Optimizing the TLD-100h Readout System Under Various Radioactive I-131 Doses via the Revised Taguchi Dynamic Quality Loss Function

Pan, Lung-Fa; Le, Yingyi; Yen, Yu-Chen; Weng, Jui-Hung; Chen, Chien-Yi; Liang, Chun-Chieh; Pan, Lung‐Kwang

doi:10.1142/s0219519420400242

Cited by 3 publications

(3 citation statements)

References 9 publications

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“…As the unique quality characteristic of Taguchi's dynamic algorithm, sensitivity can be customized and revised according to different perspectives. For most dynamic studies, high sensitivity is always preferable [8,13,19]. However, the sensitivity has a different interpretation in this study because the sensitivity implies the imaging quality versus various phantoms' weights.…”

Section: Sensitivity In the Dynamic Algorithmmentioning

confidence: 95%

“…Unlike the static preset in Taguchi's optimization, the dynamic one is reputed for its strong flexibility in various PMMA phantom weights defined in this study or exposed radioactive doses [8,13]. Nevertheless, 78 the β parameter is preset via "higherthe-better" criterion to intensify good quality characteristics in the 79 conventional robust designation.…”

Section: Taguchi's Dynamic Algorithmmentioning

confidence: 99%

“…The imaging quality of scans in medical facilities, such as X-ray, cardiac bi-plane X-ray, CT, CTA, mammography, and a gamma camera, is vital for the accurate diagnosis. Therefore, multiple techniques have been introduced to upgrade the spatial resolution, compromising the high quality of the acquired images and an acceptable exposed dose required for their provision [6][7][8][9][10][11][12][13]. Taguchi's optimization analysis became an assessable technique in providing quantified data for optimization due to its userfriendly and reliable realization.…”

Section: Introductionmentioning

confidence: 99%

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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

Pan

Chen

Wang

et al. 2022

THC

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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.

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Section: Sensitivity In the Dynamic Algorithmmentioning

confidence: 95%

Section: Taguchi's Dynamic Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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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

Pan

Chen

Wang

et al. 2022

THC

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Practical Application of Taguchi Optimization Methodology to Medical Facilities: An Integrated Study

Peng

Pan

Huang

et al. 2022

J. Mech. Med. Biol.

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A comprehensive review of applying Taguchi’s optimization methodology to medical facilities was evaluated in this study. Taguchi’s optimization methodology is one kind of robust designation and is reputed for integrating multiple factors to pursue one goal. According to Taguchi’s suggestion, the efficient and reliable arrangement of experimental groups with numerous factors shortened the observed timing and provided bountiful statistical data. Although this method is widely used in mechanical, civil, and chemical engineering fields, it became adopted in medical facilities only in the last decade. Most of Taguchi’s analyses focused on optimizing the imaging quality for diagnosis. The medical facilities include regular X-ray, cardiac X-ray, CT (computed tomography), CTA (computed tomography angiography), LINAC (medical linear accelerator), or gamma camera scans. The images were all manipulated according to various radiation-induced interactions; thus, the optimization process of imaging resolution can offer an essential contribution to this kind of facility. In this study, we summarized the Taguchi-related papers in medical facilities and evaluated common principles in organizing the unique orthogonal array, assigning various signal-to-noise ratios, using quantified gauges, and ranking or grading the obtained imaging quality in the datum analysis process. The further elaboration on how to preset the user demanded goal in the optimization process, the necessity of focusing on cross interaction among factors, dynamic analysis superiority over static one preset in Taguchi’s analysis, and how to preset an ideal signal-to-noise ratio to satisfy the researcher demand, the importance of verification or testification in clinical cases or the assistance of ANOVA to depict a complete concept of applying Taguchi’s optimization methodology.

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Optimizing the Ultrasound Image Quality of Carotid Artery Stenosis Patients via Taguchi’s Dynamic Analysis and an Indigenous Water Phantom

Hsiao

Lin

et al. 2022

Applied Sciences

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This study optimized the ultrasound image of carotid artery stenosis using Taguchi dynamic analysis and an indigenous water phantom. Eighteen combinations of seven essential factors of the ultrasound scan facility were organized according to Taguchi’s L18 orthogonal array. The seven factors were assigned as follows: (1) angle of probe; (2) signal gain; (3) resolution vs. speed; (4) dynamic range; (5) XRES; (6) zoom; (7) time gain compensation. An indigenous water phantom was customized to satisfy the quantified need in Taguchi’s analysis. Unlike the conventional dynamic Taguchi analysis, an innovative quantified index, the figure of merit (FOM), was proposed to integrate four specific quality characteristics, namely (i) average difference between the practical scan and theoretically preset area (78.5, 50.2 and 12.6 mm2) of stenosis, (ii) standard deviation of the average, (iii) practical scan’s sensitivity β to various stenosis diameters (10, 8, and 4 mm), and (iv) correlation coefficient r2 of the linear regressed sensitivity curve. The highest value (FOM = 0.413) was furnished by the optimal combination of factors on 18 groups under study, yielding high r2 and low β or standard deviation values and the best quality of ultrasound images for the further clinical diagnosis. The comparison between FOM and the conventional signal-to-noise (S/N) ratio in Taguchi’s analysis revealed that FOM compiled more quality characteristics that were superior by nature to fulfill the practical need in clinical diagnosis. The alternative choice in ultrasound scan optimization can be based on stenosis diameter variation from a different perspective to be explored in the follow-up study.

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Optimizing the TLD-100h Readout System Under Various Radioactive I-131 Doses via the Revised Taguchi Dynamic Quality Loss Function

Cited by 3 publications

References 9 publications

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

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

Practical Application of Taguchi Optimization Methodology to Medical Facilities: An Integrated Study

Optimizing the Ultrasound Image Quality of Carotid Artery Stenosis Patients via Taguchi’s Dynamic Analysis and an Indigenous Water Phantom

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