Hideo Onishi

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

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.

A 3-Dimensional Mathematic Cylinder Phantom for the Evaluation of the Fundamental Performance of SPECT

Degradation of SPECT images results from various physical factors. The primary aim of this study was the development of a digital phantom for use in the characterization of factors that contribute to image degradation in clinical SPECT studies. Methods: A 3-dimensional mathematic cylinder (3D-MAC) phantom was devised and developed. The phantom (200 mm in diameter and 200 mm long) comprised 3 imbedded stacks of five 30-mm-long cylinders (diameters, 4, 10, 20, 40, and 60 mm). In simulations, the 3 stacks and the background were assigned radioisotope concentrations and attenuation coefficients. SPECT projection datasets that included Compton scattering effects, photoelectric effects, and γ-camera models were generated using the electron γ-shower Monte Carlo simulation program. Collimator parameters, detector resolution, total photons acquired, number of projections acquired, and radius of rotation were varied in simulations. The projection data were formatted in Digital Imaging and Communications in Medicine (DICOM) and imported to and reconstructed using commercial reconstruction software on clinical SPECT workstations. Results: Using the 3D-MAC phantom, we validated that contrast depended on size of region of interest (ROI) and was overestimated when the ROI was small. The low-energy general-purpose collimator caused a greater partial-volume effect than did the low-energy high-resolution collimator, and contrast in the cold region was higher using the filtered backprojection algorithm than using the ordered-subset expectation maximization algorithm in the SPECT images. We used imported DICOM projection data and reconstructed these data using vendor software; in addition, we validated reconstructed images. Conclusion: The devised and developed 3D-MAC SPECT phantom is useful for the characterization of various physical factors, contrasts, partial-volume effects, reconstruction algorithms, and such, that contribute to image degradation in clinical SPECT studies.

Comparative study of anatomical normalization errors in SPM and 3D-SSP using digital brain phantom

ObjectiveIn single photon emission computed tomography (SPECT) cerebral blood flow studies, two major algorithms are widely used statistical parametric mapping (SPM) and three-dimensional stereotactic surface projections (3D-SSP). The aim of this study is to compare an SPM algorithm-based easy Z score imaging system (eZIS) and a 3D-SSP system in the errors of anatomical standardization using 3D-digital brain phantom images.MethodsWe developed a 3D-brain digital phantom based on MR images to simulate the effects of head tilt, perfusion defective region size, and count value reduction rate on the SPECT images. This digital phantom was used to compare the errors of anatomical standardization by the eZIS and the 3D-SSP algorithms.ResultsWhile the eZIS allowed accurate standardization of the images of the phantom simulating a head in rotation, lateroflexion, anteflexion, or retroflexion without angle dependency, the standardization by 3D-SSP was not accurate enough at approximately 25° or more head tilt. When the simulated head contained perfusion defective regions, one of the 3D-SSP images showed an error of 6.9% from the true value. Meanwhile, one of the eZIS images showed an error as large as 63.4%, revealing a significant underestimation.ConclusionWhen required to evaluate regions with decreased perfusion due to such causes as hemodynamic cerebral ischemia, the 3D-SSP is desirable. In a statistical image analysis, we must reconfirm the image after anatomical standardization by all means.

Does applying resolution recovery to normal databases confer an advantage over conventional 3D-stereotactic surface projection techniques?

We evaluated a novel normal database (NDB) generated using single photon emission computed tomography (SPECT) data obtained from healthy brains by using a SPECT/CT system, analyzed using a resolution recovery (RR) technique applied to the three-dimensional stereotactic surface projection (3D-SSP) technique. We used a three-dimensional ordered subset expectation maximization method (3D-OSEM) with applied scatter correction (SC), attenuation correction, and RR to reconstruct the data. We verified the accuracy of the novel NDB’s values (Z, extent, and error scores), and compared the novel NDB to the 3D-SSP technique by using simulated misery perfusion-related patient data from a conventional NDB. In addition, Z, extent, and error scores at the precuneus, cuneus, and posterior cingulate were compared under different reconstruction conditions by using the patient data. In the simulation, Z scores decreased when using the novel NDB corrected using computed tomography-based attenuation correction (CTAC), SC, and RR. The extent scores of the posterior cingulate increased using the novel NDB, relative to the other NDBs. The error score with the novel NDB without RR decreased by 15% compared to that of the conventional NDB. Z scores generated from patient data decreased in the novel NDB with RR. The extent scores tended to decrease in the novel NDB with RR. The extent scores in the novel NDB with RR improved at the posterior cingulate, compared to the scores with the other NDBs. However, applying RR to the novel NDB conferred no advantage because the cut-off of the current Z score must be reconsidered when using the additive RR technique.

Development of Realistic Striatal Digital Brain (SDB) Phantom for 123 I-FP-CIT SPECT and Effect on Ventricle in the Brain for Semi-quantitative Index of Specific Binding Ratio

PURPOSE This study aimed at developing the realistic striatal digital brain (SDB) phantom and to assess specific binding ratio (SBR) for ventricular effect in the 123I-FP-CIT SPECT imaging. METHODS SDB phantom was constructed in to four segments (striatum, ventricle, brain parenchyma, and skull bone) using Percentile method and other image processing in the T2-weighted MR images. The reference image was converted into 128×128 matrixes to align MR images with SPECT images. The process image was reconstructed with projection data sets generated from reference images additive blurring, attenuation, scatter, and statically noise. The SDB phantom was evaluated to find the accuracy of calculated SBR and to find the effect of SBR with/without ventricular counts with the reference and process images. RESULTS We developed and investigated the utility of the SDB phantom in the 123I-FP-CIT SPECT clinical study. The true value of SBR was just marched to calculate SBR from reference and process images. The SBR was underestimated 58.0% with ventricular counts in reference image, however, was underestimated 162% with ventricular counts in process images. CONCLUSION The SDB phantom provides an extremely convenient tool for discovering basic properties of 123I-FP-CIT SPECT clinical study image. It was suggested that the SBR was susceptible to ventricle.

Validation of Computed Tomography-based Attenuation Correction of Deviation between Theoretical and Actual Values in Four Computed Tomography Scanners.

Objective(s): In this study, we aimed to validate the accuracy of computed tomography-based attenuation correction (CTAC), using the bilinear scaling method. Methods: The measured attenuation coefficient (μm) was compared to the theoretical attenuation coefficient (μt), using four different CT scanners and an RMI 467 phantom. The effective energy of CT beam X-rays was calculated, using the aluminum half-value layer method and was used in conjunction with an attenuation coefficient map to convert the CT numbers to μm values for the photon energy of 140 keV. We measured the CT number of RMI 467 phantom for each of the four scanners and compared the μm and μt values for the effective energies of CT beam X-rays, effective atomic numbers, and physical densities. Results: The μm values for CT beam X-rays with low effective energies decreased in high construction elements, compared with CT beam X-rays of high effective energies. As the physical density increased, the μm values elevated linearly. Compared with other scanners, the μm values obtained from the scanner with CT beam X-rays of maximal effective energy increased once the effective atomic number exceeded 10.00. The μm value of soft tissue was equivalent to the μt value. However, the ratios of maximal difference between μm and μt values were 25.4% (lung tissue) and 21.5% (bone tissue), respectively. Additionally, the maximal difference in μm values was 6.0% in the bone tissue for each scanner. Conclusion: The bilinear scaling method could accurately convert CT numbers to μ values in soft tissues.

Novel Index (Hepatic Receptor: IHR) to Evaluate Hepatic Functional Reserve Using (99m)Tc-GSA Scintigraphy.

PURPOSE This study aimed to evaluate the novel index of hepatic receptor (IHR) on the regression analysis derived from time activity curve of the liver for hepatic functional reserve. METHODS Sixty patients had undergone (99m)Tc-galactosyl serum albumin ((99m)Tc-GSA) scintigraphy in the retrospective clinical study. Time activity curves for liver were obtained by region of interest (ROI) on the whole liver. A novel hepatic functional predictor was calculated with multiple regression analysis of time activity curves. In the multiple regression function, the objective variables were the indocyanine green (ICG) retention rate at 15 min, and the explanatory variables were the liver counts in 3-min intervals until end from beginning. Then, this result was defined by IHR, and we analyzed the correlation between IHR and ICG, uptake ratio of the heart at 15 minutes to that at 3 minutes (HH15), uptake ratio of the liver to the liver plus heart at 15 minutes (LHL15), and index of convexity (IOC). RESULTS Regression function of IHR was derived as follows: IHR=0.025×L(6)-0.052×L(12)+0.027×L(27). The multiple regression analysis indicated that liver counts at 6 min, 12 min, and 27 min were significantly related to objective variables. The correlation coefficient between IHR and ICG was 0.774, and the correlation coefficient between ICG and conventional indices (HH15, LHL15, and IOC) were 0.837, 0.773, and 0.793, respectively. IHR had good correlation with HH15, LHL15, and IOC. CONCLUSIONS The finding results suggested that IHR would provide clinical benefit for hepatic functional assessment in the (99m)Tc-GSA scintigraphy.

Evaluation of optimal threshold of Z score map for statistical brain image analysis

PURPOSE Aim of this study was to investigate optimal threshold of Z score when evaluating statistics image of Alzheimers disease visually. METHOD We classified 53 clinical patients in control and target group, and evaluated the distribution of Z score calculated with statistical brain image analysis for magnetic resonance and perfusion single photon emission computed tomography (SPECT). The optimal Z score threshold was determined from statistical significance that compared previously mentioned groups. RESULTS Target group was able to classify significantly Z score at 1.25 from control group in wide region of parietal lobe with statistical brain image analysis for perfusion SPECT. DISCUSSION The optimal threshold is equal or less than 2.0, in the case of Z score variance is close to the standard normal distribution. In contrast, the threshold is over 2.0 in the case of Z score variance is more than 1.0, and then by using ordinary threshold 2.0, it cannot point out abnormality.

[Validation of an optimal analysis method and reproducibility to calculate the heart-to-mediastinum ratio and washout rate in the iodine-123-labeled metaiodobenzylguanidine myocardial scintigraphy].

PURPOSE The aim of this study was to investigate an appropriate analysis method and multicenter reproducibility of heart-to-mediastinum ratio (H/M) and washout rate (WR) in iodine-123-labeled metaiodobenzylguanidine (123I-MIBG) myocardial scintigraphy with a phantom. METHODS We evaluated the optimal region of interest (ROI) setting method about the mediastinum and heart by varying the position and shape of the ROI. The mathematical method was changed to a combination of decay time correction (DTC) and background correction (BC). We evaluated the reproducibility of the H/M and WR between institutions. RESULT H/M decreased to 23.49% and WR increased to 20.68% by changing the mediastinum ROI position from upper to lower. H/M increased to 26.03% by changing the heart ROI position from base to apex. H/M decreased to 38.36% with BC, and WR was reduced up to 48.51% with DTC. Reproducibility of the H/M and WR between institutions was improved by performing optimization of the ROI setting and unification of the mathematical method. DISCUSSION The position of the mediastinum ROI should be set on the upper mediastinum. The position of the heart ROI should be set on the apex of the heart. WR should be calculated with DTC and BC. Our results suggest that the reproducibility of the H/M and WR between institutions was improved by performing optimization of the ROI setting and unification of the mathematical method.

Impact of quantitative index derived from 123I-FP-CIT-SPECT on reconstruction with correction methods evaluated using a 3D-striatum digital brain phantom

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.