Iterative model reconstruction reduces calcified plaque volume in coronary CT angiography

Feasibility of Low-Dose and Low-Contrast Media Volume Approach in Computed Tomography Cardiovascular Imaging Reconstructed with Model-Based Algorithm

Aim: To evaluate the dose reduction and image quality of low-dose, low-contrast media volume in computed tomography (CT) examinations reconstructed with the model-based iterative reconstruction (MBIR) algorithm in comparison with the hybrid iterative (HIR) one. Methods: We prospectively enrolled a total of 401 patients referred for cardiovascular CT, evaluated with a 256-MDCT scan with a low kVp (80 kVp) reconstructed with an MBIR (study group) or a standard HIR protocol (100 kVp-control group) after injection of a fixed dose of contrast medium volume. Vessel contrast enhancement and image noise were measured by placing the region of interest (ROI) in the left ventricle, ascending aorta; left, right and circumflex coronary arteries; main, right and left pulmonary arteries; aortic arch; and abdominal aorta. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were computed. Subjective image quality obtained by consensus was assessed by using a 4-point Likert scale. Radiation dose exposure was recorded. Results: HU values of the proximal tract of all coronary arteries; main, right and left pulmonary arteries; and of the aorta were significantly higher in the study group than in the control group (p < 0.05), while the noise was significantly lower (p < 0.05). SNR and CNR values in all anatomic districts were significantly higher in the study group (p < 0.05). MBIR subjective image quality was significantly higher than HIR in CCTA and CTPA protocols (p < 0.05). Radiation dose was significantly lower in the study group (p < 0.05). Conclusions: The MBIR algorithm combined with low-kVp can help reduce radiation dose exposure, reduce noise, and increase objective and subjective image quality.

Detection of monosodium urate depositions and atherosclerotic plaques in the cardiovascular system by dual-energy computed tomography

Aim

The study aimed to explore the relationship between urate deposition and surrounding atherosclerotic plaques, and to confirm the contribution of urate deposition to the development of coronary atherosclerosis.

Methods and results

The present study employed Dual-energy CT (DECT) material separation technology through calcium score scan to access the presence of MSU crystal deposition in coronary atherosclerotic plaques in patients with clinically suspected coronary heart diseases undergoing DECT. DECT showed that among 872 patients, 441 had plaques in coronary arteries; the incidence of plaque was 50.6 %. The patients were divided in the atherosclerotic plaque vs. non-plaque groups. There were significant differences in age, sex, blood pressure, blood glucose, serum creatinine, and history of gout and hyperuricemia between the plaque and non-plaque groups (all P < 0.05). Among the patients with coronary plaques, there were 348 patients (78.9 %) with simple atherosclerotic plaque (AP), 8 (1.8 %) with simple urate depositions (UD), and 85 (19.3 %) with urate depositions and atherosclerotic plaques (UDAP). The multivariable analysis showed that urate deposition was independently associated with plaques after adjustment for age, sex, blood pressure, blood glucose, serum creatinine, history of gout, and history of hyperuricemia (OR = 13.69, 95%CI: 7.53-22.95, P = 0.035). UPAP patients had significantly higher coronary calcium scores than AP patients [210.1 (625.2) AU vs 58.2 (182.5) AU, P < 0.001] Urate deposition (16.7 mm3) positively correlated with plaque calcification (73.8 mm³) in UPAP patients (r = 0.325, P < 0.001).

Conclusion

Patients with gout or a history of hyperuricemia were more likely to exhibit UDAP. Urate deposition was independently associated with plaques.

An Increased Diagnostic Accuracy of Significant Coronary Artery Stenosis Using 320-slice Computed Tomography with Model-based Iterative Reconstruction in Cases with Severely Calcified Coronary Arteries

Objective High-quality images can be obtained with 320-slice computed tomography (CT) with model-based iterative reconstruction (MBIR). We therefore investigated the diagnostic accuracy of 320-slice CT with MBIR for detecting significant coronary artery stenosis. Methods This was a retrospective study of 160 patients who underwent coronary CT and invasive coronary angiography (ICA). The first 100 consecutive patients (Group 1) underwent 320-slice CT without MBIR or small-focus scanning. The next 60 consecutive patients (Group 2) underwent 320-slice CT with both MBIR and small-focus scanning. Patients who underwent coronary artery bypass surgery were excluded. The diagnostic performance of 320-slice CT without MBIR or small-focus scanning and 320-slice CT with both of them, with ICA regarded as a reference standard, was compared to detect significant coronary artery stenosis (≥70% on CT, ≥75% on ICA). Results In a patient-based analysis, the sensitivity, specificity, and overall accuracy of detection of significant stenosis on CT against ICA were 95%, 85%, and 91% in Group 1, and 93%, 83%, and 90% in Group 2, respectively. No significant differences were observed between the two groups in the patient- and segment-based analyses. However, among cases with a severe coronary artery calcium score >400 (31 cases in Group 1 and 28 in Group 2), the specificity and overall accuracy were significantly higher (all p<0.01) in Group 2 than in Group 1 according to the segment-based analysis. Conclusion The diagnostic accuracy of the detection of coronary artery stenosis on CT was improved using 320-slice CT with MBIR.

Prevalence of Monosodium Urate (MSU) Deposits in Cadavers Detected by Dual-Energy Computed Tomography (DECT)

Background: Dual-energy computed tomography (DECT) allows direct visualization of monosodium urate (MSU) deposits in joints and soft tissues. Purpose: To describe the distribution of MSU deposits in cadavers using DECT in the head, body trunk, and feet. Materials and Methods: A total of 49 cadavers (41 embalmed and 8 fresh cadavers; 20 male, 29 female; mean age, 79.5 years; SD ± 11.3; range 52–95) of unknown clinical history underwent DECT to assess MSU deposits in the head, body trunk, and feet. Lens, thoracic aorta, and foot tendon dissections of fresh cadavers were used to verify MSU deposits by polarizing light microscopy. Results: 33/41 embalmed cadavers (80.5%) showed MSU deposits within the thoracic aorta. 11/41 cadavers (26.8%) showed MSU deposits within the metatarsophalangeal (MTP) joints and 46.3% of cadavers demonstrated MSU deposits within foot tendons, larger than and equal to 5 mm. No MSU deposits were detected in the cranium/intracerebral vessels, or the coronary arteries. Microscopy used as a gold standard could verify the presence of MSU deposits within the lens, thoracic aorta, or foot tendons in eight fresh cadavers. Conclusions: Microscopy confirmed the presence of MSU deposits in fresh cadavers within the lens, thoracic aorta, and foot tendons, whereas no MSU deposits could be detected in cranium/intracerebral vessels or coronary arteries. DECT may offer great potential as a screening tool to detect MSU deposits and measure the total uric acid burden in the body. The clinical impact of this cadaver study in terms of assessment of MSU burden should be further proven.

Computed tomography-based calcium scoring in cadaver leg arteries: Influence of dose, reader, and reconstruction algorithm

PURPOSE

Computed tomography (CT) might be a good diagnostic test to accurately quantify calcium in vascular beds but there are multiple factors influencing the quantification. The aim of this study was to investigate the influence of different computed tomography protocol settings in the quantification of calcium in the lower extremities using modified Agatston and volume scores.

METHODS

Fresh-frozen human legs were scanned at different tube current protocols and reconstructed at different slice thickness. Two different iterative reconstruction protocols for conventional CT images were compared. Calcium was manually scored using modified Agatston and volume scores. Outcomes were statistically analyzed using Wilcoxon signed-rank tests and mean absolute and relative differences were plotted in Bland-Altman plots.

RESULTS

Of the 20 legs, 16 had CT detectable calcifications. Differences between thick and thin slice reconstruction protocols were 129 Agatston units and 125% for Agatston and 78.4 mm³ and 57.8% for volume (all p ≤ 0.001). No significant differences were found between low and high tube current protocols. Differences between iDose⁴ and IMR reconstruction protocols for modified Agatston were 34.2 Agatston units and 17.7% and the volume score 33.5 mm³ and 21.2% (all p ≤ 0.001).

CONCLUSIONS

Slice thickness reconstruction and reconstruction method protocols influenced the modified Agatston and volume scores in leg arteries, but tube current and different observers did not have an effect. This data emphasizes the need for standardized quantification of leg artery calcifications. Possible implications are in the development of a more universal quantification method, independent of the type of scan and vasculature.

Model-based adaptive filter for a dedicated cardiovascular CT scanner: Assessment of image noise, sharpness and quality

BACKGROUND

Filtered back projection (FBP) and adaptive statistical iterative reconstruction (ASIR) are ubiquitously applied in the reconstruction of coronary CT angiography (CCTA) datasets. However, currently no data is available on the impact of a model-based adaptive filter (MBAF2), recently developed for a dedicated cardiac scanner.

PURPOSE

Our aim was to determine the effect of MBAF2 on subjective and objective image quality parameters of coronary arteries on CCTA.

METHODS

Images of 102 consecutive patients referred for CCTA were evaluated. Four reconstructions of coronary images (FBP, ASIR, MBAF2, ASIR + MBAF2) were co-registered and cross-section were assessed for qualitative (graininess, sharpness, overall image quality) and quantitative [image noise, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR)] image quality parameters. Image noise and signal were measured in the aortic root and the left main coronary artery, respectively. Graininess, sharpness, and overall image quality was assessed on a 4-point Likert scale.

RESULTS

As compared to FBP, ASIR, and MBAF2, ASIR + MBAF2 resulted in reduced image noise [53.1 ± 12.3, 30.6 ± 8.5, 36.3 ± 4.2, 26.3 ± 4.0 Hounsfield units (HU), respectively; p < 0.001], improved SNR (8.4 ± 2.6, 14.1 ± 3.6, 11.8 ± 2.3, 16.3 ± 3.3 HU, respectively; p < 0.001) and CNR (9.4 ± 2.7, 15.9 ± 4.0, 13.3 ± 2.5, 18.3 ± 3.5 HU, respectively; p < 0.001). No difference in sharpness was observed amongst the reconstructions (p = 0.08). Although ASIR + MBAF2 was non-superior to ASIR regarding overall image quality (p = 0.99), it performed better than FBP (p < 0.001) and MBAF2 (p < 0.001) alone.

CONCLUSION

The combination of ASIR and MBAF2 resulted in reduced image noise and improved SNR and CNR. The implementation of MBAF2 in clinical practice may result in improved noise reduction performance and could potentiate radiation dose reduction.

Effect of different reconstruction algorithms on coronary artery calcium scores using the reduced radiation dose protocol: a clinical and phantom study

Background

This study aimed to evaluate the effects of different iterative reconstruction (IR) algorithms on coronary artery calcium (CAC) score quantification using the reduced radiation dose (RRD) protocol in an anthropomorphic phantom and in patients.

Methods

A thorax phantom, containing 9 calcification inserts with varying hydroxyapatite (HA) densities, was scanned with the reference protocol [120 kv, 80 mAs, filtered back projection (FBP)] and RRD protocol (120 kV, 20-80 mAs, 5 mAs interval) using a 256-slice computed tomography (CT) scanner. Raw data were reconstructed with different reconstruction algorithms [iDose⁴ levels 1-7 and iterative model reconstruction (IMR) levels 1-3]. Signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and Agatston score (AS) were calculated for each image series. The correction factor was derived from linear regression analysis between the reference image series and other image series with different parameters. Additionally, 40 patients were scanned with the RRD protocol (50 mAs) and reconstructed with FBP, iDose⁴ level 4, and IMR level 2. AS was calculated for the 3-group image series, and was corrected by applying a correction factor for the IMR group. The agreement of risk stratification with different reconstruction algorithms was also analyzed.

Results

For the phantom study, the iDose⁴ and IMR groups had significantly higher SNR and CNR than the FBP group (all P<0.05). There were no significant differences in the total AS after comparing image series reconstructed with iDose⁴ (level 1-7) and FBP (all P>0.05), while AS from the IMR (level 1-3) image series were lower than the FBP group (all P<0.05). The tube current of 50 mAs was determined for the clinical study, and the correction factor was 1.14. For the clinical study, the median AS from the iDose⁴ and IMR groups were both significantly lower compared to the FBP image series [(112.89 (63.01, 314.09), 113.22 (64.78, 364.95) vs. 118.59 (65.05, 374.48), both P<0.05]. After applying the correction factor, the adjusted AS from the IMR group was not significantly different from that of the FBP group [126.48 (69.62, 355.85) vs. 118.59 (65.05, 374.48), P=0.145]. Moreover, the agreement in risk stratification between FBP and IMR improved from 0.81 to 0.85.

Conclusions

The RRD CAC scoring scan using the IMR reconstruction algorithm is clinically feasible, and a correction factor can help reduce the AS underestimation effect.

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.

Identification of invasive and radionuclide imaging markers of coronary plaque vulnerability using radiomic analysis of coronary computed tomography angiography

Aims

Identification of invasive and radionuclide imaging markers of coronary plaque vulnerability by a single, widely available non-invasive technique may provide the opportunity to identify vulnerable plaques and vulnerable patients in broad populations. Our aim was to assess whether radiomic analysis outperforms conventional assessment of coronary computed tomography angiography (CTA) images to identify invasive and radionuclide imaging markers of plaque vulnerability.

Methods and results

We prospectively included patients who underwent coronary CTA, sodium-fluoride positron emission tomography (NaF¹⁸-PET), intravascular ultrasound (IVUS), and optical coherence tomography (OCT). We assessed seven conventional plaque features and calculated 935 radiomic parameters from CTA images. In total, 44 plaques of 25 patients were analysed. The best radiomic parameters significantly outperformed the best conventional CT parameters to identify attenuated plaque by IVUS [fractal box counting dimension of high attenuation voxels vs. non-calcified plaque volume, area under the curve (AUC): 0.72, confidence interval (CI): 0.65–0.78 vs. 0.59, CI: 0.57–0.62; P < 0.001], thin-cap fibroatheroma by OCT (fractal box counting dimension of high attenuation voxels vs. presence of low attenuation voxels, AUC: 0.80, CI: 0.72–0.88 vs. 0.66, CI: 0.58–0.73; P < 0.001), and NaF¹⁸-positivity (surface of high attenuation voxels vs. presence of two high-risk features, AUC: 0.87, CI: 0.82–0.91 vs. 0.65, CI: 0.64–0.66; P < 0.001).

Conclusion

Coronary CTA radiomics identified invasive and radionuclide imaging markers of plaque vulnerability with good to excellent diagnostic accuracy, significantly outperforming conventional quantitative and qualitative high-risk plaque features. Coronary CTA radiomics may provide a more accurate tool to identify vulnerable plaques compared with conventional methods. Further larger population studies are warranted.

Dual-Energy Computed Tomography Detection of Cardiovascular Monosodium Urate Deposits in Patients With Gout

Importance

The prevalence of gout has increased in recent decades. Several clinical studies have demonstrated an association between gout and coronary heart disease, but direct cardiovascular imaging of monosodium urate (MSU) deposits by using dual-energy computed tomography (DECT) has not been reported to date.

Objective

To compare coronary calcium score and cardiovascular MSU deposits detected by DECT in patients with gout and controls.

Design, Setting, and Participants

This prospective Health Insurance Portability and Accountability Act-compliant study included patients with gout and controls who presented to a rheumatologic clinic from January 1, 2017, to November 1, 2018. All consecutive patients underwent DECT to assess coronary calcium score and MSU deposits in aorta and coronary arteries. In addition, cadavers were assessed by DECT for cardiovascular MSU deposits and verified by polarizing microscope. Analysis began in January 2017.

Main Outcomes and Measures

Detection rate of cardiovascular MSU deposits using DECT in patients with gout and control group patients without a previous history of gout or inflammatory rheumatic diseases.

Results

A total of 59 patients with gout (mean [SD] age, 59 [5.7] years; range, 47-89 years), 47 controls (mean [SD] age, 70 [10.4] years; range, 44-86 years), and 6 cadavers (mean [SD] age at death, 76 [17] years; range, 56-95 years) were analyzed. The frequency of cardiovascular MSU deposits was higher among patients with gout (51 [86.4%]) compared with controls (7 [14.9%]) (χ2 = 17.68, P < .001), as well as coronary MSU deposits among patients with gout (19 [32.2%]) vs controls (2 [4.3%]) (χ2 = 8.97, P = .003). Coronary calcium score was significantly higher among patients with gout (900 Agatston units [AU]; 95% CI, 589-1211) compared with controls (263 AU; 95% CI, 76-451; P = .001) and also significantly higher among 58 individuals with cardiovascular MSU deposits (950 AU; 95% CI, 639-1261) compared with 48 individuals without MSU deposits (217 AU; 95% CI, 37-397; P < .001). Among 6 cadavers, 3 showed cardiovascular MSU deposits, which were verified by polarizing light microscope.

Conclusion and Relevance

Dual-energy computed tomography demonstrates cardiovascular MSU deposits, as confirmed by polarized light microscopy. Cardiovascular MSU deposits were detected by DECT significantly more often in patients with gout compared with controls and were associated with higher coronary calcium score. This new modality may be of importance in gout population being at risk from cardiovascular disease.

Coronary computed tomography angiography using model-based iterative reconstruction algorithms in the detection of significant coronary stenosis: how the plaque type influences the diagnostic performance

Purpose

To evaluate the ability of coronary computed tomography angiography (CCTA) with model-based iterative reconstruction (MBIR) algorithm in detecting significant coronary artery stenosis compared with invasive coronary angiography (ICA).

Material and methods

We retrospectively identified 55 patients who underwent CCTA using the MBIR algorithm with evidence of at least one significant stenosis (≥ 50%) and an ICA within three months. Patients were stratified based on calcium score; stenoses were classified by type and by coronary segment involved. Dose-length-product was compared with the literature data obtained with previous reconstruction algorithms. Coronary artery stenosis was estimated on ICAs based on a qualitative method.

Results

CCTA data were confirmed by ICA in 89% of subjects, and in 73% and 94% of patients with CS < 400 and ≥ 400, respectively. ICA confirmed 81% of calcific stenoses, 91% of mixed, and 67% of soft plaques. Both the dose exposure of patients with prospective acquisition (34) and the exposure of the whole population were significantly lower than the standard of reference (p < 0.001 and p = 0.007).

Conclusions

CCTA with MBIR is valuable in detecting significant coronary artery stenosis with a solid reduction of radiation dose. Diagnostic performance was influenced by plaque composition, being lower compared with ICA for patients with lower CAC score and soft plaques; the visualisation of an intraluminal hypodensity could cause false positives, particularly in D1 and MO segments.

Diagnostic performance and image quality of iterative model-based reconstruction of coronary CT angiography using 100 kVp for heavily calcified coronary vessels

OBJECTIVES

To evaluate the diagnostic performance and image quality of an iterative model-based reconstruction (IMR) using a 100-kVp protocol for the assessment of heavily calcified coronary vessels, compared to those of filtered back projection (FBP) and hybrid iterative technique (iDose4), and also compared to those of IMR with standard 120 kVp protocol.

METHODS

Among patients with Agatston scores ≥ 400 who had undergone both coronary CT angiography (CCTA) and invasive coronary angiography (ICA), age- and sex-matched patients with body mass index < 30 were retrospectively enrolled from CCTA with low-kVp protocol (100 kVp, n = 30) and with standard-kVp protocol (120 kVp, n = 30). Image data were all reconstructed with FBP, iDose4, and IMR. In each dataset, the objective and subjective image quality, and diagnostic accuracy (> 50% in luminal reduction as compared with ICA) were assessed.

RESULTS

IMR showed better objective and subjective image quality than FBP and iDose4 in both 100 kVp and 120 kVp groups (all p < 0.05). IMR showed a significantly improved all diagnostic performance compared with FBP (p < 0.05). Compared with iDose4, IMR significantly improved positive predictive value (85.0% vs. 80.5%; p < 0.05). There was no significant difference in image quality and diagnostic performance using IMR between the 100 kVp and 120 kVp groups.

CONCLUSIONS

100 kVp IMR may be useful for the assessment of heavily calcified coronary vessels, providing better diagnostic performance than FBP or iDose4 at the same dose, while maintaining similar diagnostic accuracy to 120 kVp IMR.

Effect of a calcium deblooming algorithm on accuracy of coronary computed tomography angiography

BACKGROUND

Coronary artery calcification is a significant contributor to reduced accuracy of coronary computed tomographic angiography (CTA) in the assessment of coronary artery disease severity. The aim of the current study is to assess the impact of a prototype calcium deblooming algorithm on the diagnostic accuracy of CTA.

METHODS

40 patients referred for invasive catheter angiography underwent CTA and invasive catheter angiography. The CTA were reconstructed using a standard soft tissue kernel (CTA_STAND) and a deblooming algorithm (CTA_DEBLOOM). CTA studies were read with and without the deblooming algorithm blinded to the invasive coronary angiogram findings. Sensitivity, specificity, accuracy, positive predictive value and negative predictive value for the detection of stenosis ≥50% or ≥70% were evaluated using quantitative coronary angiography as the reference standard. Image quality was assessed using a 5-point scale, and the presence of image artifact recorded.

RESULTS

All studies were diagnostic with 548 segments available for evaluation. Image score was 3.64 ± 0.72 with CTA_DEBLOOM, versus 3.56 ± 0.72 with CTA_STAND (p = 0.38). CTA_DEBLOOM had significantly less calcium blooming artifact than CTA_STAND (12.5% vs. 47.5%, p = 0.001). Based on a 50% stenosis threshold for defining significant disease, the Sensitivity/Specificity/PPV/NPV/Accuracy were 65.9/84.9/27.6/96.6/83.4 for CTA_DEBLOOM and 75.0/81.9/26.6/97.4/81.4 for CTA_STAND using a ≥50% threshold. CTA_DEBLOOM specificity was significantly higher than CTA_STAND (84.9% vs. 81.5%, p = 0.03), with no difference between the algorithms in sensitivity (p = 0.22), or accuracy (p = 0.15). These results remained unchanged when a stenosis threshold of ≥70% was used. Interobserver agreement was fair with both techniques (CTA_DEBLOOM k = 0.38, CTA_STAND k = 0.37).

CONCLUSION

In this proof of concept study, coronary calcification deblooming using a prototype post-processing algorithm is feasible and reduces calcium blooming with an improvement of the specificity of the CTA exam.

Image reconstruction in cardiovascular CT: Part 2 - Iterative reconstruction; potential and pitfalls

The use of IR in CT previously has been prohibitively complicated and time consuming, however improvements in computer processing power now make it possible on almost all CT scanners. Due to its potential to allow scanning at lower doses, IR has received a lot of attention in the medical literature and has become a successful commercial product. Its use in cardiovascular CT has been driven in part due to concerns about radiation dose and image quality. This manuscript discusses the various vendor permutations of iterative reconstruction (IR) in detail and critically appraises the current clinical research available on the various IR techniques used in cardiovascular CT.

Texture analysis of myocardial infarction in CT: Comparison with visual analysis and impact of iterative reconstruction

OBJECTIVES

To compare texture analysis (TA) with subjective visual diagnosis of myocardial infarction (MI) in cardiac computed tomography (CT) and to evaluate the impact of iterative reconstruction (IR).

METHODS

Ten patients (4 women, mean age 68 ± 11 years) with confirmed chronic MI and 20 controls (8 women, mean age 52 ± 11 years) with no cardiac abnormality underwent contrast-enhanced cardiac CT with the same protocol. Images were reconstructed with filtered back projection (FBP) and with advanced modeled IR at strength levels 3-5. Subjective diagnosis of MI was made by three independent, blinded readers with different experience levels. Classification of MI was performed using machine learning-based decision tree models for the entire data set and after splitting into training and test data to avoid overfitting.

RESULTS

Subjective visual analysis for diagnosis of MI showed excellent intrareader (kappa: 0.93) but poor interreader agreement (kappa: 0.3), with variable performance at different image reconstructions. TA showed high performance for all image reconstructions (correct classifications: 94%-97%, areas under the curve: 0.94-0.99). After splitting into training and test data, overall lower performances were observed, with best results for IR at level 5 (correct classifications: 73%, area under the curve: 0.65).

CONCLUSIONS

As compared with subjective, nonreliable visual analysis of inexperienced readers, TA enables objective and reproducible diagnosis of chronic MI in cardiac CT with higher accuracy. IR has a considerable impact on both subjective and objective image analysis.

Effect of image reconstruction algorithms on volumetric and radiomic parameters of coronary plaques

BACKGROUND

Volumetric and radiomic analysis of atherosclerotic plaques on coronary CT angiography have been shown to predict high-risk plaque morphology and to predict patient outcomes. However, there is limited information whether image reconstruction algorithms and preprocessing steps (type of binning, number of bins used for discretization) may influence parameter values.

METHODS

We retrospectively identified 60 coronary lesions on coronary CT angiography (CTA). All images were reconstructed using filtered back projection (FBP), hybrid (HIR) and model-based (MIR) iterative reconstruction. Plaques were segmented manually on HIR images and copied to FBP and MIR images to ensure identical voxels were analyzed. Overall, 4 volumetric and 169 radiomic parameters were calculated. Intra-class correlation coefficient (ICC) was used to assess reproducibility between image reconstructions, while linear regression analysis was used to assess the effect of preprocessing steps done before calculating radiomic metrics.

RESULTS

All volumetric and radiomic metrics had ICC>0.90 except for first-order statistics: mode, harmonic mean, minimum (0.45, 0.76, 0.84; respectively) and gray level co-occurrence (GLCM) parameters: inverse difference sum and sum variance (0.01, 0.04; respectively). Among GLCM parameters 90% were significantly affected by the type of binning and 100% by the number of bins. In case of gray level run length matrix parameters 100% of metrics were affected by both preprocessing steps.

CONCLUSIONS

Volumetric and radiomic statistics are robust to image reconstruction algorithms. However, all radiomic variables were affected by preprocessing steps therefore, showing the need for standardization before being implemented into everyday clinical practice.

Blooming Artifact Reduction in Coronary Artery Calcification by A New De-blooming Algorithm: Initial Study

The aim of this study was to investigate the use of de-blooming algorithm in coronary CT angiography (CCTA) for optimal evaluation of calcified plaques. Calcified plaques were simulated on a coronary vessel phantom and a cardiac motion phantom. Two convolution kernels, standard (STND) and high-definition standard (HD STND), were used for imaging reconstruction. A dedicated de-blooming algorithm was used for imaging processing. We found a smaller bias towards measurement of stenosis using the de-blooming algorithm (STND: bias 24.6% vs 15.0%, range 10.2% to 39.0% vs 4.0% to 25.9%; HD STND: bias 17.9% vs 11.0%, range 8.9% to 30.6% vs 0.5% to 21.5%). With use of de-blooming algorithm, specificity for diagnosing significant stenosis increased from 45.8% to 75.0% (STND), from 62.5% to 83.3% (HD STND); while positive predictive value (PPV) increased from 69.8% to 83.3% (STND), from 76.9% to 88.2% (HD STND). In the patient group, reduction in calcification volume was 48.1 ± 10.3%, reduction in coronary diameter stenosis over calcified plaque was 52.4 ± 24.2%. Our results suggest that the novel de-blooming algorithm could effectively decrease the blooming artifacts caused by coronary calcified plaques, and consequently improve diagnostic accuracy of CCTA in assessing coronary stenosis.

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.