Automated Deep Learning Segmentation of Cardiac Inflammatory FDG PET.

Background: Fluorodeoxyglucose positron emission tomography (FDG PET) with glycolytic metabolism suppression plays a pivotal role in diagnosing cardiac sarcoidosis. Reorientation of images to match perfusion datasets is critical and myocardial segmentation enables consistent image scaling and quantification. However, both are challenging and labor intensive. We developed a 3D U-Net deep learning (DL) algorithm for automated myocardial segmentation in cardiac sarcoidosis FDG PET. Methods: The DL model was trained on 316 patients' FDG PET scans, and left ventricular contours derived from perfusion datasets. Qualitative analysis of clinical readability was performed to compare DL segmentation with the current automated method on a 50-patient test subset. Additionally, left ventricle displacement and angulation, as well as SUVmax sampling were compared to inter-user reproducibility results. Results: DL segmentation enhanced readability scores in over 90% of cases compared to the standard segmentation currently used in the software. DL segmentation performed similarly to a trained technologist, surpassing standard segmentation for left ventricle displacement and angulation, as well as correlation of SUVmax. Conclusion: The DL-based automated segmentation tool presents a marked improvement in the processing of cardiac sarcoidosis FDG PET, promising enhanced clinical workflow. This tool holds significant potential for accelerating clinical practice and improving consistency and quality. Further research with varied datasets is warranted to broaden its applicability.

Deep neural network for identification of impaired microvascular and vasomotor function from stress electrocardiography.

Impaired microvascular and vasomotor function is a common consequence of aging, diabetes, and other risk factors, and is associated with adverse cardiac outcomes. Such impairments are not readily identified by standard clinical methods of cardiovascular testing such as coronary angiography and noninvasive single photon emission tomography (SPECT) myocardial perfusion imaging (MPI). We hypothesized that signals embedded within stress electrocardiograms (ECGs) identify individuals with microvascular and vasomotor dysfunction. Methods: We developed and validated a novel convolutional neural network (CNN) using stress and rest ECG data (ECG-Flow) to identify patients with impaired myocardial flow reserve (MFR) on quantitative positron emission tomography (PET) MPI (N=3887). Diagnostic accuracy was validated with an internal holdout set of patients undergoing stress PET MPI (N=963). The prognostic association of ECG-Flow with mortality was then evaluated in a separate cohort of patients undergoing SPECT MPI (N=5102). Results: ECG-Flow achieved good diagnostic accuracy for impaired MFR in the holdout PET cohort (AUC, sensitivity, specificity: 0.737, 71.1%, 65.7%). Abnormal ECG-Flow was found to be significantly associated with mortality in both PET holdout and SPECT MPI cohorts (adjusted HR 2.12 [95 ρ CI 1.45, 2.10], ρ = 0.0001, and 2.07 [1.82, 2.36], ρ < 0.0001, respectively). Conclusion: Signals predictive of microvascular and vasomotor dysfunction are embedded in stress ECG waveforms. These signals can be identified by deep learning methods and are related to prognosis in patients undergoing both stress PET and SPECT MPI.

Integrated myocardial flow reserve (iMFR) assessment: diffuse atherosclerosis and microvascular dysfunction are more strongly associated with mortality than focally impaired perfusion.

BACKGROUND AND AIMS: Although treatment of ischemia-causing epicardial stenoses may improve symptoms of ischemia, current evidence does not suggest that revascularization improves survival. Conventional myocardial ischemia imaging does not uniquely identify diffuse atherosclerosis, microvascular dysfunction, or nonobstructive epicardial stenoses. We sought to evaluate the prognostic value of integrated myocardial flow reserve (iMFR), a novel noninvasive approach to distinguish the perfusion impact of focal atherosclerosis from diffuse coronary disease. METHODS: This study analyzed a large single-center registry of consecutive patients clinically referred for rest-stress myocardial perfusion positron emission tomography. Cox proportional hazards modeling was used to assess the association of two previously reported and two novel perfusion measures with mortality risk: global stress myocardial blood flow (MBF); global myocardial flow reserve (MFR); and two metrics derived from iMFR analysis: the extents of focal and diffusely impaired perfusion. RESULTS: In total, 6867 patients were included with a median follow-up of 3.4 years [1st-3rd quartiles, 1.9-5.0] and 1444 deaths (21%). Although all evaluated perfusion measures were independently associated with death, diffusely impaired perfusion extent (hazard ratio 2.65, 95%C.I. [2.37-2.97]) and global MFR (HR 2.29, 95%C.I. [2.08-2.52]) were consistently stronger predictors than stress MBF (HR 1.62, 95%C.I. [1.46-1.79]). Focally impaired perfusion extent (HR 1.09, 95%C.I. [1.03-1.16]) was only moderately related to mortality. Diffusely impaired perfusion extent remained a significant independent predictor of death when combined with global MFR (p < 0.0001), providing improved risk stratification (overall net reclassification improvement 0.246, 95%C.I. [0.183-0.310]). CONCLUSIONS: The extent of diffusely impaired perfusion is a strong independent and additive marker of mortality risk beyond traditional risk factors, standard perfusion imaging, and global MFR, while focally impaired perfusion is only moderately related to mortality.

Integrated myocardial flow reserve (iMFR) assessment: optimized PET blood flow quantification for diagnosis of coronary artery disease.

PURPOSE: Distinguishing obstructive epicardial coronary artery disease (CAD) from microvascular dysfunction and diffuse atherosclerosis would be of immense benefit clinically. However, quantitative measures of absolute myocardial blood flow (MBF) integrate the effects of focal epicardial stenosis, diffuse atherosclerosis, and microvascular dysfunction. In this study, MFR and relative perfusion quantification were combined to create integrated MFR (iMFR) which was evaluated using data from a large clinical registry and an international multi-center trial and validated against invasive coronary angiography (ICA). METHODS: This study included 1,044 clinical patients referred for 82Rb rest/stress positron emission tomography myocardial perfusion imaging and ICA, along with 231 patients from the Flurpiridaz 301 trial (clinicaltrials.gov NCT01347710). MFR and relative perfusion quantification were combined to create an iMFR map. The incremental value of iMFR was evaluated for diagnosis of obstructive stenosis, adjusted for patient demographics and pre-test probability of CAD. Models for high-risk anatomy (left main or three-vessel disease) were also constructed. RESULTS: iMFR parameters of focally impaired perfusion resulted in best fitting diagnostic models. Receiver-operating characteristic analysis showed a slight improvement compared to standard quantitative perfusion approaches (AUC 0.824 vs. 0.809). Focally impaired perfusion was also associated with high-risk CAD anatomy (OR 1.40 for extent, and OR 2.40 for decreasing mean MFR). Diffusely impaired perfusion was associated with lower likelihood of obstructive CAD, and, in the absence of transient ischemic dilation (TID), with lower likelihood of high-risk CAD anatomy. CONCLUSIONS: Focally impaired perfusion extent derived from iMFR assessment is a powerful incremental predictor of obstructive CAD while diffusely impaired perfusion extent can help rule out obstructive and high-risk CAD in the absence of TID.

Improved diagnostic accuracy for coronary artery disease detection with quantitative 3D 82Rb PET myocardial perfusion imaging.

PURPOSE: To establish requirements for normal databases for quantitative rubidium-82 (82Rb) PET MPI analysis with contemporary 3D PET/CT technology and reconstruction methods for maximizing diagnostic accuracy of total perfusion deficit (TPD), a combined metric of defect extent and severity, versus invasive coronary angiography. METHODS: In total, 1571 patients with 82Rb PET/CT MPI on a 3D scanner and stress static images reconstructed with and without time-of-flight (TOF) modeling were identified. An additional eighty low pre-test probability of disease (PTP) patients reported as normal were used to form separate sex-stratified and sex-independent iterative and TOF normal databases. 3D normal databases were applied to matched patient reconstructions to quantify TPD. Per-patient and per-vessel performance of 3D versus 2D PET normal databases was assessed with receiver operator characteristic curve analysis. Diagnostic accuracy was evaluated at optimal thresholds established from PTP patients. Results were compared against logistic regression modeling of TPD adjusted for clinical variables, and standard clinical interpretation. RESULTS: TPD diagnostic accuracy was significantly higher using 3D PET normal databases (per-patient: 80.1% for 3D databases, versus 74.9% and 77.7% for 2D database applied to iterative and TOF images respectively, p < 0.05). Differences in male and female normal distributions for 3D attenuation-corrected reconstructions were not clinically meaningful; therefore, sex-independent databases were used. Logistic regression modeling including TPD demonstrated improved performance over clinical reads. CONCLUSIONS: Normal databases tailored to 3D PET images provide significantly improved diagnostic accuracy for PET MPI evaluation with automated quantitative TPD. Clinical application of these techniques should be considered to support accurate image interpretation.

Multi-center, multi-vendor validation of deep learning-based attenuation correction in SPECT MPI: data from the international flurpiridaz-301 trial.

PURPOSE: Although SPECT myocardial perfusion imaging (MPI) is susceptible to artifacts from soft tissue attenuation, most scans are performed without attenuation correction. Deep learning-based attenuation corrected (DLAC) polar maps improved diagnostic accuracy for detection of coronary artery disease (CAD) beyond non-attenuation-corrected (NAC) polar maps in a large single center study. However, the generalizability of this approach to other institutions with different scanner models and protocols is uncertain. In this study, we evaluated the diagnostic performance of DLAC compared to NAC for detection of CAD as defined by invasive coronary angiography (ICA) in a large multi-center trial. METHODS: During the phase 3 flurpiridaz multi-center diagnostic clinical trial, conducted over 74 international sites, patients with known or suspected CAD who were referred for a clinically indicated ICA were enrolled. Using receiver operating characteristic (ROC) analysis, we evaluated the detectability of obstructive CAD, defined by quantitative coronary angiography by a core laboratory, using total perfusion deficit (TPD) as an integrated measure of defect extent and severity on DLAC polar maps compared to NAC polar maps. This was also compared against the visual scoring of three expert core lab readers. RESULTS: Out of 755 patients, 722 (69% male) had evaluable SPECT and ICA for this study. ROC analysis demonstrated significant improvement in detecting per-patient obstructive CAD with DLAC over NAC with area under the curve (AUC) of 0.752 (95% CI: 0.711-0.792) for DLAC compared to 0.717 (0.675-0.759) for NAC (p value = 0.016). Compared to the consensus of expert readers AUC = 0.743 (0.701-0.784), DLAC was comparable (p value = 0.913), whereas NAC underperformed (p value = 0.051). CONCLUSION: DL-based attenuation correction improves diagnostic performance of SPECT MPI for detecting CAD in data from a large multi-center clinical trial regardless of SPECT camera model or protocol. TRIAL REGISTRATION: A Phase 3 Multi-center Study to Assess PET Imaging of Flurpiridaz F 18 Injection in Patients With CAD, ClinicalTrials.gov Identifier: NCT01347710, registered on 4 May 2011. https://clinicaltrials.gov/ct2/show/study/NCT01347710.

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

PURPOSE: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Effect of iterations and time of flight on normal distributions of 82Rb PET relative perfusion and myocardial blood flow.

BACKGROUND: As clinical use of myocardial blood flow (MBF) increases, dynamic series are becoming part of the typical workflow. The methods and parameters used to reconstruct these series require investigation to ensure accurate quantification. METHODS: Fifty-nine rest/stress dynamic 82Rb PET studies, acquired on a Biograph mCT, from a combination of normal volunteers and low-likelihood patients were reconstructed with and without time of flight (TOF) for varying iterations and processed to obtain relative perfusion and MBF polar maps. Regional values from mean polar maps were fit to a linear mixed-effect model to quantify convergence and select the optimal number of iterations. RESULTS: TOF reconstructions converged faster and yielded more uniform relative perfusion polar maps. However, the stress MBF distribution for TOF reconstructions was more heterogeneous, with a higher-intensity septal wall. This phenomenon requires further investigation, with right ventricle blood pool spillover possibly having an effect. Optimal reconstructions were defined as 5-iteration non-TOF (24-subset) reconstructions and 3-iteration TOF (21-subset) reconstructions. CONCLUSION: Optimal cardiac reconstructions were identified for non-TOF and TOF reconstructions of dynamic series. TOF reconstruction presents as the more accurate method, given the more uniform relative perfusion distribution.

Myocardial flow reserve estimation with contemporary CZT-SPECT and 99mTc-tracers lacks precision for routine clinical application.

BACKGROUND: PET myocardial flow reserve (MFR) has established diagnostic and prognostic value. Technological advances have now enabled SPECT MFR quantification. We investigated whether SPECT MFR precision is sufficient for clinical categorization of patients. METHODS: Validation studies vs invasive flow measurements and PET MFR were reviewed to determine global SPECT MFR thresholds. Studies vs PET and a SPECT MFR repeatability study were used to establish imprecision in SPECT MFR measurements as the standard deviation of the difference between SPECT and PET MFR, or test-retest SPECT MFR. Simulations were used to evaluate the impact of SPECT MFR imprecision on confidence of clinically relevant categorization. RESULTS: Based on validation studies, the typical PET MFR categories were used for SPECT MFR classification (< 1.5, 1.5-2.0, > 2.0). Imprecision vs PET MFR ranged from 0.556 to 0.829, and test-retest imprecision was 0.781-0.878. Simulations showed correct classification of up to only 34% of patients when 1.5 ≤ true MFR ≤ 2.0. Categorization with high confidence (> 80%) was only achieved for extreme MFR values (< 1.0 or > 2.5), with correct classification in only 15% of patients in a typical lab with MFR of 1.8 ± 0.5. CONCLUSIONS: Current SPECT-derived estimates of MFR lack precision and require further optimization for clinical risk stratification.

Impact of residual subtraction on myocardial blood flow and reserve estimates from rapid dynamic PET protocols.

BACKGROUND: 13N-ammonia and 18F-flurpiridaz require longer delays between rest and stress studies to allow for decay, lowering clinical throughput. In this study, we investigated the impact of residual subtraction on MBF and MFR estimates, as well as its effects on diagnostic accuracy. METHODS: We retrospectively analyzed 63 patients who underwent a dynamic ammonia rest/stress study and 231 patients from the flurpiridaz 301 trial. Residual subtraction was performed by subtracting the mean pre-injection activity in each sampled region from that region's time activity curve. Corrected and uncorrected MBF and MFR were analyzed. Diagnostic accuracy was compared to quantitative coronary angiograms (QCA) for the flurpiridaz population. RESULTS: With delays between injections above 3 half-lives, and a doubled stress dose, residual activity did not meaningfully increase ammonia MBF (< 5%). For shorter injection delays, stress MBF was overestimated by 13.6% ± 5.0% (P < .001). Residual activity had a large effect on flurpiridaz stress MBF, overestimating it by 37.9% ± 23.2% (P < .001). Comparison to QCA showed a significant improvement in AUC with residual subtraction (from 0.748 to 0.831, P = .001). MFR yielded similar results. CONCLUSIONS: Accounting for residual activity has a marked impact on stress MBF and MFR and improves diagnostic accuracy relative to QCA.

Effects of two patient-specific dosing protocols on measurement of myocardial blood flow with 3D 82Rb cardiac PET.

PURPOSE: Clinical measurement of myocardial blood flow (MBF) has emerged as an important component of routine PET-CT assessment of myocardial perfusion in patients with known or suspected coronary artery disease. Although multiple society guidelines recommend patient-specific dosing, there is a lack of studies evaluating the efficacy of patient-specific dosing for quantitative MBF accuracy. METHODS: Two patient-specific dosing protocols (weight- and BMI-adjusted) were retrospectively evaluated in 435 consecutive clinical patients referred for PET myocardial perfusion assessment. MBF was estimated at rest and after regadenoson-induced hyperemia. The effect of dosing protocol on dose reduction, PET scanner saturation, relative perfusion, and image quality was compared. The effect of PET saturation on the accuracy of MBF and myocardial flow reserve (MFR) in remote myocardium was assessed with multivariable linear regression. RESULTS: BMI-adjusted dosing was associated with lower administered 82Rb activities (1036.0 ± 274 vs. 1147 ± 274 MBq, p = 0.003) and lower PET scanner saturation incidence (28 vs. 38%, p = 0.006) and severity (median saturation severity index 0.219 ± 0.33 vs. 0.397 ± 0.59%, p = 0.018) compared to weight-adjusted dosing. PET saturation that occurred with either dosing protocol was moderate and resulted in modest remote MBF and MFR biases ranging from 2 to 9% after adjusting for patient age, sex, BMI, rate-pressure product, and LV ejection fraction. No adverse effects of BMI dose adjustment were observed in relative perfusion assessment or image quality. CONCLUSIONS: Patient-specific dosing according to BMI is an effective method for guideline-directed dose reduction while maintaining image quality and accuracy for routine MBF and MFR quantification.

Added value of myocardial blood flow using 18F-flurpiridaz PET to diagnose coronary artery disease: The flurpiridaz 301 trial.

BACKGROUND: 18F-Flurpiridaz is a promising investigational radiotracer for PET myocardial perfusion imaging with favorable properties for quantification of myocardial blood flow (MBF). We sought to validate the incremental diagnostic value of absolute MBF quantification in a large multicenter trial against quantitative coronary angiography. METHODS: We retrospectively analyzed a subset of patients (N = 231) from the first phase 3 flurpiridaz trial (NCT01347710). Dynamic PET data at rest and pharmacologic stress were fit to a previously validated 2-tissue-compartment model. Absolute MBF and myocardial flow reserve (MFR) were compared with coronary artery disease severity quantified by invasive coronary angiography on a per-patient and per-vessel basis. RESULTS: Stress MBF per-vessel accurately identified obstructive disease (c-index 0.79) and progressively declined with increasing stenosis severity (2.35 ± 0.71 in patients without CAD; 1.92 ± 0.49 in non-obstructed territories of CAD patients; and 1.54 ± 0.50 in diseased territories, P < 0.05). MFR similarly declined with increasing stenosis severity (3.03 ± 0.94; 2.69 ± 0.95; and 2.33 ± 0.86, respectively, P < 0.05). In multivariable logistic regression modeling, stress MBF and MFR provided incremental diagnostic value beyond patient characteristics and relative perfusion analysis. CONCLUSIONS: Clinical myocardial blood flow measurement with 18F-flurpiridaz cardiac PET shows promise for routine application.

Initial clinical experience of N13-ammonia myocardial perfusion PET/CT using a compact superconducting production system.

BACKGROUND: Although N13-ammonia has favorable properties among FDA approved radiotracers, complexity of implementation has limited its use. We describe the initial patient experience of N13-ammonia PET imaging using a compact N13-ammonia production system. METHODS: N13 was produced using the ION-12SC, a 12MeV, 10uA superconducting minimally shielded cyclotron, and reduced to N13-ammonia in an automated multi-use purification unit. Patients were power injected with 9.3 ± 1.1 mCi (344.1 ± 40.7 MBq) of N13-ammonia for rest imaging, and 18.8 ± 0.9 mCi (695.6 ± 33.3 MBq) of N13-ammonia was injected at peak hyperemia for stress testing. Images were interpreted for relative perfusion, left ventricular volumes/function, blood flow quantification, and scored for image quality. RESULTS: In total 97 patients underwent 98 N13-ammonia PET scans (32 rest only/65 rest-stress/1 stress only). Image quality was 91.8% good or excellent. None were poor/non-diagnostic. Study durations were acceptable. Tracer related radiation dosimetry to patients was 0.7 ± 0.1 mSv (rest only), and 2.1 ± 0.1 mSv (rest-stress). CONCLUSION: Clinical N13-ammonia production by the Ionetix ION-12SC delivers high quality myocardial PET perfusion images in a rapid protocol.

Quantitative clinical nuclear cardiology, part 2: Evolving/emerging applications.

Quantitative analysis has been applied extensively to image processing and interpretation in nuclear cardiology to improve disease diagnosis and risk stratification. This is Part 2 of a two-part continuing medical education article, which will review the potential clinical role for emerging quantitative analysis tools. The article will describe advanced methods for quantifying dyssynchrony, ventricular function and perfusion, and hybrid imaging analysis. This article discusses evolving methods to measure myocardial blood flow with positron emission tomography and single-photon emission computed tomography. Novel quantitative assessments of myocardial viability, microcalcification and in patients with cardiac sarcoidosis and cardiac amyloidosis will also be described. Lastly, we will review the potential role for artificial intelligence to improve image analysis, disease diagnosis, and risk prediction. The potential clinical role for all these novel techniques will be highlighted as well as methods to optimize their implementation. (J Nucl Cardiol 2020).

Quantitative clinical nuclear cardiology, part 2: Evolving/emerging applications.

Quantitative analysis has been applied extensively to image processing and interpretation in nuclear cardiology to improve disease diagnosis and risk stratification. This is Part 2 of a two-part continuing medical education article, which will review the potential clinical role for emerging quantitative analysis tools. The article will describe advanced methods for quantifying dyssynchrony, ventricular function and perfusion, and hybrid imaging analysis. This article discusses evolving methods to measure myocardial blood flow with positron emission tomography and single-photon emission computed tomography. Novel quantitative assessments of myocardial viability, microcalcification and in patients with cardiac sarcoidosis and cardiac amyloidosis will also be described. Lastly, we will review the potential role for artificial intelligence to improve image analysis, disease diagnosis, and risk prediction. The potential clinical role for all these novel techniques will be highlighted as well as methods to optimize their implementation.

Multiparametric assessment of left atrial remodeling using 18F-FDG PET/CT cardiac imaging: A pilot study.

BACKGROUND: Left atrial (LA) remodeling is associated with structural, electric, and metabolic LA changes. Integrated evaluation of these features in vivo is lacking. METHODS: Patients undergoing 18F-fluorodeoxyglucose (FDG) PET-CT during a hyperinsulinemic-euglycemic clamp were classified into sinus rhythm (SR), paroxysmal AF (PAF), and persistent AF (PerAF). The LA was semiautomatically segmented, and global FDG uptake was quantified using standardized uptake values (SUVmax and SUVmean) in gated, attenuation-corrected images and normalized to LA blood pool activity. Regression was used to relate FDG data to AF burden and critical patient factors. Continuous variables were compared using t-tests or Mann-Whitney tests. RESULTS: 117 patients were included (76% men, age 66.4 ± 11.0, ejection fraction (EF) 25[22-35]%) including those with SR (n = 48), PAF (n = 55), and PerAF (n = 14). Patients with any AF had increased SUVmean (2.3[1.5-2.4] vs 2.0[1.5-2.5], P = 0.006), SUVmax (4.4[2.8-6.7] vs 3.2[2.3-4.3], P < 0.001), uptake coefficient of variation (CoV) 0.28[0.22-0.40] vs 0.25[0.2-0.33], P < 0.001), and hypometabolic scar (32%[14%-53%] vs 16.5%[0%-38.5%], P = 0.01). AF burden correlated with increased SUVmean, SUVmax, CoV, and scar independent of age, gender, EF, or LA size (P < 0.03 for all). CONCLUSIONS: LA structure and metabolism can be assessed using FDG PET/CT. Greater AF burden correlates with the increased LA metabolism and scar.

Automated dynamic motion correction using normalized gradient fields for 82rubidium PET myocardial blood flow quantification.

BACKGROUND: Patient motion can lead to misalignment of left ventricular (LV) volumes-of-interest (VOIs) and subsequently inaccurate quantification of myocardial blood flow (MBF) and flow reserve (MFR) from dynamic PET myocardial perfusion images. We aimed to develop an image-based 3D-automated motion-correction algorithm that corrects the full dynamic sequence for translational motion, especially in the early blood phase frames (~ first minute) where the injected tracer activity is transitioning from the blood pool to the myocardium and where conventional image registration algorithms have had limited success. METHODS: We studied 225 consecutive patients who underwent dynamic rest/stress rubidium-82 chloride (82Rb) PET imaging. Dynamic image series consisting of 30 frames were reconstructed with frame durations ranging from 5 to 80 seconds. An automated algorithm localized the RV and LV blood pools in space and time and then registered each frame to a tissue reference image volume using normalized gradient fields with a modification of a signed distance function. The computed shifts and their global and regional flow estimates were compared to those of reference shifts that were assessed by three physician readers. RESULTS: The automated motion-correction shifts were within 5 mm of the manual motion-correction shifts across the entire sequence. The automated and manual motion-correction global MBF values had excellent linear agreement (R = 0.99, y = 0.97x + 0.06). Uncorrected flows outside of the limits of agreement with the manual motion-corrected flows were brought into agreement in 90% of the cases for global MBF and in 87% of the cases for global MFR. The limits of agreement for stress MBF were also reduced twofold globally and by fourfold in the RCA territory. CONCLUSIONS: An image-based, automated motion-correction algorithm for dynamic PET across the entire dynamic sequence using normalized gradient fields matched the results of manual motion correction in reducing bias and variance in MBF and MFR, particularly in the RCA territory.

Characterization of a highly effective preparation for suppression of myocardial glucose utilization.

BACKGROUND: With appropriate protocols, F-18 fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) can visualize myocardial inflammation. Optimal protocols and normative myocardial FDG uptake values are not well-established. METHODS: We evaluated 111 patients referred for inflammation cardiac FDG PET/CT. Patients followed a low-carbohydrate, high-fat diet for 36 hours before imaging and received unfractionated heparin. Glucose and fatty acid metabolism biomarkers were obtained. Mean blood pool and maximum myocardial uptake (SUVmean, SUVmax) were measured, avoiding areas of abnormal FDG uptake or spillover. RESULTS: Adequate suppression of myocardial FDG uptake occurred in 95% of patients (n = 106). Myocardial SUVmax was significantly below background blood pool SUVmean: septal myocardial to blood pool ratio 0.75 (95% CI 0.73-0.77; P < 0.001); lateral myocardial to blood pool ratio 0.70 (95% CI 0.68-0.72; P < 0.001). Glucose, insulin, and C-peptide correlated to blood pool SUVmean (Spearman rs = 0.39, P < 0.01; rs = 0.40, P < 0.01; rs = 0.35, P < 0.01) and myocardial SUVmax (Spearman rs = 0.31, P < 0.01; rs = 0.31, P < 0.01; rs = 0.26, P < 0.01). Fatty acid metabolism biomarkers did not correlate to myocardial SUVmax. CONCLUSIONS: Patients following intensive metabolic preparation have myocardial FDG SUVmax below background SUVmean. Biomarkers of glucose metabolism modestly correlate to FDG uptake.