ArticleJournal of medical radiation sciences2017
Accuracy of eight deformable image registration (DIR) methods for tomotherapy megavoltage computed tomography (MVCT) images.
Article in Journal of medical radiation sciences, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- The effects of mega-voltage CT scan parameters on offline adaptive radiation therapy.Radiological physics and technology · 2024Article
- Feasibility of artificial intelligence-driven interfractional monitoring of organ changes by mega-voltage computed tomography in intensity-modulated radiotherapy of prostate cancer.Radiation oncology journal · 2023Article
- Validation of accuracy deformable image registration contour propagation using a benchmark virtual HN phantom dataset.Journal of applied clinical medical physics · 2021Article
- Autosegmentation of the rectum on megavoltage image guidance scans.Biomedical physics & engineering express · 2019Article
- Accuracy of eight deformable image registration (DIR) methods for tomotherapy megavoltage computed tomography (MVCT) images.Journal of medical radiation sciences · 2017Article
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Abstract
introductionThe application of deformable image registration (DIR) to megavoltage computed tomography (MVCT) images benefits adaptive radiotherapy. This study aims to quantify the accuracy of DIR for MVCT images when using different deformation methods assessed in a cubic phantom and nasopharyngeal carcinoma (NPC) patients.
methodsIn the control studies, the DIR accuracy in air-tissue and tissue-tissue interface areas was observed using twelve shapes of acrylic and tissue-equivalent material inserted in the phantom. In the clinical studies, the 1st and 20th fraction MVCT images of seven NPC patients were used to evaluate application of DIR. The eight DIR methods used in the DIRART software varied in (i) transformation framework (asymmetric or symmetric), (ii) DIR registration algorithm (Demons or Optical Flow) and (iii) mapping direction (forward or backward). The accuracy of the methods was compared using an intensity-based criterion (correlation coefficient, CC) and volume-based criterion (Dice's similarity coefficient, DSC).
resultsThe asymmetric transformation with Optical Flow showed the best performance for air-tissue interface areas, with a mean CC and DSC of 0.97 ± 0.03 and 0.79 ± 0.11 respectively. The symmetric transformation with Optical Flow showed good agreement for tissue-tissue interface areas with a CC of (0.99 ± 0.01) and DSC of (0.89 ± 0.03). The sequences of target domains were significantly different in tissue-tissue interface areas.
conclusionsThe deformation method and interface area affected the accuracy of DIR. The validation techniques showed satisfactory volume matching of greater than 0.7 with DSC analysis. The methods can yield acceptable results for clinical applications.
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