Perfusion Single Photon Emission Computed Tomography Research Articles

The Legacy of the TTASAAN Report-Premature Conclusions and Forgotten Promises: A Review of Policy and Practice Part I.

Brain perfusion single photon emission computed tomography (SPECT) scans were initially developed in 1970's. A key radiopharmaceutical, hexamethylpropyleneamine oxime (HMPAO), was originally approved in 1988, but was unstable. As a result, the quality of SPECT images varied greatly based on technique until 1993, when a method of stabilizing HMPAO was developed. In addition, most SPECT perfusion studies pre-1996 were performed on single-head gamma cameras. In 1996, the Therapeutics and Technology Assessment Subcommittee of the American Academy of Neurology (TTASAAN) issued a report regarding the use of SPECT in the evaluation of neurological disorders. Although the TTASAAN report was published in January 1996, it was approved for publication in October 1994. Consequently, the reported brain SPECT studies relied upon to derive the conclusions of the TTASAAN report largely pre-date the introduction of stabilized HMPAO. While only 12% of the studies on traumatic brain injury (TBI) in the TTASAAN report utilized stable tracers and multi-head cameras, 69 subsequent studies with more than 23,000 subjects describe the utility of perfusion SPECT scans in the evaluation of TBI. Similarly, dementia SPECT imaging has improved. Modern SPECT utilizing multi-headed gamma cameras and quantitative analysis has a sensitivity of 86% and a specificity of 89% for the diagnosis of mild to moderate Alzheimer's disease—comparable to fluorodeoxyglucose positron emission tomography. Advances also have occurred in seizure neuroimaging. Lastly, developments in SPECT imaging of neurotoxicity and neuropsychiatric disorders have been striking. At the 25-year anniversary of the publication of the TTASAAN report, it is time to re-examine the utility of perfusion SPECT brain imaging. Herein, we review studies cited by the TTASAAN report vs. current brain SPECT imaging research literature for the major indications addressed in the report, as well as for emerging indications. In Part II, we elaborate technical aspects of SPECT neuroimaging and discuss scan interpretation for the clinician.

"Virtual" attenuation correction: improving stress myocardial perfusion SPECT imaging using deep learning.

Myocardial perfusion imaging (MPI) using single-photon emission computed tomography (SPECT) is widely used for coronary artery disease (CAD) evaluation. Although attenuation correction is recommended to diminish image artifacts and improve diagnostic accuracy, approximately 3/4ths of clinical MPI worldwide remains non-attenuation-corrected (NAC). In this work, we propose a novel deep learning (DL) algorithm to provide "virtual" DL attenuation-corrected (DLAC) perfusion polar maps solely from NAC data without concurrent computed tomography (CT) imaging or additional scans. SPECT MPI studies (N = 11,532) with paired NAC and CTAC images were retrospectively identified. A convolutional neural network-based DL algorithm was developed and trained on half of the population to predict DLAC polar maps from NAC polar maps. Total perfusion deficit (TPD) was evaluated for all polar maps. TPDs from NAC and DLAC polar maps were compared to CTAC TPDs in linear regression analysis. Moreover, receiver-operating characteristic analysis was performed on NAC, CTAC, and DLAC TPDs to predict obstructive CAD as diagnosed from invasive coronary angiography. DLAC TPDs exhibited significantly improved linear correlation (p < 0.001) with CTAC (R2 = 0.85) compared to NAC vs. CTAC (R2 = 0.68). The diagnostic performance of TPD was also improved with DLAC compared to NAC with an area under the curve (AUC) of 0.827 vs. 0.780 (p = 0.012) with no statistically significant difference between AUC for CTAC and DLAC. At 88% sensitivity, specificity was improved by 18.9% for DLAC and 25.6% for CTAC. The proposed DL algorithm provided attenuation correction comparable to CTAC without the need for additional scans. Compared to conventional NAC perfusion imaging, DLAC significantly improved diagnostic accuracy.

Deep learning-guided attenuation correction in the image domain for myocardial perfusion SPECT imaging

Abstract We investigate the accuracy of direct attenuation correction (AC) in the image domain for myocardial perfusion SPECT (single-photon emission computed tomography) imaging (MPI-SPECT) using residual (ResNet) and UNet deep convolutional neural networks. MPI-SPECT 99mTc-sestamibi images of 99 patients were retrospectively included. UNet and ResNet networks were trained using non-attenuation-corrected SPECT images as input, whereas CT-based attenuation-corrected (CT-AC) SPECT images served as reference. Chang’s calculated AC approach considering a uniform attenuation coefficient within the body contour was also implemented. Clinical and quantitative evaluations of the proposed methods were performed considering SPECT CT-AC images of 19 subjects (external validation set) as reference. Image-derived metrics, including the voxel-wise mean error (ME), mean absolute error, relative error, structural similarity index (SSI), and peak signal-to-noise ratio, as well as clinical relevant indices, such as total perfusion deficit (TPD), were utilized. Overall, AC SPECT images generated using the deep learning networks exhibited good agreement with SPECT CT-AC images, substantially outperforming Chang’s method. The ResNet and UNet models resulted in an ME of −6.99 ± 16.72 and −4.41 ± 11.8 and an SSI of 0.99 ± 0.04 and 0.98 ± 0.05, respectively. Chang’s approach led to ME and SSI of 25.52 ± 33.98 and 0.93 ± 0.09, respectively. Similarly, the clinical evaluation revealed a mean TPD of 12.78 ± 9.22% and 12.57 ± 8.93% for ResNet and UNet models, respectively, compared to 12.84 ± 8.63% obtained from SPECT CT-AC images. Conversely, Chang’s approach led to a mean TPD of 16.68 ± 11.24%. The deep learning AC methods have the potential to achieve reliable AC in MPI-SPECT imaging.

Delayed development of cerebral atrophy after cerebral hyperperfusion following arterial bypass for adult patients with ischemic moyamoya disease: supplementary analysis of a 5-year prospective cohort.

Adult patients with moyamoya disease (MMD) occasionally exhibit cerebral hyperperfusion after arterial bypass surgery, leading to persistent cognitive decline. The present supplementary analysis of a prospective 5-year cohort study aimed to determine whether cerebral hyperperfusion after arterial bypass surgery for adult patients with misery perfusion due to ischemic MMD causes cerebral atrophy, and whether the development of cerebral atrophy is related to persistent cognitive decline. In total, 31 patients who underwent arterial bypass surgery also underwent fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) and neuropsychological testing before surgery and at the end of a 5-year follow-up. The development of cerebral hyperperfusion and hyperperfusion syndrome after surgery was defined based on brain perfusion single-photon emission computed tomography (SPECT) findings and clinical symptoms. Univariate and multivariate logistic regression analyses of factors related to the development of cerebral atrophy on FLAIR MRI or cognitive decline on neuropsychological testing at the end of the 5-year follow-up were performed. Eleven patients (35%) developed cerebral atrophy in the frontal lobe where the superficial temporal artery was anastomosed. Cerebral hyperperfusion on brain perfusion SPECT (odds ratio [OR], 50.6; p = 0.0008) or cerebral hyperperfusion syndrome (OR, 41.8; p = 0.0026) was independently associated with the development of cerebral atrophy, and cerebral atrophy development was significantly associated with cognitive decline (OR, 47.7; p = 0.0010). Cerebral hyperperfusion after arterial bypass surgery for adult patients with misery perfusion due to ischemic MMD can cause cerebral atrophy related to persistent cognitive decline.

The Strengths and Obstacles in the Differential Diagnosis of Progressive Supranuclear Palsy-Parkinsonism Predominant (PSP-P) and Multiple System Atrophy (MSA) Using Magnetic Resonance Imaging (MRI) and Perfusion Single Photon Emission Computed Tomography (SPECT).

Multiple System Atrophy—Parkinsonism Predominant (MSA-P) and Progressive Supranuclear Palsy—Parkinsonism Predominant (PSP-P) are the clinical manifestations of atypical parkinsonism. Currently, there are no efficient in vivo methods available relating to neuroimaging or biochemical analysis in the examination of these entities. Among the advanced methods available, using positron emission tomography is constrained by high cost and low accessibility. In this study the authors examined patients with two types of atypical parkinsonism—MSA-P and PSP-P, which are difficult to differentiate, especially in the early years of their development. The aim of this study was to assess whether the examination of patients in the period following the early years (3–6-year duration of symptoms) could be enhanced by perfusion single photon emission computed tomography (SPECT), magnetic resonance imaging (MRI) or evaluation of cognitive abilities. Extended examination using MRI and perfusion SPECT showed that the evaluation of the mesencephalon/pons ratio, mesencephalic volume decrease, the Magnetic Resonance Parkinsonism Index (MRPI) and frontal perfusion should be considered more feasible than screening cognitive evaluation in MSA-P and PSP-P with a 3–6-year duration of symptoms.

Correlation between noise pareidolia test scores for visual hallucinations and regional cerebral blood flow in dementia with Lewy bodies.

This study aimed at investigating the correlation between recurrent visual hallucinations (VHs) and regional cerebral blood flow (rCBF) in patients with dementia with Lewy bodies (DLB). In 147 DLB patients, the correlation between noise pareidolia scores and rCBF in brain perfusion single photon emission computed tomography (SPECT) was evaluated. The 147 subjects comprised 52 probable and 95 possible DLB patients, of whom 107 did not have visual hallucinations and 40 had visual hallucinations. Brain perfusion SPECT was then performed, and memory impairment was assessed using the Mini-Mental State Examination (MMSE), while the optical illusion "pareidolia" (the tendency to see a specific image in a random visual pattern) was evaluated using noise pareidolia test. The correlations between rCBF and MMSE or noise pareidolia scores were then analyzed. The rCBF and MMSE scores were positively correlated, and rCBF was correlated with MMSE scores in a region that was consistent with a previously reported memory-related site. There was no correlation between noise pareidolia scores and occipital CBF, but there were weak correlations between noise pareidolia scores and rCBF in the bilateral frontal lobes (Brodmann area [BA]8 and BA9), left cingulate cortex (BA31), and left angular and supramarginal gyri (BA39 and BA40) in DLB patients. Weak correlation was found between noise pareidolia scores and rCBF in several sites (BA8, BA9, BA31, BA39 and BA40) other than in occipital lobe. These findings suggest that DLB hallucinations may be manifested by more complex brain network disorders, rather than by primary visual cortex disorders alone.

60 Years of Achievements by KSNM in Neuroimaging Research.

Nuclear medicine neuroimaging is able to show functional and molecular biologic abnormalities in various neuropsychiatric diseases. Therefore, it has played important roles in the clinical diagnosis and in research on the normal and pathological states of the brain. More than 400 outstanding studies have been conducted by Korean researchers over the past 60years. In the 1990s, when multiheaded single-photon emission computed tomography (SPECT) scanners were first introduced in South Korea, stroke research using brain perfusion SPECT was conducted. With the spread of positron emission tomography (PET) scanners in the 2000s, research on the clinical usefulness of PET and the evaluation of pathophysiology in various diseases such as epilepsy, brain tumors, degenerative brain diseases, and other neuropsychiatric diseases were actively conducted using [18F]FDG and various neuroreceptor tracers. In the 2010s, with the clinical application of new radiopharmaceuticals for amyloid and tau imaging, research demonstrating the clinical usefulness of PET imaging and the pathophysiology of dementia has increased rapidly. It is expected that the role of nuclear medicine will expand with the development of new radiopharmaceuticals and analysis technologies, along with the application of artificial intelligence for early and differential diagnosis, and the development of therapeutic agents for degenerative brain diseases.

Clinical Validation of Japanese Normal Myocardial Perfusion Imaging Databases Using Semi-conductor Gamma Camera (D-SPECT): Japanese Society of Nuclear Cardiology Working Group Reports.

Objective: A working group (WG) of the Japanese Society of Nuclear Cardiology (JSNC) determined Japanese normal databases of myocardial perfusion single-photon emission computed tomography (SPECT) on semi-conductor gamma camera (D-SPECT), and the aim of this study was to validate its clinical utility. Materials and methods: The normal myocardial perfusion SPECT (MPS) databases of Japanese patients in the 201Tl stress/redistribution protocol (201Tl protocol), 99mTc stress/rest or rest/stress protocol (99mTc protocol), and rest 99mTc/stress 201Tl simultaneous acquisition dual-isotope protocol (SDI protocol) were created by JSNC WG. The WG collected clinical cases for the 201Tl protocol (male/female [m/f], 8/8), 99mTc protocol (m/f, 9/7), and SDI protocol (m/f, 10/10) from WG participating hospitals. Four WG members read those clinical cases on a 17-segment and 5-point scale (0-4). Using the most frequent values as the score for each segment, weighted κ values were calculated with the scores obtained from quantitative perfusion software (QPS). Results: Weighted κ values were as follows; 201Tl stress/female, 0.77; 201Tl rest/female, 0.74; 201Tl stress/male, 0.81; 201Tl rest/male, 0.68; 99mTc stress/female, 0.77; 99mTc rest/female, 0.62; 99mTc stress/male, 0.77; 99mTc rest/male, 0.75; SDI stress/female, 0.87; SDI rest/female, 0.82; SDI stress/male, 0.87; SDI rest/male, 0.85. Conclusions: The diagnostic accuracy of Japanese MPS normal databases on D-SPECT were comparable with nuclear cardiology expert reading and further clinical applications are expected.

A Novel Method to Suppress the Effect of Subdiaphragmatic Activity in 99mTc Myocardial Perfusion SPECT and Evaluation of Its Usefulness Using a Myocardial Phantom.

Background: Smoothing in 99mTc myocardial perfusion single-photon emission computed tomography (SPECT) often increases myocardial artifacts due to subdiaphragmatic activity near the heart. To reduce these artifacts, we developed a new process flow, masking on unsmoothed images (MUS), that includes the extraction of the myocardium by masking before smoothing. Methods: This study evaluated the relationships between matrix sizes and distances to the subdiaphragmatic activity using the MUS method compared to conventional methods using a combination of image reconstruction methods (filtered back-projection [FBP] and ordered subset expectation maximization [OSEM]) with or without corrections (attenuation [AC], scatter [SC], and resolution recovery [RR]) using a myocardial phantom. The results were compared for two matrix sizes (pixel sizes) (128×128 [3.3 mm] and 64×64 [6.6 mm]); four subdiaphragmatic activity distances (5, 10, 15, and 20 mm); and three reconstruction methods (FBP without correction; OSEM with RR; and OSEM with AC, SC, and RR). Results: In the conventional method, increasing distance resulted in interference with myocardial perfusion SPECT evaluation however, the artifacts were less apparent when the MUS method was applied. The images converted to 64×64 did not show the same effect as the 128×128 images, even when RR was used. The MUS method was useful for acquisition at 128×128, along with the use of RR in the reconstruction process. Conclusion: MUS mitigated the effects of subdiaphragmatic activity on myocardial perfusion SPECT, particularly combined with 128×128 acquisitions and iterative reconstruction with RR.

Performance Evaluation of a Preclinical SPECT Scanner with a Collimator Designed for Medium-Sized Animals.

Background Equipped with two stationary detectors, a large bore collimator for medium-sized animals has been recently introduced for dedicated preclinical single-photon emission computed tomography (SPECT) imaging. We aimed to evaluate the basic performance of the system using phantoms and healthy rabbits. Methods A general-purpose medium-sized animal (GP-MSA) collimator with 135 mm bore diameter and thirty-three holes of 2.5 mm diameter was installed on an ultrahigh-resolution scanner equipped with two large stationary detectors (U-SPECT5-E/CT). The sensitivity and uniformity were investigated using a point source and a cylinder phantom containing 99mTc-pertechnetate, respectively. Uniformity (in %) was derived using volumes of interest (VOIs) on images of the cylinder phantom and calculated as [(maximum count − minimum count)/(maximum count + minimum count) × 100], with lower values of % indicating superior performance. The spatial resolution and contrast-to-noise ratios (CNRs) were evaluated with images of a hot-rod Derenzo phantom using different activity concentrations. Feasibility of in vivo SPECT imaging was finally confirmed by rabbit imaging with the most commonly used clinical myocardial perfusion SPECT agent [99mTc]Tc-sestamibi (dynamic acquisition with a scan time of 5 min). Results In the performance evaluation, a sensitivity of 790 cps/MBq, a spatial resolution with the hot-rod phantom of 2.5 mm, and a uniformity of 39.2% were achieved. The CNRs of the rod size 2.5 mm were 1.37, 1.24, 1.20, and 0.85 for activity concentration of 29.2, 1.0, 0.5, and 0.1 MBq/mL, respectively. Dynamic SPECT imaging in rabbits allowed to visualize most of the thorax and to generate time-activity curves of the left myocardial wall and ventricular cavity. Conclusion Preclinical U-SPECT5-E/CT equipped with a large bore collimator demonstrated adequate sensitivity and resolution for in vivo rabbit imaging. Along with its unique features of SPECT molecular functional imaging is a superior collimator technology that is applicable to medium-sized animal models and thus may promote translational research for diagnostic purposes and development of novel therapeutics.

A myocardial extraction method using deep learning for 99mTc myocardial perfusion SPECT images: A basic study to reduce the effects of extra-myocardial activity

AimThe purpose of this study was to automatically extract myocardial regions from transaxial single-photon emission computed tomography (SPECT) images using deep learning to reduce the effects of extracardiac activity, which has been problematic in cardiac nuclear imaging. Method: Myocardial region extraction was performed using two deep neural network architectures, U-Net and U-Net ++, and 694 myocardial SPECT images manually labeled with myocardial regions were used as the training data. In addition, a multi-slice input method was introduced during the learning session while taking the relationships to adjacent slices into account. Accuracy was assessed using Dice coefficients at both the slice and pixel levels, and the most effective number of input slices was determined. Results: The Dice coefficient was 0.918 at the pixel level, and there were no false positives at the slice level using U-Net++ with 9 input slices. Conclusion: The proposed system based on U-Net++ with multi-slice input provided highly accurate myocardial region extraction and reduced the effects of extracardiac activity in myocardial SPECT images.

Data-driven respiratory signal estimation from temporally finely sampled projection data in conventional cardiac perfusion SPECT imaging.

The aim of this work was to revisit the data-driven approach of axial center-of-mass (COM) measurements to recover a surrogate respiratory signal from finely sampled (100ms) single photon emission computed tomography (SPECT) projection data derived from list-mode acquisitions. For our initial evaluation, we acquired list-mode projection data from an anthropomorphic cardiac phantom mounted on a Quasar respiratory motion platform simulating 15mm amplitude respiratory motion. We also selected 302 consecutive patients (138 males, 164 females) with list-mode acquisitions, external respiratory motion tracking, and written consent to evaluate the clinical efficacy of our data-driven approach. Linear regression, Pearson's correlation coefficient (r), and standard error of the estimates (SEE) between the respiratory signals obtained with a visual tracking system (VTS) and COM measurements were calculated for individual projection data sets and for the patient group as a whole. Both the VTS- and COM-derived respiratory signals were used to estimate and correct respiratory motion. The reconstruction for six-degree of freedom rigid-body motion estimation was done in two ways: (1) using three iterations of ordered-subsets expectation-maximization (OSEM) with four subsets (16 projection angles per subset), or 12 iterations of maximum-likelihood expectation-maximization (MLEM). Respiratory motion compensation was done employing either OSEM with 16 subsets (four projection angles per subset) and five iterations or MLEM and 80 iterations, using the two respiratory estimates, respectively. Polar map quantification was also performed, calculating the percentage count difference (%Diff) between polar maps without and with respiratory motion included. Average % Diff was calculated in 17 segments (defined according to ASNC Guidelines). Paired t-tests were used to determine significance (p-values). The r-value calculated when comparing the VTS and COM respiratory signals varied widely between -0.01 and 0.96 with an average of 0.70, while the SEE varied between 0.80 and 6.48mm with an average of 2.05mm for our patient set, while the same values for the one anthropomorphic phantom acquisition are 0.91 and 1.11mm, respectively. A comparison between the respiratory motion estimates for VTS and COM in the S-I direction yielded an r=0.90 (0.94), and an SEE of 1.56mm (1.20mm) for OSEM (MLEM), respectively. Bland-Altman plots and calculated intraclass correlation coefficients also showed excellent agreement between the VTS and COM respiratory motion estimates. Average S-I respiratory estimates for the VTS (COM) were 9.04 (9.2mm) and 9.01mm (9.14mm) for the OSEM and MLEM, respectively. The paired t-test approached significance when comparing VTS and COM estimated respiratory signals with p-values of 0.069 and 0.051 for OSEM and MLEM. The respiratory estimates from the anthropomorphic cardiac phantom experiment using the VTS (COM) were 12.62 (14.10mm) and 12.55mm (14.29mm) for OSEM and MLEM, respectively. Polar map quantification yielded average % Diff consistently better when employing VTS-derived respiratory estimates to correct for respiration compared to the COM-derived estimates. The results indicate that our COM method has the potential to provide an automated data-driven correction of cardiac respiratory motion without the drawbacks of our VTS methodology. However, it is not generally equivalent to the VTS method in extent of correction.

Challenges of gated myocardial perfusion SPECT processing

The paper provides an in-depth look at gated myocardial perfusion single photon emission computed tomography (SPECT) data processing. Attention paid to several unmentioned subjects of the quantitative analysis of gated myocardial perfusion SPECT data. The article considers several options in the construction process of the ellipsoid coordinate system of the left ventricle (LV). Mathematical representation of polar maps is given. Formulas of the regional parameters calculation are proposed. Issues of phase analysis are explored.

SPECT Functional Neuroimaging Distinguishes Adult Attention Deficit Hyperactivity Disorder From Healthy Controls in Big Data Imaging Cohorts.

Background: The diagnosis of attention deficit hyperactivity disorder (ADHD) relies on history and observation, as no reliable biomarkers have been identified. In this study, we compared a large single diagnosis group of patients with ADHD (combined, inattentive, and hyperactive) to healthy controls using brain perfusion single-photon emission computed tomography (SPECT) imaging to determine specific brain regions which could serve as potential biomarkers to reliably distinguish ADHD.Methods: In a retrospective analysis, subjects (n = 1,135) were obtained from a large multisite psychiatric database, where resting state (baseline) and on-task SPECT scans were obtained. Only baseline scans were analyzed in the present study. Subjects were separated into two groups – Group 1 (n = 1,006) was composed of patients who only met criteria for ADHD with no comorbid diagnoses, while a control group (n = 129) composed of individuals who did not meet criteria for any psychiatric diagnosis, brain injury, or substance use served as a non-matched control. SPECT regions of interests (ROIs) and visual readings were analyzed using binary logistic regression. Predicted probabilities from this analysis were inputted into a Receiver Operating Characteristic analysis to identify sensitivity, specificity, and accuracy.Results: The baseline ROIs and visual readings show significant separations from healthy controls. Sensitivity of the visual reads was 100% while specificity was >97%. The sensitivity and specificity of the post-hoc ROI analysis were both 100%. Decreased perfusion was primarily seen in the orbitofrontal cortices, anterior cingulate gyri, areas of the prefrontal cortices, basal ganglia, and temporal lobes. In addition, ROI analysis revealed some unexpected areas with predictive value in distinguishing ADHD, such as cerebellar subregions and portions of the temporal lobes.Conclusions: Brain perfusion SPECT distinguishes adult ADHD patients without comorbidities from healthy controls. Areas which were highly significantly different from control and thus may serve as biomarkers in baseline SPECT scans included: medial anterior prefrontal cortex, left anterior temporal lobe, and right insular cortex. Future studies of these potential biomarkers in ADHD patients with comorbidities are warranted.

De Novo Cerebral Microbleeds and Cognitive Decline in Cerebral Hyperperfusion After Direct Revascularization for Adult Moyamoya Disease

ObjectivesAdult patients with moyamoya disease (MMD) occasionally develop cognitive decline due to cerebral hyperperfusion following direct revascularization surgery. However, how the hyperperfusion phenomenon contributes to declines in cognitive function remains unclear. The present supplementary analysis of a prospective study aimed to determine whether cerebral hyperperfusion following direct revascularization surgery for adult MMD with ischemic presentation and misery perfusion leads to development of de novo cerebral microbleeds (CMBs) and whether postoperative cognitive decline is related to these CMBs. Materials and MethodsIn total, 32 patients who underwent direct revascularization surgery also underwent T2*-weighted magnetic resonance imaging (T2*WI) and neuropsychological testing before and 2 months after surgery. Development of cerebral hyperperfusion and hyperperfusion syndrome following surgery was defined based on brain perfusion single-photon emission computed tomography (SPECT) findings and clinical symptoms. ResultsCerebral hyperperfusion on brain perfusion SPECT (95% confidence interval [CI], 1.1–10.8; p = 0.0175) or cerebral hyperperfusion syndrome (95%CI, 1.3–15.3; p = 0.0029) was significantly associated with postoperatively increased CMBs on T2*WI. Postoperatively increased CMBs were significantly associated with postoperative cognitive decline (95%CI, 1.8–20.4, p = 0.0041). For patients with cerebral hyperperfusion on brain perfusion SPECT, the incidence of postoperative cognitive decline was significantly greater in patients with than in those without postoperatively increased CMBs (p = 0.0294). ConclusionsCerebral hyperperfusion following direct revascularization surgery for adult MMD with ischemic presentation and misery perfusion contributes to the development of de novo CMBs and postoperative cognitive decline is related to these CMBs.

Diagnostic Value of Single-Photon Emission Tomography Stress Test in Patients With Suspected Coronary Artery Disease in Saudi Arabia.

BackgroundInvasive coronary angiography (ICA) is the gold standard procedure for the diagnosis of coronary artery disease (CAD). ICA allows for clear visualization of the coronary arterial blood flow. Single-photon emission computed tomography (SPECT) is currently in widespread use to non-invasively evaluate patients known or suspected of coronary artery disease (CAD). This study aimed to examine the association between (SPECT) stress test and elective ICA in terms of diagnostic value in patients suspected of coronary artery disease at the King Faisal Cardiac Center (KFCC), Jeddah, Saudi Arabia.MethodsThis study is a retrospective diagnostic validation study using a consecutive sampling technique to select the study sample at KFCC. The study included all patients who presented with chest pain that were investigated with either exercise or pharmacologic myocardial perfusion SPECT study followed by elective ICA within six months from January 2015 to January 2020.ResultsA total of 207 patients met the inclusion criteria, where 43% (n = 90) of patients were females and 57% (n = 117) were males; 68% (n = 141) of the patients had both test results concordant (both SPECT and ICA results were in agreement). In 32% of the patients (n = 66), there was a discordant result (discrepant result between SPECT and ICA). SPECT had a sensitivity of 92.4% and a specificity of 26.3%. SPECT had a negative predictive value of 0.68 and a positive predictive value of 0.66 compared to ICA. There was a low degree of reliability between SPECT and ICA.ConclusionReliability between the SPECT and ICA in exclusion of significant CAD is high. The rate of false-positive tests was high while the accuracy of SPECT in detecting CAD in patients with diabetes and hypertension was high. The overall reliability of SPECT to ICA in the Saudi population was low.

Post-reconstruction attenuation correction for SPECT myocardium perfusion imaging facilitated by deep learning-based attenuation map generation

BackgroundAttenuation correction can improve the quantitative accuracy of single-photon emission computed tomography (SPECT) images. Existing SPECT-only systems normally can only provide non-attenuation corrected (NC) images which are susceptible to attenuation artifacts. In this work, we developed a post-reconstruction attenuation correction (PRAC) approach facilitated by a deep learning-based attenuation map for myocardial perfusion SPECT imaging. MethodsIn the PRAC method, new projection data were estimated via forwardly projecting the scanner-generated NC image. Then an attenuation map, generated from NC image using a pretrained deep learning (DL) convolutional neural network, was incorporated into an offline reconstruction algorithm to obtain the attenuation-corrected images from the forwardly projected projections. We evaluated the PRAC method using 30 subjects with a DL network trained with 40 subjects, using the vendor-generated AC images and CT-based attenuation maps as the ground truth. ResultsThe PRAC methods using DL-generated and CT-based attenuation maps were both highly consistent with the scanner-generated AC image. The globally normalized mean absolute errors were 1.1% ± .6% and .7% ± .4% and the localized absolute percentage errors were 8.9% ± 13.4% and 7.8% ± 11.4% in the left ventricular (LV) blood pool, respectively, and − 1.3% ± 8.0% and − 3.8% ± 4.5% in the LV myocardium for PRAC methods using DL-generated and CT-based attenuation maps, respectively. The summed stress scores after PRAC using both attenuation maps were more consistent with the ground truth than those of the NC images. ConclusionWe developed a PRAC approach facilitated by deep learning-based attenuation maps for SPECT myocardial perfusion imaging. It may be feasible for this approach to provide AC images for SPECT-only scanner data.

Regional cerebral perfusion in patients with amnestic mild cognitive impairment: effect of cerebral small vessel disease.

To explore the effort of cerebral small vessel disease (CSVD) on regional cerebral perfusion in patients with mild cognitive impairment (MCI) using NeuroGam™ software and evaluate the capability of brain perfusion single photon emission computed tomography (SPECT) in distinguishing MCI with and without CSVD. 34 amnestic MCI subjects entered this study, conducting neuropsychological tests, MRI and 99mTechnetium ethyl cystine dimer brain perfusion SPECT imaging. All subjects were divided into those with CSVD and those without CSVD. Perfusion value was measured with Brodmann area (BA) mapping in these two groups. Automated software (NeuroGam™) was used for semi-quantitative analyses of perfusion value and comparison with normal database. Compared with normal database, perfusion levels in BAs 23-left, 28 and 36-left of MCI without CSVD group had great deviations, while perfusion levels in BAs 21, 23, 24, 25, 28, 36, 38 and 47-left of MCI with CSVD group had great deviations. Furthermore, compared with CSVD group, there was significantly lower perfusion value in BA 7-left (P < 0.001) in MCI without CSVD group. CSVD could interact with pathological changes related to AD, exacerbating hypoperfusion in BAs 21, 23, 28, 36, 38 while compensating for cerebral blood perfusion disorder in BA 7-left in MCI patients. Meanwhile, MCI patients with CSVD shared similar hypoperfusion with vascular cognitive impairment (VCI) in BAs 24, 25 and 47L. Brain perfusion SPECT may help improve our ability to differentiate MCI with and without CSVD.

Assessment of Impaired Cerebrovascular Reactivity in Chronic Cerebral Ischemia using Intravoxel Incoherent Motion Magnetic Resonance Imaging

BackgroundThe severity of chronic cerebral ischemia can be assessed using cerebrovascular reactivity (CVR) to acetazolamide (ACZ) challenge, which is measured by single-photon emission computed tomography (SPECT); however, this is an invasive method. We investigated whether intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) can assess impaired CVR in preoperative patients with chronic cerebral ischemia and compared it to SPECT-CVR. MethodsForty-seven patients with unilateral cervical carotid artery stenosis underwent diffusion-weighted MRI with 11 b-values in the range of 0–800 s/mm2 and cerebral perfusion SPECT with the ACZ challenge. The perfusion fraction (f) and diffusion coefficient (D) of the IVIM parameters were calculated using a bi-exponential model. The f and D values and these ratios of the ipsilateral middle cerebral artery territory against the contralateral side were compared with the CVR values of the affected side calculated from the SPECT data. ResultsThe IVIM-f and D values in the affected side were significantly higher than those in the unaffected side (median: 7.74% vs. 7.45%, p = 0.027; 0.816 vs. 0.801 10−3mm2/s, p < 0.001; respectively). However, there were no significant correlations between the f or D values and SPECT-CVR values in the affected side. In contrast, the f ratio showed a moderate negative correlation with the SPECT-CVR values (r = -0.40, p = 0.006) and detected impaired CVR (< 18.4%) with a sensitivity/specificity of 0.71/0.90. ConclusionThe IVIM perfusion parameter, f, can noninvasively assess impaired CVR with high sensitivity and specificity in patients with unilateral cervical carotid artery stenosis.

Multimodal assessment of regional gray matter integrity in early relapsing-remitting multiple sclerosis patients with normal cognition: a voxel-based structural and perfusion approach.

There is increasing evidence that gray matter (GM) impairment is strongly associated with clinical performance decline. We aim to perform a voxelwise analysis between regional GM (rGM) perfusion and structural abnormalities in early relapsing-remitting multiple sclerosis patients with normal cognition (RRMS-IC) and explore clinical correlate of early rGM abnormalities. We studied 14 early RRMS-IC patients and 14 healthy age- and sex-matched controls. Brain perfusion single photon emission computed tomography (SPECT), structural MRI, and a comprehensive neuropsychological examination were acquired from all participants. Neuropsychological tests include expanded disability status scale, minimal mental status examination, short physical performance battery, Wechsler memory scale, and quick smell test. Voxel-based morphometry was used for analyzing SPECT and T1-MR images to identify rGM hypoperfusion and atrophy, respectively (RRMS-IC vs controls (group analysis), and also, each patient vs controls (individual analysis)) (p < 0.001). Then, anatomical location of impaired regions was acquired by automated anatomical labeling software. There was no significant difference in total GM volume between RRMS-IC and healthy controls, however, rGM atrophy and hypoperfusion were detected. Individual analysis revealed more rGM impairment compared with group analysis. rGM hypoperfusion was more extensive rather than rGM atrophy in RRMS-IC. There was no spatial association between rGM atrophy and rGM hypoperfusion (p > 0.05). rGM abnormalities correlated with several relevant minimal clinical deficits. Lack of spatial correlation between rGM atrophy and hypoperfusion might suggest that independent mechanisms might underlie atrophy and hypoperfusion. Perfusion SPECT may provide supplementary information along with MRI. Association between rGM atrophy and rGM hypoperfusion and their clinical significance in early RRMS-IC is not well described yet. Our study showed that there is spatial dissociation between rGM atrophy and rGM hypoperfusion, suggesting that different mechanisms might underlie these pathologies.