Impact of regadenoson-induced myocardial creep on dynamic Rubidium-82 PET myocardial blood flow quantification

Downward myocardial creep during stress PET imaging is inversely associated with mortality

PURPOSE

The myocardial creep is a phenomenon in which the heart moves from its original position during stress-dynamic PET myocardial perfusion imaging (MPI) that can confound myocardial blood flow measurements. Therefore, myocardial motion correction is important to obtain reliable myocardial flow quantification. However, the clinical importance of the magnitude of myocardial creep has not been explored. We aimed to explore the prognostic value of myocardial creep quantified by an automated motion correction algorithm beyond traditional PET-MPI imaging variables.

METHODS

Consecutive patients undergoing regadenoson rest-stress [82Rb]Cl PET-MPI were included. A newly developed 3D motion correction algorithm quantified myocardial creep, the maximum motion at stress during the first pass (60 s), in each direction. All-cause mortality (ACM) served as the primary endpoint.

RESULTS

A total of 4,276 patients (median age 71 years; 60% male) were analyzed, and 1,007 ACM events were documented during a 5-year median follow-up. Processing time for automatic motion correction was < 12 s per patient. Myocardial creep in the superior to inferior (downward) direction was greater than the other directions (median, 4.2 mm vs. 1.3-1.7 mm). Annual mortality rates adjusted for age and sex were reduced with a larger downward creep, with a 4.2-fold ratio between the first (0 mm motion) and 10th decile (11 mm motion) (mortality, 7.9% vs. 1.9%/year). Downward creep was associated with lower ACM after full adjustment for clinical and imaging parameters (adjusted hazard ratio, 0.93; 95%CI, 0.91-0.95; p < 0.001). Adding downward creep to the standard PET-MPI imaging model significantly improved ACM prediction (area under the receiver operating characteristics curve, 0.790 vs. 0.775; p < 0.001), but other directions did not (p > 0.5).

CONCLUSIONS

Downward myocardial creep during regadenoson stress carries additional information for the prediction of ACM beyond conventional flow and perfusion PET-MPI. This novel imaging biomarker is quantified automatically and rapidly from stress dynamic PET-MPI.

Automated Motion Correction for Myocardial Blood Flow Measurements and Diagnostic Performance of 82Rb PET Myocardial Perfusion Imaging

Motion correction (MC) affects myocardial blood flow (MBF) measurements in 82Rb PET myocardial perfusion imaging (MPI); however, frame-by-frame manual MC of dynamic frames is time-consuming. This study aims to develop an automated MC algorithm for time-activity curves used in compartmental modeling and compare the predictive value of MBF with and without automated MC for significant coronary artery disease (CAD). Methods: In total, 565 patients who underwent PET-MPI were considered. Patients without angiographic findings were split into training (n = 112) and validation (n = 112) groups. The automated MC algorithm used simplex iterative optimization of a count-based cost function and was developed using the training group. MBF measurements with automated MC were compared with those with manual MC in the validation group. In a separate cohort, 341 patients who underwent PET-MPI and invasive coronary angiography were enrolled in the angiographic group. The predictive performance in patients with significant CAD (≥70% stenosis) was compared between MBF measurements with and without automated MC. Results: In the validation group (n = 112), MBF measurements with automated and manual MC showed strong correlations (r = 0.98 for stress MBF and r = 0.99 for rest MBF). The automatic MC took less time than the manual MC (<12 s vs. 10 min per case). In the angiographic group (n = 341), MBF measurements with automated MC decreased significantly compared with those without (stress MBF, 2.16 vs. 2.26 mL/g/min; rest MBF, 1.12 vs. 1.14 mL/g/min; MFR, 2.02 vs. 2.10; all P < 0.05). The area under the curve (AUC) for the detection of significant CAD by stress MBF with automated MC was higher than that without (AUC, 95% CI, 0.76 [0.71-0.80] vs. 0.73 [0.68-0.78]; P < 0.05). The addition of stress MBF with automated MC to the model with ischemic total perfusion deficit showed higher diagnostic performance for detection of significant CAD (AUC, 95% CI, 0.82 [0.77-0.86] vs. 0.78 [0.74-0.83]; P = 0.022), but the addition of stress MBF without MC to the model with ischemic total perfusion deficit did not reach significance (AUC, 95% CI, 0.81 [0.76-0.85] vs. 0.78 [0.74-0.83]; P = 0.067). Conclusion: Automated MC on 82Rb PET-MPI can be performed rapidly with excellent agreement with experienced operators. Stress MBF with automated MC showed significantly higher diagnostic performance than without MC.

Detection and correction of patient motion in dynamic 15O-water PET MPI

BACKGROUND

Patient motion constitutes a limitation to 15O-water cardiac PET imaging. We examined the ability of image readers to detect and correct patient motion using simulated motion data and clinical patient scans.

METHODS

Simulated data consisting of 16 motions applied to 10 motion-free scans were motion corrected using two approaches, pre-analysis and post-analysis for motion identification. Both approaches employed a manual frame-by-frame correction method. In addition, a clinical cohort was analyzed for assessment of prevalence and effect of motion and motion correction.

RESULTS

Motion correction was performed on 94% (pre-analysis) and 64% (post-analysis) of the scans. Large motion artifacts were corrected in 91% (pre-analysis) and 74% (post-analysis) of scans. Artifacts in MBF were reduced in 56% (pre-analysis) and 58% (post-analysis) of the scans. The prevalence of motion in the clinical patient cohort (n = 762) was 10%. Motion correction altered exam interpretation in only 10 (1.3%) clinical patient exams.

CONCLUSION

Frame-by-frame motion correction after visual inspection is useful in reducing motion artifacts in cardiac 15O-water PET. Reviewing the initial results (parametric images and polar maps) as part of the motion correction process, reduced erroneous corrections in motion-free scans. In a large clinical cohort, the impact of motion correction was limited to few patients.

Myocardial creep and cardiorespiratory motion correction improves diagnostic accuracy of Rubidium-82 cardiac positron emission tomography

AIM

To evaluate the feasibility of retrospectively detecting and correcting periodical (cardiac and respiratory motion) and non-periodical shifts of the myocardial position (myocardial creep) using only the acquired Rubidium-82 positron emission tomography raw (listmode) data.

METHODS

This study comprised 25 healthy participants (median age = 23 years) who underwent repeat rest/adenosine stress Rubidium-82 myocardial perfusion imaging (MPI) and 53 patients (median age = 64 years) considered for revascularization who underwent a single MPI session. All subjects were evaluated for myocardial creep during MPI by assessing the myocardial position every 200 ms. A proposed motion correction protocol, including corrections for cardiorespiratory and creep motion (3xMC), was compared to a guideline-recommended protocol (StandardRecon). For the volunteers, we report test-retest repeatability using standard error of measurements (SEM). For the patient cohort, we evaluated the area under the receiver operating curve (AUC) for both stress and ischemic total perfusion deficits (sTPD and iTPD, respectively) using myocardial ischemia defined as fractional flow reserve values < 0.8 in the relevant coronary segment as the gold standard.

RESULTS

Test-retest repeatability was significantly improved following corrections for myocardial creep (SEM; sTPD: StandardRecon = 2.2, 3xMC = 1.8; iTPD: StandardRecon = 1.6, 3xMC = 1.2). AUC analysis of the ROC curves revealed significant improvements for iTPD measurements following 3xMC [sTPD: StandardRecon = 0.88, 3xMC = 0.92 (P = .21); iTPD: StandardRecon = 0.88, 3xMC = 0.95 (P = .039)].

CONCLUSION

3xMC has the potential to improve the diagnostic accuracy of myocardial MPI obtained from positron emission tomography. Therefore, its use should be considered both in clinical routine and large-scale multicenter studies.

Patient-tailored risk assessment of obstructive coronary artery disease using Rubidium-82 PET-based myocardial flow quantification with visual interpretation

INTRODUCTION

Our aim was to estimate the probability of obstructive CAD (oCAD) for an individual patient as a function of the myocardial flow reserve (MFR) measured with Rubidium-82 (Rb-82) PET in patients with a visually normal or abnormal scan.

MATERIALS AND METHODS

We included 1519 consecutive patients without a prior history of CAD referred for rest-stress Rb-82 PET/CT. All images were visually assessed by two experts and classified as normal or abnormal. We estimated the probability of oCAD for visually normal scans and scans with small (5%-10%) or larger defects (> 10%) as function of MFR. The primary endpoint was oCAD on invasive coronary angiography, when available.

RESULTS

1259 scans were classified as normal, 136 with a small defect and 136 with a larger defect. For the normal scans, the probability of oCAD increased exponentially from 1% to 10% when segmental MFR decreased from 2.1 to 1.3. For scans with small defects, the probability increased from 13% to 40% and for larger defects from 45% to > 70% when segmental MFR decreased from 2.1 to 0.7.

CONCLUSION

Patients with > 10% risk of oCAD can be distinguished from patients with < 10% risk based on visual PET interpretation only. However, there is a strong dependence of MFR on patient's individual risk of oCAD. Hence, combining both visual interpretation and MFR results in a better individual risk assessment which may impact treatment strategy.

Measuring myocardial blood flow using dynamic myocardial perfusion SPECT: artifacts and pitfalls

Dynamic acquisition allows absolute quantification of myocardial perfusion and flow reserve, offering an alternative to overcome the potential limits of relative quantification, especially in patients with balanced multivessel coronary artery disease. SPECT myocardial perfusion is widely available, at lower cost than PET. Dynamic cardiac SPECT is now feasible and has the potential to be the next step of comprehensive perfusion imaging. In order to help nuclear cardiologists potentially interested in using dynamic perfusion SPECT, we sought to review the different steps of acquisition, processing, and reporting of dynamic SPECT studies in order to enlighten the potentially critical pitfalls and artifacts. Both patient-related and technical artifacts are discussed. Key parameters of the acquisition include pharmacological stress, radiopharmaceuticals, and injection device. When it comes to image processing, attention must be paid to image-derived input function, patient motion, and extra-cardiac activity. This review also mentions compartment models, cameras, and attenuation correction. Finally, published data enlighten some facets of dynamic cardiac SPECT while several issues remain. Harmonizing acquisition and quality control procedures will likely improve its performance and clinical strength.

Machine learning based model to diagnose obstructive coronary artery disease using calcium scoring, PET imaging, and clinical data

INTRODUCTION

Accurate risk stratification in patients with suspected stable coronary artery disease is essential for choosing an appropriate treatment strategy. Our aim was to develop and validate a machine learning (ML) based model to diagnose obstructive CAD (oCAD).

METHOD

We retrospectively have included 1007 patients without a prior history of CAD who underwent CT-based calcium scoring (CACS) and a Rubidium-82 PET scan. The entire dataset was split 4:1 into a training and test dataset. An ML model was developed on the training set using fivefold stratified cross-validation. The test dataset was used to compare the performance of expert readers to the model. The primary endpoint was oCAD on invasive coronary angiography (ICA).

RESULTS

ROC curve analysis showed an AUC of 0.92 (95% CI 0.90-0.94) for the training dataset and 0.89 (95% CI 0.84-0.93) for the test dataset. The ML model showed no significant differences as compared to the expert readers (p ≥ 0.03) in accuracy (89% vs. 88%), sensitivity (68% vs. 69%), and specificity (92% vs. 90%).

CONCLUSION

The ML model resulted in a similar diagnostic performance as compared to expert readers, and may be deployed as a risk stratification tool for obstructive CAD. This study showed that utilization of ML is promising in the diagnosis of obstructive CAD.

Myocardial blood flow evaluation with dynamic cadmium-zinc-telluride single-photon emission computed tomography: Bright and dark sides

Myocardial blood flow (MBF) and myocardial perfusion reserve (MPR) assessment with non-invasive techniques represent an important tool to evaluate both coronary artery disease severity and extent. Currently, cardiac positron emission tomography-computed tomography (PET-CT) is the "gold standard" for the assessment of coronary function and provides accurate estimations of baseline and hyperemic MBF and MFR. Nevertheless, due to the high cost and complexity, PET-CT is not widely used in clinical practice. The introduction of cardiac-dedicated cadmium-zinc-telluride (CZT) cameras has renewed researchers' interest on MBF quantitation by single-photon emission computed tomography (SPECT). Indeed, many studies evaluated MPR and MBF measurements by dynamic CZT-SPECT in different cohorts of patients with suspected or overt coronary artery disease. As well, many others have compared the values obtained by CZT-SPECT to the ones by PET-CT, showing good correlations in detecting significant stenosis, although with different and non-standardized cut-off values. Nevertheless, the lack of standardized protocol for acquisition, reconstruction and elaboration makes more difficult to compare different studies and to further assess the real advantages of MBF quantitation by dynamic CZT-SPECT in clinical routine. Many are the issues involved in the bright and dark sides of dynamic CZT-SPECT. They include different type of CZT cameras, different execution protocols, different tracers with different myocardial extraction fraction and distribution, different software packages with different tools and algorithms, often requiring manual post-processing elaboration. This review article provides a clear summary of the state of the art on MBF and MPR evaluation by dynamic CZT-SPECT and outlines the major issues to solve to optimize this technique.

Effect of temporal sampling protocols on myocardial blood flow measurements using Rubidium-82 PET

BACKGROUND

A variety of temporal sampling protocols is used worldwide to measure myocardial blood flow (MBF). Both the length and number of time frames in these protocols may alter MBF and myocardial flow reserve (MFR) measurements. We aimed to assess the effect of different clinically used temporal sampling protocols on MBF and MFR quantification in Rubidium-82 (Rb-82) PET imaging.

METHODS

We retrospectively included 20 patients referred for myocardial perfusion imaging using Rb-82 PET. A literature search was performed to identify appropriate sampling protocols. PET data were reconstructed using 14 selected temporal sampling protocols with time frames of 5-10 seconds in the first-pass phase and 30-120 seconds in the tissue phase. Rest and stress MBF and MFR were calculated for all protocols and compared to the reference protocol with 26 time frames.

RESULTS

MBF measurements differed (P ≤ 0.003) in six (43%) protocols in comparison to the reference protocol, with mean absolute relative differences up to 16% (range 5%-31%). Statistically significant differences were most frequently found for protocols with tissue phase time frames < 90 seconds. MFR did not differ (P ≥ 0.11) for any of the protocols.

CONCLUSIONS

Various temporal sampling protocols result in different MBF values using Rb-82 PET. MFR measurements were more robust to different temporal sampling protocols.

The prevalence of image degradation due to motion in rest-stress rubidium-82 imaging on a SiPM PET-CT system

BACKGROUND

Motion of the heart is known to affect image quality in cardiac PET. The prevalence of motion blurring in routine cardiac PET is not fully appreciated due to challenges identifying subtle motion artefacts. This study utilizes a recent prototype Data-Driven Motion Correction (DDMC) algorithm to generate corrected images that are compared with non-corrected images to identify visual differences in relative rubidium-82 perfusion images due to motion.

METHODS

300 stress and 300 rest static images were reconstructed with DDMC and without correction (NMC). The 600 DDMC/NMC image pairs were assigned Visual Difference Score (VDS). The number of non-diagnostic images were noted. A "Dwell Fraction" (DF) was derived from the data to quantify motion and predict image degradation.

RESULTS

Motion degradation (VDS = 1 or 2) was evident in 58% of stress images and 33% of rest images. Seven NMC images were non-diagnostic-these originated from six studies giving a 2% rate of non-diagnostic studies due to motion. The DF metric was able to effectively predict image degradation. The DDMC heart identification and tracking was successful in all images.

CONCLUSION

Motion degradation is present in almost half of all relative perfusion images. The DDMC algorithm is a robust tool for predicting, assessing and correcting image degradation.

Influence of patient motion on quantitative accuracy in cardiac 15O-water positron emission tomography

BACKGROUND

Patient motion is a common problem during cardiac PET. The purpose of the present study was to investigate to what extent motions influence the quantitative accuracy of cardiac 15O-water PET/CT and to develop a method for automated motion detection.

METHOD

Frequency and magnitude of motion was assessed visually using data from 50 clinical 15O-water PET/CT scans. Simulations of 4 types of motions with amplitude of 5 to 20 mm were performed based on data from 10 scans. An automated motion detection algorithm was evaluated on clinical and simulated motion data. MBF and PTF of all simulated scans were compared to the original scan used as reference.

RESULTS

Patient motion was detected in 68% of clinical cases by visual inspection. All observed motions were small with amplitudes less than half the LV wall thickness. A clear pattern of motion influence was seen in the simulations with a decrease of myocardial blood flow (MBF) in the region of myocardium to where the motion was directed. The perfusable tissue fraction (PTF) trended in the opposite direction. Global absolute average deviation of MBF was 3.1% ± 1.8% and 7.3% ± 6.3% for motions with maximum amplitudes of 5 and 20 mm, respectively. Automated motion detection showed a sensitivity of 90% for simulated motions ≥ 10 mm but struggled with the smaller (≤ 5 mm) simulated (sensitivity 45%) and clinical motions (accuracy 48%).

CONCLUSION

Patient motion can impair the quantitative accuracy of MBF. However, at typically occurring levels of patient motion, effects are similar to or only slightly larger than inter-observer variability, and downstream clinical effects are likely negligible.

Value of SiPM PET in myocardial perfusion imaging using Rubidium-82

BACKGROUND

PET scanners using silicon photomultipliers with digital readout (SiPM PET) have an improved temporal and spatial resolution compared to PET scanners using conventional photomultiplier tubes (PMT PET). However, the effect on image quality and visibility of perfusion defects in myocardial perfusion imaging (MPI) is unknown. Our aim was to determine the value of a SiPM PET scanner in MPI.

METHODS

We prospectively included 30 patients who underwent rest and regadenoson-induced stress Rubidium-82 (Rb-82) MPI on the D690 PMT PET (GE Healthcare) and within three weeks on the Vereos SiPM PET (Philips Healthcare). Two expert readers scored the image quality and assessed the existence of possible defects. In addition, interpreter's confidence, myocardial blood flow (MBF), and myocardial flow reserve (MFR) values were compared.

RESULTS

Image quality improved (P = 0.03) using the Vereos as compared to the D690. Image quality of the Vereos and the D690 was graded fair in 20% and 10%, good in 60% and 50%, and excellent in 20% and 40%, respectively. Defect interpretation and interpreter's confidence did not differ between the D690 and the Vereos (P > 0.50). There were no significant differences in rest MBF (P ≥ 0.29), stress MBF (P ≥ 0.11), and MFR (P ≥ 0.51).

CONCLUSION

SiPM PET provides an improved image quality in comparison with PMT PET. Defect interpretation, interpreter's confidence, and absolute blood flow measurements were comparable between both systems. SiPM PET is therefore a reliable technique for MPI using Rb-82.

TRIAL REGISTRATION

ToetsingOnline NL63853.075.17. Registered 13 November, 2017.

A preliminary evaluation of a high temporal resolution data-driven motion correction algorithm for rubidium-82 on a SiPM PET-CT system

BACKGROUND

In myocardial perfusion PET, images are acquired during vasodilator stress, increasing the likelihood of intra-frame motion blurring of the heart in reconstructed static images to assess relative perfusion. This work evaluated a prototype data-driven motion correction (DDMC) algorithm designed specifically for cardiac PET.

METHODS

A cardiac torso phantom, with a solid defect, was scanned stationary and being manually pulled to-and-fro in the axial direction with a random motion. Non-motion-corrected (NMC) and DDMC images were reconstructed. Total perfusion deficit was measured in the defect and profiles through the cardiac insert were defined. In addition, 46 static perfusion images from 36 rubidium-82 MPI patients were selected based upon a perception of motion blurring in the images. NMC and DDMC images were reconstructed, blinded, and scored on image quality and perceived motion.

RESULTS

Phantom data demonstrated near-perfect recovery of myocardial wall visualization and defect quantification with DDMC compared with the stationary phantom. Quality of clinical images was NMC: 10 non-diagnostic, 31 adequate, and 5 good; DDMC images: 0 non-diagnostic, 6 adequate, and 40 good.

CONCLUSION

The DDMC algorithm shows great promise in rubidium MPI PET with substantial improvements in image quality and the potential to salvage images considered non-diagnostic due to significant motion blurring.

Improved myocardial blood flow estimation with residual activity correction and motion correction in 18F-flurpiridaz PET myocardial perfusion imaging

PURPOSE

We sought to evaluate the diagnostic performance for coronary artery disease (CAD) of myocardial blood flow (MBF) quantification with ¹⁸F-flurpiridaz PET using motion correction (MC) and residual activity correction (RAC).

METHODS

In total, 231 patients undergoing same-day pharmacologic rest and stress ¹⁸F-flurpiridaz PET from Phase III Flurpiridaz trial (NCT01347710) were studied. Frame-by-frame MC was performed and RAC was accomplished by subtracting the rest residual counts from the dynamic stress polar maps. MBF and myocardial flow reserve (MFR) were derived with a two-compartment early kinetic model for the entire left ventricle (global), each coronary territory, and 17-segment. Global and minimal values of three territorial (minimal vessel) and segmental estimation (minimal segment) of stress MBF and MFR were evaluated in the prediction of CAD. MBF and MFR were evaluated with and without MC and RAC (1: no MC/no RAC, 2: no MC/RAC, 3: MC/RAC).

RESULTS

The area-under the receiver operating characteristics curve (AUC [95% confidence interval]) of stress MBF with MC/RAC was higher for minimal segment (0.89 [0.85-0.94]) than for minimal vessel (0.86 [0.81-0.92], p = 0.03) or global estimation (0.81 [0.75-0.87], p < 0.0001). The AUC of MFR with MC/RAC was higher for minimal segment (0.87 [0.81-0.93]) than for minimal vessel (0.83 [0.76-0.90], p = 0.014) or global estimation (0.77 [0.69-0.84], p < 0.0001). The AUCs of minimal segment stress MBF and MFR with MC/RAC were higher compared to those with no MC/RAC (p < 0.001 for both) or no MC/no RAC (p < 0.0001 for both).

CONCLUSIONS

Minimal segment MBF or MFR estimation with MC and RAC improves the diagnostic performance for obstructive CAD compared to global assessment.

Inter- and Intraobserver Repeatability of Myocardial Flow Reserve Values Determined with SPECT Study Using a Discovery NM530c Camera and Corridor 4DM Software

BACKGROUND

Myocardial blood flow (MBF) and flow reserve (MFR) examination, especially useful in the diagnosis of multivessel coronary artery disease (CAD), can be assessed with a cadmium-zinc-telluride (CZT) SPECT gamma camera, as an alternative to the expensive and less available PET. However, study processing is not free from subjective factors. Therefore, this paper aims to evaluate intra- and interobserver repeatability of MBF and MFR values obtained by the same operator and two independent operators.

METHODS

This study included 57 adult patients. MBF and MFR were assessed using a Discovery NM530c camera in a two-day, rest/dipyridamople protocol, using ^99mTc-MIBI. Data were processed using Corridor4DM software, twice by one operator and once by another operator.

RESULTS

The repeatability of the assessed values was quite good in the whole myocardium, LAD and LCX vascular territories, but was poor in the RCA territory.

CONCLUSIONS

The poor repeatability of MBF and MFR in RCA vascular territory can be explained by poor automatic orientation of the heart axis during post-processing and a so-called "cardiac creep" phenomenon. Better automatic heart orientation and introduction of automatic motion correction is likely to drastically improve this repeatability. In the present state of the software, PET is better for patients requiring assessment of MFR in the RCA territory.

Short-term repeatability of myocardial blood flow using 82Rb PET/CT: The effect of arterial input function position and motion correction

BACKGROUND

We tested the repeatability of myocardial blood flow (MBF) quantified using 82Rb with and without motion correction (MC) and with arterial input functions estimated from left ventricle (LV) and atrium (LA).

METHODS

Twenty-one patients referred for clinical 82Rb PET/CT underwent repeated rest scans in a single imaging session. Global MBF was quantified using three different assessments by two operators: (1) automatic processing without MC and LV arterial input function (AIF), (2) with MC and LV-AIF, and (3) with MC and LA-AIF. Inter-scan and inter-operator repeatability were tested using coefficient of variation (CV).

RESULTS

MC with LV-AIF did not change MBF (no MC: 1.01 ± 0.30 mL/min/g vs MC with LV-AIF: 1.01 ± 0.29, P = 0.70), whereas MC with LA-AIF showed significantly lower MBF assessments (0.95 ± 0.28 mL/min/g, P = 0.0006). We report significant improvement for test-retest reproducibility for global MBF following MC (CV; No MC: 16.0, MC (LV-AIF): 9.2, MC (LA-AIF): 8.8). Good inter-operator repeatability was observed for LV-AIF (CV = 4.7) and LA-AIF (CV = 5.6) for global MBF assessments.

CONCLUSIONS

MC significantly improved the test-retest repeatability between operators and between scans. MBF obtained after MC with LV-AIF were comparable, whereas MBFs after MC and LA-AIF were significantly reduced.

Assessment of motion correction in dynamic rubidium-82 cardiac PET with and without frame-by-frame adjustment of attenuation maps for calculation of myocardial blood flow

BACKGROUND

Patient motion during pharmacological stressing can have substantial impact on myocardial blood flow (MBF) estimated from dynamic PET. This work evaluated a motion correction algorithm with and without adjustment of the PET attenuation map.

METHODS

Frame-by-frame motion correction was performed by three users on 30 rubidium-82 studies. Data were divided equally into three groups of motion severity [mild (M1), moderate (M2) and severe (M3)]. MBF data were compared for non-motion corrected (NC), motion-corrected-only (MC) and with adjustment of the attenuation map (MCAC). Percentage differences of MBF were calculated in the coronary territories and 17-segment polar plots. Polar plots of spill-over were also generated from the data.

RESULTS

Median differences of 23% were seen in the RCA and 18% for the LAD in the M3 category for MC vs NC images. Differences for MCAC vs MC images were considerably smaller and typically < 10%. Spill-over plots for MC and MCAC were notably more uniform compared with NC images.

CONCLUSION

Motion correction for dynamic rubidium data is desirable for future MBF software updates. Adjustment of the PET attenuation map results in only marginal differences and therefore is unlikely to be an essential requirement. Assessing the uniformity of spill-over plots is a useful visual aid for verifying motion correction techniques.

Dynamic cardiac PET motion correction using 3D normalized gradient fields in patients and phantom simulations

This work expands on the implementation of three-dimensional (3D) normalized gradient fields to correct for whole-body motion and cardiac creep in [N-13]-ammonia patient studies and evaluates its accuracy using a dynamic phantom simulation model.

METHODS

A full rigid-body algorithm was developed using 3D normalized gradient fields including a multi-resolution step and sampling off the voxel grid to reduce interpolation artifacts. Optimization was performed using a weighted similarity metric that accounts for opposing gradients between images of blood pool and perfused tissue without the need for segmentation. Forty-three retrospective dynamic [N-13]-ammonia PET/CT rest/adenosine-stress patient studies were motion corrected and the mean motion parameters plotted at each frame time point. Motion correction accuracy was assessed using a comprehensive dynamic XCAT simulation incorporating published physiologic parameters of the heart's trajectory following adenosine infusion as well as corrupted attenuation correction commonly observed in clinical studies. Accuracy of the algorithm was assessed objectively by comparing the errors between isosurfaces and centers of mass of the motion corrected XCAT simulations.

RESULTS

In the patient studies, the overall mean cranial-to-caudal translation was 7 mm at stress over the duration of the adenosine infusion. Noninvasive clinical measures of relative flow reserve and myocardial flow reserve were highly correlated with their invasive analogues. Motion correction accuracy assessed with the XCAT simulations showed an error of <1 mm in late perfusion frames that broadened gradually to <3 mm in earlier frames containing blood pool.

CONCLUSION

This work demonstrates that patients undergoing [N-13]-ammonia dynamic PET/CT exhibit a large cranial-to-caudal translation related to cardiac creep primarily at stress and to a lesser extent at rest, which can be accurately corrected by optimizing their 3D normalized gradient fields. Our approach provides a solution to the challenging condition where the image intensity and its gradients are opposed without the need for segmentation and remains robust in the presence of PET-CT mismatch.

EANM procedural guidelines for PET/CT quantitative myocardial perfusion imaging

The use of cardiac PET, and in particular of quantitative myocardial perfusion PET, has been growing during the last years, because scanners are becoming widely available and because several studies have convincingly demonstrated the advantages of this imaging approach. Therefore, there is a need of determining the procedural modalities for performing high-quality studies and obtaining from this demanding technique the most in terms of both measurement reliability and clinical data. Although the field is rapidly evolving, with progresses in hardware and software, and the near perspective of new tracers, the EANM Cardiovascular Committee found it reasonable and useful to expose in an updated text the state of the art of quantitative myocardial perfusion PET, in order to establish an effective use of this modality and to help implementing it on a wider basis. Together with the many steps necessary for the correct execution of quantitative measurements, the importance of a multiparametric approach and of a comprehensive and clinically useful report have been stressed.

Myocardial creep-induced misalignment artifacts in PET/MR myocardial perfusion imaging

Purpose

Misalignment between positron emission tomography (PET) datasets and attenuation correction (AC) maps is a potential source of artifacts in myocardial perfusion imaging (MPI). We assessed the impact of adenosine on the alignment of AC maps derived from magnetic resonance (MR) and PET datasets during MPI on a hybrid PET/MR scanner.

Methods

Twenty-eight volunteers underwent adenosine stress and rest 13N-ammonia MPI on a PET/MR. We acquired Dixon sequences for the creation of MRAC maps. After reconstruction of the original non-shifted PET images, we examined MRAC and PET datasets for cardiac spatial misalignment and, if necessary, reconstructed a second set of shifted PET images after manually adjusting co-registration. Summed rest, stress, and difference scores (SRS, SSS, and SDS) were compared between shifted and non-shifted PET images. Additionally, we measured the amount of cranial movement of the heart (i.e., myocardial creep) after termination of adenosine infusion.

Results

Realignment was necessary for 25 (89.3%) stress and 12 (42.9%) rest PET datasets. Median SRS, SSS, and SDS of the non-shifted images were 6 (IQR = 4–7), 12 (IQR = 7–18), and 8 (IQR = 2–11), respectively, and of the shifted images 2 (IQR = 1–6), 4 (IQR = 7–18), and 1 (IQR = 0–2), respectively. All three scores were significantly higher in non-shifted versus shifted images (all p < 0.05). The difference in SDS correlated moderately but significantly with the amount of myocardial creep (r = 0.541, p = 0.005).

Conclusion

Misalignment of MRAC and PET datasets commonly occurs during adenosine stress MPI on a hybrid PET/MR device, potentially leading to an increase in false-positive findings. Our results suggest that myocardial creep may substantially account for this and prompt for a careful review and correction of PET/MRAC data.

No need for frame-wise attenuation correction in dynamic Rubidium-82 PET for myocardial blood flow quantification

BACKGROUND

Regadenoson-induced stress causes a repositioning of the heart, myocardial creep, in half of the patients undergoing Rubidium-82 (Rb-82) positron emission tomography (PET). As a result, misalignment of dynamic PET and computer tomography (CT) may occur, possibly affecting CT-based attenuation correction (AC) and thereby PET-based myocardial blood flow (MBF) quantification. Our aim was to determine the need for frame-wise PET-CT AC to obtain reliable MBF measurements.

METHODS

31 Out of 64 consecutive patients had myocardial creep during regadenoson-induced stress Rb-82 PET-CT and were included. Prior to PET image reconstruction, we applied two AC methods; single PET-CT alignment and frame-wise alignment in which PET time-frames with myocardial creep were individually co-registered with CT. The PET-CT misalignment was then quantified and MBFs for the three vascular territories and whole myocardium were calculated and compared between both methods.

RESULTS

The magnitude of misalignment due to myocardial creep was 13.8 ± 4.5 mm in caudal-cranial direction, 1.8 ± 2.1 mm in medial-lateral and 2.5 ± 1.8 mm in anterior-posterior direction. Frame-wise PET-CT registration did not result in different MBF measurements (P ≥ .07) and the magnitude of misalignment and MBF differences did not correlate (P ≥ .58).

CONCLUSION

There is no need for frame-wise AC in dynamic Rb-82 PET for MBF quantification. Single alignment seems sufficient in patients with myocardial creep.

How to detect and correct myocardial creep in myocardial perfusion imaging using Rubidium-82 PET?

Reliability of myocardial blood flow (MBF) quantification in myocardial perfusion imaging (MPI) using PET can majorly be affected by the occurrence of myocardial creep when using pharmacologically induced stress. In this paper, we provide instructions on how to detect and correct for myocardial creep. For example, in each time frame of the PET images the myocardium contour and the observed activity have to be compared to check for misalignments. In addition, we provide an overview of the functionality of commonly used software packages to perform this quality control step as not all software packages currently provide this functionality. Furthermore, important clinical considerations to obtain accurate MBF measurements are given.