BackgroundAlthough quantitative analysis using standardized uptake value (SUV) becomes realistic in clinical single-photon emission computed tomography/computed tomography (SPECT/CT) imaging, reconstruction parameter settings can deliver different quantitative results among different SPECT/CT systems. This study aims to propose a use of the digital reference object (DRO), which is a National Electrical Manufacturers Association (NEMA) phantom-like object developed by the Quantitative Imaging Biomarker Alliance (QIBA) fluorodeoxyglucose-positron emission tomography technical committee, for the purpose of harmonizing SUVs in Tc-99m SPECT/CT imaging.MethodsThe NEMA body phantom with determined Tc-99m concentration was scanned with the four state-of-the-art SPECT/CT systems. SPECT data were reconstructed using different numbers of the product of subset and iteration numbers (SI) and the width of 3D Gaussian filter (3DGF). The mean (SUVmean), maximal (SUVmax), and peak (SUVpeak) SUVs for six hot spheres (10, 13, 17, 22, 28, and 37 mm) were measured after converting SPECT count into SUV using Becquerel calibration factor. DRO smoothed by 3DGF with a FWHM of 17 mm (DRO17 mm) was generated, and the corresponding SUVs were measured. The reconstruction condition to yield the lowest root mean square error (RMSE) of SUVmeans for all the spheres between DRO17 mm and actual phantom images was determined as the harmonized condition for each SPECT/CT scanner. Then, inter-scanner variability in all quantitative metrics was measured before (i.e., according to the manufacturers’ recommendation or the policies of their own departments) and after harmonization.ResultsRMSE was lowest in the following reconstruction conditions: SI of 100 and 3DGF of 13 mm for Brightview XCT, SI of 160 and 3DGF of 3 pixels for Discovery NM/CT, SI of 60 and 3DGF of 2 pixels for Infinia, and SI of 140 and 3DGF of 15 mm for Symbia. In pre-harmonized conditions, coefficient of variations (COVs) among the SPECT/CT systems were greater than 10% for all quantitative metrics in three of the spheres, SUVmax and SUVmean, in one of the spheres. In contrast, all metrics except SUVmax in the 17-mm sphere yielded less than 10% of COVs after harmonization.ConclusionsOur proposed method clearly reduced inter-scanner variability in SUVs. A digital phantom developed by QIBA would be useful for harmonizing SUVs in multicenter trials using SPECT/CT.

Resting-state functional connectivity is one promising biomarker for Alzheimer's disease (AD) and mild cognitive impairment (MCI). However, it is still not known how accurately network analysis identifies AD and MCI across multiple sites. In this study, we examined whether resting-state functional connectivity data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) could identify patients with AD and MCI at our site. We implemented an index based on the functional connectivity frequency distribution, and compared performance for AD and MCI identification with multi-voxel pattern analysis. The multi-voxel pattern analysis using a connectivity map of the default mode network showed good performance, with an accuracy of 81.9% for AD and MCI identification within the ADNI, but the classification model obtained from the ADNI failed to classify AD, MCI, and healthy elderly adults from our site, with an accuracy of only 43.1%. In contrast, a functional connectivity index of the medial temporal lobe based on the frequency distribution showed moderate performance, with an accuracy of 76.5 - 80.3% for AD identification within the ADNI. The performance of this index was similar for our data, with an accuracy of 73.9 - 82.6%. The frequency distribution-based index of functional connectivity could be a good biomarker for AD across multiple sites.

We evaluated quantitation accuracy of the specific binding ratio (SBR) and specific uptake ratio (SUR) of dopamine transporter for various correction methods by using a novel three-dimensional striatum digital brain (3D-SDB) phantom comprised of segments containing the striatum, ventricle, brain parenchyma, and skull bone extracted from T2-weighted MR images. A process image was reconstructed by projection data sets with blurring, scatter, and attenuation from 3D-SDB phantom data. A 3D-iterative reconstruction algorithm was used without correction (OSEM), or with scatter (SC), attenuation (AC), AC + SC (ACSC), AC + resolution recovery (RR; ACRR), SC + RR (SCRR), AC + SC + RR (ACSCRR), AC + SC + RR + partial volume (PVC; ACSCRRP), and AC + SC + RR + PVC + ventricle (ACSCRRPV). Data were then quantified using SBR and SUR. Differences between measured and true SBR values were (in order): ACSCRR< ACSC < ACRR < AC < SCRR < SC < OSEM: the maximal error was 45.3%. The trend of differences between measured and true SUR values was similar to that of SBR; maximal error was 65%. The ACSCRR-corrected SUR, which was closer to the true value, was underestimated by 30.4%. However, the ACSCRRP-corrected SUR was underestimated by a maximum of 22.5%. The SUR in the ACSCRRPV was underestimated by 6.2%. The accuracy of quantitation was improved using various types of compensation and correction. Accuracy improved more for the SUR when PVC and ventricle correction were added.

In the dopamine transporter scintigraphy there are two quantitative analysis softwares, DaTView and DaTQUANT. The quantitative value of both software has to be treated independently because there is a difference between them in the point of how to set the region of interest on the striatum and the background, calculation formula of quantitation. And also DaTQUANT has a capability of performing anatomical standardization which DaTView does not have. The aim of this study was to evaluate the accuracy of registration on DaTQUANT using a phantom, and to evaluate the correlation between the quantitative values between DaTView and DaTQUANT using clinical data. As a result, the accuracy of registration was acceptable. Regardless of the degree of accumulation in the striatum, there was a high correlation to each analysis software (r>0.85).

SummaryPurpose: 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 halflife. 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 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.