Enhanced acrylic gauge with five eccentric circles for optimizing CT angiography spatial resolution via Taguchi's methodology.

BACKGROUND: Cerebral examination via CTA is always the first choice for patients with unexpected brain injury or different types of brain lesions to detect ruptured hemangiomas, vascular infarcts, or other brain tissue lesions. OBJECTIVE: This study innovated the acrylic gauge with five eccentric circles for computed tomography angiography (CTA) analysis to optimize the spatial resolution via Taguchi's methodology. METHODS: The customized gauge was revised from the V-shaped slit gauge and transferred into five eccentric circles' slit gauge. The gauge was assembled with another six acrylic layers to simulate the human head. Taguchi's L18 orthogonal array was adopted to optimize the spatial resolution of CTA imaging quality. In doing so, six essential factors of CTA are kVp, mAs, spiral rotation pitch, FOV, rotation time of the CT and reconstruction filter, and each factor has either two or three levels to organize into eighteen combinations to simulate the full factor combination of 486 (21 × 35 = 486) times according to Taguchi's recommendation. Three well-trained radiologists ranked the gauge's 18 CTA scanned imaging qualities according to contrast, sharpness, and spatial resolution and derived the unique fish-bone-plot of six factors for further analysis. The optimal factor combination of CTA was proven by follow-up verification and ANOVA to obtain this study's dominant or minor factor. RESULTS: The optimal factor combination of CTA was A2 (120 kVp), B3 (200 mAs), C1 (Pitch 0.6), D2 (FOV 220 mm2), E1 (rotation time 0.33 s), and F3 (Brain sharp, UC). Furthermore, deriving a quantified MDD (minimum detectable difference) to imply the spatial resolution of CTA, a semiauto profile analysis program run in MATLAB and OriginPro was recommended to evaluate the MDD and to suppress the manual error in calculation. Eventually, the derived MDDs of the conventional and optimal factor combinations of CTA were 2.35 and 2.26 mm, respectively, in this study. CONCLUSION: Taguchi's methodology was found applicable for quantifying the CTA imaging quality in practical applications.

Inverse Problem Algorithm-Based Time-Resolved Imaging of Head and Neck Computed Tomography Angiography Contrast Kinetics with Clinical Testification.

This study mitigated the challenge of head and neck CT angiography by IPA-based time-resolved imaging of contrast kinetics. To this end, 627 cerebral hemorrhage patients with dizziness, brain aneurysm, stroke, or hemorrhagic stroke diagnosis were randomly categorized into three groups, namely, the original dataset (450), verification group (112), and in vivo testified group (65), in the Affiliated BenQ Hospital of Nanjing Medical University. In the first stage, seven risk factors were assigned: age, CTA tube voltage, body surface area, heart rate per minute, cardiac output blood per minute, the actual injected amount of contrast media, and CTA delayed trigger timing. The expectation value of the semi-empirical formula was the CTA number of the patient's left artery (LA). Accordingly, 29 items of the first-order nonlinear equation were calculated via the inverse problem analysis (IPA) technique run in the STATISTICA 7.0 program, yielding a loss function and variance of 3.1837 and 0.8892, respectively. A dimensionless AT was proposed to imply the coincidence, with a lower AT indicating a smaller deviation between theoretical and practical values. The derived formula was confirmed for the verification group of 112 patients, reaching high coincidence, with average ATavg and standard deviation values of 3.57% and 3.06%, respectively. In the second stage, the formula was refined to find the optimal amount of contrast media for the CTA number of LA approaching 400. Finally, the above procedure was applied to head and neck CTA images of the third group of 65 patients, reaching an average CTA number of LA of 407.8 ± 16.2 and finding no significant fluctuations.

Treatment and mortality risk of older adults with non-small cell cancer in Taiwan: A population-based cohort study.

BACKGROUND: Older patients tend to have decreased physical functions and more comorbidities than younger patients. At present, the best management for very elderly patients with lung cancer is not known. In this study, we aimed to investigate treatment and mortality risk of older adults with non-small cell cancer (NSCLC) in Taiwan. METHODS: This study analyzed data from the Taiwan Cancer Registry database. Patients aged ≥80 years with newly diagnosed NSCLC between 2010 and 2017 were included. Treatment options were categorized as curative, palliative, and no treatment. Patients were followed up until death or December 31, 2020. Univariable and multivariable Cox proportional hazards models were used to estimate mortality risk, and Kaplan-Meier survival curves were drawn. RESULTS: A total of 11 941 patients, aged ≥80 years, with newly diagnosed NSCLC between 2010 and 2017 were identified from the Taiwan Cancer Registry and followed up until 2020. The mean age was 84.4 ± 3.7 years old, and 7468 (62.54%) were men. The Kaplan-Meier survival curves showed significant differences across the three treatment options (log-rank p < 0.001). Results from multivariate Cox regression demonstrated that patients on palliative treatment (adjusted HR: 0.52, 95% CI: 0.48-0.56, p < 0.001) and curative treatment (adjusted HR: 0.45, 95% CI: 0.42-0.48, p < 0.001) had a significantly lower mortality risk than those with no treatment. The subgroup analyses stratified by cancer stages also showed consistent findings. CONCLUSION: Elderly patients with NSCLC had significantly decreased mortality risk when receiving curative or palliative treatment compared with those without treatment. In the future, further studies are warranted to investigate complications and quality of life of elderly patients with NSCLC during palliative or curative treatment.

Potential risk quantification from multiple biological factors via the inverse problem algorithm as an artificial intelligence tool in clinical diagnosis.

BACKGROUND: The inverse problem algorithm (IPA) uses mathematical calculations to estimate the expectation value of a specific index according to patient risk factor groups. The contributions of particular risk factors or their cross-interactions can be evaluated and ranked by their importance. OBJECTIVE: This paper quantified the potential risks from multiple biological factors by integrated case studies in clinical diagnosis via the IPA technique. Acting as artificial intelligence field component, this technique constructs a quantified expectation value from multiple patients' biological index series, e.g., the optimal trigger timing for CTA, a particular drug in blood concentration data, the risk for patients with clinical syndromes. METHODS: Common biological indices such as age, body surface area, mean artery pressure, and others are treated as risk factors upon their normalization to the range from -1.0 to +1.0, with a non-dimensional zero point 0.0 corresponding to the average risk factor index. The patients' quantified indices are re-arranged into a large data matrix. Next, the inverse and column matrices of the compromised numerical solution are constructed. RESULTS: This paper discusses quasi-Newton and Rosenbrock analyses performed via the STATISTICA program to solve the above inverse problem, yielding the specific expectation value in the form of a multiple-term nonlinear semi-empirical equation. The extensive background, including six previous publications of these authors' team on IPA, was comprehensively re-addressed and scrutinized, focusing on limitations, stumbling blocks, and validity range of the IPA approach as applied to various tasks of preventive medicine. Other key contributions of this study are detailed estimations of the effect of risk factors' coupling/cross-interactions on the IPA computations and the convergence rate of the derived semi-empirical equation viz. the final constant term. CONCLUSION: The main findings and practical recommendations are considered useful for preventive medicine tasks concerning potential risks of patients with various clinical syndromes.

Quantitative Prediction of SYNTAX Score for Cardiovascular Artery Disease Patients via the Inverse Problem Algorithm Technique as Artificial Intelligence Assessment in Diagnostics.

The quantitative prediction of the SYNTAX score for cardiovascular artery disease patients using the inverse problem algorithm (IPA) technique in artificial intelligence was explored in this study. A 29-term semi-empirical formula was defined according to seven risk factors: (1) age, (2) mean arterial pressure, (3) body surface area, (4) pre-prandial blood glucose, (5) low-density-lipoprotein cholesterol, (6) Troponin I, and (7) C-reactive protein. Then, the formula was computed via the STATISTICA 7.0 program to obtain a compromised solution for a 405-patient dataset with a specific loss function [actual-predicted]2 as low as 3.177, whereas 0.0 implies a 100% match between the prediction and observation via "the lower, the better" principle. The IPA technique first created a data matrix [405 × 29] from the included patients' data and then attempted to derive a compromised solution of the column matrix of 29-term coefficients [29 × 1]. The correlation coefficient, r2, of the regression line for the actual versus predicted SYNTAX score was 0.8958, showing a high coincidence among the dataset. The follow-up verification based on another 105 patients' data from the same group also had a high correlation coefficient of r2 = 0.8304. Nevertheless, the verified group's low derived average AT (agreement) (ATavg = 0.308 ± 0.193) also revealed a slight deviation between the theoretical prediction from the STATISTICA 7.0 program and the grades assigned by clinical cardiologists or interventionists. The predicted SYNTAX scores were compared with earlier reported findings based on a single-factor statistical analysis or scanned images obtained by sonography or cardiac catheterization. Cardiologists can obtain the SYNTAX score from the semi-empirical formula for an instant referral before performing a cardiac examination.

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

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.

Evaluating environmental radiations of the tomotherapy facility by optimizing full factorial design of the TLD technique.

BACKGROUND: In the last 40 years, the number of deaths due to cancer has been the highest in TaiwanOBJECTIVE: To optimize the readout system of the thermoluminescent dosimeter (TLD)-100H, the radiation rates among the Tomotherapy (TOMO) facility of the Department of Radiology Oncology of Chung Shan Medical University Hospital (CSMUH) were calculated with a 32 full factorial design (FFD). METHODS: A ten-month survey of the facility was employed using the sensitive and accurate TLD method. The TLD system was optimized for maximum temperature, heat rate, and preheat temperature of Harshaw 3500 reader. Eight analyzed groups with different factors were tested. RESULTS: The TOMO facility had significantly different radiation rates. The farther away from the gantry head, environmental radiation rates. The half value layer (HVL) was also determined. These results were compared with published. No significant contributions of environmental gamma radiations were detected except in the treatment room. CONCLUSIONS: Those were far below the occupational doses recommended by ICRP 60.

Biokinetic model of radioiodine I-131 in nine thyroid cancer patients subjected to in-vivo gamma camera scanning: A simplified five-compartmental model.

A five-compartmental biokinetic model of I-131 radioiodine based on in-vivo gamma camera scanning results was developed and successfully applied to nine thyroid cancer patients who were administered 1,110 MBq I-131 in capsules for the residual thyroid gland ablation. The I-131 solution activity among internal organs was analyzed via the revised biokinetic model of iodine recommended by the ICRP-30 and -56 reports. Accordingly, a five-compartmental (stomach, body fluid, thyroid, whole body, and excretion) model was established to simulate the metabolic mechanism of I-131 in thyroid cancer patients, whereas the respective four simultaneous differential equations were solved via a self-developed program run in MATLAB. This made it possible to provide a close correlation between MATLAB simulation results and empirical data. The latter data were collected through in-vivo gamma camera scans of nine patients obtained after 1, 4, 24, 48, 72, and 168 hours after radioactive I-131 administration. The average biological half-life values for the stomach, body fluid, thyroid, and whole body of thyroid cancer patients under study were 0.54±0.32, 12.6±1.8, 42.8±5.1, and 12.6±1.8 h, respectively. The corresponding branching ratios I12, I23, I25, I34, I42, and I45 as denoted in the biokinetic model of iodine were 1.0, 0.21±0.14, 0.79±0.14, 1.0, 0.1, and 0.9, respectively. The average values of the AT dimensionless index used to verify the agreement between empirical and numerical simulation results were 0.056±0.017, 0.017±0.014, 0.044±0.023, and 0.045±0.009 for the stomach, thyroid, body fluid + whole body, and total, respectively. The results obtained were considered quite instrumental in the elucidation of metabolic mechanisms in the human body, particularly in thyroid cancer patients.

TLD environmental monitoring of new scanner facilities at the Nuclear Medicine Department of the Taiwan Medical University Hospital.

OBJECTIVE: Single-photon emission computed tomography (SPECT) as well as dual energy X-ray absorptiometry (DXA) scanners were designed in July 2018 at the Nuclear Medicine Department (NM), of the Taiwan Medical University Hospital. These scanners emit substantial X-rays from the target, which are tungsten, iron. Therefore, patients undergoing SPECT and DXA diagnosis, in addition to medical personnel, are exposed to undesirable photon leakage. METHODS: Following administration of radiopharmaceuticals, patients become radioactive sources; thus, it is necessary to evaluate a possible increase in the environmental gamma exposure rates in the NM as a result of the operation of the new scanners. A three month evaluation of environmental radiation in the NM was performed using the accurate and sensitive TLD-100H approach, which gives an error rate less than 10%. RESULTS: Detected exposure radiation rates in the NM ranged from 0.12 ± 0.02 to 1.00 ± 0.15 mSv per month, indicating that the imaging room had significantly different radiation rates. The results were compared with previous results, and no significant contribution to the enhancement of environmental gamma radiation was detected, which remained far below the occupational dose recommended by ICRP 60. The minimum detectable dose (MDD) for environmental radiation is also discussed herein to demonstrate the reliability of TLD-100H. CONCLUSION: Recommendations were sent to the authorities of AEC-ROC to implement actions that could reduce doses at these high-dose locations to meet the ALARA principle.

Estimation and clinical verification of the effective and skin doses for pediatric and adult patients undergoing the cardiac interventional examination using five PMMA phantoms and TLD/ionization chamber technique.

BACKGROUND: Effective and skin doses gain much attention since the cardiac catheterization laboratory (CCL) is a place where both patients and medical staff are exposed to X-ray or fluoroscopy environment and gain a cumulative dose during the cardiac interventional procedure. OBJECTIVE: These doses for pediatric and adult patients undergone cardiac interventional examination using five PMMA phantoms and thermoluminescence dosimeter (TLD)/ionization chamber technique were estimated in this work with the further clinical verification. METHODS: Five PMMA phantoms (10, 30, 50, 70, and 90 kg) were customized to represent baby, child, adult female, adult male, and overweight adult (by Asian complexion standards), respectively, in accordance with the ICRU-48 report. Each phantom could be disassembled into 31 plates to insert TLD chips for measuring X-ray exposed dose or assisted with an auxiliary plate to insert high-sensitivity ionization chamber for surveying low-energy fluoroscopy dose. RESULTS: The data acquired from five phantoms were integrated into four semi-empirical formulas, in order to fit the binary quadratic form "Dose = A⋅BMI2+B⋅DAP2+C⋅BMI+ D⋅DAP+E". The latter linked the X-ray and fluoroscopy effective/skin doses, respectively, with a high coefficient of determination R2(from 0.888 to 0.986). CONCLUSIONS: The model refinement with DAP share adjustment is envisaged.

Survival rate prediction of breast cancer patients of 0-IV stages with and without radiotherapy via a revised Taylor series expansion algorithm: A population-based study in Taiwan.

BACKGROUND: The morbidity of breast cancer has continuously achieved a global topicality. In particular, during the last decade several ten thousand female adults in Taiwan have been confirmed as breast cancer patients. OBJECTIVE: To predict the survival rate of breast cancer patients at various (0-IV) stages and provide efficient assessment of proposed radiotherapy for patients. METHODS: The prediction algorithm proposed is based on the revised hit and target model and implies the application of Taylor series expansion to the population-based survey dataset. The proposed algorithm features a specific function comprising a single simple exponential term exp⁡(-α⁢t) to imply the fundamental degradation of patient's health multiplied by an additional term P⁢(α⁢t), which specifies the recovery effect of a particular therapy. RESULTS: Its calculated values for breast cancer patients who undergone radiotherapy at different stages 0-IV were {0.0029, 0.0066, 0.0178, 0.0475, 0.1785} yr-1, respectively, while those for corresponding groups of patients with no radiotherapy were assessed as {0.0072, 0.0137, 0.0264, 0.0913, 0.2425} yr-1. CONCLUSIONS: The revised algorithm successfully interpreted the breast cancer patients' survival rate at stages 0-IV and evaluated the necessity of radiotherapy for patients at various stages as well.

Semi-quantification of the minimum detectable difference of imaging quality of gamma camera SPET for four radionuclides via an innovative PMMA phantom with a V-shaped slit: interpretation of a feasibility study.

OBJECTIVE: An indigenous polymethyl metacrylate (PMMA) phantom with a V-shaped slit and a correlated technique for semi-quantifying the minimum detectable difference (MDD) of single photon emission tomography (SPET) via gamma camera scanning are proposed and validated using four radionuclides. MATERIALS AND METHODS: Radio-actinide solutions of gallium-67 (67Ga), technetium-99m (99mTc), iodine-131 (131I) and thallium-201 (201Tl) were diluted to 11c.c. and thoroughly injected into the continuous zig zag slit of the PMMA phantom. Either depth or edge of the slit between two lines of the V-shape was customized from deep or wide to change into shallow or narrow gradually. Thus, the quantified MDD could be easily evaluated, according to the revised Student's t-test evaluation. The revised Student's t-test was calculated by both full width at half maximum (FWHM) and edge width between two adjacent peaks that were acquired from the original data matrix of SPET. The derived MDD was indicated as for radionuclide, depth, width in mm: For 67Ga, 2.9, 2.13, for 99mTc, 2.5, 0.66, for 131I, 4.7, 2.38 and for 201Tl, 3.3, 2.00, respectively. RESULTS: Technetium-99m had the highest and 131I had the lowest MDD among the four radionuclides. Furthermore, two adjacent peaks of 67Ga could be easily identified with fewer counts than for 201Tl (depth, 2.9 vs. 3.3mm), but its MDD was poorer (width: 2.13 vs.2.00mm). The revised Student's t-test analysis proved to be an acceptable technique for the MDD identification. CONCLUSION: The proposed new combination of PMMA phantom with a V-slit and the revised Student's t-test proved to be instrumental in the MDD of SPET optimization analysis.

A quantitative evaluation of multiple biokinetic models using an assembled water phantom: A feasibility study.

This study examined the feasibility of quantitatively evaluating multiple biokinetic models and established the validity of the different compartment models using an assembled water phantom. Most commercialized phantoms are made to survey the imaging system since this is essential to increase the diagnostic accuracy for quality assurance. In contrast, few customized phantoms are specifically made to represent multi-compartment biokinetic models. This is because the complicated calculations as defined to solve the biokinetic models and the time-consuming verifications of the obtained solutions are impeded greatly the progress over the past decade. Nevertheless, in this work, five biokinetic models were separately defined by five groups of simultaneous differential equations to obtain the time-dependent radioactive concentration changes inside the water phantom. The water phantom was assembled by seven acrylic boxes in four different sizes, and the boxes were linked to varying combinations of hoses to signify the multiple biokinetic models from the biomedical perspective. The boxes that were connected by hoses were then regarded as a closed water loop with only one infusion and drain. 129.1±24.2 MBq of Tc-99m labeled methylene diphosphonate (MDP) solution was thoroughly infused into the water boxes before gamma scanning; then the water was replaced with de-ionized water to simulate the biological removal rate among the boxes. The water was driven by an automatic infusion pump at 6.7 c.c./min, while the biological half-life of the four different-sized boxes (64, 144, 252, and 612 c.c.) was 4.8, 10.7, 18.8, and 45.5 min, respectively. The five models of derived time-dependent concentrations for the boxes were estimated either by a self-developed program run in MATLAB or by scanning via a gamma camera facility. Either agreement or disagreement between the practical scanning and the theoretical prediction in five models was thoroughly discussed. The derived biokinetic model represented the metabolic mechanism in the human body and helped to solidify the internal circulatory system into concert with numerical verification.

Revised inverse problem algorithm-based prediction of coronary artery stenosis readings from the clinical data of patients with coronary heart diseases.

AIM: Coronary artery stenosis readings were predicted in this study on the basis of clinical data for patients with coronary heart diseases using the inverse problem algorithm. METHOD: Five factors, including age, BSA (body surface area), MAP (mean artery pressure), sugar AC (ante cibum), and LDL-C (low-density Lipoprotein-Cholesterol) were incorporated into a nonlinear first-order regression fit analysis to develop a prediction equation with sixteen terms derived via a revised inverse problem algorithm implemented through the STATISTICA default regression fit. The clinical data acquired from ninety-three coronary heart disease patients were first normalized to the same domain range of [-1 to +1], and then processed by the above algorithm to find the compromised solution of predicted coronary artery stenosis reading. The actual reading was obtained by weighting the stenosis of three major cardiac artery branches, namely, the left anterior descending artery (LAD) (wi 0.3), left circumflex artery (LCA) (wi 0.3), and right coronary artery (RCA) (wi 0.4). RESULT: The derived regression fit possessed the final loss function value Φ = 3.589 and correlation coefficient r2 = 0.892 with variance of 79.55%. Accordingly, forty-five patients with similar syndromes were analyzed to verify the prediction, which exhibited a high coincidence. The LDL-C factor was dominant for the prediction of the largest coefficient in the derived equation, whereas the age factor exhibited a minor contribution to the regression fit. The attempts to reduce the number of influence factors to 4, 3 or 2 for the model simplification yielded the results, whose low linearity and high loss function values reflected their inappropriate setting. CONCLUSION: The algorithm proved to be an effective technique for prediction of the potential diagnosis in the medical field.

Optimizing left anterior oblique (LAO) caudal imaging in coronary angiography using the Taguchi method: A phantom study with clinical verification.

The aim of this work tried to optimize the spider view of the coronary angiograph for the clinical diagnosis of cardiac artery disease by cardiologists. A qualified spider view in coronary angiography must be exactly a "quasi-spider" image, which can help to diagnose a lesion in left main coronary artery and related regions. Coronary artery phantom was placed in a 75 mm-thick acrylic box to model a 70 kg human thorax. Eighteen groups of various combinations of operating factors of the X-ray facility were organized based on a Taguchi analysis. The six factors that govern the imaging quality of X-ray were (A) whether the X-rays emitted through a filter, (B, C) the Left Anterior Oblique (LAO) and Caudal Angulation (CAU) projection angles, (D) X-ray peak voltage (kVp), (E) X-ray pulse duration and current (mAs) and (F) distance between X-ray source and intensifying plate (SID). The obtained X-ray spider view images of each group were graded to determine the optimal settings; X-ray emitted without filter, 70° LAO, 30° CAU, 110 kVp, 1.5 mAs and 108 cm of SID. X-ray imaging quality optimal result was confirmed based on a clinical diagnosis of 43 patients, to prove the effectiveness of this study.

The Population Effective Dose of Medical Computed Tomography Examinations in Taiwan for 2013.

PURPOSE: To evaluate the annual effective dose per capita attributed to computed tomography (CT) examinations in 2013 and to predict the population effective dose from 2000 to 2013 in Taiwan. METHODS: A CT examination database collected from 30 hospitals was divided into 22 procedures and classified into six regions: head, neck, chest, abdomen, pelvis, and other, respectively. The effective doses in different regions were evaluated by dose-length product (DLP) multiplied by conversion factors. RESULTS: The CT scan dose parameters were collected from 4,407 patients. For the six scanned regions, the percentages of patients scanned were: head (39.8%), neck (3.9%), chest (23.3%), abdomen (26.7%), pelvis (4.8%), and other (1.6%), respectively. The DLPs per patient (mGy·cm/patient) were head (1,071±225), neck (1,103±615), chest (724±509), abdomen (1,315±550), pelvis (1,231±620) and other (1,407±937), respectively. The number of CT examinations increased rapidly, with an average annual growth rate of 7.6%. The number of CT examinations in 2013 was 2.6 times that in 2000. The population effective dose was 0.30 mSv per capita in 2000 and increased to 0.74 mSv per capita in 2013, with an annual growth rate of 7.2%. The growth trend indicates that the effective dose will continue to rise in Taiwan. CONCLUSION: Some strategies should be applied to cope with this growth. Defining the CT dose reference level stipulated in official recommendations and encouraging the use of iterative reconstruction imaging instead of filtered back-projection imaging could be a useful method for optimizing the effective dose and image quality.

Quantitative analysis of multiple biokinetic models using a dynamic water phantom: A feasibility study.

This study analyzed multiple biokinetic models using a dynamic water phantom. The phantom was custom-made with acrylic materials to model metabolic mechanisms in the human body. It had 4 spherical chambers of different sizes, connected by 8 ditches to form a complex and adjustable water loop. One infusion and drain pole connected the chambers to an auxiliary silicon-based hose, respectively. The radio-active compound solution (TC-99m-MDP labeled) formed a sealed and static water loop inside the phantom. As clean feed water was infused to replace the original solution, the system mimicked metabolic mechanisms for data acquisition. Five cases with different water loop settings were tested and analyzed, with case settings changed by controlling valve poles located in the ditches. The phantom could also be changed from model A to model B by transferring its vertical configuration. The phantom was surveyed with a clinical gamma camera to determine the time-dependent intensity of every chamber. The recorded counts per pixel in each chamber were analyzed and normalized to compare with theoretical estimations from the MATLAB program. Every preset case was represented by uniquely defined, time-dependent, simultaneous differential equations, and a corresponding MATLAB program optimized the solutions by comparing theoretical calculations and practical measurements. A dimensionless agreement (AT) index was recommended to evaluate the comparison in each case. ATs varied from 5.6 to 48.7 over the 5 cases, indicating that this work presented an acceptable feasibility study.

Optimizing quality of digital mammographic imaging using Taguchi analysis with an ACR accreditation phantom.

This work demonstrated the improvement of the visualization of lesions by modulating the factors of an X-ray mammography imaging system using Taguchi analysis. Optimal combinations of X-ray operating factors in each group of level combination were determined using the Taguchi method, in which all factors were organized into only 18 groups, yielding analytical results with the same confidence as if each factor had been examined independently. The 4 considered operating factors of the X-ray machine were (1) anode material (target), (2) kVp, (3) mAs and (4) field of view (FOV). Each of these factors had 2 or 3 levels. Therefore, 54 (2×3×3×3 = 54) combinations were generated. The optimal settings were Rh as the target, 28 kVp, 80 mAs and 19×23 cm(2) FOV. The grade of exposed mammographic phantom image increased from the automatic exposure control (AEC) setting 70.92 to 72.00 under the optimal setting, meeting the minimum standard (70.00) set by Taiwan's Department of Health. The average glandular dose (AGD) of the exposed phantom, 0.182 cGy, was lower than that, 0.203 cGy, under the AEC setting. The Taguchi method was extremely promising for the design of imaging protocols in clinical diagnosis.