Walter Tinganelli

Dr. Walter Tinganelli

Biophysics division, GSI Helmholtz Center for Heavy Ion Research, 64291 Darmstadt, Germany
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Research Focus & Metrics

Academic Career Length

14Years (2013-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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17 October 2020 in Cancers
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Walter TinganelliWalter Tinganelli
Walter Tinganelli
Marco DuranteMarco Durante
Marco Durante
Radiotherapy using accelerated charged particles is rapidly growing worldwide. About 85% of the cancer patients receiving particle therapy are irradiated with protons, which have physical advantages compared to X-rays but a similar biological response. In addition to the ballistic advantages, heavy ions present specific radiobiological features that can make them attractive for treating radioresistant, hypoxic tumors. An ideal heavy ion should have lower toxicity in the entrance channel (normal tissue) and be exquisitely effective in the target region (tumor). Carbon ions have been chosen because they represent the best combination in this direction. Normal tissue toxicities and second cancer risk are similar to those observed in conventional radiotherapy. In the target region, they have increased relative biological effectiveness and a reduced oxygen enhancement ratio compared to X-rays. Some radiobiological properties of densely ionizing carbon ions are so distinct from X-rays and protons that they can be considered as a different “drug” in oncology, and may elicit favorable responses such as an increased immune response and reduced angiogenesis and metastatic potential. The radiobiological properties of carbon ions should guide patient selection and treatment protocols to achieve optimal clinical results.

24 November 2015 in Scientific Reports
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Walter TinganelliWalter Tinganelli
Walter Tinganelli
Marco DuranteMarco Durante
Marco Durante
RHRyoichi Hirayama
Ryoichi Hirayama
MKMichael Krämer
Michael Krämer
AMAndreas Maier
Andreas Maier
Emanuele ScifoniEmanuele Scifoni
Emanuele Scifoni
Solid tumours often present regions with severe oxygen deprivation (hypoxia), which are resistant to both chemotherapy and radiotherapy. Increased radiosensitivity as a function of the oxygen concentration is well described for X-rays. It has also been demonstrated that radioresistance in anoxia is reduced using high-LET radiation rather than conventional X-rays. However, the dependence of the oxygen enhancement ratio (OER) on radiation quality in the regions of intermediate oxygen concentrations, those normally found in tumours, had never been measured and biophysical models were based on extrapolations. Here we present a complete survival dataset of mammalian cells exposed to different ions in oxygen concentration ranging from normoxia (21%) to anoxia (0%). The data were used to generate a model of the dependence of the OER on oxygen concentration and particle energy. The model was implemented in the ion beam treatment planning system to prescribe uniform cell killing across volumes with heterogeneous radiosensitivity. The adaptive treatment plans have been validated in two different accelerator facilities, using a biological phantom where cells can be irradiated simultaneously at three different oxygen concentrations. We thus realized a hypoxia-adapted treatment plan, which will be used for painting by voxel of hypoxic tumours visualized by functional imaging.

7 May 2022 in Radiotherapy and Oncology
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Walter TinganelliWalter Tinganelli
Walter Tinganelli
UWUli Weber
Uli Weber
APAnggraeini Puspitasari
Anggraeini Puspitasari
PSPalma Simoniello
Palma Simoniello
AAAmir Abdollahi
Amir Abdollahi
Marco DuranteMarco Durante
Marco Durante

30 March 2016 in Medical Physics
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MKMichael Krämer
Michael Krämer
Emanuele ScifoniEmanuele Scifoni
Emanuele Scifoni
CSChristoph Schuy
Christoph Schuy
MRMarta Rovituso
Marta Rovituso
Walter TinganelliWalter Tinganelli
Walter Tinganelli
Marco DuranteMarco Durante
Marco Durante
Purpose: Modern facilities for actively scanned ion beam radiotherapy allow in principle the use of helium beams, which could present specific advantages, especially for pediatric tumors. In order to assess the potential use of these beams for radiotherapy, i.e., to create realistic treatment plans, the authors set up a dedicated 4He beam model, providing base data for their treatment planning system TRiP98, and they have reported that in this work together with its physical and biological validations.Methods: A semiempirical beam model for the physical depth dose deposition and the production of nuclear fragments was developed and introduced in TRiP98. For the biological effect calculations the last version of the local effect model was used. The model predictions were experimentally verified at the HIT facility. The primary beam attenuation and the characteristics of secondary charged particles at various depth in water were investigated using 4He ion beams of 200 MeV/u. The nuclear charge of secondary fragments was identified using a ΔE/E telescope. 3D absorbed dose distributions were measured with pin point ionization chambers and the biological dosimetry experiments were realized irradiating a Chinese hamster ovary cells stack arranged in an extended target.Results: The few experimental data available on basic physical processes are reproduced by their beam model. The experimental verification of absorbed dose distributions in extended target volumes yields an overall agreement, with a slight underestimation of the lateral spread. Cell survival along a 4 cm extended target is reproduced with remarkable accuracy.Conclusions: The authors presented a simple simulation model for therapeutical 4He beams which they introduced in TRiP98, and which is validated experimentally by means of physical and biological dosimetries. Thus, it is now possible to perform detailed treatment planning studies with 4He beams, either exclusively or in combination with other ion modalities.

1 March 2022 in International Journal of Radiation Oncology, Biology, Physics
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Walter TinganelliWalter Tinganelli
Walter Tinganelli
OSOlga Sokol
Olga Sokol
MQMartina Quartieri
Martina Quartieri
APAnggraeini Puspitasari
Anggraeini Puspitasari
IDIvana Dokic
Ivana Dokic
UWUlrich Weber
Ulrich Weber

16 May 2013 in Physics in Medicine & Biology
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Emanuele ScifoniEmanuele Scifoni
Emanuele Scifoni
Walter TinganelliWalter Tinganelli
Walter Tinganelli
WWW K Weyrather
W K Weyrather
Marco DuranteMarco Durante
Marco Durante
AMAndreas Maier
Andreas Maier
MKM Krämer
M Krämer
We present a method for adapting a biologically optimized treatment planning for particle beams to a spatially inhomogeneous tumor sensitivity due to hypoxia, and detected e.g., by PET functional imaging. The TRiP98 code, established treatment planning system for particles, has been extended for including explicitly the oxygen enhancement ratio (OER) in the biological effect calculation, providing the first set up of a dedicated ion beam treatment planning approach directed to hypoxic tumors, TRiP-OER, here reported together with experimental tests. A simple semi-empirical model for calculating the OER as a function of oxygen concentration and dose averaged linear energy transfer, generating input tables for the program is introduced. The code is then extended in order to import such tables coming from the present or alternative models, accordingly and to perform forward and inverse planning, i.e., predicting the survival response of differently oxygenated areas as well as optimizing the required dose for restoring a uniform survival effect in the whole irradiated target. The multiple field optimization results show how the program selects the best beam components for treating the hypoxic regions. The calculations performed for different ions, provide indications for the possible clinical advantages of a multi-ion treatment. Finally the predictivity of the code is tested through dedicated cell culture experiments on extended targets irradiation using specially designed hypoxic chambers, providing a qualitative agreement, despite some limits in full survival calculations arising from the RBE assessment. The comparison of the predictions resulting by using different model tables are also reported.