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Kraus KM, Oreshko M, Schnabel JA, Bernhardt D, Combs SE, Peeken JC. Dosiomics and radiomics-based prediction of pneumonitis after radiotherapy and immune checkpoint inhibition: The relevance of fractionation. Lung Cancer 2024; 189:107507. [PMID: 38394745 DOI: 10.1016/j.lungcan.2024.107507] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 12/08/2023] [Accepted: 02/14/2024] [Indexed: 02/25/2024]
Abstract
OBJECTIVES Post-therapy pneumonitis (PTP) is a relevant side effect of thoracic radiotherapy and immunotherapy with checkpoint inhibitors (ICI). The influence of the combination of both, including dose fractionation schemes on PTP development is still unclear. This study aims to improve the PTP risk estimation after radio(chemo)therapy (R(C)T) for lung cancer with and without ICI by investigation of the impact of dose fractionation on machine learning (ML)-based prediction. MATERIALS AND METHODS Data from 100 patients who received fractionated R(C)T were collected. 39 patients received additional ICI therapy. Computed Tomography (CT), RT segmentation and dose data were extracted and physical doses were converted to 2-Gy equivalent doses (EQD2) to account for different fractionation schemes. Features were reduced using Pearson intercorrelation and the Boruta algorithm within 1000-fold bootstrapping. Six single (clinics, Dose Volume Histogram (DVH), ICI, chemotherapy, radiomics, dosiomics) and four combined models (radiomics + dosiomics, radiomics + DVH + Clinics, dosiomics + DVH + Clinics, radiomics + dosiomics + DVH + Clinics) were trained to predict PTP. Dose-based models were tested using physical dose and EQD2. Four ML-algorithms (random forest (rf), logistic elastic net regression, support vector machine, logitBoost) were trained and tested using 5-fold nested cross validation and Synthetic Minority Oversampling Technique (SMOTE) for resampling in R. Prediction was evaluated using the area under the receiver operating characteristic curve (AUC) on the test sets of the outer folds. RESULTS The combined model of all features using EQD2 surpassed all other models (AUC = 0.77, Confidence Interval CI 0.76-0.78). DVH, clinical data and ICI therapy had minor impact on PTP prediction with AUC values between 0.42 and 0.57. All EQD2-based models outperformed models based on physical dose. CONCLUSIONS Radiomics + dosiomics based ML models combined with clinical and dosimetric models were found to be suited best for PTP prediction after R(C)T and could improve pre-treatment decision making. Different RT dose fractionation schemes should be considered for dose-based ML approaches.
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Affiliation(s)
- Kim Melanie Kraus
- Department of Radiation Oncology, School of Medicine and Klinikum rechts der Isar, Technical University of Munich (TUM), 81675 Munich, Germany; Institute of Radiation Medicine (IRM), Helmholtz Zentrum München (HMGU) GmbH, German Research Center for Environmental Health, 85764 Neuherberg, Germany; Partner Site Munich, German Consortium for Translational Cancer Research (DKTK), 80336 Munich, Germany.
| | - Maksym Oreshko
- Department of Radiation Oncology, School of Medicine and Klinikum rechts der Isar, Technical University of Munich (TUM), 81675 Munich, Germany; Medical Faculty, University Hospital, LMU Munich, 80539 Munich, Germany
| | - Julia Anne Schnabel
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom; School of Computation, Information and Technology, Technical University of Munich, Germany; Institute of Machine Learning in Biomedical Imaging, Helmholtz Zentrum München (HMGU) GmbH, German Research Center for Environmental Health, 85764 Neuherberg, Germany
| | - Denise Bernhardt
- Department of Radiation Oncology, School of Medicine and Klinikum rechts der Isar, Technical University of Munich (TUM), 81675 Munich, Germany; Partner Site Munich, German Consortium for Translational Cancer Research (DKTK), 80336 Munich, Germany
| | - Stephanie Elisabeth Combs
- Department of Radiation Oncology, School of Medicine and Klinikum rechts der Isar, Technical University of Munich (TUM), 81675 Munich, Germany; Institute of Radiation Medicine (IRM), Helmholtz Zentrum München (HMGU) GmbH, German Research Center for Environmental Health, 85764 Neuherberg, Germany; Partner Site Munich, German Consortium for Translational Cancer Research (DKTK), 80336 Munich, Germany
| | - Jan Caspar Peeken
- Department of Radiation Oncology, School of Medicine and Klinikum rechts der Isar, Technical University of Munich (TUM), 81675 Munich, Germany; Institute of Radiation Medicine (IRM), Helmholtz Zentrum München (HMGU) GmbH, German Research Center for Environmental Health, 85764 Neuherberg, Germany; Partner Site Munich, German Consortium for Translational Cancer Research (DKTK), 80336 Munich, Germany
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Kraus KM, Oreshko M, Bernhardt D, Combs SE, Peeken JC. The Value of Equivalent Dose Calculation for Dosiomics and Radiomics-Based Prediction of Pneumonitis after Thoracic Radiotherapy with Immune Checkpoint Inhibition. Int J Radiat Oncol Biol Phys 2023; 117:e473. [PMID: 37785503 DOI: 10.1016/j.ijrobp.2023.06.1683] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Post-therapy pneumonitis (PTP) is a relevant side effect after thoracic radiotherapy (RT) and immunotherapy with checkpoint inhibitors (ICI). The impact of the combination of both is unclear. We aim to improve risk estimation by prediction of PTP with and without ICI therapy. To analyze the influence of different fractionation schemes, the value of voxel-wise 2 Gy equivalent dose (EQD2) is investigated. MATERIALS/METHODS Clinical data from 100 patients who received fractionated RT (single dose ≤ 3Gy) RT were collected. 36 patients received additional ICI therapy. PTP of all grades were monitored. Planning Computed tomographies (CTs), segmentations and 3D dose data were extracted and converted to EQD2. Dosiomics and radiomics features were extracted using 1000-fold bootstrapping using Pearson intercorrelation and the Boruta algorithm for 5 single and 4 combined predictive models. Machine learning algorithms (random forest (rf), logistic elastic net regression, support vector machine, logitBoost) were trained and tested using a 5-fold nested cross validation approach and Synthetic Minority Oversampling Technique resampling in R. Analysis was performed using the area under the receiver operating characteristic curve (AUC) on the test sets of the outer folds. RESULTS All investigated models predicted PTP better than random (AUC>.5) (Table 1). Dosiomics+Radiomics models based on EQD2 using rf classifier resulted in the highest predictive performance (AUC = .83 (95% Confidence Interval .83-.84)) and performed worse on physical dose data (AUC = .72 (.71-.73)). For single models, radiomics and dosiomics achieved the best prediction (AUC = .73 (.72-.74), AUC = .8 (.79-.81)) for physical dose and EQD2, respectively. Clinical factors and ICI therapy (AUC = .6 (.59-.62)) had minor impact on PTP prediction. Table 1: AUC and 95% confidence intervals (CI) for all investigated Machine Learning models for EQD2 and physical doses (D). CONCLUSION Dosiomics+Radiomics machine learning models have strong capability of PTP prediction and could contribute to pre-treatment decision making. Fractionation schemes should be considered for dose-based prediction strategies. Additional ICI therapy has limited impact on PTP prediction.
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Affiliation(s)
- K M Kraus
- Department of Radiation Oncology, School of Medicine and Klinikum rechts der Isar, Technical University of Munich (TUM), Munich, Germany; Institute of Radiation Medicine (IRM), Helmholtz Zentrum München (HMGU) GmbH German Research Center for Environmental Health, Neuherberg, Germany
| | - M Oreshko
- Department of Radiation Oncology, School of Medicine and Klinikum rechts der Isar, Technical University of Munich (TUM), Munich, Germany; Medical Faculty, University Hospital, LMU Munich, Munich, Germany
| | - D Bernhardt
- Department of Radiation Oncology, School of Medicine and Klinikum rechts der Isar, Technical University of Munich (TUM), Munich, Germany; German Cancer Consortium (DKTK), Partner Site Munich, Germany, Munich, Germany
| | - S E Combs
- Institute of Radiation Medicine (IRM), Helmholtz Zentrum München (HMGU) GmbH German Research Center for Environmental Health, Neuherberg, Germany; Department of Radiation Oncology, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany
| | - J C Peeken
- Department of Radiation Oncology, School of Medicine and Klinikum rechts der Isar, Technical University of Munich (TUM), Munich, Germany; Institute of Radiation Medicine (IRM), Helmholtz Zentrum München (HMGU) GmbH German Research Center for Environmental Health, Neuherberg, Germany
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Petrich C, Dimroth A, Kraus KM, Winter J, Matejcek C, Butzek M, Natour G, Ravichandran M, Zimmermann M, Aulenbacher K, Galek M, Wilkens J, Combs SE, Bartzsch S. Towards Clinical Translation of Microbeam Radiation Therapy (MRT) with a Compact Source. Int J Radiat Oncol Biol Phys 2023; 117:S38-S39. [PMID: 37784488 DOI: 10.1016/j.ijrobp.2023.06.308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) MRT is an innovative concept of spatially fractionated radiation therapy that has demonstrated substantially improved normal tissue tolerance while achieving local tumor control in a wealth of preclinical studies. In MRT a collimator shapes a few micrometers wide planar x-ray beams with a spacing of a few 100 µm. MRT has the potential to improve cancer treatment substantially. However, until now, only a few large 3rd generation synchrotrons provide beam parameters that would allow patient treatments and therefore, MRT has not yet become clinically available. For a clinical translation, compact x-ray sources are required, that produce high dose rate orthovoltage x-rays from a micrometer sized emitter. MATERIALS/METHODS We developed and built a first prototype of a line focus x-ray tube (LFxT) dedicated to preclinical MRT research. By exploiting the heat capacity limit, the LFxT can deliver dose rates above 100 Gy/s from a just 50 µm-wide focal spot without destroying the rapidly (>200 Hz) rotating x-ray target. A bespoke collimator splits the homogeneous x-ray field into 50 µm wide high-dose peaks separated by 350 µm wide low-dose troughs (valleys). While the prototype in our lab is restricted to a power of 90 kW and 10 Gy/s at 300 kVp, we have started the development of the first clinically usable LFxT-2 at 1.5 MW power and >100 Gy/s at 600 kVp beam quality. We investigated the clinical applicability of the LFxT-2 by performing retrospective treatment planning studies. In particular, we were examining, whether 600 kVp photons would suffice to meet clinical dose constraints in MRT treatments treatment scenarios for first clinical use of MRT. We coupled the open source platform 3D Slicer with an in-house developed dose calculation algorithm for MRT treatment planning. For comparability of spatially fractionated MRT doses with conventional broad beam treatments, the MRT dose was converted to equivalent uniform dose (EUD) and equivalent doses in 2-Gy-fractions (EQD2). The 3D Slicer RT toolkit enabled the dosimetric analysis based on dose volume histograms (DVHs). RESULTS We installed a preclinical prototype of the LFxT that is currently put into operation and commissioned. Simulations show the feasibility of the next generation LFxT-2 with more than 100 Gy/s peak dose rate. Planned MRT dose distributions with the LFxT-2 meet established radiotherapy dose constraints in many of the investigated clinical cases. However, treatment planning procedures are not yet optimal and require improvement. CONCLUSION In a next step, we will build the LFxT-2 and aim for first clinical MRT trials at this source. In order to further improve calculated MRT dose distributions, we will implement inverse treatment planning techniques.
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Affiliation(s)
- C Petrich
- Department of Radiation Oncology, School of Medicine and Klinikum rechts der Isar, Technical University of Munich (TUM), Munich, Germany; Neutron Source Heinz Maier-Leibnitz (FRM II), Munich, Germany
| | - A Dimroth
- Research Centre Juelich, Juelich, Germany
| | - K M Kraus
- Department of Radiation Oncology, School of Medicine and Klinikum rechts der Isar, Technical University of Munich (TUM), Munich, Germany; Institute of Radiation Medicine (IRM), Helmholtz Zentrum München (HMGU) GmbH German Research Center for Environmental Health, Neuherberg, Germany
| | - J Winter
- Department of Radiation Oncology, School of Medicine and Klinikum rechts der Isar, Technical University of Munich (TUM), Munich, Germany; Institute for Radiation Medicine, Helmholtz Zentrum München, Neuherberg, Germany
| | - C Matejcek
- Helmholtz Institute Mainz, Mainz, Germany
| | - M Butzek
- Research Centre Juelich, Juelich, Germany
| | - G Natour
- Research Centre Juelich, Juelich, Germany
| | - M Ravichandran
- Department of Radiation Oncology, School of Medicine and Klinikum rechts der Isar, Technical University of Munich (TUM), Munich, Germany; Technical University of Munich, Munich, Germany
| | | | | | - M Galek
- University of Applied Sciences Munich, Munich, Germany
| | - J Wilkens
- Department of Radiation Oncology, School of Medicine and Klinikum rechts der Isar, Technical University of Munich (TUM), Munich, Germany
| | - S E Combs
- Institute for Radiation Medicine, Helmholtz Zentrum München, Neuherberg, Germany; Department of Radiation Oncology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - S Bartzsch
- Department of Radiation Oncology, School of Medicine and Klinikum rechts der Isar, Technical University of Munich (TUM), Munich, Germany; Neutron Source Heinz Maier-Leibnitz (FRM II), Munich, Germany
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Kraus KM, Oreshko M, Bernhardt D, Combs SE, Peeken JC. Dosiomics and radiomics to predict pneumonitis after thoracic stereotactic body radiotherapy and immune checkpoint inhibition. Front Oncol 2023; 13:1124592. [PMID: 37007119 PMCID: PMC10050584 DOI: 10.3389/fonc.2023.1124592] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 03/01/2023] [Indexed: 03/17/2023] Open
Abstract
IntroductionPneumonitis is a relevant side effect after radiotherapy (RT) and immunotherapy with checkpoint inhibitors (ICIs). Since the effect is radiation dose dependent, the risk increases for high fractional doses as applied for stereotactic body radiation therapy (SBRT) and might even be enhanced for the combination of SBRT with ICI therapy. Hence, patient individual pre-treatment prediction of post-treatment pneumonitis (PTP) might be able to support clinical decision making. Dosimetric factors, however, use limited information and, thus, cannot exploit the full potential of pneumonitis prediction.MethodsWe investigated dosiomics and radiomics model based approaches for PTP prediction after thoracic SBRT with and without ICI therapy. To overcome potential influences of different fractionation schemes, we converted physical doses to 2 Gy equivalent doses (EQD2) and compared both results. In total, four single feature models (dosiomics, radiomics, dosimetric, clinical factors) were tested and five combinations of those (dosimetric+clinical factors, dosiomics+radiomics, dosiomics+dosimetric+clinical factors, radiomics+dosimetric+clinical factors, radiomics+dosiomics+dosimetric+clinical factors). After feature extraction, a feature reduction was performed using pearson intercorrelation coefficient and the Boruta algorithm within 1000-fold bootstrapping runs. Four different machine learning models and the combination of those were trained and tested within 100 iterations of 5-fold nested cross validation.ResultsResults were analysed using the area under the receiver operating characteristic curve (AUC). We found the combination of dosiomics and radiomics features to outperform all other models with AUCradiomics+dosiomics, D = 0.79 (95% confidence interval 0.78-0.80) and AUCradiomics+dosiomics, EQD2 = 0.77 (0.76-0.78) for physical dose and EQD2, respectively. ICI therapy did not impact the prediction result (AUC ≤ 0.5). Clinical and dosimetric features for the total lung did not improve the prediction outcome.ConclusionOur results suggest that combined dosiomics and radiomics analysis can improve PTP prediction in patients treated with lung SBRT. We conclude that pre-treatment prediction could support clinical decision making on an individual patient basis with or without ICI therapy.
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Affiliation(s)
- Kim Melanie Kraus
- Department of Radiation Oncology, School of Medicine and Klinikum rechts der Isar, Technical University of Munich (TUM), Munich, Germany
- Institute of Radiation Medicine (IRM), Helmholtz Zentrum München (HMGU) GmbH German Research Center for Environmental Health, Neuherberg, Germany
- Partner Site Munich, German Consortium for Translational Cancer Research (DKTK), Munich, Germany
- *Correspondence: Kim Melanie Kraus,
| | - Maksym Oreshko
- Department of Radiation Oncology, School of Medicine and Klinikum rechts der Isar, Technical University of Munich (TUM), Munich, Germany
- Medical Faculty, University hospital, Ludwig-Maximilians-Universität (LMU) Munich, Munich, Germany
| | - Denise Bernhardt
- Department of Radiation Oncology, School of Medicine and Klinikum rechts der Isar, Technical University of Munich (TUM), Munich, Germany
- Partner Site Munich, German Consortium for Translational Cancer Research (DKTK), Munich, Germany
| | - Stephanie Elisabeth Combs
- Department of Radiation Oncology, School of Medicine and Klinikum rechts der Isar, Technical University of Munich (TUM), Munich, Germany
- Institute of Radiation Medicine (IRM), Helmholtz Zentrum München (HMGU) GmbH German Research Center for Environmental Health, Neuherberg, Germany
- Partner Site Munich, German Consortium for Translational Cancer Research (DKTK), Munich, Germany
| | - Jan Caspar Peeken
- Department of Radiation Oncology, School of Medicine and Klinikum rechts der Isar, Technical University of Munich (TUM), Munich, Germany
- Institute of Radiation Medicine (IRM), Helmholtz Zentrum München (HMGU) GmbH German Research Center for Environmental Health, Neuherberg, Germany
- Partner Site Munich, German Consortium for Translational Cancer Research (DKTK), Munich, Germany
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Kraus KM, Winter J, Zhang Y, Ahmed M, Combs SE, Wilkens JJ, Bartzsch S. Treatment Planning Study for Microbeam Radiotherapy Using Clinical Patient Data. Cancers (Basel) 2022; 14:cancers14030685. [PMID: 35158953 PMCID: PMC8833598 DOI: 10.3390/cancers14030685] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Revised: 01/25/2022] [Accepted: 01/27/2022] [Indexed: 11/16/2022] Open
Abstract
Microbeam radiotherapy (MRT) is a novel, still preclinical dose delivery technique. MRT has shown reduced normal tissue effects at equal tumor control rates compared to conventional radiotherapy. Treatment planning studies are required to permit clinical application. The aim of this study was to establish a dose comparison between MRT and conventional radiotherapy and to identify suitable clinical scenarios for future applications of MRT. We simulated MRT treatment scenarios for clinical patient data using an inhouse developed planning algorithm based on a hybrid Monte Carlo dose calculation and implemented the concept of equivalent uniform dose (EUD) for MRT dose evaluation. The investigated clinical scenarios comprised fractionated radiotherapy of a glioblastoma resection cavity, a lung stereotactic body radiotherapy (SBRT), palliative bone metastasis irradiation, brain metastasis radiosurgery and hypofractionated breast cancer radiotherapy. Clinically acceptable treatment plans were achieved for most analyzed parameters. Lung SBRT seemed the most challenging treatment scenario. Major limitations comprised treatment plan optimization and dose calculation considering the tissue microstructure. This study presents an important step of the development towards clinical MRT. For clinical treatment scenarios using a sophisticated dose comparison concept based on EUD and EQD2, we demonstrated the capability of MRT to achieve clinically acceptable dose distributions.
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Affiliation(s)
- Kim Melanie Kraus
- Department of Radiation Oncology, School of Medicine and Klinikum Rechts der Isar, Technical University of Munich (TUM), 81675 Munich, Germany; (J.W.); (Y.Z.); (M.A.); (S.E.C.); (J.J.W.); (S.B.)
- Institute of Radiation Medicine (IRM), Helmholtz Zentrum München GmbH, German Research Center for Environmental Health, 85764 Neuherberg, Germany
- Correspondence: ; Tel.: +49-89-4140-5373
| | - Johanna Winter
- Department of Radiation Oncology, School of Medicine and Klinikum Rechts der Isar, Technical University of Munich (TUM), 81675 Munich, Germany; (J.W.); (Y.Z.); (M.A.); (S.E.C.); (J.J.W.); (S.B.)
- Institute of Radiation Medicine (IRM), Helmholtz Zentrum München GmbH, German Research Center for Environmental Health, 85764 Neuherberg, Germany
- Physics Department, Technical University of Munich (TUM), 85748 Garching, Germany
| | - Yating Zhang
- Department of Radiation Oncology, School of Medicine and Klinikum Rechts der Isar, Technical University of Munich (TUM), 81675 Munich, Germany; (J.W.); (Y.Z.); (M.A.); (S.E.C.); (J.J.W.); (S.B.)
- Institute of Radiation Medicine (IRM), Helmholtz Zentrum München GmbH, German Research Center for Environmental Health, 85764 Neuherberg, Germany
| | - Mabroor Ahmed
- Department of Radiation Oncology, School of Medicine and Klinikum Rechts der Isar, Technical University of Munich (TUM), 81675 Munich, Germany; (J.W.); (Y.Z.); (M.A.); (S.E.C.); (J.J.W.); (S.B.)
- Institute of Radiation Medicine (IRM), Helmholtz Zentrum München GmbH, German Research Center for Environmental Health, 85764 Neuherberg, Germany
- Physics Department, Technical University of Munich (TUM), 85748 Garching, Germany
| | - Stephanie Elisabeth Combs
- Department of Radiation Oncology, School of Medicine and Klinikum Rechts der Isar, Technical University of Munich (TUM), 81675 Munich, Germany; (J.W.); (Y.Z.); (M.A.); (S.E.C.); (J.J.W.); (S.B.)
- Institute of Radiation Medicine (IRM), Helmholtz Zentrum München GmbH, German Research Center for Environmental Health, 85764 Neuherberg, Germany
- Partner Site Munich, Deutsches Konsortium für Translationale Krebsforschung (DKTK), 80336 Munich, Germany
| | - Jan Jakob Wilkens
- Department of Radiation Oncology, School of Medicine and Klinikum Rechts der Isar, Technical University of Munich (TUM), 81675 Munich, Germany; (J.W.); (Y.Z.); (M.A.); (S.E.C.); (J.J.W.); (S.B.)
- Physics Department, Technical University of Munich (TUM), 85748 Garching, Germany
| | - Stefan Bartzsch
- Department of Radiation Oncology, School of Medicine and Klinikum Rechts der Isar, Technical University of Munich (TUM), 81675 Munich, Germany; (J.W.); (Y.Z.); (M.A.); (S.E.C.); (J.J.W.); (S.B.)
- Institute of Radiation Medicine (IRM), Helmholtz Zentrum München GmbH, German Research Center for Environmental Health, 85764 Neuherberg, Germany
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Kraus KM, Oechsner M, Wilkens JJ, Kessel KA, Münch S, Combs SE. Patient individual phase gating for stereotactic radiation therapy of early stage non-small cell lung cancer (NSCLC). Sci Rep 2021; 11:5870. [PMID: 33712667 PMCID: PMC7955128 DOI: 10.1038/s41598-021-85031-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Accepted: 02/23/2021] [Indexed: 12/25/2022] Open
Abstract
Stereotactic body radiotherapy (SBRT) applies high doses and requires advanced techniques to spare surrounding tissue in the presence of organ motion. In this work patient individual phase gating is investigated. We studied peripheral and central primary lung tumors. The internal target volume (ITV) was defined including different numbers of phases picked from a 4D Computed tomography (CT) defining the gating window (gw). Planning target volume (PTV) reductions depending on the gw were analyzed. A treatment plan was calculated on a reference phase CT (rCT) and the dose for each breathing phase was calculated and accumulated on the rCT. We compared the dosimetric results with the dose calculated when all breathing phases were included for ITV definition. GWs including 1 to 10 breathing phases were analyzed. We found PTV reductions up to 38.4%. The mean reduction of the lung volume receiving 20 Gy due to gating was found to be 25.7% for peripheral tumors and 16.7% for central tumors. Gating considerably reduced esophageal doses. However, we found that simple reduction of the gw does not necessarily influence the dose in a clinically relevant range. Thus, we suggest a patient individual definition of the breathing phases included within the gw.
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Affiliation(s)
- K M Kraus
- School of Medicine and Klinikum Rechts Der Isar, Department of Radiation Oncology, Technichal University of Munich (TUM), Munich, Germany.
| | - M Oechsner
- School of Medicine and Klinikum Rechts Der Isar, Department of Radiation Oncology, Technichal University of Munich (TUM), Munich, Germany
| | - J J Wilkens
- School of Medicine and Klinikum Rechts Der Isar, Department of Radiation Oncology, Technichal University of Munich (TUM), Munich, Germany
| | - K A Kessel
- School of Medicine and Klinikum Rechts Der Isar, Department of Radiation Oncology, Technichal University of Munich (TUM), Munich, Germany.,Institute of Radiation Medicine (IRM), Department of Radiation Sciences (DRS), Helmholtz Zentrum München (HMGU), Neuherberg, Germany.,Deutsches Konsortium für Translationale Krebsforschung (DKTK), Partner Site Munich, Munich, Germany
| | - S Münch
- School of Medicine and Klinikum Rechts Der Isar, Department of Radiation Oncology, Technichal University of Munich (TUM), Munich, Germany
| | - S E Combs
- School of Medicine and Klinikum Rechts Der Isar, Department of Radiation Oncology, Technichal University of Munich (TUM), Munich, Germany.,Institute of Radiation Medicine (IRM), Department of Radiation Sciences (DRS), Helmholtz Zentrum München (HMGU), Neuherberg, Germany.,Deutsches Konsortium für Translationale Krebsforschung (DKTK), Partner Site Munich, Munich, Germany
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Kessel KA, Grosser RCE, Kraus KM, Hoffmann H, Oechsner M, Combs SE. Stereotactic body radiotherapy (SBRT) in patients with lung metastases - prognostic factors and long-term survival using patient self-reported outcome (PRO). BMC Cancer 2020; 20:442. [PMID: 32429940 PMCID: PMC7236290 DOI: 10.1186/s12885-020-6635-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2019] [Accepted: 02/14/2020] [Indexed: 12/11/2022] Open
Abstract
OBJECTIVES The present study aims to evaluate long-term side-effects and outcomes and confirm prognostic factors after stereotactic body radiotherapy (SBRT) of pulmonary lesions. This is the first work that combines the investigated data from patient charts and patient-reported outcome (PRO) up to 14 years after therapy. MATERIALS AND METHODS We analyzed 219 patients and 316 lung metastases treated between 2004 and 2019. The pulmonary lesions received a median dose and dose per fraction of 35 Gy (range: 14-60.5 Gy) and 8 Gy (range: 3-20 Gy) to the surrounding isodose. During the last 1.5 years of monitoring, we added PRO assessment to our follow-up routine. We sent an invitation to a web-based survey questionnaire to all living patients whose last visit was more than 6 months ago. RESULTS Median OS was 27.6 months. Univariate analysis showed a significant influence on OS for KPS ≥90%, small gross tumor volume (GTV) and planning target volume (PTV), the absence of external metastases, ≤3 pulmonary metastases, and controlled primary tumor. The number of pulmonary metastases and age influenced local control (LC) significantly. During follow-up, physicians reported severe side-effects ≥ grade 3 in only 2.9% within the first 6 months and in 2.5% after 1 year. Acute symptomatic pneumonitis grade 2 was observed in 9.7%, as grade 3 in 0.5%. During PRO assessment, 39 patients were contacted, 38 patients participated, 14 participated twice during follow-up. Patients reported 15 cases of severe side effects (grade ≥ 3) according to PROCTCAE classification. Severe dyspnea (n = 6) was reported mostly. CONCLUSION We could confirm excellent local control and low toxicity rates. PROs improve and complement follow-up care. They are an essential measure in addition to the physician-reported outcomes. Future research must be conducted regarding the correct interpretation of PRO data.
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Affiliation(s)
- Kerstin A Kessel
- Department of Radiation Oncology, Klinikum rechts der Isar, Technical University of Munich (TUM), Ismaninger Straße 22, 81675, Munich, Germany. .,Institute of Radiation Medicine (IRM), Helmholtz Zentrum München, Neuherberg, Germany. .,Deutsches Konsortium für Translationale Krebsforschung (DKTK), Partner Site Munich, Munich, Germany.
| | - Rebekka C E Grosser
- Department of Radiation Oncology, Klinikum rechts der Isar, Technical University of Munich (TUM), Ismaninger Straße 22, 81675, Munich, Germany
| | - Kim Melanie Kraus
- Department of Radiation Oncology, Klinikum rechts der Isar, Technical University of Munich (TUM), Ismaninger Straße 22, 81675, Munich, Germany
| | - Hans Hoffmann
- Division of Thoracic Surgery, Technical University of Munich (TUM), Munich, Germany
| | - Markus Oechsner
- Department of Radiation Oncology, Klinikum rechts der Isar, Technical University of Munich (TUM), Ismaninger Straße 22, 81675, Munich, Germany
| | - Stephanie E Combs
- Department of Radiation Oncology, Klinikum rechts der Isar, Technical University of Munich (TUM), Ismaninger Straße 22, 81675, Munich, Germany.,Institute of Radiation Medicine (IRM), Helmholtz Zentrum München, Neuherberg, Germany.,Deutsches Konsortium für Translationale Krebsforschung (DKTK), Partner Site Munich, Munich, Germany
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Kraus KM, Combs SE. Zweitmalignomrisiko nach Behandlung von lokal begrenzten Prostatakarzinomen mit Kohlenstoffionen möglicherweise niedriger als nach Photonenbestrahlung. Strahlenther Onkol 2019; 195:1033-1035. [DOI: 10.1007/s00066-019-01510-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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Kraus KM, Pfaffenberger A, Jäkel O, Debus J, Sterzing F. Evaluation of Dosimetric Robustness of Carbon Ion Boost Therapy for Anal Carcinoma. Int J Part Ther 2017; 3:382-391. [PMID: 31772987 DOI: 10.14338/ijpt-16-00028.1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2016] [Accepted: 01/13/2017] [Indexed: 12/15/2022] Open
Abstract
Purpose The radiation therapy treatment outcome of human papillomavirus-negative anal carcinoma may be improved by the biological effectiveness of carbon ions. However, abdominal tissue motion can compromise the precision of carbon ion therapy. This work aims to evaluate the dosimetric feasibility of carbon ion boost (CIB) therapy for anal carcinoma. Materials and Methods An algorithm to generate computed tomographies based on daily magnetic resonance imaging data and deformable image registration was developed. By means of this algorithm, fractional computed tomography data for 54 treatment fractions for 3 different patients with anal carcinoma were derived. The dose for a sequential CIB (CIBseq) treatment plan was recalculated on the fractional computed tomography data and accumulated over the number of fractions. The resulting dose distributions were compared to standard intensity-modulated radiation therapy treatment with an integrated photon boost. Results For the investigated patient cases, similar dosimetric results for CIBseq treatment and for intensity-modulated radiation therapy with an integrated photon boost were found. For CIBseq treatment, bladder-filling variation had the strongest influence on the dose distribution. However, the detrimental effects on the mean target dose remained below 1 Gy (RBE) as compared to photon therapy. Conclusion This study shows the dosimetric feasibility of CIB therapy for anal carcinoma for the first time and gives reason for clinical exploitation of the enhanced biological effect of carbon ions for patients with human papillomavirus-negative anal cancer.
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Affiliation(s)
- Kim Melanie Kraus
- Department of Radiation Oncology and Radiation Therapy, University Hospital Heidelberg, Heidelberg, Germany.,Department of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Asja Pfaffenberger
- Department of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Oliver Jäkel
- Department of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Heidelberg Ion-Beam Therapy Center, Heidelberg, Germany
| | - Jürgen Debus
- Department of Radiation Oncology and Radiation Therapy, University Hospital Heidelberg, Heidelberg, Germany.,Department of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Heidelberg Ion-Beam Therapy Center, Heidelberg, Germany
| | - Florian Sterzing
- Department of Radiation Oncology and Radiation Therapy, University Hospital Heidelberg, Heidelberg, Germany.,Department of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany
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Kraus KM, Jäkel O, Niebuhr NI, Pfaffenberger A. Generation of synthetic CT data using patient specific daily MR image data and image registration. Phys Med Biol 2017; 62:1358-1377. [DOI: 10.1088/1361-6560/aa5200] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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Abstract
A method for simulating spot-scanned delivery to a moving tumour was developed which uses patient-specific image and plan data. The magnitude of interplay effects was investigated for two patient cases under different fractionation and respiratory motion variation scenarios. The use of volumetric rescanning for motion mitigation was also investigated. For different beam arrangements, interplay effects lead to severely distorted dose distributions for a single fraction delivery. Baseline shift variations for single fraction delivery reduced the dose to the clinical target volume (CTV) by up to 14.1 Gy. Fractionated delivery significantly reduced interplay effects; however, local overdosage of 12.3% compared to the statically delivered dose remained for breathing period variations. Variations of the tumour baseline position and respiratory period were found to have the largest influence on target inhomogeneity; these effects were reduced with fractionation. Volumetric rescanning improved the dose homogeneity. For the CTV, underdosage was improved by up to 34% in the CTV and overdosage to the lung was reduced by 6%. Our results confirm that rescanning potentially increases the dose homogeneity; however, it might not sufficiently compensate motion-induced dose distortions. Other motion mitigation techniques may be required to additionally treat lung tumours with scanned proton beams.
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Affiliation(s)
- K M Kraus
- German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany.
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