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Human Rules - AI Brains (Research Group E0401)

While flat AI in principle has mastered reliable segmentation of anatomical structures visible in medical image scans, how to guarantee its individual prediction to comform with rule-based and harmonized expert-guidelines for traget volume delineations typically showing no visible contrast at all?

Project Name: Human Rules - AI Brains: Towards Expert-Guideline Conformance for Machine-Learning-based Segmentations of Clinical Target Volumes

Project Duration: 2020 – 2024 (doctoral project)

Funded by: HIDSS4Health – Kristina Giske, Oliver Jäkel, Martin Frank (KIT)  => Projects 2020 => Surgery & Intervention 4.0

Patient-tailored contours of target volumes are fundamental for radiation treatment planning and thus, the outcome of the cancer treatment. Delineation of clinical target volumes on planning CT scans is challenging for human experts, is extremely time consuming, and shows large variation between observers. State-of-the-art machine learning algorithms reach high accuracy on the automatic segmentation of anatomical structures which is yet not transferable to target volumes without additional constraints. The translation of the expert guidelines into the machine learning realm can advance automated target volume delineation to facilitate its guideline conformance and its clinical use. In this HIDSS4Health-funded doctoral project Alexandra Walter tackles the implications of supervised learning on data prone to inter-observer variabilities and patient-individual differences utilizing mathematical rules given by human experts. for more details. 

High-, moderate- and low-LET ion beams (Research Group E0402)

Project Name: High-, moderate- and low-LET ion beams in the treatment of radioresistant tumors: Impact of beam quality, tumor grading, and hypoxic status on radiation response.

Project Duration: 04/2020 - 04/2024 (2nd funding period)

Funded by: Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) -- Project number 319589509

Besides allowing for highly conformal irradiations, ion beams also exhibit an increased radiobiological effectiveness (RBE), which may be suited to improve the effectiveness in the treatment of hypoxic tumors. This project investigates the RBE of experimental prostate tumors in the rat under normoxic (oxygen breathing) and hypoxic (clamping of tumor-supplying artery) conditions after irradiation with photons, protons, helium, carbon and oxygen ions and quantifies the oxygen enhancement ratio (OER). These investigations are accompanied by detailed histological characterization of the radiation response. for more details. 

matRad (Research Group E0404)

Graphical User Interface of matRad featuring a proton prostate plan
© matRad

Project Name: matRad – an open-source dose calculation and treatment planning toolkit

Funding Period: 2022 – 2025

Funding Information: matRad development is currently funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) -- Project No. 443188743: "Sustainable development of the open source radiotherapy dose calculation and optimization toolkit matRad"

matRad is an open source software for radiation treatment planning of intensity-modulated photon, proton, and carbon ion therapy. matRad is developed for educational and research purposes and entirely written in MATLAB. matRad is published on GitHub ( and is used I numerous in-house, collaborative, and independent international research projects.

matRad implements established dose calculation algorithms for photons, protons and carbon ions as well as non-linear constrained biological treatment plan optimization. It includes open patient and machine data and features a graphical user interface and a powerful scripting API. During the funding period, matRad will be extended to facilitate interfacing of open Monte Carlo dose calculation techniques, inclusion of helium and advanced biological models, and working with matRad from Python. Further, development will be professionalized to follow continuous integration standards and automated tests & builds. for more details.

InViMo (Research Group E0406)


Project Name: In-vivo monitoring of carbon ion radiotherapy delivery (InViMo)

Project Duration:  2019 - 2023

Funded by: National Center for Tumor Diseases (NCT), Funding Program "Proof-of-Concept Clinical Trials"

During the radiation treatments of patients by carbon ions, a wide spectra of secondary radiation is leaving the patient. We developed a method to track these single secondary ions. By analysing their paths we draw conclusions about possible internal changes in the patient's tissue along the beam path (e.g. filling of the nose cavity), which might be critical for the local controll of the dissease. Since secondary radiation is escaping the treated patient as a by-product of the treatiment, this kind of imaging does not require any additional radiation dose to the patient. Following year-long research on patient models, we are about to start a clinical study at the Heidelberg Ion Beam Therapy Center. for more details. 

Secondary neutrons in particle therapy (Research Group E0408)

Secondary neutrons fluence generated from a proton SOBP, along with the most probable energy at the high-energy region in the inset. (J. Vedelago et al 2022 Phys. Med. Biol. 67 015008)

Project Name: Reducing secondary cancer risk by measuring neutron exposure in light ion beam radiotherapy

Project Duration: 2023 - 2026

Funded by: Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), funding number 495217943

With particular relevance for paediatric patients and radiotherapy during pregnancy, the effects of secondary neutrons in proton and light ion beam therapy need to be further investigated. It is, therefore, necessary to improve the current neutron detection techniques, particularly with a focus on the high-energy neutrons generated during particle therapy. For this, this project is currently implementing Fluorescent Nuclear Track Detectors (FNTDs) as a technique to improve secondary neutron dose quantification. Even considering previous reports where these secondary neutron doses are rather low, improving their experimental quantification will help to better estimate the potential long-term risk. As a long-term goal, including this information in the treatment planning systems would make it possible to select improved treatment for the patients.

PUMA Trial (Research Group E0409)


Project Name: Online adaptive radiotherapy for locally advanced lung cancer: assessing the patient benefit in a multi-centric comparison of CBCT- and MRI-guidance approaches

Project Duration: 03/2023 - 02/2028

Funded by: German Cancer Aid, funding number 70114708 => 8. Ausschreibungsrunde (2021)

Within the Priority Program Translational Oncology of the German Cancer Aid, we were successful to obtain funds for a collaborative research project and clinical study for radiotherapy in lung cancer patients. For our project application entitled Online adaptive radiotherapy for locally advanced lung cancer: assessing the patient benefit in a multi-centric comparison of CBCT- and MRI-guidance approaches, we were able to obtain a 1.5M€ grant to perform a clinical trial for MR-guided radiotherapy, which has been initiated at the three participating MR-linac centers at the University Hospitals in Heidelberg, Tübingen and the Ludwigs-Maximilians-University (LMU) in Munich and which will soon be started at the new ETHOS® system at DKFZ.

For more information, please click here.

Personalized Radiotherapy (Research Group E0409)

AI-Driven Integration of Multi-Omics Data workflow for Personalized Lung Cancer RT. RT: Radiotherapy, FU: Follow-up Timepoint, RNN: Recurrent Neural Network, MLP: Multilayer Perceptron

Project Name: AI-Based Risk Assessment for Radiation-Induced Lung Injury in Lung Cancer SBRT

Project Duration: 2022 - 2024

Funded by: Wilhelm Sander-Stiftung, funding number 3010001119

In the multifaceted field of lung cancer research, distinct biomarkers have been discovered through separate omics analyses, encompassing clinical phenomics, radiomics, dosiomics, and biomolecular omics. These biomarkers provide crucial insights, captured both longitudinally over time and at specific instances. Importantly, the diverse datasets derived from these omics analyses are routinely collected and available when a patient undergoes radiotherapy treatment. Our project seeks to harness this information by developing an AI-based workflow that will integrate these different layers of data. The objective is to accurately predict the risk of radiation-induced lung injury and distinguish it from cancer recurrence. This critical differentiation aids in selecting the optimal clinical therapeutic strategies to manage post-radiotherapy complications, ultimately guiding clinicians toward a more personalized, data-driven approach to lung cancer treatment. for more information.

Further projects and collaboration

Project: "Center of Excellence in Investigation and Teaching",
Prof. Dr. Oliver Jäkel (phase 1: 2009 - 2014, phase 2: 2014 - 2019, phase 3: 2019 - 2024, German Academic Exchange Service (DAAD))

HiDA, Helmholtz Information & Data Science Academy (
Groups involved:

AI Health Innovation Cluster (
Groups involved:

Further research projects can be found on the websites of each research group of our division.

Former Research Projects

Project: "Quantification of the biological effectiveness of proton, helium and oxygen ions in the spinal cord to optimize patient treatments." (2nd funding period)

Prof. Dr. Christian Karger (funded from 02/2018 - 10/2022 by German Cancer Aid/Deutsche Krebshilfe)

Project: "High-, moderate- and low-LET ion beams in the treatment of radioresistant tumors: Impact of beam quality, tumor grading, and hypoxic status on radiation response." (2nd funding period)
Prof. Dr. Christian Karger (funded from 04/2020 - 03/2023 by German Research Foundation/Deutsche Forschungsgemeinschaft (DFG))

Project: "Traceable dosimetry for small fields in MR-guided radiotherapy (MRgRT-DOS)"
Prof. Dr. Christian Karger (funded from 05/2020 - 04/2023 by European Metrology Programme for Innovation and Research (EMPIR)

Project: "Adaptive Radiotherapie mit MR-gesteuerten IonenStrahlen" (ARTEMIS), download overview as poster here
Prof. Dr. Oliver Jäkel (funded from 08/2019 - 07/2022 by the Federal Ministry of Education and Research (BMBF))

Project: "Chilean German Consortium for Medical Physics in Radiation Oncology" (CGCoMPRO),
Prof. Dr. Oliver Jäkel (2017 - 12/2022, Federal Ministry of Education and Research (FMER))

Project: "High-LET ion beams in the treatment of radioresistant tumors: Impact of beam quality, tumor grading, hypoxic status and tumor volume on radiation response"
Prof. Dr. Christian Karger (funded from 01/2017 - 03/2020 by: German Research
Foundation/Deutsche Forschungsgemeinschaft (DFG)

Project: "Quantifizierung der biologischen Wirkung von Protonen, Helium‐ und Sauerstoffionen im Rückenmark für die Optimierung der Patientenbehandlung"
Prof. Dr. Christian Karger (funded from 12/2014 - 11/2017 (three years) by: German Cancer Aid/Deutsche Krebshilfe)

Project: "Metrology for MR guided Radiotherapy",
Prof. Dr. Christian Karger (2016 - 2019, EMPIR)

Project: SFB "Cognition-Guided Surgery",
Involved groups: E0401, E0403, E0404 (German Research Foundation (DFG))

  • Project C01: Adaptive Photon Therapy in the Treatment of Lung and Liver Tumours
  • Project C02: Biological and Time Adaptive Therapy of Pancreatic Carcinoma

Project: "MR guided Proton Therapy"
Prof. Dr. Oliver Jäkel (2017 - 2018, German Academic Exchange Service (DAAD))

Project: "SPARTA" (Softwareplattform für die Adaptive Multimodale Radio- und Partikeltherapie mit Autarker Erweiterbarkeit)
Involved groups: E0401, E0402, E0403, E076, SIDT (Federal Ministry of Education and Research (FMER))

Project: "Analytical probabilistic modeling for radiation therapy planning"
Involved groups: E0404 (German Research Foundation (DFG))

Project: "Low-intensity Therapeutical Ultrasound (LiFu)"

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