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.

Pulmonary interstitial lymphography: A prospective trial with potential impact on stereotactic ablative radiotherapy planning for early-stage lung cancer.

This prospective feasibility trial investigated pulmonary interstitial lymphography to identify thoracic primary nodal drainage (PND). A post-hoc analysis of nodal recurrences was compared with PND for patients with early-stage lung cancer; larger studies are needed to establish correlation. Exploratory PND-inclusive stereotactic ablative radiotherapy plans were assessed for dosimetric feasibility.

Hemodynamic effects of entry and exit tear size in aortic dissection evaluated with in vitro magnetic resonance imaging and fluid-structure interaction simulation.

Understanding the complex interplay between morphologic and hemodynamic features in aortic dissection is critical for risk stratification and for the development of individualized therapy. This work evaluates the effects of entry and exit tear size on the hemodynamics in type B aortic dissection by comparing fluid-structure interaction (FSI) simulations with in vitro 4D-flow magnetic resonance imaging (MRI). A baseline patient-specific 3D-printed model and two variants with modified tear size (smaller entry tear, smaller exit tear) were embedded into a flow- and pressure-controlled setup to perform MRI as well as 12-point catheter-based pressure measurements. The same models defined the wall and fluid domains for FSI simulations, for which boundary conditions were matched with measured data. Results showed exceptionally well matched complex flow patterns between 4D-flow MRI and FSI simulations. Compared to the baseline model, false lumen flow volume decreased with either a smaller entry tear (- 17.8 and - 18.5%, for FSI simulation and 4D-flow MRI, respectively) or smaller exit tear (- 16.0 and - 17.3%). True to false lumen pressure difference (initially 11.0 and 7.9 mmHg, for FSI simulation and catheter-based pressure measurements, respectively) increased with a smaller entry tear (28.9 and 14.6 mmHg), and became negative with a smaller exit tear (- 20.6 and - 13.2 mmHg). This work establishes quantitative and qualitative effects of entry or exit tear size on hemodynamics in aortic dissection, with particularly notable impact observed on FL pressurization. FSI simulations demonstrate acceptable qualitative and quantitative agreement with flow imaging, supporting its deployment in clinical studies.

Longitudinal investigation of aortic dissection in mice with computational fluid dynamics.

Predicting late adverse events in aortic dissections is challenging. One commonly observed risk factor is partial thrombosis of the false lumen. In this study we investigated false lumen thrombus progression over 7 days in four mice with angiotensin II-induced aortic dissection. We performed computational fluid dynamic simulations with subject-specific boundary conditions from velocity and pressure measurements. We investigated endothelial cell activation potential, mean velocity, thrombus formation potential, and other hemodynamic factors. Our findings support the hypothesis that flow stagnation is the predominant hemodynamic factor driving a large thrombus ratio in false lumina, particularly those with a single fenestration.

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.

Radiology: Cardiothoracic Imaging Highlights 2022.

Since its inaugural issue in 2019, Radiology: Cardiothoracic Imaging has disseminated the latest scientific advances and technical developments in cardiac, vascular, and thoracic imaging. In this review, we highlight select articles published in this journal between October 2021 and October 2022. The scope of the review encompasses various aspects of coronary artery and congenital heart diseases, vascular diseases, thoracic imaging, and health services research. Key highlights include changes in the revised Coronary Artery Disease Reporting and Data System 2.0, the value of coronary CT angiography in informing prognosis and guiding treatment decisions, cardiac MRI findings after COVID-19 vaccination or infection, high-risk features at CT angiography to identify patients with aortic dissection at risk for late adverse events, and CT-guided fiducial marker placement for preoperative planning for pulmonary nodules. Ongoing research and future directions include photon-counting CT and artificial intelligence applications in cardiovascular imaging. Keywords: Pediatrics, CT Angiography, CT-Perfusion, CT-Spectral Imaging, MR Angiography, PET/CT, Transcatheter Aortic Valve Implantation/Replacement (TAVI/TAVR), Cardiac, Pulmonary, Vascular, Aorta, Coronary Arteries © RSNA, 2023.

Early clinical outcomes and molecular smooth muscle cell phenotyping using a prophylactic aortic arch replacement strategy in Loeys-Dietz syndrome.

OBJECTIVES: Patients with Loeys-Dietz syndrome demonstrate a heightened risk of distal thoracic aortic events after valve-sparing aortic root replacement. This study assesses the clinical risks and hemodynamic consequences of a prophylactic aortic arch replacement strategy in Loeys-Dietz syndrome and characterizes smooth muscle cell phenotype in Loeys-Dietz syndrome aneurysmal and normal-sized downstream aorta. METHODS: Patients with genetically confirmed Loeys-Dietz syndrome (n = 8) underwent prophylactic aortic arch replacement during valve-sparing aortic root replacement. Four-dimensional flow magnetic resonance imaging studies were performed in 4 patients with Loeys-Dietz syndrome (valve-sparing aortic root replacement + arch) and compared with patients with contemporary Marfan syndrome (valve-sparing aortic root replacement only, n = 5) and control patients (without aortopathy, n = 5). Aortic tissues from 4 patients with Loeys-Dietz syndrome and 2 organ donors were processed for anatomically segmented single-cell RNA sequencing and histologic assessment. RESULTS: Patients with Loeys-Dietz syndrome valve-sparing aortic root replacement + arch had no deaths, major morbidity, or aortic events in a median of 2 years follow-up. Four-dimensional magnetic resonance imaging demonstrated altered flow parameters in patients with postoperative aortopathy relative to controls, but no clear deleterious changes due to arch replacement. Integrated analysis of aortic single-cell RNA sequencing data (>49,000 cells) identified a continuum of abnormal smooth muscle cell phenotypic modulation in Loeys-Dietz syndrome defined by reduced contractility and enriched extracellular matrix synthesis, adhesion receptors, and transforming growth factor-beta signaling. These modulated smooth muscle cells populated the Loeys-Dietz syndrome tunica media with gradually reduced density from the overtly aneurysmal root to the nondilated arch. CONCLUSIONS: Patients with Loeys-Dietz syndrome demonstrated excellent surgical outcomes without overt downstream flow or shear stress disturbances after concomitant valve-sparing aortic root replacement + arch operations. Abnormal smooth muscle cell-mediated aortic remodeling occurs within the normal diameter, clinically at-risk Loeys-Dietz syndrome arch segment. These initial clinical and pathophysiologic findings support concomitant arch replacement in Loeys-Dietz syndrome.

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.

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.

Hemodynamic Effects of Entry and Exit Tear Size in Aortic Dissection Evaluated with In Vitro Magnetic Resonance Imaging and Fluid-Structure Interaction Simulation.

Understanding the complex interplay between morphologic and hemodynamic features in aortic dissection is critical for risk stratification and for the development of individualized therapy. This work evaluates the effects of entry and exit tear size on the hemodynamics in type B aortic dissection by comparing fluid-structure interaction (FSI) simulations with in vitro 4D-flow magnetic resonance imaging (MRI). A baseline patient-specific 3D-printed model and two variants with modified tear size (smaller entry tear, smaller exit tear) were embedded into a flow- and pressure-controlled setup to perform MRI as well as 12-point catheter-based pressure measurements. The same models defined the wall and fluid domains for FSI simulations, for which boundary conditions were matched with measured data. Results showed exceptionally well matched complex flow patterns between 4D-flow MRI and FSI simulations. Compared to the baseline model, false lumen flow volume decreased with either a smaller entry tear (-17.8 and -18.5 %, for FSI simulation and 4D-flow MRI, respectively) or smaller exit tear (-16.0 and -17.3 %). True to false lumen pressure difference (initially 11.0 and 7.9 mmHg, for FSI simulation and catheter-based pressure measurements, respectively) increased with a smaller entry tear (28.9 and 14.6 mmHg), and became negative with a smaller exit tear (-20.6 and -13.2 mmHg). This work establishes quantitative and qualitative effects of entry or exit tear size on hemodynamics in aortic dissection, with particularly notable impact observed on FL pressurization. FSI simulations demonstrate acceptable qualitative and quantitative agreement with flow imaging, supporting its deployment in clinical studies.

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.

Inter-observer variability of expert-derived morphologic risk predictors in aortic dissection.

OBJECTIVES: Establishing the reproducibility of expert-derived measurements on CTA exams of aortic dissection is clinically important and paramount for ground-truth determination for machine learning. METHODS: Four independent observers retrospectively evaluated CTA exams of 72 patients with uncomplicated Stanford type B aortic dissection and assessed the reproducibility of a recently proposed combination of four morphologic risk predictors (maximum aortic diameter, false lumen circumferential angle, false lumen outflow, and intercostal arteries). For the first inter-observer variability assessment, 47 CTA scans from one aortic center were evaluated by expert-observer 1 in an unconstrained clinical assessment without a standardized workflow and compared to a composite of three expert-observers (observers 2-4) using a standardized workflow. A second inter-observer variability assessment on 30 out of the 47 CTA scans compared observers 3 and 4 with a constrained, standardized workflow. A third inter-observer variability assessment was done after specialized training and tested between observers 3 and 4 in an external population of 25 CTA scans. Inter-observer agreement was assessed with intraclass correlation coefficients (ICCs) and Bland-Altman plots. RESULTS: Pre-training ICCs of the four morphologic features ranged from 0.04 (-0.05 to 0.13) to 0.68 (0.49-0.81) between observer 1 and observers 2-4 and from 0.50 (0.32-0.69) to 0.89 (0.78-0.95) between observers 3 and 4. ICCs improved after training ranging from 0.69 (0.52-0.87) to 0.97 (0.94-0.99), and Bland-Altman analysis showed decreased bias and limits of agreement. CONCLUSIONS: Manual morphologic feature measurements on CTA images can be optimized resulting in improved inter-observer reliability. This is essential for robust ground-truth determination for machine learning models. KEY POINTS: • Clinical fashion manual measurements of aortic CTA imaging features showed poor inter-observer reproducibility. • A standardized workflow with standardized training resulted in substantial improvements with excellent inter-observer reproducibility. • Robust ground truth labels obtained manually with excellent inter-observer reproducibility are key to develop reliable machine learning models.

Thoracic Endovascular Aortic Repair for Chronic Type B Aortic Dissection: Pre- and Postprocedural Imaging.

Aortic dissection is a chronic disease that requires lifelong clinical and imaging surveillance, long after the acute event. Imaging has an important role in prognosis, timing of repair, device sizing, and monitoring for complications, especially in the endovascular therapy era. Important anatomic features at preprocedural imaging include the location of the primary intimal tear and aortic zonal and branch vessel involvement, which influence the treatment strategy. Challenges of repair in the chronic phase include a small true lumen in conjunction with a stiff intimal flap, complex anatomy, and retrograde perfusion from distal reentry tears. The role of thoracic endovascular aortic repair (TEVAR) remains controversial for treatment of chronic aortic dissection. Standard TEVAR is aimed at excluding the primary intimal tear to decrease false lumen perfusion, induce false lumen thrombosis, promote aortic remodeling, and prevent aortic growth. In addition to covering the primary intimal tear with an endograft, several adjunctive techniques have been developed to mitigate retrograde false lumen perfusion. These techniques are broadly categorized into false lumen obliteration and landing zone optimization strategies, such as the provisional extension to induce complete attachment (PETTICOAT), false lumen embolization, cheese-wire fenestration, and knickerbocker techniques. Familiarity with these techniques is important to recognize expected changes and complications at postintervention imaging. The authors detail imaging options, provide examples of simple and complex endovascular repairs of aortic dissections, and highlight complications that can be associated with various techniques. Online supplemental material is available for this article. ©RSNA, 2022.

Imaging Challenges in Chronic Dissection.

Chronic aortic dissection comprises a heterogeneous group of unrepaired and repaired disease requiring lifelong clinical and imaging surveillance. CT and MRI are the main imaging modalities for longitudinal surveillance, with growing interest in emerging imaging techniques for prognostic potential. Imaging difficulties span technical and diagnostic challenges, some of which are unique to the repaired aorta, with specific complications depending on the type of repair. This review describes existing and emerging imaging techniques, outlines the technical and diagnostic challenges encountered at CT and MRI, and highlights the diagnostic pitfalls of chronic aortic dissection.

Tetralogy of Fallot and Aortic Dissection: Implications in Management.

We present the case of a 61-year-old man with tetralogy of Fallot postrepair and mechanical aortic valve replacement with an aortic root/ascending/arch aneurysm with chronic type A aortic dissection. He underwent uncomplicated aortic root and total arch replacement. Continued surveillance for aortic aneurysm is necessary in the tetralogy of Fallot population. (Level of Difficulty: Intermediate.).

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.