Iterative image reconstruction algorithms in coronary CT angiography improve the detection of lipid-core plaque – a comparison with histology

Characteristics and evaluation of atherosclerotic plaques: an overview of state-of-the-art techniques

Atherosclerosis is an important cause of cerebrovascular and cardiovascular disease (CVD). Lipid infiltration, inflammation, and altered vascular stress are the critical mechanisms that cause atherosclerotic plaque formation. The hallmarks of the progression of atherosclerosis include plaque ulceration, rupture, neovascularization, and intraplaque hemorrhage, all of which are closely associated with the occurrence of CVD. Assessing the severity of atherosclerosis and plaque vulnerability is crucial for the prevention and treatment of CVD. Integrating imaging techniques for evaluating the characteristics of atherosclerotic plaques with computer simulations yields insights into plaque inflammation levels, spatial morphology, and intravascular stress distribution, resulting in a more realistic and accurate estimation of plaque state. Here, we review the characteristics and advancing techniques used to analyze intracranial and extracranial atherosclerotic plaques to provide a comprehensive understanding of atheroma.

Performance of Spectral Photon-Counting Coronary CT Angiography and Comparison with Energy-Integrating-Detector CT: Objective Assessment with Model Observer

AIMS

To evaluate spectral photon-counting CT's (SPCCT) objective image quality characteristics in vitro, compared with standard-of-care energy-integrating-detector (EID) CT.

METHODS

We scanned a thorax phantom with a coronary artery module at 10 mGy on a prototype SPCCT and a clinical dual-layer EID-CT under various conditions of simulated patient size (small, medium, and large). We used filtered back-projection with a soft-tissue kernel. We assessed noise and contrast-dependent spatial resolution with noise power spectra (NPS) and target transfer functions (TTF), respectively. Detectability indices (d') of simulated non-calcified and lipid-rich atherosclerotic plaques were computed using the non-pre-whitening with eye filter model observer.

RESULTS

SPCCT provided lower noise magnitude (9-38% lower NPS amplitude) and higher noise frequency peaks (sharper noise texture). Furthermore, SPCCT provided consistently higher spatial resolution (30-33% better TTF10). In the detectability analysis, SPCCT outperformed EID-CT in all investigated conditions, providing superior d'. SPCCT reached almost perfect detectability (AUC ≈ 95%) for simulated 0.5-mm-thick non-calcified plaques (for large-sized patients), whereas EID-CT had lower d' (AUC ≈ 75%). For lipid-rich atherosclerotic plaques, SPCCT achieved 85% AUC vs. 77.5% with EID-CT.

CONCLUSIONS

SPCCT outperformed EID-CT in detecting simulated coronary atherosclerosis and might enhance diagnostic accuracy by providing lower noise magnitude, markedly improved spatial resolution, and superior lipid core detectability.

A Novel Iterative MLEM Image Reconstruction Algorithm Based on Beltrami Filter: Application to ECT Images

The implementation of emission-computed tomography (ECT), including positron emission tomography and single-photon emission-computed tomography, has been an important research topic in recent years and is of significant and practical importance. However, the slow rate of convergence and the computational complexity have severely impeded the efficient implementation of iterative reconstruction. By combining the maximum-likelihood expectation maximization (MLEM) iteratively along with the Beltrami filter, this paper proposes a new approach to reformulate the MLEM algorithm. Beltrami filtering is applied to an image obtained using the MLEM algorithm for each iteration. The role of Beltrami filtering is to remove mainly out-of-focus slice blurs, which are artifacts present in most existing images. To improve the quality of an image reconstructed using MLEM, the Beltrami filter employs similar structures, which in turn reduce the number of errors in the reconstructed image. Numerical image reconstruction tomography experiments have demonstrated the performance capability of the proposed algorithm in terms of an increase in signal-to-noise ratio (SNR) and the recovery of fine details that can be hidden in the data. The SNR and visual inspections of the reconstructed images are significantly improved compared to those of a standard MLEM. We conclude that the proposed algorithm provides an edge-preserving image reconstruction and substantially suppress noise and edge artifacts.

Extraction of Coronary Atherosclerotic Plaques From Computed Tomography Imaging: A Review of Recent Methods

Background: Atherosclerotic plaques are the major cause of coronary artery disease (CAD). Currently, computed tomography (CT) is the most commonly applied imaging technique in the diagnosis of CAD. However, the accurate extraction of coronary plaque geometry from CT images is still challenging.

Summary of Review: In this review, we focused on the methods in recent studies on the CT-based coronary plaque extraction. According to the dimension of plaque extraction method, the studies were categorized into two-dimensional (2D) and three-dimensional (3D) ones. In each category, the studies were analyzed in terms of data, methods, and evaluation. We summarized the merits and limitations of current methods, as well as the future directions for efficient and accurate extraction of coronary plaques using CT imaging.

Conclusion: The methodological innovations are important for more accurate CT-based assessment of coronary plaques in clinical applications. The large-scale studies, de-blooming algorithms, more standardized datasets, and more detailed classification of non-calcified plaques could improve the accuracy of coronary plaque extraction from CT images. More multidimensional geometric parameters can be derived from the 3D geometry of coronary plaques. Additionally, machine learning and automatic 3D reconstruction could improve the efficiency of coronary plaque extraction in future studies.

Coronary Computed Tomography Angiography From Clinical Uses to Emerging Technologies: JACC State-of-the-Art Review

Evaluation of coronary artery disease (CAD) using coronary computed tomography angiography (CCTA) has seen a paradigm shift in the last decade. Evidence increasingly supports the clinical utility of CCTA across various stages of CAD, from the detection of early subclinical disease to the assessment of acute chest pain. Additionally, CCTA can be used to noninvasively quantify plaque burden and identify high-risk plaque, aiding in diagnosis, prognosis, and treatment. This is especially important in the evaluation of CAD in immune-driven conditions with increased cardiovascular disease prevalence. Emerging applications of CCTA based on hemodynamic indices and plaque characterization may provide personalized risk assessment, affect disease detection, and further guide therapy. This review provides an update on the evidence, clinical applications, and emerging technologies surrounding CCTA as highlighted at the 2019 National Heart, Lung and Blood Institute CCTA Summit.

The impact of iterative reconstruction algorithms on machine learning-based coronary CT angiography-derived fractional flow reserve (CT-FFRML) values

To evaluate the impact of an iterative reconstruction (IR) algorithm (advanced modeled iterative reconstruction, ADMIRE) on machine learning-based coronary computed tomography angiography-derived fractional flow reserve (CT-FFR_ML) measurements compared with filtered back projection (FBP). 170 plaque-containing vessels in 107 patients were included. CT-FFR_ML values were measured and compared among 5 imaging reconstruction algorithms (FBP and ADMIRE at strength levels of 1, 2, 3 and 5). The plaques were classified as, 'calcified" or "noncalcified" and "≥ 50% stenosis" or "< 50% stenosis', a total of four subgroups by consensus. There were no significant differences of CT-FFR_ML values among the FBP and ADMIRE 1, 2, 3 and 5 groups wherever comparisons were done at the level of subgroups (P = 0.676, 0.414, 0.849, 0.873, respectively) or overall (P = 0.072). There were 20, 21, 19, 19 and 29 vessels with lesion-specific ischemia (CT-FFR_ML ≤ 0.80) in FBP and ADMIRE 1, 2, 3 and 5 datasets, respectively, but no statistical differences were found (P = 0.437). Compared with CT-FFR_ML value of FBP dataset, the CT-FFR_ML values of 9 (5.3%) vessels from 8 patients (7.5%) in ADMIRE5 dataset switched from above 0.8 to below or equal to 0.8. There were no significant differences of the CT-FFR_ML values among the FBP and IR image algorithms at different strength levels. However, high iterative strength level (ADMIRE 5) was not recommended, which might have an impact on diagnosis of lesion-specific ischemia, although changes only occurred in a modest number of subjects.

Radiomics versus Visual and Histogram-based Assessment to Identify Atheromatous Lesions at Coronary CT Angiography: An ex Vivo Study

Background Visual and histogram-based assessments of coronary CT angiography have limited accuracy in the identification of advanced lesions. Radiomics-based machine learning (ML) could provide a more accurate tool. Purpose To compare the diagnostic performance of radiomics-based ML with that of visual and histogram-based assessment of ex vivo coronary CT angiography cross sections to identify advanced atherosclerotic lesions defined with histologic examination. Materials and Methods In this prospective study, 21 coronary arteries from seven hearts obtained from male donors (mean age, 52.3 years ± 5.3) were imaged ex vivo with coronary CT angiography between February 23, 2009, and July 31, 2010. From 95 coronary plaques, 611 histologic cross sections were coregistered with coronary CT cross sections. Lesions were considered advanced if early fibroatheroma, late fibroatheroma, or thin-cap atheroma was present. CT cross sections were classified as showing homogeneous, heterogeneous, or napkin-ring sign plaques on the basis of visual assessment. The area of low attenuation (<30 HU) and the average Hounsfield unit were quantified. Radiomic parameters were extracted and used as inputs to ML algorithms. Eight radiomics-based ML models were trained on randomly selected cross sections (training set, 75% of the cross sections) to identify advanced lesions. Visual assessment, histogram-based assessment, and the best ML model were compared on the remaining 25% of the data (validation set) by using the area under the receiver operating characteristic curve (AUC) to identify advanced lesions. Results After excluding sections with no visible plaque (n = 134) and with heavy calcium (n = 32), 445 cross sections were analyzed. Of those 445 cross sections, 134 (30.1%) were advanced lesions. Visual assessment of the 445 cross sections indicated that 207 (46.5%) were homogeneous, 200 (44.9%) were heterogeneous, and 38 (8.5%) demonstrated the napkin-ring sign. A radiomics-based ML model incorporating 13 parameters outperformed visual assessment (AUC = 0.73 with 95% confidence interval [CI] of 0.63, 0.84 vs 0.65 with 95% CI of 0.56, 0.73, respectively; P = .04), area of low attenuation (AUC = 0.55 with 95% CI of 0.42, 0.68; P = .01), and average Hounsfield unit (AUC = 0.53 with 95% CI of 0.42, 0.65; P = .004) in the identification of advanced atheromatous lesions. Conclusion Radiomics-based machine learning analysis improves the discriminatory power of coronary CT angiography in the identification of advanced atherosclerotic lesions. Published under a CC BY 4.0 license.

Combining cholesterol-lowering strategies with imaging data: a visible benefit?

Coronary artery disease is characterised by the development of atherosclerotic plaques and is associated with significant morbidity and mortality on a global level. However, many patients with atherosclerosis are asymptomatic and the prediction of acute coronary events is challenging. The role of imaging studies in characterising plaque morphology and stability is emerging as a valuable prognostic tool, while providing evidence for the beneficial effects of cholesterol-lowering therapy on plaque burden. This review provides an overview of contemporary studies describing the value of imaging strategies for atherosclerotic plaques. Coronary angiography is commonly used in the clinical setting, but requires a significant radiation dose (similar to computed tomography). Magnetic resonance imaging evaluation of coronary vessels would avoid exposure to ionising radiation, but is not yet feasible due to motion artefacts. The roles of alternative imaging techniques, including grey-scale intravascular ultrasound, optical coherence tomography and near-infrared spectroscopy have emerged in recent years. In particular, grey-scale intravascular ultrasound has been effectively applied to detect changes in plaque burden and features of plaques predictive of rupture, as well as plaque characteristics during cholesterol-lowering therapy, providing novel insights into factors that may contribute to treatment effectiveness. Challenges and limitations to the use of imaging techniques are considered in this context, along with future imaging strategies.

The role of advanced reconstruction algorithms in cardiac CT

Non-linear iterative reconstruction (IR) algorithms have been increasingly incorporated into clinical cardiac CT protocols at institutions around the world. Multiple IR algorithms are available commercially from various vendors. IR algorithms decrease image noise and are primarily used to enable lower radiation dose protocols. IR can also be used to improve image quality for imaging of obese patients, coronary atherosclerotic plaques, coronary stents, and myocardial perfusion. In this article, we will review the various applications of IR algorithms in cardiac imaging and evaluate how they have changed practice.

Improved Estimation of Coronary Plaque and Luminal Attenuation Using a Vendor-specific Model-based Iterative Reconstruction Algorithm in Contrast-enhanced CT Coronary Angiography

RATIONALE AND OBJECTIVES

To investigate the stabilities of plaque attenuation and coronary lumen for different plaque types, stenotic degrees, lumen densities, and reconstruction methods using coronary vessel phantoms and the visualization of coronary plaques in clinical patients through coronary computed tomography (CT) angiography.

MATERIALS AND METHODS

We performed 320-detector volume scanning of vessel tubes with stenosis and a tube without stenosis using three types of plaque CT numbers. The stenotic degrees were 50% and 75%. Images were reconstructed with filtered back projection (FBP) and two types of iterative reconstructions (AIDR3D and FIRST [forward-projected model-based iterative reconstruction solution]), with stenotic CT number of approximately 40, 80, and 150 HU (Hounsfield unit), respectively. In each case, the tubing of the coronary vessel was filled with diluted contrast material and distilled water to reach the target lumen CT numbers of approximately 350 HU and 450 HU, and 0 HU, respectively. Peak lumen and plaque CT numbers were measured to calculate the lumen-plaque contrast. In addition, we retrospectively evaluated the image quality with regard to coronary arterial lumen and the plaque in 10 clinical patients on a 4-point scale.

RESULTS

At 50% stenosis, the plaque CT number with contrast enhancement increased for FBP and AIDR3D, and the difference in the plaque CT number with and without contrast enhancement was 15-44 HU for FBP and 10-31 HU for AIDR3D. However, the plaque CT number for FIRST had a smaller variation and the difference with and without contrast enhancement was -12 to 8 HU. The visual evaluation score for the vessel lumen was 2.8 ± 0.6, 3.5 ± 0.5, and 3.7 ± 0.5 for FBP, AIDR3D, and FIRST, respectively.

CONCLUSIONS

The FIRST method controls the increase in plaque density and the lumen-plaque contrast. Consequently, it improves the visualization of coronary plaques in coronary CT angiography.

In vivo coronary artery plaque assessment with computed tomography angiography: is there an impact of iterative reconstruction on plaque volume and attenuation metrics?

Background Coronary computed tomography angiography (CTA) allows the evaluation of coronary plaque volume and low attenuation (lipid-rich) component, for plaque vulnerability assessment. Purpose To determine the effect of iterative reconstruction (IR) on coronary plaque volume and composition. Material and Methods Consecutive patients without coronary artery disease were prospectively enrolled for 256-slice CT. Images were reconstructed with both filtered back projection (FBP) and a hybrid IR algorithm (iDose⁴, Philips) levels 1, 3, 5, and 7. Coronary plaques were assessed according to predefined Hounsfield unit (HU) attenuation intervals, for total plaque and HU-interval volumes. Results Fifty-three patients (mean age, 53.6 years) were included. Noise was significantly decreased and signal-to-noise ratio (SNR) / contrast-to-noise (CNR) were both significantly improved at all IR levels in comparison to FBP. Plaque characterization was performed in 41 patients for a total of 125 plaques. Total plaque volume ranged from 104.4 ± 120.7 to 107.4 ± 128.9 mm³ and low attenuation plaque component from 40.5 ± 54.7 to 43.5 ± 58.9 mm³, with no statistically significant differences between all IR levels and FBP ( P = 0.786 and P ≥ 0.078, respectively). Conclusion IR improved image quality. Total and low attenuation plaque volumes were similar using either IR or FBP.

Diagnostic accuracy of contemporary multidetector computed tomography (MDCT) for the detection of lumbar disc herniation

OBJECTIVES

To evaluate the diagnostic accuracy of multidetector CT (MDCT) for detection of lumbar disc herniation with MRI as standard of reference.

METHODS

Patients with low back pain underwent indicated MDCT (128-row MDCT, helical pitch), 60 patients with iterative reconstruction (IR) and 67 patients with filtered back projection (FBP). Lumbar spine MRI (1.5 T) was performed within 1 month. Signal-to-noise ratios (SNR) of cerebrospinal fluid (CSF), annulus fibrosus (AF) and the spinal cord (SC) were determined for all modalities. Two readers independently rated image quality (IQ), diagnostic confidence and accuracy in the diagnosis of lumbar disc herniation using MRI as standard of reference. Inter-reader correlation was assessed with weighted κ.

RESULTS

Sensitivity, specificity, precision and accuracy of MDCT for disc protrusion were 98.8%, 96.5%, 97.1%, 97.8% (disc level), 97.7%, 92.9%, 98.6%, 96.9% (patient level). SNR of IR was significantly higher than FBP. IQ was significantly better in IR owing to visually reduced noise and improved delineation of the discs. κ (>0.90) was excellent for both algorithms.

CONCLUSION

MDCT of the lumbar spine yields high diagnostic accuracy for detection of lumbar disc herniation. IR improves image quality so that the provided diagnostic accuracy is principally equivalent to MRI.

KEY POINTS

• MDCT is an accurate alternative to MRI in disc herniation diagnosis. • By IR enhanced image quality improves MDCT diagnostic confidence similar to MRI. • Advances in CT technology contribute to improved diagnostic performance in lumbar spine imaging.

First experiences with model based iterative reconstructions influence on quantitative plaque volume and intensity measurements in coronary computed tomography angiography

PURPOSE

Investigate the influence of adaptive statistical iterative reconstruction (ASIR) and the model-based IR (Veo) reconstruction algorithm in coronary computed tomography angiography (CCTA) images on quantitative measurements in coronary arteries for plaque volumes and intensities.

METHODS

Three patients had three independent dose reduced CCTA performed and reconstructed with 30% ASIR (CTDI_vol at 6.7 mGy), 60% ASIR (CTDI_vol 4.3 mGy) and Veo (CTDI_vol at 1.9 mGy). Coronary plaque analysis was performed for each measured CCTA volumes, plaque burden and intensities.

RESULTS

Plaque volume and plaque burden show a decreasing tendency from ASIR to Veo as median volume for ASIR is 314 mm³ and 337 mm³-252 mm³ for Veo and plaque burden is 42% and 44% for ASIR to 39% for Veo. The lumen and vessel volume decrease slightly from 30% ASIR to 60% ASIR with 498 mm³-391 mm³ for lumen volume and vessel volume from 939 mm³ to 830 mm³. The intensities did not change overall between the different reconstructions for either lumen or plaque.

CONCLUSION

We found a tendency of decreasing plaque volumes and plaque burden but no change in intensities with the use of low dose Veo CCTA (1.9 mGy) compared to dose reduced ASIR CCTA (6.7 mGy & 4.3 mGy), although more studies are warranted.

Association between serum N-terminal pro-B-type natriuretic peptide levels and characteristics of coronary atherosclerotic plaque detected by coronary computed tomography angiography

The aim of the present study was to explore the association between the levels of serum N-terminal pro-B-type natriuretic peptide (NT-pro BNP) and the characteristics of coronary atherosclerotic plaque detected by coronary computed tomography angiography (CCTA), in patients with unstable angina (UA). A total of 202 patients (age range, 47-82 years) were divided into the following three groups: Non-cardiac disease group (57 patients); stable angina pectoris (SAP) group (62 patients); and UA group (83 patients). There were significant differences between the serum NT-pro BNP levels among the three groups (P=0.007). However, in multivariant diagnoses, NT-pro BNP level was not an independent risk factor for UA. The levels of serum NT-pro BNP were observed to be positively correlated with the number of vessels involved (r=0.462; P<0.001), SIS (r=0.475; P<0.001), segment-stenosis score (r=0.453; P<0.001), coronary calcification score (r=0.412; P=0.001), number of obstructive diseases (r=0.346; P<0.001), and the number of segments with non-calcified plaque (r=0.235; P=0.017), mixed plaque (r=0.234; P=0.017) and calcified plaque (r=0.431; P<0.001). The levels of serum NT-pro BNP were significantly higher in patients with UA and left main-left anterior descending (LM-LAD) disease, compared with UA patients without LM-LAD disease (P<0.001). In addition, serum NT-pro BNP was significantly higher in patients with obstructive disease and UA than in those without obstructive disease (P<0.001). The area under the curve of log(NT-pro BNP) was 0.656 (P=0.006; optimal cut-off value, 1.74; sensitivity, 77.6%; specificity, 51.9%). In conclusion, the levels of serum NT-pro BNP are associated with the burden and severity of coronary artery atherosclerotic disease in patients with UA, and may be helpful in risk stratification of patients with UA.

Plaque assessment by coronary CT

Coronary CT angiography (CTA) has emerged as a highly reliable and non-invasive modality for the exclusion of coronary artery disease. Recent technological advancements in coronary CTA imaging allow for robust qualitative and quantitative assessment of atherosclerotic plaques. Furthermore, CTA is a promising modality for functional evaluation of coronary lesions. Individual plaque features, the extent and severity of atherosclerotic plaque burden were proposed to improve cardiovascular risk stratification. It has been suggested that total atherosclerotic plaque burden is a stronger predictor of coronary events than total ischemia burden. The quest to noninvasively detect individual vulnerable plaques still remains. In the current review we sought to summarize state-of-the-art coronary artery plaque assessment by CTA.

Iterative reconstruction in cardiac CT

Iterative reconstruction (IR) has the ability to reduce image noise in CT without compromising diagnostic quality, which permits a significant reduction in effective radiation dose. This been increasingly integrated into clinical CT practice over the past 7 years and has been particularly important in the field of cardiac CT with multiple vendors introducing cardiac CT-compatible IR algorithms. The following review will summarize the principles of IR algorithms, studies validating their noise- and dose-reducing abilities, and the specific applications of IR in cardiac CT.