Comparison of blood flow models and acquisitions for quantitative myocardial perfusion estimation from dynamic CT

Low-dose quantitative CT myocardial flow measurement using a single volume scan: phantom and animal validation

Purpose

To validate a low-dose, single-volume quantitative CT myocardial flow technique in a cardiovascular flow phantom and a swine animal model of coronary artery disease.

Approach

A cardiovascular flow phantom was imaged dynamically over different flow rates (0.97 to 2.45    mL / min / g ) using 15 mL of contrast per injection. Six swine (37 ± 8    kg ) were also imaged dynamically, with different left anterior descending coronary artery balloon stenoses assessed under intracoronary adenosine stress, using 1    mL / kg of contrast per injection. The resulting images were used to simulate dynamic bolus tracking and peak volume scan acquisition. After which, first-pass single-compartment modeling was performed to derive quantitative flow, where the pre-contrast myocardial attenuation was assumed to be spatially uniform. The accuracy of CT flow was then assessed versus ultrasound and microsphere flow in the phantom and animal models, respectively, using regression analysis.

Results

Single-volume quantitative CT flow measurements in the phantom (Q CT _ PHANTOM ) were related to reference ultrasound flow measurements (Q US ) by Q CT _ PHANTOM = 1.04 Q US - 0.1 (Pearson's r = 0.98 ; RMSE = 0.09    mL / min / g ). In the animal model (Q CT _ ANIMAL ), they were related to reference microsphere flow measurements (Q MICRO ) by Q CT _ ANIMAL = 1.00 Q MICRO - 0.05 (Pearson's r = 0.96 ; RMSE = 0.48    mL / min / g ). The effective dose per CT measurement was 1.21 mSv.

Conclusions

The single-volume quantitative CT flow technique only requires bolus tracking data, spatially uniform pre-contrast myocardial attenuation, and a single volume scan acquired near the peak aortic enhancement for accurate, low-dose, myocardial flow measurement (in mL/min/g) under rest and adenosine stress conditions.

Technical Considerations for Dynamic Myocardial Computed Tomography Perfusion as Part of a Comprehensive Evaluation of Coronary Artery Disease Using Computed Tomography

Dynamic myocardial computed tomography perfusion (DM-CTP) has good diagnostic accuracy for identifying myocardial ischemia as compared with both invasive and noninvasive reference standards. However, DM-CTP has not yet been implemented in the routine clinical examination of patients with suspected or known coronary artery disease. An important hurdle in the clinical dissemination of the method is the development of the DM-CTP acquisition protocol and image analysis. Therefore, the aim of this article is to provide a review of critical parameters in the design and execution of DM-CTP to optimize each step of the examination and avoid common mistakes. We aim to support potential users in the successful implementation and performance of DM-CTP in daily practice. When performed appropriately, DM-CTP may support clinical decision making. In addition, when combined with coronary computed tomography angiography, it has the potential to shorten the time to diagnosis by providing immediate visualization of both coronary atherosclerosis and its functional relevance using one single modality.

Basis and current state of computed tomography perfusion imaging: a review

Computed tomography perfusion (CTP) is a functional imaging that allows for providing capillary-level hemodynamics information of the desired tissue in clinics. In this paper, we aim to offer insight into CTP imaging which covers the basics and current state of CTP imaging, then summarize the technical applications in the CTP imaging as well as the future technological potential. At first, we focus on the fundamentals of CTP imaging including systematically summarized CTP image acquisition and hemodynamic parameter map estimation techniques. A short assessment is presented to outline the clinical applications with CTP imaging, and then a review of radiation dose effect of the CTP imaging on the different applications is presented. We present a categorized methodology review on known and potential solvable challenges of radiation dose reduction in CTP imaging. To evaluate the quality of CTP images, we list various standardized performance metrics. Moreover, we present a review on the determination of infarct and penumbra. Finally, we reveal the popularity and future trend of CTP imaging.

A Multimodality Myocardial Perfusion Phantom: Initial Quantitative Imaging Results

This proof-of-concept study explores the multimodal application of a dedicated cardiac flow phantom for ground truth contrast measurements in dynamic myocardial perfusion imaging with CT, PET/CT, and MRI. A 3D-printed cardiac flow phantom and flow circuit mimics the shape of the left ventricular cavity (LVC) and three myocardial regions. The regions are filled with tissue-mimicking materials and the flow circuit regulates and measures contrast flow through LVC and myocardial regions. Normal tissue perfusion and perfusion deficits were simulated. Phantom measurements in PET/CT, CT, and MRI were evaluated with clinically used hardware and software. The reference arterial input flow was 4.0 L/min and myocardial flow 80 mL/min, corresponding to myocardial blood flow (MBF) of 1.6 mL/g/min. The phantom demonstrated successful completion of all processes involved in quantitative, multimodal myocardial perfusion imaging (MPI) applications. Contrast kinetics in time intensity curves were in line with expectations for a mimicked perfusion deficit (38 s vs. 32 s in normal tissue). Derived MBF in PET/CT and CT led to under- and overestimation of reference flow of 0.9 mL/g/min and 4.5 mL/g/min, respectively. Simulated perfusion deficit (0.8 mL/g/min) in CT resulted in MBF of 2.8 mL/g/min. We successfully performed initial, quantitative perfusion measurements with a dedicated phantom setup utilizing clinical hardware and software. These results showcase the multimodal phantom’s potential.

Knowledge of Hyperemic Myocardial Blood Flow in Healthy Subjects Helps Identify Myocardial Ischemia in Patients With Coronary Artery Disease

Backgrounds

Dynamic CT myocardial perfusion imaging (CT-MPI) allows absolute quantification of myocardial blood flow (MBF). Although appealing, CT-MPI has not yet been widely applied in clinical practice, partly due to our relatively limited knowledge of CT-MPI. Knowledge of distribution and variability of MBF in healthy subjects helps in recognition of physiological and pathological states of coronary artery disease (CAD).

Objectives

To describe the distribution and normal range of hyperemic MBF in healthy subjects obtained by dynamic CT-MPI and validate whether it can accurately identify functional myocardial ischemia when the cut-off value of hyperemia MBF is set to the lower limit of the normal range.

Materials and Methods

Fifty-one healthy volunteers (age, 38 ± 12 years; 15 men) were prospectively recruited. Eighty patients (age, 58 ± 10 years; 55 men) with suspected or known CAD who underwent interventional coronary angiography (ICA) examinations were retrospectively recruited. Comprehensive CCTA + dynamic CT-MPI protocol was performed by the third – generation dual-source CT scanner. Invasive fractional flow reserve (FFR) measurements were performed in vessels with 30–90% diameter reduction. ICA/FFR was used as the reference standard for diagnosing functional ischemia. The normal range for the hyperemic MBF were defined as the mean ± 1.96 SD. The cut-off value of hyperemic MBF was set to the lower limit of the normal range.

Results

The global hyperemic MBF were 164 ± 24 ml/100 ml/min and 123 ± 26 ml/100 ml/min for healthy participants and patients. The normal range of the hyperemic MBF was 116–211 ml/100 ml/min. Of vessels with an ICA/FFR result (n = 198), 67 (34%) were functionally significant. In the per-vessel analysis, an MBF cutoff value of <116 ml/100 ml/min can identify myocardial ischemia with a diagnostic accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of 85.9% (170/198), 91.0% (61/67), 83.2 % (109/131), 73.5% (61/83), and 94.8% (109/115). CT-MPI showed good consistency with ICA/FFR in diagnosing functional ischemia, with a Cohen's kappa statistic of 0.7016 (95%CI, 0.6009 – 0.8023).

Conclusion

Recognizing hyperemic MBF in healthy subjects helps better understand myocardial ischemia in CAD patients.

Temporal feature prior-aided separated reconstruction method for low-dose dynamic myocardial perfusion computed tomography

Dynamic myocardial perfusion computed tomography (DMP-CT) is an effective medical imaging technique for coronary artery disease diagnosis and therapy guidance. However, the radiation dose received by the patient during repeated CT scans is a widespread concern of radiologists because of the increased risk of cancer. The sparse few-view CT scanning protocol can be a feasible approach to reduce the radiation dose of DMP-CT imaging; however, an advanced reconstruction algorithm is needed. In this paper, a temporal feature prior-aided separated reconstruction method (TFP-SR) for low-dose DMP-CT images reconstruction from sparse few-view sinograms is proposed. To implement the proposed method, the objective perfusion image is divided into the baseline fraction and the enhancement fraction introduced by the arrival of the contrast agent. The core of the proposed TFP-SR method is the utilization of the temporal evolution information that naturally exists in the DMP-CT image sequence to aid the enhancement image reconstruction from limited data. The temporal feature vector of an image pixel is defined by the intensities of this pixel in the pre-reconstructed enhancement sequence, and the connection between two related features is calculated via a zero-mean Gaussian function. A prior matrix is constructed based on the connections between the extracted temporal features and used in the iterative reconstruction of the enhancement images. To evaluate the proposed method, the conventional filtered back-projection algorithm, the total variation regularized PWLS (PWLS-TV) and the prior image constrained compressed sensing are compared in this paper based on studies on a digital extended cardiac-torso (XCAT) thoracic phantom and a preclinical porcine DMP-CT data set that take image misregistration into account. The experimental results demonstrate that the proposed TFP-SR method has superior performance in sparse DMP-CT images reconstruction in terms of image quality and the analyses of the time attenuation curve and hemodynamic parameters.

Combining perfusion and angiography with a low-dose cardiac CT technique: a preliminary investigation in a swine model

Morphological and physiological assessment of coronary artery disease (CAD) is necessary for proper stratification of CAD risk. The objective was to evaluate a low-dose cardiac CT technique that combines morphological and physiological assessment of CAD. The low-dose technique was evaluated in twelve swine, where three of the twelve had coronary balloon stenosis. The technique consisted of rest perfusion measurement combined with angiography followed by stress perfusion measurement, where the ratio of stress to rest was used to derive coronary flow reserve (CFR). The technique only required two volume scans for perfusion measurement in mL/min/g; hence, four volume scans were acquired in total; two for rest with angiography and two for stress. All rest, stress, and CFR measurements were compared to a previously validated reference technique that employed 20 consecutive volume scans for rest perfusion measurement combined with angiography, and stress perfusion measurement, respectively. The 32 cm diameter volumetric CT dose index (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text{CTDI}}_{\text{vol}}^{32}$$\end{document}CTDIvol32) and size-specific dose estimate (SSDE) of the low-dose technique were also recorded. All low-dose perfusion measurements (P_LOW) in mL/min/g were related to reference perfusion measurements (P_REF) through regression by P_LOW = 1.04 P_REF − 0.08 (r = 0.94, RMSE = 0.32 mL/min/g). The \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text{CTDI}}_{\text{vol}}^{32}$$\end{document}CTDIvol32 and SSDE of the low-dose cardiac CT technique were 8.05 mGy and 12.80 mGy respectively, corresponding to an estimated effective dose and size-specific effective dose of 1.8 and 2.87 mSv, respectively. Combined morphological and physiological assessment of coronary artery disease is feasible using a low-dose cardiac CT technique.

Quantitative analysis of dynamic computed tomography angiography for the detection of endoleaks after abdominal aorta aneurysm endovascular repair: A feasibility study

Objectives

To assess the feasibility of quantitative analysis of dynamic computed tomography angiography (dCTA) for the detection of endoleaks in patients who underwent endovascular repair of abdominal aortic aneurysms (EVAR).

Material and methods

Twenty patients scheduled for contrast-enhanced CT angiography (CTA) of the abdominal aorta post-EVAR were prospectively enrolled. All patients received a standard triphasic CTA protocol, followed by an additional dCTA. The dCTA acquisition enabled reconstruction of color-coded maps depicting blood perfusion and a dCTA dataset of the aneurysm sac. Observers assessed the dCTA and dynamic CT perfusion (dCTP) images for the detection of endoleaks, establishing diagnostic confidence based on a modified 5-point Likert scale. An index was calculated for the ratio between the endoleak and aneurysm sac using blood flow for dCTP and Hounsfield units (HU) for dCTA. The Wilcoxon test compared the endoleak index and the diagnostic confidence of the observers.

Results

In total, 19 patients (18 males, median age 74 years [70.5–75.7]) were included for analysis. Nine endoleaks were detected in 7 patients using triphasic CTA as the reference standard. There was complete agreement for endoleak detection between the two techniques on a per-patient basis. Both dCTA and dCTP identified an additional endoleak in one patient. The diagnostic confidence using dCTP for detection of endoleaks was not significantly superior to dCTA (5.0 [5–5] vs. 4.5 [4–5], respectively; p = 0.11); however, dCTP demonstrated superior diagnostic confidence for endoleak exclusion compared to dCTA (1.0 [1–1] vs 1.5 [1.5–1.5], respectively; p <0.01). Moreover, the dCTP endoleak index was significantly higher than the dCTA index (18.5 [10.8–20.5] vs. 3.5 [5–2.7], respectively; p = 0.02).

Conclusions

Quantitative analysis of dCTP imaging can aid in the detection of endoleaks and demonstrates a higher endoleak detection rate than triphasic CTA, as well as a strong correlation with visual assessment of dCTA images.

Comparison of automated beam hardening correction (ABHC) algorithms for myocardial perfusion imaging using computed tomography

PURPOSE

Myocardial perfusion imaging using computed tomography (MPI-CT) and coronary CT angiography (CTA) have the potential to make CT an ideal noninvasive imaging gatekeeper exam for invasive coronary angiography. However, beam hardening can prevent accurate blood flow estimation in dynamic MPI-CT and can create artifacts that resemble flow deficits in single-shot MPI-CT. In this work, we compare four automatic beam hardening correction algorithms (ABHCs) applied to CT images, for their ability to produce accurate single images of contrast and accurate MPI flow maps using images from conventional CT systems, without energy sensitivity.

METHODS

Previously, we reported a method, herein called ABHC-1, where we iteratively optimized a cost function sensitive to beam hardening artifacts in MPI-CT images and used a low order polynomial correction on projections of segmentation-processed CT images. Here, we report results from two new algorithms with higher order polynomial corrections, ABHC-2 and ABHC-3 (with three and seven free parameters, respectively), having potentially better correction but likely reduced estimability. Additionally, we compared results to an algorithm reported by others in the literature (ABHC-NH). Comparisons were made on a digital static phantom with simulated water, bone, and iodine regions; on a digital dynamic anthropomorphic phantom, with simulated blood flow; and on preclinical porcine experiments. We obtained CT images on a prototype spectral detector CT (Philips Healthcare) scanner that provided both conventional and virtual keV images, allowing us to quantitatively compare corrected CT images to virtual keV images. To test these methods' parameter optimization sensitivity to noise, we evaluated results on images obtained using different mAs.

RESULTS

In images of the static phantom, ABHC-2 reduced beam hardening artifacts better than our previous ABHC-1 algorithm, giving artifacts smaller than 1.8 HU, even in the presence of high noise which should affect parameter optimization. Taken together, the quality of static phantom results ordered ABHC-2> ABHC-3> ABHC-1>> ABHC-NH. In an anthropomorphic MPI-CT simulator with homogeneous myocardial blood flow of 100 ml⋅min-1 ⋅100 g-1 , blood flow estimation results were 122 ± 24 (FBP), 135 ± 24 (ABHC-NH), 104 ± 14 (ABHC-1), 100 ± 12 (ABHC-2), and 108 ± 18 (ABHC-3) ml⋅min-1 ⋅100 g-1 , showing ABHC-2 as a clear winner. Visual and quantitative evaluations showed much improved homogeneity of myocardial flow with ABHC-2, nearly eliminating substantial artifacts in uncorrected flow maps which could be misconstrued as flow deficits. ABHC-2 performed universally better than ABHC-1, ABHC-3, and ABHC-NH in simulations with different acquisitions (varying noise and kVp values). In the presence of a simulated flow deficit, all ABHC methods retained the flow deficit, and ABHC-2 gave the most accurate flow ratio and homogeneity. ABHC-3 corrected phantom flow values were slightly better than ABHC-2, in noiseless images, suggesting that reduced quality in noisy images was due to reduced estimability. In an experiment with a pig expected to have uniform flow, ABHC-2 applied to conventional images improved flow maps to compare favorably to those from 70keV images.

CONCLUSION

The automated algorithm can be used with different parametric BH correction models. ABHC-2 improved MPI-CT blood flow estimation as compared to other approaches and was robust to noisy images. In simulation and preclinical experiments, ABHC-2 gave results approaching gold standard 70 keV measurements.

Quantitative low-dose rest and stress CT myocardial perfusion imaging with a whole-heart coverage scanner improves functional assessment of coronary artery disease

Objective

We evaluated the diagnostic accuracy of myocardial blood flow (MBF) and perfusion reserve (MPR) measured from low-dose dynamic contrast-enhanced (DCE) imaging with a whole-heart coverage CT scanner for detecting functionally significant coronary artery disease (CAD).

Methods

Twenty one patients with suspected or known CAD had rest and dipyridamole stress MBF measurements with CT and SPECT myocardial perfusion imaging (MPI), and lumen narrowing assessment with coronary angiography (catheter and/or CT based) within 6 weeks. SPECT MBF measurements and coronary angiography were used together as reference to determine the functional significance of coronary artery stenosis. In each CT MPI study, DCE images of the whole heart were acquired with breath-hold using a low-dose acquisition protocol to generate MBF maps. Binomial logistic regression analysis was used to determine the diagnostic accuracy of CT-measured MBF and MPR (ratio of stress to rest MBF) for assessing functionally significant coronary stenosis.

Results

Mean stress MBF and MPR in ischemic segments were lower than those in non-ischemic segments (1.37 ± 0.34 vs. 2.14 ± 0.64 ml/min/g; 1.56 ± 0.41 vs. 2.53 ± 0.70; p < 0.05 for all). The receiver operating characteristic curve analysis revealed that MPR (AUC 0.916, 95%CI: 0.885–0.947) had a superior power than stress MBF (AUC 0.869, 95%CI: 0.830–0.909) for differentiating non-ischemic and ischemic myocardial segments (p = 0.045). On a per-vessel and per-segment analysis, concomitant use of MPR and stress MBF thresholds further improved the diagnostic accuracy compared to MPR or stress MBF alone for detecting obstructive coronary lesions (per-vessel: 93.4% vs. 83.6% and 88.5%, respectively; per-segment: 90.0% vs. 83.7% and 83.1%, respectively). The estimated effective dose of a rest and stress CT MPI study was 3.04 and 3.19 mSv respectively.

Conclusion

Quantitative rest and stress myocardial perfusion measurement with a large-coverage CT scanner improves the diagnostic accuracy for detecting functionally significant coronary stenosis.

Dynamic Quantitative Iodine Myocardial Perfusion Imaging with Dual-Layer CT using a Porcine Model

Ischemic heart disease is the globally leading cause of death. When using coronary CT angiography, the functional hemodynamics within the myocardium remain uncertain. In this study myocardial CT perfusion imaging using iodine contrast agent demonstrated to strongly improve the assessment of myocardial disorders. However, a retrieval of such dynamics using Hounsfield units from conventional CT poses concerns with respect to beam-hardening effects and low contrast-to-noise ratio (CNR). Dual-energy CT offers novel approaches to overcome aforementioned limitations. Quantitative peak enhancement, perfusion, time to peak and iodine volume measurements inside the myocardium were determined resulting in 0.92 mg/ml, 0.085 mg/ml/s 17.12 s and 29.89 mg/ml*s, respectively. We report on the first extensive quantitative and iodine-based analysis of myocardial dynamics in a healthy porcine model using a dual-layer spectral CT. We further elucidate on the potential of reducing the radiation dose from 135 to 18 mGy and the contrast agent volume from 60 to 30 mL by presenting a two-shot acquisition approach and measuring iodine concentrations in the myocardium in-vivo down to 1 mg/ml, respectively. We believe that dynamic quantitative iodine perfusion imaging may be a highly sensitive tool for the precise functional assessment and monitoring of early myocardial ischemia.

Low-Radiation-Dose Stress Myocardial Perfusion Measurement Using First-Pass Analysis Dynamic Computed Tomography: A Preliminary Investigation in a Swine Model

OBJECTIVES

The aim of this study was to assess the feasibility of a prospective first-pass analysis (FPA) dynamic computed tomography (CT) perfusion technique for accurate low-radiation-dose global stress perfusion measurement.

MATERIALS AND METHODS

The prospective FPA technique was evaluated in 10 swine (42 ± 12 kg) by direct comparison to a previously validated retrospective FPA technique. Of the 10 swine, 3 had intermediate stenoses with fractional flow reserve severities of 0.70 to 0.90. In each swine, contrast and saline were injected peripherally followed by dynamic volume scanning with a 320-slice CT scanner. Specifically, for the reference standard retrospective FPA technique, volume scans were acquired continuously at 100 kVp and 200 mA over 15 to 20 seconds, followed by systematic selection of only 2 volume scans for global perfusion measurement. For the prospective FPA technique, only 2 volume scans were acquired at 100 kVp and 50 mA for global perfusion measurement. All prospective global stress perfusion measurements were then compared with the corresponding reference standard retrospective global stress perfusion measurements through regression analysis. The CTDIvol and size-specific dose estimate of the prospective FPA technique were also determined.

RESULTS

All prospective global stress perfusion measurements (PPRO) at 50 mA were in good agreement with the reference standard retrospective global stress perfusion measurements (PREF) at 200 mA (PPRO = 1.07 PREF -0.09, r = 0.94; root-mean-square error = 0.30 mL/min per gram). The CTDIvol and size-specific dose estimate of the prospective FPA technique were 2.3 and 3.7 mGy, respectively.

CONCLUSIONS

Accurate low-radiation-dose global stress perfusion measurement is feasible using a prospective FPA dynamic CT perfusion technique.

SLICR super-voxel algorithm for fast, robust quantification of myocardial blood flow by dynamic computed tomography myocardial perfusion imaging

We created and evaluated a processing method for dynamic computed tomography myocardial perfusion imaging (CT-MPI) of myocardial blood flow (MBF), which combines a modified simple linear iterative clustering algorithm (SLIC) with robust perfusion quantification, hence the name SLICR. SLICR adaptively segments the myocardium into nonuniform super-voxels with similar perfusion time attenuation curves (TACs). Within each super-voxel, an α-trimmed-median TAC was computed to robustly represent the super-voxel and a robust physiological model (RPM) was implemented to semi-analytically estimate MBF. SLICR processing was compared with another voxel-wise MBF preprocessing approach, which included a spatiotemporal bilateral filter (STBF) for noise reduction prior to perfusion quantification. Image data from a digital CT-MPI phantom and a porcine ischemia model were evaluated. SLICR was ∼ 50 -fold faster than voxel-wise RPM and other model-based methods while retaining sufficient resolution to show clinically relevant features, such as a transmural perfusion gradient. SLICR showed markedly improved accuracy and precision, as compared with other methods. At a simulated MBF of 100 mL/min-100 g and a tube current-time product of 100 mAs (50% of nominal), the MBF estimates were 101 ± 12 , 94 ± 56 , and 54 ± 24    mL / min - 100    g for SLICR, the voxel-wise Johnson-Wilson model, and a singular value decomposition-model independent method with STBF, respectively. SLICR estimated MBF precisely and accurately ( 103 ± 23    mL / min - 100    g ) at 25% nominal dose, while other methods resulted in larger errors. With the porcine model, the SLICR results were consistent with the induced ischemia. SLICR simultaneously accelerated and improved the quality of quantitative perfusion processing without compromising clinically relevant distributions of perfusion characteristics.

Accuracy of Myocardial Blood Flow Estimation From Dynamic Contrast-Enhanced Cardiac CT Compared With PET

Background The accuracy of absolute myocardial blood flow (MBF) from dynamic contrast-enhanced cardiac computed tomography acquisitions has not been fully characterized. We evaluate computed tomography (CT) compared with rubidium-82 positron emission tomography (PET) MBF estimates in a high-risk population. Methods In a prospective trial, patients receiving clinically indicated rubidium-82 PET exams were recruited to receive a dynamic contrast-enhanced cardiac computed tomography exam. The CT protocol included a rest and stress dynamic portion each acquiring 12 to 18 cardiac-gated frames. The global MBF was estimated from the PET and CT exam. Results Thirty-four patients referred for cardiac rest-stress PET were recruited. Of the 68 dynamic contrast-enhanced cardiac computed tomography scans, 5 were excluded because of injection errors or mismatched hemodynamics. The CT-derived global MBF was highly correlated with the PET MBF (r=0.92; P<0.001) with a mean difference of 0.7±26.4%. The CT MBF estimates were within 20% of PET estimates ( P<0.02) with a mean of (1) MBF for resting flow of PET versus CT of 0.9±0.3 versus 1.0±0.2 mL/min per gram and (2) MBF for stress flow of 2.1±0.7 versus 2.0±0.8 mL/min per gram. Myocardial flow reserve was -14±28% underestimated with CT (PET versus CT myocardial flow reserve, 2.5±0.6 versus 2.2±0.6). The proposed rest+stress+computed tomography angiography protocol had a dose length product of 598±76 mGy×cm resulting in an approximate effective dose of 8.4±1.1 mSv. Conclusions In a high-risk clinical population, a clinically practical dynamic contrast-enhanced cardiac computed tomography provided unbiased MBF estimates within 20% of rubidium-82 PET. Although unbiased, the CT estimates contain substantial variance with an standard error of the estimate of 0.44 mL/min per gram. Myocardial flow reserve estimation was not as accurate as individual MBF estimates.

Timing optimization of low-dose first-pass analysis dynamic CT myocardial perfusion measurement: validation in a swine model

Background

Myocardial perfusion measurement with a low-dose first-pass analysis (FPA) dynamic computed tomography (CT) perfusion technique depends upon acquisition of two whole-heart volume scans at the base and peak of the aortic enhancement. Hence, the objective of this study was to validate an optimal timing protocol for volume scan acquisition at the base and peak of the aortic enhancement.

Methods

Contrast-enhanced CT of 28 Yorkshire swine (weight, 55 ± 24 kg, mean ± standard deviation) was performed under rest and stress conditions over 20–30 s to capture the aortic enhancement curves. From these curves, an optimal timing protocol was simulated, where one volume scan was acquired at the base of the aortic enhancement while a second volume scan was acquired at the peak of the aortic enhancement. Low-dose FPA perfusion measurements (P_FPA) were then derived and quantitatively compared to the previously validated retrospective FPA perfusion measurements as a reference standard (P_REF). The 32-cm diameter volume CT dose index, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ {\mathrm{CTDI}}_{\mathrm{vol}}^{32} $$\end{document}CTDIvol32 and size-specific dose estimate (SSDE) of the low-dose FPA perfusion protocol were also determined.

Results

P_FPA were related to the reference standard by P_FPA = 0.95 · P_REF + 0.07 (r = 0.94, root-mean-square error = 0.27 mL/min/g, root-mean-square deviation = 0.04 mL/min/g). The \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ {\mathrm{CTDI}}_{\mathrm{vol}}^{32} $$\end{document}CTDIvol32 and SSDE of the low-dose FPA perfusion protocol were 9.2 mGy and 14.6 mGy, respectively.

Conclusions

An optimal timing protocol for volume scan acquisition at the base and peak of the aortic enhancement was retrospectively validated and has the potential to be used to implement an accurate, low-dose, FPA perfusion technique.

Calibration-free beam hardening correction for myocardial perfusion imaging using CT

PURPOSE

Computed tomography myocardial perfusion imaging (CT-MPI) and coronary CTA have the potential to make CT an ideal noninvasive imaging gatekeeper exam for invasive coronary angiography. However, beam hardening (BH) artifacts prevent accurate blood flow calculation in CT-MPI. BH correction methods require either energy-sensitive CT, not widely available, or typically, a calibration-based method in conventional CT. We propose a calibration-free, automatic BH correction (ABHC) method suitable for CT-MPI and evaluate its ability to reduce BH artifacts in single "static-perfusion" images and to create accurate myocardial blood flow (MBF) in dynamic CT-MPI.

METHODS

In the algorithm, we used input CT DICOM images and iteratively optimized parameters in a polynomial BH correction until a BH-sensitive cost function was minimized on output images. An input image was segmented into a soft tissue image and a highly attenuating material (HAM) image containing bones and regions of high iodine concentrations, using mean HU and temporal enhancement properties. We forward projected HAM, corrected projection values according to a polynomial correction, and reconstructed a correction image to obtain the current iteration's BH corrected image. The cost function was sensitive to BH streak artifacts and cupping. We evaluated the algorithm on simulated CT and physical phantom images, and on preclinical porcine with optional coronary obstruction and clinical CT-MPI data. Assessments included measures of BH artifact in single images as well as MBF estimates. We obtained CT images on a prototype spectral detector CT (SDCT, Philips Healthcare) scanner that provided both conventional and virtual keV images, allowing us to quantitatively compare corrected CT images to virtual keV images. To stress test the method, we evaluated results on images from a different scanner (iCT, Philips Healthcare) and different kVp values.

RESULTS

In a CT-simulated digital phantom consisting of water with iodine cylinder insets, BH streak artifacts between simulated iodine inserts were reduced from 13 ± 2 to 0 ± 1 HU. In a similar physical phantom having higher iodine concentrations, BH streak artifacts were reduced from 48 ± 6 to 1 ± 5 HU and cupping was reduced by 86%, from 248 to 23 HU. In preclinical CT-MPI images without coronary obstruction, BH artifact was reduced from 24 ± 6 HU to less than 5 ± 4 HU at peak enhancement. Standard deviation across different regions of interest (ROI) along the myocardium was reduced from 13.26 to 6.86 HU for ABHC, comparing favorably to measurements in the corresponding virtual keV image. Corrections greatly reduced variations in preclinical MBF maps as obtained in normal animals without obstruction (FFR = 1). Coefficients of variations were 22% (conventional CT), 9% (ABHC), and 5% (virtual keV). Moreover, variations in flow tended to be localized after ABHC, giving result which would not be confused with a flow deficit in a coronary vessel territory.

CONCLUSION

The automated algorithm can be used to reduce BH artifact in conventional CT and improve CT-MPI accuracy particularly by removing regions of reduced estimated flow which might be misinterpreted as flow deficits.

Low CT temporal sampling rates result in a substantial underestimation of myocardial blood flow measurements

The purpose of this study was to evaluate the effect of temporal sampling rate in dynamic CT myocardial perfusion imaging (CTMPI) on myocardial blood flow (MBF). Dynamic perfusion CT underestimates myocardial blood flow compared to PET and SPECT values. For accurate quantitative analysis of myocardial perfusion with dynamic perfusion CT a stable calibrated HU measurement of MBF is essential. Three porcine hearts were perfused using an ex-vivo Langendorff model. Hemodynamic parameters were monitored. Dynamic CTMPI was performed using third generation dual source CT at 70 kVp and 230-350 mAs/rot in electrocardiography(ECG)-triggered shuttle-mode (sampling rate, 1 acquisition every 2-3 s; z-range, 10.2 cm), ECG-triggered non-shuttle mode (fixed table position) with stationary tube rotation (1 acquisition every 0.5-1 s, 5.8 cm), and non-ECG-triggered continuous mode (1 acquisition every 0.06 s, 5.8 cm). Stenosis was created in the circumflex artery, inducing different fractional flow reserve values. Volume perfusion CT Myocardium software was used to analyze ECG-triggered scans. For the non-ECG triggered scans MASS research version was used combined with an in-house Matlab script. MBF (mL/g/min) was calculated for non-ischemic segments. True MBF was calculated using input flow and heart weight. Significant differences in MBF between shuttle, non-shuttle and continuous mode were found, with median MBF of 0.87 [interquartile range 0.72-1.00], 1.20 (1.07-1.30) and 1.65 (1.40-1.88), respectively. The median MBF in shuttle mode was 56% lower than the true MBF. In non-shuttle and continuous mode, the underestimation was 41% and 18%. Limited temporal sampling rate in standard dynamic CTMPI techniques contributes to substantial underestimation of true MBF.

The role of acquisition and quantification methods in myocardial blood flow estimability for myocardial perfusion imaging CT

In this work, we clarified the role of acquisition parameters and quantification methods in myocardial blood flow (MBF) estimability for myocardial perfusion imaging using CT (MPI-CT). We used a physiologic model with a CT simulator to generate time-attenuation curves across a range of imaging conditions, i.e. tube current-time product, imaging duration, and temporal sampling, and physiologic conditions, i.e. MBF and arterial input function width. We assessed MBF estimability by precision (interquartile range of MBF estimates) and bias (difference between median MBF estimate and reference MBF) for multiple quantification methods. Methods included: six existing model-based deconvolution models, such as the plug-flow tissue uptake model (PTU), Fermi function model, and single-compartment model (SCM); two proposed robust physiologic models (RPM1, RPM2); model-independent singular value decomposition with Tikhonov regularization determined by the L-curve criterion (LSVD); and maximum upslope (MUP). Simulations show that MBF estimability is most affected by changes in imaging duration for model-based methods and by changes in tube current-time product and sampling interval for model-independent methods. Models with three parameters, i.e. RPM1, RPM2, and SCM, gave least biased and most precise MBF estimates. The average relative bias (precision) for RPM1, RPM2, and SCM was  ⩽11% (⩽10%) and the models produced high-quality MBF maps in CT simulated phantom data as well as in a porcine model of coronary artery stenosis. In terms of precision, the methods ranked best-to-worst are: RPM1  >  RPM2  >  Fermi  >  SCM  >  LSVD  >  MUP [Formula: see text] other methods. In terms of bias, the models ranked best-to-worst are: SCM  >  RPM2  >  RPM1  >  PTU  >  LSVD [Formula: see text] other methods. Models with four or more parameters, particularly five-parameter models, had very poor precision (as much as 310% uncertainty) and/or significant bias (as much as 493%) and were sensitive to parameter initialization, thus suggesting the presence of multiple local minima. For improved estimates of MBF from MPI-CT, it is recommended to use reduced models that incorporate prior knowledge of physiology and contrast agent uptake, such as the proposed RPM1 and RPM2 models.

Low-dose dynamic myocardial perfusion CT imaging using a motion adaptive sparsity prior

PURPOSE

Dynamic myocardial perfusion computed tomography (DM-PCT) imaging offers benefits over quantitative assessment of myocardial blood flow (MBF) for diagnosis and risk stratification of coronary artery disease. However, one major drawback of DM-PCT imaging is that a high radiation level is imparted by repeated scanning. To address this issue, in this work, we developed a statistical iterative reconstruction algorithm based on the penalized weighted least-squares (PWLS) scheme by incorporating a motion adaptive sparsity prior (MASP) model to achieve high-quality DM-PCT imaging with low tube current dynamic data acquisition. For simplicity, we refer to the proposed algorithm as "PWLS-MASP''.

METHODS

The MASP models both the spatial and temporal structured sparsity of DM-PCT sequence images with the assumption that the differences between adjacent frames after motion correction are sparse in the gradient image domain. To validate and evaluate the effectiveness of the present PWLS-MASP algorithm thoroughly, a modified XCAT phantom and preclinical porcine DM-PCT dataset were used in the study.

RESULTS

The present PWLS-MASP algorithm can obtain high-quality DM-PCT images in both phantom and porcine cases, and outperforms the existing filtered back-projection algorithm and PWLS-based algorithms with total variation regularization (PWLS-TV) and robust principal component analysis regularization (PWLS-RPCA) in terms of noise reduction, streak artifacts mitigation, and time density curve estimation. Moreover, the PWLS-MASP algorithm can yield more accurate diagnostic hemodynamic parametric maps than the PWLS-TV and PWLS-RPCA algorithms.

CONCLUSIONS

The study indicates that there is a substantial advantage in using the present PWLS-MASP algorithm for low-dose DM-PCT, and potentially in other dynamic tomography areas.

Quantitative myocardial perfusion from static cardiac and dynamic arterial CT

Quantitative myocardial blood flow (MBF) estimation by dynamic contrast enhanced cardiac computed tomography (CT) requires multi-frame acquisition of contrast transit through the blood pool and myocardium to inform the arterial input and tissue response functions. Both the input and the tissue response functions for the entire myocardium are sampled with each acquisition. However, the long breath holds and frequent sampling can result in significant motion artifacts and relatively high radiation dose. To address these limitations, we propose and evaluate a new static cardiac and dynamic arterial (SCDA) quantitative MBF approach where (1) the input function is well sampled using either prediction from pre-scan timing bolus data or measured from dynamic thin slice 'bolus tracking' acquisitions, and (2) the whole-heart tissue response data is limited to one contrast enhanced CT acquisition. A perfusion model uses the dynamic arterial input function to generate a family of possible myocardial contrast enhancement curves corresponding to a range of MBF values. Combined with the timing of the single whole-heart acquisition, these curves generate a lookup table relating myocardial contrast enhancement to quantitative MBF. We tested the SCDA approach in 28 patients that underwent a full dynamic CT protocol both at rest and vasodilator stress conditions. Using measured input function plus single (enhanced CT only) or plus double (enhanced and contrast free baseline CT's) myocardial acquisitions yielded MBF estimates with root mean square (RMS) error of 1.2 ml/min/g and 0.35 ml/min/g, and radiation dose reductions of 90% and 83%, respectively. The prediction of the input function based on timing bolus data and the static acquisition had an RMS error compared to the measured input function of 26.0% which led to MBF estimation errors greater than threefold higher than using the measured input function. SCDA presents a new, simplified approach for quantitative perfusion imaging with an acquisition strategy offering substantial radiation dose and computational complexity savings over dynamic CT.

SLIC robust (SLICR) processing for fast, robust CT myocardial blood flow quantification

There are several computational methods for estimating myocardial blood flow (MBF) using CT myocardial perfusion imaging (CT-MPI). Previous work has shown that model-based deconvolution methods are more accurate and precise than model-independent methods such as singular value decomposition and max-upslope. However, iterative optimization is computationally expensive and models are sensitive to image noise, thus limiting the utility of low x-ray dose acquisitions. We propose a new processing method, SLICR, which segments the myocardium into super-voxels using a modified simple linear iterative clustering (SLIC) algorithm and quantifies MBF via a robust physiologic model (RPM). We compared SLICR against voxel-wise SVD and voxel-wise model-based deconvolution methods (RPM, single-compartment and Johnson-Wilson). We used image data from a digital CT-MPI phantom to evaluate robustness of processing methods to noise at reduced x-ray dose. We validate SLICR in a porcine model with and without partial occlusion of the LAD coronary artery with known pressure-wire fractional flow reserve. SLICR was ~50 times faster than voxel-wise RPM and other model-based methods while retaining sufficient resolution to show all clinically interesting features (e.g., a flow deficit in the endocardial wall). SLICR showed much better precision and accuracy than the other methods. For example, at simulated MBF=100 mL/min/100g and 100 mAs exposure (50% of nominal dose) in the digital simulator, MBF estimates were 101 ± 12 mL/min/100g, 160 ± 54 mL/min/100g, and 122 ± 99 mL/min/100g for SLICR, SVD, and Johnson-Wilson, respectively. SLICR even gave excellent results (103 ± 23 ml/min/100g) at 50 mAs, corresponding to 25% nominal dose.

[Redundancy information-induced image reconstruction for low-dose myocardial perfusion computed tomography]

OBJECTIVE

In the clinic, myocardial perfusion computed tomography (MPCT) imaging is commonly used to detect and assess myocardial ischemia quantitatively. However, repeated scanning on the myocardial region in the cine mode will increase the radiation dose for patients. With lowering radiation dose, the quality of images are degraded by noise induced artifact, which hampers the diagnostic accuracy. Therefore, in this paper, we propose a redundancy information induced iterative reconstruction framework for high quality MPCT images at the case of low dose.

METHODS

MPCT images have redundant structural information within frames and highly similarity between adjacent frames. Inspired by the two properties, in this work we propose a penalized weighted least-squares (PWLS) model incorporating NLM and TV based hybrid constraints, which is referred to as PWLS-aviNLM-TV for simplicity. The proposed algorithm can effectively eliminate noise and artifacts by taking into account the similarity between adjacent frames and redundancy information within frames, which also can improve spatial resolution within frames and maintain temporal resolution.

RESULTS

The experimental results on the 4D extended cardiac-torso (XCAT) phantom and preclinical porcine dataset demonstrates that the PWLS-aviNLM-TV algorithm obtains better performance in terms of noise reduction and artifacts suppression than the PWLS-TV and PWLSaviNLM algorithm. Moreover, the proposed algorithm can preserve the edges and detail information thereby efficiently differentiate ischemia from myocardium.

CONCLUSIONS

The present redundancy information induced reconstruction algorithm can reconstruct high-quality images from low-dose MPCT for better clinical imaging diagnosis.

Comprehensive Assessment of Coronary Artery Disease by Using First-Pass Analysis Dynamic CT Perfusion: Validation in a Swine Model

Purpose To retrospectively validate a first-pass analysis (FPA) technique that combines computed tomographic (CT) angiography and dynamic CT perfusion measurement into one low-dose examination. Materials and Methods The study was approved by the animal care committee. The FPA technique was retrospectively validated in six swine (mean weight, 37.3 kg ± 7.5 [standard deviation]) between April 2015 and October 2016. Four to five intermediate-severity stenoses were generated in the left anterior descending artery (LAD), and 20 contrast material-enhanced volume scans were acquired per stenosis. All volume scans were used for maximum slope model (MSM) perfusion measurement, but only two volume scans were used for FPA perfusion measurement. Perfusion measurements in the LAD, left circumflex artery (LCx), right coronary artery, and all three coronary arteries combined were compared with microsphere perfusion measurements by using regression, root-mean-square error, root-mean-square deviation, Lin concordance correlation, and diagnostic outcomes analysis. The CT dose index and size-specific dose estimate per two-volume FPA perfusion measurement were also determined. Results FPA and MSM perfusion measurements (P_FPA and P_MSM) in all three coronary arteries combined were related to reference standard microsphere perfusion measurements (P_MICRO), as follows: P_{FPA_COMBINED} = 1.02 P_{MICRO_COMBINED} + 0.11 (r = 0.96) and P_{MSM_COMBINED} = 0.28 P_{MICRO_COMBINED} + 0.23 (r = 0.89). The CT dose index and size-specific dose estimate per two-volume FPA perfusion measurement were 10.8 and 17.8 mGy, respectively. Conclusion The FPA technique was retrospectively validated in a swine model and has the potential to be used for accurate, low-dose vessel-specific morphologic and physiologic assessment of coronary artery disease. ^© RSNA, 2017.

Variable temporal sampling and tube current modulation for myocardial blood flow estimation from dose-reduced dynamic computed tomography

Quantification of myocardial blood flow (MBF) can aid in the diagnosis and treatment of coronary artery disease. However, there are no widely accepted clinical methods for estimating MBF. Dynamic cardiac perfusion computed tomography (CT) holds the promise of providing a quick and easy method to measure MBF quantitatively. However, the need for repeated scans can potentially result in a high patient radiation dose, limiting the clinical acceptance of this approach. In our previous work, we explored techniques to reduce the patient dose by either uniformly reducing the tube current or by uniformly reducing the number of temporal frames in the dynamic CT sequence. These dose reduction techniques result in noisy time-attenuation curves (TACs), which can give rise to significant errors in MBF estimation. We seek to investigate whether nonuniformly varying the tube current and/or sampling intervals can yield more accurate MBF estimates for a given dose. Specifically, we try to minimize the dose and obtain the most accurate MBF estimate by addressing the following questions: when in the TAC should the CT data be collected and at what tube current(s)? We hypothesize that increasing the sampling rate and/or tube current during the time frames when the myocardial CT number is most sensitive to the flow rate, while reducing them elsewhere, can achieve better estimation accuracy for the same dose. We perform simulations of contrast agent kinetics and CT acquisitions to evaluate the relative MBF estimation performance of several clinically viable variable acquisition methods. We find that variable temporal and tube current sequences can be performed that impart an effective dose of 5.5 mSv and allow for reductions in MBF estimation root-mean-square error on the order of 20% compared to uniform acquisition sequences with comparable or higher radiation doses.

Functional Assessment of Coronary Artery Disease Using Whole-Heart Dynamic Computed Tomographic Perfusion

BACKGROUND

Computed tomographic (CT) angiography is an important tool for the evaluation of coronary artery disease but often correlates poorly with myocardial ischemia. Current dynamic CT perfusion techniques can assess ischemia but have limited accuracy and deliver high radiation dose. Therefore, an accurate, low-dose, dynamic CT perfusion technique is needed.

METHODS AND RESULTS

A total of 20 contrast-enhanced CT volume scans were acquired in 5 swine (40±10 kg) to generate CT angiography and perfusion images. Varying degrees of stenosis were induced using a balloon catheter in the proximal left anterior descending coronary artery, and a pressure wire was used for reference fractional flow reserve (FFR) measurement. Perfusion measurements were made with only 2 volume scans using a new first-pass analysis (FPA) technique and with 20 volume scans using an existing maximum slope model (MSM) technique. Perfusion (P) and FFR measurements were related by P_FPA=1.01 FFR-0.03 (R²=0.85) and P_MSM=1.03 FFR-0.03 (R²=0.80) for FPA and MSM techniques, respectively. Additionally, the effective radiation doses were calculated to be 2.64 and 26.4 mSv for FPA and MSM techniques, respectively.

CONCLUSIONS

A new FPA-based dynamic CT perfusion technique was validated in a swine animal model. The results indicate that the FPA technique can potentially be used for improved anatomical and functional assessment of coronary artery disease at a relatively low radiation dose.

Low-dose dynamic myocardial perfusion CT image reconstruction using pre-contrast normal-dose CT scan induced structure tensor total variation regularization

Dynamic myocardial perfusion CT (DMP-CT) imaging provides quantitative functional information for diagnosis and risk stratification of coronary artery disease by calculating myocardial perfusion hemodynamic parameter (MPHP) maps. However, the level of radiation delivered by dynamic sequential scan protocol can be potentially high. The purpose of this work is to develop a pre-contrast normal-dose scan induced structure tensor total variation regularization based on the penalized weighted least-squares (PWLS) criteria to improve the image quality of DMP-CT with a low-mAs CT acquisition. For simplicity, the present approach was termed as 'PWLS-ndiSTV'. Specifically, the ndiSTV regularization takes into account the spatial-temporal structure information of DMP-CT data and further exploits the higher order derivatives of the objective images to enhance denoising performance. Subsequently, an effective optimization algorithm based on the split-Bregman approach was adopted to minimize the associative objective function. Evaluations with modified dynamic XCAT phantom and preclinical porcine datasets have demonstrated that the proposed PWLS-ndiSTV approach can achieve promising gains over other existing approaches in terms of noise-induced artifacts mitigation, edge details preservation, and accurate MPHP maps calculation.

Advances in myocardial CT perfusion imaging technology

With the booming development of CT technology, CT-based myocardial perfusion imaging (CTP) has begun to mature and has exhibited great advantages and application prospects as a complete evaluation method of anatomy and function for CAD. This article summarizes the CTP technology progress and analytical methods of CTP in recent years, briefly reviews the clinical relevance, and subsequently discusses the limitation and future development.

Robust dynamic myocardial perfusion CT deconvolution for accurate residue function estimation via adaptive-weighted tensor total variation regularization: a preclinical study

Dynamic myocardial perfusion computed tomography (MPCT) is a promising technique for quick diagnosis and risk stratification of coronary artery disease. However, one major drawback of dynamic MPCT imaging is the heavy radiation dose to patients due to its dynamic image acquisition protocol. In this work, to address this issue, we present a robust dynamic MPCT deconvolution algorithm via adaptive-weighted tensor total variation (AwTTV) regularization for accurate residue function estimation with low-mA s data acquisitions. For simplicity, the presented method is termed 'MPD-AwTTV'. More specifically, the gains of the AwTTV regularization over the original tensor total variation regularization are from the anisotropic edge property of the sequential MPCT images. To minimize the associative objective function we propose an efficient iterative optimization strategy with fast convergence rate in the framework of an iterative shrinkage/thresholding algorithm. We validate and evaluate the presented algorithm using both digital XCAT phantom and preclinical porcine data. The preliminary experimental results have demonstrated that the presented MPD-AwTTV deconvolution algorithm can achieve remarkable gains in noise-induced artifact suppression, edge detail preservation, and accurate flow-scaled residue function and MPHM estimation as compared with the other existing deconvolution algorithms in digital phantom studies, and similar gains can be obtained in the porcine data experiment.

Mixed Confidence Estimation for Iterative CT Reconstruction

Dynamic (4D) CT imaging is used in a variety of applications, but the two major drawbacks of the technique are its increased radiation dose and longer reconstruction time. Here we present a statistical analysis of our previously proposed Mixed Confidence Estimation (MCE) method that addresses both these issues. This method, where framed iterative reconstruction is only performed on the dynamic regions of each frame while static regions are fixed across frames to a composite image, was proposed to reduce computation time. In this work, we generalize the previous method to describe any application where a portion of the image is known with higher confidence (static, composite, lower-frequency content, etc.) and a portion of the image is known with lower confidence (dynamic, targeted, etc). We show that by splitting the image space into higher and lower confidence components, MCE can lower the estimator variance in both regions compared to conventional reconstruction. We present a theoretical argument for this reduction in estimator variance and verify this argument with proof-of-principle simulations. We also propose a fast approximation of the variance of images reconstructed with MCE and confirm that this approximation is accurate compared to analytic calculations of and multi-realization image variance. This MCE method requires less computation time and provides reduced image variance for imaging scenarios where portions of the image are known with more certainty than others allowing for potentially reduced radiation dose and/or improved dynamic imaging.

Evaluation of static and dynamic perfusion cardiac computed tomography for quantitation and classification tasks

Cardiac computed tomography (CT) acquisitions for perfusion assessment can be performed in a dynamic or static mode. Either method may be used for a variety of clinical tasks, including (1) stratifying patients into categories of ischemia and (2) using a quantitative myocardial blood flow (MBF) estimate to evaluate disease severity. In this simulation study, we compare method performance on these classification and quantification tasks for matched radiation dose levels and for different flow states, patient sizes, and injected contrast levels. Under conditions simulated, the dynamic method has low bias in MBF estimates (0 to [Formula: see text]) compared to linearly interpreted static assessment (0.45 to [Formula: see text]), making it more suitable for quantitative estimation. At matched radiation dose levels, receiver operating characteristic analysis demonstrated that the static method, with its high bias but generally lower variance, had superior performance ([Formula: see text]) in stratifying patients, especially for larger patients and lower contrast doses [area under the curve [Formula: see text] to 96 versus 0.86]. We also demonstrate that static assessment with a correctly tuned exponential relationship between the apparent CT number and MBF has superior quantification performance to static assessment with a linear relationship and to dynamic assessment. However, tuning the exponential relationship to the patient and scan characteristics will likely prove challenging. This study demonstrates that the selection and optimization of static or dynamic acquisition modes should depend on the specific clinical task.

Quantitative Myocardial Perfusion with Dynamic Contrast-Enhanced Imaging in MRI and CT: Theoretical Models and Current Implementation

Technological advances in magnetic resonance imaging (MRI) and computed tomography (CT), including higher spatial and temporal resolution, have made the prospect of performing absolute myocardial perfusion quantification possible, previously only achievable with positron emission tomography (PET). This could facilitate integration of myocardial perfusion biomarkers into the current workup for coronary artery disease (CAD), as MRI and CT systems are more widely available than PET scanners. Cardiac PET scanning remains expensive and is restricted by the requirement of a nearby cyclotron. Clinical evidence is needed to demonstrate that MRI and CT have similar accuracy for myocardial perfusion quantification as PET. However, lack of standardization of acquisition protocols and tracer kinetic model selection complicates comparison between different studies and modalities. The aim of this overview is to provide insight into the different tracer kinetic models for quantitative myocardial perfusion analysis and to address typical implementation issues in MRI and CT. We compare different models based on their theoretical derivations and present the respective consequences for MRI and CT acquisition parameters, highlighting the interplay between tracer kinetic modeling and acquisition settings.

Dynamic CT perfusion measurement in a cardiac phantom

Widespread clinical implementation of dynamic CT myocardial perfusion has been hampered by its limited accuracy and high radiation dose. The purpose of this study was to evaluate the accuracy and radiation dose reduction of a dynamic CT myocardial perfusion technique based on first pass analysis (FPA). To test the FPA technique, a pulsatile pump was used to generate known perfusion rates in a range of 0.96-2.49 mL/min/g. All the known perfusion rates were determined using an ultrasonic flow probe and the known mass of the perfusion volume. FPA and maximum slope model (MSM) perfusion rates were measured using volume scans acquired from a 320-slice CT scanner, and then compared to the known perfusion rates. The measured perfusion using FPA (P(FPA)), with two volume scans, and the maximum slope model (P(MSM)) were related to known perfusion (P(K)) by P(FPA) = 0.91P(K) + 0.06 (r = 0.98) and P(MSM) = 0.25P(K) - 0.02 (r = 0.96), respectively. The standard error of estimate for the FPA technique, using two volume scans, and the MSM was 0.14 and 0.30 mL/min/g, respectively. The estimated radiation dose required for the FPA technique with two volume scans and the MSM was 2.6 and 11.7-17.5 mSv, respectively. Therefore, the FPA technique can yield accurate perfusion measurements using as few as two volume scans, corresponding to approximately a factor of four reductions in radiation dose as compared with the currently available MSM. In conclusion, the results of the study indicate that the FPA technique can make accurate dynamic CT perfusion measurements over a range of clinically relevant perfusion rates, while substantially reducing radiation dose, as compared to currently available dynamic CT perfusion techniques.

Noninvasive physiologic assessment of coronary stenoses using cardiac CT

Coronary CT angiography (CCTA) has become an important noninvasive imaging modality in the diagnosis of coronary artery disease (CAD). CCTA enables accurate evaluation of coronary artery stenosis. However, CCTA provides limited information on the physiological significance of stenotic lesions. A noninvasive "one-stop-shop" diagnostic test that can provide both anatomical significance and functional significance of stenotic lesions would be beneficial in the diagnosis and management of CAD. Recently, with the introduction of novel techniques, such as myocardial CT perfusion, CT-derived fractional flow reserve (FFRCT), and transluminal attenuation gradient (TAG), CCTA has emerged as a noninvasive method for the assessment of both anatomy of coronary lesions and its physiological consequences during a single study. This review provides an overview of the current status of new CT techniques for the physiologic assessments of CAD.

Sinogram smoothing techniques for myocardial blood flow estimation from dose-reduced dynamic computed tomography

Dynamic contrast-enhanced computed tomography (CT) could provide an accurate and widely available technique for myocardial blood flow (MBF) estimation to aid in the diagnosis and treatment of coronary artery disease. However, one of its primary limitations is the radiation dose imparted to the patient. We are exploring techniques to reduce the patient dose by either reducing the tube current or by reducing the number of temporal frames in the dynamic CT sequence. Both of these dose reduction techniques result in noisy data. In order to extract the MBF information from the noisy acquisitions, we have explored several data-domain smoothing techniques. In this work, we investigate two specific smoothing techniques: the sinogram restoration technique in both the spatial and temporal domains and the use of the Karhunen-Loeve (KL) transform to provide temporal smoothing in the sinogram domain. The KL transform smoothing technique has been previously applied to dynamic image sequences in positron emission tomography. We apply a quantitative two-compartment blood flow model to estimate MBF from the time-attenuation curves and determine which smoothing method provides the most accurate MBF estimates in a series of simulations of different dose levels, dynamic contrast-enhanced cardiac CT acquisitions. As measured by root mean square percentage error (% RMSE) in MBF estimates, sinogram smoothing generally provides the best MBF estimates except for the cases of the lowest simulated dose levels (tube current = 25 mAs, 2 or 3 s temporal spacing), where the KL transform method provides the best MBF estimates. The KL transform technique provides improved MBF estimates compared to conventional processing only at very low doses (<7 mSv). Results suggest that the proposed smoothing techniques could provide high fidelity MBF information and allow for substantial radiation dose savings.

Simulation Evaluation of Quantitative Myocardial Perfusion Assessment from Cardiac CT

Contrast enhancement on cardiac CT provides valuable information about myocardial perfusion and methods have been proposed to assess perfusion with static and dynamic acquisitions. There is a lack of knowledge and consensus on the appropriate approach to ensure 1) sufficient diagnostic accuracy for clinical decisions and 2) low radiation doses for patient safety. This work developed a thorough dynamic CT simulation and several accepted blood flow estimation techniques to evaluate the performance of perfusion assessment across a range of acquisition and estimation scenarios. Cardiac CT acquisitions were simulated for a range of flow states (Flow = 0.5, 1, 2, 3 ml/g/min, cardiac output = 3,5,8 L/min). CT acquisitions were simulated with a validated CT simulator incorporating polyenergetic data acquisition and realistic x-ray flux levels for dynamic acquisitions with a range of scenarios including 1, 2, 3 sec sampling for 30 sec with 25, 70, 140 mAs. Images were generated using conventional image reconstruction with additional image-based beam hardening correction to account for iodine content. Time attenuation curves were extracted for multiple regions around the myocardium and used to estimate flow. In total, 2,700 independent realizations of dynamic sequences were generated and multiple MBF estimation methods were applied to each of these. Evaluation of quantitative kinetic modeling yielded blood flow estimates with an root mean square error (RMSE) of ∼0.6 ml/g/min averaged across multiple scenarios. Semi-quantitative modeling and qualitative static imaging resulted in significantly more error (RMSE = ∼1.2 and ∼1.2 ml/min/g respectively). For quantitative methods, dose reduction through reduced temporal sampling or reduced tube current had comparable impact on the MBF estimate fidelity. On average, half dose acquisitions increased the RMSE of estimates by only 18% suggesting that substantial dose reductions can be employed in the context of quantitative myocardial blood flow estimation. In conclusion, quantitative model-based dynamic cardiac CT perfusion assessment is capable of accurately estimating MBF across a range of cardiac outputs and tissue perfusion states, outperforms comparable static perfusion estimates, and is relatively robust to noise and temporal subsampling.