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Recent improvements in CT detector technology have led to smaller detector pixels resolving frequencies beyond 20 lp/cm and enabled ultra-high-resolution CT. Silicon-based photon-counting detector (PCD) CT is one such technology that promises improved spatial and spectral resolution. However, when the detector pixel sizes are reduced, the impact of cardiac motion on CT images becomes more pronounced. Here, we investigated the effects cardiac motion on the image quality of a clinical prototype Si-PCD scanner in a dynamic heart phantom. A series of 3D-printed vessels were created to simulate coronary arteries with diameter in the 1–3.5 ​mm range. Four coronary stents were set inside the d ​= ​3.5 ​mm vessels and all vessels were filled with contrast agents and were placed inside a dynamic cardiac phantom. The phantom was scanned in motion (60 bpm) and at rest on a prototype clinical Si-PCD CT scanner in 8-bin spectral UHR mode. Virtual monoenergetic images (VMI) were generated at 70 ​keV and CT number accuracy and effective spatial resolution (blooming) of rest and motion VMIs were compared. Linear regression analysis of CT numbers showed excellent agreement (r ​> ​0.99) between rest and motion. We did not observe a significant difference (p ​> ​0.48) in estimating free lumen diameters. Differences in in-stent lumen diameter and stent strut thickness were non-significant with maximum mean difference of approximately 70 ​μm. We found no significant degradation in CT number accuracy or spatial resolution due to cardiac motion. The results demonstrate the potential of spectral UHR coronary CT angiography enabled by Si-PCD. Recent improvements in CT detector technology have led to smaller detector pixels resolving frequencies beyond 20 lp/cm and enabled ultra-high-resolution CT. Silicon-based photon-counting detector (PCD) CT is one such technology that promises improved spatial and spectral resolution. However, when the detector pixel sizes are reduced, the impact of cardiac motion on CT images becomes more pronounced. we investigated the effects cardiac motion on the image quality of a clinical prototype Si-PCD scanner in a dynamic heart phantom at 60 bpm. We did not observe a significant difference in CT number accuracy and in-stent lumen measurements at rest and motion. [ABSTRACT FROM AUTHOR]

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. Photon-counting CT is an emerging technology with the potential to substantially improve cardiovascular imaging. [ABSTRACT FROM AUTHOR]

Abstract Purpose To evaluate the performance and clinical feasibility of 0.25 mm resolution mode of a dual-energy photon-counting detector (PCD) computed tomography (CT) system for coronary stent imaging and to compare the results to state-of-the-art dual-energy energy-integrating detector (EID) CT. Materials and methods Coronary stents with different diameters (2.0–4.0 mm) were examined inside a coronary artery phantom consisting of plastic tubes filled with iodine-based and gadolinium-based contrast material diluted to approximate clinical concentrations (n = 18). EID images were acquired using 2nd and 3rd generation dual-source CT systems (SOMATOM Flash and SOMATOM Force, Siemens Healthcare) at 0.60 mm (defined as standard-resolution (SR)) isotropic voxel size. Radiation-dose matched PCD images were acquired using a human prototype PCD system (Siemens Healthcare) at 0.50 mm (SR) and 0.25 mm (HR) imaging modes. Images were reconstructed using optimized convolution kernels. Results Dual-energy HR PCD images significantly better stent lumen visualization (median: 69.5%, IQR: 61.2–78.9%) over dual-energy EID, and standard-resolution PCD images (median: 53.2–57.4%, all P < 0.01). HR PCD acquisitions reconstructed at SR image voxel size showed 25.3% lower image noise compared to SR PCD acquisitions (P < 0.001). High-resolution iodine and gadolinium maps, as well as virtual monoenergetic images, were calculated from the PCD data and enabled estimation of contrast agent concentration in the lumen without interference from the coronary stent. Conclusion HR spectral PCD imaging significantly improves coronary stent lumen visibility over dual-energy EID. When the PCD-HR data was reconstructed into standard voxel sizes (0.5 mm isotropic) the image noise decreased by 25% compared to SR acquisition of PCD. Both dual-energy systems were consistent in estimating contrast agent concentrations. [ABSTRACT FROM AUTHOR]

Abstract Background CT SQUEEZ is a new automated technique to evaluate regional endocardial strain by tracking features on the endocardium from 4D cine CT data. The objective of this study was to measure the range of endocardial regional strain (RS CT) values obtained with CT SQUEEZ in the normal human left ventricle (LV) from standard clinical 4D coronary CTA exams. Methods RS CT was measured over the heart cycle in 25 humans with normal LV function using cine CT from three vendors. Mean and standard deviation of RS CT values were computed in 16 AHA LV segments to estimate the range of values expected in the normal LV. Results Curves describing RS CT vs. time were consistent between subjects. There was a slight gradient of decreasing minimum RS CT value (increased shortening) from the base to the apex of the heart. Mean RS CT values at end-systole were: base = −32% ± 1%, mid = −33% ± 1%, apex = −36% ± 1%. The standard deviation of the minimum systolic RS CT in each segment over all subjects was 5%. The average time to reach maximum shortening was 34% of the RR interval. Conclusions Regional strain (RS CT) can be rapidly obtained from standard gated coronary CCTA protocols using 4DCT SQUEEZ processing. We estimate that 95% of normal LV end-systolic RS CT values will fall between −23% and −43%; therefore, we hypothesize that an RS CT value higher than −23% will indicate a hypokinetic segment in the human heart. [ABSTRACT FROM AUTHOR]

Background: Optimal lead positioning is an important determinant of cardiac resynchronization therapy (CRT) response.Objective: The purpose of this study was to evaluate cardiac computed tomography (CT) selection of the optimal epicardial vein for left ventricular (LV) lead placement by targeting regions of late mechanical activation and avoiding myocardial scar.Methods: Eighteen patients undergoing CRT upgrade with existing pacing systems underwent preimplant electrocardiogram-gated cardiac CT to assess wall thickness, hypoperfusion, late mechanical activation, and regions of myocardial scar by the derivation of the stretch quantifier for endocardial engraved zones (SQUEEZ) algorithm. Cardiac venous anatomy was mapped to individualized American Heart Association (AHA) bull's-eye plots to identify the optimal venous target and compared with acute hemodynamic response (AHR) in each coronary venous target using an LV pressure wire.Results: Fifteen data sets were evaluable. CT-SQUEEZ-derived targets produced a similar mean AHR compared with the best achievable AHR (20.4% ± 13.7% vs 24.9% ± 11.1%; P = .36). SQUEEZ-derived guidance produced a positive AHR in 92% of target segments, and pacing in a CT-SQUEEZ target vein produced a greater clinical response rate vs nontarget segments (90% vs 60%).Conclusion: Preprocedural CT-SQUEEZ-derived target selection may be a valuable tool to predict the optimal venous site for LV lead placement in patients undergoing CRT upgrade. [ABSTRACT FROM AUTHOR]

Objectives Late contrast enhancement CT (LCE-CT) visualizes the presence of myocardial infarcts. Differentiation of the contrast-enhanced infarct from blood pool is challenging. We developed a novel method using data from first pass CT angiography (CTA) imaging to enable automatic infarct detection. Materials and methods A canine model of myocardial infarction was produced in 11 animals. Two months later, first pass CTA (90 kVp) and LCE-CT (dual energy 90 kVp/150 kVp tin filtered) were performed. Late gadolinium enhancement MRI was used as reference standard. The CTA and LCE-CT were co-registered using a fully automatic non-rigid method based on curved B-splines. The method allowed for limited elastic deformation and the considerable differences in attenuation between first-pass and delayed image. The blood pool was easily identified on the CTA image by high attenuation. Because CTA and LCE-CT were registered, the blood pool segmentation can be directly transferred to the LCE-CT – thereby solving the key problem of infarct/blood pool differentiation. The remaining segmentation of infarcted vs. noninfarcted myocardium was performed using a threshold. Automatic and MRI-guided expert segmentations of LCE-CT infarcts were compared to each other on volume and area basis (intraclass correlation coefficient, ICC) and on voxel basis (dice similarity coefficient, DSC between automatic and expert CT segmentation). CT infarct volumes were compared with the reference standard MRI. Results The infarcts were mainly subendocardial (81%) and relatively small (median MRI infarct mass 7.4 g). The automatic segmentation showed excellent agreement with expert segmentation on volume and area measurements (ICC = 0.96 and 0.87, respectively). DSC showed moderately good agreement (DSC = 0.47). Compared to MRI there was modest agreement (ICC = 0.62) and excellent correlation (R = 0.9). Manual interaction was less than 1 min per exam. Conclusion We propose an automatic method for infarct segmentation on LCE-CT using multiphase CT information, which showed excellent agreement with expert readers and favorable correlation with MRI. [ABSTRACT FROM AUTHOR]

Objectives Late contrast enhancement visualizes myocardial infarction, but the contrast to noise ratio (CNR) is low using conventional CT. The aim of this study was to determine if spectral CT can improve imaging of myocardial infarction. Materials and Methods A canine model of myocardial infarction was produced in 8 animals (90-min occlusion, reperfusion). Later, imaging was performed after contrast injection using CT at 90 kVp/150 kVpSn. The following reconstructions were evaluated: Single energy 90 kVp, mixed, iodine map, multiple monoenergetic conventional and monoenergetic noise optimized reconstructions. Regions of interest were measured in infarct and remote regions to calculate contrast to noise ratio (CNR) and Bhattacharya distance (a metric of the differentiation between regions). Blinded assessment of image quality was performed. The same reconstruction methods were applied to CT scans of four patients with known infarcts. Results For animal studies, the highest CNR for infarct vs. myocardium was achieved in the lowest keV (40 keV) VMo images (CNR 4.42, IQR 3.64–5.53), which was superior to 90 kVp, mixed and iodine map (p = 0.008, p = 0.002, p < 0.001, respectively). Compared to 90 kVp and iodine map, the 40 keV VMo reconstructions showed significantly higher histogram separation (p = 0.042 and p < 0.0001, respectively). The VMo reconstructions showed the highest rate of excellent quality scores. A similar pattern was seen in human studies, with CNRs for infarct maximized at the lowest keV optimized reconstruction (CNR 4.44, IQR 2.86–5.94). Conclusions Dual energy in conjunction with noise-optimized monoenergetic post-processing improves CNR of myocardial infarct delineation by approximately 20–25%. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic poses unprecedented and unique challenges to gastroenterologists eager to maintain clinical practice, patients' health, and their own physical/mental well-being. We aimed to estimate the prevalence and critical determinants of psychological distress in gastroenterologists during the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]