Akira Maebatake

Influence of Statistical Fluctuation on Reproducibility and Accuracy of SUVmax and SUVpeak: A Phantom Study

Standardized uptake values (SUVs) have been widely used in the diagnosis of malignant tumors and in clinical trials of tumor therapies as semiquantitative metrics of tumor 18F-FDG uptake. However, SUVs for small lesions are liable to errors due to partial-volume effect and statistical noise. The purpose of this study was to evaluate the reproducibility and accuracy of maximum and peak SUV (SUVmax and SUVpeak, respectively) of small lesions in phantom experiments. Methods: We used a body phantom with 6 spheres in a quarter warm background. The PET data were acquired for 1,800 s in list-mode, from which data were extracted to generate 15 PET images for each of the 60-, 90-, 120-, 150-, and 180-s scanning times. The SUVmax and SUVpeak of the hot spheres in the 1,800-s scan were used as a reference (SUVref,max and SUVref,peak). Coefficients of variation for both SUVmax and SUVpeak in hot spheres (CVmax and CVpeak) were calculated to evaluate the variability of the SUVs. On the other hand, percentage differences between SUVmax and SUVref,max and between SUVpeak and SUVref,peak were calculated for evaluation of the accuracy of SUV. We additionally examined the coefficients of variation of background activity and the percentage background variability as parameters for the physical assessment of image quality. Results: Visibility of a 10-mm-diameter hot sphere was considerably different among scan frames. The CVmax and CVpeak increased as the sphere size became smaller and as the acquisition time became shorter. SUVmax was generally overestimated as the scan time shortened and the sphere size increased. The SUVmax and SUVpeak of a 37-mm-diameter sphere for 60-s scans had average positive biases of 28.3% and 4.4%, compared with the reference. Conclusion: SUVmax was variable and overestimated as the scan time decreased and the sphere size increased. In contrast, SUVpeak was a more robust and accurate metric than SUVmax. The measurements of SUVpeak (or SUVpeak normalized to lean body mass) in addition to SUVmax are desirable for reproducible and accurate quantification in clinical situations.

An Anthropomorphic Phantom Study of Brain Dopamine Transporter SPECT Images Obtained Using Different SPECT/CT Devices and Collimators

The aim of this study was to evaluate differences in dopamine transporter SPECT images among different SPECT/CT devices and to determine the most appropriate region of interest (ROI) for semiquantitative evaluation. Methods: An anthropomorphic striatal phantom was filled with 123I solutions of different striatum-to-background radioactivity ratios. Data were acquired using 2 SPECT/CT devices equipped with low- to medium-energy general-purpose and low-energy high-resolution (LEHR) collimators. The SPECT images were reconstructed by filtered backprojection with both attenuation and scatter correction and then were analyzed using specific binding ratio (SBR). The most appropriate of 7 ROI types was determined, and we then compared the linearity and recovery of SBR among the different SPECT/CT devices and collimators. Results: The linearity of SBR was excellent for all types of ROIs. The ROI contouring the striatum based on the CT images showed the best recovery of SBR using mean activity in the striatal ROI (SBRmean) (47.8%). For this ROI, the recovery of SBRmean for SPECT/CT with a LEHR collimator with thick septa and a long hole length was 61.6%—significantly higher than that of other devices. Conclusion: The ROI contouring the striatum based on CT images was considered appropriate for evaluating dopamine transporter SPECT/CT. Among the different SPECT/CT devices, an LEHR collimator designed for 123II imaging is recommended.

Evaluation of Iterative Reconstruction Method and Attenuation Correction in Brain Dopamine Transporter SPECT Using an Anthropomorphic Striatal Phantom

Objective(s): The aim of this study was to determine the optimal reconstruction parameters for iterative reconstruction in different devices and collimators for dopamine transporter (DaT) single-photon emission computed tomography (SPECT). The results were compared between filtered back projection (FBP) and different attenuation correction (AC) methods. Methods: An anthropomorphic striatal phantom was filled with 123I solutions at different striatum-to-background radioactivity ratios. Data were acquired using two SPECT/CT devices, equipped with a low-to-medium-energy general-purpose collimator (cameras A-1 and B-1) and a low-energy high-resolution (LEHR) collimator (cameras A-2 and B-2). The SPECT images were once reconstructed by FBP using Chang’s AC and once by ordered subset expectation maximization (OSEM) using both CTAC and Chang’s AC; moreover, scatter correction was performed. OSEM on cameras A-1 and A-2 included resolution recovery (RR). The images were analyzed, using the specific binding ratio (SBR). Regions of interest for the background were placed on both frontal and occipital regions. Results: The optimal number of iterations and subsets was 10i10s on camera A-1, 10i5s on camera A-2, and 7i6s on cameras B-1 and B-2. The optimal full width at half maximum of the Gaussian filter was 2.5 times the pixel size. In the comparison between FBP and OSEM, the quality was superior on OSEM-reconstructed images, although edge artifacts were observed in cameras A-1 and A-2. The SBR recovery of OSEM was higher than that of FBP on cameras A-1 and A-2, while no significant difference was detected on cameras B-1 and B-2. Good linearity of SBR was observed in all cameras. In the comparison between Chang’s AC and CTAC, a significant correlation was observed on all cameras. The difference in the background region influenced SBR differently in Chang’s AC and CTAC on cameras A-1 and B-1. Conclusion: Iterative reconstruction improved image quality on all cameras, although edge artifacts were observed in images captured by cameras with RR. The SBR of OSEM with RR was higher than that of FBP, while the SBR of OSEM without RR was equal to that of FBP. Also, the SBR of Chang’s AC varied with different background regions in cameras A-1 and B-1.

Evaluation of the Reconstruction Parameters of Brain Dopamine Transporter SPECT Images Obtained by a Fan Beam Collimator: A Comparison with Parallel-hole Collimators

Objective(s): The purpose of this study was to examine the optimal reconstruction parameters for brain dopamine transporter SPECT images obtained with a fan beam collimator and compare the results with those obtained by using parallel-hole collimators. Methods: Data acquisition was performed using two SPECT/CT devices, namely a Symbia T6 and an Infinia Hawkeye 4 (device A and B) equipped with fan-beam (camera A-1 and B-1), low- and medium-energy general-purpose (camera A-2 and B-2), and low-energy high-resolution (camera A-3 and B-3) collimators. The SPECT images were reconstructed using filtered back projection (FBP) with Chang’s attenuation correction. However, the scatter correction was not performed. A pool phantom and a three-dimensional (3D) brain phantom were filled with 123I solution to examine the reconstruction parameters. The optimal attenuation coefficient was based on the visual assessment of the profile curve, coefficient of variation (CV) [%], and summed difference from the reference activity of the pool phantom. The optimal Butterworth filter for the 3D-brain phantom was also determined based on a visual assessment. The anthropomorphic striatal phantom was filled with 123I solution at striatum-to-background radioactivity ratios of 8, 6, 4, and 3. The specific binding ratio (SBR) of the striatum (calculated by the CT method) was used to compare the results with those of the parallel-hole collimators. Results: The optimal attenuation coefficients were 0.09, 0.11, 0.05, 0.05, 0.11, and, 0.10 cm-1 for cameras A-1, A-2, A-3, B-1, B-2, and B-3, respectively. The cutoff frequencies of the Butterworth filter were 0.32, 0.40, and 0.36 cycles/cm for camera A, and 0.46, 0.44, and 0.44 cycles/cm for camera B, respectively. The recovery rates of the SBRmean with camera A were 51.2%, 49.4%, and 45.6%, respectively. The difference was not statistically significant. The recovery rates of the SBR with camera B were 59.2%, 50.7%, and 50.8%, respectively. Camera B-1 showed significantly high SBR values. Conclusion: As the findings indicated, the optimal reconstruction parameters differed according to the devices and collimators. The fan beam collimator was found to provide promising results with each device.

[Harmonization of Standardized Uptake Value among Different Generation PET/ CT Cameras Based on a Phantom Experiment -Utility of SUV(peak)].

Standardized uptake value (SUV) has been widely used as a semi-quantitative metric of uptake in FDGPET/ CT for diagnosis of malignant tumors and evaluation of tumor therapies. However, the SUV depends on various factors including PET/CT scanner specifications and reconstruction parameters. The purpose of this study is to harmonize the SUV among two PET/CT models of different generation: two units of Discovery ST Elite Performance(DSTEP) and Discovery 690 (D690) PET/CT scanners. The NEMA body phantom filled with 18F solution was scanned for 30 minutes in list-mode. The D690 PET images were reconstructed with OSEM, OSEM+TOF, and OSEM+PSF. Gaussian post-filters of 4-9 mm FWHM were applied to find the parameters that provides harmonized SUV. We determined the SUV-harmonized parameter for each reconstruction algorithm. Then, the 10 PET images simulating clinical scan conditions were respectively generated to evaluate the bias and variability of SUV(max) and SUV(peak). The SUV(max) strongly depended not only on spatial resolution but also on image noise. On the other hand, the SUV(peak) was a robust metric to image noise level. TOF improved the variability of SUV(max) and SUV(peak). Thus, we were able to harmonize the spatial resolution using SUV(peak) based on the phantom study. Because SUV(max) was also strongly affected by image noise, sufficient count statistics is essential for SUV(max) harmonization. We recommended that TOF reconstruction and SUV(peak) metric should be used to harmonize SUV.