Optimization of HU threshold for coronary artery calcium scans reconstructed at 0.5-mm slice thickness using iterative reconstruction

Coronary artery calcium scoring assessment in ultra-low-dose chest computed tomography

OBJECTIVES

To investigate the effect of non-electrocardiogram (ECG) -triggered ultra-low-dose CT (ULD-CT) with different reconstruction protocols on coronary artery calcium (CAC) scoring assessment, compared with ECG-triggered CAC CT (CAC-CT).

METHODS

This prospective study included 115 patients who underwent CAC-CT and ULD-CT scans under the same topogram images. CAC-CT adopted a prospective ECG-triggered sequential acquisition with a tube potential of 120 kV, and the reconstruction protocol was standard Qr36 + slice 3 mm (CACQr-3mm group). ULD-CT adopted a non-ECG-triggered high-pitch acquisition with a tube potential of Sn100 kV, and four groups of images (named ULDQr-3mm, ULDSa-3mm, ULDQr-1.5mm, and ULDSa-1.5mm) were reconstructed using different reconstruction algorithms (standard Qr36, kV-independent Sa36) and slice thicknesses (3 mm, 1.5 mm). The accuracy of CAC detection by ULD-CT was calculated. The agreement of the CAC score between ULD-CT and CAC-CT scans was assessed using intraclass correlation coefficients (ICC) and Bland-Altman plot, and the agreement of risk categorization was assessed using weighted kappa.

RESULTS

The sensitivity and specificity of the ULDSa-1.5mm group for detecting positive CAC were 100% and 97.4%, respectively (k = 0.980). The CAC score for the ULDSa-3mm and ULDSa-1.5mm groups demonstrated excellent agreement with the CACQr-3mm group (ICC = 0.992, 0.990, respectively), with a mean difference of -12.3 and - 12.4. The agreement of risk categorization based on absolute and percentile CAC score between the ULDSa-1.5mm and CACQr-3mm groups was excellent (weighted k = 0.954, 0.983, respectively), and risk reclassification rates were low (3.5%, 2.8%, respectively). The effective dose was reduced by approximately 77.2% for the ULD-CT compared to the CAC-CT (0.18 mSv vs. 0.79 mSv, p < 0.001).

CONCLUSION

Reconstruction with a 1.5-mm slice thickness and kV-independent iterative algorithmic protocol in ULD-CT yielded excellent agreement in CAC score quantification and risk categorization compared with ECG-triggered CAC-CT.

Coronary artery calcium mass measurement based on integrated intensity and volume fraction techniques

Purpose

Agatston scoring does not detect all the calcium present in computed tomography scans of the heart. A technique that removes the need for thresholding and quantifies calcium mass more accurately and reproducibly is needed.

Approach

Integrated intensity and volume fraction techniques were evaluated for accurate quantification of calcium mass. Integrated intensity calcium mass, volume fraction calcium mass, Agatston scoring, and spatially weighted calcium scoring were compared with known calcium mass in simulated and physical phantoms. The simulation was created to match a 320-slice CT scanner. Fat rings were added to the simulated phantoms, which resulted in small (30 × 20    cm 2 ), medium (35 × 25    cm 2 ), and large (40 × 30    cm 2 ) phantoms. Three calcification inserts of different diameters and hydroxyapatite densities were placed within the phantoms. All the calcium mass measurements were repeated across different beam energies, patient sizes, insert sizes, and densities. Physical phantom images from a previously reported study were then used to evaluate the accuracy and reproducibility of the techniques.

Results

Both integrated intensity calcium mass and volume fraction calcium mass yielded lower root mean squared error (RMSE) and deviation (RMSD) values than Agatston scoring in all the measurements in the simulated phantoms. Specifically, integrated calcium mass (RMSE: 0.49 mg, RMSD: 0.49 mg) and volume fraction calcium mass (RMSE: 0.58 mg, RMSD: 0.57 mg) were more accurate for the low-density stationary calcium measurements than Agatston scoring (RMSE: 3.70 mg, RMSD: 2.30 mg). Similarly, integrated calcium mass (15.74%) and volume fraction calcium mass (20.37%) had fewer false-negative (CAC = 0) measurements than Agatston scoring (75.00%) and spatially weighted calcium scoring (26.85%), on the low-density stationary calcium measurements.

Conclusion

The integrated calcium mass and volume fraction calcium mass techniques can potentially improve risk stratification for patients undergoing calcium scoring and further improve risk assessment compared with Agatston scoring.

Evolving Role of Calcium Density in Coronary Artery Calcium Scoring and Atherosclerotic Cardiovascular Disease Risk

Coronary artery calcium (CAC) is a specific marker of coronary atherosclerosis that can be used to measure calcified subclinical atherosclerotic burden. The Agatston method is the most widely used scoring algorithm for quantifying CAC and is expressed as the product of total calcium area and a quantized peak calcium density weighting factor defined by the calcification attenuation in HU on noncontrast computed tomography. Calcium density has emerged as an important area of inquiry because the Agatston score is upweighted based on the assumption that peak calcium density and atherosclerotic cardiovascular disease (ASCVD) risk are positively correlated. However, recent evidence demonstrates that calcium density is inversely associated with lesion vulnerability and ASCVD risk in population-based cohorts when accounting for age and plaque area. Here, we review calcium density by focusing on 3 main areas: 1) CAC scan acquisition parameters; 2) pathophysiology of calcified plaques; and 3) epidemiologic evidence relating calcium density to ASCVD outcomes. Through this process, we hope to provide further insight into the evolution of CAC scoring on noncontrast computed tomography.

Relationship Between Coronary Artery Calcium and Atherosclerosis Progression Among Patients With Suspected Coronary Artery Disease

BACKGROUND

Among symptomatic patients, it remains unclear whether a coronary artery calcium (CAC) score alone is sufficient or misses a sizeable burden and progressive risk associated with obstructive and nonobstructive atherosclerotic plaque.

OBJECTIVES

Among patients with low to high CAC scores, our aims were to quantify co-occurring obstructive and nonobstructive noncalcified plaque and serial progression of atherosclerotic plaque volume.

METHODS

A total of 698 symptomatic patients with suspected coronary artery disease (CAD) underwent serial coronary computed tomographic angiography (CTA) performed 3.5 to 4.0 years apart. Atherosclerotic plaque was quantified, including by compositional subgroups. Obstructive CAD was defined as ≥50% stenosis. Multivariate linear regression models were used to measure atherosclerotic plaque progression by CAC scores. Cox proportional hazard models estimated CAD event risk (median of 10.7 years of follow-up).

RESULTS

Across baseline CAC scores from 0 to ≥400, total plaque volume ranged from 30.4 to 522.4 mm³ (P < 0.001) and the prevalence of obstructive CAD increased from 1.4% to 49.1% (P < 0.001). Of those with a 0 CAC score, 97.9% of total plaque was noncalcified. Among patients with baseline CAC <100, nonobstructive CAD was prevalent (40% and 89% in CAC scores of 0 and 1-99), with plaque largely being noncalcified. On the follow-up coronary CTA, volumetric plaque growth (P < 0.001) and the development of new or worsening stenosis (P < 0.001) occurred more among patients with baseline CAC ≥100. Progression varied compositionally by baseline CAC scores. Patients with no CAC had disproportionate growth in noncalcified plaque, and for every 1 mm³ increase in calcified plaque, there was a 5.5 mm³ increase in noncalcified plaque volume. By comparison, patients with CAC scores of ≥400 exhibited disproportionate growth in calcified plaque with a volumetric increase 15.7-fold that of noncalcified plaque. There was a graded increase in CAD event risk by the CAC with rates from 3.3% for no CAC to 21.9% for CAC ≥400 (P < 0.001).

CONCLUSIONS

CAC imperfectly characterizes atherosclerotic disease burden, but its subgroups exhibit pathogenic patterns of early to advanced disease progression and stratify long-term prognostic risk.

An Analytic Method for Calculating Scanner-, Kilovoltage Peak-, and Patient Size-Specific Hounsfield Unit Scale Thresholds for Agatston Score

OBJECTIVE

This study aimed to calculate scanner-, kilovoltage peak (kVp)-, and patient size-specific computed tomography (CT) number thresholds for determining Agatston score (AgSc).

METHODS

The proposed method was validated using calcium measurements in an anthropomorphic phantom for 4 CT scanners made by 4 vendors. The derived mass concentration (γ) thresholds were used to calculate kVp- and patient size-specific CT number thresholds. Two models were applied to reduce intrascanner and interscanner AgSc variation, respectively.

RESULTS

The mean error of the modeled CT numbers is 1.8% (0.1%-4.4%). Model 1 has comparable results to the published phantom calibration method for an average-size patient (error, 1.5%; 0.1%-5.1%). The size- and the kVp-dependent fitting of modeled results have R2 greater than 0.965.

CONCLUSIONS

Our results show a potential to enable accurate determination of AgSc under diverse conditions (eg, reduced tube potential) and are more easily applicable to different patient sizes than the phantom calibration method.

Coronary Artery Calcium Scoring: Toward a New Standard

OBJECTIVES

Although the Agatston score is a commonly used quantification method, rescan reproducibility is suboptimal, and different CT scanners result in different scores. In 2007, McCollough et al (Radiology 2007;243:527-538) proposed a standard for coronary artery calcium quantification. Advancements in CT technology over the last decade, however, allow for improved acquisition and reconstruction methods. This study aims to investigate the feasibility of a reproducible reduced dose alternative of the standardized approach for coronary artery calcium quantification on state-of-the-art CT systems from 4 major vendors.

MATERIALS AND METHODS

An anthropomorphic phantom containing 9 calcifications and 2 extension rings were used. Images were acquired with 4 state-of-the-art CT systems using routine protocols and a variety of tube voltages (80-120 kV), tube currents (100% to 25% dose levels), slice thicknesses (3/2.5 and 1/1.25 mm), and reconstruction techniques (filtered back projection and iterative reconstruction). Every protocol was scanned 5 times after repositioning the phantom to assess reproducibility. Calcifications were quantified as Agatston scores.

RESULTS

Reducing tube voltage to 100 kV, dose to 75%, and slice thickness to 1 or 1.25 mm combined with higher iterative reconstruction levels resulted in an on average 36% lower intrascanner variability (interquartile range) compared with the standard 120 kV protocol. Interscanner variability per phantom size decreased by 34% on average. With the standard protocol, on average, 6.2 ± 0.4 calcifications were detected, whereas 7.0 ± 0.4 were detected with the proposed protocol. Pairwise comparisons of Agatston scores between scanners within the same phantom size demonstrated 3 significantly different comparisons at the standard protocol (P < 0.05), whereas no significantly different comparisons arose at the proposed protocol (P > 0.05).

CONCLUSIONS

On state-of-the-art CT systems of 4 different vendors, a 25% reduced dose, thin-slice calcium scoring protocol led to improved intrascanner and interscanner reproducibility and increased detectability of small and low-density calcifications in this phantom. The protocol should be extensively validated before clinical use, but it could potentially improve clinical interscanner/interinstitutional reproducibility and enable more consistent risk assessment and treatment strategies.

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.

Modified Contrast-Detail Phantom for Determination of the CT Scanners Abilities for Low-Contrast Detection

Computerised tomography (CT) continues to be a corner stone medical and radiologic imaging modalities in radiology and radiotherapy departments. Its importance lies in its efficiency in low contrast detectability (LCD). The assessment of such capabilities requires rigorous image quality analysis using special designed phantoms with different densities as well as variation in atomic mass numbers (A) of the material. Absence of such ranges of densities and atomic mass numbers, limits the dynamic range of assessment. An example is Catphan phantom which represents only three subject contrast levels 0.3, 0.5 and 1 per cent. This project aims to present a phantom with extended range of available subject contrast to include very low-level values and to increase its dynamic scale. With this design, a relatively large number of different contrast objects (holes) can be presented for imaging by a CT scanner to assess its LCD ability. We shall thus introduce another LCD phantom to complement the existing ones, such as Catphan. The cylindrical phantom is constructed using Poly (methyl methacrylate) (PMMA), with craters (holes) having dimensions that gradually increase from 1.0 to 12.5 mm penetrated in configuration that extend from the centre to the corner. Each line of the drilled holes in the phantom is filled with contrast material of specific concentrations. As opposed to the phantom of low detail contrast used in planar imaging, the iodine (contrast material) in this phantom replaces the depth of the phantom holes. The iodine could be reduced to 0.2 l milli-Molar (mM) and can be varied for the next line of holes by a small increment depending on the required level of contrast detectability assessment required.

Machine Learning and Coronary Artery Calcium Scoring

PURPOSE OF REVIEW

To summarize current artificial intelligence (AI)-based applications for coronary artery calcium scoring (CACS) and their potential clinical impact.

RECENT FINDINGS

Recent evolution of AI-based technologies in medical imaging has accelerated progress in CACS performed in diverse types of CT examinations, providing promising results for future clinical application in this field. CACS plays a key role in risk stratification of coronary artery disease (CAD) and patient management. Recent emergence of AI algorithms, particularly deep learning (DL)-based applications, have provided considerable progress in CACS. Many investigations have focused on the clinical role of DL models in CACS and showed excellent agreement between those algorithms and manual scoring, not only in dedicated coronary calcium CT but also in coronary CT angiography (CCTA), low-dose chest CT, and standard chest CT. Therefore, the potential of AI-based CACS may become more influential in the future.