Sensitivity analysis of dual-energy computed tomography multi-triplet material decomposition

Giavanna Jadick; Ingrid Reiser; Patrick La Rivière

doi:10.1117/12.3006548

1 April 2024 Sensitivity analysis of dual-energy computed tomography multi-triplet material decomposition

Giavanna Jadick, Ingrid Reiser, Patrick La Rivière

Proceedings Volume 12925, Medical Imaging 2024: Physics of Medical Imaging; 1292529 (2024) https://doi.org/10.1117/12.3006548
Event: SPIE Medical Imaging, 2024, San Diego, California, United States

Conference Poster

Abstract

Dual-energy computed tomography (CT) can improve image quality relative to single-energy CT through decomposition into two or three basis materials and synthesis into virtual monoenergetic images (VMIs). Decomposition into even more materials is possible using a multi-triplet material decomposition (MMD) algorithm, in which a different set of materials (i.e. “material triplet”) is chosen for each voxel. MMD could be particularly useful for certain tasks, such as atherosclerotic plaque risk assessment. However, in its current form, MMD requires manual tuning to optimize its performance in different imaging scenarios. This work aimed to quantitatively explore the sensitivity of the MMD algorithm to CT image noise and initial VMI basis materials. We simulated 80-kVp and 140-kVp CT images of a water cylinder with four inserts (soft tissue, fat, calcium, and iodine) at twenty dose levels (0.2 to 4.0mGy). The needed input VMIs were generated using initial two-material decomposition into either soft tissue/bone or water/aluminum material pairs. VMIs were then used for MMD into basis images of the four insert materials. We found that the choice of VMI basis materials affects MMD image quality at lower doses; tissue/bone was best for all materials except fat using a dose below 1mGy. Additionally, the image quality benefit of increasing dose plateaus at a certain point, possibly due to the reduction in voxels “jumping” to different material triplets. This sensitivity analysis offers insight into the nuanced effects of MMD input variations and may be useful for jointly optimizing the quality of many basis material images with minimal patient dose.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Giavanna Jadick, Ingrid Reiser, and Patrick La Rivière "Sensitivity analysis of dual-energy computed tomography multi-triplet material decomposition", Proc. SPIE 12925, Medical Imaging 2024: Physics of Medical Imaging, 1292529 (1 April 2024); https://doi.org/10.1117/12.3006548

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