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Evaluation of inverse treatment planning for gamma knife radiosurgery using fMRI brain activation maps as organs at risk
Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine.ORCID iD: 0000-0002-8857-5698
Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Computer and Information Science, The Division of Statistics and Machine Learning.ORCID iD: 0000-0001-7061-7995
2023 (English)In: Medical physics (Lancaster), ISSN 0094-2405, Vol. 50, no 9, p. 5297-5311Article in journal (Refereed) Published
Abstract [en]

Background: Stereotactic radiosurgery (SRS) can be an effective primary or adjuvant treatment option for intracranial tumors. However, it carries risks of various radiation toxicities, which can lead to functional deficits for the patients. Current inverse planning algorithms for SRS provide an efficient way for sparing organs at risk (OARs) by setting maximum radiation dose constraints in the treatment planning process.Purpose: We propose using activation maps from functional MRI (fMRI) to map the eloquent regions of the brain and define functional OARs (fOARs) for Gamma Knife SRS treatment planning.Methods: We implemented a pipeline for analyzing patient fMRI data, generating fOARs from the resulting activation maps, and loading them onto the GammaPlan treatment planning software. We used the Lightning inverse planner to generate multiple treatment plans from open MRI data of five subjects, and evaluated the effects of incorporating the proposed fOARs.Results: The Lightning optimizer designs treatment plans with high conformity to the specified parameters. Setting maximum dose constraints on fOARs successfully limits the radiation dose incident on them, but can have a negative impact on treatment plan quality metrics. By masking out fOAR voxels surrounding the tumor target it is possible to achieve high quality treatment plans while controlling the radiation dose on fOARs.Conclusions: The proposed method can effectively reduce the radiation dose incident on the eloquent brain areas during Gamma Knife SRS of brain tumors.

Place, publisher, year, edition, pages
WILEY , 2023. Vol. 50, no 9, p. 5297-5311
Keywords [en]
fMRI, radiotherapy, radiosurgery, gamma knife, brain tumor
National Category
Radiology, Nuclear Medicine and Medical Imaging Cancer and Oncology
Identifiers
URN: urn:nbn:se:liu:diva-196436DOI: 10.1002/mp.16660ISI: 001041239600001PubMedID: 37531209OAI: oai:DiVA.org:liu-196436DiVA, id: diva2:1785636
Funder
Vinnova, 2018‐02230Vinnova, 2021‐01954
Note

Funding: Centrum foer Industriell Informationsteknologi, Linkoepings Universitet; Vinnova [2018-02230, 2021-01954]

Available from: 2023-08-03 Created: 2023-08-03 Last updated: 2024-05-05

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Abramian, DavidBlystad, IdaEklund, Anders

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Division of Biomedical EngineeringFaculty of Science & EngineeringCenter for Medical Image Science and Visualization (CMIV)Faculty of Medicine and Health SciencesDepartment of Radiology in LinköpingDivision of Diagnostics and Specialist MedicineThe Division of Statistics and Machine Learning
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Medical physics (Lancaster)
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