SPECT Camera Research Articles

Technological Advances in SPECT and SPECT/CT Imaging.

Single photon emission tomography/computed tomography (SPECT/CT) is a mature imaging technology with a dynamic role in the diagnosis and monitoring of a wide array of diseases. This paper reviews the technological advances, clinical impact, and future directions of SPECT and SPECT/CT imaging. The focus of this review is on signal amplifier devices, detector materials, camera head and collimator designs, image reconstruction techniques, and quantitative methods. Bulky photomultiplier tubes (PMTs) are being replaced by position-sensitive PMTs (PSPMTs), avalanche photodiodes (APDs), and silicon PMs to achieve higher detection efficiency and improved energy resolution and spatial resolution. Most recently, new SPECT cameras have been designed for cardiac imaging. The new design involves using specialised collimators in conjunction with conventional sodium iodide detectors (NaI(Tl)) or an L-shaped camera head, which utilises semiconductor detector materials such as CdZnTe (CZT: cadmium-zinc-telluride). The clinical benefits of the new design include shorter scanning times, improved image quality, enhanced patient comfort, reduced claustrophobic effects, and decreased overall size, particularly in specialised clinical centres. These noticeable improvements are also attributed to the implementation of resolution-recovery iterative reconstructions. Immense efforts have been made to establish SPECT and SPECT/CT imaging as quantitative tools by incorporating camera-specific modelling. Moreover, this review includes clinical examples in oncology, neurology, cardiology, musculoskeletal, and infection, demonstrating the impact of these advancements on clinical practice in radiology and molecular imaging departments.

Characterization of accurate 3D collimator-detector response function for single- and multi-lofthole collimated SPECT cameras.

Collimator-detector response function (CDRF) of a SPECT scanner refers to the image generated from a point source of activity. This research aims to characterize the CDRF of a breast-dedicated SPECT imager equipped with a lofthole collimator using GATE Monte Carlo simulation. To do so, a cylindrical multi-lofthole collimation system with lofthole apertures dedicated to breast imaging was modeled using the GATE Monte Carlo simulator. The dependency of the CDRF on the source-to-collimator distance of a single-lofthole as well as 8-lofthole collimations was assessed and then compared. In addition, the 3D-sensitivity map of the 8-lofthole collimation was derived. Finally, fair comparisons were conducted between the response of the 8-lofthole collimator and that of an 8-pinhole and also existing analytical derivations. In all cases, a data acquisition period of 5.0 min with an in-air 99mTc point source was considered. For the single-lofthole collimator, 4.5 times increasing the magnification factor leads to a 16- and twofold improvement in the sensitivity and spatial resolution, respectively. In the single-lofthole collimator, the resolution and sensitivity are degraded as the source-to-aperture distance increases. For the cylindrical 8-lofthole collimator, the findings confirm that CDRF strongly depends on source-to-aperture distance and angle of photon incidence. For a 30 mm in-plane offset point, a 25% increase in sensitivity is observed compared to that of the center of the FOV. Increasing the angle from 0 to 34 results in a 50% reduction in sensitivity. Furthermore, the findings illustrate that spatial resolution follows a quadratic function as where d is an offset along the x-, y-, and z-axis, and R0 is the spatial resolution at the center of the FOV. In conclusion, both spatial resolution and sensitivity of the lofthole collimation are considerably angle- and offset-dependent within the FOV of single- and multi-lofthole collimated SPECT imagers.

Kidney dynamic SPECT acquisition on a CZT swiveling-detector ring camera: an in vivo pilot study

BackgroundLarge field of view CZT SPECT cameras with a ring geometry are available for some years now. Thanks to their good sensitivity and high temporal resolution, general dynamic SPECT imaging may be performed more easily, without resorting to dedicated systems. To evaluate the dynamic SPECT imaging by such cameras, we have performed an in vivo pilot study to analyze the kidney function of a pig and compare the results to standard dynamic planar imaging by a conventional gamma camera.MethodsA 7-week-old (12 kg) female Landrace pig was injected with [99mTc]Tc-MAG3 and a 30 min dynamic SPECT acquisition of the kidneys was performed on a CZT ring camera. A fast SPECT/CT was acquired with the same camera immediately after the dynamic SPECT, without moving the pig, and used for attenuation correction and drawing regions of interest. The next day the same pig underwent a dynamic planar imaging of the kidneys by a conventional 2-head gamma camera. The dynamic SPECT acquisition was reconstructed using a MLEM algorithm with up to 20 iterations, with and without attenuation correction. Time-activity curves of the total counts of each kidney were extracted from 2D and 3D dynamic images. An adapted 2-compartment model was derived to fit the data points and extract physiological parameters. Comparison of these parameters was performed between the different reconstructions and acquisitions.ResultsTime-activity curves were nicely fitted with the 2-compartment model taking into account the anesthesia and bladder filling. Kidney physiological parameters were found in agreement with literature values. Good agreement of these parameters was obtained for the right kidney between dynamic SPECT and planar imaging. Regional analysis of the kidneys can be performed in the case of the dynamic SPECT imaging and provided good agreement with the whole kidney results.ConclusionsDynamic SPECT imaging is feasible with CZT swiveling-detector ring cameras and provides results in agreement with dynamic planar imaging by conventional gamma cameras. Regional analysis of organs uptake and clearance becomes possible. Further studies are required regarding the optimization of acquisition and reconstruction parameters to improve image quality and enable absolute quantification.

Evaluation of Approaches for the Assessment of HER2 Expression in Breast Cancer by Radionuclide Imaging Using the Scaffold Protein [99mTc]Tc-ADAPT6.

Due to its small size and high affinity binding, the engineered scaffold protein ADAPT6 is a promising targeting probe for radionuclide imaging of human epidermal growth factor receptor type 2 (HER2). In a Phase I clinical trial, [99mTc]Tc-ADAPT6 demonstrated safety, tolerability and capacity to visualize HER2 expression in primary breast cancer. In this study, we aimed to select the optimal parameters for distinguishing between breast cancers with high and low expression of HER2 using [99mTc]Tc-ADAPT6 in a planned Phase II study. HER2 expression was evaluated in primary tumours and metastatic axillary lymph nodes (mALNs). SPECT/CT imaging of twenty treatment-naive breast cancer patients was performed 2 h after injection of [99mTc]Tc-ADAPT6. The imaging data were compared with the data concerning HER2 expression obtained by immunohistochemical evaluation of samples obtained by core biopsy. Maximum Standard Uptake Values (SUVmax) afforded the best performance for both primary tumours and mALNs (areas under the receiver operating characteristic curve (ROC AUC) of 1.0 and 0.97, respectively). Lesion-to-spleen ratios provided somewhat lower performance. However, the ROC AUCs were still over 0.90 for both primary tumours and mALNs. Thus, lesion-to-spleen ratios should be further evaluated to find if these could be applied to imaging using stand-alone SPECT cameras that do not permit SUV calculations.

IMPROVING THE QUANTIFICATION ACCURACY OF Tc-99m MIBI DUAL-PHASE PARATHYROID SPECT/CT: A MONTE CARLO SIMULATION STUDY

Objective: Quantitative parathyroid SPECT imaging is a technique used to assess Primary hyperparathyroidism that may have potential in the identification and differentiation of parathyroid lesions as well as the estimation of disease severity. Studying the effect of data acquisition parameters on the quantification error is important for maximizing the accuracy of this diagnostic technique. In this study we examine the effects of different data acquisition parameters, namely the type of collimator, scatter correction status and reconstruction iteration number on the quantification accuracy using computer simulation. Methods: The SIMIND Monte Carlo Simulation and CASToR iterative reconstruction program was used to simulate a commercially available SPECT camera (Siemens Symbia Intevo Gamma Camera) with a crystal size of 29.55cm and 128x128 matrix size. A digital cylindrical phantom filled with water was constructed. A 0.36 cm radius spherical adenoma filled with a uniform 1MBq radioactivity is placed within the phantom. Low-Energy High Resolution (LEHR) and Low Energy Ultra High Resolution (LEUHR) collimator models are tested. Along with the presence of Scatter correction and differing iteration numbers (x16, x32). An image FOV based calibration method was used to gather quantitative information and checked against the input radioactivity. Results: The presence of scatter correction caused a 15-20% relative improvement in quantification accuracy. The optimal number of iterations produced a 10% relative improvement. Overall, accuracies as good as 7% in estimated activity concentration could be observed. Conclusion: The optimization of parameters can provide a significant improvement in quantification accuracy.

INVESTIGATION OF CENTERING PROBLEM IN THE CADMIUM ZINC TELLURIDE (CZT) CARDIAC CAMERA

Introduction: Cadmium Zinc Telluride (CZT) Cardiac Cameras are a special SPECT cameras with solid state cadmium zinc telluride detectors. This diagnostic method applied in the evaluation of coronary artery disease is well designed for myocardial perfusion scintigraphy. Aim: CZT cardiac cameras have limited detector area. In patients who are morbidly obese or whose heart is not in its normal location in the body, the center of the heart and the isocenter of the device do not coincide. It is aim to investigate how these conditions affect the imaging performance of the CZT cardiac camera. Methods: A homogeneous and spherical ball with a diameter of 4 cm was used for the research. To be able to measure away from the center a wooden phantom with 8 cavities and a total length of 32 cm was designed. The center as reference point has been determined by matching the center of the device with the center of the sphere. For the next imaging, the image were taken by placing the spherical ball in the other cavities, respectively, without changing the center. Results: According to the results obtained, farther from the center, deviations from sphericity and differences in dose distribution were observed. Counts decreased by 1.5% in the 2nd position and 16% in the 3rd position relative to the center in the X-axis. A disaster area has been formed and the image area has been exited from the 4th imaging. Conclusion: It is very important to center the patient as much as possible, otherwise the doctor will misdiagnose.

Respiratory signal estimation for cardiac perfusion SPECT using deep learning.

Respiratory motion induces artifacts in reconstructed cardiac perfusion SPECT images. Correction for respiratory motion often relies on a respiratory signal describing the heart displacements during breathing. However, using external tracking devices to estimate respiratory signals can add cost and operational complications in a clinical setting. We aim to develop a deep learning (DL) approach that uses only SPECT projection data for respiratory signal estimation. A modified U-Net was implemented that takes temporally finely sampled SPECT sub-projection data (100ms) as input. These sub-projections are obtained by reframing the 20-s list-mode data, resulting in 200 sub-projections, at each projection angle for each SPECT camera head. The network outputs a 200-time-point motion signal for each projection angle, which was later aggregated over all angles to give a full respiratory signal. The target signal for DL model training was from an external stereo-camera visual tracking system (VTS). In addition to comparing DL and VTS, we also included a data-driven approach based on the center-of-mass (CoM) strategy. This CoM method estimates respiratory signals by monitoring the axial changes of CoM for counts in the heart region of the sub-projections. We utilized 900 subjects with stress cardiac perfusion SPECT studies, with 302 subjects for testing and the remaining 598 subjects for training and validation. The Pearson's correlation coefficient between the DL respiratory signal and the reference VTS signal was 0.90, compared to 0.70 between the CoM signal and the reference. For respiratory motion correction on SPECT images, all VTS, DL, and CoM approaches partially de-blured the heart wall, resulting in a thinner wall thickness and increased recovered maximal image intensity within the wall, with VTS reducing blurring the most followed by the DL approach. Uptake quantification for the combined anterior and inferior segments of polar maps showed a mean absolute difference from the reference VTS of 1.7% for the DL method for patients with motion >12mm, compared to 2.6% for the CoM method and 8.5% for no correction. We demonstrate the capability of a DL approach to estimate respiratory signal from SPECT projection data for cardiac perfusion imaging. Our results show that the DL based respiratory motion correction reduces artefacts and achieves similar regional quantification to that obtained using the stereo-camera VTS signals. This may enable fully automatic data-driven respiratory motion correction without relying on external motion tracking devices.

Synthetic Attenuation Correction Maps for SPECT Imaging Using Deep Learning: A Study on Myocardial Perfusion Imaging.

(1) Background: The CT-based attenuation correction of SPECT images is essential for obtaining accurate quantitative images in cardiovascular imaging. However, there are still many SPECT cameras without associated CT scanners throughout the world, especially in developing countries. Performing additional CT scans implies troublesome planning logistics and larger radiation doses for patients, making it a suboptimal solution. Deep learning (DL) offers a revolutionary way to generate complementary images for individual patients at a large scale. Hence, we aimed to generate linear attenuation coefficient maps from SPECT emission images reconstructed without attenuation correction using deep learning. (2) Methods: A total of 384 SPECT myocardial perfusion studies that used 99mTc-sestamibi were included. A DL model based on a 2D U-Net architecture was trained using information from 312 patients. The quality of the generated synthetic attenuation correction maps (ACMs) and reconstructed emission values were evaluated using three metrics and compared to standard-of-care data using Bland-Altman plots. Finally, a quantitative evaluation of myocardial uptake was performed, followed by a semi-quantitative evaluation of myocardial perfusion. (3) Results: In a test set of 66 test patients, the ACM quality metrics were MSSIM = 0.97 ± 0.001 and NMAE = 3.08 ± 1.26 (%), and the reconstructed emission quality metrics were MSSIM = 0.99 ± 0.003 and NMAE = 0.23 ± 0.13 (%). The 95% limits of agreement (LoAs) at the voxel level for reconstructed SPECT images were: [-9.04; 9.00]%, and for the segment level, they were [-11; 10]%. The 95% LoAs for the Summed Stress Score values between the images reconstructed were [-2.8, 3.0]. When global perfusion scores were assessed, only 2 out of 66 patients showed changes in perfusion categories. (4) Conclusion: Deep learning can generate accurate attenuation correction maps from non-attenuation-corrected cardiac SPECT images. These high-quality attenuation maps are suitable for attenuation correction in myocardial perfusion SPECT imaging and could obviate the need for additional imaging in standalone SPECT scanners.

177Lu SPECT imaging in the presence of 90Y: does 90Y degrade image quantification? a simulation study

This work aims to investigate the accuracy of quantitative SPECT imaging of 177Lu in the presence of 90Y, which occurs in dual-isotope radiopharmaceutical therapy (RPT) involving both isotopes. We used the GATE Monte Carlo simulation toolkit to conduct a phantom study, simulating spheres filled with 177Lu and 90Y placed in a cylindrical water phantom that was also filled with activity of both radionuclides. We simulated multiple phantom configurations and activity combinations by varying the location of the spheres, the concentrations of 177Lu and 90Y in the spheres, and the amount of background activity. We investigated two different scatter window widths to be used with triple energy window (TEW) scatter correction. We also created multiple realizations of each configuration to improve our assessment, leading to a total of 540 simulations. Each configuration was imaged using a simulated Siemens SPECT camera. The projections were reconstructed using the standard 3D OSEM algorithm, and errors associated with 177Lu activity quantification and contrast-to-noise ratios (CNRs) were determined. In all configurations, the quantification error was within ± 6% of the no-90Y case, and we found that quantitative accuracy may slightly improve when 90Y is present because of reduction of errors associated with TEW scatter correction. The CNRs were not significantly impacted by the presence of 90Y, but they were increased when a wider scatter window width was used for TEW scatter correction. The width of the scatter windows made a small but statistically significant difference of 1%–2% on the recovered 177Lu activity. Based on these results, we can conclude that activity quantification of 177Lu and lesion detectability is not degraded by the presence of 90Y.

Validation of ^{99m}Tc and ^{177}Lu quantification parameters for a Monte Carlo modelled gamma camera

PurposeMonte Carlo (MC) simulation in Nuclear Medicine is a powerful tool for modeling many physical phenomena which are difficult to track or measure directly. MC simulation in SPECT/CT imaging is particularly suitable for optimizing the quantification of activity in a patient, and, consequently, the absorbed dose to each organ. To do so, validating MC results with real data acquired with gamma camera is mandatory. The aim of this study was the validation of the calibration factor (CF) and the recovery coefficient (RC) obtained with SIMIND Monte Carlo code for modeling a Siemens Symbia Intevo Excel SPECT-CT gamma camera to ensure optimal ^{99m}Tc and ^{177}Lu SPECT quantification.MethodsPhantom experiments using ^{99m}Tc and ^{177}Lu have been performed to measure spatial resolution and sensitivity, as well as to evaluate the CF and RC from acquired data. The geometries used for 2D planar imaging were (1) Petri dish and (2) capillary source while for 3D volumetric imaging were (3) a uniform filled cylinder phantom and (4) a Jaszczack phantom with spheres of different volumes. The experimental results have been compared with the results obtained from Monte Carlo simulations performed in the same geometries.ResultsComparison shows good accordance between simulated and experimental data. The measured planar spatial resolution was 8.3pm 0.8 mm for ^{99m}Tc and 11.8±0.6 mm for ^{177}Lu. The corresponding data obtained by SIMIND for ^{99m}Tc was 7.8±0.1 mm, while for ^{177}Lu was 12.4±0.4 mm. The CF was 110.1±5.5 cps/MBq for Technetium and 18.3±1.0 cps/MBq for Lutetium. The corresponding CF obtained by SIMIND for ^{99m}Tc was 107.3±0.3 cps/MBq, while for ^{177}Lu 20.4±0.7 cps/MBq. Moreover, a complete curve RCs vs Volume (ml) both for Technetium and Lutetium was determined to correct the PVE for all volumes of clinical interest. In none of the cases, a RC coefficient equal to 100 was found.ConclusionsThe validation of quantification parameters shows that SIMIND can be used for simulating both gamma camera planar and SPECT images of Siemens Symbia Intevo using ^{99m}Tc and ^{177}Lu radionuclides for different medical purposes and treatments.

Multi-center study of inter-rater reproducibility, image quality, and diagnostic accuracy of CZT versus conventional SPECT myocardial perfusion imaging

BackgroundCadmium-zinc-telluride (CZT)-based detectors exhibit higher diagnostic sensitivity in myocardial perfusion imaging (MPI) than conventional Anger-MPI for detection of coronary artery disease (CAD); however, reduced specificity and diagnostic accuracy of CZT-MPI were observed. This study aims to compare these different camera systems and to examine the degree of inter-rater reproducibility among readers with varying experience in MPI. Methods83 patients who underwent double stress/rest examinations using both a CZT and conventional SPECT cameras within one visit were included. Anonymized and randomized MPI-images were distributed to 15 international readers using a standardized questionnaire. Subsequent coronary angiography findings of ten patients served as a reference for analysis of sensitivity and specificity. ResultsImage quality was significantly better in CZT-MPI with significantly lower breast attenuation (P < 0.05). CZT-MPI exhibited higher sensitivity than Anger-MPI (87.5% vs. 62.5%) and significantly reduced specificity (40% vs. 100%). Readers experienced with both camera systems had the highest inter-rater agreement indicating higher reproducibility (CZT 0.54 vs. conv. 0.49, P < 0.05). ConclusionsHigher diagnostic sensitivity of CZT-MPI offers advantages in detection of CAD yet potentially of at the cost of reduced specificity, therefore it requires special training and a differentiated evaluation approach, especially for non-experienced readers with such camera systems.

Monitoring the biodistribution of radiolabeled therapeutics in mice.

Radiopharmaceutical therapy is a rapidly growing field for the treatment of cancer due to its high specificity and ability to target individual affected cells. A key component of the pre-clinical development of a new therapeutic radiopharmaceutical is the determination of its time-dependent distribution in tumors, normal tissues, and the whole body in mouse tumor models. Here, we provide an overview of the available instrumentation for the novice in radiation measurement. We also detail the methodology for assessing distribution and kinetics of a radiopharmaceutical and calculating radiation absorbed dose in mice using a gamma counter or a PET or SPECT camera.

Reduced acquisition time for thallium myocardial perfusion imaging with large field cadmium-zinc-telluride SPECT/CT cameras: An equivalence study

BackgroundCadmium-zinc-telluride (CZT) SPECT/CT cameras with large field of view offer a higher sensitivity than conventional Anger cameras. This prospective study aimed to determine the equivalence between a conventional protocol and a reduced acquisition time protocol for 201-Thallium myocardial perfusion imaging (MPI) using a whole-body CZT SPECT camera. Methods and ResultsStress MPI was obtained for 103 consecutive patients on a DISCOVERY-CZT camera. Images were anonymized and post-processed to simulate a 25% (D75 dataset) and 50% (D50 dataset) decrease in total recorded counts. Concerning the number of segments displaying a tracer uptake < 70% of maximum intensity per patient, equivalence was demonstrated for both count-reduced datasets with a good inter-observer agreement (between 0.90 and 0.88). When comparing the full-vs-D75 datasets and full-vs-D50 datasets, mean difference was 0.06 segment (CI95: [− 0.15;0.27], P < 0.001) and 0.518 segment (CI95: [0.28;0.76], P < 0.001) respectively. Inter-observer agreement was also moderate to good concerning the number of pathological segments (between 0.6 and 0.7) and excellent for functional parameters. ConclusionWhole-body CZT SPECT/CT cameras allow to reduce 201-Thallium MPI injected activity or acquisition time by 50% with an equivalence in the number of segments displaying a tracer uptake < 70% of maximum intensity and with a good inter-observer agreement.

DSPECT-specific normative limits for left ventricular size and function

BackgroundDifferences in spatial resolution and image filtering between the solid-state DSPECT and traditional Anger SPECT (ASPECT) cameras are likely to result in differences in LV measurements. However, DSPECT-specific normal values are not available. The traditional approach of using patients deemed to have a low (< 5%) probability of coronary artery disease for the derivation of normative values has a number of limitations. We used healthy organ-donor subjects without known disease or medication use for derivation of normal values. MethodsSubjects were 92 consecutive kidney or liver donors who underwent single-day rest (5 mCi)-stress (15 mCi) Tc-99m sestamibi-gated SPECT myocardial perfusion imaging (MPI) on the DSPECT camera for pre-operative evaluation and had normal perfusion and LV function. Exclusion criteria included any known cardiac disease or medications. LV measurements were made on the post-stress supine stress images using QGS®. ResultsOf 92 subjects (mean age 54.4 ± 15.0 and 39% men), mean EF ± 2SD for women and men was 77.2% ± 14.1% and 70.0 % ± 14.7%, respectively. Mean end-diastolic volume ± 2SD for women and men was 67.0 ± 32.2 mL and 99.6 ± 51.6 mL (indexed 38.3 ± 17.2 mL/m2 and 48.1 ± 25.9 mL/m2), respectively. Mean end-systolic volume ± 2SD for women and men was 16.1 ± 15.7 mL and 31.2 ± 29.2 mL (indexed 9.2 ± 8.8 mL/m2 and 15.0 ± 14.2 mL/m2), respectively. Mean LV wall volume ± 2SD for women and men was 95.9 ± 26.0 mL and 112.0 ± 48.8 mL (indexed 55.0 ± 13.8 mL/m2 and 54.1 ± 24.6 mL/m2), respectively. ConclusionWe report DSPECT-specific LV measurements from normal subjects from which limits of normality can be derived for clinic use. Organ donors who undergo pre-operative MPI are a suitable cohort for the derivation of normal values.

Optimizing the Minimum Detectable Difference of Gamma Camera SPECT Images via the Taguchi Analysis: A Feasibility Study with a V-Shaped Slit Gauge

This study tried to propose an innovated idea of solidifying the resolution of gamma camera in routine quality control and recommended a quantified index as minimum detectable difference (MDD) of gamma camera SPECT images using the Taguchi analysis and an indigenous V-shaped slit gauge. The gauge was customized to fulfill the quantitative requirement of the Taguchi analysis. The MDD among slit gauge of derived SPECT image was calculated from two overlapped peak profiles collected from a tangent slice of the V-shaped slit gauge with two nearby peaks. In particular, MDD was evaluated as minimum distance between two peak centers through the Student’s t-test with a constant, 1.96, which indicates that two peak centers separated distant enough to create a 95% confidence level of separation. Eighteen combinations of six gamma camera scanned factors were organized according to Taguchi analysis. Accordingly, (A) collimator, (B) detector to targe distance, (C) total counts, (D) acquired energy width, (E) Matrix size, and (F) zoom of collected ROI with each of two or three levels were organized into 18 groups to collect the slit gauge images according to Taguchi L18 orthogonal array. Then, three well-trained radiologists were ranked the scanned gauge images to derive the fish-bone-plot of signal-to-noise ratio (S/N, dB) and correlated ANOVA. Furthermore, the quantified MDD was proposed to verify the optimal suggestion of gamma camera scanned protocol, and obtained the MDD as 8.4, 7.9, and 7.1 mm for the second group of original L18 preset, conventional, and the optimal preset, respectively. Thus, the optimal preset of gamma camera was achieved in this study. The MDD proved to be a successful index in quantifying the imaging resolution of a gamma camera.

Initial clinical experience with dedicated multi-pinhole (MPH) collimator for 99mTc-HMPAO brain perfusion SPECT.

Dedicated multi-pinhole (MPH) collimators have been successfully tested in selected clinical investigations. The aim of our work was to report initial experiences with an MPH collimator set designed for brain perfusion single photon emission tomography (SPECT). Ten patients underwent sequential technetium-99m-hexamethylpropyleneamineoxime (99mTc-HMPAO) SPECT with a dual-head SPECT camera equipped with conventional low-energy parallel hole collimators (LEHR), and with a triple-head system equipped with MPH collimators. Low-energy parallel hole collimators data were reconstructed by filtered back projection (FBP), ordered subset expectation maximization (OSEM), software for tomographic image reconstruction (STIR). In addition, both the parallel hole data and MPH data were reconstructed by Tera-TomoTM 3D iterative reconstruction denoted LEHR_TT3D and MPH_TT3D, respectively. Five medical experts visually compared the reconstructed images of the five data sets and defined a ranking sequence from the lowest (1) to the highest (5) image quality. Results were compared using the Friedman test. P values below 0.05 were considered significant. Low-energy parallel hole collimators acquisition resulted in 5 million, while MPH acquisition in 13 million total counts with 30 and 34 minutes of acquisition time, respectively. Mean rank coefficients of the reconstruction methods were 1.96±0.52, 2.66±0.46, 2.86±0.60, 3.62±0.55, 3.9±0.68 for FBP, STIR, LEHR_TT3D, LEHR_OSEM, MPH_TT3D respectively. The differences between MPH_TT3D-FBP (P<0.01); MPH_TT3D-STIR (P<0.05); LEHR_OSEM-FBP (P<0.01) were significant. Image quality provided by MPH collimator is comparable to that provided by conventional LEHR imaging. Higher sensitivity has the potential to shorten acquisition time or to reduce the amount of administered activity.

An Algorithm for Individual Dosage in Cadmium-Zinc-Telluride SPECT-Gated Radionuclide Angiography.

The aim of the present study was to test an individualised dose without compromising the ease of analysing data when performing equilibrium radionuclide angiography (ERNA) using cadmium–zinc–telluride (CZT) SPECT. From March 2018 to January 2019, 1650 patients referred for ERNA received either an individualised dose of 99mTc-labeled human serum albumin (HSA) according to their age, sex, height, and weight (n = 1567), or a standard dose of 550 MBq (n = 83). The target count rate (CRT) was reduced every two months from 2.7 to 1.0 kcps. A final test with a CRT of 1.7 kcps was run for three months to test whether an agreement within 2% points for the determination of LVEF, on the basis of only two analyses, was obtainable in at least 95% of acquisitions. All the included ERNAs were performed on a dedicated cardiac CZT SPECT camera. When using the algorithm for an individualised dose, we found that agreement between the measured and predicted count rate was 80%. With a CRT of 1.7 kcps, the need for more than two analyses to obtain sufficient agreement for LVEF was 4.9%. Furthermore, this resulted in a mean dose reduction from 550 to 258 MBq. Patients’ weight, height, sex, and age can, therefore, be used for individualising a tracer dose while reducing the mean dose.

Standard SPECT myocardial perfusion estimation from half-time acquisitions using deep convolutional residual neural networks

IntroductionThe purpose of this work was to assess the feasibility of acquisition time reduction in MPI-SPECT imaging using deep leering techniques through two main approaches, namely reduction of the acquisition time per projection and reduction of the number of angular projections. MethodsSPECT imaging was performed using a fixed 90° angle dedicated dual-head cardiac SPECT camera. This study included a prospective cohort of 363 patients with various clinical indications (normal, ischemia, and infarct) referred for MPI-SPECT. For each patient, 32 projections for 20 seconds per projection were acquired using a step and shoot protocol from the right anterior oblique to the left posterior oblique view. SPECT projection data were reconstructed using the OSEM algorithm (6 iterations, 4 subsets, Butterworth post-reconstruction filter). For each patient, four different datasets were generated, namely full time (20 seconds) projections (FT), half-time (10 seconds) acquisition per projection (HT), 32 full projections (FP), and 16 half projections (HP). The image-to-image transformation via the residual network was implemented to predict FT from HT and predict FP from HP images in the projection domain. Qualitative and quantitative evaluations of the proposed framework was performed using a tenfold cross validation scheme using the root mean square error (RMSE), absolute relative error (ARE), structural similarity index, peak signal-to-noise ratio (PSNR) metrics, and clinical quantitative parameters. ResultsThe results demonstrated that the predicted FT had better image quality than the predicted FP images. Among the generated images, predicted FT images resulted in the lowest error metrics (RMSE = 6.8 ± 2.7, ARE = 3.1 ± 1.1%) and highest similarity index and signal-to-noise ratio (SSIM = 0.97 ± 1.1, PSNR = 36.0 ± 1.4). The highest error metrics (RMSE = 32.8 ± 12.8, ARE = 16.2 ± 4.9%) and the lowest similarity and signal-to-noise ratio (SSIM = 0.93 ± 2.6, PSNR = 31.7 ± 2.9) were observed for HT images. The RMSE decreased significantly (P value < .05) for predicted FT (8.0 ± 3.6) relative to predicted FP (6.8 ± 2.7). ConclusionReducing the acquisition time per projection significantly increased the error metrics. The deep neural network effectively recovers image quality and reduces bias in quantification metrics. Further research should be undertaken to explore the impact of time reduction in gated MPI-SPECT.

Abstract 12183: Multi-Center Evaluation of Inter-Site Variability in SPECT Myocardial Blood Flow Measurement

Introduction: Myocardial blood flow (MBF) imaging with SPECT is possible using cardiac-specific cameras. Single-center studies have shown that SPECT MBF is accurate compared with PET MBF and angiography. Clinical implementation requires consistency of SPECT MBF measurements across multiple sites. This study is the first multi-center evaluation of the inter-site processing variability of SPECT MBF. Objective: To compare SPECT MBF obtained locally to MBF calculated at the core lab in Ottawa, Canada. Methods: Six sites (2 in Canada and one each from Japan, Singapore, Italy, and Germany) each acquired 25 rest/stress MBF studies using Tc99m-tetrofosmin (377 MBq at rest; 1060 MBq at stress) on a pinhole-collimated cadmium-zinc-telluride(CZT)-based cardiac SPECT camera. Patients had intermediate to high pre-test probability of coronary artery disease. MBF was analyzed locally and at a core lab using commercially available software. The time that a room was occupied for a MBF study was compared to that for a standard rest/stress myocardial perfusion study. Results: Preliminary results from 4 sites showed a correlation in MBF between the core lab and the local site of an average of 0.96 (range 0.95 to 0.97) at rest and 0.89 (range 0.77 to 0.96) at stress. From Bland-Altman analysis, the mean bias from zero in global MBF between local and core-lab analysis was 3.3% +/- 13.4% at rest and 3.0 % +/- 18.6% at stress. Between the 4 sites, the bias ranged from -4.1% to 9.9% at rest and from -6.3% to 12.8% at stress; the standard deviation (SD) ranged from 10.5% to 14.0% at rest and from 12.0% to 24.5% at stress. There was no significant difference between sites in the SD. The SD of the local-to-core-lab MBF differences is less than the SD of the test-retest difference of 30%, measured in a previous single-center study. The average additional time to perform a MBF study acquisition varied between sites from 45 to 76 min. This additional time includes the time needed to pharmacologically stress the patient which is normally done outside the camera room. Conclusions: This multi-center evaluation supports the feasibility of consistently measuring MBF using CZT-based cardiac SPECT cameras, as has been suggested from previous single-center studies.

Deep learning\u2013based denoising of low-dose SPECT myocardial perfusion images: quantitative assessment and clinical performance

PurposeThis work was set out to investigate the feasibility of dose reduction in SPECT myocardial perfusion imaging (MPI) without sacrificing diagnostic accuracy. A deep learning approach was proposed to synthesize full-dose images from the corresponding low-dose images at different dose reduction levels in the projection space.MethodsClinical SPECT-MPI images of 345 patients acquired on a dedicated cardiac SPECT camera in list-mode format were retrospectively employed to predict standard-dose from low-dose images at half-, quarter-, and one-eighth-dose levels. To simulate realistic low-dose projections, 50%, 25%, and 12.5% of the events were randomly selected from the list-mode data through applying binomial subsampling. A generative adversarial network was implemented to predict non-gated standard-dose SPECT images in the projection space at the different dose reduction levels. Well-established metrics, including peak signal-to-noise ratio (PSNR), root mean square error (RMSE), and structural similarity index metrics (SSIM) in addition to Pearson correlation coefficient analysis and clinical parameters derived from Cedars-Sinai software were used to quantitatively assess the predicted standard-dose images. For clinical evaluation, the quality of the predicted standard-dose images was evaluated by a nuclear medicine specialist using a seven-point (− 3 to + 3) grading scheme.ResultsThe highest PSNR (42.49 ± 2.37) and SSIM (0.99 ± 0.01) and the lowest RMSE (1.99 ± 0.63) were achieved at a half-dose level. Pearson correlation coefficients were 0.997 ± 0.001, 0.994 ± 0.003, and 0.987 ± 0.004 for the predicted standard-dose images at half-, quarter-, and one-eighth-dose levels, respectively. Using the standard-dose images as reference, the Bland–Altman plots sketched for the Cedars-Sinai selected parameters exhibited remarkably less bias and variance in the predicted standard-dose images compared with the low-dose images at all reduced dose levels. Overall, considering the clinical assessment performed by a nuclear medicine specialist, 100%, 80%, and 11% of the predicted standard-dose images were clinically acceptable at half-, quarter-, and one-eighth-dose levels, respectively.ConclusionThe noise was effectively suppressed by the proposed network, and the predicted standard-dose images were comparable to reference standard-dose images at half- and quarter-dose levels. However, recovery of the underlying signals/information in low-dose images beyond a quarter of the standard dose would not be feasible (due to very poor signal-to-noise ratio) which will adversely affect the clinical interpretation of the resulting images.