Clinical validation of time reduction strategy in continuous step-and-shoot mode during SPECT acquisition

Effect of single-photon emission computed tomography acquisition method and sampling angles on image quality and quantitative accuracy in xSPECT-reconstructed images

OBJECTIVE

The aim of this study was to evaluate the effects of the single-photon emission computed tomography (SPECT) acquisition method and sampling angles on the qualitative and quantitative interpretations of xSPECT-reconstructed images.

METHODS

The spatial resolution was evaluated using a JSP phantom, and the uniformity and quantitative accuracy were verified with a NEMA IEC Body Phantom using an SIEMENS Symbia Intevo SPECT/computed tomography system. SPECT was performed using three acquisition methods (step-and-shoot, continuous, and acquire during the step), and the sampling angles were set to 2, 3, 4, 5, and 6°. The xSPECT-reconstruction technology which is used with ordered subset-conjugated gradient minimization was used for image reconstruction.

RESULTS

Full width of half maximum, an evaluation index of spatial resolution, varied up to 2.73 mm with different sampling angles and up to 2.06 mm with different acquisition methods. Uniformity, as assessed by the coefficient of variation, improved with increasing sampling angles. The accuracy of the quantification of the hot sphere showed an error rate of approximately 10% depending on the sampling angle, and an error rate of approximately 5% depending on the different acquisition methods.

CONCLUSIONS

In xSPECT-reconstructed images, the difference in sampling angle has a greater impact on image quality and quantitativity than the difference in the acquisition method. For tests in which uniformity is important, a larger sampling angle is recommended.

PET/CT and SPECT/CT for Infection in Joints and Bones: An Overview and Future Directions

Infections of the bones and joints, if misdiagnosed, may result in serious morbidity and even mortality. A prompt diagnosis followed by appropriate management may reduce the socioeconomic impact of bone and joint infections. Morphologic imaging such as ultrasound and plain radiographs form the first line investigations, however, in early infections findings may be negative or nonspecific. Nuclear medicine imaging techniques play a complementary role to morphologic imaging in the diagnosis of bone and joint infections. The availability of hybrid systems (SPECT/CT, SPECT/MRI, PET/CT or PET/MRI) offers improved specificity with ability to assess the extent of infection. Bone scans are useful as a gatekeeper wherein negative scans rule out sepsis with a good accuracy, however positive scans are nondiagnostic and more specific tracers should be considered. These include the use of labeled white blood cells and antigranulocyte antibodies. Various qualitative and quantitative interpretation criteria have been suggested to improve the specificity of the scans. PET has better image resolution and 18F-FDG is the major tracer for PET imaging with applications in oncology and inflammatory/infective disorders. It has demonstrated improved sensitivity over the SPECT based tracers, however, still suffers from lack of specificity. 18F-FDG PET has been used to monitor therapy in bone and joint infections. Other less studied, noncommercialized SPECT and PET tracers such as 111In-Biotin, 99mTc-Ubiquicidin, 18F-Na-Fluoride, 18F-labeled white blood cells and 124I-Fialuridine to name a few have shown great promise, however, their role in various bone and joint infections has not been established. Hybrid imaging with PET or PET/MRI offers huge potential for improving diagnostics in infections of the joints and bones.

The Past, Present, and Future Role of Artificial Intelligence in Ventilation/Perfusion Scintigraphy: A Systematic Review

Ventilation-perfusion (V/Q) lung scans constitute one of the oldest nuclear medicine procedures, remain one of the few studies performed in the acute setting, and are amongst the few performed in the emergency setting. V/Q studies have witnessed a long fluctuation in adoption rates in parallel to continuous advances in image processing and computer vision techniques. This review provides an overview on the status of artificial intelligence (AI) in V/Q scintigraphy. To clearly assess the past, current, and future role of AI in V/Q scans, we conducted a systematic Ovid MEDLINE(R) literature search from 1946 to August 5, 2022 in addition to a manual search. The literature was reviewed and summarized in terms of methodologies and results for the various applications of AI to V/Q scans. The PRISMA guidelines were followed. Thirty-one publications fulfilled our search criteria and were grouped into two distinct categories: (1) disease diagnosis/detection (N = 22, 71.0%) and (2) cross-modality image translation into V/Q images (N = 9, 29.0%). Studies on disease diagnosis and detection relied heavily on shallow artificial neural networks for acute pulmonary embolism (PE) diagnosis and were primarily published between the mid-1990s and early 2000s. Recent applications almost exclusively regard image translation tasks from CT to ventilation or perfusion images with modern algorithms, such as convolutional neural networks, and were published between 2019 and 2022. AI research in V/Q scintigraphy for acute PE diagnosis in the mid-90s to early 2000s yielded promising results but has since been largely neglected and thus have yet to benefit from today's state-of-the art machine-learning techniques, such as deep neural networks. Recently, the main application of AI for V/Q has shifted towards generating synthetic ventilation and perfusion images from CT. There is therefore considerable potential to expand and modernize the use of real V/Q studies with state-of-the-art deep learning approaches, especially for workflow optimization and PE detection at both acute and chronic stages. We discuss future challenges and potential directions to compensate for the lag in this domain and enhance the value of this traditional nuclear medicine scan.

Verification of the effect of acquisition time for SwiftScan on quantitative bone single-photon emission computed tomography using an anthropomorphic phantom

Background

SwiftScan single-photon emission computed tomography (SPECT) is a recently released scanning technique with data acquired when the detector is stationary and when it moves from one view to the next. The influence of scan time for using SwiftScan on quantitative bone SPECT remains unclear. This study aimed to clarify the effect of the scan time for SwiftScan SPECT on the image quality and quantification of bone SPECT compared to step and shoot mode (SSM) using ^99mTc-filled anthropomorphic phantom (SIM² bone phantom).

Materials and methods

Phantom SPECT/computed tomography (CT) images were acquired using Discovery NM/CT 860 (GE Healthcare) with a low-energy high-resolution sensitivity collimator. We used the fixed parameters (subsets 10 and iterations 5) for reconstruction. The coefficient of variation (CV), contrast-to-noise ratio (CNR), full width at half maximum (FWHM), and quantitative value of SwiftScan SPECT and SSM were compared at various acquisition times (5, 7, 17, and 32 min).

Results

In the short-time scan (< 7 min), the CV and CNR of SwiftScan SPECT were better than those of SSM, whereas in the longtime scan (> 17 min), the CV and CNR of SwiftScan SPECT were similar to those of SSM. The FWHMs for SwiftScan SPECT (13.6–14.8 mm) and SSM (13.5–14.4 mm) were similar. The mean absolute errors of quantitative values at 5, 7, 17, and 32 min were 38.8, 38.4, 48.8, and 48.1, respectively, for SwiftScan SPECT and 41.8, 40.8%, 47.2, and 49.8, respectively, for SSM.

Conclusions

SwiftScan on quantitative bone SPECT provides improved image quality in the short-time scan with quantification similar to or better than SSM. Therefore, in clinical settings, using SwiftScan SPECT instead of the SSM scan protocol in the short-time scan might provide higher-quality diagnostic images than SSM. Our results could provide vital information on the use of SwiftScan SPECT.

Monte Carlo Simulation and Reconstruction: Assessment of Myocardial Perfusion Imaging of Tracer Dynamics With Cardiac Motion Due to Deformation and Respiration Using Gamma Camera With Continuous Acquisition

Purpose

Myocardial perfusion imaging (MPI) with single photon emission computed tomography (SPECT) is routinely used for stress testing in nuclear medicine. Recently, our group extended its potential going from 3D visual qualitative image analysis to 4D spatiotemporal reconstruction of dynamically acquired data to capture the time variation of the radiotracer concentration and the estimated myocardial blood flow (MBF) and coronary flow reserve (CFR). However, the quality of reconstructed image is compromised due to cardiac deformation and respiration. The work presented here develops an algorithm that reconstructs the dynamic sequence of separate respiratory and cardiac phases and evaluates the algorithm with data simulated with a Monte Carlo simulation for the continuous image acquisition and processing with a slowly rotating SPECT camera.

Methods

A clinically realistic Monte Carlo (MC) simulation is developed using the 4D Extended Cardiac Torso (XCAT) digital phantom with respiratory and cardiac motion to model continuous data acquisition of dynamic cardiac SPECT with slowly rotating gamma cameras by incorporating deformation and displacement of the myocardium due to cardiac and respiratory motion. We extended our previously developed 4D maximum-likelihood expectation-maximization (MLEM) reconstruction algorithm for a data set binned from a continuous list mode (LM) simulation with cardiac and respiratory information. Our spatiotemporal image reconstruction uses splines to explicitly model the temporal change of the tracer for each cardiac and respiratory gate that delineates the myocardial spatial position as the tracer washes in and out. Unlike in a fully list-mode data acquisition and reconstruction the accumulated photons are binned over a specific but very short time interval corresponding to each cardiac and respiratory gate. Reconstruction results are presented showing the dynamics of the tracer in the myocardium as it continuously deforms. These results are then compared with the conventional 4D spatiotemporal reconstruction method that models only the temporal changes of the tracer activity. Mean Stabilized Activity (MSA), signal to noise ratio (SNR) and Bias for the myocardium activities for three different target-to-background ratios (TBRs) are evaluated. Dynamic quantitative indices such as wash-in (K₁) and wash-out (k₂) rates at each gate were also estimated.

Results

The MSA and SNR are higher with higher TBRs while biases were improved with higher TBRs to less than 10%. The correlation between exhalation-inhalation sequence with the ground truth during respiratory cycle was excellent. Our reconstruction method showed better resolved myocardial walls during diastole to systole as compared to the ungated 4D image. Estimated values of K₁ and k₂ were also consistent with the ground truth.

Conclusion

The continuous image acquisition for dynamic scan using conventional two-head gamma cameras can provide valuable information for MPI. Our study demonstrated the viability of using a continuous image acquisition method on a widely used clinical two-head SPECT system. Our reconstruction method showed better resolved myocardial walls during diastole to systole as compared to the ungated 4D image. Precise implementation of reconstruction algorithms, better segmentation techniques by generating images of different tissue types and background activity would improve the feasibility of the method in real clinical environment.

Simulating dose reduction for myocardial perfusion SPECT using a Poisson resampling method

Purpose

The purpose of this study was to determine the lowest Tl-201 dose that does not reduce the image quality of myocardial perfusion SPECT (MPS) by Poisson resampling simulation.

Methods

One hundred and twelve consecutive MPS data from patients with suspected or known coronary artery disease were collected retrospectively. Stress and rest MPS data were resampled using the Poisson method with 33%, 50%, 67%, and 100% count settings. Two nuclear medicine physicians assessed the image quality of reconstructed data visually by giving grades from - 2 to + 2. The summed stress score (SSS), summed rest score (SRS), and summed difference score (SDS) were obtained on the workstation. Image quality grades and semi-quantitative scores were then compared among these resampled images.

Results

The proportions of "adequate" image quality were 0.48, 0.75, 0.92, and 0.96 for the groups of images with 33%, 50%, 67%, and 100% data, respectively. The quality of the resampled images was significantly degraded at 50% and 33% count settings, while the image quality was not different between 67 and 100% count settings. We also found that high body mass index further decreased image quality at 33% count setting. Among the semi-quantitative parameters, SSS and SRS showed a tendency to increase with a decline in count.

Conclusion

Based on the simulation results, Tl-201 dose for MPS can be reduced to 74 MBq without significant loss of image quality. However, the SSS and SRS can be changed significantly, and it needs to be further verified under the different conditions.