Denoising Multiphase Functional Cardiac CT Angiography Using Deep Learning and Synthetic Data

Coronary CT angiography is increasingly used for cardiac diagnosis. Dose modulation techniques can reduce radiation dose, but resulting functional images are noisy and challenging for functional analysis. This retrospective study describes and evaluates a deep learning method for denoising functional cardiac imaging, taking advantage of multiphase information in a three-dimensional convolutional neural network. Coronary CT angiograms (n = 566) were used to derive synthetic data for training. Deep learning-based image denoising was compared with unprocessed images and a standard noise reduction algorithm (block-matching and three-dimensional filtering [BM3D]). Noise and signal-to-noise ratio measurements, as well as expert evaluation of image quality, were performed. To validate the use of the denoised images for cardiac quantification, threshold-based segmentation was performed, and results were compared with manual measurements on unprocessed images. Deep learning-based denoised images showed significantly improved noise compared with standard denoising-based images (SD of left ventricular blood pool, 20.3 HU ± 42.5 [SD] vs 33.4 HU ± 39.8 for deep learning-based image denoising vs BM3D; P < .0001). Expert evaluations of image quality were significantly higher in deep learning-based denoised images compared with standard denoising. Semiautomatic left ventricular size measurements on deep learning-based denoised images showed excellent correlation with expert quantification on unprocessed images (intraclass correlation coefficient, 0.97). Deep learning-based denoising using a three-dimensional approach resulted in excellent denoising performance and facilitated valid automatic processing of cardiac functional imaging. Keywords: Cardiac CT Angiography, Deep Learning, Image Denoising Supplemental material is available for this article. © RSNA, 2024.

Reduced Pulmonary Artery Distensibility Predicts Persistent Pulmonary Hypertension and 2-Year Mortality in Patients with Severe Aortic Stenosis Undergoing TAVR

RATIONALE AND OBJECTIVES

Post-TAVR persistent pulmonary hypertension (PH) is a better predictor of poor outcome than pre-TAVR PH. In this longitudinal study we sought to evaluate whether pulmonary artery (distensibility (DPA) measured on preprocedural ECG-gated CTA is associated with persistent-PH and 2-year mortality after TAVR.

MATERIALS AND METHODS

Three hundred and thirty-six patients undergoing TAVR between July 2012 and March 2016 were retrospectively included and followed for all-cause mortality until November 2017. All patients underwent retrospectively ECG-gated CTA prior to TAVR. Main pulmonary artery (MPA) area was measured in systole and in diastole. DPA was calculated as: [(area-MPAmax-area-MPAmin)/area-MPAmax]%. ROC analysis was performed to assess the AUC for persistent-PH. Youden Index was used to determine the optimal threshold of DPA for persistent-PH. Two groups were compared based on a DPA threshold of 8% (specificity of 70% for persistent-PH). Kaplan-Meier, Cox proportional-hazard, and logistic regression analyses were performed. The primary clinical endpoint was defined as persistent-PH post-TAVR. The secondary endpoint was defined as all-cause mortality 2 years after TAVR.

RESULTS

Median follow-up time was 413 (interquartiles 339-757) days. A total of 183 (54%) had persistent-PH and 68 (20%) patients died within 2-years after TAVR. Patients with DPA<8% had significantly more persistent-PH (67% vs 47%, p<0.001) and 2-year deaths (28% vs 15%, p=0.006), compared to patients with DPA>8%. Adjusted multivariable regression analyses showed that DPA<8% was independently associated with persistent-PH (OR 2.10 [95%-CI 1.3-4.5], p=0.007) and 2-year mortality (HR 2.91 [95%-CI 1.5-5.8], p=0.002). Kaplan-Meier analysis showed that 2-year mortality of patients with DPA<8% was significantly higher compared to patients with DPA≥8% (mortality 28% vs 15%; log-rank p=0.003).

CONCLUSION

DPA on preprocedural CTA is independently associated with persistent-PH and two-year mortality in patients who undergo TAVR.

Vendor Independent Coronary Calcium Scoring Improves Individual Risk Assessment: MESA (Multi-Ethnic Study of Atherosclerosis)

BACKGROUND

Substantial variation in Agatston scores (AS) acquired with different computed tomography (CT) scanners may influence patient risk classification.

OBJECTIVES

This study sought to develop a calibration tool for state-of-the-art CT systems resulting in vendor-neutral AS (vnAS), and to assess the impact of vnAS on coronary heart disease (CHD) event prediction.

METHODS

The vnAS calibration tool was derived by imaging 2 anthropomorphic calcium containing phantoms on 7 different CT and 1 electron beam tomography system, which was used as the reference system. The effect of vnAS on CHD event prediction was analyzed with data from 3,181 participants from MESA (Multi-Ethnic Study on Atherosclerosis). Chi-square analysis was used to compare CHD event rates between low (vnAS <100) and high calcium groups (vnAS ≥100). Multivariable Cox proportional hazard regression models were used to assess the incremental value of vnAS.

RESULTS

For all CT systems, a strong correlation with electron beam tomography-AS was found (R2 >0.932). Of the MESA participants originally in the low calcium group (n = 781), 85 (11%) participants were reclassified to a higher risk category based on the recalculated vnAS. For reclassified participants, the CHD event rate of 15% was significantly higher compared with participants in the low calcium group (7%; P = 0.008) with a CHD HR of 3.39 (95% CI: 1.82-6.35; P = 0.001).

CONCLUSIONS

The authors developed a calibration tool that enables calculation of a vnAS. MESA participants who were reclassified to a higher calcium category by means of the vnAS experienced more CHD events, indicating improved risk categorization.

Automated cross-sectional view selection in CT angiography of aortic dissections with uncertainty awareness and retrospective clinical annotations

Surveillance imaging of patients with chronic aortic diseases, such as aneurysms and dissections, relies on obtaining and comparing cross-sectional diameter measurements along the aorta at predefined aortic landmarks, over time. The orientation of the cross-sectional measuring planes at each landmark is currently defined manually by highly trained operators. Centerline-based approaches are unreliable in patients with chronic aortic dissection, because of the asymmetric flow channels, differences in contrast opacification, and presence of mural thrombus, making centerline computations or measurements difficult to generate and reproduce. In this work, we present three alternative approaches - INS, MCDS, MCDbS - based on convolutional neural networks and uncertainty quantification methods to predict the orientation (ϕ,θ) of such cross-sectional planes. For the monitoring of chronic aortic dissections, we show how a dataset of 162 CTA volumes with overall 3273 imperfect manual annotations routinely collected in a clinic can be efficiently used to accomplish this task, despite the presence of non-negligible interoperator variabilities in terms of mean absolute error (MAE) and 95% limits of agreement (LOA). We show how, despite the large limits of agreement in the training data, the trained model provides faster and more reproducible results than either an expert user or a centerline method. The remaining disagreement lies within the variability produced by three independent expert annotators and matches the current state of the art, providing a similar error, but in a fraction of the time.

Robustness of pulmonary nodule radiomic features on computed tomography as a function of varying radiation dose levels-a multi-dose in vivo patient study

OBJECTIVE

Analysis of textural features of pulmonary nodules in chest CT, also known as radiomics, has several potential clinical applications, such as diagnosis, prognostication, and treatment response monitoring. For clinical use, it is essential that these features provide robust measurements. Studies with phantoms and simulated lower dose levels have demonstrated that radiomic features can vary with different radiation dose levels. This study presents an in vivo stability analysis of radiomic features for pulmonary nodules against varying radiation dose levels.

METHODS

Nineteen patients with a total of thirty-five pulmonary nodules underwent four chest CT scans at different radiation dose levels (60, 33, 24, and 15 mAs) in a single session. The nodules were manually delineated. To assess the robustness of features, we calculated the intra-class correlation coefficient (ICC). To visualize the effect of milliampere-second variation on groups of features, a linear model was fitted to each feature. We calculated bias and calculated the R2 value as a measure of goodness of fit.

RESULTS

A small minority of 15/100 (15%) radiomic features were considered stable (ICC > 0.9). Bias increased and R2 decreased at lower dose, but shape features seemed to be more robust to milliampere-second variations than other feature classes.

CONCLUSION

A large majority of pulmonary nodule radiomic features were not inherently robust to radiation dose level variations. For a subset of features, it was possible to correct this variability by a simple linear model. However, the correction became increasingly less accurate at lower radiation dose levels.

CLINICAL RELEVANCE STATEMENT

Radiomic features provide a quantitative description of a tumor based on medical imaging such as computed tomography (CT). These features are potentially useful in several clinical tasks such as diagnosis, prognosis prediction, treatment effect monitoring, and treatment effect estimation.

KEY POINTS

• The vast majority of commonly used radiomic features are strongly influenced by variations in radiation dose level. • A small minority of radiomic features, notably the shape feature class, are robust against dose-level variations according to ICC calculations. • A large subset of radiomic features can be corrected by a linear model taking into account only the radiation dose level.

Characterizing the Heart and the Myocardium With Photon-Counting CT

ABSTRACT

Noninvasive cardiac imaging has rapidly evolved during the last decade owing to improvements in computed tomography (CT)-based technologies, among which we highlight the recent introduction of the first clinical photon-counting detector CT (PCD-CT) system. Multiple advantages of PCD-CT have been demonstrated, including increased spatial resolution, decreased electronic noise, and reduced radiation exposure, which may further improve diagnostics and may potentially impact existing management pathways. The benefits that can be obtained from the initial experiences with PCD-CT are promising. The implementation of this technology in cardiovascular imaging allows for the quantification of coronary calcium, myocardial extracellular volume, myocardial radiomics features, epicardial and pericoronary adipose tissue, and the qualitative assessment of coronary plaques and stents. This review aims to discuss these major applications of PCD-CT with a focus on cardiac and myocardial characterization.

Radiation Dose Reduction for Coronary Artery Calcium Scoring Using a Virtual Noniodine Algorithm on Photon-Counting Detector Computed-Tomography Phantom Data

Background: On the basis of the hypothesis that virtual noniodine (VNI)-based coronary artery calcium scoring (CACS) is feasible at reduced radiation doses, this study assesses the impact of radiation dose reduction on the accuracy of this VNI algorithm on a photon-counting detector (PCD)-CT. Methods: In a systematic in vitro setting, a phantom for CACS simulating three chest sizes was scanned on a clinical PCD-CT. The standard radiation dose was chosen at volumetric CT dose indices (CTDI_Vol) of 1.5, 3.3, 7.0 mGy for small, medium-sized, and large phantoms, and was gradually reduced by adjusting the tube current resulting in 100, 75, 50, and 25%, respectively. VNI images were reconstructed at 55 keV, quantum iterative reconstruction (QIR)1, and at 60 keV/QIR4, and evaluated regarding image quality (image noise (IN), contrast-to-noise ratio (CNR)), and CACS. All VNI results were compared to true noncontrast (TNC)-based CACS at 70 keV and standard radiation dose (reference). Results: IN_TNC was significantly higher than IN_VNI, and IN_VNI at 55 keV/QIR1 higher than at 60 keV/QIR4 (100% dose: 16.7 ± 1.9 vs. 12.8 ± 1.7 vs. 7.7 ± 0.9; p < 0.001 for every radiation dose). CNR_TNC was higher than CNR_VNI, but it was better to use 60 keV/QIR4 (p < 0.001). CACS_VNI showed strong correlation and agreement at every radiation dose (p < 0.001, r > 0.9, intraclass correlation coefficient > 0.9). The coefficients of the variation in root-mean squared error were less than 10% and thus clinically nonrelevant for the CACS_VNI of every radiation dose. Conclusion: This phantom study suggests that CACS_VNI is feasible on PCD-CT, even at reduced radiation dose while maintaining image quality and CACS accuracy.

Deep Learning Image Reconstruction for CT: Technical Principles and Clinical Prospects

Filtered back projection (FBP) has been the standard CT image reconstruction method for 4 decades. A simple, fast, and reliable technique, FBP has delivered high-quality images in several clinical applications. However, with faster and more advanced CT scanners, FBP has become increasingly obsolete. Higher image noise and more artifacts are especially noticeable in lower-dose CT imaging using FBP. This performance gap was partly addressed by model-based iterative reconstruction (MBIR). Yet, its "plastic" image appearance and long reconstruction times have limited widespread application. Hybrid iterative reconstruction partially addressed these limitations by blending FBP with MBIR and is currently the state-of-the-art reconstruction technique. In the past 5 years, deep learning reconstruction (DLR) techniques have become increasingly popular. DLR uses artificial intelligence to reconstruct high-quality images from lower-dose CT faster than MBIR. However, the performance of DLR algorithms relies on the quality of data used for model training. Higher-quality training data will become available with photon-counting CT scanners. At the same time, spectral data would greatly benefit from the computational abilities of DLR. This review presents an overview of the principles, technical approaches, and clinical applications of DLR, including metal artifact reduction algorithms. In addition, emerging applications and prospects are discussed.

Intra-individual comparison of coronary calcium scoring between photon counting detector- and energy integrating detector-CT: Effects on risk reclassification

Purpose

To compare coronary artery calcium volume and score (CACS) between photon-counting detector (PCD) and conventional energy integrating detector (EID) computed tomography (CT) in a phantom and prospective patient study.

Methods

A commercially available CACS phantom was scanned with a standard CACS protocol (120 kVp, slice thickness/increment 3/1.5 mm, and a quantitative Qr36 kernel), with filtered back projection on the EID-CT, and with monoenergetic reconstruction at 70 keV and quantum iterative reconstruction off on the PCD-CT. The same settings were used to prospectively acquire data in patients (n = 23, 65 ± 12.1 years), who underwent PCD- and EID-CT scans with a median of 5.5 (3.0-12.5) days between the two scans in the period from August 2021 to March 2022. CACS was quantified using a commercially available software solution. A regression formula was obtained from the aforementioned comparison and applied to simulate risk reclassification in a pre-existing cohort of 514 patients who underwent a cardiac EID-CT between January and December 2021.

Results

Based on the phantom experiment, CACS _PCD-CT showed a more accurate measurement of the reference CAC volumes (overestimation of physical volumes: PCD-CT 66.1 ± 1.6% vs. EID-CT: 77.2 ± 0.5%). CACS _EID-CT and CACS _PCD-CT were strongly correlated, however, the latter measured significantly lower values in the phantom (CACS _PCD-CT : 60.5 (30.2-170.3) vs CACS _EID-CT 74.7 (34.6-180.8), p = 0.0015, r = 0.99, mean bias -9.7, Limits of Agreement (LoA) -36.6/17.3) and in patients (non-significant) (CACS _PCD-CT : 174.3 (11.1-872.7) vs CACS _EID-CT 218.2 (18.5-876.4), p = 0.10, r = 0.94, mean bias -41.1, LoA -315.3/232.5). The systematic lower measurements of Agatston score on PCD-CT system led to reclassification of 5.25% of our simulated patient cohort to a lower classification class.

Conclusion

CACS _PCD-CT is feasible and correlates strongly with CACS _EID-CT , however, leads to lower CACS values. PCD-CT may provide results that are more accurate for CACS than EID-CT.

Registry of Aortic Diseases to Model Adverse Events and Progression (ROADMAP) in Uncomplicated Type B Aortic Dissection: Study Design and Rationale

Purpose

To describe the design and methodological approach of a multicenter, retrospective study to externally validate a clinical and imaging-based model for predicting the risk of late adverse events in patients with initially uncomplicated type B aortic dissection (uTBAD).

Materials and Methods

The Registry of Aortic Diseases to Model Adverse Events and Progression (ROADMAP) is a collaboration between 10 academic aortic centers in North America and Europe. Two centers have previously developed and internally validated a recently developed risk prediction model. Clinical and imaging data from eight ROADMAP centers will be used for external validation. Patients with uTBAD who survived the initial hospitalization between January 1, 2001, and December 31, 2013, with follow-up until 2020, will be retrospectively identified. Clinical and imaging data from the index hospitalization and all follow-up encounters will be collected at each center and transferred to the coordinating center for analysis. Baseline and follow-up CT scans will be evaluated by cardiovascular imaging experts using a standardized technique.

Results

The primary end point is the occurrence of late adverse events, defined as aneurysm formation (≥6 cm), rapid expansion of the aorta (≥1 cm/y), fatal or nonfatal aortic rupture, new refractory pain, uncontrollable hypertension, and organ or limb malperfusion. The previously derived multivariable model will be externally validated by using Cox proportional hazards regression modeling.

Conclusion

This study will show whether a recent clinical and imaging-based risk prediction model for patients with uTBAD can be generalized to a larger population, which is an important step toward individualized risk stratification and therapy.Keywords: CT Angiography, Vascular, Aorta, Dissection, Outcomes Analysis, Aortic Dissection, MRI, TEVAR© RSNA, 2022See also the commentary by Rajiah in this issue.

Limited Aortic Intimal Tears: CT Imaging Features and Clinical Characteristics

Limited aortic intimal tear is an uncommon lesion of the dissection spectrum. The lesion has several imaging features that are not well known, including asymmetric aortic contour abnormalities, filling defects, and various morphologic patterns, such as linear, L-shaped, T-shaped, and stellate configurations. Hemorrhage of the aortic wall may also be present in patients with this rare entity. This imaging essay reviews the CT imaging findings and clinical characteristics of patients with limited intimal tears. Keywords: Aorta, CT © RSNA, 2022.

Toward Foundational Deep Learning Models for Medical Imaging in the New Era of Transformer Networks

Deep learning models are currently the cornerstone of artificial intelligence in medical imaging. While progress is still being made, the generic technological core of convolutional neural networks (CNNs) has had only modest innovations over the last several years, if at all. There is thus a need for improvement. More recently, transformer networks have emerged that replace convolutions with a complex attention mechanism, and they have already matched or exceeded the performance of CNNs in many tasks. Transformers need very large amounts of training data, even more than CNNs, but obtaining well-curated labeled data is expensive and difficult. A possible solution to this issue would be transfer learning with pretraining on a self-supervised task using very large amounts of unlabeled medical data. This pretrained network could then be fine-tuned on specific medical imaging tasks with relatively modest data requirements. The authors believe that the availability of a large-scale, three-dimension-capable, and extensively pretrained transformer model would be highly beneficial to the medical imaging and research community. In this article, authors discuss the challenges and obstacles of training a very large medical imaging transformer, including data needs, biases, training tasks, network architecture, privacy concerns, and computational requirements. The obstacles are substantial but not insurmountable for resourceful collaborative teams that may include academia and information technology industry partners. © RSNA, 2022 Keywords: Computer-aided Diagnosis (CAD), Informatics, Transfer Learning, Convolutional Neural Network (CNN).

Vendor independent coronary calcium scoring improves individual risk assessment – the Multi-Ethnic Study of Atherosclerosis (MESA)

Background

Coronary artery calcium (CAC) scoring improves event prediction of coronary heart disease (CHD) and can be used to guide initiation or deferral of statin therapy in asymptomatic individuals at low-to-intermediate risk. However, there is substantial variation of CAC scores acquired with different CT scanners. Therefore, CAC scoring discrepancies may lead to suboptimal patients' treatment and harmonization is needed.

Purpose

The aim of our study was twofold. Our first aim was to develop a calibration tool resulting in vendor neutral Agatston Score (vnAS). Second, we aimed to assess the effect of using this calibration tool in the existing Multi-Ethnic Study of Atherosclerosis (MESA) study cohort on both risk prediction of coronary heart disease (CHD), and initiation of statin therapy.

Methods

Two static anthropomorphic phantoms containing multiple CAC inserts were imaged on seven different CT systems and one EBT system. For each CT system, the vnAS calculator parameters were derived using regression analysis based on Agatston scores from EBT and CT. To validate our vnAS, we used CAC scoring information and clinical data of participants from MESA study. All included participants (Cohort I, n=3181) were assigned to one out of four calcium groups, which were defined as zero-calcium (AS and vnAS of 0), low-calcium (AS and vnAS of 1–99) high-calcium (AS and vnAS ≥100), and reclassified individuals (AS &lt;100 and vnAS ≥100). The occurrence of CHD events in each group was assessed and multivariable Cox regression models were used to assess the added value of the vnAS in the prediction of CHD events

For a sub-cohort of 890 participants at intermediate cardiovascular risk, the potential benefit from statin therapy was estimated based on the number needed to treat (NNT). NNT were determined for patients with vnAS ≥100 and vnAS ≥300 with original AS below 100 (group I) or 300 (group II), respectively.

Results

For all CT systems, a high degree of correlation with EBT Agatston scores was shown (R2 &gt;0.932). Using the vnAS, 85 individuals (2.7%) were reclassified from a lower to a higher risk category. For the reclassified participants, CHD event rates increased significantly from 7% to 15% (p=0.008) with a CHD hazard ratio of 3.39 (95% CI 1.82–6.35, p=0.001) (Figure 1). In intermediate risk cohort, the NNT was smaller for reclassified individuals as compared to their original (low) calcium group, at 7 vs 12 for group I and 2 vs 15 for group II, respectively. The summary of vnAS applicability is depicted in Figure 2.

Conclusions

We developed a calibration tool, which enables to calculate vendor neutral AS (vnAS). Based on vnAS, 85 individuals from MESA study, who were reclassified from a lower to a higher calcium category, did indeed have a higher CHD event rate. Consequently, the potential benefit from statin therapy, based on vnAS, was also increased for reclassified participants at intermediate cardiovascular risk.

Funding Acknowledgement

Type of funding sources: None.

Low-dose coronary calcium scoring CT using a dedicated reconstruction filter for kV-independent calcium measurements

In this prospective, pilot study, we tested a kV-independent coronary artery calcium scoring CT protocol, using a novel reconstruction kernel (Sa36f). From December 2018 to November 2019, we performed an additional research scan in 61 patients undergoing clinical calcium scanning. For the standard protocol (120 kVp), images were reconstructed with a standard, medium-sharp kernel (Qr36d). For the research protocol (automated kVp selection), images were reconstructed with a novel kernel (Sa36f). Research scans were sequentially performed using a higher (cohort A, n = 31) and a lower (cohort B, n = 30) dose optimizer setting within the automatic system with customizable kV selection. Agatston scores, coronary calcium volumes, and radiation exposure of the standard and research protocol were compared. A phantom study was conducted to determine inter-scan variability. There was excellent correlation for the Agatston score between the two protocols (r = 0.99); however, the standard protocol resulted in slightly higher Agatston scores (29.4 [0-139.0] vs 17.4 [0-158.2], p = 0.028). The median calcium volumes were similar (11.5 [0-109.2] vs 11.2 [0-118.0] mm³; p = 0.176), and the number of calcified lesions was not significantly different (p = 0.092). One patient was reclassified to another risk category. The research protocol could be performed at a lower kV and resulted in a substantially lower radiation exposure, with a median volumetric CT dose index of 4.1 vs 5.2 mGy, respectively (p < 0.001). Our results showed that a consistent coronary calcium scoring can be achieved using a kV-independent protocol that lowers radiation doses compared to the standard protocol. KEY POINTS: • The Sa36f kernel enables kV-independent Agatston scoring without changing the original Agatston weighting threshold. • Agatston scores and calcium volumes of the standard and research protocols showed an excellent correlation. • The research protocol resulted in a significant reduction in radiation exposure with a mean reduction of 22% in DLP and 25% in CTDI_vol.

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.

Imaging and Surveillance of Chronic Aortic Dissection: A Scientific Statement From the American Heart Association

All patients surviving an acute aortic dissection require continued lifelong surveillance of their diseased aorta. Late complications, driven predominantly by chronic false lumen degeneration and aneurysm formation, often require surgical, endovascular, or hybrid interventions to treat or prevent aortic rupture. Imaging plays a central role in the medical decision-making of patients with chronic aortic dissection. Accurate aortic diameter measurements and rigorous, systematic documentation of diameter changes over time with different imaging equipment and modalities pose a range of practical challenges in these complex patients. Currently, no guidelines or recommendations for imaging surveillance in patients with chronic aortic dissection exist. In this document, we present state-of-the-art imaging and measurement techniques for patients with chronic aortic dissection and clarify the need for standardized measurements and reporting for lifelong surveillance. We also examine the emerging role of imaging and computer simulations to predict aortic false lumen degeneration, remodeling, and biomechanical failure from morphological and hemodynamic features. These insights may improve risk stratification, individualize contemporary treatment options, and potentially aid in the conception of novel treatment strategies in the future.

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.

Deep Learning-Based 3D Segmentation of True Lumen, False Lumen, and False Lumen Thrombosis in Type-B Aortic Dissection

Patients with initially uncomplicated typeB aortic dissection (uTBAD) remain at high risk for developing late complications. Identification of morphologic features for improving risk stratification of these patients requires automated segmentation of computed tomography angiography (CTA) images. We developed three segmentation models utilizing a 3D residual U-Net for segmentation of the true lumen (TL), false lumen (FL), and false lumen thrombosis (FLT). Model 1 segments all labels at once, whereas model 2 segments them sequentially. Best results for TL and FL segmentation were achieved by model 2, with median (interquartiles) Dice similarity coefficients (DSC) of 0.85 (0.77-0.88) and 0.84 (0.82-0.87), respectively. For FLT segmentation, model 1 was superior to model 2, with median (interquartiles) DSCs of 0.63 (0.40-0.78). To purely test the performance of the network to segment FLT, a third model segmented FLT starting from the manually segmented FL, resulting in median (interquartiles) DSCs of 0.99 (0.98-0.99) and 0.85 (0.73-0.94) for patent FL and FLT, respectively. While the ambiguous appearance of FLT on imaging remains a significant limitation for accurate segmentation, our pipeline has the potential to help in segmentation of aortic lumina and thrombosis in uTBAD patients.Clinical relevance- Most predictors of aortic dissection (AD) degeneration are identified through anatomical modeling, which is currently prohibitive in clinical settings due to the timeintense human interaction. False lumen thrombosis, which often develops in patients with type B AD, has proven to show significant prognostic value for predicting late adverse events. Our automated segmentation algorithm offers the potential of personalized treatment for AD patients, leading to an increase in long-term survival.

CTA pulmonary artery enlargement in patients with severe aortic stenosis: Prognostic impact after TAVR

BACKGROUND

Identifying high-risk patients who will not derive substantial survival benefit from TAVR remains challenging. Pulmonary hypertension is a known predictor of poor outcome in patients undergoing TAVR and correlates strongly with pulmonary artery (PA) enlargement on CTA. We sought to evaluate whether PA enlargement, measured on pre-procedural computed tomography angiography (CTA), is associated with 1-year mortality in patients undergoing TAVR.

METHODS

We retrospectively included 402 patients undergoing TAVR between July 2012 and March 2016. Clinical parameters, including Society of Thoracic Surgeons (STS) score and right ventricular systolic pressure (RVSP) estimated by transthoracic echocardiography were reviewed. PA dimensions were measured on pre-procedural CTAs. Association between PA enlargement and 1-year mortality was analyzed. Kaplan-Meier and Cox proportional hazards regression analyses were performed.

RESULTS

The median follow-up time was 433 (interquartiles 339-797) days. A total of 56/402 (14%) patients died within 1 year after TAVR. Main PA area (area-MPA) was independently associated with 1-year mortality (hazard ratio per standard deviation equal to 2.04 [95%-confidence interval (CI) 1.48-2.76], p ​< ​0.001). Area under the curve (95%-CI) of the clinical multivariable model including STS-score and RVSP increased slightly from 0.67 (0.59-0.75) to 0.72 (0.72-0.89), p ​= ​0.346 by adding area-MPA. Although the AUC increased, differences were not significant (p ​= ​0.346). Kaplan-Meier analysis showed that mortality was significantly higher in patients with a pre-procedural non-indexed area-MPA of ≥7.40 ​cm² compared to patients with a smaller area-MPA (mortality 23% vs. 9%; p ​< ​0.001).

CONCLUSIONS

Enlargement of MPA on pre-procedural CTA is independently associated with 1-year mortality after TAVR.

Coronary calcium scoring potential of large field-of-view spectral photon-counting CT: a phantom study

OBJECTIVE

The aim of the current study was, first, to assess the coronary artery calcium (CAC) scoring potential of spectral photon-counting CT (SPCCT) in comparison with computed tomography (CT) for routine clinical protocols. Second, improved CAC detection and quantification at reduced slice thickness were assessed.

METHODS

Raw data was acquired and reconstructed with several combinations of reduced slice thickness and increasing strengths of iterative reconstruction (IR) for both CT systems with routine clinical CAC protocols for CT. Two CAC-containing cylindrical inserts, consisting of CAC of different densities and sizes, were placed in an anthropomorphic phantom. A specific CAC was detectable when 3 or more connected voxels exceeded the CAC scoring threshold of 130 Hounsfield units (HU). For all reconstructions, total CAC detectability was compared between both CT systems. Significant differences in CAC quantification (Agatston and volume scores) were assessed with Mann-Whitney U tests. Furthermore, volume scores were compared with the known CAC physical.

RESULTS

CAC scores for routine clinical protocols were comparable between SPCCT and CT. SPCCT showed 34% and 4% higher detectability of CAC for the small and large phantom, respectively. At reduced slice thickness, CAC detection increased by 142% and 169% for CT and SPCCT, respectively. In comparison with CT, volume scores from SPCCT were more comparable with the physical volume of the CAC.

CONCLUSION

CAC scores using routine clinical protocols are comparable between conventional CT and SPCCT. The increased spatial resolution of SPCCT allows for increased detectability and more accurate CAC volume estimation.

KEY POINTS

• Coronary artery calcium scores using routine clinical protocols are comparable between conventional CT and spectral photon-counting CT. • In comparison with conventional CT, increased coronary artery calcium detectability was shown for spectral photon-counting CT due to increased spatial resolution. • Volumes scores were more accurately determined with spectral photon-counting CT.

Diagnostic performance of single-phase dual-energy CT to differentiate vascular and nonvascular incidental renal lesions on portal venous phase: comparison with CT

OBJECTIVES

To determine whether single-phase dual-energy CT (DECT) differentiates vascular and nonvascular renal lesions in the portal venous phase (PVP). Optimal iodine threshold was determined and compared to Hounsfield unit (HU) measurements.

METHODS

We retrospectively included 250 patients (266 renal lesions) who underwent a clinically indicated PVP abdominopelvic CT on a rapid-kilovoltage-switching single-source DECT (rsDECT) or a dual-source DECT (dsDECT) scanner. Iodine concentration and HU measurements were calculated by four experienced readers. Diagnostic accuracy was determined using biopsy results and follow-up imaging as reference standard. Area under the curve (AUC) was calculated for each DECT scanner to differentiate vascular from nonvascular lesions and vascular lesions from hemorrhagic/proteinaceous cysts. Univariable and multivariable logistic regression analyses evaluated the association between variables and the presence of vascular lesions.

RESULTS

A normalized iodine concentration threshold of 0.25 mg/mL yielded high accuracy in differentiating vascular and nonvascular lesions (AUC 0.93, p < 0.001), with comparable performance to HU measurements (AUC 0.93). Both iodine concentration and HU measurements were independently associated with vascular lesions when adjusted for age, gender, body mass index, and lesion size (AUC 0.95 and 0.95, respectively). When combined, diagnostic performance was higher (AUC 0.96). Both absolute and normalized iodine concentrations performed better than HU measurements (AUC 0.92 vs. AUC 0.87) in differentiating vascular lesions from hemorrhagic/proteinaceous cysts.

CONCLUSION

A single-phase (PVP) DECT scan yields high accuracy to differentiate vascular from nonvascular renal lesions. Iodine concentration showed a slightly higher performance than HU measurements in differentiating vascular lesions from hemorrhagic/proteinaceous cysts.

KEY POINTS

• A single-phase dual-energy CT scan in the portal venous phase differentiates vascular from nonvascular renal lesions with high accuracy (AUC 0.93). • When combined, iodine concentration and HU measurements showed the highest diagnostic performance (AUC 0.96) to differentiate vascular from nonvascular renal lesions. • Compared to HU measurements, iodine concentration showed a slightly higher performance in differentiating vascular lesions from hemorrhagic/proteinaceous cysts.

Evaluating a calcium-aware kernel for CT CAC scoring with varying surrounding materials and heart rates: a dynamic phantom study

OBJECTIVES

The purpose of this study was twofold. First, the influence of a novel calcium-aware (Ca-aware) computed tomography (CT) reconstruction technique on coronary artery calcium (CAC) scores surrounded by a variety of tissues was assessed. Second, the performance of the Ca-aware reconstruction technique on moving CAC was evaluated with a dynamic phantom.

METHODS

An artificial coronary artery, containing two CAC of equal size and different densities (196 ± 3, 380 ± 2 mg hydroxyapatite cm^-3), was moved in the center compartment of an anthropomorphic thorax phantom at different heart rates. The center compartment was filled with mixtures, which resembled fat, water, and soft tissue equivalent CT numbers. Raw data was acquired with a routine clinical CAC protocol, at 120 peak kilovolt (kVp). Subsequently, reduced tube voltage (100 kVp) and tin-filtration (150Sn kVp) acquisitions were performed. Raw data was reconstructed with a standard and a novel Ca-aware reconstruction technique. Agatston scores of all reconstructions were compared with the reference (120 kVp) and standard reconstruction technique, with relevant deviations defined as > 10%.

RESULTS

For all heart rates, Agatston scores for CAC submerged in fat were comparable to the reference, for the reduced-kVp acquisition with Ca-aware reconstruction kernel. For water and soft tissue, medium-density Agatston scores were again comparable to the reference for all heart rates. Low-density Agatston scores showed relevant deviations, up to 15% and 23% for water and soft tissue, respectively.

CONCLUSION

CT CAC scoring with varying surrounding materials and heart rates is feasible at patient-specific tube voltages with the novel Ca-aware reconstruction technique.

KEY POINTS

• A dedicated calcium-aware reconstruction kernel results in similar Agatston scores for CAC surrounded by fatty materials regardless of CAC density and heart rate. • Application of a dedicated calcium-aware reconstruction kernel allows for radiation dose reduction. • Mass scores determined with CT underestimated physical mass.

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.

Aortic growth and development of partial false lumen thrombosis are associated with late adverse events in type B aortic dissection

BACKGROUND

Patients with medically treated type B aortic dissection (TBAD) remain at significant risk for late adverse events (LAEs). We hypothesize that not only initial morphological features, but also their change over time at follow-up are associated with LAEs.

MATERIALS AND METHODS

Baseline and 188 follow-up computed tomography (CT) scans with a median follow-up time of 4 years (range, 10 days to 12.7 years) of 47 patients with acute uncomplicated TBAD were retrospectively reviewed. Morphological features (n = 8) were quantified at baseline and each follow-up. Medical records were reviewed for LAEs, which were defined according to current guidelines. To assess the effects of changes of morphological features over time, the linear mixed effects models were combined with Cox proportional hazards regression for the time-to-event outcome using a joint modeling approach.

RESULTS

LAEs occurred in 21 of 47 patients at a median of 6.6 years (95% confidence interval [CI], 5.1-11.2 years). Among the 8 investigated morphological features, the following 3 features showed strong association with LAEs: increase in partial false lumen thrombosis area (hazard ratio [HR], 1.39; 95% CI, 1.18-1.66 per cm2 increase; P < .001), increase of major aortic diameter (HR, 1.24; 95% CI, 1.13-1.37 per mm increase; P < .001), and increase in the circumferential extent of false lumen (HR, 1.05; 95% CI, 1.01-1.10 per degree increase; P < .001).

CONCLUSIONS

In medically treated TBAD, increases in aortic diameter, new or increased partial false lumen thrombosis area, and increases of circumferential extent of the false lumen are strongly associated with LAEs.

Emerging methods for the characterization of ischemic heart disease: ultrafast Doppler angiography, micro-CT, photon-counting CT, novel MRI and PET techniques, and artificial intelligence

After an ischemic event, disruptive changes in the healthy myocardium may gradually develop and may ultimately turn into fibrotic scar. While these structural changes have been described by conventional imaging modalities mostly on a macroscopic scale-i.e., late gadolinium enhancement at magnetic resonance imaging (MRI)-in recent years, novel imaging methods have shown the potential to unveil an even more detailed picture of the postischemic myocardial phenomena. These new methods may bring advances in the understanding of ischemic heart disease with potential major changes in the current clinical practice. In this review article, we provide an overview of the emerging methods for the non-invasive characterization of ischemic heart disease, including coronary ultrafast Doppler angiography, photon-counting computed tomography (CT), micro-CT (for preclinical studies), low-field and ultrahigh-field MRI, and ¹¹C-methionine positron emission tomography. In addition, we discuss new opportunities brought by artificial intelligence, while addressing promising future scenarios and the challenges for the application of artificial intelligence in the field of cardiac imaging.

Spectral photon-counting CT in cardiovascular imaging

Photon-counting computed tomography (PCCT) is an emerging technology promising to substantially improve cardiovascular imaging. Recent engineering and manufacturing advances by several vendors are expected to imminently launch this new technology into clinical reality. Photon-counting detectors (PCDs) have multiple potential advantages over conventional energy integrating detectors (EIDs) such as the absence of electronic noise, multi-energy capability, and increased spatial resolution. These developments will have different timescales for implementation and will affect different clinical scopes. We describe the technical aspects of PCCT, explain the current developments, and finally discuss potential advantages of PCCT in cardiovascular imaging.

Ultra-high resolution, 3-dimensional magnetic resonance imaging of the atherosclerotic vessel wall at clinical 7T

Accurate quantification and characterization of atherosclerotic plaques with MRI requires high spatial resolution acquisitions with excellent image quality. The intrinsically better signal-to-noise ratio (SNR) at high-field clinical 7T compared to the widely employed lower field strengths of 1.5 and 3T may yield significant improvements to vascular MRI. However, 7T atherosclerosis imaging also presents specific challenges, related to local transmit coils and B1 field inhomogeneities, which may overshadow these theoretical gains. We present the development and evaluation of 3D, black-blood, ultra-high resolution vascular MRI on clinical high-field 7T in comparison lower-field 3T. These protocols were applied for in vivo imaging of atherosclerotic rabbits, which are often used for development, testing, and validation of translatable cardiovascular MR protocols. Eight atherosclerotic New Zealand White rabbits were imaged on clinical 7T and 3T MRI scanners using 3D, isotropic, high (0.63 mm3) and ultra-high (0.43 mm3) spatial resolution, black-blood MR sequences with extensive spatial coverage. Following imaging, rabbits were sacrificed for validation using fluorescence imaging and histology. Image quality parameters such as SNR and contrast-to-noise ratio (CNR), as well as morphological and functional plaque measurements (plaque area and permeability) were evaluated at both field strengths. Using the same or comparable imaging parameters, SNR and CNR were in general higher at 7T compared to 3T, with a median (interquartiles) SNR gain of +40.3 (35.3-80.1)%, and a median CNR gain of +68.1 (38.5-95.2)%. Morphological and functional parameters, such as vessel wall area and permeability, were reliably acquired at 7T and correlated significantly with corresponding, widely validated 3T vessel wall MRI measurements. In conclusion, we successfully developed 3D, black-blood, ultra-high spatial resolution vessel wall MRI protocols on a 7T clinical scanner. 7T imaging was in general superior to 3T with respect to image quality, and comparable in terms of plaque area and permeability measurements.

CT-based True- and False-Lumen Segmentation in Type B Aortic Dissection Using Machine Learning

Purpose

To develop a segmentation pipeline for segmentation of aortic dissection CT angiograms into true and false lumina on multiplanar reformations (MPRs) perpendicular to the aortic centerline and derive quantitative morphologic features, specifically aortic diameter and true- or false-lumen cross-sectional area.

Materials and Methods

An automated segmentation pipeline including two convolutional neural network (CNN) segmentation algorithms was developed. The algorithm derives the aortic centerline, generates MPRs orthogonal to the centerline, and segments the true and false lumina. A total of 153 CT angiograms obtained from 45 retrospectively identified patients (mean age, 50 years; range, 22-79 years) were used to train (n = 103), validate (n = 22), and test (n = 28) the CNN pipeline. Accuracy was evaluated by using the Dice similarity coefficient (DSC). Segmentations were then used to derive the maximal diameter of test-set patients and cross-sectional area profiles of the true and false lumina.

Results

The segmentation pipeline yielded a mean DSC of 0.873 ± 0.056 for the true lumina and 0.894 ± 0.040 for the false lumina of test-set cases. Automated maximal diameter measurements correlated well with manual measurements (R ² = 0.95). Profiles of cross-sectional diameter, true-lumen area, and false-lumen area over several follow-up examinations were derived.

Conclusion

A segmentation pipeline was used to accurately identify true and false lumina on CT angiograms of aortic dissection. These segmentations can be used to obtain diameter and other morphologic parameters for surveillance and risk stratification.Supplemental material is available for this article.© RSNA, 2020.

The Project Baseline Health Study: a step towards a broader mission to map human health

The Project Baseline Health Study (PBHS) was launched to map human health through a comprehensive understanding of both the health of an individual and how it relates to the broader population. The study will contribute to the creation of a biomedical information system that accounts for the highly complex interplay of biological, behavioral, environmental, and social systems. The PBHS is a prospective, multicenter, longitudinal cohort study that aims to enroll thousands of participants with diverse backgrounds who are representative of the entire health spectrum. Enrolled participants will be evaluated serially using clinical, molecular, imaging, sensor, self-reported, behavioral, psychological, environmental, and other health-related measurements. An initial deeply phenotyped cohort will inform the development of a large, expanded virtual cohort. The PBHS will contribute to precision health and medicine by integrating state of the art testing, longitudinal monitoring and participant engagement, and by contributing to the development of an improved platform for data sharing and analysis.

Preparing Medical Imaging Data for Machine Learning

Artificial intelligence (AI) continues to garner substantial interest in medical imaging. The potential applications are vast and include the entirety of the medical imaging life cycle from image creation to diagnosis to outcome prediction. The chief obstacles to development and clinical implementation of AI algorithms include availability of sufficiently large, curated, and representative training data that includes expert labeling (eg, annotations). Current supervised AI methods require a curation process for data to optimally train, validate, and test algorithms. Currently, most research groups and industry have limited data access based on small sample sizes from small geographic areas. In addition, the preparation of data is a costly and time-intensive process, the results of which are algorithms with limited utility and poor generalization. In this article, the authors describe fundamental steps for preparing medical imaging data in AI algorithm development, explain current limitations to data curation, and explore new approaches to address the problem of data availability.

Incremental Value of Aortomitral Continuity Calcification for Risk Assessment after Transcatheter Aortic Valve Replacement

Purpose

To investigate the association of aortomitral continuity calcification (AMCC) with all-cause mortality, postprocedural paravalvular leak (PVL), and prolonged hospital stay in patients undergoing transcatheter aortic valve replacement (TAVR).

Materials and Methods

The authors retrospectively evaluated 329 patients who underwent TAVR between March 2013 and March 2016. AMCC, aortic valve calcification (AVC), and coronary artery calcification (CAC) were quantified by using preprocedural CT. Pre-procedural Society of Thoracic Surgeons (STS) score was recorded. Associations between baseline AMCC, AVC, and CAC and 1-year mortality, PVL, and hospital stay longer than 7 days were analyzed.

Results

The median follow-up was 415 days (interquartiles, 344-727 days). After 1 year, 46 of the 329 patients (14%) died and 52 (16%) were hospitalized for more than 7 days. Of the 326 patients who underwent postprocedural echocardiography, 147 (45%) had postprocedural PVL. The CAC score (hazard ratio: 1.11 per 500 points) and AMCC mass (hazard ratio: 1.13 per 500 mg) were associated with 1-year mortality. AVC mass (odds ratio: 1.93 per 100 mg) was associated with postprocedural PVL. Only the STS score was associated with prolonged hospital stay (odds ratio: 1.19 per point).

Conclusion

AMCC is associated with mortality within 1 year after TAVR and substantially improves individual risk classification when added to a model consisting of STS score and AVC mass only.Supplemental material is available for this article.© RSNA, 2019See also the commentary by Brown and Leipsic in this issue.

Diagnostic Performance of On-Site Coronary CT Angiography-derived Fractional Flow Reserve Based on Patient-specific Lumped Parameter Models

Purpose

To evaluate the diagnostic performance of a prototype on-site coronary CT angiography-derived fractional flow reserve (CT FFR) algorithm, based on patient-specific lumped parameter models, for the detection of functionally significant stenosis defined by invasive FFR, and to compare the performance to anatomic evaluation of stenosis degree.

Materials and Methods

In this retrospective feasibility study, 77 vessels in 57 patients (42 of 57 [74%]) men; mean age, 58.5 years ± 9.2 [standard deviation]) who underwent clinically indicated coronary CT angiography within 60 days prior to an invasive FFR measurement were analyzed. Invasive FFR less than or equal to 0.80 was used to indicate a functionally significant stenosis. Diagnostic performance of CT FFR was evaluated and compared with evaluation of stenosis degree. Analysis was performed on a per-vessel basis.

Results

Invasive FFR revealed functionally significant stenoses in 37 vessels (48%). CT FFR showed a significantly increased ability to indicate functionally significant stenosis (area under the receiver operating characteristic curve [AUC], 0.87) compared with degree of stenosis at coronary CT angiography (AUC, 0.70; ΔAUC 0.17; P < .01). Using a cutoff of less than or equal to 0.80 for CT FFR and greater than or equal to 50% degree of stenosis at coronary CT angiography to indicate a significant stenosis, sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were 33 of 37 (89.2%), 31 of 40 (77.5%), 33 of 42 (78.6%), 31 of 35 (88.6%), and 64 of 77 (83.1%), respectively, for CT FFR, and 33 of 37 (89.2%), 17 of 40 (42.5%), 33 of 56 (58.9%), 17 of 21 (81.0%), and 50 of 77 (64.9%), respectively, for degree of stenosis at coronary CT angiography.

Conclusion

Diagnostic performance of on-site CT FFR was superior to stenosis evaluation at coronary CT angiography for identification of functionally significant coronary artery stenosis in patients suspected of having or known to have coronary artery disease.© RSNA, 2019See also commentary by Schoepf et al.

Acute Limited Intimal Tears of the Thoracic Aorta

BACKGROUND

Limited intimal tears (LITs) of the aorta (Class 3 dissection variant) are the least common form of aortic pathology in patients presenting with acute aortic syndrome (AAS). LITs are difficult to detect on imaging and may be underappreciated.

OBJECTIVES

This study sought to describe the frequency, pathology, treatment, and outcome of LITs compared with other AAS, and to demonstrate that LITs can be detected pre-operatively by contemporary imaging.

METHODS

The authors retrospectively reviewed 497 patients admitted for 513 AAS events at a single academic aortic center between 2003 and 2012. AAS were classified into classic dissection (AD), intramural hematoma, LIT, penetrating atherosclerotic ulcer, and rupturing thoracic aortic aneurysm. The prevalence, pertinent risk factors, and detailed imaging findings with surgical and pathological correlation of LITs are described. Management, early outcomes, and late mortality are reported.

RESULTS

Among 497 patients with AAS, the authors identified 24 LITs (4.8% of AAS) in 16 men and 8 women (17 type A, 7 type B). Patients with LITs were older than those with AD, and type A LITs had similarly dilated ascending aortas as type A AD. Three patients presented with rupture. Eleven patients underwent urgent surgical aortic replacement, and 2 patients underwent endovascular repair. Medial degeneration was present in all surgical specimens. In-hospital mortality was 4% (1 of 24), and in total, 5 patients with LIT died subsequently at 1.5 years (interquartile range [IQR]: 0.3 to 2.5 years). Computed tomography imaging detected all but 1 LIT, best visualized on volume-rendered images.

CONCLUSIONS

LITs are rare acute aortic lesions within the dissection spectrum, with similar presentation, complications, and outcomes compared with AD and intramural hematoma. Awareness of this lesion allows pre-operative diagnosis using high-quality computed tomography angiography.

Application of speCtraL computed tomogrAphy to impRove specIficity of cardiac compuTed tomographY (CLARITY study): rationale and design

INTRODUCTION

Anatomic stenosis evaluation on coronary CT angiography (CCTA) lacks specificity in indicating the functional significance of a stenosis. Recent developments in CT techniques (including dual-layer spectral detector CT [SDCT] and static stress CT perfusion [CTP]) and image analyses (including fractional flow reserve [FFR] derived from CCTA images [FFR_CT] and deep learning analysis [DL]) are potential strategies to increase the specificity of CCTA by combining both anatomical and functional information in one investigation. The aim of the current study is to assess the diagnostic performance of (combinations of) SDCT, CTP, FFR_CT and DL for the identification of functionally significant coronary artery stenosis.

METHODS AND ANALYSIS

Seventy-five patients aged 18 years and older with stable angina and known coronary artery disease and scheduled to undergo clinically indicated invasive FFR will be enrolled. All subjects will undergo the following SDCT scans: coronary calcium scoring, static stress CTP, rest CCTA and if indicated (history of myocardial infarction) a delayed enhancement acquisition. Invasive FFR of ≤0.80, measured within 30 days after the SDCT scans, will be used as reference to indicate a functionally significant stenosis. The primary study endpoint is the diagnostic performance of SDCT (including CTP) for the identification of functionally significant coronary artery stenosis. Secondary study endpoint is the diagnostic performance of SDCT, CTP, FFR_CT and DL separately and combined for the identification of functionally significant coronary artery stenosis.

ETHICS AND DISSEMINATION

Ethical approval was obtained. All subjects will provide written informed consent. Study findings will be disseminated through peer-reviewed conference presentations and journal publications.

TRIAL REGISTRATION NUMBER

NCT03139006; Pre-results.

Emphysema quantification using chest CT: influence of radiation dose reduction and reconstruction technique

BACKGROUND

Computed tomography (CT) emphysema quantification is affected by both radiation dose (i.e. image noise) and reconstruction technique. At reduced dose, filtered back projection (FBP) results in an overestimation of the amount of emphysema due to higher noise levels, while the use of iterative reconstruction (IR) can result in an underestimation due to reduced noise. The objective of this study was to determine the influence of dose reduction and hybrid IR (HIR) or model-based IR (MIR) on CT emphysema quantification.

METHODS

Twenty-two patients underwent inspiratory chest CT scan at routine radiation dose and at 45%, 60% and 75% reduced radiation dose. Acquisitions were reconstructed with FBP, HIR and MIR. Emphysema was quantified using the 15th percentile of the attenuation curve and the percentage of voxels below -950 HU. To determine whether the use of a different percentile or HU threshold is more accurate at reduced dose levels and with IR, additional measurements were performed using different percentiles and HU thresholds to determine the optimal combination.

RESULTS

Dose reduction resulted in a significant overestimation of emphysema, while HIR and MIR resulted in an underestimation. Lower HU thresholds with FBP at reduced dose and higher HU thresholds with HIR and MIR resulted in emphysema percentages comparable to the reference. The 15th percentile quantification method showed similar results as the HU threshold method.

CONCLUSIONS

This within-patients study showed that CT emphysema quantification is significantly affected by dose reduction and IR. This can potentially be solved by adapting commonly used thresholds.

The evolution of image reconstruction for CT-from filtered back projection to artificial intelligence

Abstract

The first CT scanners in the early 1970s already used iterative reconstruction algorithms; however, lack of computational power prevented their clinical use. In fact, it took until 2009 for the first iterative reconstruction algorithms to come commercially available and replace conventional filtered back projection. Since then, this technique has caused a true hype in the field of radiology. Within a few years, all major CT vendors introduced iterative reconstruction algorithms for clinical routine, which evolved rapidly into increasingly advanced reconstruction algorithms. The complexity of algorithms ranges from hybrid-, model-based to fully iterative algorithms. As a result, the number of scientific publications on this topic has skyrocketed over the last decade. But what exactly has this technology brought us so far? And what can we expect from future hardware as well as software developments, such as photon-counting CT and artificial intelligence? This paper will try answer those questions by taking a concise look at the overall evolution of CT image reconstruction and its clinical implementations. Subsequently, we will give a prospect towards future developments in this domain.

Key Points

• Advanced CT reconstruction methods are indispensable in the current clinical setting.

• IR is essential for photon-counting CT, phase-contrast CT, and dark-field CT.

• Artificial intelligence will potentially further increase the performance of reconstruction methods.

Photon-counting CT: Technical Principles and Clinical Prospects

Photon-counting CT is an emerging technology with the potential to dramatically change clinical CT. Photon-counting CT uses new energy-resolving x-ray detectors, with mechanisms that differ substantially from those of conventional energy-integrating detectors. Photon-counting CT detectors count the number of incoming photons and measure photon energy. This technique results in higher contrast-to-noise ratio, improved spatial resolution, and optimized spectral imaging. Photon-counting CT can reduce radiation exposure, reconstruct images at a higher resolution, correct beam-hardening artifacts, optimize the use of contrast agents, and create opportunities for quantitative imaging relative to current CT technology. In this review, the authors will explain the technical principles of photon-counting CT in nonmathematical terms for radiologists and clinicians. Following a general overview of the current status of photon-counting CT, they will explain potential clinical applications of this technology.

Contrast agent concentration optimization in CTA using low tube voltage and dual-energy CT in multiple vendors: a phantom study

We investigated the feasibility and extent to which iodine concentration can be reduced in computed tomography angiography imaging of the aorta and coronary arteries using low tube voltage and virtual monochromatic imaging of 3 major dual-energy CT (DECT) vendors. A circulation phantom was imaged with dual source CT (DSCT), gemstone spectral imaging (GSI) and dual-layer spectral detector CT (SDCT). For each scanner, a reference scan was acquired at 120 kVp using routine iodine concentration (300 mg I/ml). Subsequently, scans were acquired at lowest possible tube potential (70, 80, 80 kVp, respectively), and DECT-mode (80/150Sn, 80/140 and 120 kVp, respectively) in arterial phase after administration of iodine (300, 240, 180, 120, 60, 30 mg I/ml). Objective image quality was evaluated using attenuation, CNR and dose corrected CNR (DCCNR) measured in the aorta and left main coronary artery. Average DCCNR at reference was 227.0, 39.7 and 60.2 for DSCT, GSI and SDCT. Maximum iodine concentration reduction without loss of DCCNR was feasible down to 180 mg I/ml (40% reduced) for DSCT (DCCNR 467.1) and GSI (DCCNR 46.1) using conventional CT low kVp, and 120 mg I/ml (60% reduced) for SDCT (DCCNR 171.5) using DECT mode. Low kVp scanning and DECT allows for 40-60% iodine reduction without loss in image quality compared to reference. Optimal scan protocol and to which extent varies per vendor. Further patient studies are needed to extend and translate our findings to clinical practice.

Influence of heart rate on coronary calcium scores: a multi-manufacturer phantom study

To evaluate the influence of heart rate on coronary calcium scores (CCS) using a dynamic phantom on four high-end computed tomography (CT) systems from different manufacturers. Artificial coronary arteries were moved in an anthropomorphic chest phantom at linear velocities, corresponding to < 60, 60-75 and > 75 beats per minute (bpm). Data was acquired with routinely used clinical protocols for CCS on four high-end CT systems (CT1-CT4). CCS, quantified as Agatston and mass scores were compared to reference scores at < 60 bpm. Influence of heart rate was assessed for each system with the cardiac motion susceptibility (CMS) Index. At increased heart rates (> 75 bpm), Agatston scores of the low mass calcification were similar to the reference score, while Agatston scores of the medium and high mass calcification increased significantly up to 50% for all CT systems. Threefold CMS increases at > 75 bpm in comparison with < 60 bpm were shown. For medium and high mass calcifications, significant differences in CMS between CT systems were found. Heart rate substantially influences CCS for high-end CT systems of four major manufacturers, but CT systems differ in motion susceptibility. Follow-up CCS CT scans should be acquired on the same CT system and protocol, and preferably with comparable heart rates.

The Effects of Iodine Attenuation on Pulmonary Nodule Volumetry using Novel Dual-Layer Computed Tomography Reconstructions

OBJECTIVES

To assess the effect of iodine attenuation on pulmonary nodule volumetry using virtual non-contrast (VNC) and mono-energetic reconstructions.

METHODS

A consecutive series of patients who underwent a contrast-enhanced chest CT scan were included. Images were acquired on a novel dual-layer spectral CT system. Conventional reconstructions as well as VNC and mono-energetic images at different keV levels were used for nodule volumetry.

RESULTS

Twenty-four patients with a total of 63 nodules were included. Conventional reconstructions showed a median (interquartile range) volume and diameter of 174 (87 - 253) mm3 and 6.9 (5.4 - 9.9) mm, respectively. VNC reconstructions resulted in a significant volume reduction of 5.5% (2.6 - 11.2%; p<0.001). Mono-energetic reconstructions showed a correlation between nodule attenuation and nodule volume (Spearman correlation 0.77, (0.49 - 0.94)). Lowering the keV resulted in increased volumes while higher keV levels resulted in decreased pulmonary nodule volumes compared to conventional CT.

CONCLUSIONS

Novel dual-layer spectral CT offers the possibility to reconstruct VNC and mono-energetic images. Those reconstructions show that higher pulmonary nodule attenuation results in larger nodule volumes. This may explain the reported underestimation in nodule volume on non-contrast enhanced compared to contrast-enhanced acquisitions.

KEY POINTS

• Pulmonary nodule volumes were measured on virtual non-contrast and mono-energetic reconstructions • Mono-energetic reconstructions showed that higher attenuation results in larger volumes • This may explain the reported nodule volume underestimation on non-contrast enhanced CT • Mostly metastatic pulmonary nodules were evaluated, results might differ for benign nodules.

Radiation dose reduction for CT assessment of urolithiasis using iterative reconstruction: A prospective intra-individual study

Objective

To assess the performance of hybrid (HIR) and model-based iterative reconstruction (MIR) in patients with urolithiasis at reduced-dose computed tomography (CT).

Methods

Twenty patients scheduled for unenhanced abdominal CT for follow-up of urolithiasis were prospectively included. Routine dose acquisition was followed by three low-dose acquisitions at 40%, 60% and 80% reduced doses. All images were reconstructed with filtered back projection (FBP), HIR and MIR. Urolithiasis detection rates, gall bladder, appendix and rectosigmoid evaluation and overall subjective image quality were evaluated by two observers.

Results

74 stones were present in 17 patients. Half the stones were not detected on FBP at the lowest dose level, but this improved with MIR to a sensitivity of 100%. HIR resulted in a slight decrease in sensitivity at the lowest dose to 72%, but outperformed FBP. Evaluation of other structures with HIR at 40% and with MIR at 60% dose reductions was comparable to FBP at routine dose, but 80% dose reduction resulted in non-evaluable images.

Conclusions

CT radiation dose for urolithiasis detection can be safely reduced by 40 (HIR)–60 (MIR) % without affecting assessment of urolithiasis, possible extra-urinary tract pathology or overall image quality.

Key Points

• Iterative reconstruction can be used to substantially lower the radiation dose.

• This allows for radiation reduction without affecting sensitivity of stone detection.

• Possible extra-urinary tract pathology evaluation is feasible at 40–60% reduced dose.

Electronic supplementary material

The online version of this article (doi:10.1007/s00330-017-4929-2) contains supplementary material, which is available to authorized users.

Accuracy of bone mineral density quantification using dual-layer spectral detector CT: a phantom study

OBJECTIVES

To investigate the accuracy of bone mineral density (BMD) quantification using dual-layer spectral detector CT (SDCT) at various scan protocols.

METHODS

Two validated anthropomorphic phantoms containing inserts of 50-200 mg/cm³ calcium hydroxyapatite (HA) were scanned using a 64-slice SDCT scanner at various acquisition protocols (120 and 140 kVp, and 50, 100 and 200 mAs). Regions of interest (ROIs) were placed in each insert and mean attenuation profiles at monochromatic energy levels (90-200 keV) were constructed. These profiles were fitted to attenuation profiles of pure HA and water to calculate HA concentrations. For comparison, one phantom was scanned using dual energy X-ray absorptiometry (DXA).

RESULTS

At both 120 and 140 kVp, excellent correlations (R = 0.97, P < 0.001) were found between true and measured HA concentrations. Mean error for all measurements at 120 kVp was -5.6 ± 5.7 mg/cm³ (-3.6 ± 3.2%) and at 140 kVp -2.4 ± 3.7 mg/cm³ (-0.8 ± 2.8%). Mean measurement errors were smaller than 6% for all acquisition protocols. Strong linear correlations (R² ≥ 0.970, P < 0.001) with DXA were found.

CONCLUSIONS

SDCT allows for accurate BMD quantification and potentially opens up the possibility for osteoporosis evaluation and opportunistic screening in patients undergoing SDCT for other clinical indications. However, patient studies are needed to extend and translate our findings.

KEY POINTS

• Dual-layer spectral detector CT allows for accurate bone mineral density quantification. • BMD measurements on SDCT are strongly linearly correlated to DXA. • SDCT, acquired for several indications, may allow for evaluation of osteoporosis. • This potentially opens up the possibility for opportunistic osteoporosis screening.

Feasibility and accuracy of dual-layer spectral detector computed tomography for quantification of gadolinium: a phantom study

Objectives

The aim of this study was to evaluate the feasibility and accuracy of dual-layer spectral detector CT (SDCT) for the quantification of clinically encountered gadolinium concentrations.

Methods

The cardiac chamber of an anthropomorphic thoracic phantom was equipped with 14 tubular inserts containing different gadolinium concentrations, ranging from 0 to 26.3 mg/mL (0.0, 0.1, 0.2, 0.4, 0.5, 1.0, 2.0, 3.0, 4.0, 5.1, 10.6, 15.7, 20.7 and 26.3 mg/mL). Images were acquired using a novel 64-detector row SDCT system at 120 and 140 kVp. Acquisitions were repeated five times to assess reproducibility. Regions of interest (ROIs) were drawn on three slices per insert. A spectral plot was extracted for every ROI and mean attenuation profiles were fitted to known attenuation profiles of water and pure gadolinium using in-house-developed software to calculate gadolinium concentrations.

Results

At both 120 and 140 kVp, excellent correlations between scan repetitions and true and measured gadolinium concentrations were found (R > 0.99, P < 0.001; ICCs > 0.99, CI 0.99–1.00). Relative mean measurement errors stayed below 10% down to 2.0 mg/mL true gadolinium concentration at 120 kVp and below 5% down to 1.0 mg/mL true gadolinium concentration at 140 kVp.

Conclusion

SDCT allows for accurate quantification of gadolinium at both 120 and 140 kVp. Lowest measurement errors were found for 140 kVp acquisitions.

Key Points

• Gadolinium quantification may be useful in patients with contraindication to iodine.

• Dual-layer spectral detector CT allows for overall accurate quantification of gadolinium.

• Interscan variability of gadolinium quantification using SDCT material decomposition is excellent.