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Optimizing cardiac CT angiography minimum detectable difference via Taguchi’s dynamic algorithm, a V-shaped line gauge, and three PMMA phantoms

Published: 01 January 2022 Publication History

Abstract

Background:

Radiologists widely use the minimum detectable difference (MDD) concept for inspecting the imaging quality and quantify the spatial resolution of scans.

Objective:

This study adopted Taguchi’s dynamic algorithm to optimize the MDD of cardiac CT angiography (CTA) using a V-shaped line gauge and three PMMA phantoms (50, 70, and 90 kg).

Methods:

The phantoms were customized in compliance with the ICRU-48 report, whereas the V-shaped line gauge was indigenous to solidify the cardiac CTA scan image quality by two adjacent peaks along the V-shaped slit. Accordingly, the six factors A-F assigned in this study were A (kVp), B (mAs), C (CT pitch), D (FOV), E (iDose), and F (reconstruction filter). Since each factor could have two or three levels, eighteen groups of factor combinations were organized according to Taguchi’s dynamic algorithm. Three welltrained radiologists ranked the CTA scan images three times for three different phantoms. Thus, 27 (3 × 3 × 3) ranked scores were summed and averaged to imply the integrated performance of one specific group, and eventually, 18 groups of CTA scan images were analyzed. The unique signal-to-noise ratio (S/N, dB) and sensitivity in the dynamic algorithm were calculated to reveal the true contribution of assigned factors and clarify the situation in routine CTA diagnosis.

Results:

Minimizing the cross-interactions among factors, the optimal factor combination was found to be as follows: A (100 kVp), B (600 mAs), C (pitch 0.200 mm), D (FOV 280 mm), E (iDose 5), and F (filter XCA). The respective MDD values were 2.15, 2.32, and 1.87 mm for 50, 70, and 90 kg phantoms, respectively. The MDD of the 90 kg phantom had the most precise spatial resolution, while that of the 70 kg phantom was the worst.

Conclusion:

The Taguchi static and dynamic optimization algorithms were compared, and the latter’s superiority was substantiated.

References

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Cited By

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  • (2024)Enhanced acrylic gauge with five eccentric circles for optimizing CT angiography spatial resolution via Taguchi’s methodologyTechnology and Health Care10.3233/THC-24800632:S1(65-78)Online publication date: 31-May-2024
  • (2023)Potential risk quantification from multiple biological factors via the inverse problem algorithm as an artificial intelligence tool in clinical diagnosisTechnology and Health Care10.3233/THC-23600831:S1(69-79)Online publication date: 28-Apr-2023

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          cover image Technology and Health Care
          Technology and Health Care  Volume 30, Issue S1
          2022
          534 pages
          This is an open access article distributed under the terms of the Creative Commons Attribution Non-Commercial (CC BY-NC 4.0) License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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          IOS Press

          Netherlands

          Publication History

          Published: 01 January 2022

          Author Tags

          1. Taguchi dynamic
          2. phantom
          3. CT angiography
          4. resolution

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          View all
          • (2024)Enhanced acrylic gauge with five eccentric circles for optimizing CT angiography spatial resolution via Taguchi’s methodologyTechnology and Health Care10.3233/THC-24800632:S1(65-78)Online publication date: 31-May-2024
          • (2023)Potential risk quantification from multiple biological factors via the inverse problem algorithm as an artificial intelligence tool in clinical diagnosisTechnology and Health Care10.3233/THC-23600831:S1(69-79)Online publication date: 28-Apr-2023

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