Effects of patient movement on measurements of myocardial blood flow and viability in resting ¹⁵O-water PET studies

TAI-GAN: A Temporally and Anatomically Informed Generative Adversarial Network for early-to-late frame conversion in dynamic cardiac PET inter-frame motion correction

Inter-frame motion in dynamic cardiac positron emission tomography (PET) using rubidium-82 (82Rb) myocardial perfusion imaging impacts myocardial blood flow (MBF) quantification and the diagnosis accuracy of coronary artery diseases. However, the high cross-frame distribution variation due to rapid tracer kinetics poses a considerable challenge for inter-frame motion correction, especially for early frames where intensity-based image registration techniques often fail. To address this issue, we propose a novel method called Temporally and Anatomically Informed Generative Adversarial Network (TAI-GAN) that utilizes an all-to-one mapping to convert early frames into those with tracer distribution similar to the last reference frame. The TAI-GAN consists of a feature-wise linear modulation layer that encodes channel-wise parameters generated from temporal information and rough cardiac segmentation masks with local shifts that serve as anatomical information. Our proposed method was evaluated on a clinical 82Rb PET dataset, and the results show that our TAI-GAN can produce converted early frames with high image quality, comparable to the real reference frames. After TAI-GAN conversion, the motion estimation accuracy and subsequent myocardial blood flow (MBF) quantification with both conventional and deep learning-based motion correction methods were improved compared to using the original frames. The code is available at https://github.com/gxq1998/TAI-GAN.

Improvement in the estimation of perfusable tissue fraction and myocardial flow reserve in the ischemic myocardial lesions using ECG-gated dynamic myocardial PET with 15O-water

OBJECTIVE

Perfusable tissue fraction (PTF) and myocardial flow reserve (MFR) from 15O-water dynamic positron emission tomography (PET) are parameters of myocardial viability. However, myocardial motion causes errors in these values. We aimed to develop accurate estimation of PTF and MFR in ischemic lesions using an electro-cardiogram (ECG)-gated dynamic myocardial PET with 15O-water.

METHODS

Twenty-seven patients with ischemic heart disease were enrolled. All patients underwent percutaneous coronary intervention (PCI) or coronary artery bypass grafting (CABG). List mode 3D PET data and ECG signals were acquired using Philips Gemini TF64 instrument. For each scan, 500 MBq of 15O-water was infused slowly for 2 min, and the dynamic data were scanned for 6 min. Both non-gated dynamic images and ECG-gated diastolic dynamic images were reconstructed. On the myocardial PET images of each patient, the entire myocardial region of interest (ROI) was set and divided into 17 segments. Myocardial blood flow in the resting state (rest MBF), hyperemic state (stress MBF), PTF, and MFR in each segment were estimated from both non-gated and ECG-gated dynamic PET images. Coronary arteriograms were obtained for all patients. In total, 128 normal segments without stenosis and 50 ischemic segments with > 90% stenosis were evaluated.

RESULTS

In the ischemic myocardial segments, the PTF with ECG-gated PET was estimated as significantly lower than that with non-gated PET (0.63 ± 0.09 vs. 0.72 ± 0.08 [mL/mL], p < 0.001). The ECG-gated PET estimated a significantly lower PTF in the ischemic segments than in the normal segments (0.63 ± 0.09 vs. 0.67 ± 0.07 [mL/mL], p < 0.01). In the normal segments, the ECG-gated PET detected no significant difference in MFR compared with those from the non-gated PET (2.15 ± 0.76 vs. 2.24 ± 0.79, p = 0.28). However, in the ischemic myocardial segments, the MFR with ECG-gated PET was estimated as significantly lower than that with the non-gated PET (1.23 ± 0.29 vs. 1.69 ± 0.71, p < 0.001). The ECG-gated PET presented a significantly higher inter-observer reproducibility of PTF and rest MBF than the non-gated PET (p < 0.01). Neither stress MBF nor MFR yielded significant differences in inter-observer reproducibility between the ECG-gated and non-gated PET.

CONCLUSIONS

The ECG-gated dynamic 15O-water PET suppressed the myocardial motion effect and resulted in a lower PTF and MFR in ischemic myocardial lesions than the non-gated PET. The ECG-gated PET seemed to be better than the conventional non-gated dynamic PET for the detection of ischemic myocardial lesion.

82Rb and [15O]H2O myocardial perfusion PET imaging: a prospective head to head comparison

BACKGROUND

82Rb PET and [15O]H2O PET are both validated tracers for myocardical perfusion imaging but have not previously been compared clinically. During our site's transition from 82Rb to [15O]H2O PET, we performed a head-to-head comparison in a mixed population with suspected ischemic heart disease.

METHODS

A total of 37 patients referred for perfusion imaging due to suspicion of coronary stenosis were examined with both 82Rb and [15O]H2O PET on the same day in rest and during adenosine-induced stress. The exams were rated by two blinded readers as normal, regional ischemia, globally reduced myocardial perfusion, or myocardial scarring. For [15O]H2O PET, regional ischemia was defined as two neighboring segments with average stress perfusion ≤ 2.3 mL/(min·g). Further, we evaluated a total perfusion deficit (TPD) of ≥ 10% as a more conservative marker of ischemia.

RESULTS

[15O]H2O PET identified more patients with regional ischemia: 17(46%) vs 9(24%), agreement: 59% corresponding to a Cohen's kappa of .31 [95%CI .08-.53], (P < .001). Using the more conservative TPD ≥ 10%, the agreement increased to 86% corresponding to a kappa of .62 [95%CI .33-.92], (P = .001). For the subgroup of patients with no known heart disease (n = 18), the agreement was 94%. Interrater agreement was 95% corresponding to a kappa of .89 [95%CI .74-1.00] (P < .001).

CONCLUSIONS

In clinical transition from 82Rb to [15O]H2O PET, it is important to take into account the higher frequency of patients with regional ischemia detected by [15O]H2O PET.

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.

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.

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.

Automatic Inter-Frame Patient Motion Correction for Dynamic Cardiac PET Using Deep Learning

Patient motion during dynamic PET imaging can induce errors in myocardial blood flow (MBF) estimation. Motion correction for dynamic cardiac PET is challenging because the rapid tracer kinetics of 82Rb leads to substantial tracer distribution change across different dynamic frames over time, which can cause difficulties for image registration-based motion correction, particularly for early dynamic frames. In this paper, we developed an automatic deep learning-based motion correction (DeepMC) method for dynamic cardiac PET. In this study we focused on the detection and correction of inter-frame rigid translational motion caused by voluntary body movement and pattern change of respiratory motion. A bidirectional-3D LSTM network was developed to fully utilize both local and nonlocal temporal information in the 4D dynamic image data for motion detection. The network was trained and evaluated over motion-free patient scans with simulated motion so that the motion ground-truths are available, where one million samples based on 65 patient scans were used in training, and 600 samples based on 20 patient scans were used in evaluation. The proposed method was also evaluated using additional 10 patient datasets with real motion. We demonstrated that the proposed DeepMC obtained superior performance compared to conventional registration-based methods and other convolutional neural networks (CNN), in terms of motion estimation and MBF quantification accuracy. Once trained, DeepMC is much faster than the registration-based methods and can be easily integrated into the clinical workflow. In the future work, additional investigation is needed to evaluate this approach in a clinical context with realistic patient motion.

Motion in nuclear cardiology imaging: types, artifacts, detection and correction techniques

In this paper, the authors review the field of motion detection and correction in nuclear cardiology with single photon emission computed tomography (SPECT) and positron emission tomography (PET) imaging systems. We start with a brief overview of nuclear cardiology applications and description of SPECT and PET imaging systems, then explaining the different types of motion and their related artefacts. Moreover, we classify and describe various techniques for motion detection and correction, discussing their potential advantages including reference to metrics and tasks, particularly towards improvements in image quality and diagnostic performance. In addition, we emphasize limitations encountered in different motion detection and correction methods that may challenge routine clinical applications and diagnostic performance.

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.

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.

Blood pool and tissue phase patient motion effects on 82rubidium PET myocardial blood flow quantification

BACKGROUND

Patient motion can lead to misalignment of left ventricular volumes of interest and subsequently inaccurate quantification of myocardial blood flow (MBF) and flow reserve (MFR) from dynamic PET myocardial perfusion images. We aimed to identify the prevalence of patient motion in both blood and tissue phases and analyze the effects of this motion on MBF and MFR estimates.

METHODS

We selected 225 consecutive patients that underwent dynamic stress/rest rubidium-82 chloride (82Rb) PET imaging. Dynamic image series were iteratively reconstructed with 5- to 10-second frame durations over the first 2 minutes for the blood phase and 10 to 80 seconds for the tissue phase. Motion shifts were assessed by 3 physician readers from the dynamic series and analyzed for frequency, magnitude, time, and direction of motion. The effects of this motion isolated in time, direction, and magnitude on global and regional MBF and MFR estimates were evaluated. Flow estimates derived from the motion corrected images were used as the error references.

RESULTS

Mild to moderate motion (5-15 mm) was most prominent in the blood phase in 63% and 44% of the stress and rest studies, respectively. This motion was observed with frequencies of 75% in the septal and inferior directions for stress and 44% in the septal direction for rest. Images with blood phase isolated motion had mean global MBF and MFR errors of 2%-5%. Isolating blood phase motion in the inferior direction resulted in mean MBF and MFR errors of 29%-44% in the RCA territory. Flow errors due to tissue phase isolated motion were within 1%.

CONCLUSIONS

Patient motion was most prevalent in the blood phase and MBF and MFR errors increased most substantially with motion in the inferior direction. Motion correction focused on these motions is needed to reduce MBF and MFR errors.

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

BACKGROUND

Repositioning of the heart during myocardial perfusion imaging (MPI) using Rubidium-82 (Rb-82) PET may occur when using regadenoson. Our aim was to determine the prevalence and the effect of correcting for this myocardial creep on myocardial blood flow (MBF) quantification.

METHODS

We retrospectively included 119 consecutive patients who underwent dynamic rest- and regadenoson-induced stress MPI using Rb-82 PET. The presence of myocardial creep was visually assessed in the dynamic stress PET series by identifying differences between the automatically drawn myocardium contour and the activity. Uncorrected and corrected stress MBFs were compared for the three vascular territories (LAD, LCX, and RCA) and for the whole myocardium.

RESULTS

Myocardial creep was observed in 52% of the patients during stress. Mean MBF values decreased after correction in the RCA from 4.0 to 2.7 mL/min/g (P  < 0.001), in the whole myocardium from 2.7 to 2.6 mL/min/g (P  = 0.01), and increased in the LAD from 2.5 to 2.6 mL/min/g (P  = 0.03) and remained comparable in the LCX (P  = 0.3).

CONCLUSIONS

Myocardial creep is a frequent phenomenon when performing regadenoson-induced stress Rb-82 PET and has a significant impact on MBF values, especially in the RCA territory. As this may hamper diagnostic accuracy, myocardial creep correction seems necessary for reliable quantification.

Assessing Reliability of Myocardial Blood Flow After Motion Correction With Dynamic PET Using a Bayesian Framework

The estimation of myocardial blood flow (MBF) in dynamic PET can be biased by many different processes. A major source of error, particularly in clinical applications, is patient motion. Patient motion, or gross motion, creates displacements between different PET frames as well as between the PET frames and the CT-derived attenuation map, leading to errors in MBF calculation from voxel time series. Motion correction techniques are challenging to evaluate quantitatively and the impact on MBF reliability is not fully understood. Most metrics, such as signal-to-noise ratio (SNR), are characteristic of static images, and are not specific to motion correction in dynamic data. This study presents a new approach of estimating motion correction quality in dynamic cardiac PET imaging. It relies on calculating a MBF surrogate, K₁ , along with the uncertainty on the parameter. This technique exploits a Bayesian framework, representing the kinetic parameters as a probability distribution, from which the uncertainty measures can be extracted. If the uncertainty extracted is high, the parameter studied is considered to have high variability - or low confidence - and vice versa. The robustness of the framework is evaluated on simulated time activity curves to ensure that the uncertainties are consistently estimated at the multiple levels of noise. Our framework is applied on 40 patient datasets, divided in 4 motion magnitude categories. Experienced observers manually realigned clinical datasets with 3D translations to correct for motion. K₁ uncertainties were compared before and after correction. A reduction of uncertainty after motion correction of up to 60% demonstrates the benefit of motion correction in dynamic PET and as well as provides evidence of the usefulness of the new method presented.

Impact of pharmacological stress agent on patient motion during rubidium-82 myocardial perfusion PET/CT

BACKGROUND

Patient motion has been demonstrated to have a significant impact on the quality and accuracy of rubidium-82 myocardial perfusion PET/CT. This study aimed to investigate the effect on patient motion of two pharmacological stressing agents, adenosine and regadenoson.

METHODS AND RESULTS

Dynamic data were retrospectively analyzed in 90 patients undergoing adenosine (n = 30), incremental adenosine (n = 30), or regadenoson (n = 30) rubidium-82 myocardial perfusion PET/CT. Severity of motion was scored qualitatively using a four-point (0-3) scale and quantitatively using frame-to-frame pixel shifts. The type of motion, returning or non-returning, and the frame in which it occurred were also recorded. There were significant differences in both the qualitative and quantitative scores comparing regadenoson to adenosine (P = .025 and P < .001) and incremental adenosine (P = .014, P = .015), respectively. The difference in scores between adenosine and incremental adenosine was not significant. Where motion was present, significantly more adenosine patients were classed as non-returning (P = .018). The median frames for motion occurring were 12 for regadenoson and 14 for both adenosine cohorts.

CONCLUSIONS

The choice of stressing protocol impacts significantly on patient motion. Patients stressed with regadenoson have significantly lower motion scores than those stressed with adenosine, using local protocols. This motion is more likely to be associated with a drift of the heart away from a baseline position, coinciding with the termination of infusion.

Motion Correction and Its Impact on Absolute Myocardial Blood Flow Measures with PET

PURPOSE OF REVIEW

Motion artifacts, due to cardiac and respiratory cycles, myocardial cardiac creep, or gross patient movements, have been extensively investigated in the context of relative myocardial perfusion imaging with SPECT and PET. These movements have been identified as a major source of errors in image quantification and diagnosis. Recently, as dynamic PET quantification for myocardial blood flow assessment has entered clinical practice, similar questions have arisen on the impact of motion on final blood flow values.

RECENT FINDINGS

While preliminary investigations have underlined the potential impact of these motions on MBF quantification, their correction on dynamic acquisition remains challenging and limited to research studies. Gross patient's body movements occur in a consistent number of cases, particularly during stress acquisition, typically involving a limited number of image frames. If undetected, these movements can lead to great differences in flow values and consequently misdiagnosis. Quality control routines can be applied to automatically inspect the shape of time activity curves and to help identify motion artifacts. Cyclic cardiac and respiratory motion may have a considerable impact on final flow values. Correction of gross body motion represents a priority in the context of optimizing absolute flow clinical routine utilization and protocol standardization.

Current status of nuclear cardiology in Japan: Ongoing efforts to improve clinical standards and to establish evidence

Nuclear cardiology imaging tests are widely performed in Japan as clinical practice. The Japanese nuclear cardiology community has developed new diagnostic imaging tests using (123)I-beta-methyl-p-iodophenyl-pentadecanoic acid, (123)I-metaiodobenzylguanidine, and (18)F-fluorodeoxyglucose PET for detecting cardiac involvement in sarcoidosis. These tests have become popular worldwide. The Japanese Circulation Society and the Japanese Society of Nuclear Cardiology have published clinical imaging guidelines showing indications and standards for the new imaging tests. JSNC is currently striving to improve the standard of clinical practice and is promoting research activities.

Data-driven respiratory motion tracking and compensation in CZT cameras: a comprehensive analysis of phantom and human images

BACKGROUND

This study described a method for tracking and compensating respiratory motion in cadmium-zinc-telluride (CZT) cameras. We evaluated motion effects on myocardial perfusion imaging and assessed the usefulness of motion compensation in phantom and clinical studies.

METHODS

SPECT studies were obtained from an oscillating heart phantom and 552 patients using CZT cameras with list-mode acquisition. Images were reformatted in 500-ms frames, and the activity centroid was calculated as respiratory signal. The myocardial perfusion, left ventricular (LV) wall thickness, and LV volume were assessed before and after the motion compensation technique.

RESULTS

In phantom studies, we documented only minimal bias between simulated and measured shifts. Significantly reduced tracer activity, increased wall thickness and decreased volume in scans with 15 mm or more axial shifts were noted. In clinical studies, there was a higher prevalence of significant motion after treadmill exercise. The motion compensation technique could successfully compensate those motion artifacts.

CONCLUSION

The described method allows for tracking and compensating respiratory motion in CZT cameras. Significant respiratory motion is still not uncommon using CZT cameras, especially in patients who underwent treadmill tests. Motion blurring can be compensated using image processing techniques and image quality could be significantly improved.

Quantification of myocardial blood flow using (201)Tl SPECT and population-based input function

OBJECTIVES

Thallium-201 ((201)Tl) single photon emission computed tomography (SPECT) is an important tool in the diagnosis of ischemic heart disease. Absolute quantification of myocardial blood flow (MBF) has the potential to provide more useful information on myocardial perfusion than semi-quantitative assessments. This study aimed to validate the quantification of MBF using (201)Tl cardiac SPECT based on a population-averaged input function (STD-IF) and one-point blood sample technique.

METHODS

(201)Tl emission and computed tomography (CT)-based attenuation scans were performed on 11 healthy volunteers at rest using a SPECT/CT scanner. Individual input functions (IND-IFs) during the emission scans were based on arterial blood samples. The STD-IF technique was validated as follows: (1) optimal time to calibrate a STD-IF was determined to minimize differences between the calibrated STD-IF and the IND-IFs. (2) Tissue time-activity curves (TTACs) were generated based on a single-tissue compartment model for MBFtrue = 0.5, 1.0, 1.5, and 2.0 mL/min/g, a constant distribution volume of 45 mL/mL, and IND-IFs. The pseudo STD-IF for each subject was generated using the leave-one-out technique. Using the optimal calibration time and the pseudo STD-IFs, MBF values were estimated on the TTACs with an autoradiography method. Optimal mid-scan time (MST) with a fixed duration of 20 min was determined to minimize intersubject variation in estimated MBF errors, and (3) Global and regional MBF values estimated with pseudo STD-IFs were compared to those with IND-IFs using the optimal calibration time and MST.

RESULTS

The optimal calibration time and MST were both 20 min after (201)Tl injection. Global MBF determined using both IND-IFs and pseudo STD-IF showed significant correlations with rate-pressure products, R (2) = 0.645; p < 0.01 and R (2) = 0.303; p < 0.05, respectively. The mean percent error in regional MBF using pseudo STD-IFs was 0.69 ± 7.80 % (-12.80 to 14.25 %). No significant difference was observed between regional MBF values using IND-IFs and pseudo STD-IFs.

CONCLUSION

This study demonstrated that the proposed technique based on a STD-IF and one-point blood sample provided hemodynamically reasonable global MBF values and the regional MBF values comparable to those with IND-IFs.

Motion Artifacts in Oncological and Cardiac PET Imaging

Image quality in PET examinations is influenced by several factors. Patient motion during PET data acquisition is a substantial problem that potentially leads to smearing artifacts, resulting in the loss of diagnostic accuracy both in visual and quantitative image analyses. In hybrid imaging, coregistration of functional (PET) and morphologic (CT or MR imaging) data can be hampered by patient movement between the acquisitions, resulting in additional sources of error. This article describes the artifacts due to patient movement.