Combining anatomical and biochemical markers in the detection and risk stratification of coronary artery disease.

AIM: We aimed to test the hypothesis if combining coronary artery calcium score (Ca-score) as a quantitative anatomical marker of coronary atherosclerosis with high-sensitive cardiac troponin as a quantitative biochemical marker of myocardial injury provided incremental value in the detection of functional relevant CAD (fCAD) and risk stratification. METHODS AND RESULTS: Consecutive patients undergoing myocardial perfusion SPECT (MPS) without prior CAD were enrolled. The diagnosis of fCAD was based on the presence of ischemia on MPS and coronary angiography- fCAD was centrally adjudicated in the diagnostic and prognostic domain. Diagnostic accuracy was evaluated using the area under receiver-operating characteristic curve. The composite of cardiovascular death and non-fatal acute myocardial infarction (AMI) within 730 days were the primary prognostic endpoints.Among 1715 patients eligible for the diagnostic analysis, 399 patients had fCAD. The combination of Ca-Score and hs-cTnT had good diagnostic accuracy for the diagnosis of fCAD, AUC 0.79 (95 % CI 0.77-0.81), but no incremental value compared to the Ca-score alone (AUC 0.79 (95%CI 0.77-0.81, p=0.965). Similar results were observed using hs-cTnI (AUC 0.80, 95%CI 0.77-0.82) instead of hs-cTnT.Among 1709 patients (99.7%) with available follow-up, 59 patients (3.5%) suffered the composite primary prognostic endpoint (nonfatal AMI n=34, CV death n=28).Both, Ca-score and hs-cTnT had independent prognostic value. Increased risk was restricted to patients with elevation in both markers. CONCLUSION: The combination of the Ca-score with hs-cTnT increases the prognostic accuracy for future events defining fCAD, but does not provide incremental value versus the Ca-Score alone for the diagnosis of fCAD.

Spatial-temporal V-Net for automatic segmentation and quantification of right ventricle on gated myocardial perfusion SPECT images.

BACKGROUND: Functional assessment of right ventricle (RV) using gated myocardial perfusion single-photon emission computed tomography (MPS) heavily relies on the precise extraction of right ventricular contours. PURPOSE: In this paper, we present a new deep-learning-based model integrating both the spatial and temporal features in gated MPS images to perform the segmentation of the RV epicardium and endocardium. METHODS: By integrating the spatial features from each cardiac frame of the gated MPS and the temporal features from the sequential cardiac frames of the gated MPS, we developed a Spatial-Temporal V-Net (ST-VNet) for automatic extraction of RV endocardial and epicardial contours. In the ST-VNet, a V-Net is employed to hierarchically extract spatial features, and convolutional long-term short-term memory (ConvLSTM) units are added to the skip-connection pathway to extract the temporal features. The input of the ST-VNet is ECG-gated sequential frames of the MPS images and the output is the probability map of the epicardial or endocardial masks. A Dice similarity coefficient (DSC) loss which penalizes the discrepancy between the model prediction and the manual annotation was adopted to optimize the segmentation model. RESULTS: Our segmentation model was trained and validated on a retrospective dataset with 45 subjects, and the cardiac cycle of each subject was divided into eight gates. The proposed ST-VNet achieved a DSC of 0.8914 and 0.8157 for the RV epicardium and endocardium segmentation, respectively. The mean absolute error, the mean squared error, and the Pearson correlation coefficient of the RV ejection fraction (RVEF) between the manual annotation and the model prediction were 0.0609, 0.0830, and 0.6985. CONCLUSION: Our proposed ST-VNet is an effective model for RV segmentation. It has great promise for clinical use in RV functional assessment.

Clinical validation of an AI-based automatic quantification tool for lung lobes in SPECT/CT.

BACKGROUND: Lung lobar ventilation and perfusion (V/Q) quantification is generally obtained by generating planar scintigraphy images and then imposing three equally sized regions of interest on the data of each lung. This method is fast but not as accurate as SPECT/CT imaging, which provides three-dimensional data and therefore allows more precise lobar quantification. However, the manual delineation of each lobe is time-consuming, which makes SPECT/CT incompatible with the clinical workflow for V/Q estimation. An alternative may be to use artificial intelligence-based auto-segmentation tools such as AutoLung3D (Siemens Healthineers, Knoxville, USA), which automatically delineate the lung lobes on the CT data acquired with the SPECT data. The present study assessed the clinical validity of this approach relative to planar scintigraphy and manual quantification in SPECT/CT. METHODS: The Autolung3D software was tested on the retrospective SPECT/CT data of 43 patients who underwent V/Q scintigraphy with 99mTc-macroaggregated albumin and 99mTc-labeled aerosol. It was compared to planar scintigraphy and SPECT/CT using the manual quantification method in terms of relative lobar V/Q quantification values and interobserver variability. RESULTS: The three methods provided similar V/Q estimates for the left lung lobes and total lungs. However, compared to the manual SPECT/CT method, planar scintigraphy yielded significantly higher estimates for the middle right lobe and significantly lower estimates for the superior and inferior right lobes. The estimates of the manual and automated SPECT/CT methods were similar. However, the post-processing time in the automated method was approximately 5 min compared to 2 h for the manual method. Moreover, the automated method associated with a drastic reduction in interobserver variability: Its maximal relative standard deviation was only 5%, compared to 23% for planar scintigraphy and 19% for the manual SPECT/CT method. CONCLUSIONS: This study validated the AutoLung3D software for general clinical use since it rapidly provides accurate lobar quantification in V/Q scans with markedly less interobserver variability than planar scintigraphy or the manual SPECT/CT method.

3D-Quantitated Single Photon Emission Computed Tomography/Computed Tomography: Impact on intended Management Compared to Lung Perfusion Scan in Marginal Candidates for Pulmonary Resection.

OBJECTIVES: Based on previous studies, single-photon emission computed tomography/computed tomography (SPECT/CT) has been proven more accurate and reproducible than planar lung perfusion scintigraphy to assess lobar perfusion. However, the impact of 3D-quantitated SPECT/CT on intended management in functionally marginal candidates for pulmonary resection is unknown. The evaluation of this impact was the main aim of this study. METHODS: Consecutive candidates for lung resection underwent preoperative evaluation according to ERS/ESTS Algorithm and underwent preoperative lung perfusion imaging. The lobar contribution to the total lung perfusion was estimated using established planar scintigraphic methods and 3-dimensional quantitative SPECT/CT method (CT Pulmo3D and xSPECT-Quant, Siemens). The difference in estimated lobar perfusion with resulting changes in predicted postoperative (ppo) lung function and extent of lung resection were analyzed to reveal possible changes in operability. In-hospital outcome was assessed. RESULTS: One hundred twenty patients (46 females) were enrolled. The mean age (±SD) of patients was 68 ± 9 years, target lesions were in upper lobes in 57.7% and in lower lobes in 33.5%. The median FEV1 (forced expiratory volume in 1 second) was 70.5% (IQR 52-84) and median DLCO (diffusion capacity of lung for carbon monoxide) was 56.6% [47.1-67.4]. The planar posterior oblique method, compared to 3D-quantitated SPECT/CT, underestimated the perfusion of upper lobes by a median difference of 5% (right [2-9], left [2.5-8]; P = <.0001), while it overestimated the perfusion of lower lobes (left by 4% [2-7], right by 6% [2-9]; P = <.0001). In contrast to planar scintigraphy-based evaluation, 4 patients (3.3%), all with upper lobe lesions, were classified as inoperable when 3D-quantitated SPECT/CT was used for calculation of the ppo lung function. CONCLUSIONS: In selected patients with upper lobe lesions, 3D-quantitated SPECT/CT would have changed the treatment strategy from operable to inoperable. Importantly, postoperative mortality in this particular subgroup was disproportionally high. 3D-quantitated SPECT/CT shall be further evaluated as it might improve preoperative risk stratification in functionally marginal candidates.

Quantitative analysis of lung function and airway remodeling using ventilation/perfusion single photon emission tomography/computed tomography and HRCT in patients with chronic obstructive pulmonary disease and asthma.

OBJECTIVE: To investigate the role of V/P SPECT/CT and HRCT quantitative parameters in evaluating COPD and asthma disease severity, airway obstructivity-grade, ventilation and perfusion distribution patterns, airway remodeling, and lung parenchymal changes. METHOD: Fifty-three subjects who underwent V/P SPECT/CT, HRCT, and pulmonary function tests (PFTs) were included. Preserved lung ventilation (PLVF), perfusion function (PLPF), airway obstructivity-grade (OG), proportion of anatomical volume, ventilation and perfusion contribution of each lobe, and V/P distribution patterns were evaluated using V/P SPECT/CT. The quantitative parameters of HRCT included CT bronchial and CT pulmonary function parameters. In addition, the correlation and difference of V/P SPECT/CT-, HRCT-, and PFT-related parameters were compared. RESULTS: There was a statistically significant difference between severe asthma and severe-very severe COPD in CT bronchial parameters, like WA, LA and AA, in the lung segment airways (P < 0.05). CT bronchial parameters, like as WT and WA, were statistically significant (p < 0.05) among asthma patients. The EI of severe-very severe COPD was different from that of the disease severity groups in asthma patients (P < 0.05). The airway obstructivity-grade, PLVF and PLPF differed significantly among the severe-very severe COPD and mild-moderate asthma patients (P < 0.05). And the PLPF was statistically significant among the disease severity groups in asthma and COPD (P < 0.05). OG and PLVF, PLPF, and PFT parameters were significantly correlated, with the FEV1 correlation being the most significant (r = - 0.901, r = 0.915, and r = 0.836, respectively; P < 0.01). There was a strong negative correlation between OG and PLVF (r = - 0.945) and OG and PLPF (r = - 0.853) and a strong positive correlation between PLPF and PLVF (r = 0.872). In addition, OG, PLVF, and PLPF were moderately to strongly correlated with CT lung function parameters (r = - 0.673 to - 0.839; P < 0.01), while lowly to moderately correlated with most CT bronchial parameters (r = - 0.366 to - 0.663, P < 0.01). There were three different V/P distribution patterns, including matched, mismatched, and reverse mismatched patterns. Last, the CT volume overestimated the contribution in the upper lobes and underestimated the lower lobes' contribution to overall function. CONCLUSIONS: Quantitative assessment of ventilation and perfusion abnormalities and the degree of pulmonary functional loss by V/P SPECT/CT shows promise as an objective measure to assess the severity of disease and lung function to guide localized treatments. There are differences between HRCT parameters and SPECT/CT parameters among the disease severity groups in asthma and COPD, which may enhance, to some extent, the understanding of complex physiological mechanisms in asthma and COPD.

A new method incorporating deep learning with shape priors for left ventricular segmentation in myocardial perfusion SPECT images.

Accurate segmentation of the left ventricle (LV) is crucial for evaluating myocardial perfusion SPECT (MPS) and assessing LV functions. In this study, a novel method combining deep learning with shape priors was developed and validated to extract the LV myocardium and automatically measure LV functional parameters. The method integrates a three-dimensional (3D) V-Net with a shape deformation module that incorporates shape priors generated by a dynamic programming (DP) algorithm to guide its output during training. A retrospective analysis was performed on an MPS dataset comprising 31 subjects without or with mild ischemia, 32 subjects with moderate ischemia, and 12 subjects with severe ischemia. Myocardial contours were manually annotated as the ground truth. A 5-fold stratified cross-validation was used to train and validate the models. The clinical performance was evaluated by measuring LV end-systolic volume (ESV), end-diastolic volume (EDV), left ventricular ejection fraction (LVEF), and scar burden from the extracted myocardial contours. There were excellent agreements between segmentation results by our proposed model and those from the ground truth, with a Dice similarity coefficient (DSC) of 0.9573 ± 0.0244, 0.9821 ± 0.0137, and 0.9903 ± 0.0041, as well as Hausdorff distances (HD) of 6.7529 ± 2.7334 mm, 7.2507 ± 3.1952 mm, and 7.6121 ± 3.0134 mm in extracting the LV endocardium, myocardium, and epicardium, respectively. Furthermore, the correlation coefficients between LVEF, ESV, EDV, stress scar burden, and rest scar burden measured from our model results and the ground truth were 0.92, 0.958, 0.952, 0.972, and 0.958, respectively. The proposed method achieved a high accuracy in extracting LV myocardial contours and assessing LV functions.

Identification of resting-state networks using dynamic brain perfusion SPECT imaging: A fSPECT case report.

Connectivity studies with nuclear medicine systems are scarce in literature. They mainly employ PET imaging and group level analyses due to the low temporal resolution of PET and especially SPECT imaging. Our current study analyses connectivity at an individual level using dynamic SPECT imaging, which has been enabled by the improved temporal resolution performances provided by the 360°CZT cameras. We present the case of an 80-year-old man referred for brain perfusion SPECT imaging for cognitive disorders for whom a dynamic SPECT acquisition was performed utilizing a 360°CZT camera (temporal sampling of 15 frames × 3 s, 10 frames × 15 s, 14 frames × 30 s), followed by a conventional static acquisition of 15 m. Functional SPECT connectivity (fSPECT) was assessed through a seed correlation analysis and 5 well-known resting-state networks were identified: the executive, the default mode, the sensory motor, the salience, and the visual networks. This case report supports the feasibility of fSPECT imaging to identify well known resting-state networks, thanks to the novel properties of a 360°CZT camera, and opens the way to the development of more dedicated functional connectivity studies using brain perfusion SPECT imaging.

Adjustment of acquisition arc in cardiac malposition during myocardial perfusion SPECT imaging: computer simulation based on deterministic modeling.

OBJECTIVES: To simulate cardiac malpositions, leftward and rightward shift and dextrocardia, and also to compare distribution of activity of septal and lateral walls of left ventricle acquired in standard acquisition arc and after relevant adjustment. METHODS: In this study, digital phantoms with cardiac malpositions are designed and procedure of acquisition of scan in standard arc (from right anterior oblique to left posterior oblique) and adjusted acquisition arc is simulated. The three situations of malposition including leftward and rightward shift and dextrocardia are considered. For all types, acquisition is conducted in standard and then adjusted arcs (from anterior to posterior and also from right to left for leftward and rightward shifts, respectively, and for dextrocardia, from left anterior oblique to right posterior oblique). All obtained projections are reconstructed using the algorithm of filtered back projection. During forward projection to obtain sinograms, radiation attenuation is also modeled by incorporation of a simplified transmission map to emission map. The resulting tomographic slices of the LV (septum, apex, and lateral wall) are presented visually and are compared by plotting intensity profiles of the walls. Finally, normalized error images are also computed. All the computations are performed in MATLAB software package. RESULTS: In transverse slice, septum and lateral wall are attenuated progressively from apex, which is closer to the camera, to the base in similar fashion. In tomographic slices of standard acquisition arc, the septum shows remarkably higher activity compared to lateral wall. However, after adjustment, both seems equally intense and progressively being attenuated from apex to base, similar to that found in phantom with normally positioned heart. Likewise, for the phantom with rightward shift, when the scanning was done in standard arc, the septum is more intense than the lateral wall. And similarly, adjustment of the arc renders both walls equally intense. In dextrocardia, level of attenuation of basal parts of septum and lateral wall is higher in 360° arc compared to adjusted 180° arc. CONCLUSION: Adjustment of acquisition arc exerts perceptible changes in distribution of activity over LV walls which are more compatible with normally positioned heart.

Non-dominant right coronary artery (RCA) is associated with suspected inferior ischemia on SPECT in patients without significant coronary artery disease (CAD).

OBJECTIVE: There is a huge uncertainty in the medical community regarding the significance of non-dominant right coronary artery (RCA) in patients with inferior wall ischemia on myocardial perfusion single-photon emission computed tomography (SPECT). The purpose of this study is to determine the effect of non-dominant RCA on myocardial perfusion SPECT (MPS) with respect to the misleading detection of ischemia in the inferior wall of the myocardium. METHODS: This is a retrospective study of 155 patients, who had undergone elective coronary angiography owing to an indication of inferior wall ischemia by MPS between 2012 and 2017. Patients were divided into two groups based on the coronary dominance: group 1 (n = 107), if RCA is the dominant artery, and group 2 (n = 48), if there are dominance of left artery and codominance of both arteries. Obstructive CAD was diagnosed in the case of stenosis that had severity greater than 50%. The positive predictive value (PPV), which was calculated as per the correlation between the inferior wall ischemia in MPS and obstruction level in RCA, was compared in both groups. RESULTS: Majority of patients were male (109, 70%) and the mean age was 59.5 ± 10.2. There were 45 patients with obstructive RCA disease (PPV: 42%) among 107 patients in group 1, whereas there were only 8 patients with obstructive coronary artery disease (CAD) in RCA among 48 patients in group 2, (PPV: 16% and p = 0.004). CONCLUSIONS: The results demonstrated that non-dominant RCA is associated with false-positive detection of inferior wall ischemia via MPS.

Incremental Value of Exercise ECG to Myocardial Perfusion Single-Photon Emission Computed Tomography for Prediction of Cardiac Events.

Background Both myocardial perfusion single-photon emission computed tomography (MPS) and exercise ECG (Ex-ECG) carry prognostic information in patients with stable chest pain. However, it is not fully understood if combining the findings of MPS and Ex-ECG improves risk prediction. Current guidelines no longer recommend Ex-ECG for diagnostic evaluation of chronic coronary syndrome, but Ex-ECG could still be of incremental prognostic importance. Methods and Results This study comprised 908 consecutive patients (age 63.3±9.4 years, 49% male) who performed MPS with Ex-ECG. Subjects were followed for 5 years. The end point was a composite of cardiovascular death, acute myocardial infarction, unstable angina, and unplanned percutaneous coronary intervention. National registry data and medical charts were used for end point allocation. Combining the findings of MPS and Ex-ECG resulted in concordant evidence of ischemia in 72 patients or absence of ischemia in 634 patients. Discordant results were found in 202 patients (MPS-/Ex-ECG+, n=126 and MPS+/Ex-ECG-, n=76). During follow-up, 95 events occurred. Annualized event rates significantly increased across groups (MPS-/Ex-ECG- =1.3%, MPS-/Ex-ECG+ =3.0%, MPS+/Ex-ECG- =5.1% and MPS+/Ex-ECG+ =8.0%). In multivariable analyses MPS was the strongest predictor regardless of Ex-ECG findings (MPS+/Ex-ECG-, hazard ratio [HR], 3.0, P=0.001 or MPS+/Ex-ECG+, HR,4.0, P<0.001). However, an abnormal Ex-ECG almost doubled the risk in subjects with normal MPS (MPS-/Ex-ECG+, HR, 1.9, P=0.04). Conclusions In patients with chronic coronary syndrome, combining the results from MPS and Ex-ECG led to improved risk prediction. Even though MPS is the stronger predictor, there is an incremental value of adding data from Ex-ECG to MPS, especially in patients with normal MPS.

Neuroblastoma-related severe hypoperfusion in the cerebellum of an infant: A case of opsoclonus-myoclonus syndrome.

A 2-year-old girl started to wobble without any specific triggers, so the patient was admitted to our hospital's pediatric department. The entire cerebellum showed severe atrophy on MRI and much lower uptake than that in the cerebral cortex on perfusion SPECT. The diagnosis of opsoclonus-myoclonus syndrome (OMS) was suspected. MRI visualized a small mass behind the inferior vena cava. Although its uptake on I-123 MIBG scintigraphy was inconclusive, the mass was surgically removed, and the diagnosis of neuroblastoma was pathologically confirmed. OMS is one of the paraneoplastic neurological syndromes with cerebellar ataxia, myoclonus of the trunk and extremities, and opsoclonus as its main symptoms. Approximately 50% of children cases with OMS are associated with neuroblastoma. The prognosis for neuroblastoma itself with OMS is relatively good, but the neurological prognosis is very poor. If there is decreased blood flow in the cerebellum of an infant, it may be necessary to search for neuroblastoma.

Deep-learning-based estimation of attenuation map improves attenuation correction performance over direct attenuation estimation for myocardial perfusion SPECT.

BACKGROUND: Deep learning (DL)-based attenuation correction (AC) is promising to improve myocardial perfusion (MP) SPECT. We aimed to optimize and compare the DL-based direct and indirect AC methods, with and without SPECT and CT mismatch. METHODS: One hundred patients with different 99mTc-sestamibi activity distributions and anatomical variations were simulated by a population of XCAT phantoms. Additionally, 34 patients 99mTc-sestamibi stress/rest SPECT/CT scans were retrospectively recruited. Projections were reconstructed by OS-EM method with or without AC. Mismatch between SPECT and CT images was modeled. A 3D conditional generative adversarial network (cGAN) was optimized for two DL-based AC methods: (i) indirect approach, i.e., non-attenuation corrected (NAC) SPECT paired with the corresponding attenuation map for training. The projections were reconstructed with the DL-generated attenuation map for AC; (ii) direct approach, i.e., NAC SPECT paired with the corresponding AC SPECT for training to perform direct AC. RESULTS: Mismatch between SPECT and CT degraded DL-based AC performance. The indirect approach is superior to direct approach for various physical and clinical indices, even with mismatch modeled. CONCLUSION: DL-based estimation of attenuation map for AC is superior and more robust to direct generation of AC SPECT.

Diagnosis, performance and added value of assessing ventricular dyssynchrony by phase analysis in patients with three-vessel disease: A single-center cross-sectional study in Mexico.

BACKGROUND: Three-vessel disease (3VD) is a cardiovascular disorder that affects the three main coronary arteries. Gated myocardial perfusion SPECT (GMPS) evaluates ventricular function, synchrony, and myocardial perfusion. However, the diagnostic performance of GMPS parameters to assess 3VD has not been fully explored. AIMS: To assess the univariate performance capacity of GMPS parameters, and to evaluate whether phase parameters could provide additional predictive value for the detection of patients with 3VD compared to control subjects. METHODS: We designed paired retrospective samples of GMPS images of patients with 3VD (stenosis > 70% of left anterior descending, right coronary, and circumflex coronary arteries) and without 3VD. A GMPS in rest-stress protocol was performed using 99mTc-Sestamibi and thallium and analyzed with the 3D method. Area under the receiver-operating characteristic curves (AUROC), decision curve analyses and diagnostic test performance were obtained for univariable analyses and stepwise binomial logistic regression for multivariable performance. RESULTS: 474 Patients were included: 237 with 3VD (84% males, mean age 61.7 ± 9.9 years) and 237 with normal GMPS (51% women, mean age 63.8 ± 10.6 years). The highest AUROC for perfusion parameters were recorded for SSS, SRS and TID. For dyssynchrony parameters, both entropy and bandwidth in rest and stress phases displayed the highest AUROC and diagnostic capacity to detect 3VD. A multivariate model with SRS ≥ 4, SDS ≥ 2, TID > 1.19 and sBW ≥ 48° displayed the highest diagnostic capacity (0.923 [95% CI 0.897-0.923]) to detect 3VD. CONCLUSION: Perfusion and dyssynchrony were the parameters which were most able to discriminate patients with 3VD from those who did not have CAD.

Deep learning-based denoising in projection-domain and reconstruction-domain for low-dose myocardial perfusion SPECT.

BACKGROUND: Low-dose (LD) myocardial perfusion (MP) SPECT suffers from high noise level, leading to compromised diagnostic accuracy. Here we investigated the denoising performance for MP-SPECT using a conditional generative adversarial network (cGAN) in projection-domain (cGAN-prj) and reconstruction-domain (cGAN-recon). METHODS: Sixty-four noisy SPECT projections were simulated for a population of 100 XCAT phantoms with different anatomical variations and 99mTc-sestamibi distributions. Series of LD projections were obtained by scaling the full dose (FD) count rate to be 1/20 to 1/2 of the original. Twenty patients with 99mTc-sestamibi stress SPECT/CT scans were retrospectively analyzed. For each patient, LD SPECT images (7/10 to 1/10 of FD) were generated from the FD list mode data. All projections were reconstructed by the quantitative OS-EM method. A 3D cGAN was implemented to predict FD images from their corresponding LD images in the projection- and reconstruction-domain. The denoised projections were reconstructed for analysis in various quantitative indices along with cGAN-recon, Gaussian, and Butterworth-filtered images. RESULTS: cGAN denoising improves image quality as compared to LD and conventional post-reconstruction filtering. cGAN-prj can further reduce the dose level as compared to cGAN-recon without compromising the image quality. CONCLUSIONS: Denoising based on cGAN-prj is superior to cGAN-recon for MP-SPECT.

Post-ISCHEMIA Trial Era: Reconsideration of the Role of Nuclear Cardiology in Patients with Chronic Coronary Artery Disease.

The International Study of Comparative Health Effectiveness with Medical and Invasive Approaches (ISCHEMIA) trial has had a great impact on the management of chronic coronary artery disease (CAD). One of the implications of this trial is the importance of close patient follow-up. To improve patient prognosis, evaluation of the residual extent of ischemia after treatment may be important because several studies have shown a close relationship between residual ischemia and cardiac events. For this assessment, myocardial perfusion single-photon emission computed tomography (MPS) has been utilized and is almost the only modality. Among the participants in the ISCHEMIA trial, more than 10% were excluded due to the absence of obstructive CAD. The pathophysiology of ischemia without non-obstructive coronary artery disease (INOCA) is gaining recognition; however, diagnosis is difficult, except for the assessment of myocardial flow reserve (MFR). Myocardial perfusion positron emission tomography (PET) is the most common modality for noninvasive evaluation of MFR; however, its availability in Japan is limited. For a breakthrough in this situation, a novel gamma camera with a cadmium zinc telluride (CZT) semiconductor might be one of the solutions that enables the evaluation of MFR with a commercially available perfusion tracer, similar to PET. Another solution is a novel PET tracer with a longer half-life. Clinical trials with 18F labeled perfusion agents have been initiated in Japan, and in a few years, delivery of this perfusion tracer will result in more frequent and easier assessment of MFR.

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.

Normal and Range Value Evaluations Using Heart Risk View-Function Based on the Japanese Societyof Nuclear Medicine Working Group Database.

Background: Gated myocardial perfusion single-photon emission computed tomography (SPECT) has been used to non-invasively evaluate the left ventricular (LV) volume and function. This study aimed to measure the normal and range values for heart risk view-function (HRV-F) software using the Japanese Society of Nuclear Medicine Working Group (JSNM-WG) normal database and clarify the characteristics of the normal database. Methods:We used 206 myocardial perfusion short-axis images from the normal database. Ejection fraction (EF), end-systolic volume (ESV), end-diastolic volume (EDV), peak filling rate (PFR), 1/3 mean filling rate (MFR), time to PFR (TTPF), and TTPF divided by RR interval (TPFR/RR) were calculated. Phase parameters of 95% histogram bandwidth and standard deviation were also computed using the phase analysis. The relationships among phase parameters, LV volumes, and body surface area (BSA) were evaluated in the age group of ≤65 years. Results: Higher EF was observed in females than in males (p<0.0001). EDV and ESV were significantly higher in males than in females (p<0.0001). Additionally, PFR and 1/3 MFR significantly differed between sexes (p≤0.075). Phase parameters were higher in males than in females, and higher at stress than at rest. All diastolic parameters showed no significant differences between sexes in any age group, whereas differences have remained in phase values. Phase parameters were weakly correlated with EDV (r=0.31), ESV (r=0.43), and BSA (r=0.27), respectively. Conclusions: Mean normal and range values of the normal database were determined using the HRV-F software. The normal and range values can help diagnose gated SPECT data in patients with cardiac diseases.

Evaluation of lung perfusion by using lung perfusion SPECT and lung CT with breathing synchronization software.

BACKGROUND: Lung perfusion using 99mTc-macroaggregated albumin single-photon emission computed tomography (SPECT) and lung computed tomography (CT) is a useful modality for identifying patients with pulmonary artery embolism. However, conformity between SPECT and CT at the bottom of the lung is generally low. This study aims to investigate the progression of conformity between lung perfusion SPECT and lung CT using a breathing synchronization software. METHODS: Among 95 consecutive patients who underwent lung perfusion SPECT and lung CT within 14 days because of suspected pulmonary embolism between June 2019 and August 2020 in department of cardiovascular medicine, we identified 28 patients (73 ± 10 years) who had normal pulmonary artery on contrast lung CT. We compared lung volumes calculated using lung perfusion SPECT and lung CT as gold standard. Visual conformity between lung SPECT and lung CT was scored 0-4 (0: 0-25%, 1: 25-50%, 2: 50-75%, 3: 75-90%, 4: > 90%) by two specialists in nuclear medicine and assessed. RESULTS: The lung volume calculated from lung CT was 3749 ± 788 ml. The lung volume calculated from lung perfusion SPECT without using the breathing synchronization software was 3091 ± 610 ml. There was a significant difference between the lung volume calculated from CT and SPECT without using the breathing synchronization software (P < 0.01). The lung volume calculated from lung perfusion SPECT using the breathing synchronization software was 3435 ± 686 ml, and there was no significant difference between the lung volume calculated from CT and SPECT using the breathing synchronization software. The visual score improved with the use of breathing synchronization software (without software; 1.9 ± 0.6 vs. with software; 3.4 ± 0.7, P < 0.001). CONCLUSION: This study demonstrated that the breathing synchronization software could improve conformity between lung perfusion SPECT and lung CT.

Dual gating myocardial perfusion SPECT denoising using a conditional generative adversarial network.

PURPOSE: Dual respiratory-cardiac gating reduces respiratory and cardiac motion blur in myocardial perfusion single-photon emission computed tomography (MP-SPECT). However, image noise is increased as detected counts are reduced in each dual gate (DG). We aim to develop a denoising method for dual gating MP-SPECT images using a 3D conditional generative adversarial network (cGAN). METHODS: Twenty extended cardiac-torso phantoms with various 99m Tc-sestamibi distributions, defect characteristics, and body and organ sizes were used in the simulation, modeling six respiratory and eight cardiac gates (CGs), that is, 48 DGs for ordered subset expectation maximization reconstruction. Twenty clinical 99m Tc-sestamibi SPECT/CT datasets were re-binned into 7 respiratory gates and 8 CGs, that is, 56 DGs for maximum likelihood expectation maximization reconstruction. We evaluated the use of (i) phantoms' own datasets (patient-specific denoising [PD]) or other phantoms' datasets (cross-patient denoising) for training; (ii) the CG or the static (non-gated [NG]) data as the training references for cGAN; and (iii) cGAN as compared to conventional 3D post-reconstruction filtering, cardiac gating methods, and convolutional neural network. Normalized mean squared error, noise as assessed by normalized standard deviation, spatial blurring measured as the full-width-at-half-maximum of left ventricular wall, ejection fraction, joint correlation histogram, and defect size were analyzed as metrics of image quality. RESULTS: Training using patients' own dataset is superior to conventional training based on other patients' data. Using CG image as training reference provides a better trade-off in terms of noise and image blur as compared to the use of NG. cGAN-CG-PD provides superior performance as compared to other denoising methods for all physical and diagnostic indices evaluated in both simulation and clinical studies. CONCLUSIONS: cGAN denoising is promising for dual gating MP-SPECT based on the metrics mentioned earlier.

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

PURPOSE: 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 (100 ms) single photon emission computed tomography (SPECT) projection data derived from list-mode acquisitions. METHODS: For our initial evaluation, we acquired list-mode projection data from an anthropomorphic cardiac phantom mounted on a Quasar respiratory motion platform simulating 15 mm 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). RESULTS: 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 6.48 mm with an average of 2.05 mm for our patient set, while the same values for the one anthropomorphic phantom acquisition are 0.91 and 1.11 mm, 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 1.56 mm (1.20 mm) 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 (9.2 mm) and 9.01 mm (9.14 mm) 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 (14.10 mm) and 12.55 mm (14.29 mm) 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. CONCLUSIONS: 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.