Dynamic CT perfusion imaging of the myocardium: a technical note on improvement of image quality

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.

Improvement of image quality on low-dose dynamic myocardial perfusion computed tomography with a novel 4-dimensional similarity filter

The aim of this study was to evaluate the effect of a novel 4-dimensional similarity filter (4DSF) on quantitative and qualitative parameters of low-dose dynamic myocardial computed tomography perfusion (CTP) images.In this retrospective study, medical records of 32 patients with suspected or known coronary artery disease who underwent dynamic myocardial CTP at 80 kV were included. The 4DSF reduces noise by averaging voxels that have similar dynamic behavior after adaptive iterative dose reduction 3D (AIDR3D) and deformable image registration were applied. Qualitative (artefact, contour sharpness, and myocardial homogeneity [1 = poor; 2 = intermediate; 3 = good]) and quantitative measurement (standard deviation [SD] and signal-to-noise ratio [SNR]) were compared between the 4DSF and AIDR3D. Contrast-to-noise ratio (CNR) between ischemic and normal remote myocardium was also assessed using myocardial perfusion magnetic resonance imaging as the reference standard in seven patients.The 4DSF was successfully applied to all the images. Improvement in subjective image quality yielded by 4DSF was higher than that yielded by AIDR3D (homogeneity, 1.0 [3 vs 2]; artefact, 1.5 [3 vs 1.5]; P < .001) in all patients. The 4DSF significantly decreased the SD by 59% (AIDR3D vs 4DSF: 33.5 ± 0.4 vs 13.8 ± 0.4, P < .001), increased the SNR by 134% (AIDR3D vs 4DSF: 4.4 ± 0.2 vs 10.3 ± 0.2, P < .001), and increased the CNR by 131% (AIDR3D vs 4DSF: 1.6 ± 0.2 vs 3.7 ± 0.2, P < .001).The 4DSF improved the qualitative and quantitative parameters of low-dose dynamic myocardial CTP images.

Clinical application of four-dimensional noise reduction filtering with a similarity algorithm in dynamic myocardial computed tomography perfusion imaging

We aimed to evaluate the effects of four-dimensional noise reduction filtering using a similarity algorithm (4D-SF) on the image quality and hemodynamic parameter of dynamic myocardial computed tomography perfusion (CTP). Sixty-eight patients who underwent dynamic myocardial CTP for the assessment of coronary artery disease were enrolled. Dynamic CTP was performed using a 320-row CT with low tube voltage scan (80 kVp). Two different datasets of dynamic CTP were reconstructed using iterative reconstruction (IR) alone and a combination of IR and 4D-SF. Qualitative (5-grade scale) and quantitative image quality scores were assessed, and the CT-derived myocardial blood flow (CT-MBF) was quantified. These results were compared between the two different CTP images. The qualitative image quality in CTP images reconstructed with IR and 4D-SF was significantly higher than that with IR alone (noise score: 4.7 vs. 3.4, p < 0.05). The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) in CTP images reconstructed with IR and 4D-SF were significantly higher than those with IR alone (SNR: 20.6 vs. 9.7; CNR: 7.9 vs. 3.9, respectively; p < 0.05). There was no significant difference in mean CT-MBF between the two sets of CTP images (3.01 vs. 3.03 mL/g/min, p = 0.1081). 4D-SF showed incremental value in improving image quality in combination with IR without altering CT-MBF quantification in dynamic myocardial CTP imaging with a low tube potential.

Impact of Knowledge-Based Iterative Model Reconstruction on Image Quality and Hemodynamic Parameters in Dynamic Myocardial Computed Tomography Perfusion Using Low-Tube-Voltage Scan: A Feasibility Study

OBJECTIVE

Knowledge-based iterative model reconstruction (IMR) yields diagnostically acceptable image quality in low-dose static computed tomography (CT). We aimed to evaluate the feasibility of IMR in dynamic myocardial computed tomography perfusion (CTP).

METHODS

We enrolled 24 patients who underwent stress dynamic CTP using a 256-slice CT. Images were reconstructed using filtered back projection (FBP), hybrid IR, and IMR. Image quality and hemodynamic parameters were compared among three algorithms.

RESULTS

Qualitative image quality and contrast-to-noise ratio were significantly higher by IMR than by FBP or hybrid IR (visual score: 4.1 vs. 3.0 and 3.5; contrast-to-noise ratio: 12.4 vs. 6.6 and 8.4; P < 0.05). No significant difference was observed among algorithms in CTP-derived myocardial blood flow (1.68 vs. 1.73 and 1.70 mL/g/min).

CONCLUSIONS

The use of knowledge-based iterative model reconstruction improves image quality without altering hemodynamic parameters in low-dose dynamic CTP, compared with FBP or hybrid IR.

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.

Dual-energy CT: a phantom comparison of different platforms for abdominal imaging

OBJECTIVES

Evaluation of imaging performance across dual-energy CT (DECT) platforms, including dual-layer CT (DLCT), rapid-kVp-switching CT (KVSCT) and dual-source CT (DSCT).

METHODS

A semi-anthropomorphic abdomen phantom was imaged on these DECT systems. Scans were repeated three times for CTDIvol levels of 10 mGy, 20 mGy, 30 mGy and different fat-simulating extension rings. Over the available range of virtual-monoenergetic images (VMI), noise as well as quantitative accuracy of hounsfield units (HU) and iodine concentrations were evaluated.

RESULTS

For all VMI levels, HU values could be determined with high accuracy compared to theoretical values. For KVSCT and DSCT, a noise increase was observed towards lower VMI levels. A patient-size dependent increase in the uncertainty of quantitative iodine concentrations is observed for all platforms. For a medium patient size the iodine concentration root-mean-square deviation at 20 mGy is 0.17 mg/ml (DLCT), 0.30 mg/ml (KVSCT) and 0.77mg/ml (DSCT).

CONCLUSION

Noticeable performance differences are observed between investigated DECT systems. Iodine concentrations and VMI HUs are accurately determined across all DECT systems. KVSCT and DLCT deliver slightly more accurate iodine concentration values than DSCT for investigated scenarios. In DLCT, low-noise and high-image contrast at low VMI levels may help to increase diagnostic information in abdominal CT.

KEY POINTS

• Current dual-energy CT platforms provide accurate, reliable quantitative information. • Dual-energy CT cross-platform evaluation revealed noticeable performance differences between different systems. • Dual-layer CT offers constant noise levels over the complete energy range.

Radiation Dose Reduction in CT Myocardial Perfusion Imaging Using SMART-RECON

In this paper, a newly developed statistical model-based image reconstruction [referred to as Simultaneous Multiple Artifacts Reduction in Tomographic RECONstruction (SMART-RECON)] is applied to low dose computer tomography (CT) myocardial perfusion imaging (CT-MPI). This method uses the nuclear norm of the spatial-temporal image matrix of the CT-MPI images as a regularizer, rather than a conventional spatial regularizer that incorporates image smoothness, edge preservation, or spatial sparsity into the reconstruction. In addition to providing the needed noise reduction for low-dose CT-MPI, SMART-RECON provides images with spatial resolution and noise power spectrum (NPS) properties, which are independent of contrast and dose levels. Both numerical simulations and in vivo animal studies were performed to validate the proposed method. In these studies, it was found that: 1) quantitative accuracy of perfusion maps in CT-MPI was well maintained for radiation dose level as low as 10 mAs per image frame, compared with the reference standard of 200 mAs for conventional filtered backprojection; 2) flow-occluded myocardium in the porcine heart was well delineated by SMART-RECON at 10 mAs per frame when compared with model-based image reconstruction using spatial total variation (TV) as the regularizer (referred to as TV-SIR) or spatial-temporal TV (ST-TV-SIR); the CT-MPI results were confirmed with positron-emission tomography imaging; 3) image sharpness in SMART-RECON images was nearly independent of image contrast level and radiation dose level, in stark contrast to TV-SIR and ST-TV-SIR, which displayed a strong dependence on both image contrast and radiation dose levels; and 4) the structure of the dose-normalized NPS for the SMART-RECON method did not depend on dose, while the TV-SIR and ST-TV-SIR NPS structure was dose-dependent.

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.

Technical prerequisites and imaging protocols for dynamic and dual energy myocardial perfusion imaging

Coronary CT angiography (CCTA) is an established imaging technique used for the non-invasive morphological assessment of coronary artery disease. As in invasive coronary angiography, CCTA anatomical assessment of coronary stenosis does not adequately predict hemodynamic relevance. However, recent technical improvements provide the possibility of CT myocardial perfusion imaging (CTMPI). Two distinct CT techniques are currently available for myocardial perfusion assessment: static CT myocardial perfusion imaging (sCTMPI), with single- or dual-energy modality, and dynamic CT myocardial perfusion imaging (dCTMPI). The combination of CCTA morphological assessment and CTMPI functional evaluation holds promise for achieving a comprehensive assessment of coronary artery anatomy and myocardial perfusion using a single image modality.

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.

Beyond stenosis detection: computed tomography approaches for determining the functional relevance of coronary artery disease

Coronary computed tomography angiography (CCTA) is an established imaging technique for the noninvasive assessment of coronary arteries. However, CCTA remains a morphologic technique with the same limitations as invasive coronary angiography in evaluating the hemodynamic significance of coronary stenosis. Different computed tomography (CT) techniques for the functional analysis of coronary lesions have recently emerged, including static and dynamic CT myocardial perfusion imaging and CT-based fractional flow reserve and transluminal attenuation gradient methods. These techniques hold promise for achieving a comprehensive appraisal of anatomic and functional aspects of coronary heart disease with a single modality.

Cardiac CT for myocardial ischaemia detection and characterization--comparative analysis

The assessment of patients presenting with symptoms of myocardial ischaemia remains one of the most common and challenging clinical scenarios faced by physicians. Current imaging modalities are capable of three-dimensional, functional and anatomical views of the heart and as such offer a unique contribution to understanding and managing the pathology involved. Evidence has accumulated that visual anatomical coronary evaluation does not adequately predict haemodynamic relevance and should be complemented by physiological evaluation, highlighting the importance of functional assessment. Technical advances in CT technology over the past decade have progressively moved cardiac CT imaging into the clinical workflow. In addition to anatomical evaluation, cardiac CT is capable of providing myocardial perfusion parameters. A variety of CT techniques can be used to assess the myocardial perfusion. The single energy first-pass CT and dual energy first-pass CT allow static assessment of myocardial blood pool. Dynamic cardiac CT imaging allows quantification of myocardial perfusion through time-resolved attenuation data. CT-based myocardial perfusion imaging (MPI) is showing promising diagnostic accuracy compared with the current reference modalities. The aim of this review is to present currently available myocardial perfusion techniques with a focus on CT imaging in light of recent clinical investigations. This article provides a comprehensive overview of currently available CT approaches of static and dynamic MPI and presents the results of corresponding clinical trials.

Dynamic CT Myocardial Perfusion Imaging: Detection of Ischemia in a Porcine Model with FFR Verification

Dynamic cardiac CT perfusion (CTP) is a high resolution, non-invasive technique for assessing myocardial blood flow (MBF), which in concert with coronary CT angiography enable CT to provide a unique, comprehensive, fast analysis of both coronary anatomy and functional flow. We assessed perfusion in a porcine model with and without coronary occlusion. To induce occlusion, each animal underwent left anterior descending (LAD) stent implantation and angioplasty balloon insertion. Normal flow condition was obtained with balloon completely deflated. Partial occlusion was induced by balloon inflation against the stent with FFR used to assess the extent of occlusion. Prospective ECG-triggered partial scan images were acquired at end systole (45% R-R) using a multi-detector CT (MDCT) scanner. Images were reconstructed using FBP and a hybrid iterative reconstruction (iDose 4, Philips Healthcare). Processing included: beam hardening (BH) correction, registration of image volumes using 3D cubic B-spline normalized mutual-information, and spatio-temporal bilateral filtering to reduce partial scan artifacts and noise variation. Absolute blood flow was calculated with a deconvolution-based approach using singular value decomposition (SVD). Arterial input function was estimated from the left ventricle (LV) cavity. Regions of interest (ROIs) were identified in healthy and ischemic myocardium and compared in normal and occluded conditions. Under-perfusion was detected in the correct LAD territory and flow reduction agreed well with FFR measurements. Flow was reduced, on average, in LAD territories by 54%.