Real-time fully automated dosimetric computation for CT images in the clinical workflow: A feasibility study

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Abstract

Background: Currently, the volume computed tomography dose index (CTDIvol), the most-used quantity to express the output dose of a computed tomography (CT) patient’s dose, is not related to the real size and attenuation properties of each patient. The size-specific dose estimates (SSDE), based on the water-equivalent diameter (DW) overcome those issues. The proposed methods found in the literature do not allow real-time computation of DW and SSDE. Purpose: This study aims to develop a software to compute DW and SSDE in a real-time clinical workflow. Method: In total, 430 CT studies and scans of a water-filled funnel phantom were used to compute accuracy and evaluate the times required to compute the DW and SSDE. Two one-sided tests (TOST) equivalence test, Bland–Altman analysis, and bootstrap-based confidence interval estimations were used to evaluate the differences between actual diameter and DW computed automatically and between DW computed automatically and manually. Results: The mean difference between the DW computed automatically and the actual water diameter for each slice is −0.027% with a TOST confidence interval equal to [−0.087%, 0.033%]. Bland–Altman bias is −0.009% [−0.016%, −0.001%] with lower limits of agreement (LoA) equal to −0.0010 [−0.094%, −0.068%] and upper LoA equal to 0.064% [0.051%, 0.077%]. The mean difference between DW computed automatically and manually is −0.014% with a TOST confidence interval equal to [−0.056%, 0.028%] on phantom and 0.41% with a TOST confidence interval equal to [0.358%, 0.462%] on real patients. The mean time to process a single image is 13.99 ms [13.69 ms, 14.30 ms], and the mean time to process an entire study is 11.5 s [10.62 s, 12.63 s]. Conclusion: The system shows that it is possible to have highly accurate DW and SSDE in almost real-time without affecting the clinical workflow of CT examinations.

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Porzio, M., & Anam, C. (2022). Real-time fully automated dosimetric computation for CT images in the clinical workflow: A feasibility study. Frontiers in Oncology, 12. https://doi.org/10.3389/fonc.2022.798460

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