[Evaluation of Measurement Accuracy and Inter-institutional Comparison for Dose Calibrators].

PURPOSE: The aim of this study was to validate the reliability of dose calibrators for measuring the radioactivity of several radioisotopes in multi-institution. METHODS: We evaluated the measurement accuracy of dose calibrators using a commercially available source ((67) Ga, (99m) Tc, (123) I, (201) TL). Nine dose calibrators (five models) in seven institutions were performed in this study. Each source was measured at least 3 times a day over a period of 4 half-life. Linearity of concentration (%error value) and percent difference values (%diff measurement) between measured and estimated radioactivity were calculated to evaluate the measurement accuracy. In addition, difference among institutions (%diff institution) was evaluated by the error values between measured and reference institution values. RESULTS: Good linearity of concentration was found between measured and estimated radioactivity in (99m)Tc and (123)I. However, %error value was increased in (67)Ga and (201)TL (maximum 19.3%). %diff measurements were 1.9 ± 0.3% for (67)Ga, -0.9 ± 0.3% for (99m)Tc, 2.2 ± 0.4% for (123)I, and -0.7 ± 0.3% for (201)TL, respectively. Although there were no clear differences in six institutions, %diff institution in one institution tended to be higher than that obtained in other institutions. CONCLUSIONS: Our results indicated that measurement accuracy of nine dose calibrators (five models) was relatively stable. However, difference of measured values tended to be higher in a part of institution and source. It is important to perform quality assurance and quality control for dose calibrator using traceable source.

Reduced Tyk2 gene expression in ß-cells due to natural mutation determines susceptibility to virus-induced diabetes.

Accumulating evidence suggests that viruses play an important role in the development of diabetes. Although the diabetogenic encephalomyocarditis strain D virus induces diabetes in restricted lines of inbred mice, the susceptibility genes to virus-induced diabetes have not been identified. We report here that novel Tyrosine kinase 2 (Tyk2) gene mutations are present in virus-induced diabetes-sensitive SJL and SWR mice. Mice carrying the mutant Tyk2 gene on the virus-resistant C57BL/6 background are highly sensitive to virus-induced diabetes. Tyk2 gene expression is strongly reduced in Tyk2-mutant mice, associated with low Tyk2 promoter activity, and leads to decreased expression of interferon-inducible genes, resulting in significantly compromised antiviral response. Tyk2-mutant pancreatic ß-cells are unresponsive even to high dose of Type I interferon. Reversal of virus-induced diabetes could be achieved by ß-cell-specific Tyk2 gene expression. Thus, reduced Tyk2 gene expression in pancreatic ß-cells due to natural mutation is responsible for susceptibility to virus-induced diabetes.

Evaluation of a novel normal database with matched SPECT systems and optimal pre-filter parameters for 3D-SSP.

PURPOSE: A normal perfusion database (NDB) is imperative for the statistical imaging of brain function. This study validates a novel NDB created under the same injection dose and acquisition conditions for three gamma camera systems and evaluates optimal pre-filter parameters for three-dimensional stereotactic surface projections (3D-SSPs). METHOD: We compared a novel NDB that matched the databases in each of three vendor gamma camera systems with a conventionally constructed NDB (conventional NDB) and a NDB constructed in-house for 3D-SSP. We generated hypoperfused regions where pre-specified volumes were simulated for various areas in SPECT images. The properties of each NDB were evaluated based on the distribution of the standard deviation (SD). Abnormal accumulation regions were validated using Z, extent, and artifactual scores. Detection error was used to evaluate the optimal Butterworth pre-filter cutoff frequency with the perfusion defect rate (PDR) in 3D-SSP. RESULTS: The SD distribution was the same in the novel NDB and in the NDB constructed in-house, and the SD of the peak distribution was 0.08-0.07. The Z and extent scores of the novel DB and the NDB constructed in-house were similar, but increased along with the artifactual scores when using the conventional NDB. Many artifacts appeared in the Z score map when using the conventional NDB. The detection error deviated from the actual value by -1.3% at a cutoff frequency of 0.58 cycles/cm and a PDR of 30%, which was the lowest. The cutoff frequency became lower or higher, and the low-perfusion defect rate increased according to the increasing detection error. The optimal cutoff frequency was between 0.52 and 0.58 cycles/cm. CONCLUSIONS: We generated a novel NDB according to the individual devices and compared it with a conventional and a NDB constructed in-house. The Z and extent scores were essentially equal when using the novel DB and the NDB constructed in-house, but considerably differed when using the conventional NDB. The optimal cutoff frequency of the Butterworth filter evaluated from the detection error was in the range of 0.52-0.58 cycles/cm. The detection error increased the perfusion defect rate by <15% and this was undetectable in 3D-SSP. The next step will be to improve the accuracy of the extent of abnormal regions and the sensitivity of the Z score using a novel NDB constructed according to the individual devices.

Effect of prefiltering cutoff frequency and scatter and attenuation corrections during normal database creation for statistical imaging analysis of the brain.

UNLABELLED: The present study aimed to quantify which image reconstruction conditions for normal databases and patients affect statistical brain function image analysis using an easy z score imaging system (eZIS) and 3-dimensional stereotactic surface projections (3D-SSP). METHODS: We constructed normal databases based on cerebral perfusion SPECT images obtained from 15 healthy individuals. Each normal database was created with the following unique conditions: a variable Butterworth filter cutoff frequency (fc) with and without scatter and attenuation corrections. To simulate patient data, we selected 1 dataset from among those created from the 15 healthy individuals. The simulated patient data were designed to include hypoperfused regions with prespecified volumes. Using 3D-SSP and eZIS, we compared how the above processing conditions affect the distribution of SD in normal database images and the accuracy of detecting specific regions. RESULTS: The SD for the SPECT images increased with the fc of the Butterworth filter. The z score decreased by 30% for 3D-SSP and by 14% for eZIS, indicating that the prefilter significantly affected z scores. The accuracy of detecting the hypoperfused regions was significantly influenced by the fc; 3D-SSP decreased by 7.51%, and eZIS decreased by 55.34%. The detection accuracy with eZIS, which involves a smoothing process, was significantly decreased. The error of the area of hypoperfused regions was minimized when normal database and patient data were both corrected for scatter and attenuation. CONCLUSION: When the reconstruction conditions (fc, scatter correction, and attenuation correction) at normal database creation differed from those at patient data processing, the z scores widely underestimated the analytic results because the SD varied according to the reconstruction conditions. The accuracy of brain function image analysis can be improved by considering the reconstruction conditions and correcting for scatter and attenuation on both normal databases and patient data.