Volume change of the prostate during moderately hypo-fractionated radiotherapy assessed by artificial intelligence
Background: Diagnostic quality MRI acquired daily for radiotherapy (RT) planning on an MR-linac allows longitudinal evaluation of the patients’ anatomy. This study investigated changes in prostate volume during MR-guided RT. The changes were assessed from manual delineations used clinically for dail...
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| Format: | Article |
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Elsevier
2025-04-01
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| Series: | Physics and Imaging in Radiation Oncology |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405631625000752 |
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| author | Rasmus L. Christiansen Bahar Celik Lars Dysager Christina J. Nyborg Steinbjørn Hansen Tine Schytte Søren N. Agergaard Anders S. Bertelsen Uffe Bernchou Christian R. Hansen Karina L. Gottlieb Nis Sarup Ebbe L. Lorenzen |
| author_facet | Rasmus L. Christiansen Bahar Celik Lars Dysager Christina J. Nyborg Steinbjørn Hansen Tine Schytte Søren N. Agergaard Anders S. Bertelsen Uffe Bernchou Christian R. Hansen Karina L. Gottlieb Nis Sarup Ebbe L. Lorenzen |
| author_sort | Rasmus L. Christiansen |
| collection | DOAJ |
| description | Background: Diagnostic quality MRI acquired daily for radiotherapy (RT) planning on an MR-linac allows longitudinal evaluation of the patients’ anatomy. This study investigated changes in prostate volume during MR-guided RT. The changes were assessed from manual delineations used clinically for daily online adaptation as well as automated segmentation by artificial intelligence (AI). The consistency and congruity of these two methods were evaluated. Methods: The prostate volumes were extracted from daily planning MRI scans of 45 patients receiving 60 Gy in 20 fractions. These volumes were manually edited during the online adaptive treatment planning workflow. The prostate was re-segmented retrospectively for each fraction by AI with an in-house developed nnU-net, trained on prostate cancer patients. The volume for each fraction was normalized to the volume at the patients’ 1st fraction to identify possible time trends. Results: Increased population mean prostate volume was seen both based on manual and automatic segmentation. However, based on manual delineations, the peak volume occurred at the 12th fraction at 106.8% of the initial volume, while based on automatic segmentation, the volume peaked at a mean increase 110.8% by the 5th fraction. Standard deviation of volumes for automated segmentation (5.2%) versus manual delineation (12.7%), and reduced variation between fractions from 3.6% to 2.6% indicate better consistency of the automatic segmentation. Conclusion: Automated segmentation by our locally trained nnU-net was more consistent than manual delineations performed clinically. The population mean increase in prostate volume peaked at 110.8% by the 5th fraction after reduce over the remaining treatment course. |
| format | Article |
| id | doaj-art-2dfff423f8da441e88ca4be2f3e6fa57 |
| institution | Kabale University |
| issn | 2405-6316 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Physics and Imaging in Radiation Oncology |
| spelling | doaj-art-2dfff423f8da441e88ca4be2f3e6fa572025-08-20T03:52:19ZengElsevierPhysics and Imaging in Radiation Oncology2405-63162025-04-013410077010.1016/j.phro.2025.100770Volume change of the prostate during moderately hypo-fractionated radiotherapy assessed by artificial intelligenceRasmus L. Christiansen0Bahar Celik1Lars Dysager2Christina J. Nyborg3Steinbjørn Hansen4Tine Schytte5Søren N. Agergaard6Anders S. Bertelsen7Uffe Bernchou8Christian R. Hansen9Karina L. Gottlieb10Nis Sarup11Ebbe L. Lorenzen12Laboratory of Radiation Physics, Department of Oncology, Odense University Hospital, J. B. Winsløws Vej 4, 5000 Odense C, Denmark; Corresponding author.Laboratory of Radiation Physics, Department of Oncology, Odense University Hospital, J. B. Winsløws Vej 4, 5000 Odense C, DenmarkDepartment of Oncology, Odense University Hospital, J. B. Winsløws Vej 4, 5000 Odense C, DenmarkDepartment of Oncology, Odense University Hospital, J. B. Winsløws Vej 4, 5000 Odense C, DenmarkDepartment of Oncology, Odense University Hospital, J. B. Winsløws Vej 4, 5000 Odense C, Denmark; Department of Clinical Research, University of Southern Denmark, J.B. Winsløws Vej 19, 3., 5000 Odense C, DenmarkDepartment of Oncology, Odense University Hospital, J. B. Winsløws Vej 4, 5000 Odense C, Denmark; Department of Clinical Research, University of Southern Denmark, J.B. Winsløws Vej 19, 3., 5000 Odense C, DenmarkLaboratory of Radiation Physics, Department of Oncology, Odense University Hospital, J. B. Winsløws Vej 4, 5000 Odense C, DenmarkLaboratory of Radiation Physics, Department of Oncology, Odense University Hospital, J. B. Winsløws Vej 4, 5000 Odense C, DenmarkLaboratory of Radiation Physics, Department of Oncology, Odense University Hospital, J. B. Winsløws Vej 4, 5000 Odense C, Denmark; Department of Clinical Research, University of Southern Denmark, J.B. Winsløws Vej 19, 3., 5000 Odense C, DenmarkLaboratory of Radiation Physics, Department of Oncology, Odense University Hospital, J. B. Winsløws Vej 4, 5000 Odense C, Denmark; Department of Clinical Research, University of Southern Denmark, J.B. Winsløws Vej 19, 3., 5000 Odense C, DenmarkLaboratory of Radiation Physics, Department of Oncology, Odense University Hospital, J. B. Winsløws Vej 4, 5000 Odense C, DenmarkLaboratory of Radiation Physics, Department of Oncology, Odense University Hospital, J. B. Winsløws Vej 4, 5000 Odense C, DenmarkLaboratory of Radiation Physics, Department of Oncology, Odense University Hospital, J. B. Winsløws Vej 4, 5000 Odense C, Denmark; Department of Clinical Research, University of Southern Denmark, J.B. Winsløws Vej 19, 3., 5000 Odense C, DenmarkBackground: Diagnostic quality MRI acquired daily for radiotherapy (RT) planning on an MR-linac allows longitudinal evaluation of the patients’ anatomy. This study investigated changes in prostate volume during MR-guided RT. The changes were assessed from manual delineations used clinically for daily online adaptation as well as automated segmentation by artificial intelligence (AI). The consistency and congruity of these two methods were evaluated. Methods: The prostate volumes were extracted from daily planning MRI scans of 45 patients receiving 60 Gy in 20 fractions. These volumes were manually edited during the online adaptive treatment planning workflow. The prostate was re-segmented retrospectively for each fraction by AI with an in-house developed nnU-net, trained on prostate cancer patients. The volume for each fraction was normalized to the volume at the patients’ 1st fraction to identify possible time trends. Results: Increased population mean prostate volume was seen both based on manual and automatic segmentation. However, based on manual delineations, the peak volume occurred at the 12th fraction at 106.8% of the initial volume, while based on automatic segmentation, the volume peaked at a mean increase 110.8% by the 5th fraction. Standard deviation of volumes for automated segmentation (5.2%) versus manual delineation (12.7%), and reduced variation between fractions from 3.6% to 2.6% indicate better consistency of the automatic segmentation. Conclusion: Automated segmentation by our locally trained nnU-net was more consistent than manual delineations performed clinically. The population mean increase in prostate volume peaked at 110.8% by the 5th fraction after reduce over the remaining treatment course.http://www.sciencedirect.com/science/article/pii/S2405631625000752RadiotherapyProstate cancerAdaptive radiotherapyMRI-guidedAutomatic segmentationnnU-net |
| spellingShingle | Rasmus L. Christiansen Bahar Celik Lars Dysager Christina J. Nyborg Steinbjørn Hansen Tine Schytte Søren N. Agergaard Anders S. Bertelsen Uffe Bernchou Christian R. Hansen Karina L. Gottlieb Nis Sarup Ebbe L. Lorenzen Volume change of the prostate during moderately hypo-fractionated radiotherapy assessed by artificial intelligence Physics and Imaging in Radiation Oncology Radiotherapy Prostate cancer Adaptive radiotherapy MRI-guided Automatic segmentation nnU-net |
| title | Volume change of the prostate during moderately hypo-fractionated radiotherapy assessed by artificial intelligence |
| title_full | Volume change of the prostate during moderately hypo-fractionated radiotherapy assessed by artificial intelligence |
| title_fullStr | Volume change of the prostate during moderately hypo-fractionated radiotherapy assessed by artificial intelligence |
| title_full_unstemmed | Volume change of the prostate during moderately hypo-fractionated radiotherapy assessed by artificial intelligence |
| title_short | Volume change of the prostate during moderately hypo-fractionated radiotherapy assessed by artificial intelligence |
| title_sort | volume change of the prostate during moderately hypo fractionated radiotherapy assessed by artificial intelligence |
| topic | Radiotherapy Prostate cancer Adaptive radiotherapy MRI-guided Automatic segmentation nnU-net |
| url | http://www.sciencedirect.com/science/article/pii/S2405631625000752 |
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