Volumetric quantification of myocardial perfusion using analysis of multi-detector computed tomography 3D datasets: comparison with nuclear perfusion imaging

Can Dynamic Contrast-Enhanced CT Quantify Perfusion in a Stimulated Muscle of Limited Size? A Rat Model

BACKGROUND

Muscle injury may result in damage to the vasculature, rendering it unable to meet the metabolic demands of muscle regeneration and healing. Therefore, therapies frequently aim to maintain, restore, or improve blood supply to the injured muscle. Although there are several options to assess the vascular outcomes of these therapies, few are capable of spatially assessing perfusion in large volumes of tissue.

QUESTIONS/PURPOSES

Can dynamic contrast-enhanced CT (DCE-CT) imaging acquired with a clinical CT scanner be used in a rat model to quantify perfusion in the anterior tibialis muscle at spatially relevant volumes, as assessed by (1) the blood flow rate and tissue blood volume in the muscle after three levels of muscle stimulation (low, medium, and maximum) relative to baseline as determined by the non-stimulated contralateral leg; and (2) how do these measurements compare with those obtained by the more standard approach of microsphere perfusion?

METHODS

The right anterior tibialis muscles of adult male Sprague Dawley rats were randomized to low- (n = 10), medium- (n = 6), or maximum- (n = 3) level (duty cycles of 2.5%, 5.0%, and 20%, respectively) nerve electrode coupled muscle stimulation directly followed by DCE-CT imaging. Tissue blood flow and blood volume maps were created using commercial software and volumetrically measured using NIH software. Although differences in blood flow were detectable across the studied levels of muscle stimulation, a review of the evidence suggested the absolute blood flow quantified was underestimated. Therefore, at a later date, a separate set of adult male Sprague Dawley rats were randomized for microsphere perfusion (n = 7) to define blood flow in the animal model with an accepted standard. With this technique, intra-arterial particles sized to freely flow in blood but large enough to lodge in tissue capillaries were injected. Simultaneously, blood sampling at a fixed flow rate was simultaneously performed to provide a fixed blood flow rate sample. The tissues of interest were then explanted and assessed for the total number of particles per tissue volume. Tissue blood flow rate was then calculated based on the particle count ratio within the reference sample. Note that a tissue's blood volume cannot be calculated with this method. Comparison analysis to the non-stimulated baseline leg was performed using two-tailed paired student t-test. An ANOVA was used to compare difference between stimulation groups.

RESULTS

DCE-CT measured (mean ± SD) increasing tissue blood flow differences in stimulated anterior tibialis muscle at 2.5% duty cycle (32 ± 5 cc/100 cc/min), 5.0% duty cycle (46 ± 13 cc/100 cc/min), and 20% duty cycle (73 ± 3 cc/100 cc/min) compared with the paired contralateral non-stimulated anterior tibialis muscle (10 ± 2 cc/100 cc/min, mean difference 21 cc/100 cc/min [95% CI 17.08 to 25.69]; 9 ± 1 cc/100 cc/min, mean difference 37 cc/100 cc/min [95% CI 23.06 to 50.11]; and 11 ± 2 cc/100 cc/min, mean difference 62 cc/100 cc/min [95% CI 53.67 to 70.03]; all p < 0.001). Similarly, DCE-CT showed increasing differences in tissue blood volumes within the stimulated anterior tibialis muscle at 2.5% duty cycle (23.2 ± 4.2 cc/100 cc), 5.0% duty cycle (39.2 ± 7.2 cc/100 cc), and 20% duty cycle (52.5 ± 13.1 cc/100 cc) compared with the paired contralateral non-stimulated anterior tibialis muscle (3.4 ± 0.7 cc/100 cc, mean difference 19.8 cc/100 cc [95% CI 16.46 to 23.20]; p < 0.001; 3.5 ± 0.4 cc/100 cc, mean difference 35.7 cc/100 cc [95% CI 28.44 to 43.00]; p < 0.001; and 4.2 ± 1.3 cc/100 cc, mean difference 48.3 cc/100 cc [95% CI 17.86 to 78.77]; p = 0.010). Microsphere perfusion measurements also showed an increasing difference in tissue blood flow in the stimulated anterior tibialis muscle at 2.5% duty cycle (62 ± 43 cc/100 cc/min), 5.0% duty cycle (89 ± 52 cc/100 cc/min), and 20% duty cycle (313 ± 269 cc/100 cc/min) compared with the paired contralateral non-stimulated anterior tibialis muscle (8 ± 4 cc/100 cc/min, mean difference 55 cc/100 cc/min [95% CI 15.49 to 94.24]; p = 0.007; 9 ± 9 cc/100 cc/min, mean difference 79 cc/100 cc/min [95% CI 33.83 to 125.09]; p = 0.003; and 18 ± 18 cc/100 cc/min, mean difference 295 cc/100 cc/min [95% CI 8.45 to 580.87]; p = 0.023). Qualitative comparison between the methods suggests that DCE-CT values underestimate tissue blood flow with a post-hoc ANOVA showing DCE-CT blood flow values within the 2.5% duty cycle group (32 ± 5 cc/100 cc/min) to be less than the microsphere perfusion value (62 ± 43 cc/100 cc/min) with a mean difference of 31 cc/100 cc/min (95% CI 2.46 to 60.23; p = 0.035).

CONCLUSIONS

DCE-CT using a clinical scanner is a feasible modality to measure incremental changes of blood flow and tissue blood volume within a spatially challenged small animal model. Care should be taken in studies where true blood flow values are needed, as this particular small-volume muscle model suggests true blood flow is underestimated using the specific adaptions of DCE-CT acquisition and image processing chosen.

CLINICAL RELEVANCE

CT perfusion is a clinically available modality allowing for translation of science from bench to bedside. Adapting the modality to fit small animal models that are relevant to muscle healing may hasten time to clinical utility.

Hemodynamic impact of coronary stenosis using computed tomography: comparison between noninvasive fractional flow reserve and 3D fusion of coronary angiography with stress myocardial perfusion

Vasodilator-stress CT perfusion imaging in addition to CT coronary angiography (CTCA) may provide a single-test alternative to nuclear stress testing, commonly used to assess hemodynamic significance of stenosis. Another alternative is fractional flow reserve (FFR) calculated from cardiac CT images. We studied the concordance between these two approaches and their relationship to outcomes. We prospectively studied 150 patients with chest pain, who underwent CTCA and regadenoson CT. CTCA images were interpreted for presence and severity of stenosis. Fused 3D displays of subendocardial X-ray attenuation with coronary arteries were created to detect stress perfusion defects (SPD) in each coronary territory. In patients with stenosis > 25%, CT-FFR was quantified. Significant stenosis was determined by: (1) combination of stenosis > 50% with an SPD, (2) CT-FFR ≤ 0.80. Patients were followed-up for 36 ± 25 months for death, myocardial infarction or revascularization. After excluding patients with normal arteries and technical/quality issues, in final analysis of 76 patients, CTCA depicted stenosis > 70% in 13/224 arteries, 50-70% in 24, and < 50% in 187. CT-FFR ≤ 0.80 was found in 41/224 arteries, and combination of SPD with > 50% stenosis in 31/224 arteries. Inter-technique agreement was 89%. Despite high incidence of abnormal CT-FFR (30/76 patients), only 7 patients experienced adverse outcomes; 6/7 also had SPDs. Only 1/9 patients with CT-FFR ≤ 0.80 but normal perfusion had an event. Fusion of CTCA and stress perfusion can help determine the hemodynamic impact of stenosis in one test, in good agreement with CT-FFR. Adding stress CT perfusion analysis may help risk-stratify patients with abnormal CT-FFR.

Non-invasive assessment of the haemodynamic significance of coronary stenosis using fusion of cardiac computed tomography and 3D echocardiography

Aims

Abnormal computed tomography coronary angiography (CTCA) often leads to stress testing to determine haemodynamic significance of stenosis. We hypothesized that instead, this could be achieved by fusion imaging of the coronary anatomy with 3D echocardiography (3DE)-derived resting myocardial deformation.

Methods and results

We developed fusion software that creates combined 3D displays of the coronary arteries with colour maps of longitudinal strain and tested it in 28 patients with chest pain, referred for CTCA (256 Philips scanner) who underwent 3DE (Philips iE33) and regadenoson stress CT. To obtain a reference for stenosis significance, coronaries were also fused with colour maps of stress myocardial perfusion. 3D displays were used to detect stress perfusion defect (SPD) and/or resting strain abnormality (RSA) in each territory. CTCA showed 56 normal arteries, stenosis <50% in 17, and >50% in 8 arteries. Of the 81 coronary territories, SPDs were noted in 20 and RSAs in 29. Of the 59 arteries with no stenosis >50% and no SPDs, considered as normal, 12 (20%) had RSAs. Conversely, with stenosis >50% and SPDs (haemodynamically significant), RSAs were considerably more frequent (5/6 = 83%). Overall, resting strain and stress perfusion findings were concordant in 64/81 arteries (79% agreement).

Conclusions

Fusion of CTCA and 3DE-derived data allows direct visualization of each coronary artery and strain in its territory. In this feasibility study, resting strain showed good agreement with stress perfusion, indicating that it may be potentially used to assess haemodynamic impact of coronary stenosis, as an alternative to stress testing that entails additional radiation exposure.

Fusion of Three-Dimensional Echocardiographic Regional Myocardial Strain with Cardiac Computed Tomography for Noninvasive Evaluation of the Hemodynamic Impact of Coronary Stenosis in Patients with Chest Pain

BACKGROUND

Combined evaluation of coronary stenosis and the extent of ischemia is essential in patients with chest pain. Intermediate-grade stenosis on computed tomographic coronary angiography (CTCA) frequently triggers downstream nuclear stress testing. Alternative approaches without stress and/or radiation may have important implications. Myocardial strain measured from echocardiographic images can be used to detect subclinical dysfunction. The authors recently tested the feasibility of fusion of three-dimensional (3D) echocardiography-derived regional resting longitudinal strain with coronary arteries from CTCA to determine the hemodynamic significance of stenosis. The aim of the present study was to validate this approach against accepted reference techniques.

METHODS

Seventy-eight patients with chest pain referred for CTCA who also underwent 3D echocardiography and regadenoson stress computed tomography were prospectively studied. Left ventricular longitudinal strain data (TomTec) were used to generate fused 3D displays and detect resting strain abnormalities (RSAs) in each coronary territory. Computed tomographic coronary angiographic images were interpreted for the presence and severity of stenosis. Fused 3D displays of subendocardial x-ray attenuation were created to detect stress perfusion defects (SPDs). In patients with stenosis >25% in at least one artery, fractional flow reserve was quantified (HeartFlow). RSA as a marker of significant stenosis was validated against two different combined references: stenosis >50% on CTCA and SPDs seen in the same territory (reference standard A) and fractional flow reserve < 0.80 and SPDs in the same territory (reference standard B).

RESULTS

Of the 99 arteries with no stenosis >50% and no SPDs, considered as normal, 19 (19%) had RSAs. Conversely, with stenosis >50% and SPDs, RSAs were considerably more frequent (17 of 24 [71%]). The sensitivity, specificity, and accuracy of RSA were 0.71, 0.81, and 0.79, respectively, against reference standard A and 0.83, 0.81, and 0.82 against reference standard B.

CONCLUSIONS

Fusion of CTCA and 3D echocardiography-derived resting myocardial strain provides combined displays, which may be useful in determination of the hemodynamic or functional impact of coronary abnormalities, without additional ionizing radiation or stress testing.

Update on Computed Tomography Myocardial Perfusion Imaging

PURPOSE OF REVIEW

Computed tomography (CT) coronary angiography is a well-validated non-invasive technique for accurate and expedient diagnosis of coronary artery disease (CAD). However, a limitation of coronary CT angiography (CCTA) is its limited capability to identify physiologically significant stenoses, which may eventuate the need for further functional testing. Stress CT myocardial perfusion imaging (CT-MPI) is an emerging technique that has the ability to identify flow-limiting stenoses.

RECENT FINDINGS

The combination of CCTA coronary and CT-MPI has transformed the modality from a tool to assess anatomy and morphology to a modality capable of simultaneous assessment of coronary stenoses and their physiologic significance. A growing number of studies have demonstrated the feasibility and diagnostic accuracy of CT-MPI in comparison to a number of reference standard modalities for CAD diagnosis, including single-photon emission CT, cardiovascular magnetic resonance imaging, and invasive coronary angiography with and without fractional flow-reserve testing.

SUMMARY

While there is still a need for consensus regarding acquisition techniques as well as analysis and interpretation of CT-MPI, with further validation, it is likely to become a powerful adjunctive tool to CCTA in the management of patients with suspected coronary disease.

Three-dimensional quantification of myocardial perfusion during regadenoson stress computed tomography

BACKGROUND

There is no accepted methodology for CT-based vasodilator stress myocardial perfusion imaging and analysis. We developed a technique for quantitative 3D analysis of CT images, which provides several indices of myocardial perfusion. We sought to determine the ability of these indices during vasodilator stress to identify segments supplied by coronary arteries with obstructive disease and to test the accuracy of the detection of perfusion abnormalities against SPECT.

METHODS

We studied 93 patients referred for CT coronary angiography (CTCA) who underwent regadenoson stress. 3D analysis of stress CT images yielded segmental perfusion indices: mean X-ray attenuation, severity of defect and relative defect volume. Each index was averaged for myocardial segments, grouped by severity of stenosis: 0%, <50%, 50-70%, and >70%. Objective detection of perfusion abnormalities was optimized in 47 patients and then independently tested in the remaining 46 patients.

RESULTS

CTCA depicted normal coronary arteries or non-obstructive disease in 62 patients and stenosis of >50% in 31. With increasing stenosis, segmental attenuation showed a 7% decrease, defect severity increased 11%, but relative defect volume was 7-fold higher in segments with obstructive disease (p<0.001). In the test group, detection of perfusion abnormalities associated with stenosis >50% showed sensitivity 0.78, specificity 0.54, accuracy 0.59. When compared to SPECT in a subset of 21 patients (14 with abnormal SPECT), stress CT perfusion analysis showed sensitivity 0.79, specificity 0.71, accuracy 0.76.

CONCLUSIONS

3D analysis of vasodilator stress CT images provides quantitative indices of myocardial perfusion, of which relative defect volume was most robust in identifying segments supplied by arteries with obstructive disease. This study may have implications on how CT stress perfusion imaging is performed and analyzed.

Myocardial perfusion analysis in cardiac computed tomography angiographic images at rest

Cardiac computed tomography angiography (CTA) is a non-invasive method for anatomic evaluation of coronary artery stenoses. However, CTA is prone to artifacts that reduce the diagnostic accuracy to identify stenoses. Further, CTA does not allow for determination of the physiologic significance of the visualized stenoses. In this paper, we propose a new system to determine the physiologic manifestation of coronary stenoses by assessment of myocardial perfusion from typically acquired CTA images at rest. As a first step, we develop an automated segmentation method to delineate the left ventricle. Both endocardium and epicardium are compactly modeled with subdivision surfaces and coupled by explicit thickness representation. After initialization with five anatomical landmarks, the model is adapted to a target image by deformation increments including control vertex displacements and thickness variations guided by trained AdaBoost classifiers, and regularized by a prior of deformation increments from principal component analysis (PCA). The evaluation using a 5-fold cross-validation demonstrates the overall segmentation error to be 1.00 ± 0.39 mm for endocardium and 1.06 ± 0.43 mm for epicardium, with a boundary contour alignment error of 2.79 ± 0.52. Based on our LV model, two types of myocardial perfusion analyzes have been performed. One is a perfusion network analysis, which explores the correlation (as network edges) pattern of perfusion between all pairs of myocardial segments (as network nodes) defined in AHA 17-segment model. We find perfusion network display different patterns in the normal and disease groups, as divided by whether significant coronary stenosis is present in quantitative coronary angiography (QCA). The other analysis is a clinical validation assessment of the ability of the developed algorithm to predict whether a patient has significant coronary stenosis when referenced to an invasive QCA ground truth standard. By training three machine learning techniques using three features of normalized perfusion intensity, transmural perfusion ratio, and myocardial wall thickness, we demonstrate AdaBoost to be slightly better than Naive Bayes and Random Forest by the area under receiver operating characteristics (ROC) curve. For the AdaBoost algorithm, an optimal cut-point reveals an accuracy of 0.70, with sensitivity and specificity of 0.79 and 0.64, respectively. Our study shows perfusion analysis from CTA images acquired at rest is useful for providing physiologic information in diagnosis of obstructive coronary artery stenoses.

Myocardial perfusion imaging with cardiac computed tomography: state of the art

Cardiac computed tomography (CCT) has become an important tool for the anatomic assessment of patients with suspected coronary disease. Its diagnostic accuracy for detecting the presence of underlying coronary artery disease and ability to risk stratify patients are well documented. However, the role of CCT for the physiologic assessment of myocardial perfusion during resting and stress conditions is only now emerging. With the addition of myocardial perfusion imaging to coronary imaging, CCT has the potential to assess both coronary anatomy and its functional significance with a single non-invasive test. In this review, we discuss the current state of CCT myocardial perfusion imaging for the detection of myocardial ischemia and myocardial infarction and examine its complementary role to CCT coronary imaging.

Time efficiency and diagnostic accuracy of new automated myocardial perfusion analysis software in 320-row CT cardiac imaging

Objective

We aimed to evaluate the time efficiency and diagnostic accuracy of automated myocardial computed tomography perfusion (CTP) image analysis software.

Materials and Methods

320-row CTP was performed in 30 patients, and analyses were conducted independently by three different blinded readers by the use of two recent software releases (version 4.6 and novel version 4.71GR001, Toshiba, Tokyo, Japan). Analysis times were compared, and automated epi- and endocardial contour detection was subjectively rated in five categories (excellent, good, fair, poor and very poor). As semi-quantitative perfusion parameters, myocardial attenuation and transmural perfusion ratio (TPR) were calculated for each myocardial segment and agreement was tested by using the intraclass correlation coefficient (ICC). Conventional coronary angiography served as reference standard.

Results

The analysis time was significantly reduced with the novel automated software version as compared with the former release (Reader 1: 43:08 ± 11:39 min vs. 09:47 ± 04:51 min, Reader 2: 42:07 ± 06:44 min vs. 09:42 ± 02:50 min and Reader 3: 21:38 ± 3:44 min vs. 07:34 ± 02:12 min; p < 0.001 for all). Epi- and endocardial contour detection for the novel software was rated to be significantly better (p < 0.001) than with the former software. ICCs demonstrated strong agreement (≥ 0.75) for myocardial attenuation in 93% and for TPR in 82%. Diagnostic accuracy for the two software versions was not significantly different (p = 0.169) as compared with conventional coronary angiography.

Conclusion

The novel automated CTP analysis software offers enhanced time efficiency with an improvement by a factor of about four, while maintaining diagnostic accuracy.

Quantitative three-dimensional evaluation of myocardial perfusion during regadenoson stress using multidetector computed tomography

OBJECTIVE

The ability of multidetector computed tomography (MDCT) to detect stress-induced myocardial perfusion abnormalities is of great clinical interest as a potential tool for the combined evaluation of coronary stenosis and its hemodynamic significance. We tested the hypothesis that quantitative 3-dimensional (3D) analysis of myocardial perfusion from MDCT images obtained during regadenoson stress would more accurately detect the presence of significant coronary artery disease (CAD) than identical analysis when performed on resting MDCT images.

METHODS

We prospectively studied 50 consecutive patients referred for CT coronary angiography (CTCA) who agreed to undergo additional imaging with regadenoson (0.4 mg; Astellas). Images were acquired using prospective gating (256-channel; Philips). Custom analysis software was used to define 3D myocardial segments, and calculate for each segment an index of severity and extent of perfusion abnormality, Qh, which was compared with perfusion defects predicted by the presence and severity of coronary stenosis on CTCA.

RESULTS

Three patients were excluded because of image artifacts. In the remaining 47 patients, CTCA depicted stenosis more than 50% in 23 patients in 37 of 141 coronary arteries. In segments supplied by the obstructed arteries, myocardial attenuation was slightly reduced compared with normally perfused segments at rest (mean [SD], 91 [21] vs 93 [26] Hounsfield units, not significant) and, to a larger extent, at peak stress (102 [21] vs 112 [20] Hounsfield units, P < 0.05). In contrast, index Qh was significantly increased at rest (0.40 [0.48] vs 0.26 [0.41], P < 0.05) and reached a nearly 3-fold difference at peak stress (0.66 [0.74] vs 0.28 [0.51], P < 0.05). The addition of regadenoson improved the diagnosis of CAD, as reflected by an increase in sensitivity (from 0.57 to 0.91) and improvement in accuracy (from 0.65 to 0.77).

CONCLUSIONS

Quantitative 3D analysis of MDCT images allows objective detection of CAD, the accuracy of which is improved by regadenoson stress.

A stepwise approach to the visual interpretation of CT-based myocardial perfusion

Cardiovascular anatomic and functional testing have been longstanding and key components of cardiac risk assessment. As part of that strategy, CT-based imaging has made steady progress, with coronary computed tomography angiography (CTA) now established as the most sensitive noninvasive strategy for assessment of significant coronary artery disease. Myocardial CT perfusion imaging (CTP), as the functional equivalent of coronary CTA, is being tested in currently ongoing multicenter trials and is proposed to enhance the accuracy of coronary CTA alone. However, unlike coronary CTA that has published guidelines for interpretation and is rapidly gaining applicability in the noninvasive risk assessment paradigms, myocardial CTP is rapidly evolving, and guidance on a standard approach to its interpretation is lacking. In this article we describe a practical stepwise approach for interpretation of myocardial CTP that should add to the clinical applicability of this modality. These steps include (1) coronary CTA interpretation for potentially obstructive atherosclerosis, (2) reconstruction and preprocessing of myocardial CTP images, (3) image quality assessment and the identification of potentially confounding artifacts, (4) rest and stress image interpretation for enhancement patterns and areas of hypoattenuation, and (5) correlation of coronary anatomy and myocardial perfusion deficits. This systematic review uses already published methods from multiple clinical studies and is intended for general usage, independent of the platform used for image acquisition.

Detection of myocardial perfusion abnormalities using ultra-low radiation dose regadenoson stress multidetector computed tomography

BACKGROUND

The ability of multidetector computed tomography (MDCT) to detect stress-induced myocardial perfusion abnormalities is of great clinical interest as a potential tool for the combined evaluation of coronary stenosis and its significance. However, stress testing requires repeated scanning that is associated with additional radiation exposure and iodine contrast.

OBJECTIVE

Our goal was to determine the effects of reduced tube voltage and contrast dose on the ability to detect perfusion abnormalities.

METHODS

We studied 40 patients referred for coronary CT angiography (CTA) who agreed to undergo additional imaging after administration of an A(2A)-agonist (regadenoson 0.4 mg). Images were acquired at rest and during hyperemia with prospective gating with 120 kV tube voltage with 80-90 mL of contrast in 20 patients (group 1) and 100 kV with 55-70 mL of contrast in the remaining 20 patients (group 2). Custom 3D analysis software was used to define 3D myocardial segments and measure x-ray attenuation in each segment. In each group of patients, myocardial attenuation was averaged for segments supplied by coronary arteries with stenosis causing >50% luminal narrowing on coronary CTA and separately for segments supplied by arteries without significant stenosis.

RESULTS

Coronary CTA detected stenosis >50% in 23 of 120 coronary arteries in 16 of 40 patients. In all patients combined, myocardial attenuation increased from 86 ± 9 at rest to 110 ± 17 HU with stress, reflecting an increase in tissue blood flow, despite the decrease in left ventricular cavity attenuation (347 ± 72 to 281 ± 55 HU), reflecting an increase in cardiac output. Importantly, in both groups, myocardial attenuation was equally reduced in segments supplied by diseased arteries (group 1: 119 ± 19 vs 103 ± 14 HU, P < 0.05; group 2: 108 ± 20 vs 97 ± 16 HU, P < 0.05), despite the 74% reduction in radiation (from 7.4 ± 2.8 to 1.9 ± 0.45 mSv) and the 28% reduction in contrast dose (from 84 ± 7 to 60 ±7 mL) (both P < 0.05).

CONCLUSIONS

Regadenoson stress MDCT imaging can detect hypoperfused myocardium even when imaging settings are optimized to provide a significant reduction in radiation and contrast doses.