Deep Learning from Dual-Energy Information for Whole-Heart Segmentation in Dual-Energy and Single-Energy Non-Contrast-Enhanced Cardiac CT

Deep learning-based whole-heart segmentation in coronary CT angiography (CCTA) allows the extraction of quantitative imaging measures for cardiovascular risk prediction. Automatic extraction of these measures in patients undergoing only non-contrast-enhanced CT (NCCT) scanning would be valuable. In this work, we leverage information provided by a dual-layer detector CT scanner to obtain a reference standard in virtual non-contrast (VNC) CT images mimicking NCCT images, and train a 3D convolutional neural network (CNN) for the segmentation of VNC as well as NCCT images. Contrast-enhanced acquisitions on a dual-layer detector CT scanner were reconstructed into a CCTA and a perfectly aligned VNC image. In each CCTA image, manual reference segmentations of the left ventricular (LV) myocardium, LV cavity, right ventricle, left atrium, right atrium, ascending aorta, and pulmonary artery trunk were obtained and propagated to the corresponding VNC image. These VNC images and reference segmentations were used to train 3D CNNs for automatic segmentation in either VNC images or NCCT images. Automatic segmentations in VNC images showed good agreement with reference segmentations, with an average Dice similarity coefficient of 0.897 \pm 0.034 and an average symmetric surface distance of 1.42 \pm 0.45 mm. Volume differences [95% confidence interval] between automatic NCCT and reference CCTA segmentations were -19 [-67; 30] mL for LV myocardium, -25 [-78; 29] mL for LV cavity, -29 [-73; 14] mL for right ventricle, -20 [-62; 21] mL for left atrium, and -19 [-73; 34] mL for right atrium, respectively. In 214 (74%) NCCT images from an independent multi-vendor multi-center set, two observers agreed that the automatic segmentation was mostly accurate or better. This method might enable quantification of additional cardiac measures from NCCT images for improved cardiovascular risk prediction

Radiation dose reduction in pediatric great vessel stent computed tomography using iterative reconstruction: A phantom study

Background To study dose reduction using iterative reconstruction (IR) for pediatric great vessel stent computed tomography (CT). Methods Five different great vessel stents were separately placed in a gel-containing plastic holder within an anthropomorphic chest phantom. The stent lumen was filled with diluted contrast gel. CT acquisitions were performed at routine dose, 52% and 81% reduced dose and reconstructed with filtered back projection (FBP) and IR. Objective image quality in terms of noise, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) as well as subjective image quality were evaluated. Results Noise, SNR and CNR were improved with IR at routine and 52% reduced dose, compared to FBP at routine dose. The lowest dose level resulted in decreased objective image quality with both FBP and IR. Subjective image quality was excellent at all dose levels. Conclusion IR resulted in improved objective image quality at routine dose and 52% reduced dose, while objective image quality deteriorated at 81% reduced dose. Subjective image quality was not affected by dose reduction

Baseline MDCT findings after prosthetic heart valve implantation provide important complementary information to echocardiography for follow-up purposes

Objectives: Recent studies have proposed additional multidetector-row CT (MDCT) for prosthetic heart valve (PHV) dysfunction. References to discriminate physiological from pathological conditions early after implantation are lacking. We present baseline MDCT findings of PHVs 6 weeks post implantation. Methods: Patients were prospectively enrolled and TTE was performed according to clinical guidelines. 256-MDCT images were systematically assessed for leaflet excursions, image quality, valve-related artefacts, and pathological and additional findings. Results: Forty-six patients were included comprising 33 mechanical and 16 biological PHVs. Overall, MDCT image quality was good and relevant regions remained reliably assessable despite mild-moderate PHV-artefacts. MDCT detected three unexpected valve-related pathology cases: (1) prominent subprosthetic tissue, (2) pseudoaneurysm and (3) extensive pseudoaneurysms and valve dehiscence. The latter patient required valve surgery to be redone. TTE only showed trace periprosthetic regurgitation, and no abnormalities in the other cases. Additional findings were: tilted aortic PHV position (n = 3), pericardial haematoma (n = 3) and pericardial effusion (n = 3). Periaortic induration was present in 33/40 (83 %) aortic valve patients. Conclusions: MDCT allowed evaluation of relevant PHV regions in all valves, revealed baseline postsurgical findings and, despite normal TTE findings, detected three cases of unexpected, clinically relevant pathology. Key Points: • Postoperative MDCT presents baseline morphology relevant for prosthetic valve follow-up. • 83 % of patients show periaortic induration 6 weeks after aortic valve replacement. • MDCT detected three cases of clinically relevant pathology not found with TTE. • Valve dehiscence detection by MDCT required redo valve surgery in one patient. • MDCT is a suitable and complementary imaging tool for follow-up purposes

Imaging of pediatric great vessel stents: Computed tomography or magnetic resonance imaging?

__Background:__ Complications might occur after great vessel stent implantation in children. Therefore follow- up using imaging is warranted. __Purpose:__ To determine the optimal imaging modality for the assessment of stents used to treat great vessel obstructions in children. __Material and methods:__ Five different large vessel stents were evaluated in an in-vitro setting. All stents were expanded to the maximal vendor recommended diameter (20mm; n = 4 or 10mm; n = 1), placed in an anthropomorphic chest phantom and imaged with a 256-slice CT-scanner. MRI images were acquired at 1.5T using a multi-slice T2-weighted turbo spin echo, an RFspoiled three-dimensional T1-weighted Fast Field Echo and a balanced turbo field echo 3D seq

Surgically implanted aortic valve bioprostheses deform after implantation: insights from computed tomography

Objective: Little is known about the prevalence and degree of deformation of surgically implanted aortic biological valve prostheses (bio-sAVRs). We assessed bio-sAVR deformation using multidetector-row computed tomography (MDCT). Methods: Three imaging databases were searched for patients with MDCT performed after bio-sAVR implantation. Minimal and maximal valve ring diameters were obtained in systole and/or diastole, depending on the acquired cardiac phase(s). The eccentricity index (EI) was calculated as a measure of deformation as (1 − (minimal diameter/maximal diameter)) × 100%. EI of 10% non-circular. Indications for MDCT and implanted valve type were retrieved. Results: One hundred fifty-two scans of bio-sAVRs were included. One hundred seventeen measurements were performed in systole and 35 in diastole. None or trivial deformation (EI 5%) in 56% of studied cases and were considered non-circular (eccentricity index > 10%) in 17% of studied valves. • The higher deformity rate found in bio-sAVRs with (suspected) valve pathology could suggest that geometric deformity may play a role in leaflet malformation and thrombus formation similar to that of transcatheter heart valves

Cardiac CT in CRT as a Singular Imaging Modality for Diagnosis and Patient-Tailored Management

Between 30–40% of patients with cardiac resynchronization therapy (CRT) do not show an improvement in left ventricular (LV) function. It is generally known that patient selection, LV lead implantation location, and device timing optimization are the three main factors that determine CRT response. Research has shown that image-guided CRT placement, which takes into account both anatomical and functional cardiac properties, positively affects the CRT response rate. In current clinical practice, a multimodality imaging approach comprised of echocardiography, cardiac magnetic resonance imaging, or nuclear medicine imaging is used to capture these features. However, with cardiac computed tomography (CT), one has an all-in-one acquisition method for both patient selection and the division of a patient-tailored, image-guided CRT placement strategy. This review discusses the applicability of CT in CRT patient identification, selection, and guided placement, offering insights into potential advancements in optimizing CRT outcomes

Cardiovascular Magnetic Resonance Reference Ranges From the Healthy Hearts Consortium

Background: The absence of population-stratified cardiovascular magnetic resonance (CMR) reference ranges from large cohorts is a major shortcoming for clinical care. Objectives: This paper provides age-, sex-, and ethnicity-specific CMR reference ranges for atrial and ventricular metrics from the Healthy Hearts Consortium, an international collaborative comprising 9,088 CMR studies from verified healthy individuals, covering the complete adult age spectrum across both sexes, and with the highest ethnic diversity reported to date. Methods: CMR studies were analyzed using certified software with batch processing capability (cvi42, version 5.14 prototype, Circle Cardiovascular Imaging) by 2 expert readers. Three segmentation methods (smooth, papillary, anatomic) were used to contour the endocardial and epicardial borders of the ventricles and atria from long- and short-axis cine series. Clinically established ventricular and atrial metrics were extracted and stratified by age, sex, and ethnicity. Variations by segmentation method, scanner vendor, and magnet strength were examined. Reference ranges are reported as 95% prediction intervals. Results: The sample included 4,452 (49.0%) men and 4,636 (51.0%) women with average age of 61.1 ± 12.9 years (range: 18-83 years). Among these, 7,424 (81.7%) were from White, 510 (5.6%) South Asian, 478 (5.3%) mixed/other, 341 (3.7%) Black, and 335 (3.7%) Chinese ethnicities. Images were acquired using 1.5-T (n = 8,779; 96.6%) and 3.0-T (n = 309; 3.4%) scanners from Siemens (n = 8,299; 91.3%), Philips (n = 498; 5.5%), and GE (n = 291, 3.2%). Conclusions: This work represents a resource with healthy CMR-derived volumetric reference ranges ready for clinical implementation

Cardiac magnetic resonance in advanced heart failure

Heart failure (HF) is a chronic and progressive disease that often progresses to an advanced stage where conventional therapy is insufficient to relieve patients' symptoms. Despite the availability of advanced therapies such as mechanical circulatory support or heart transplantation, the complexity of defining advanced HF, which requires multiple parameters and multimodality assessment, often leads to delays in referral to dedicated specialists with the result of a worsening prognosis. In this review, we aim to explore the role of cardiac magnetic resonance (CMR) in advanced HF by showing how CMR is useful at every step in managing these patients: from diagnosis to prognostic stratification, hemodynamic evaluation, follow-up and advanced therapies such as heart transplantation. The technical challenges of scanning advanced HF patients, which often require troubleshooting of intracardiac devices and dedicated scans, will be also discussed

Functional cardiac CT-Going beyond Anatomical Evaluation of Coronary Artery Disease with Cine CT, CT-FFR, CT Perfusion and Machine Learning

The aim of this review is to provide an overview of different functional cardiac CT techniques which can be used to supplement assessment of the coronary arteries to establish the significance of coronary artery stenoses. We focus on cine-CT, CT-FFR, CT-myocardial perfusion and how developments in machine learning can supplement these techniques

ESR Essentials: ten steps to cardiac MR—practice recommendations by ESCR

Abstract: Cardiovascular MR imaging has become an indispensable noninvasive tool in diagnosing and monitoring a broad range of cardiovascular diseases. Key to its clinical success and efficiency are appropriate clinical indication triage, technical expertise, patient safety, standardized preparation and execution, quality assurance, efficient post-processing, structured reporting, and communication and clinical integration of findings. Technological advancements are driving faster, more accessible, and cost-effective approaches. This ESR Essentials article presents a ten-step guide for implementing a cardiovascular MR program, covering indication assessments, optimized imaging, post-processing, and detailed reporting. Future goals include streamlined protocols, improved tissue characterization, and automation for greater standardization and efficiency. Clinical relevance statement: The growing clinical role of cardiovascular MR in risk assessment, diagnosis, and treatment planning highlights the necessity for radiologists to achieve expertise in this modality, advancing precision medicine and healthcare efficiency. Key Points: • Cardiovascular MR is essential in diagnosing and monitoring many acute and chronic cardiovascular pathologies. • Features such as technical expertise, quality assurance, patient safety, and optimized tailored imaging protocols, among others, are essential for a successful cardiovascular MR program. • Ongoing technological advances will push rapid multi-parametric cardiovascular MR, thus improving accessibility, patient comfort, and cost-effectiveness. Key Points: • Cardiovascular MR is essential in diagnosing and monitoring a wide array of cardiovascular pathologies (Level of Evidence: High). • A successful cardiovascular MR program depends on standardization (Level of Evidence: Low). • Future developments will increase the efficiency and accessibility of cardiovascular MR (Level of Evidence: Low)