Application of error classification model using indices based on dose distribution for characteristics evaluation of multileaf collimator position errors
Abstract This study aims to evaluate the specific characteristics of various multileaf collimator (MLC) position errors that are correlated with the indices using dose distribution. The dose distribution was investigated using the gamma, structural similarity, and dosiomics indices. Cases from the A...
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| Format: | Article |
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Nature Portfolio
2023-07-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-35570-1 |
| _version_ | 1797784729561333760 |
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| author | Heesoon Sheen Han-Back Shin Hojae Kim Changhwan Kim Jihun Kim Jin Sung Kim Chae-Seon Hong |
| author_facet | Heesoon Sheen Han-Back Shin Hojae Kim Changhwan Kim Jihun Kim Jin Sung Kim Chae-Seon Hong |
| author_sort | Heesoon Sheen |
| collection | DOAJ |
| description | Abstract This study aims to evaluate the specific characteristics of various multileaf collimator (MLC) position errors that are correlated with the indices using dose distribution. The dose distribution was investigated using the gamma, structural similarity, and dosiomics indices. Cases from the American Association of Physicists in Medicine Task Group 119 were planned, and systematic and random MLC position errors were simulated. The indices were obtained from distribution maps and statistically significant indices were selected. The final model was determined when all values of the area under the curve, accuracy, precision, sensitivity, and specificity were higher than 0.8 (p < 0.05). The dose–volume histogram (DVH) relative percentage difference between the error-free and error datasets was examined to investigate clinical relations. Seven multivariate predictive models were finalized. The common significant dosiomics indices (GLCM Energy and GLRLM_LRHGE) can characterize the MLC position error. In addition, the finalized logistic regression model for MLC position error prediction showed excellent performance with AUC > 0.9. Furthermore, the results of the DVH were related to dosiomics analysis in that it reflects the characteristics of the MLC position error. It was also shown that dosiomics analysis could provide important information on localized dose-distribution differences in addition to DVH information. |
| first_indexed | 2024-03-13T00:44:03Z |
| format | Article |
| id | doaj.art-e3d6965f57174609a41fef0765467760 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-03-13T00:44:03Z |
| publishDate | 2023-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-e3d6965f57174609a41fef07654677602023-07-09T11:11:35ZengNature PortfolioScientific Reports2045-23222023-07-0113111110.1038/s41598-023-35570-1Application of error classification model using indices based on dose distribution for characteristics evaluation of multileaf collimator position errorsHeesoon Sheen0Han-Back Shin1Hojae Kim2Changhwan Kim3Jihun Kim4Jin Sung Kim5Chae-Seon Hong6Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences and Technology, Sungkyunkwan UniversityDepartment of Radiation Oncology, Gachon University Gil Medical CenterDepartment of Radiation Oncology, Yonsei Cancer CenterDepartment of Radiation Oncology, Yonsei Cancer Center, Yonsei University College of MedicineDepartment of Radiation Oncology, Yonsei Cancer Center, Yonsei University College of MedicineDepartment of Radiation Oncology, Yonsei Cancer Center, Yonsei University College of MedicineDepartment of Radiation Oncology, Yonsei Cancer Center, Yonsei University College of MedicineAbstract This study aims to evaluate the specific characteristics of various multileaf collimator (MLC) position errors that are correlated with the indices using dose distribution. The dose distribution was investigated using the gamma, structural similarity, and dosiomics indices. Cases from the American Association of Physicists in Medicine Task Group 119 were planned, and systematic and random MLC position errors were simulated. The indices were obtained from distribution maps and statistically significant indices were selected. The final model was determined when all values of the area under the curve, accuracy, precision, sensitivity, and specificity were higher than 0.8 (p < 0.05). The dose–volume histogram (DVH) relative percentage difference between the error-free and error datasets was examined to investigate clinical relations. Seven multivariate predictive models were finalized. The common significant dosiomics indices (GLCM Energy and GLRLM_LRHGE) can characterize the MLC position error. In addition, the finalized logistic regression model for MLC position error prediction showed excellent performance with AUC > 0.9. Furthermore, the results of the DVH were related to dosiomics analysis in that it reflects the characteristics of the MLC position error. It was also shown that dosiomics analysis could provide important information on localized dose-distribution differences in addition to DVH information.https://doi.org/10.1038/s41598-023-35570-1 |
| spellingShingle | Heesoon Sheen Han-Back Shin Hojae Kim Changhwan Kim Jihun Kim Jin Sung Kim Chae-Seon Hong Application of error classification model using indices based on dose distribution for characteristics evaluation of multileaf collimator position errors Scientific Reports |
| title | Application of error classification model using indices based on dose distribution for characteristics evaluation of multileaf collimator position errors |
| title_full | Application of error classification model using indices based on dose distribution for characteristics evaluation of multileaf collimator position errors |
| title_fullStr | Application of error classification model using indices based on dose distribution for characteristics evaluation of multileaf collimator position errors |
| title_full_unstemmed | Application of error classification model using indices based on dose distribution for characteristics evaluation of multileaf collimator position errors |
| title_short | Application of error classification model using indices based on dose distribution for characteristics evaluation of multileaf collimator position errors |
| title_sort | application of error classification model using indices based on dose distribution for characteristics evaluation of multileaf collimator position errors |
| url | https://doi.org/10.1038/s41598-023-35570-1 |
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