The TLD-100H readout system performance under various radioactive I-131 exposure doses was optimized by four key factors via the revised Taguchi dynamic quality loss function. Taguchi dynamic analysis and the orthogonal array reorganizing the essential factors are crucial for the optimization of the thermoluminescent dosimeter (TLD) readout system given strict criteria of multiple irradiated environments and long-term exposure for calibrated TLDs. Accordingly, 96 TLD-100H chips were selected and randomly categorized into three batches with eight groups (four TLD chips in each group). Four factors, namely (1) initial temperature, (2) heating rate, (3) maximal temperature, and (4) TLD preheat time before reading were organized into eight combinations according to Taguchi suggestion, whereas each factor was preset at two levels. All 96 [Formula: see text] chips were put in three concentric circles with 30, 60, and 90 cm radii for 48 h, surrounding the radioactive 150[Formula: see text]mCi ([Formula: see text][Formula: see text]MBq) I-131 capsule and exposed to the cumulative doses of 88.2, 18.6, and 8.6[Formula: see text]mSv for the respective radii, accordingly. The TLD readings obtained from each group were analyzed to derive the sensitivity, coincidence, and reproducibility, then those were reorganized to draw four fish-bone-plots for the optimization. The optimal option for the TLD readout system implied the combination of A1 (a [Formula: see text]C initial temperature), B1 (a [Formula: see text]C/s heating rate), C1 (a [Formula: see text]C maximal temperature), and D2 (a 15[Formula: see text]s preheat time), which was further verified by the follow-up measurements. The dominant factors were A (initial temperature) and B (heating rate), whereas C (maximal temperature) and D (preheat time) were minor and provided negligible contributions to the system performance optimization.
Biokinetic model of Tc-99m MIBI for eight patients undergone myocardial perfusion examination was studied using gamma camera and MATLAB program. A six-compartment model was adopted to interpret the metabolic mechanism of each patient. Within the model framework, the respective set of simultaneous differential equations was solved by a self-developed program run in MATLAB. The experimental results exhibited a good fit with the theoretical predictions via the model. The average biological half-lives of body fluid, heart, thyroid, liver, GI Tract and remainder were assessed as [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text][Formula: see text]h, respectively. A dimensionless AT index of disagreement between the experimental data and MATLAB optimal solution was proposed of validating the applied acquisition system and analytical method feasibility. An AT of zero implies a perfect agreement between the theoretical and empirical results, while averages of the derived AT were fluctuated from 3 [Formula: see text] 2 to [Formula: see text] for five compartments. The proposed refined equation estimated the internal dose from gamma-ray as [Formula: see text][Formula: see text]mSv for eight patients according to a fast screening method, which defined human body as a spherical ball to simplify the calculation in reality. The proposed MATLAB-based fitting of in-vivo data with the theoretical results was instrumental for assessing the radiation dose received by the Tc-99m MIBI scan participants.
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