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Radiotherapy Optimization

Group leader: Dr. Niklas Wahl

News

Pia's approach to proton therapy uncertainty quantification using only a single Monte Carlo dose calculation was featured in the ESTRO newsletter.

matRad, our open-source software for dose calculation and optimiztiation, keeps growing and was featured in Mathworks' techinical newsletters.

Amit's paper on joint photon-carbon treatment planning was published in the Red Journal.

Nish's work on using LSTM-ANNs for proton dose prediction is published in Medical Physics.

Niklas' ICCR presentation on confidence constraints for probabilistic treatment planning has been selected as Highlight Presentation and Hans-Peter's presentation on biological uncertainy modeling in carbon therapy won 3rd place in the rising stars competition.

Our work revolves around the development and implementation of physical, biological and mathematical models into the treatment planning process for radiation therapy. Thereby, we maintain the open source dose calculation and treatment planning toolkit "matRad" (www.matRad.org)

Currently, we focus on three topics:

Numerical optimization techniques for the quantification and minimization of uncertainties in radiation therapy
Machine Learning to infer predictive models for the outcome of radiation therapy
Incorporation of additional optimization parameters into automated radiation therapy planning

All projects are carried out in collaboration with renowned colleagues in the field:

Dr. Malte Ellerbrock @ Heidelberg Ion-Beam Therapy Center
Prof. Jan Unkelbach @ Zürich University
Prof. Philipp Hennig @ Max Planck Institute for Intelligent Systems / University Tübingen
Prof. Martin Frank @ Karslruhe Institute of Technology
Prof. Yair Censor @ University of Haifa
Prof. Reinhard Schulte @ Loma Linda University
Dr. Gonzalo Cabal @ Clinica El Rosario Medellin
Prof. Bruce Faddegon @ University of California, San Francisco
Liyong Lin @ Emory Winship Cancer Institute

We are constantly looking for motivated individuals coming from a physics, math, and/or computer science background with a genuine interest in medical physics in radiation oncology. If you are interested to join our research group for your Bachelor, Master, and PhD thesis or for a postdoc position, do not hesitate and get in touch. In particular, we a currently looking for a fixed-term Research Software Enginner to work on our open-source toolkit matRad.

People

Dr. Niklas Wahl (Group leader - CV)

Dr. Amit Ben Antony Bennan (PostDoc)
Tobias Becher (PhD Student)
Remo Cristoforetti (PhD student)
Simona Facchiano (PhD student)
Jennifer Hardt (PhD student)
Noa Homolka (PhD student)
Tim Ortkamp (associated PhD student from KIT in the HIDSS4Health Program)
Goran Stanic (PhD student), also associated with K. Giske's Group
Lina Bucher (HiWi / BSc Student
Lisa Seckler (BSc Student)
Tobias Di Nunzio (Azubi)
Antonios Kontopoulos (HiWi)
Marios Dallas (Erasmus+ Intern)

Code

With our work we try to support open science. As such we make a lot of our programming work freely available via our group's github site. Most notably, we maintain the Matlab-based open-source dose calculation and optimization toolkit matRad for radiotherapy research and education.

Projects

Check out our independent and third party funded projects:

Publications

Hardt, J. J., Pryanichnikov, A. A., Homolka, N., DeJongh, E. A., DeJongh, D. F., Cristoforetti, R., Jaekel, O., Seco, J., & Wahl, N. (2024). The potential of mixed carbon-helium beams for online treatment verification: A simulation and treatment planning study. Physics in Medicine & Biology, 69(12), 125028.
Faddegon, B., Descovich, M., Chen, K., Ramos-Méndez, J., Roach, M., III, Wahl, N., Taylor, P., Griffin, K., & Lee, C. (2024). A digital male pelvis phantom series showing anatomical variations over the course of fractionated radiotherapy treatment. Medical Physics, 51(4), 3034–3044.
Gesualdi, F., & Wahl, N. (2024). Cumulative Histograms under Uncertainty: An Application to Dose–Volume Histograms in Radiotherapy Treatment Planning. Stats, 7(1), Article 1.
Han, Y., Geng, C., Altieri, S., Bortolussi, S., Liu, Y., Wahl, N., & Tang, X. (2024). Combined BNCT-CIRT treatment planning for glioblastoma using the effect-based optimization. Physics in Medicine & Biology, 69(1), 015024.
Barkmann, F., Censor, Y., & Wahl, N. (2023). Superiorization of projection algorithms for linearly constrained inverse radiotherapy treatment planning. Frontiers in Oncology, 13.
Faddegon, B. A., Blakely, E. A., Burigo, L. N., Censor, Y., Dokic, I., D-Kondo, J. N., Ortiz, R., Ramos-Mendez, J., Rucinski, A., Schubert, K. E., Wahl, N., & Schulte, R. W. (2023). Ionization detail parameters and cluster dose: A mathematical model for selection of nanodosimetric quantities for use in treatment planning in charged particle radiotherapy. Physics in Medicine & Biology, 68(17), 175013.
Liu, R., Charyyev, S., Wahl, N., Liu, W., Kang, M., Zhou, J., Yang, X., Baltazar, F., Palkowitsch, M., Higgins, K., Dynan, W., Bradley, J., & Lin, L. (2023). An Integrated Physical Optimization framework for proton SBRT FLASH treatment planning allows dose, dose rate, and LET optimization using patient-specific ridge filters. International Journal of Radiation Oncology, Biology, Physics, 116(4), P949-959.
Stammer, P., Burigo, L., Jäkel, O., Frank, P., & Wahl, N. (2023). Multivariate error modeling and uncertainty quantification using importance (re-)weighting for Monte Carlo simulations in particle transport. Journal of Computational Physics, 473, 111725.
Stammer, P., Burigo, L., Jäkel, O., Frank, M., & Wahl, N. (2021). Efficient uncertainty quantification for Monte Carlo dose calculations using importance (re-)weighting. Physics in Medicine & Biology, 66(20), 205003.
Bennan, A. B. A., Unkelbach, J., Wahl, N., Salome, P., & Bangert, M. (2021). Joint optimization of photon – carbon ion treatments for Glioblastoma. International Journal of Radiation Oncology*Biology*Physics, 111(2), 559–572.
Neishabouri, A., Wahl, N., Mairani, A., Köthe, U., & Bangert, M. (2021). Long short‐term memory networks for proton dose calculation in highly heterogeneous tissues. Medical Physics, 48(4), 1893–1908.
Wahl, N., Hennig, P., Wieser, H.‐P. and Bangert, M. (2020), Analytical probabilistic modeling of dose‐volume histograms. Medical Physics 47(10), 5260.
Wieser, H. P., Karger, C. P., Wahl, N., & Bangert, M (2020). Impact of Gaussian uncertainty assumptions on probabilistic optimization in particle therapy. Physics in Medicine & Biology 65(14), 145007.
Astaburuaga R., Gabryś H. S., Sánchez-Nieto B., Floca R. O., Klüter S., Schubert K., Hauswald H. and Bangert M. (2019). Incorporation of Dosimetric Gradients and Parotid Gland Migration Into Xerostomia Prediction. Frontiers in Oncology, 8, 697.
Gabryś, H. S., Buettner, F., Sterzing, F., Hauswald, H., & Bangert, M. (2018). Design and Selection of Machine Learning Methods Using Radiomics and Dosiomics for Normal Tissue Complication Probability Modeling of Xerostomia. Frontiers in Oncology, 8, 35.
Wahl, N., Hennig, P., Wieser, H. P., & Bangert, M. (2018). Analytical incorporation of fractionation effects in probabilistic treatment planning for intensity‐modulated proton therapy. Medical Physics, 45(4), 1317-1328.
Wieser, H. P., Hennig, P., Wahl, N., & Bangert, M. (2017). Analytical probabilistic modeling of RBE-weighted dose for ion therapy. Physics in Medicine & Biology.
Mescher, H., Ulrich, S., & Bangert, M. (2017). Coverage-based constraints for IMRT optimization. Physics in Medicine & Biology, 62(18), N460-N473.
Ulrich, S., Wieser, H. P., Cao, W., Mohan, R., & Bangert, M. (2017). Impact of respiratory motion on variable relative biological effectiveness in 4D-dose distributions of proton therapy. Acta Oncologica, 1-8.
Wahl, N., Hennig, P., Wieser, H. P., & Bangert, M. (2017). Efficiency of analytical and sampling-based uncertainty propagation in intensity-modulated proton therapy. Physics in Medicine & Biology, 62(14), 5790.
Gabryś, H. S., Buettner, F., Sterzing, F., Hauswald, H., & Bangert, M. (2017). Parotid gland mean dose as a xerostomia predictor in low-dose domains. Acta Oncologica, 1-7.
Wieser, H. P., Cisternas, E., Wahl, N., Ulrich, S., Stadler, A., Mescher, H., ... & Mairani, A. (2017). Development of the open‐source dose calculation and optimization toolkit matRad. Medical Physics, 44(6), 2556.
Steitz, J., Naumann, P., Ulrich, S., Haefner, M. F., Sterzing, F., Oelfke, U., & Bangert, M. (2016). Worst case optimization for interfractional motion mitigation in carbon ion therapy of pancreatic cancer. Radiation Oncology, 11(1), 134.
Bangert, M., Hennig, P., & Oelfke, U. (2013). Analytical probabilistic modeling for radiation therapy treatment planning. Physics in Medicine & Biology, 58(16), 5401.
Bangert, M., Ziegenhein, P., & Oelfke, U. (2013). Comparison of beam angle selection strategies for intracranial IMRT. Medical Physics, 40(1).

The list includes publications from previous group leaders as well (Dr. Mark Bangert up until 2018).