Background: Myocardial blood flow quantification (MBF) is one of the distinctive features for cardiac PET. The MBF calculation is mostly obtained by estimating the input function from the time activity curve in dynamic scan. However, there is a substantial risk of count-loss because the high radioactivity pass through the left ventricular (LV) cavity within a short period. We aimed to determine the optimal intraventricular activity using the noise equivalent count rate (NECR) analysis with simplified phantom model.
Methods: PETCT scanner with LYSO crystal and time of flight was used for phantom study. 150 MBq/mL of ¹³N was filled in 10 mL of syringe, placed in neck phantom to imitate end-systolic small LV. 3D list-mode acquisition was repeatedly performed along radioactive decay. Net true and random count rate were calculated and compared to the theoretical activity in the syringe. NECR curve analysis was used to determine the optimal radioactive concentration.
Result: The attenuation curves showed good correlation to the theoretical activity between 20 to 370, and 370 to 740 MBq (r² = 1.0 ± 0.0001, p < 0.0001; r² = 0.99 ± 0.0001, p < 0.0001 for 20 to 370, and 370 to 740, respectively), while did not over 740 MBq (p = 0.62). NECR analysis revealed that the peak rate was at 2.9 Mcps, there at the true counts were significantly suppressed. The optimal radioactive concentration was determined as 36 MBq/mL.
Conclusion: Simulative analysis for high-dose of ¹³N using the phantom imitating small LV confirmed that the risk of count-loss was increased. The result can be useful information in assessing the feasibility of MBF quantification in clinical routine.

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Both exercise single photon emission computed tomography (SPECT) imaging and myocardial perfusion imaging with positron emission tomography produce multiple outcome variables. These include the stress electrocardiogram (ECG), visual perfusion assessment and quantitative myocardial blood flow. Bayes’ analysis using conditional probability allows the distillation of multiple test results into a single probability of disease for individual patients. This paper examines the application of conditional probability analysis to two noninvasive modalities that generate multiple outcome results: exercise ECG combined with SPECT imaging and vasodilator RB-82 positron emission tomography perfusion imaging combined with quantitative measure of absolute myocardial blood flow. In this manner, a single probability of disease incorporating all the available data is generated for an individual patient.

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Background: Due to the limitation of spatial resolution, cardiac nuclear medicine images have not been applied to feature-tracking method to automatic extraction of myocardial contours. We have successfully applied the feature-tracking method to high-resolution cine ¹³N-ammonia positron emission tomography (PET) images to calculate the regional myocardial strains. Here, we investigate the potential of ¹³N-ammonia PET-derived strain to detect ischemia-related wall motion abnormality.
Methods: Data of adenosine-stress/rest ¹³N-ammonia PET for 95 coronary artery disease patients was retrospectively analyzed. Using an original algorithm dedicated to ¹³N-ammonia PET, the longitudinal strain (LS) corresponding to the three main coronary artery territories [right coronary artery: RCA, left anterior descending artery (LAD), and left circumflex coronary artery (LCX)] was calculated from semi-automatic endocardial contours extraction on cine ¹³N-ammonia PET images of the left ventricular long-axis. The presence of ischemia in three main territories was determined from rest and stress-perfusion images.
Results: In all three coronary territories, LS at stress was significantly smaller at rest in the ischemic region RCA: -19.2±8.0% vs. -22.7±6.1%, LAD: -19.0±6.9% vs. -24.4±6.4%, LCX: -20.5%±7.6% vs. -22.6±6.9%). In contrast, in the non-ischemic region, there was no significant difference between the LS at stress and at rest. Receiver-operating-characteristic analysis revealed that using the optimal cutoff of the LS ratio of stress to rest, ischemia could be diagnosed with area under the curve of 0.82 in the RCA, 0.86 in the LAD, and 0.69 in the LCX.
Conclusions: Myocardial strain derived from endocardial feature-tracking of ¹³N-ammonia PET cine imaging is reduced in the ischemia induced by adenosine-stress. The LS ratio of stress to rest may detect wall motion abnormality related to ischemia.

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Background: The arithmetic mean of washout rate (WR) (namely, AMWR) of each segment is a commonly used algorithm for calculating WR from a polar map in single-photon emission computerized tomography (SPECT). However, in this algorithm, uneven radiotracer uptake among segments affects WR calculation. To solve this possible issue, we formulated a modified algorithm for calculating WR based on the total count (namely, TCWR).
Methods: The WR of iodine-123-β-methyl-p-iodophenylpentadecanoic acid (BMIPP) was calculated using TCWR and AMWR, and WR values using TCWR and AMWR were compared by disease. Participants included those without cardiovascular diseases (normal), those with CD36 deficiency, triglyceride deposit cardiomyovasculopathy (TGCV), TGCV with old myocardial infarction (OMI), and non-TGCV with OMI.
Results: WR values using TCWR and AMWR did not differ significantly in the following groups: normal, 27.4 ± 8.5 and 27.3 ± 8.5% (p = 0.97); CD36 deficiency, -3.2 ± 6.5 and -4.1 ± 7.4% (p = 0.81); TGCV, 2.4 ± 6.3 and 2.2 ± 6.3% (p = 0.93); and TGCV with OMI, -0.9 ± 7.6 and -3.7 ± 8.4% (p = 0.32). However, AMWR showed a lower WR than TCWR in non-TGCV with OMI (4.8 ± 8.7 and 18.9 ± 6.7%, p = 0.0008).
Conclusions: TCWR is suitable for calculating WR using SPECT polar maps even in cases with heterogeneous radiotracer uptake, such as OMIs. TCWR may be applied to measuring the WR of radiopharmaceuticals other than BMIPP in investigating the pathophysiology of heart diseases.

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Background: Single-photon emission computed tomography (SPECT) encounters difficulties in diagnosing severe multi-vessel coronary artery disease (svMVD) because of balanced ischemia. We estimated the predictive value of electrocardiogram-gated SPECT for svMVD and improved it using machine learning (ML).
Methods and results: We enrolled consecutive 335 patients (median age, 74 years; 255 men) who underwent adenosine stress-gated SPECT (^99mTechnesium) and coronary angiography. svMVD was defined as three-vessel disease or left main tract stenosis. Predictive models were constructed using statistical and ML methods. Eighteen cases (5%) showed svMVD, and diabetes, summed stress score (SSS), and the max difference among segmental time of stroke volume per cardiac cycle (MDSV: a parameter of left ventricular (LV) end-systolic dyssynchrony) on adenosine stress were independent significant predictors. The area under the receiver operating characteristic curve (AUC) of SSS and MDSV on stress were 0.759 and 0.763, respectively. Conversely, the extra trees classifier and light gradient boosting machine had improved AUC values of 0.826 and 0.870, respectively, and the MDSV on stress and diabetes showed high feature values in the ML models.
Conclusion: ML on SPECT helped to improve the diagnostic performance of svMVD and diabetes, and the parameters of LV dyssynchrony played essential roles in the ML predictive models.

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