Learned high-resolution cardiac CT imaging from ultra-high-resolution PCD-CT.

Coronary computed tomography angiography (cCTA) is a widely used non-invasive diagnostic exam for patients with coronary artery disease (CAD). However, most clinical CT scanners are limited in spatial resolution from use of energy-integrating detectors (EIDs). Radiological evaluation of CAD is challenging, as coronary arteries are small (3-4 mm diameter) and calcifications within them are highly attenuating, leading to blooming artifacts. As such, this is a task well suited for high spatial resolution. Recently, photon-counting-detector (PCD) CT became commercially available, allowing for ultra-high resolution (UHR) data acquisition. However, PCD-CTs are costly, restricting widespread accessibility. To address this problem, we propose a super resolution convolutional neural network (CNN): ILUMENATE (Improved LUMEN visualization through Artificial super-resoluTion imagEs), creating a high resolution (HR) image simulating UHR PCD-CT. The network was trained and validated using patches extracted from 8 patients with a modified U-Net architecture. Training input and labels consisted of UHR PCD-CT images reconstructed with a smooth kernel degrading resolution (LR input) and sharp kernel (HR label). The network learned the resolution difference and was tested on 5 unseen LR patients. We evaluated network performance quantitatively and qualitatively through visual inspection, line profiles to assess spatial resolution improvements, ROIs for CT number stability and noise assessment, structural similarity index (SSIM), and percent diameter luminal stenosis. Overall, ILUMENATE improved images quantitatively and qualitatively, creating sharper edges more closely resembling reconstructed HR reference images, maintained stable CT numbers with less than 4% difference, reduced noise by 28%, maintained structural similarity (average SSIM = 0.70), and reduced percent diameter stenosis with respect to input images. ILUMENATE demonstrates potential impact for CAD patient management, improving the quality of LR CT images bringing them closer to UHR PCD-CT images.

Improving Stenosis Assessment in Energy Integrating Detector CT via Learned Monoenergetic Imaging Capability.

Coronary CT angiography (cCTA) is a fast non-invasive imaging exam for coronary artery disease (CAD) but struggles with dense calcifications and stents due to blooming artifacts, potentially causing stenosis overestimation. Virtual monoenergetic images (VMIs) at higher keV (e.g., 100 keV) from photon counting detector (PCD) CT have shown promise in reducing blooming artifacts and improving lumen visibility through its simultaneous high-resolution and multi-energy imaging capability. However, most cCTA exams are performed with single-energy CT (SECT) using conventional energy-integrating detectors (EID). Generating VMIs through EID-CT requires advanced multi-energy CT (MECT) scanners and potentially sacrifices temporal resolution. Given these limitations, MECT cCTA exams are not commonly performed on EID-CT and VMIs are not routinely generated. To tackle this, we aim to enhance the multi-energy imaging capability of EID-CT through the utilization of a convolutional neural network to LEarn MONoenergetic imAging from VMIs at Different Energies (LEMONADE). The neural network was trained using ten patient cCTA exams acquired on a clinical PCD-CT (NAEOTOM Alpha, Siemens Healthineers), with 70 keV VMIs as input (which is nominally equivalent to the SECT from EID-CT scanned at 120 kV) and 100 keV VMIs as the target. Subsequently, we evaluated the performance of EID-CT equipped with LEMONADE on both phantom and patient cases (n=10) for stenosis assessment. Results indicated that LEMONADE accurately quantified stenosis in three phantoms, aligning closely with ground truth and demonstrating stenosis percentage area reductions of 13%, 8%, and 9%. In patient cases, it led to a 12.9% reduction in average diameter luminal stenosis when compared to the original SECT without LEMONADE. These outcomes highlight LEMONADE's capacity to enable multi-energy CT imaging, mitigate blooming artifacts, and improve stenosis assessment for the widely available EID-CT. This has a high potential impact as most cCTA exams are performed on EID-CT.

Task-based automatic keV selection: leveraging routine virtual monoenergetic imaging for dose reduction on clinical photon-counting detector CT.

OBJECTIVE: Photon-counting detector (PCD) CT enables routine virtual-monoenergetic image (VMI) reconstruction. We evaluated the performance of an automatic VMI energy level (keV) selection tool on a clinical PCD-CT system in comparison to an automatic tube potential (kV) selection tool from an energy-integrating-detector (EID) CT system from the same manufacturer. Approach: Four torso-shaped phantoms (20-50 cm width) containing iodine (2, 5, and 10-mg/cc) and calcium (100 mg/cc) were scanned on PCD-CT and EID-CT. Dose optimization techniques, task-based VMI energy level and tube-potential selection on PCD-CT (CARE keV) and task-based tube potential selection on EID-CT (CARE kV), were enabled. CT numbers, image noise, and dose-normalized contrast-to-noise ratio (CNRd) were compared. Main results: PCD-CT produced task-specific VMIs at 70, 65, 60, and 55 keV for non-contrast, bone, soft tissue with contrast, and vascular settings, respectively. A 120 kV tube potential was automatically selected on PCD-CT for all scans. In comparison, EID-CT used x-ray tube potentials from 80 kV to 150 kV based on imaging task and phantom size. PCD-CT achieved consistent dose reduction at 9%, 21% and 39% for bone, soft tissue with contrast, and vascular tasks relative to the non-contrast task, independent of phantom size. On EID-CT, dose reduction factor for contrast tasks relative to the non-contrast task ranged from a 65% decrease (vascular task, 70 kV, 20 cm phantom) to a 21% increase (soft tissue with contrast task, 150 kV, 50 cm phantom) due to size-specific tube potential adaptation. PCD-CT CNRd was equivalent to or higher than those of EID-CT for all tasks and phantom sizes, except for the vascular task with 20 cm phantom, where 70 kV EID-CT CNRd outperformed 55 keV PCD-CT images. Significance: PCD-CT produced more consistent CT numbers compared to EID-CT due to standardized VMI output, which greatly benefits standardization efforts and facilitates radiation dose reduction.

3D printed phantom with 12 000 submillimeter lesions to improve efficiency in CT detectability assessment.

BACKGROUND: The detectability performance of a CT scanner is difficult to precisely quantify when nonlinearities are present in reconstruction. An efficient detectability assessment method that is sensitive to small effects of dose and scanner settings is desirable. We previously proposed a method using a search challenge instrument: a phantom is embedded with hundreds of lesions at random locations, and a model observer is used to detect lesions. Preliminary tests in simulation and a prototype showed promising results. PURPOSE: In this work, we fabricated a full-size search challenge phantom with design updates, including changes to lesion size, contrast, and number, and studied our implementation by comparing the lesion detectability from a nonprewhitening (NPW) model observer between different reconstructions at different exposure levels, and by estimating the instrument sensitivity to detect changes in dose. METHODS: Designed to fit into QRM anthropomorphic phantoms, our search challenge phantom is a cylindrical insert 10 cm wide and 4 cm thick, embedded with 12 000 lesions (nominal width of 0.6 mm, height of 0.8 mm, and contrast of -350 HU), and was fabricated using PixelPrint, a 3D printing technique. The insert was scanned alone at a high dose to assess printing accuracy. To evaluate lesion detectability, the insert was placed in a QRM thorax phantom and scanned from 50 to 625 mAs with increments of 25 mAs, once per exposure level, and the average of all exposure levels was used as high-dose reference. Scans were reconstructed with three different settings: filtered-backprojection (FBP) with Br40 and Br59, and Sinogram Affirmed Iterative Reconstruction (SAFIRE) with strength level 5 and Br59 kernel. An NPW model observer was used to search for lesions, and detection performance of different settings were compared using area under the exponential transform of free response ROC curve (AUC). Using propagation of uncertainty, the sensitivity to changes in dose was estimated by the percent change in exposure due to one standard deviation of AUC, measured from 5 repeat scans at 100, 200, 300, and 400 mAs. RESULTS: The printed insert lesions had an average position error of 0.20 mm compared to printing reference. As the exposure level increases from 50 mAs to 625 mAs, the lesion detectability AUCs increase from 0.38 to 0.92, 0.42 to 0.98, and 0.41 to 0.97 for FBP Br40, FBP Br59, and SAFIRE Br59, respectively, with a lower rate of increase at higher exposure level. FBP Br59 performed best with AUC 0.01 higher than SAFIRE Br59 on average and 0.07 higher than FBP Br40 (all P < 0.001). The standard deviation of AUC was less than 0.006, and the sensitivity to detect changes in mAs was within 2% for FBP Br59. CONCLUSIONS: Our 3D-printed search challenge phantom with 12 000 submillimeter lesions, together with an NPW model observer, provide an efficient CT detectability assessment method that is sensitive to subtle effects in reconstruction and is sensitive to small changes in dose.

Histone deacetylase 9-mediated phenotypic transformation of vascular smooth muscle cells is a potential target for treating aortic aneurysm/dissection.

Aortic aneurysm/dissection (AAD) is a serious cardiovascular condition characterized by rapid onset and high mortality rates. Currently, no effective drug treatment options are known for AAD. AAD pathogenesis is associated with the phenotypic transformation and abnormal proliferation of vascular smooth muscle cells (VSMCs). However, endogenous factors that contribute to AAD progression remain unclear. We aimed to investigate the role of histone deacetylase 9 (HDAC9) in AAD pathogenesis. HDAC9 expression was considerably increased in human thoracic aortic dissection specimens. Using RNA-sequencing (RNA-seq) and chromatin immunoprecipitation, we demonstrated that HDAC9 transcriptionally inhibited the expression of superoxide dismutase 2 and insulin-like growth factor-binding protein-3, which are critically involved in various signaling pathways. Furthermore, HDAC9 triggered the transformation of VSMCs from a systolic to synthetic phenotype, increasing their proliferation and migration abilities and suppressing their apoptosis. Consistent with these results, in vivo experiments revealed that TMP195, a pharmacological inhibitor of HDAC9, suppressed the formation of the ß-aminopropionitrile-induced AAD phenotype in mice. Our findings indicate that HDAC9 may be a novel endogenous risk factor that promotes the onset of AAD by mediating the phenotypic transformation of VSMCs. Therefore, HDAC9 may serve as a potential therapeutic target for drug-based AAD treatment. Furthermore, TMP195 holds potential as a therapeutic agent for AAD treatment.

Enhancer of zeste homolog 2 facilitates phenotypic transition of vascular smooth muscle cells leading to aortic aneurysm/dissection.

Thoracic aortic aneurysms (TAAs) are a major cause of death owing to weaker blood vessel walls and higher rupture rates in affected individuals. Vascular smooth muscle cells (VSMCs) are the predominant cell type within the aortic wall and their dysregulation may contribute to TAA progression. Enhancer of zeste homolog 2 (EZH2), a histone methyltransferase, is involved in several pathological processes; however, the biological functions and mechanisms underlying VSMC phenotype transition and vascular intimal hyperplasia remain unclear. The present study aimed to determine the involvement of EZH2 in mediating VSMC function in the development of TAAs. The expression of EZH2 was revealed to be elevated in patients with thoracic aortic dissection and TAA mouse model through western blotting and reverse transcription-quantitative PCR experiments. Subsequently, a mouse model was established using ß-aminopropionitrile. In vitro, EdU labeling, Transwell assay, wound healing assay and hematoxylin-eosin staining revealed that knocking down the Ezh2 gene could reduce the proliferation, invasion, migration, and calcification of mouse primary aortic smooth muscle cells. Flow cytometry analysis found that EZH2 deficiency increased cell apoptosis. Depletion of Ezh2 in mouse primary aortic VSMCs promoted the transformation of VSMCs from a synthetic to a contractile phenotype. Using RNA-sequencing analysis, it was demonstrated that Ezh2 regulated a group of genes, including integrin ß3 (Itgb3), which are critically involved in the extracellular matrix signaling pathway. qChIP found Ezh2 occupies the Itgb3 promoter, thereby suppressing the expression of Itgb3. Ezh2 promotes the invasion and calcification of VSMCs, and this promoting effect is partially reversed by co-knocking down Itgb3. In conclusion, the present study identified a previously unrecognized EZH2-ITGB3 regulatory axis and thus provides novel mechanistic insights into the pathophysiological function of EZH2. EZH2 may thus serve as a potential target for the management of TAAs.

Multiple Kernel Synthesis of Head CT Using a Task-Based Loss Function.

In CT imaging of the head, multiple image series are routinely reconstructed with different kernels and slice thicknesses. Reviewing the redundant information is an inefficient process for radiologists. We address this issue with a convolutional neural network (CNN)-based technique, synthesiZed Improved Resolution and Concurrent nOise reductioN (ZIRCON), that creates a single, thin, low-noise series that combines the favorable features from smooth and sharp head kernels. ZIRCON uses a CNN model with an autoencoder U-Net architecture that accepts two input channels (smooth- and sharp-kernel CT images) and combines their salient features to produce a single CT image. Image quality requirements are built into a task-based loss function with a smooth and sharp loss terms specific to anatomical regions. The model is trained using supervised learning with paired routine-dose clinical non-contrast head CT images as training targets and simulated low-dose (25%) images as training inputs. One hundred unique de-identified clinical exams were used for training, ten for validation, and ten for testing. Visual comparisons and contrast measurements of ZIRCON revealed that thinner slices and the smooth-kernel loss function improved gray-white matter contrast. Combined with lower noise, this increased visibility of small soft-tissue features that would be otherwise impaired by partial volume averaging or noise. Line profile analysis showed that ZIRCON images largely retained sharpness compared to the sharp-kernel input images. ZIRCON combined desirable image quality properties of both smooth and sharp input kernels into a single, thin, low-noise series suitable for both brain and skull imaging.

Motion artifact correction in cardiac CT using cross-phase temporospatial information and synergistic attention gate and spatial transformer sub-networks.

Objectives.To improve quality of coronary CT angiography (CCTA) images using a generalizable motion-correction algorithm.Approach. A neural network with attention gate and spatial transformer (ATOM) was developed to correct coronary motion. Phantom and patient CCTA images (39 males, 32 females, age range 19-92, scan date 02/2020 to 10/2021) retrospectively collected from dual-source CT were used to create training, development, and testing sets corresponding to 140- and 75 ms temporal resolution, with 75 ms images as labels. To test generalizability, ATOM was deployed for locally adaptive motion-correction in both 140- and 75 ms patient images. Objective metrics were used to assess motion-corrupted and corrected phantom and patient images, including structural-similarity-index (SSIM), dice-similarity-coefficient (DSC), peak-signal-noise-ratio (PSNR), and normalized root-mean-square-error (NRMSE). In objective quality assessment, ATOM was compared with several baseline networks, including U-net, U-net plus attention gate, U-net plus spatial transformer, VDSR, and ResNet. Two cardiac radiologists independently interpreted motion-corrupted and -corrected images at 75 and 140 ms in a blinded fashion and ranked diagnostic image quality (worst to best: 1-4, no ties).Main results. ATOM improved quality metrics (p< 0.05) before/after correction: in phantom, SSIM 0.87/0.95, DSC 0.85/0.93, PSNR 19.4/22.5, NRMSE 0.38/0.27; in patient images, SSIM 0.82/0.88, DSC 0.88/0.90, PSNR 30.0/32.0, NRMSE 0.16/0.12. ATOM provided more consistent improvement of objective image quality, compared to the presented baseline networks. The motion-corrected images received better ranks than un-corrected at the same temporal resolution (p< 0.05): 140 ms images 1.65/2.25, and 75 ms images 3.1/3.2. The motion-corrected 75 ms images received the best rank in 65% of testing cases. A fair-to-good inter-reader agreement was observed (Kappa score 0.58).Significance. ATOM reduces motion artifacts, improving visualization of coronary arteries. This algorithm can be used to virtually improve temporal resolution in both single- and dual-source CT.

Photon Counting Versus Energy-integrated Detector CT in Detection of Superior Semicircular Canal Dehiscence.

BACKGROUND: Superior semicircular canal dehiscence (SSCD), an osseous defect overlying the SSC, is associated with a constellation of audiovestibular symptoms. This study sought to compare conventional energy-integrated detector (EID) computed tomography (CT) to photon-counting detector (PCD)-CT in the detection of SSCD. MATERIAL AND METHODS: Included patients were prospectively recruited to undergo a temporal bone CT on both EID-CT and PCD-CT scanners. Two blinded neuroradiologists reviewed both sets of images for 1) the presence or absence of SSCD (graded as present, absent, or indeterminate), and 2) the width of the bone overlying the SSC (if present). Any discrepancies in the presence or absence of SSCD were agreed upon by consensus. RESULTS: In the study 31 patients were evaluated, for a total of 60 individual temporal bones (2 were excluded). Regarding SSCD presence or absence, there was substantial agreement between EID-CT and PCD-CT (k = 0.76; 95% confidence interval, CI 0.54-0.97); however, SSCD was present in only 9 (15.0%) temporal bones on PCD-CT, while EID-CT examinations were interpreted as being positive in 14 (23.3%) temporal bones. This yielded a false positive rate of 8.3% on EID-CT. The bone overlying the SSC was thinner on EID-CT images (0.66 mm; SD = 0.64) than on PCD-CT images (0.72 mm; SD = 0.66) (p < 0.001). CONCLUSION: The EID-CT examinations tend to overcall the presence of SSCD compared to PCD-CT and also underestimate the thickness of bone overlying the SSC.

Technical Note: Assessment of Pulse Pileup on Single-Energy and Multienergy Images From a Clinical Photon-Counting Detector Computed Tomography.

OBJECTIVE: Pulse pileup effects occur when pulses occur so close together that they fall on top of one another, resulting in count loss and errors in energy thresholding. To date, there has been little work systematically detailing the quantitative effects of pulse pileup on material decomposition accuracy for photon-counting detector (PCD) computed tomography (CT). Our aim in this work was to quantify the effects of pulse pileup on single-energy and multienergy CT images, including low-energy bin (BL), high-energy bin (BH), iodine map, and virtual noncontrast images from a commercial PCD-CT. METHODS: Scans of a 20-cm diameter multienergy CT phantom with 10 solid inserts were acquired at a fixed tube potential as the tube current was varied across the available range. Four types of images (BL, BH, iodine map, and virtual noncontrast) were reconstructed using an iterative reconstruction algorithm at strength 2, a quantitative reconstruction kernel (Qr40), 2-/1-mm slice thickness/increment, and a 210-mm field-of-view. The mean and standard deviation of CT numbers were recorded and the ratios of CT number between BL and BH images were calculated and plotted, along with noise versus tube current and noise × versus tube current. RESULTS: As tube current was increased, the range of variations in CT numbers was less than 13.4 HU for all inserts and image types evaluated. Noise × versus tube current showed a small positive slope equal to a noise increase from 100 mA of 10% at 500 mA and 15% at 900 mA compared with what would be expected if the slope was zero. CONCLUSIONS: Minimal impact on single-energy and multienergy CT numbers and noise performance was observed for the evaluated clinical PCD-CT system.

Targeted Training Reduces Search Errors but Not Classification Errors for Hepatic Metastasis Detection at Contrast-Enhanced CT.

RATIONALE AND OBJECTIVES: Methods are needed to improve the detection of hepatic metastases. Errors occur in both lesion detection (search) and decisions of benign versus malignant (classification). Our purpose was to evaluate a training program to reduce search errors and classification errors in the detection of hepatic metastases in contrast-enhanced abdominal computed tomography (CT). MATERIALS AND METHODS: After Institutional Review Board approval, we conducted a single-group prospective pretest-posttest study. Pretest and posttest were identical and consisted of interpreting 40 contrast-enhanced abdominal CT exams containing 91 liver metastases under eye tracking. Between pretest and posttest, readers completed search training with eye-tracker feedback and coaching to increase interpretation time, use liver windows, and use coronal reformations. They also completed classification training with part-task practice, rating lesions as benign or malignant. The primary outcome was metastases missed due to search errors (<2 seconds gaze under eye tracker) and classification errors (>2 seconds). Jackknife free-response receiver operator characteristic (JAFROC) analysis was also conducted. RESULTS: A total of 31 radiologist readers (8 abdominal subspecialists, 8 nonabdominal subspecialists, 15 senior residents/fellows) participated. Search errors were reduced (pretest 11%, posttest 8%, difference 3% [95% confidence interval, 0.3%-5.1%], P = .01), but there was no difference in classification errors (difference 0%, P = .97) or in JAFROC figure of merit (difference -0.01, P = .36). In subgroup analysis, abdominal subspecialists demonstrated no evidence of change. CONCLUSION: Targeted training reduced search errors but not classification errors for the detection of hepatic metastases at contrast-enhanced abdominal CT. Improvements were not seen in all subgroups.

Infrapopliteal Segments on Lower Extremity CTA: Prospective Intraindividual Comparison of Energy-Integrating Detector CT and Photon-Counting Detector CT.

BACKGROUND. The higher spatial resolution and image contrast for iodine-containing tissues of photon-counting detector (PCD) CT may address challenges in evaluating small calcified vessels when performing lower extremity CTA by energy-integrating detector (EID) CTA. OBJECTIVE. The purpose of the study was to compare the evaluation of infrapopliteal vasculature between lower extremity CTA performed using EID CT and PCD CT. METHODS. This prospective study included 32 patients (mean age, 69.7 ± 11.3 [SD] years; 27 men, five women) who underwent clinically indicated lower extremity EID CTA between April 2021 and March 2022; participants underwent investigational lower extremity PCD CTA later the same day as EID CTA using a reduced IV contrast media dose. Two radiologists independently reviewed examinations in two sessions, each containing a random combination of EID CTA and PCD CTA examinations; the readers assessed the number of visualized fibular perforators, characteristics of stenoses at 11 infrapopliteal segmental levels, and subjective arterial sharpness. RESULTS. Mean IV contrast media dose was 60.0 ± 11.0 (SD) mL for PCD CTA versus 139.6 ± 11.8 mL for EID CTA (p < .001). The number of identified fibular perforators per lower extremity was significantly higher for PCD CTA than for EID CTA for reader 1 (R1) (mean ± SD, 6.4 ± 3.2 vs 4.2 ± 2.4; p < .001) and reader 2 (R2) (8.8 ± 3.4 vs 7.6 ± 3.3; p = .04). Reader confidence for assessing stenosis was significantly higher for PCD CTA than for EID CTA for R1 (mean ± SD, 82.3 ± 20.3 vs 78.0 ± 20.2; p < .001) but not R2 (89.8 ± 16.7 vs 90.6 ± 7.1; p = .24). The number of segments per lower extremity with total occlusion was significantly lower for PCD CTA than for EID CTA for R2 (mean ± SD, 0.5 ± 1.3 vs 0.9 ± 1.7; p = .04) but not R1 (0.6 ± 1.3 vs 1.0 ± 1.5; p = .07). The number of segments per lower extremity with clinically significant nonocclusive stenosis was significantly higher for PCD CTA than for EID CTA for R1 (mean ± SD, 2.2 ± 2.2 vs 1.6 ± 1.7; p = .01) but not R2 (1.1 ± 2.0 vs 1.1 ± 1.4; p = .89). Arterial sharpness was significantly greater for PCD CTA than for EID CTA for R1 (mean ± SD, 3.2 ± 0.5 vs 1.8 ± 0.5; p < .001) and R2 (3.2 ± 0.4 vs 1.7 ± 0.8; p < .001). CONCLUSION. PCD CTA yielded multiple advantages relative to EID CTA for visualizing small infrapopliteal vessels and characterizing associated plaque. CLINICAL IMPACT. The use of PCD CTA may improve vascular evaluation in patients with peripheral arterial disease.

Photon-Counting Detector Computed Tomography Versus Energy-Integrating Detector Computed Tomography for Coronary Artery Calcium Quantitation.

OBJECTIVES: Photon-counting detector (PCD) computed tomography (CT) offers improved spatial and contrast resolution, which can impact quantitative measurements. This work aims to determine in human subjects the effect of dual-source PCD-CT on the quantitation of coronary artery calcification (CAC) compared with dual-source energy-integrating detector (EID) CT in both 1- and 3-mm images. METHODS: This prospective study enrolled patients receiving a clinical EID-CT CAC examination to undergo a research PCD-CT CAC examination. Axial images were reconstructed with a 512 × 512 matrix, 200-mm field of view, 3-mm section thickness/1.5-mm interval using a quantitative kernel (Qr36). Sharper kernels (Qr56/QIR strength 4 for PCD and Qr49/ADMIRE strength 5 for EID) were used to reconstruct images with 1-mm section thickness/0.5-mm interval. Pooled analysis was performed for all calcifications with nonzero values, and volume and Agatston scores were compared between EID-CT and PCD-CT. A Wilcoxon signed-rank test was performed with P < 0.05 considered statistically significant. RESULTS: In 21 subjects (median age, 58 years; range, 50-75 years; 13 male [62%]) with a total of 42 calcified arteries detected at 3 mm and 46 calcified arteries at 1-mm images, EID-CT CAC volume and Agatston scores were significantly lower than those of PCD-CT ( P ≤ 0.001). At 3-mm thickness, the mean (standard deviation) volume and Agatston score for EID-CT were 55.5 (63.4) mm 3 and 63.8 (76.9), respectively, and 61.5 (69.4) mm 3 and 70.4 (85.3) for PCD-CT ( P = 0.0001 and P = 0.0013). At 1-mm thickness, the mean (standard deviation) volume and score for EID-CT were 50.0 (56.3) mm 3 and 61.1 (69.3), respectively, and 59.5 (63.9) mm 3 and 72.5 (79.9) for PCD-CT ( P < 0.0001 for both). The applied radiation dose (volume CT dose index) for the PCD-CT scan was 2.1 ± 0.6 mGy, which was 13% lower than for the EID-CT scan (2.4 ± 0.7 mGy, P < 0.001). CONCLUSIONS: Relative to EID-CT, PCD-CT demonstrated a small but significant increase in coronary artery calcium volume and Agatston score.

Coronary artery stenosis quantification in patients with dense calcifications using ultra-high-resolution photon-counting-detector computed tomography.

BACKGROUND: To quantify differences in coronary artery stenosis severity in patients with calcified lesions between conventional energy-integrating detector (EID) CT and ultra-high-resolution (UHR) photon-counting-detector (PCD) CT. METHODS: Patients undergoing clinically indicated coronary CT angiography were prospectively recruited and scanned first on an EID-CT (SOMATOM Force, Siemens Healthineers) and then a PCD-CT (NAEOTOM Alpha, Siemens Healthineers) on the same day. EID-CT was performed with standard mode (192 â€‹× â€‹0.6 â€‹mm detector collimation) following our clinical protocol. PCD-CT scans were performed under UHR mode (120 â€‹× â€‹0.2 â€‹mm detector collimation). For each patient, left main, left anterior descending, right coronary artery, and circumflex were reviewed and the most severe stenosis from dense calcification for each coronary was quantified using commercial software. Additionally, each measured stenosis was assigned a severity category based on percent diameter stenosis, and changes in severity category across EID-CT and PCD-CT were assessed. RESULTS: A total of 23 patients were enrolled, with 34 coronary artery stenoses analyzed. Stenosis was significantly reduced in PCD-CT compared to EID-CT (p â€‹< â€‹0.001), resulting in an average of 11% (SD â€‹= â€‹11%) reduction in percent diameter stenosis. Among the 34 lesions, 15 changed in stenosis severity category: 3 went from moderate to minimal, 1 from moderate to mild, 9 from mild to minimal, and 2 from minimal to mild with the use of PCD-CT compared to EID-CT. CONCLUSION: Use of UHR PCD-CT decreased percent diameter stenosis by an average of 11% relative to EID-CT, resulting in 13 of 34 stenoses being downgraded in stenosis severity category, potentially sparing patients from unnecessary intervention.

Comparison of Photon-counting Detector and Energy-integrating Detector CT for Visual Estimation of Coronary Percent Luminal Stenosis.

Background Compared with energy-integrating detector (EID) CT, the improved resolution of photon-counting detector (PCD) CT coupled with high-energy virtual monoenergetic images (VMIs) has been shown to decrease calcium blooming on images in phantoms and cadaveric specimens. Purpose To determine the impact of dual-source PCD CT on visual and quantitative estimation of percent diameter luminal stenosis compared with dual-source EID CT in patients. Materials and Methods This prospective study recruited consecutive adult patients from an outpatient facility between January and March 2022. Study participants underwent clinical dual-source EID coronary CT angiography followed by a research dual-source PCD CT examination. For PCD CT, multienergy data were used to create VMIs at 50 and 100 keV. Two readers independently reviewed EID CT images followed by PCD CT images after a washout period. Readers visually graded the most severe stenosis in terms of percent diameter luminal stenosis for the left main, left anterior descending, right, and circumflex coronary arteries, unblinded to scanner type. Quantitative measures of percent stenosis were made using commercial software. Visual and quantitative estimates of percent stenosis were compared between EID CT and PCD CT using the Wilcoxon signed-rank test. Results A total of 25 participants (median age, 59 years [range, 18-78 years]; 16 male participants) were enrolled. On EID CT images, readers 1 and 2 identified 39 and 32 luminal stenoses, respectively, with a percent diameter luminal stenosis greater than 0%. Visual estimates of percent stenosis were lower on PCD CT images than EID CT images (reader 1: median 20.6% [IQR, 8.8%-61.2%] vs 31.8% [IQR, 12.9%-69.7%], P < .001; reader 2: 6.5% [IQR, 0.4%-54.1%] vs 22.9% [IQR, 1.8%-67.4%], P = .002). No difference was observed between EID CT and PCD CT for quantitative measures of percent stenosis (median difference, -1.5% [95% CI: -3.0%, 2.5%]; P = .51). Conclusion Relative to using EID CT, using PCD CT led to decreases in visual estimates of percent stenosis. © RSNA, 2023 See also the editorial by Murphy and Donnelly in this issue.

Bilateral lunotriquetral coalition: a dynamic four-dimensional computed tomography technical case report.

Lunotriquetral coalitions are the most common form of carpal coalition wherein the cartilage between the lunate and triquetrum ossification centers failed to undergo apoptosis. This technical case report examines the arthrokinematics of bilateral lunotriquetral coalitions with dissimilar Minnaar types in one participant with one asymptomatic wrist and one wrist with suspected distal radioulnar joint injury. Static and dynamic (four-dimensional) CT images during pronosupination were captured using a photon-counting detector CT scanner. Interosseous proximity distributions were calculated between the lunotriquetral coalition and adjacent bones in both wrists to quantify arthrokinematics. Interosseous proximity distributions at joints adjacent to the lunotriquetral coalition demonstrate differences in median and minimum interosseous proximities between the asymptomatic and injured wrists during resisted pronosupination. Altered kinematics from lunotriquetral coalitions may be a source of ulnar-sided wrist pain and discomfort, limiting the functional range of motion. This case report highlights potential alterations to wrist arthrokinematics in the setting of lunotriquetral coalitions and possible associations with ulnar-sided wrist pain, highlighting anatomy to examine in radiographic follow-up. Furthermore, this case report demonstrates the technical feasibility of four-dimensional CT using photon-counting detector technology in assessing arthrokinematics in the setting of variant wrist anatomy.

Dual-Energy, Spectral and Photon Counting Computed Tomography for Evaluation of the Gastrointestinal Tract.

The use of dual-energy computed tomography (CT) allows for reconstruction of energy- and material-specific image series. The combination of low-energy monochromatic images, iodine maps, and virtual unenhanced images can improve lesion detection and disease characterization in the gastrointestinal tract in comparison with single-energy CT.

Characterization of single- and multi-energy CT performance of an oral dark borosilicate contrast media using a clinical photon-counting-detector CT platform.

BACKGROUND: The feasibility of oral dark contrast media is under exploration in abdominal computed tomography (CT) applications. One of the experimental contrast media in this class is dark borosilicate contrast media (DBCM), which has a CT attenuation lower than that of intra-abdominal fat. PURPOSE: To evaluate the performances of DBCM using single- and multi-energy CT imaging on a clinical photon-counting-detector CT (PCD-CT). METHODS: Five vials, three with iodinated contrast agent (5, 10, and 20 mg/mL; Omnipaque 350) and two with DBCM (6% and 12%; Nextrast, Inc.), and one solid-water rod (neutral contrast agent) were inserted into two multi-energy CT phantoms, and scanned on a clinical PCD-CT system (NAEOTOM Alpha) at 90, 120, 140, Sn100, and Sn140 kV (Sn: tin filter) in multi-energy mode. CARE keV IQ level was 180 (CTDIvol: 3.0 and 12.0 mGy for the small and large phantoms, respectively). Low-energy threshold images were reconstructed with a quantitative kernel (Qr40, iterative reconstruction strength 2) and slice thickness/increment of 2.0/2.0 mm. Virtual monoenergetic images (VMIs) were reconstructed from 40 to 140 keV at 10 keV increments. On all images, average CT numbers for each vial/rod were measured using circular region-of-interests and averaged over eight slices. The contrast-to-noise ratio (CNR) of iodine (5 mg/mL) against DBCM was calculated and plotted against tube potential and VMI energy level, and compared to the CNR of iodine against water. Similar analyses were performed on iodine maps and VNC images derived from the multi-energy scan at 120 kV. RESULTS: With increasing kV or VMI keV, the negative HU of DBCM decreased only slightly, whereas the positive HU of iodine decreased across all contrast concentrations and phantom sizes. CT numbers for DBCM decreased from -178.5 ± 9.6 to -194.4 ± 6.3 HU (small phantom) and from -181.7 ± 15.7 to -192.1 ± 11.9 HU (large phantom) for DBCM-12% from 90 to Sn140 kV; on VMIs, the CT numbers for DBCM decreased minimally from -147.1 ± 15.7 to -185.1 ± 9.2 HU (small phantom) and -158.8 ± 28.6 to -188.9 ± 14.7 HU (large phantom) from 40 to 70 keV, but remained stable from 80 to 140 keV. The highest iodine CNR against DBCM in low-energy threshold images was seen at 90 or Sn140 kV for the small phantom, whereas all CNR values from low-energy threshold images for the large phantom were comparable. The CNR values of iodine against DBCM computed on VMIs were highest at 40 or 70 keV depending on iodine and DBCM concentrations. The CNR values of iodine against DBCM were consistently higher than iodine to water (up to 460% higher dependent on energy level). Further, the CNR of iodine compared to DBCM is less affected by VMI energy level than the identical comparison between iodine and water: CNR values at 140 keV were reduced by 46.6% (small phantom) or 42.6% (large phantom) compared to 40 keV; CNR values for iodine compared to water were reduced by 86.3% and 83.8% for similar phantom sizes, respectively. Compared to 70 keV VMI, the iodine CNR against DBCM was 13%-79% lower on iodine maps and VNC. CONCLUSIONS: When evaluated at different tube potentials and VMI energy levels using a clinical PCD-CT system, DBCM showed consistently higher CNR compared to iodine versus water (a neutral contrast).

Adaptation of a channelized Hotelling observer model to accommodate anthropomorphic backgrounds and moving test objects in X-ray angiography.

BACKGROUND: Prior implementations of the channelized Hotelling observer (CHO) model have succeeded in assessing the performance of X-ray angiography systems under a variety of imaging conditions. However, often times these conditions do not resemble those present in routine clinical imaging scenarios, such as having complex anthropomorphic backgrounds in conjunction with moving test objects. PURPOSE: This work builds up on prior established CHO methods and introduces a new approach to switch from the already established "multiple-sample" CHO implementation to a "single-sample" technique. The proposed implementation enables the inclusion of moving test objects upon nonuniform backgrounds by allowing only a single sample to represent the test object present condition that is to be used within the statistical test to estimate the detectability index. METHODS: To assess the proposed method, two image data sets were acquired with a clinical X-ray angiography system. The first set consisted of a uniform background in combination with static test objects while the second consisted of an anthropomorphic chest phantom in conjunction with moving test objects. The first set was used to validate the proposed approach against the multiple-sample method while the second was used to assess the feasibility of the proposed method under a variety of imaging conditions, including seven object sizes and seven detector target dose (DTD) levels. RESULTS: For the uniform background data set, considering all detectability indices greater or equal than 1, the ratio between the detectability indices of the proposed single-sample approach versus the multiple-sample method was 0.997 ± 0.056 (range 0.884-1.159). The average single-direction width of the 95% confidence intervals (CIs) of the detectability index estimates for the multiple-sample method was 0.38 ± 0.43 (range 0.03-2.20). For the single-sample approach, the average width was 2.52 ± 0.63 (range 1.11-5.44). For the anthropomorphic background image set, the results were consistent with classical quantum-limited signal-to-noise ratio (SNR) theory. The magnitude of the detectability indices varied predictably with changes in both object size and DTD, with the highest value associated with the highest dose and the largest object size. Additionally, the proposed method was able to capture differences in the imaging performance for a given test object across the field of view, which was associated with the attenuation levels provided by different features of the anthropomorphic background. CONCLUSIONS: A new single-sample variant of the CHO model to assess the performance of X-ray angiography imaging systems is proposed. The new approach is consistent with quantum-limited image quality theory and with a standard implementation of the CHO model. The proposed method enables the assessment of moving test objects in combination with complex, nonuniform image backgrounds, thereby opening the possibility to assess imaging conditions which more closely resemble those used in clinical care.