Influence of dose reduction and iterative reconstruction on CT calcium scores: a multi-manufacturer dynamic phantom study

Improved coronary calcium detection and quantification with low-dose full field-of-view photon-counting CT: a phantom study

OBJECTIVE

The aim of the current study was to systematically assess coronary artery calcium (CAC) detection and quantification for spectral photon-counting CT (SPCCT) in comparison to conventional CT and, in addition, to evaluate the possibility of radiation dose reduction.

METHODS

Routine clinical CAC CT protocols were used for data acquisition and reconstruction of two CAC containing cylindrical inserts which were positioned within an anthropomorphic thorax phantom. In addition, data was acquired at 50% lower radiation dose by reducing tube current, and slice thickness was decreased. Calcifications were considered detectable when three adjacent voxels exceeded the CAC scoring threshold of 130 Hounsfield units (HU). Quantification of CAC (as volume and mass score) was assessed by comparison with known physical quantities.

RESULTS

In comparison with CT, SPCCT detected 33% and 7% more calcifications for the small and large phantoms, respectively. At reduced radiation dose and reduced slice thickness, small phantom CAC detection increased by 108% and 150% for CT and SPCCT, respectively. For the large phantom size, noise levels interfered with CAC detection. Although comparable between CT and SPCCT, routine protocols CAC quantification showed large deviations (up to 134%) from physical CAC volume. At reduced radiation dose and slice thickness, physical volume overestimations decreased to 96% and 72% for CT and SPCCT, respectively. In comparison with volume scores, mass score deviations from physical quantities were smaller.

CONCLUSION

CAC detection on SPCCT is superior to CT, and was even preserved at a reduced radiation dose. Furthermore, SPCCT allows for improved physical volume estimation.

KEY POINTS

• In comparison with conventional CT, increased coronary artery calcium detection (up to 156%) for spectral photon-counting CT was found, even at 50% radiation dose reduction. • Spectral photon-counting CT can more accurately measure physical volumes than conventional CT, especially at reduced slice thickness and for high-density coronary artery calcium. • For both conventional and spectral photon-counting CT, reduced slice thickness reconstructions result in more accurate physical mass approximation.

Quantification of Calcium in Peripheral Arteries of the Lower Extremities: Comparison of Different CT Scanners and Scoring Platforms

OBJECTIVES

The aim of this study was to investigate the interscanner and interscoring platform variability of calcium quantification in peripheral arteries of the lower extremities.

MATERIALS AND METHODS

Twenty human fresh-frozen legs were scanned using 3 different computed tomography (CT) scanners. The radiation dose (CTDIvol) was kept similar for all scanners. The calcium scores (Agatston and volume scores) were quantified using 4 semiautomatic scoring platforms. Comparative analysis of the calcium scores between scanners and scoring platforms was performed by using the Friedman test; post hoc analysis was performed by using the Wilcoxon signed rank test with Bonferroni correction.

RESULTS

Sixteen legs had calcifications and were used for data analysis. Agatston and volume scores ranged from 12.1 to 6580 Agatston units and 18.2 to 5579 mm3. Calcium scores differed significantly between Philips IQon and Philips Brilliance 64 (Agatston: 19.5% [P = 0.001]; volume: 14.5% [P = 0.001]) and Siemens Somatom Force (Agatston: 18.1% [P = 0.001]; volume: 17.5% [P = 0.001]). The difference between Brilliance 64 and Somatom Force was smaller (Agatston: 5.6% [P = 0.778]; volume: 7.7% [P = 0.003]). With respect to the interscoring platform variability, OsiriX produced significantly different Agatston scores compared with the other 3 scoring platforms (OsiriX vs IntelliSpace: 14.8% [P = 0.001] vs Syngo CaScore: 13.9% [P = 0.001] vs iX viewer: 13.2% [P < 0.001]). For the volume score, the differences between all scoring platforms were small ranging from 2.9% to 4.0%. Post hoc analysis showed a significant difference between OsiriX and IntelliSpace (3.8% [P = 0.001]).

CONCLUSIONS

The use of different CT scanners resulted in notably different Agatston and volume scores, whereas the use of different scoring platforms resulted in limited variability especially for the volume score. In conclusion, the variability in calcium quantification was most evident between different CT scanners and for the Agatston score.

Classification of moving coronary calcified plaques based on motion artifacts using convolutional neural networks: a robotic simulating study on influential factors

BACKGROUND

Motion artifacts affect the images of coronary calcified plaques. This study utilized convolutional neural networks (CNNs) to classify the motion-contaminated images of moving coronary calcified plaques and to determine the influential factors for the classification performance.

METHODS

Two artificial coronary arteries containing four artificial plaques of different densities were placed on a robotic arm in an anthropomorphic thorax phantom. Each artery moved linearly at velocities ranging from 0 to 60 mm/s. CT examinations were performed with four state-of-the-art CT systems. All images were reconstructed with filtered back projection and at least three levels of iterative reconstruction. Each examination was performed at 100%, 80% and 40% radiation dose. Three deep CNN architectures were used for training the classification models. A five-fold cross-validation procedure was applied to validate the models.

RESULTS

The accuracy of the CNN classification was 90.2 ± 3.1%, 90.6 ± 3.5%, and 90.1 ± 3.2% for the artificial plaques using Inception v3, ResNet101 and DenseNet201 CNN architectures, respectively. In the multivariate analysis, higher density and increasing velocity were significantly associated with higher classification accuracy (all P < 0.001). The classification accuracy in all three CNN architectures was not affected by CT system, radiation dose or image reconstruction method (all P > 0.05).

CONCLUSIONS

The CNN achieved a high accuracy of 90% when classifying the motion-contaminated images into the actual category, regardless of different vendors, velocities, radiation doses, and reconstruction algorithms, which indicates the potential value of using a CNN to correct calcium scores.

Fully automated quantification method (FQM) of coronary calcium in an anthropomorphic phantom

Objective

Coronary artery calcium (CAC) score is a strong predictor for future adverse cardiovascular events. Anthropomorphic phantoms are often used for CAC studies on computed tomography (CT) to allow for evaluation or variation of scanning or reconstruction parameters within or across scanners against a reference standard. This often results in large number of datasets. Manual assessment of these large datasets is time consuming and cumbersome. Therefore, this study aimed to develop and validate a fully automated, open‐source quantification method (FQM) for coronary calcium in a standardized phantom.

Materials and Methods

A standard, commercially available anthropomorphic thorax phantom was used with an insert containing nine calcifications with different sizes and densities. To simulate two different patient sizes, an extension ring was used. Image data were acquired with four state‐of‐the‐art CT systems using routine CAC scoring acquisition protocols. For interscan variability, each acquisition was repeated five times with small translations and/or rotations. Vendor‐specific CAC scores (Agatston, volume, and mass) were calculated as reference scores using vendor‐specific software. Both the international standard CAC quantification methods as well as vendor‐specific adjustments were implemented in FQM. Reference and FQM scores were compared using Bland‐Altman analysis, intraclass correlation coefficients, risk reclassifications, and Cohen’s kappa. Also, robustness of FQM was assessed using varied acquisitions and reconstruction settings and validation on a dynamic phantom. Further, image quality metrics were implemented: noise power spectrum, task transfer function, and contrast‐ and signal‐to‐noise ratio among others. Results were validated using imQuest software.

Results

Three parameters in CAC scoring methods varied among the different vendor‐specific software packages: the Hounsfield unit (HU) threshold, the minimum area used to designate a group of voxels as calcium, and the usage of isotropic voxels for the volume score. The FQM was in high agreement with vendor‐specific scores and ICC’s (median [95% CI]) were excellent (1.000 [0.999‐1.000] to 1.000 [1.000‐1.000]). An excellent interplatform reliability of κ = 0.969 and κ = 0.973 was found. TTF results gave a maximum deviation of 3.8% and NPS results were comparable to imQuest.

Conclusions

We developed a fully automated, open‐source, robust method to quantify CAC on CT scans in a commercially available phantom. Also, the automated algorithm contains image quality assessment for fast comparison of differences in acquisition and reconstruction parameters.

Best practice for the nuclear medicine technologist in CT-based attenuation correction and calcium score for nuclear cardiology

The use of hybrid systems is increasingly growing in Europe and this is progressively important for the final result of diagnostic tests. As an integral part of the hybrid imaging system, computed tomography (CT) plays a crucial role in myocardial perfusion imaging diagnostics. Throughout Europe, a variety of equipment is available and also different university curricula of the nuclear medicine technologist are observed. Hence, the Technologist Committee of the European Association of Nuclear Medicine proposes to identify, through a bibliographic review, the recommendations for best practice in computed tomography applied to attenuation correction and calcium score in myocardial perfusion imaging, which courses in the set of knowledge, skills, and competencies for nuclear medicine technologists. This document aims at providing recommendations for CT acquisition protocols and CT image optimization in nuclear cardiology.

Aortic valve calcification scoring with computed tomography: impact of iterative reconstruction techniques

To investigate whether image reconstruction with iterative reconstruction (IR) affects aortic valve calcification (AVC) scoring and likelihood categorization of severe aortic stenosis (AS). In this IRB-approved retrospective study, we included 100 consecutive patients with AS (40 females; mean age 77 ± 10 years; age range: 36-99 years) undergoing CT prior to transcatheter aortic valve replacement. Non-enhanced, electrocardiography-gated CT of the heart was reconstructed with filtered back projection (FBP) and with advanced modeled IR at strength levels 1-5. AVC Agatston scores were calculated and gender-specific cut-off values for AS likelihood categorization were applied according to current European Society of Cardiology recommendations (from unlikely to very likely). Friedman test with post-hoc Bonferroni correction was applied to analyze interval- and ordinal-scaled data. Compared to FBP, each IR strength level produced significantly different AVC Agatston scores (p < 0.001-0.002). Median AVC Agatston score for image reconstruction with FBP was 2527 (IQR: 1711-3663) and decreased with increasing IR strength levels up to 2281 (IQR: 1471-3357) at strength level 5. Likelihood categorization of severe AS was significantly different among image reconstruction algorithms (p < 0.001). Image reconstruction with IR strength level 5 led to a downward shift of likelihood categorization in 28 patients (28%) compared to images reconstructed with FBP. IR significantly impacts AVC scoring with significantly decreasing AVC scores with increasing IR strength levels. This leads to relevant changes in likelihood categorization of patients with severe AS., leading to underestimation of severe AS.

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

PURPOSE

This work investigated the simultaneous influence of tube voltage, tube current, body size, and HU threshold on calcium scoring reconstructed at 0.5-mm slice thickness using iterative reconstruction (IR) through multivariate analysis. Regression results were used to optimize the HU threshold to calibrate the resulting Agatston scores to be consistent with those obtained from the conventional protocol.

METHODS

A thorax phantom set simulating three different body sizes was used in this study. A total of 14 coronary artery calcium (CAC) protocols were studied, including 1 conventional protocol reconstructed at 3-mm slice thickness, 1 FBP protocol, and 12 statistical IR protocols (3 kVp values*4 SD values) reconstructed at 0.5-mm slice thickness. Three HU thresholds were applied for calcium identification, including 130, 150, and 170 HU. A multiple linear regression method was used to analyze the impact of kVp, SD, body size, and HU threshold on the Agatston scores of three calcification densities for IR-reconstructed CAC scans acquired with 0.5-mm slice thickness.

RESULTS

Each regression relationship has R² larger than 0.80, indicating a good fit to the data. Based on the regression models, the HU thresholds as a function of SD estimated to ensure the quantification accuracy of calcium scores for 120-, 100-, and 80-kVp CAC scans reconstructed at 0.5-mm slice thickness using IR for three different body sizes were proposed. Our results indicate that the HU threshold should be adjusted according to the imaging condition, whereas a 130-HU threshold is appropriate for 120-kVp CAC scans acquired with SD = 55 for body size of 24.5 cm.

CONCLUSION

The optimized HU thresholds were proposed for CAC scans reconstructed at 0.5-mm slice thickness using IR. Our study results may provide a potential strategy to improve the reliability of calcium scoring by reducing partial volume effect while keeping radiation dose as low as reasonably achievable.

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.

High-pitch versus sequential mode for coronary calcium in individuals with a high heart rate: Potential for dose reduction

BACKGROUND

To determine the impact of high-pitch spiral acquisition on radiation dose and cardiovascular disease (CVD) risk stratification by coronary artery calcium (CAC) assessment with computed tomography in individuals with a high heart rate.

METHODS

Of the ROBINSCA trial, 1990 participants with regular rhythm and heart rates >65 beats per minute (bpm) were included. As reference, 390 participants with regular heart rates ≤65 bpm were used. All participants underwent prospectively electrocardiographically(ECG)-triggered imaging of the coronary arteries using dual source CT at 120 kVp, 80 ref mAs using both high-pitch spiral mode and sequential mode. Radiation dose, Agatston score, number of positive scores, as well as median absolute difference of the Agatston score were determined and participants were stratified into CVD risk categories.

RESULTS

A similar percentage of participants with low heart rates and high heart rates had a positive CAC score in data sets acquired in high-pitch spiral (low heart rate: 57.7%, high heart rate: 55.8%) and sequential mode (58.0%, 54.7%, p = n.s.). The median absolute difference in Agatston scores between acquisition modes was 14.2% and 9.2%, for the high and low heart rate groups, respectively. Excellent agreement for risk categorization between the two data acquisition modes was found for the high (κ = 0.927) and low (κ = 0.946) heart rate groups. Radiation dose was 48% lower for high-pitch spiral versus sequential acquisitions.

CONCLUSION

Radiation dose for the quantification of coronary calcium can be reduced by 48% when using the high-pitch spiral acquisition mode compared to the sequential mode in participants with a regular high heart rate. CVD risk stratification agreement between the two modes of data acquisition is excellent.

Generative Adversarial Networks for Noise Reduction in Low-Dose CT

Noise is inherent to low-dose CT acquisition. We propose to train a convolutional neural network (CNN) jointly with an adversarial CNN to estimate routine-dose CT images from low-dose CT images and hence reduce noise. A generator CNN was trained to transform low-dose CT images into routine-dose CT images using voxelwise loss minimization. An adversarial discriminator CNN was simultaneously trained to distinguish the output of the generator from routine-dose CT images. The performance of this discriminator was used as an adversarial loss for the generator. Experiments were performed using CT images of an anthropomorphic phantom containing calcium inserts, as well as patient non-contrast-enhanced cardiac CT images. The phantom and patients were scanned at 20% and 100% routine clinical dose. Three training strategies were compared: the first used only voxelwise loss, the second combined voxelwise loss and adversarial loss, and the third used only adversarial loss. The results showed that training with only voxelwise loss resulted in the highest peak signal-to-noise ratio with respect to reference routine-dose images. However, CNNs trained with adversarial loss captured image statistics of routine-dose images better. Noise reduction improved quantification of low-density calcified inserts in phantom CT images and allowed coronary calcium scoring in low-dose patient CT images with high noise levels. Testing took less than 10 s per CT volume. CNN-based low-dose CT noise reduction in the image domain is feasible. Training with an adversarial network improves the CNNs ability to generate images with an appearance similar to that of reference routine-dose CT images.