Open AccessArticle
A Retrospective Analysis of the First Clinical 5DCT Workflow
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Michael Lauria, Minji Kim, Dylan O’Connell, Yi Lao, Claudia R. Miller, Louise Naumann, Peter Boyle, Ann Raldow, Alan Lee, Ricky R. Savjani, Drew Moghanaki and Daniel A. Low
Cancers 2025, 17(3), 531; https://doi.org/10.3390/cancers17030531 (registering DOI) - 5 Feb 2025
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Abstract
Background/Objectives: 5DCT was first proposed in 2005 as a motion-compensated CT simulation approach for radiotherapy treatment planning to avoid sorting artifacts that arise in 4DCT when patients breathe irregularly. Since March 2019, 5DCT has been clinically implemented for routine use at our institution
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Background/Objectives: 5DCT was first proposed in 2005 as a motion-compensated CT simulation approach for radiotherapy treatment planning to avoid sorting artifacts that arise in 4DCT when patients breathe irregularly. Since March 2019, 5DCT has been clinically implemented for routine use at our institution to leverage this technological advantage. The clinical workflow includes a quality assurance report that describes the output of primary workflow steps. This study reports on the challenges and quality of the clinical 5DCT workflow using these quality assurance reports. Methods: We evaluated all thoracic 5DCT simulation datasets consecutively acquired at our institution between March 2019 and December 2022 for thoracic radiotherapy treatment planning. The 5DCT datasets utilized motion models constructed from 25 fast-helical free-breathing computed tomography (FHFBCTs) with simultaneous respiratory bellows signal monitoring to reconstruct individual, user-specified breathing-phase images (termed 5DCT phase images) for internal target volume contouring. Each 5DCT dataset was accompanied by a structured quality assurance report composed of qualitative and quantitative measures of the breathing pattern, image quality, DIR quality, model fitting accuracy, and a validation process by which the original FHFBCT scans were regenerated with the 5DCT model. Measures of breathing irregularity, image quality, and DIR quality were retrospectively categorized on a grading scale from 1 (regular breathing and accurate registration/modeling) to 4 (irregular breathing and inaccurate registration/modeling). The validation process was graded according to the same scale, and this grade was termed the suitability-for-treatment-planning (STP) grade. We correlated the graded variables to the STP grade. In addition to the quality assurance reports, we reviewed the contour sessions to determine how often 5DCT phase images were used for treatment planning and delivery. Results: There were 169 5DCT simulation datasets available from 156 patients for analysis. The STP was moderately correlated with breathing irregularity, image quality, and DIR quality (Spearman coefficients: 0.26, 0.30, and 0.50, respectively). Multiple linear regression analysis demonstrated that STP was correlated with regular breathing patterns (
p = 0.008), image quality (
p < 0.001), and better DIR quality (
p < 0.001). 5DCT datasets were used for treatment planning in 82% of cases, while in 12% of cases, a backup image process was used. In total, 6% of image datasets were not used for treatment planning due to factors unrelated to the 5DCT workflow quality. Conclusions: The strongest association with STP was with DIR quality grades, as indicated by both Spearman and multiple linear regression analysis, implying that improvements to DIR accuracy and evaluation may be the best route for further improvement to 5DCT. The high rate of 5DCT phase image use for treatment planning showed that the workflow was reliable, and this has encouraged us to continue to develop and improve the workflow steps.
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