download PDF
5. Spatiotemporal fractionation schemes for stereotactic radiosurgery of multiple brain metastases
- Author
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Torelli, Nathan, Papp, Dávid, Unkelbach, Jan, Torelli, Nathan, Papp, Dávid, and Unkelbach, Jan
- Abstract
BACKGROUND Stereotactic radiosurgery (SRS) is an established treatment for patients with brain metastases (BMs). However, damage to the healthy brain may limit the tumor dose for patients with multiple lesions. PURPOSE In this study, we investigate the potential of spatiotemporal fractionation schemes to reduce the biological dose received by the healthy brain in SRS of multiple BMs, and also demonstrate a novel concept of spatiotemporal fractionation for polymetastatic cancer patients that faces less hurdles for clinical implementation. METHODS Spatiotemporal fractionation (STF) schemes aim at partial hypofractionation in the metastases along with more uniform fractionation in the healthy brain. This is achieved by delivering distinct dose distributions in different fractions, which are designed based on their cumulative biologically effective dose ( ) such that each fraction contributes with high doses to complementary parts of the target volume, while similar dose baths are delivered to the normal tissue. For patients with multiple brain metastases, a novel constrained approach to spatiotemporal fractionation (cSTF) is proposed, which is more robust against setup and biological uncertainties. The approach aims at irradiating entire metastases with possibly different doses, but spatially similar dose distributions in every fraction, where the optimal dose contribution of every fraction to each metastasis is determined using a new planning objective to be added to the BED-based treatment plan optimization problem. The benefits of spatiotemporal fractionation schemes are evaluated for three patients, each with >25 BMs. RESULTS For the same tumor BED$_{10}$ and the same brain volume exposed to high doses in all plans, the mean brain BED$_{2}$ can be reduced compared to uniformly fractionated plans by 9%-12% with the cSTF plans and by 13%-19% with the STF plans. In contrast to the STF plans, the cSTF plans avoid partial irradiation of the individual metastases and are
- Published
- 2023
6. Efficiency enhancements of a Monte Carlo beamlet based treatment planning process: implementation and parameter study
- Author
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Mueller, Silvan, Guyer, Gian, Volken, Werner, Frei, Daniel, Torelli, Nathan, Aebersold, Daniel M, Manser, Peter, and Fix, Michael K
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Radiological and Ultrasound Technology ,530 Physics ,610 Medicine & health ,Radiology, Nuclear Medicine and imaging - Abstract
Objective. The computational effort to perform beamlet calculation, plan optimization and final dose calculation of a treatment planning process (TPP) generating intensity modulated treatment plans is enormous, especially if Monte Carlo (MC) simulations are used for dose calculation. The goal of this work is to improve the computational efficiency of a fully MC based TPP for static and dynamic photon, electron and mixed photon-electron treatment techniques by implementing multiple methods and studying the influence of their parameters. Approach. A framework is implemented calculating MC beamlets efficiently in parallel on each available CPU core. The user can specify the desired statistical uncertainty of the beamlets, a fractional sparse dose threshold to save beamlets in a sparse format and minimal distances to the PTV surface from which 2 × 2 × 2 = 8 (medium) or even 4 × 4 × 4 = 64 (large) voxels are merged. The compromise between final plan quality and computational efficiency of beamlet calculation and optimization is studied for several parameter values to find a reasonable trade-off. For this purpose, four clinical and one academic case are considered with different treatment techniques. Main results. Setting the statistical uncertainty to 5% (photon beamlets) and 15% (electron beamlets), the fractional sparse dose threshold relative to the maximal beamlet dose to 0.1% and minimal distances for medium and large voxels to the PTV to 1 cm and 2 cm, respectively, does not lead to substantial degradation in final plan quality compared to using 2.5% (photon beamlets) and 5% (electron beamlets) statistical uncertainty and no sparse format nor voxel merging. Only OAR sparing is slightly degraded. Furthermore, computation times are reduced by about 58% (photon beamlets), 88% (electron beamlets) and 96% (optimization). Significance. Several methods are implemented improving computational efficiency of beamlet calculation and plan optimization of a fully MC based TPP without substantial degradation in final plan quality.
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- 2023
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7. A novel stochastic optimization method for handling misalignments of proton and photon doses in combined treatments
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Fabiano, Silvia, Torelli, Nathan, Papp, Dávid, Unkelbach, Jan, University of Zurich, and Fabiano, Silvia
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Organs at Risk ,Photons ,Radiological and Ultrasound Technology ,Radiotherapy Planning, Computer-Assisted ,Radiotherapy Dosage ,610 Medicine & health ,10044 Clinic for Radiation Oncology ,Neoplasms ,Proton Therapy ,Humans ,2741 Radiology, Nuclear Medicine and Imaging ,Radiology, Nuclear Medicine and imaging ,Radiotherapy, Intensity-Modulated ,Protons ,3614 Radiological and Ultrasound Technology - Abstract
Objective. Combined proton–photon treatments, where most fractions are delivered with photons and only a few are delivered with protons, may represent a practical approach to optimally use limited proton resources. It has been shown that, when organs at risk (OARs) are located within or near the tumor, the optimal multi-modality treatment uses protons to hypofractionate parts of the target volume and photons to achieve near-uniform fractionation in dose-limiting healthy tissues, thus exploiting the fractionation effect. These plans may be sensitive to range and setup errors, especially misalignments between proton and photon doses. Thus, we developed a novel stochastic optimization method to directly incorporate these uncertainties into the biologically effective dose (BED)-based simultaneous optimization of proton and photon plans. Approach. The method considers the expected value E b and standard deviation σ b of the cumulative BED b in every voxel of a structure. For the target, a piecewise quadratic penalty function of the form b min − E b − 2 σ b + 2 is minimized, aiming for plans in which the expected BED minus two times the standard deviation exceeds the prescribed BED b min . Analogously, E b + 2 σ b − b max + 2 is considered for OARs. Main results. Using a spinal metastasis case and a liver cancer patient, it is demonstrated that the novel stochastic optimization method yields robust combined treatment plans. Tumor coverage and a good sparing of the main OARs are maintained despite range and setup errors, and especially misalignments between proton and photon doses. This is achieved without explicitly considering all combinations of proton and photon error scenarios. Significance. Concerns about range and setup errors for safe clinical implementation of optimized proton–photon radiotherapy can be addressed through an appropriate stochastic planning method.
- Published
- 2022
8. A novel stochastic optimization method for handling misalignments of proton and photon doses in combined treatments
- Author
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Fabiano, Silvia, primary, Torelli, Nathan, additional, Papp, Dávid, additional, and Unkelbach, Jan, additional
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- 2022
- Full Text
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9. Impact of skin: to-target distance on treatment plan quality for mixed beam radiotherapy
- Author
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Torelli, Nathan, Müller, Silvan Andreas, Fix, Michael, Stampanoni, M, and Manser, Peter
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- 2019
10. A new approach to combined proton-photon therapy for metastatic cancer patients.
- Author
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Torelli N, Bicker Y, Marc L, Fabiano S, and Unkelbach J
- Subjects
- Humans, Radiotherapy Planning, Computer-Assisted methods, Radiotherapy, Intensity-Modulated methods, Neoplasm Metastasis radiotherapy, Radiotherapy Dosage, Proton Therapy methods, Photons therapeutic use, Brain Neoplasms secondary, Brain Neoplasms radiotherapy, Liver Neoplasms secondary, Liver Neoplasms radiotherapy
- Abstract
Objective. Proton therapy is a limited resource and is typically not available to metastatic cancer patients. Combined proton-photon therapy (CPPT), where most fractions are delivered with photons and only few with protons, represents an approach to distribute proton resources over a larger patient population. In this study, we consider stereotactic radiotherapy of multiple brain or liver metastases, and develop an approach to optimally take advantage of a single proton fraction by optimizing the proton and photon dose contributions to each individual metastasis. Approach. CPPT treatments must balance two competing goals: (1) deliver a larger dose in the proton fractions to reduce integral dose, and (2) fractionate the dose in the normal tissue between metastases, which requires using the photon fractions. Such CPPT treatments are generated by simultaneously optimizing intensity modulated proton therapy (IMPT) and intensity modulated radiotherapy (IMRT) plans based on their cumulative biologically effective dose (BED
α / β ). The dose contributions of the proton and photon fractions to each individual metastasis are handled as additional optimization variables in the optimization problem. The method is demonstrated for two patients with 29 and 30 brain metastases, and two patients with 4 and 3 liver metastases. Main results. Optimized CPPT plans increase the proton dose contribution to most of the metastases, while using photons to fractionate the dose around metastases which are large or located close to critical structures. On average, the optimized CPPT plans reduce the mean brain BED2 by 29% and the mean liver BED4 by 42% compared to IMRT-only plans. Thereby, the CPPT plans approach the dosimetric quality of IMPT-only plans, for which the mean brain BED2 and mean liver BED4 are reduced by 28% and 58%, respectively, compared to IMRT-only plans. Significance. CPPT with optimized proton and photon dose contributions to individual metastases may benefit selected metastatic cancer patients without tying up major proton resources., (Creative Commons Attribution license.)- Published
- 2024
- Full Text
- View/download PDF
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