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Impending major hardware advances in cardiac CT include three areas: ultra-high-resolution (UHR) CT, photon-counting CT, and phase-contrast CT. Cardiac CT is a particularly demanding CT application that requires a high degree of temporal resolution, spatial resolution, and soft-tissue contrast in a moving structure. In this review, cardiac CT is used to highlight the strengths of these technical advances. UHR CT improves visualization of calcified and stented vessels but may result in increased noise and radiation exposure. Photon-counting CT uses multiple photon energies to reduce artifacts, improve contrast resolution, and perform material decomposition. Finally, phase-contrast CT uses x-ray refraction properties to improve spatial and soft-tissue contrast. This review describes these hardware advances in CT and their relevance to cardiovascular imaging. © RSNA, 2020

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.

To evaluate the performance of photon-counting detector (PCD) computed tomography (CT) for coronary artery calcium (CAC) score imaging at standard and reduced radiation doses compared to conventional energy-integrating detector (EID) CT. A dedicated cardiac CT phantom, ten ex vivo human hearts, and ten asymptomatic volunteers underwent matched EID and PCD CT scans at different dose settings without ECG gating. CAC score, contrast, and contrast-to-noise ratio (CNR) were calculated in the cardiac CT phantom. CAC score accuracy and reproducibility was assessed in the ex vivo hearts. Standard radiation dose (120 kVp, reference mAs = 80) in vivo CAC scans were compared against dose-reduced CAC scans (75% dose reduction; reference mAs = 20) for image quality and CAC score reproducibility. Interstudy agreement was assessed by using intraclass correlation (ICC), linear regression, and Bland–Altman analysis with 95% confidence interval limits of agreement (LOA). Calcium-soft tissue contrast and CNR were significantly higher for the PCD CAC scans in the cardiac CT phantom (all P

The aim of this study was to assess the clinical feasibility, image quality, and radiation dose implications of 0.25-mm imaging mode in a cohort of humans, achieved by dividing the photon-counting detector (PCD) size in half compared with standard-resolution photon-counting computed tomography (CT) (0.5 mm).In this technical feasibility study, a whole-body prototype PCD-CT scanner was studied in the 0.25 mm detector mode (measured at isocenter). A high-resolution PCD-CT protocol was first tested in phantom and canine studies in terms of image noise and spatial resolution. Then, 8 human subjects (mean age, 58 ± 8 years; 2 men) underwent axial PCD 0.25-mm scans of the brain, the thorax, and at the level of the upper left kidney. Filtered backprojection reconstruction was performed with a sharp kernel (B70) for standard-resolution and high-resolution data at 0.5-mm isotropic image voxel. High-resolution data, in addition, were reconstructed with an ultrasharp kernel (U70) at 0.25-mm isotropic voxels.Image reconstructions from the PCD 0.25-mm detector system led to an improvement in resolution from 9 to 18 line pairs/cm in a line pair phantom. Modulation transfer function improved from 9.5 to 15.8 line pairs/cm at 10% modulation transfer function. When fully exploiting this improvement, image noise increased by 75% compared with dose-matched 0.5-mm slice PCD standard-resolution acquisition. However, when comparing with standard-resolution data at same in-plane resolution and slice thickness, the PCD 0.25-mm detector mode showed 19% less image noise in phantom, animal, and human scans.High-resolution photon-counting CT in humans showed improved image quality in terms of spatial resolution and image noise compared with standard-resolution photon-counting.

Recent improvements in cardiac computed tomography (CCT) allow for whole-heart functional studies to be acquired at low radiation dose (

PURPOSE: To determine whether the type of VHL gene pathogenic variant influences the growth rate or CT enhancement values of renal lesions in VHL patients. MATERIALS AND METHODS: Thirty-two VHL patients (19 male) were selected from a prospectively maintained imaging database for patients that underwent surgical tumor resection between 2014 and 2016. One hundred and eleven VHL lesions were marked for resection and pathology analysis. Whole lesion volumetric segmentation was performed on nephrographic phase of the two most recent contrast-enhanced CT scans before surgery. Intensity distribution curves were obtained from segmentations. A linear mixed model, accounting for within-patient correlations, was used to compare the growth and enhancement differences between different germline pathogenic variant types. RESULTS: There was no significant difference for the lesions’ total growth between different germline pathogenic variants (P value = 0.78). The median growth rate for all lesions was 1.7 cc/year (IQR 0.5, 3.9) with a baseline median size of 4.1 cm(3) (IQR 1.7, 11.7). In complex lesions, the solid portion of the tumor demonstrated a higher growth rate (1.6 cc/year) than cystic portions (0.02 cc/year) which stayed relatively unchanged. Only one pathogenic variant (Splice donor) showed some levels of difference in its relative enhancement from other subtypes. CONCLUSION: The type of germline pathogenic variant on the VHL gene does not affect the growth rate or CT enhancement values of renal lesions in patients with VHL. The absolute growth rate of these tumors may be used in the scheduling of follow-up studies.

The purpose of this study was to evaluate image quality of a spectral photon-counting detector (PCD) computed tomography (CT) system for evaluation of major arteries of the head and neck compared with conventional single-energy CT scans using energy-integrating detectors (EIDs).In this institutional review board-approved study, 16 asymptomatic subjects (7 men) provided informed consent and received both PCD and EID contrast-enhanced CT scans of the head and neck (mean age, 58 years; range, 46-75 years). Tube settings were (EID: 120 kVp/160 mA vs PCD: 140 kVp/108 mA) for all volunteers. Quantitative analysis included measurements of mean attenuation, image noise, and contrast-to-noise ratio (CNR). Spectral PCD data were used to reconstruct virtual monoenergetic images and iodine maps. A head phantom was used to validate iodine concentration measurements in PCD images only. Two radiologists blinded to detector type independently scored the image quality of different segments of the arteries, as well as diagnostic acceptability, image noise, and severity of artifacts of the PCD and EID images. Reproducibility was assessed with intraclass correlation coefficient. Linear mixed models that account for within-subject correlation of analyzed arterial segments were used. Linear regression and Bland-Altman analysis with 95% limits of agreement were used to calculate the accuracy of material decomposition.Photon-counting detector image quality scores were significantly higher compared with EID image quality scores with lower image noise (P0.01) and less image artifacts (P0.001). Photon-counting detector image noise was 9.1% lower than EID image noise (8.0 ± 1.3 HU vs 8.8 ± 1.5 HU, respectively, P0.001). Arterial segments showed artifacts on EID images due to beam hardening that were not present on PCD images. On PCD images of the head phantom, there was excellent correlation (R = 0.998) between actual and calculated iodine concentrations without significant bias (bias: -0.4 mg/mL [95% limits of agreements: -1.1 to 0.4 mg/mL]). Iodine maps had 20.7% higher CNR compared with nonspectral PCD (65.2 ± 9.0 vs 54.0 ± 4.5, P = 0.01), and virtual monoenergetic image at 70 keV showed similar CNR to nonspectral images (52.6 ± 4.2 vs 54.0 ± 4.5, P = 0.39).Photon-counting CT has the potential to improve the image quality of carotid and intracranial CT angiography compared with single-energy EID CT.

BACKGROUND AND PURPOSE: Photon-counting detectors offer the potential for improved image quality for brain CT but have not yet been evaluated in vivo. The purpose of this study was to compare photon-counting detector CT with conventional energy-integrating detector CT for human brains. MATERIALS AND METHODS: Radiation dose–matched energy-integrating detector and photon-counting detector head CT scans were acquired with standardized protocols (tube voltage/current, 120 kV(peak)/370 mAs) in both an anthropomorphic head phantom and 21 human asymptomatic volunteers (mean age, 58.9 ± 8.5 years). Photon-counting detector thresholds were 22 and 52 keV (low-energy bin, 22–52 keV; high-energy bin, 52–120 keV). Image noise, gray matter, and white matter signal-to-noise ratios and GM–WM contrast and contrast-to-noise ratios were measured. Image quality was scored by 2 neuroradiologists blinded to the CT detector type. Reproducibility was assessed with the intraclass correlation coefficient. Energy-integrating detector and photon-counting detector CT images were compared using a paired t test and the Wilcoxon signed rank test. RESULTS: Photon-counting detector CT images received higher reader scores for GM–WM differentiation with lower image noise (all P < .001). Intrareader and interreader reproducibility was excellent (intraclass correlation coefficient, ≥0.86 and 0.79, respectively). Quantitative analysis showed 12.8%–20.6% less image noise for photon-counting detector CT. The SNR of photon-counting detector CT was 19.0%–20.0% higher than of energy-integrating detector CT for GM and WM. The contrast-to-noise ratio of photon-counting detector CT was 15.7% higher for GM–WM contrast and 33.3% higher for GM–WM contrast-to-noise ratio. CONCLUSIONS: Photon-counting detector brain CT scans demonstrated greater gray–white matter contrast compared with conventional CT. This was due to both higher soft-tissue contrast and lower image noise for photon-counting CT.

Purpose To demonstrate the feasibility of spectral imaging using photon-counting detector (PCD) x-ray computed tomography (CT) for simultaneous material decomposition of three contrast agents in vivo in a large animal model. Methods This Institutional Animal Care and Use Committee-approved study used a canine model. Bismuth subsalicylate was administered orally 24–72 h before imaging. PCD CT was performed during intravenous administration of 40–60 ml gadoterate meglumine; 3.5 min later, iopamidol 370 was injected intravenously. Renal PCD CT images were acquired every 2 s for 5–6 min to capture the wash-in and wash-out kinetics of the contrast agents. Least mean squares linear material decomposition was used to calculate the concentrations of contrast agents in the aorta, renal cortex, renal medulla and renal pelvis. Results Using reference vials with known concentrations of materials, we computed molar concentrations of the various contrast agents during each phase of CT scanning. Material concentration maps allowed simultaneous quantification of both arterial and delayed renal enhancement in a single CT acquisition. The accuracy of the material decomposition algorithm in a test phantom was −0.4 ± 2.2 mM, 0.3 ± 2.2 mM for iodine and gadolinium solutions, respectively. Peak contrast concentration of gadolinium and iodine in the aorta, renal cortex, and renal medulla were observed 16, 24, and 60 s after the start each injection, respectively. Conclusion Photon-counting spectral CT allowed simultaneous material decomposition of multiple contrast agents in vivo. Besides defining contrast agent concentrations, tissue enhancement at multiple phases was observed in a single CT acquisition, potentially obviating the need for multiphase CT scans and thus reducing radiation dose.

To determine the feasibility of dual—contrast agent imaging of the heart using photon-counting detector (PCD) computed tomography (CT) to simultaneously assess both first-pass and late enhancement of the myocardium. An occlusion-reperfusion canine model of myocardial infarction was used. Gadolinium-based contrast was injected 10 min prior to PCD CT. Iodinated contrast was infused immediately prior to PCD CT, thus capturing late gadolinium enhancement as well as first-pass iodine enhancement. Gadolinium and iodine maps were calculated using a linear material decomposition technique and compared to single-energy (conventional) images. PCD images were compared to in vivo and ex vivo magnetic resonance imaging (MRI) and histology. For infarct versus remote myocardium, contrast-to-noise ratio (CNR) was maximal on late enhancement gadolinium maps (CNR 9.0 ± 0.8, 6.6 ± 0.7, and 0.4 ± 0.4, p

To evaluate the feasibility of using a whole-body photon-counting detector (PCD) CT scanner for low-dose lung cancer screening compared to a conventional energy integrating detector (EID) system. Radiation dose-matched EID and PCD scans of the COPDGene 2 phantom were acquired at different radiation dose levels (CTDIvol: 3.0, 1.5, and 0.75 mGy) and different tube voltages (120, 100, and 80 kVp). EID and PCD images were compared for quantitative Hounsfield unit (HU) accuracy, noise levels, and contrast-to-noise ratios (CNR) for detection of ground-glass nodules (GGN) and emphysema. The PCD HU accuracy was better than EID for water at all scan parameters. PCD HU stability for lung, GGN and emphysema regions were superior to EID and PCD attenuation values were more reproducible than EID for all scan parameters (all P < 0.01), while HUs for lung, GGN and emphysema ROIs changed significantly for EID with decreasing dose (all P < 0.001). PCD showed lower noise levels at the lowest dose setting at 120, 100 and 80 kVp (15.2 ± 0.3 HU versus 15.8 ± 0.2 HU, P = 0.03; 16.1 ± 0.3 HU versus 18.0 ± 0.4 HU, P = 0.003; and 16.1 ± 0.3 HU versus 17.9 ± 0.3 HU, P = 0.001, respectively), resulting in superior CNR for evaluation of GGNs and emphysema at 100 and 80 kVp. PCD provided better HU stability for lung, ground-glass, and emphysema-equivalent foams at lower radiation dose settings with better reproducibility than EID. Additionally, PCD showed up to 10% less noise, and 11% higher CNR at 0.75 mGy for both 100 and 80 kVp. PCD technology may help reduce radiation exposure in lung cancer screening while maintaining diagnostic quality.

Purpose To determine reader and computed tomography (CT) scan variability for measurement of coronary plaque volume. Materials and Methods This HIPAA-compliant study followed Standards for Reporting of Diagnostic Accuracy guidelines. Baseline coronary CT angiography was performed in 40 prospectively enrolled subjects (mean age, 67 years ± 6 [standard deviation]) with asymptomatic hyperlipidemia by using a 320-detector row scanner (Aquilion One Vision; Toshiba, Otawara, Japan). Twenty of these subjects underwent coronary CT angiography repeated on a separate day with the same CT scanner (Toshiba, group 1); 20 subjects underwent repeat CT performed with a different CT scanner (Somatom Force; Siemens, Forchheim, Germany [group 2]). Intraclass correlation coefficients (ICCs) and Bland-Altman analysis were used to assess interreader, intrareader, and interstudy reproducibility. Results Baseline and repeat coronary CT angiography scans were acquired within 19 days ± 6. Interreader and intrareader agreement rates were high for total, calcified, and noncalcified plaques for both CT scanners (all ICCs ≥ 0.96) without bias. Scanner variability was ±18.4% (coefficient of variation) with same-vendor follow-up. However, scanner variability increased to ±29.9% with different-vendor follow-up. The sample size to detect a 5% change in noncalcified plaque volume with 90% power and an α error of .05 was 286 subjects for same-CT scanner follow-up and 753 subjects with different-vendor follow-up. Conclusion State-of-the-art coronary CT angiography with same-vendor follow-up has good scan-rescan reproducibility, suggesting a role of coronary CT angiography in monitoring coronary artery plaque response to therapy. Differences between coronary CT angiography vendors resulted in lower scan-rescan reproducibility.

To evaluate the performance of a prototype photon-counting detector (PCD) computed tomography (CT) system for abdominal CT in humans and to compare the results with a conventional energy-integrating detector (EID).The study was HIPAA-compliant and institutional review board-approved with informed consent. Fifteen asymptomatic volunteers (seven men; mean age, 58.2 years ± 9.8 [standard deviation]) were prospectively enrolled between September 2 and November 13, 2015. Radiation dose-matched delayed contrast agent-enhanced spiral and axial abdominal EID and PCD scans were acquired. Spiral images were scored for image quality (Wilcoxon signed-rank test) in five regions of interest by three radiologists blinded to the detector system, and the axial scans were used to assess Hounsfield unit accuracy in seven regions of interest (paired t test). Intraclass correlation coefficient (ICC) was used to assess reproducibility. PCD images were also used to calculate iodine concentration maps. Spatial resolution, noise-power spectrum, and Hounsfield unit accuracy of the systems were estimated by using a CT phantom.In both systems, scores were similar for image quality (median score, 4; P = .19), noise (median score, 3; P = .30), and artifact (median score, 1; P = .17), with good interrater agreement (image quality, noise, and artifact ICC: 0.84, 0.88, and 0.74, respectively). Hounsfield unit values, spatial resolution, and noise-power spectrum were also similar with the exception of mean Hounsfield unit value in the spinal canal, which was lower in the PCD than the EID images because of beam hardening (20 HU vs 36.5 HU; P.001). Contrast-to-noise ratio of enhanced kidney tissue was improved with PCD iodine mapping compared with EID (5.2 ± 1.3 vs 4.0 ± 1.3; P.001).The performance of PCD showed no statistically significant difference compared with EID when the abdomen was evaluated in a conventional scan mode. PCD provides spectral information, which may be used for material decomposition.

Characterization of anatomical change and other differences is important in sequential computed tomography (CT) imaging, where a high-fidelity patient-specific prior image is typically present, but is not used, in the reconstruction of subsequent anatomical states. Here, we introduce a penalized likelihood (PL) method called reconstruction of difference (RoD) to directly reconstruct a difference image volume using both the current projection data and the (unregistered) prior image integrated into the forward model for the measurement data. The algorithm utilizes an alternating minimization to find both the registration and reconstruction estimates. This formulation allows direct control over the image properties of the difference image, permitting regularization strategies that inhibit noise and structural differences due to inconsistencies between the prior image and the current data. Additionally, if the change is known to be local, RoD allows local acquisition and reconstruction, as opposed to traditional model-based approaches that require a full support field of view (or other modifications). We compared the performance of RoD to a standard PL algorithm, in simulation studies and using test-bench cone-beam CT data. The performances of local and global RoD approaches were similar, with local RoD providing a significant computational speedup. In comparison across a range of data with differing fidelity, the local RoD approach consistently showed lower error (with respect to a truth image) than PL in both noisy data and sparsely sampled projection scenarios. In a study of the prior image registration performance of RoD, a clinically reasonable capture ranges were demonstrated. Lastly, the registration algorithm had a broad capture range and the error for reconstruction of CT data was 35% and 20% less than filtered back-projection for RoD and PL, respectively. The RoD has potential for delivering high-quality difference images in a range of sequential clinical scenarios including image-guided surgeries and treatments where accurate and quantitative assessments of anatomical change is desired.

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.

PURPOSE: To determine whether objective volumetric whole-lesion apparent diffusion coefficient (ADC) distribution analysis improves upon the capabilities of conventional subjective small region-of-interest (ROI) ADC measurements for prediction of renal cell carcinoma (RCC) subtype. METHODS: This IRB-approved study retrospectively enrolled 55 patients (152 tumors). Diffusion-weighted imaging DWI was acquired at b values of 0, 250, and 800 s/mm(2) on a 1.5T system (Aera, Siemens Healthcare). Whole-lesion measurements were performed by a research fellow and reviewed by a fellowship-trained radiologist. Mean, median, skewness, kurtosis, and every 5th percentile ADCs were determined from the whole-lesion histogram. Linear mixed models that accounted for within-subject correlation of lesions were used to compare ADCs among RCC subtypes. Receiver-operating characteristic (ROC) curve analysis with optimal cutoff points from the Youden index was used to test the ability of ADCs to differentiate clear cell RCC (ccRCC), papillary RCC (pRCC), and oncocytoma subtypes. RESULTS: Whole-lesion ADC values were significantly different between pRCC and ccRCC, and between pRCC and oncocytoma, demonstrating strong ability to differentiate subtypes across the quantiles (both P < 0.001). Best percentile ROC analysis demonstrated AUC values of 95.2 for ccRCC vs. pRCC; 67.6 for oncocytoma vs. ccRCC; and 95.8 for oncocytoma vs. pRCC. Best percentile ROC analysis further indicated model sensitivities/specificities of 84.5%/93.1% for ccRCC vs. pRCC; 100.0%/10.3% for oncocytoma vs. ccRCC; and 88.5%/ 93.1% for oncocytoma vs. pRCC. CONCLUSION: The objective methodology of whole-lesion volumetric ADC measurements maintains the sensitivity/ specificity of conventional expert-based ROI analysis, provides information on lesion heterogeneity, and reduces observer bias.

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.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.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.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.

The objective of this study was to investigate the correlation between local myocardial function estimates from CT and myocardial strain from tagged MRI in the same heart. Accurate detection of regional myocardial dysfunction can be an important finding in the diagnosis of functionally significant coronary artery disease. Tagged MRI is currently a reference standard for noninvasive regional myocardial function analysis; however, it has practical drawbacks. We have developed a CT imaging protocol and automated image analysis algorithm for estimating regional cardiac function from a few heartbeats. This method tracks the motion of the left ventricular (LV) endocardial surface to produce local function maps: we call the method Stretch Quantification of Endocardial Engraved Zones (SQUEEZ). Myocardial infarction was created by ligation of the left anterior descending coronary artery for 2 h followed by reperfusion in canine models. Tagged and cine MRI scans were performed during the reperfusion phase and first-pass contrast enhanced CT scans were acquired. The average delay between the CT and MRI scans was

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.

PURPOSE: Resting regional wall motion abnormality (RWMA) has significant prognostic value beyond the findings of computed tomography (CT) coronary angiography. Stretch quantification of endocardial engraved zones (SQUEEZ) has been proposed as a measure of regional cardiac function. The purpose of the work reported here was to determine the effect of lowering the radiation dose on the precision of automatic SQUEEZ assessments of RWMA. METHODS: Chronic myocardial infarction (MI) was created by a two-hour occlusion of the left anterior descending coronary artery in 10 swine (heart rates 80–100, Ejection Fraction 25%–57%). CT was performed 5–11 months post infarct using first-pass contrast enhanced segmented cardiac function scans on a 320-detector row scanner at 80 kVp / 500 mA. Images were reconstructed at end diastole and end systole with both filtered back projection and using the “standard” Adaptive Iterative Dose Reduction (AIDR) algorithm. For each acquisition, 9 lower dose acquisitions were created. End systolic myocardial function maps were calculated using SQUEEZ for all noise levels and contrast-to-noise ratio (CNR) between the left ventricle blood and myocardium was calculated as a measure of image quality. RESULTS: For acquisitions with CNR>4, SQUEEZ could be estimated with a precision of ±0.04 (p

Purpose To investigate whether photon-counting detector (PCD) technology can improve dose-reduced chest computed tomography (CT) image quality compared with that attained with conventional energy-integrating detector (EID) technology in vivo. Materials and Methods This was a HIPAA-compliant institutional review board-approved study, with informed consent from patients. Dose-reduced spiral unenhanced lung EID and PCD CT examinations were performed in 30 asymptomatic volunteers in accordance with manufacturer-recommended guidelines for CT lung cancer screening (120-kVp tube voltage, 20-mAs reference tube current-time product for both detectors). Quantitative analysis of images included measurement of mean attenuation, noise power spectrum (NPS), and lung nodule contrast-to-noise ratio (CNR). Images were qualitatively analyzed by three radiologists blinded to detector type. Reproducibility was assessed with the intraclass correlation coefficient (ICC). McNemar, paired t, and Wilcoxon signed-rank tests were used to compare image quality. Results Thirty study subjects were evaluated (mean age, 55.0 years ± 8.7 [standard deviation]; 14 men). Of these patients, 10 had a normal body mass index (BMI) (BMI range, 18.5-24.9 kg/m

PURPOSE: We present a denoising algorithm designed for a whole‐body prototype photon‐counting computed tomography (PCCT) scanner with up to 4 energy thresholds and associated energy‐binned images. METHODS: Spectral PCCT images can exhibit low signal to noise ratios (SNRs) due to the limited photon counts in each simultaneously‐acquired energy bin. To help address this, our denoising method exploits the correlation and exact alignment between energy bins, adapting the highly‐effective block‐matching 3D (BM3D) denoising algorithm for PCCT. The original single‐channel BM3D algorithm operates patch‐by‐patch. For each small patch in the image, a patch grouping action collects similar patches from the rest of the image, which are then collaboratively filtered together. The resulting performance hinges on accurate patch grouping. Our improved multi‐channel version, called BM3D_PCCT, incorporates two improvements. First, BM3D_PCCT uses a more accurate shared patch grouping based on the image reconstructed from photons detected in all 4 energy bins. Second, BM3D_PCCT performs a cross‐channel decorrelation, adding a further dimension to the collaborative filtering process. These two improvements produce a more effective algorithm for PCCT denoising. RESULTS: Preliminary results compare BM3D_PCCT against BM3D_Naive, which denoises each energy bin independently. Experiments use a three‐contrast PCCT image of a canine abdomen. Within five regions of interest, selected from paraspinal muscle, liver, and visceral fat, BM3D_PCCT reduces the noise standard deviation by 65.0%, compared to 40.4% for BM3D_Naive. Attenuation values of the contrast agents in calibration vials also cluster much tighter to their respective lines of best fit. Mean angular differences (in degrees) for the original, BM3D_Naive, and BM3D_PCCT images, respectively, were 15.61, 7.34, and 4.45 (iodine); 12.17, 7.17, and 4.39 (galodinium); and 12.86, 6.33, and 3.96 (bismuth). CONCLUSION: We outline a multi‐channel denoising algorithm tailored for spectral PCCT images, demonstrating improved performance over an independent, yet state‐of‐the‐art, single‐channel approach.

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., Graphical abstract

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.

Sequential CT studies present an excellent opportunity to apply prior-image-based reconstruction (PIBR) methods that leverage high-fidelity prior imaging studies to improve image quality and/or reduce x-ray exposure in subsequent studies. One major obstacle in using PIBR is that the initial and subsequent studies are often performed on different scanners (e.g. diagnostic CT followed by CBCT for interventional guidance); this results in mismatch in attenuation values due to hardware and software differences. While improved artifact correction techniques can potentially mitigate such differences, the correction is often incomplete. Here, we present an alternate strategy where the PIBR itself is used to mitigate these differences. We define a new penalty for the previously introduced PIBR called Reconstruction of Difference (RoD). RoD differs from many other PIBRs in that it reconstructs only changes in the anatomy (vs. reconstructing the current anatomy). Direct regularization of the difference image in RoD provides an opportunity to selectively penalize spatial frequencies of the difference image (e.g. low frequency differences associated with attenuation offsets and shading artifacts) without interfering with the variations in unchanged background image. We leverage this flexibility and introduce a novel regularization strategy using a generalized Fourier penalty within the RoD framework and develop the modified reconstruction algorithm. We evaluate the performance of the new approach in both simulation studies and in physical CBCT test-bench data. We find that generalized Fourier penalty can be highly effective in reducing low-frequency x-ray artifacts through selective suppression of spatial frequencies in the reconstructed difference image.

Air embolism is an infrequent but potentially catastrophic complication. It could be a complication of invasive procedures including surgery, central line placement, positive pressure ventilation, trauma, hemodialysis, pacemaker placement, cardiac ablation, and decompression sickness. Usually, it does not cause any hemodynamic complication. In rare cases, it could lodge in the heart and cause cardiac arrest. We present a case of an 82-year-old white female who underwent computed tomography (CT) guided biopsy of right lung pulmonary nodule. When she was turned over after the lung biopsy, she became unresponsive and developed cardiopulmonary arrest. She underwent successful resuscitation and ultimately was intubated. CT chest was performed immediately after resuscitation which showed frothy air dense material in the left atrium and one of the right pulmonary veins suggesting a Broncho venous fistula with air embolism. Although very rare, air embolism could be catastrophic resulting in cardiac arrest. Supportive care including mechanical ventilation, vasopressors, volume resuscitation, and supplemental oxygen is the initial management. Patients with cardiac, neurological, or respiratory complications benefit from hyperbaric oxygen therapy.

Purpose: To evaluate the feasibility of using a whole-body photon counting detector (PCD) CT scanner for low dose lung cancer screening compared to a conventional energy integrating detector (EID) system. Methods: Radiation dose-matched EID and PCD scans of the COPDGene 2 phantom and 2 human volunteers were acquired. Phantom images were acquired at different radiation dose levels (CTDIvol: 3.0, 1.5, and 0.75 mGy) and different tube voltages (120, 100, and 80 kVp), while human images were acquired at vendor recommended low-dose lung cancer screening settings. EID and PCD images were compared for quantitative Hounsfield unit accuracy, noise levels, and contrast-to-noise ratios (CNR) for detection of ground-glass nodules (GGNs) and emphysema. Results: The PCD Hounsfield unit accuracy was better for water at all scan parameters, and for lung, GGN and emphysema equivalent regions of interest (ROIs) at 1.5 and 0.75 mGy. PCD attenuation accuracy was more consistent for all scan parameters (all P

Image registration has been proposed as an automatic method for recovering cardiac displacement fields from Tagged Magnetic Resonance Imaging (tMRI) sequences. Initially performed as a set of pairwise registrations, these techniques have evolved to the use of 3D+t deformation models, requiring metrics of joint image alignment (JA). However, only linear combinations of cost functions defined with respect to the first frame have been used. In this paper, we have applied k-Nearest Neighbors Graphs (kNNG) estimators of the -entropy (H ) to measure the joint similarity between frames, and to combine the information provided by different cardiac views in an unified metric. Experiments performed on six subjects showed a significantly higher accuracy (p < 0.05) with respect to a standard pairwise alignment (PA) approach in terms of mean positional error and variance with respect to manually placed landmarks. The developed method was used to study strains in patients with myocardial infarction, showing a consistency between strain, infarction location, and coronary occlusion. This paper also presents/nan interesting clinical application of graph-based metric estimators, showing their value for solving practical problems found in medical imaging.