Detectability of cold tumors by xSPECT bone technology compared with hot tumors: a supine phantom study.

Detecting cold as well as hot tumors is vital for interpreting bone tumors on single-photon emission computed tomography (SPECT) images. This study aimed to visually and quantitatively demonstrate the detectability of cold tumors using xSPECT technology compared with that of hot tumors in the phantom study. Five tumors of different sizes and normal bone contained a mixture of 99mTc and K2HPO4 in a spine phantom. We acquired SPECT data using an xSPECT protocol and transverse images were reconstructed using xSPECT Bone (xB) and xSPECT Quant (xQ). Mean standardized uptake values (SUVmean) in volumes of interest (VOI) were calculated. Recovery coefficients (RCs) for each tumor site were calculated with reference to radioactive concentrations. The SUVmeans of the whole vertebral body for hot tumor bone image in cortical bone phantom reconstructed by with xB and xQ were 5.77 and 4.86 respectively. The SUVmean of xB was similar to the true value. The SUVmeans for xB and xQ reconstructed images of cold tumors were both approximately 0.16. The RC of the cold tumor on xQ images increased as the tumor diameter decreased, whereas that of xB remained almost constant regardless of the tumor diameter. In conclusion, the quantitative accuracy of detecting hot and cold tumors was higher in the xB image than in the xQ image. Moreover, the visual detectability of cold tumors was also excellent in xB images.

Evaluation of deep learning reconstruction on diffusion-weighted imaging quality and apparent diffusion coefficient using an ice-water phantom.

This study assessed the influence of deep learning reconstruction (DLR) on the quality of diffusion-weighted images (DWI) and apparent diffusion coefficient (ADC) using an ice-water phantom. An ice-water phantom with known diffusion properties (true ADC = 1.1 × 10-3 mm2/s at 0 °C) was imaged at various b-values (0, 1000, 2000, and 4000 s/mm2) using a 3 T magnetic resonance imaging scanner with slice thicknesses of 1.5 and 3.0 mm. All DWIs were reconstructed with or without DLR. ADC maps were generated using combinations of b-values 0 and 1000, 0 and 2000, and 0 and 4000 s/mm2. Based on the quantitative imaging biomarker alliance profile, the signal-to-noise ratio (SNRs) in DWIs was calculated, and the accuracy, precision, and within-subject parameter variance (wCV) of the ADCs were evaluated. DLR improved the SNR in DWIs with b-values ranging from 0 to 2000s/mm2; however, its effectiveness was diminished at 4000 s/mm2. There was no noticeable difference in the ADCs of images generated with or without implementing DLR. For a slice thickness of 1.5 mm and combined b-values of 0 and 4000 s/mm2, the ADC values were 0.97 × 10-3and 0.98 × 10-3mm2/s with and without DLR, respectively, both being lower than the true ADC value. Furthermore, DLR enhanced the precision and wCV of the ADC measurements. DLR can enhance the SNR, repeatability, and precision of ADC measurements; however, it does not improve their accuracies.

Verification of optimal conditions for the scattering correction of 123I-FP-CIT SPECT on a single-photon emission tomography system with a two-detector whole-body cadmium-zinc-telluride semiconductor detector.

To identify the optimal scattering correction for 123I-FP-CIT SPECT (DAT-SPECT) using a two-detector whole-body cadmium-zinc-telluride semiconductor detector (C-SPECT) system with a medium-energy high-resolution sensitivity (MEHRS) collimator. The C-SPECT system with the MEHRS collimator assessed image quality and quantification using a striated phantom. Different reconstruction methods and scattering correction settings were compared, including filtered back projection (FBP) and ordered subset expectation maximization (OSEM). Higher %contrast and %CV values were observed > 10% subwindow (SW) for all conditions, with no significant differences between images without scattering correction and those < 7% SW. The FBP images show a greater increase in %CV > 10% SW than the OSEM images. The specific binding ratio in the radioactivity ratio of 8:1 was higher than the true value under all conditions. The C-SPECT system with an MEHRS collimator provided accurate scattering suppression and enabled high-quality imaging for DAT-SPECT. Careful setting of the scattering correction is essential for total count accuracy.

Evaluation of Collimators in a High-Resolution, Whole-Body SPECT/CT Device with a Dual-Head Cadmium-Zinc-Telluride Detector for 123I-FP-CIT SPECT.

The study aim was to evaluate the adaptation of collimators to 123I-N-fluoropropyl-2b-carbomethoxy-3b-(4-iodophenyl)nortropane (123I-FP-CIT) dopamine transporter SPECT (DAT-SPECT) by a high-resolution whole-body SPECT/CT system with a cadmium-zinc-telluride detector (C-SPECT) in terms of image quality, quantitation, diagnostic performance, and acquisition time. Methods: Using a C-SPECT device equipped with a wide-energy, high-resolution collimator and a medium-energy, high-resolution sensitivity (MEHRS) collimator, we evaluated the image quality and quantification of DAT-SPECT for an anthropomorphic striatal phantom. Ordered-subset expectation maximization iterative reconstruction with resolution recovery, scatter, and attenuation correction was used, and the optimal collimator was determined on the basis of the contrast-to-noise ratio (CNR), percentage contrast, and specific binding ratio. The acquisition time that could be reduced using the optimal collimator was determined. The optimal collimator was used to retrospectively evaluate diagnostic accuracy via receiver-operating-characteristic analysis and specific binding ratios for 41 consecutive patients who underwent DAT-SPECT. Results: When the collimators were compared in the phantom verification, the CNR and percentage contrast were significantly higher for the MEHRS collimator than for the wide-energy high-resolution collimator (P < 0.05). There was no significant difference in the CNR between 30 and 15 min of imaging time using the MEHRS collimator. In the clinical study, the areas under the curve for acquisition times of 30 and 15 min were 0.927 and 0.906, respectively, and the diagnostic accuracies of the DAT-SPECT images did not significantly differ between the 2 times. Conclusion: The MEHRS collimator provided the best results for DAT-SPECT with C-SPECT; shorter acquisition times (<15 min) may be possible with injected activity of 167-186 MBq.

Impact of arm position on vertebral bone marrow proton density fat fraction in chemical-shift-encoded magnetic resonance imaging: a preliminary study.

Arm positions employed during magnetic resonance imaging (MRI) can affect magnetic field distribution, which may result in variability in proton density fat fraction (PDFF) measurements. This study evaluated the effect of arm position on lumbar PDFF measured using chemical-shift-encoded MRI (CSE-MRI). Fifteen healthy volunteers from a single-center underwent lumbar CSE-MRI at two different arm positions (side and elevated) using a single 3T scanner. Scans were performed twice in each position. PDFFs of the L1-L5 vertebrae were independently measured by two readers, and reader measurements were compared by calculating intraclass correlation coefficients (ICC). We compared PDFF measurements from two arm positions and from two consecutive scans using the Wilcoxon test and Bland-Altman analysis. Measurements from the two readers were in high agreement [ICC =0.999; 95% confidence interval (CI), 0.998-0.999]. No significant difference was observed between PDFFs from the first and second scans of all vertebrae for each reader (all P>0.05); however, PDFF for the elevated arm position was significantly higher than that for the side arm position (37.9-44.8% vs. 37.0-43.8%; all P<0.05), except at the L2 level by reader 2. The mean differences in PDFF measurements from the first and second scans [0.1%; 95% limits of agreement (LoA), -1.8% to 1.9%] and from the side arm and elevated arm positions (0.8%; 95% LoA, -1.6% to 3.2%) were small. In conclusion, these preliminary data suggest that different arm positions during CSE-MRI can slightly affect lumbar PDFF; however, the mean absolute differences were very small.

Variability in contrast and apparent diffusion coefficient of kiwifruit used as prostate MRI phantom: 1-week validation.

Kiwifruit has been proposed as a phantom for prostate magnetic resonance imaging (MRI) to adjust multiparametric MRI factors. This study evaluated the variability in contrasts and apparent diffusion coefficients (ADCs) via repeated scans of kiwifruits for 1 week. All scans were performed using a 3T MRI system. Six kiwifruits were prepared as phantoms. Each kiwifruit was scanned consecutively for 1 week, and T2-weighted and diffusion-weighted images were acquired. Contrasts between the peripheral placenta (PP) and central placenta (CP), and between the outer pericarp (OP) and CP were calculated. The ADCs of the PP, OP, and CP were also determined. The Friedman test with Scheffé's post hoc comparison was used to assess contrast and ADC variability over 1 week; no significant differences between the contrasts or ADCs were found. Thus, each kiwifruit phantom exhibited low variability when used as a prostate MRI phantom.

Adapting a low-count acquisition of the bone scintigraphy using deep denoising super-resolution convolutional neural network.

PURPOSE: Deep-layer learning processing may improve contrast imaging with greater precision in low-count acquisition. However, no data on noise reduction using super-resolution processing for deep-layer learning have been reported in nuclear medicine imaging. OBJECTIVES: This study was designed to evaluate the adaptability of deep denoising super-resolution convolutional neural networks (DDSRCNN) in nuclear medicine by comparing them with denoising convolutional natural networks (DnCNN), Gaussian processing, and nonlinear diffusion (NLD) processing. METHODS: In this study, 156 patients were included. Data were collected using a matrix size of 256 × 256 with a pixel size of 2.46 mm at 0.898 folds, 15% energy window at the center of the photopeak energy (140 keV), and total count of 1000 kilocounts (kct). Following the training and validation of two learning models, we created 100 images for each 20-test datum. The peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) between each image and the reference image were calculated. RESULTS: DDSRCNN showed the highest PSNR values for all total counts. Regarding SSIM, DDSRCNN had significantly higher values than the original and Gaussian. In DnCNN, false accumulation was observed as the total counts increased. Regarding PSNR and SSIM transition, the model using 100-500-kct training data was significantly higher than that using 100-kct training data. CONCLUSIONS: Edge-preserving noise reduction processing was possible, and adaptability to low-count acquisition was demonstrated using DDSRCNN. Using training data with different noise levels, DDSRCNN could learn the noise components with high accuracy and contrast improvement.

Denoising Using Noise2Void for Low-Field Magnetic Resonance Imaging: A Phantom Study.

To reduce noise for low-field magnetic resonance imaging (MRI) using Noise2Void (N2V) and to demonstrate the N2V validity. N2V is one of the denoising convolutional neural network methods that allows the training of a model without a noiseless clean image. In this study, a kiwi fruit was scanned using a 0.35 Tesla MRI system, and the image qualities at pre- and postdenoising were evaluated. Structural similarity (SSIM), signal-to-noise ratio (SNR), and contrast ratio (CR) were measured, and visual assessment of noise and sharpness was observed. Both SSIM and SNR were significantly improved using N2V (P < 0.05). CR was unchanged between pre- and postdenoising images. The results of visual assessment for noise revealed higher scores in postdenoising images than that in predenoising images. The sharpness scores of postdenoising images were high when SNR was low. N2V provides effective noise reduction and is a useful denoising technique in low-field MRI.

Optimization of cross-calibration factor for quantitative bone SPECT without attenuation and scatter correction in the lumbar spine: head-to-head comparison with attenuation and scatter correction.

OBJECTIVES: Quantitative single-photon emission computed tomography (SPECT) with computed tomography (SPECT/CT) is known to improve diagnostic performance. Although SPECT-alone systems are used widely, accurate quantitative SPECT using these systems is challenging. This study aimed to improve the accuracy of quantitative bone SPECT of the lumbar spine with the SPECT-alone system. METHODS: The cross-calibration factor (CCF) was measured using three kinds of phantoms and the optimal values were determined. The recovery coefficient with and without attenuation and scatter correction (ACSC) were compared. Bone SPECT/CT was performed on 93 consecutive patients with prostate cancer, and the standardized uptake values (SUVs) were compared using the respective CCFs. The first 60 patients were classified according to body weight, and the correlation coefficient between SUVs with and without ACSC were calculated; the slopes were defined as body weight-based coefficients (BWCs). In the remaining 33 patients, the SUV was adjusted according to BWC, and the accuracy of the adjustment was verified. RESULTS: The quantitative SPECT values obtained from the CCF using SIM2 bone phantom showed nearly accurate radioactivity concentrations, even without ACSC. The recovery coefficients with and without ACSC were similar. Unadjusted SUVs with and without ACSC were strongly correlated; however, SUVs without ACSC were significantly higher than those with ACSC (P < 0.0001). The mean difference between the SUVs with and without ACSC disappeared when the SUVs without ACSC were adjusted by BWC (P = 0.9814). CONCLUSIONS: Our cross-calibration method for quantitative bone SPECT enables interpretation with a harmonized SUV even in SPECT-alone systems.

Verification of phantom accuracy using a Monte Carlo simulation: bone scintigraphy chest phantom.

We aimed to compare the measurement and simulation data of bone scintigraphy of a chest phantom using a Monte Carlo simulation to verify the accuracy of the simulated data. The SIM2 bone phantom was enclosed using 300 kBq/mL of technetium-99 m (99mTc) to represent the bone tumor and 50 kBq/mL of 99mTc to represent normal bone. Projection data were obtained using single-photon emission computed tomography (SPECT). Simulated projection data were constructed based on CT data. The contrast ratio, recovery coefficient (RC), % coefficient variation (CV), and power spectrum density (PSD) of each part were calculated from the reconstructed data. The contrast ratio and RC were equal between the actual and simulated data. Higher % CV values were noted for soft tissue than for normal bone. The PSD was equal for all frequency band ranges. Our results prove the utility of the Monte Carlo simulation for verifying various data using phantoms.

Automatic quantification package (Hone Graph) for phantom-based image quality assessment in bone SPECT: computerized automatic classification of detectability.

OBJECTIVE: We previously developed a custom-design thoracic bone scintigraphy-specific phantom ("SIM2 bone phantom") to assess image quality in bone single-photon emission computed tomography (SPECT). We aimed to develop an automatic assessment system for imaging technology in bone SPECT and demonstrate the validity of this system. METHODS: Four spherical lesions of 13-, 17-, 22-, and 28-mm diameters in the vertebrae of SIM2 bone phantom simulating the thorax were filled with radioactivity (target-to-background ratio: 4). Dynamic SPECT acquisitions were performed for 15 min; reconstructions were performed using ordered subset expectation maximization at 3-15-min timepoints. Consequently, 216 lesions (54 SPECT images) were obtained: 120 and 96 lesions were used for software development and validation, respectively. The developed software used statistical parametric mapping to rigidly register and automatically calculate quantitative indexes (contrast-to-noise ratio, % coefficient of variance, % detectability equivalence volume, recovery coefficient, target-to-normal bone ratio, and full width at half maximum). A detectability score (DS) was used to define the four observation types (4, excellent; 3, adequate; 2, average; 1, poor) to score hot spherical lesions. The gold standard for DSs was independently classified by three experienced board-certified nuclear medicine technologists using the four observation types; thereafter, a consensus regarding the gold standard for DSs was reached. Using 120 lesions for development, decision tree analysis was performed to determine DS based on the quantitative indexes. We verified the validation of the quantitative indexes and their threshold values for automatic classification using 96 lesions for validation. RESULTS: The trends in the automatically calculated quantitative indices were consistent. Decision tree analysis produced four terminal groups; two quantitative indexes (% detectability equivalence volume and contrast-to-noise ratio) were used to classify DS. The automatically classified DSs exhibited an almost perfect agreement with the gold standard. The percentage agreement and kappa coefficient were 91.7% and 0.93, respectively, in 96 lesions for validation. CONCLUSIONS: The developed software automatically classified the detectability of hot lesions in the SIM2 bone phantom using the automatically calculated quantitative indexes, suggesting that this software could provide a means to automatically perform detectability analysis after data input that is excellent in reproducibility and accuracy.

[Validation of Simulation Codes for Nuclear Imaging Using Digital Phantoms].

Validation study of simulation codes was performed based on the measurement of a sphere phantom and the National Electrical Manufacturers Association (NEMA) body phantoms. SIMIND and Prominence Processor were used for the simulation. Both source and density maps were generated using the characteristics of 99mTc energy. A full width at half maximum (FWHM) of the sphere phantom was measured and simulated. Simulated recovery coefficient and the background count coefficient of variation were also compared with the measured values in the body phantom study. When the two simulation codes were compared with actual measurements, maximum relative errors of FWHM values were 3.6% for Prominence Processor and -10.0% for SIMIND. The maximum relative errors of relative recovery coefficients exhibited 11.8% for Prominence Processor and -2.0% for SIMIND in the body phantom study. The coefficients of variation of the SPECT count in the background were significantly different among the measurement and two simulation codes. The simulated FWHM values and recovery coefficients paralleled measured results. However, the noise characteristic differed among actual measurements and two simulation codes in the background count statistics.

Experimental evaluation of the GE NM/CT 870 CZT clinical SPECT system equipped with WEHR and MEHRS collimator.

PURPOSE: A high-energy-resolution whole-body SPECT-CT device (NM/CT 870 CZT; C-SPECT) equipped with a CZT detector has been developed and is being used clinically. A MEHRS collimator has also been developed recently, with an expected improvement in imaging accuracy using medium-energy radionuclides. The objective of this study was to compare and analyze the accuracies of the following devices: a WEHR collimator and the MEHRS collimator installed on a C-SPECT, and a NaI scintillation detector-equipped Anger-type SPECT (A-SPECT) scanner, with a LEHR and LMEGP. METHODS: A line phantom was used to measure the energy resolutions including collimator characteristics in the planar acquisition of each device using 99m Tc and 123 I. We also measured the system's sensitivity and high-contrast resolution using a lead bar phantom. We evaluated SPECT spatial resolution, high-contrast resolution, radioactivity concentration linearity, and homogeneity, using a basic performance evaluation phantom. In addition, the effect of scatter correction was evaluated by varying the sub window (SW) employed for scattering correction. RESULTS: The energy resolution with 99m Tc was 5.6% in C-SPECT with WEHR and 9.9% in A-SPECT with LEHR. Using 123I, the results were 9.1% in C-SPECT with WEHR, 5.5% in C-SPECT with MEHRS, and 10.4% in A-SPECT with LMEGP. The planar spatial resolution was similar under all conditions, but C-SPECT performed better in SPECT acquisition. High-contrast resolution was improved in C-SPECT under planar condition and SPECT. The sensitivity and homogeneity were improved by setting the SW for scattering correction to 3% of the main peak in C-SPECT. CONCLUSION: C-SPECT demonstrates excellent energy resolution and improved high-contrast resolution for each radionuclide. In addition, when using 123I, careful attention should be paid to SW for scatter correction. By setting the appropriate SW, C-SPECT with MEHRS has an excellent scattered ray removal effect, and highly homogenous imaging is possible while maintaining the high-contrast resolution.

Study of novel deformable image registration in myocardial perfusion single-photon emission computed tomography.

OBJECTIVE: In the present study, deformable image registration (DIR) technology was applied to gated myocardial perfusion single-photon emission computed tomography (G-MPS) reconstructed images in distorting all image phases. We aimed to define a new method of end-diastole compatible image registration and verify the clinical usability for any cardiac volume. METHODS: Projection images were created using the Monte Carlo simulation. All image phases were shifted to fit the end-diastole phase by applying DIR to images that were reconstructed from projection images. Defect ratios were subsequently evaluated using the simulated images of the anterior wall simulated ischemia. Furthermore, receiver operating characteristic (ROC) analysis was performed for the clinical evaluation of DIR and nongated images. To this end, normal volume and small hearts of 33 patients without coronary artery disease and 55 with single vessel disease (coronary stenosis > 70%) were evaluated. RESULTS: Defect ratio analysis for voxel values of 25-100 were 75.7-21.3 for nongated and 74.7-15.6 for DIR images. For normal cardiac volume, the area under the ROC curve was 0.901 ± 0.088 for nongated and 0.925 ± 0.073 for DIR images (P = 0.078). Finally, for small cardiac volume, the area under the ROC curve was 0.651 ± 0.124 for nongated and 0.815 ± 0.119 for DIR (P < 0.01). CONCLUSIONS: In the present study, we developed a new registration technique by applying DIR to G-MPS images. When optimal DIR conditions were applied, the resolution of G-MPS images was improved. Furthermore, the diagnostic ability was improved in cases of small cardiac volume.

Evaluation of edge-preserving and noise-reducing effects using the nonlinear diffusion method in bone single-photon emission computed tomography.

OBJECTIVES: This study aims to evaluate nonlinear diffusion (NLD) processing to smoothen images while suppressing resolution degradation in single-photon emission computed tomography (SPECT) images. Phantom data were used for NLD method optimization. The resultant optimal settings were used for NLD processing of clinical images. MATERIALS AND METHODS: Tc was used to simulate tumors and normal soft tissues. Using the data collected, images were reconstructed. Images were processed using various k values and iteration. The background region's coefficient of variation (CV) was determined, and the effects of parameters on image properties were examined. NLD-processed images with optimal parameters were compared with Butterworth (BW)-filtered and nine-point smoothing (SM)-processed images to evaluate smoothing filter properties in real and frequency space. Receiver operating characteristic curve analysis was carried out on NLD-processed and BW048-processed bone SPECT images. RESULTS: From CVs in background, with NLD, increased k value and iteration led to a low CV, indicating enhanced smoothing effect. At k=0.9, a strong noise-reducing effect with less iteration was achieved. Contrasts and recovery coefficients of NLD were the highest. The visual score for SPECT image quality was significantly higher with NLD than with BW048, BW090, and SM. In the low-frequency and high-frequency ranges, BW048, BW090, and NLD showed similar signal strengths and NLD and BW090 showed high signal strength, respectively. SM processing reduced the signal strength at all frequency ranges. On receiver operating characteristic analysis, noise reduction using NLD processing enhanced diagnostic performance than with the use of BW processing. CONCLUSION: NLD processing of bone SPECT images using optimized parameters enabled smoothing with less resolution degradation.