Ultra-High-Resolution and K-Edge Imaging of Prosthetic Heart Valves With Spectral Photon-Counting CT: A Phantom Study.

BACKGROUND AND PURPOSE: The contribution of cardiac computed tomography (CT) for the detection and characterization of prosthetic heart valve (PHV) complications is still limited due mainly to artifacts. Computed tomography systems equipped with photon-counting detectors (PCDs) have the potential to overcome these limitations. Therefore, the aim of the study was to compare image quality of PHV with PCD-CT and dual-energy dual-layer CT (DEDL-CT). MATERIALS AND METHODS: Two metallic and 3 biological PHVs were placed in a tube containing diluted iodinated contrast inside a thoracic phantom and scanned repeatedly at different angles on a DEDL-CT and PCD-CT. Two small lesions (~2 mm thickness; containing muscle and fat, respectively) were attached to the structure of 4 valves, placed inside the thoracic phantom, with and without an extension ring, and scanned again. Acquisition parameters were matched for the 2 CT systems and used for all scans. Metallic valves were scanned again with parameters adapted for tungsten K-edge imaging. For all valves, different metallic parts were measured on conventional images to assess their thickness and blooming artifacts. In addition, 6 parallelepipeds per metallic valve were drawn, and all voxels with density <3 times the standard deviation of the contrast media were recorded as an estimate of streak artifacts. For subjective analysis, 3 expert readers assessed conventional images of the valves, with and without lesions, and tungsten K-edge images. Conspicuity and sharpness of the different parts of the valve, the lesions, metallic, and blooming artifacts were scored on a 4-point scale. Measurements and scores were compared with the paired t test or Wilcoxon test. RESULTS: The objective analysis showed that, with PCD-CT, valvular metallic structures were thinner and presented less blooming artifacts. Metallic artifacts were also reduced with PCD-CT (11 [interquartile (IQ) = 6] vs 40 [IQ = 13] % of voxels). Subjective analysis allowed noticing that some structures were visible or clearly visible only with PCD-CT. In addition, PCD-CT yielded better scores for the conspicuity and for the sharpness of all structures (all Ps < 0.006), except for the conspicuity of the leaflets of the mechanical valves, which were well visible with either technique (4 [IQ = 3] for both). Both blooming and streak artifacts were reduced with PCD-CT (P ≤ 0.01). Overall, the use of PCD-CT resulted in better conspicuity and sharpness of the lesions compared with DEDL-CT (both Ps < 0.02). In addition, only with PCD-CT some differences between the 2 lesions were detectable. Adding the extension ring resulted in reduced conspicuity and sharpness with DEDL-CT (P = 0.04 and P = 0.02, respectively) and only in reduced sharpness with PCD-CT (P = 0.04). Tungsten K-edge imaging allowed for the visualization of the only dense structure containing it, the leaflets, and it resulted in images judged having less blooming and metallic artifacts as compared with conventional PCD-CT images (P < 0.01). CONCLUSIONS: With PCD-CT, objective and subjective image quality of metallic and biological PHVs is improved compared with DEDL-CT. Notwithstanding the improvements in image quality, millimetric lesions attached to the structure of the valves remain a challenge for PCD-CT. Tungsten K-edge imaging allows for even further reduction of artifacts.

Detection and severity quantification of pulmonary embolism with 3D CT data using an automated deep learning-based artificial solution.

PURPOSE: The purpose of this study was to propose a deep learning-based approach to detect pulmonary embolism and quantify its severity using the Qanadli score and the right-to-left ventricle diameter (RV/LV) ratio on three-dimensional (3D) computed tomography pulmonary angiography (CTPA) examinations with limited annotations. MATERIALS AND METHODS: Using a database of 3D CTPA examinations of 1268 patients with image-level annotations, and two other public datasets of CTPA examinations from 91 (CAD-PE) and 35 (FUME-PE) patients with pixel-level annotations, a pipeline consisting of: (i), detecting blood clots; (ii), performing PE-positive versus negative classification; (iii), estimating the Qanadli score; and (iv), predicting RV/LV diameter ratio was followed. The method was evaluated on a test set including 378 patients. The performance of PE classification and severity quantification was quantitatively assessed using an area under the curve (AUC) analysis for PE classification and a coefficient of determination (R²) for the Qanadli score and the RV/LV diameter ratio. RESULTS: Quantitative evaluation led to an overall AUC of 0.870 (95% confidence interval [CI]: 0.850-0.900) for PE classification task on the training set and an AUC of 0.852 (95% CI: 0.810-0.890) on the test set. Regression analysis yielded R² value of 0.717 (95% CI: 0.668-0.760) and of 0.723 (95% CI: 0.668-0.766) for the Qanadli score and the RV/LV diameter ratio estimation, respectively on the test set. CONCLUSION: This study shows the feasibility of utilizing AI-based assistance tools in detecting blood clots and estimating PE severity scores with 3D CTPA examinations. This is achieved by leveraging blood clots and cardiac segmentations. Further studies are needed to assess the effectiveness of these tools in clinical practice.

Value of Chest X-Ray and Chest Computed Tomography for Systemic Sarcoidosis Diagnosis in Undifferentiated Uveitis.

BACKGROUND: To evaluate the contribution of chest X-ray and chest CT for the diagnosis of sarcoid uveitis. METHODS: Retrospective study on consecutive patients with uveitis of unknown etiology, who underwent both chest X-ray and CT during uveitis diagnosis workup in a tertiary French university hospital. RESULTS: A total of 914 patients were included. Systemic sarcoidosis was identified in 23.1%. The probability of discordance between chest X-ray and CT increased with age at diagnosis (p < 0.001). In patients 30 years of age and younger, the probability of discordance was 5% or less, and 0.8% if the ACE level was normal. After 78.3 years of age, the probability of discordance was 20% or more. CONCLUSION: We recommend not to perform CT in patients under 30 years of age with a normal chest X ray and ACE level, and suggest performing chest CT first in the elderly.

Silent myocardial infarction fatty scars detected by coronary calcium score CT scan in diabetic patients without history of coronary heart disease.

OBJECTIVES: To evaluate the prevalence of intra-myocardial fatty scars (IMFS) most likely indicating previous silent myocardial infarction (SMI), as detected on coronary artery calcium (CAC) computed tomography (CT) scans in diabetic patients without history of coronary heart disease (CHD). METHODS: Diabetic patients screened for silent coronary insufficiency in a tertiary-care, university hospital between Jan-2015 and Dec-2016 were categorized according to their CAC score in two groups comprising 242 patients with CACS = 0 and 145 patients with CACS ≥ 300. CAC-CT scans were retrospectively evaluated for subendorcardial and transmural IMFS of the left ventricle. Adipose remodeling, patients' characteristics, cardiovascular risk factors and metabolic profile were compared between groups. RESULTS: Eighty-three (21%) patients with IMFS were identified, 55 (37.9%) in the group CACS ≥ 300 and 28 (11.6%) in the CACS = 0 (OR = 4.67; 95% CI = 2.78-7.84; p < 0.001). Total and average surface of IMFS and their number per patient were similar in both groups (p = 0.55; p = 0.29; p = 0.61, respectively). In the group CACS ≥ 300, patients with IMFS were older (p = 0.03) and had longer-lasting diabetes (p = 0.04). Patients with IMFS were older and had longer history of diabetes, reduced glomerular filtration rate, more coronary calcifications (all p < 0.05), and higher prevalence of carotid plaques (OR = 3.03; 95% CI = 1.43-6.39, p = 0.004). After correction for other variables, only a CACS ≥ 300 (OR = 5.12; 95% CI = 2.66-9.85; p < 0.001) was associated with an increased risk of having IMFS. CONCLUSIONS: In diabetic patients without known CHD, IMFSs were found in patients without coronary calcifications, although not as frequently as in patients with heavily calcified coronary arteries. It remains to be established if this marker translates in an upwards cardiovascular risk restratification especially in diabetic patients with CACS = 0. CLINICAL RELEVANCE STATEMENT: In diabetic patients without history of coronary heart disease, intramyocardial fatty scars, presumably of post-infarction origin, can be detected on coronary artery calcium CT scans more frequently, but not exclusively, if the coronary arteries are heavily calcified as compared to those without calcifications. KEY POINTS: • Intramyocardial fatty scars (IMFS), presumably of post-infarction origin, can be detected on coronary artery calcium (CAC) CT scans more frequently, but not exclusively, in diabetic patients with CACS ≥ 300 as compared to patients CACS = 0. • Patients with IMFS were older and had longer history of diabetes, reduced glomerular filtration rate, and more coronary calcifications. • Carotid plaques and CACS ≥ 300 were associated with an increased risk of having IMFS, about three and five folds respectively.

Clinical Applications of Photon-counting CT: A Review of Pioneer Studies and a Glimpse into the Future.

CT systems equipped with photon-counting detectors (PCDs), referred to as photon-counting CT (PCCT), are beginning to change imaging in several subspecialties, such as cardiac, vascular, thoracic, and musculoskeletal radiology. Evidence has been building in the literature underpinning the many advantages of PCCT for different clinical applications. These benefits derive from the distinct features of PCDs, which are made of semiconductor materials capable of converting photons directly into electric signal. PCCT advancements include, among the most important, improved spatial resolution, noise reduction, and spectral properties. PCCT spatial resolution on the order of 0.25 mm allows for the improved visualization of small structures (eg, small vessels, arterial walls, distal bronchi, and bone trabeculations) and their pathologies, as well as the identification of previously undetectable anomalies. In addition, blooming artifacts from calcifications, stents, and other dense structures are reduced. The benefits of the spectral capabilities of PCCT are broad and include reducing radiation and contrast material dose for patients. In addition, multiple types of information can be extracted from a single data set (ie, multiparametric imaging), including quantitative data often regarded as surrogates of functional information (eg, lung perfusion). PCCT also allows for a novel type of CT imaging, K-edge imaging. This technique, combined with new contrast materials specifically designed for this modality, opens the door to new applications for imaging in the future.

Gadolinium K-edge angiography with a spectral photon counting CT in atherosclerotic rabbits.

PURPOSE: The purpose of this study was to investigate the feasibility of gadolinium-K-edge-angiography (angio-Gd-K-edge) with gadolinium-based contrast agents (GBCAs) as obtained with spectral photon counting CT (SPCCT) in atherosclerotic rabbits. MATERIALS AND METHODS: Seven atherosclerotic rabbits underwent angio-SPCCT acquisitions with two GBCAs, with similar intravenous injection protocol. Conventional and angio-Gd-K-edge images were reconstructed with the same parameters. Regions of interest were traced in different locations of the aorta and its branches. Hounsfield unit values, Gd concentrations, signal-to-noise (SNR) and contrast-to-noise (CNR) were calculated and compared. The maximum diameter and the diameter of the aorta in regard to atherosclerotic plaques were measured by two observers. Images were subjectively evaluated regarding vessels' enhancement, artefacts, border sharpness and overall image quality. RESULTS: In the analyzable six rabbits, Gd-K-edge allowed visualization of target vessels and no other structures. HU values and Gd concentrations were greatest in the largest artery (descending aorta, 5.6 ± 0.8 [SD] mm), and lowest in the smallest (renal arteries, 2.1 ± 0.3 mm). While greater for conventional images, CNR and SNR were satisfactory for both images (all P < 0.001). For one observer there were no statistically significant differences in either maximum or plaque-diameters (P = 0.45 and all P > 0.05 in post-hoc analysis, respectively). For the second observer, there were no significant differences for images reconstructed with the same parameters (all P < 0.05). All subjective criteria scored higher for conventional images compared to K-edge (all P < 0.01), with the highest scores for enhancement (4.3-4.4 vs. 3.1-3.4). CONCLUSION: With SPCCT, angio-Gd-K-edge after injection of GBCAs in atherosclerotic rabbits is feasible and allows for angiography-like visualization of small arteries and for the reliable measurement of their diameters.

Artificial Intelligence as a Decision-Making Tool in Forensic Dentistry: A Pilot Study with I3M.

Expert determination of the third molar maturity index (I3M) constitutes one of the most common approaches for dental age estimation. This work aimed to investigate the technical feasibility of creating a decision-making tool based on I3M to support expert decision-making. Methods: The dataset consisted of 456 images from France and Uganda. Two deep learning approaches (Mask R-CNN, U-Net) were compared on mandibular radiographs, leading to a two-part instance segmentation (apical and coronal). Then, two topological data analysis approaches were compared on the inferred mask: one with a deep learning component (TDA-DL), one without (TDA). Regarding mask inference, U-Net had a better accuracy (mean intersection over union metric (mIoU)), 91.2% compared to 83.8% for Mask R-CNN. The combination of U-Net with TDA or TDA-DL to compute the I3M score revealed satisfying results in comparison with a dental forensic expert. The mean ± SD absolute error was 0.04 ± 0.03 for TDA, and 0.06 ± 0.04 for TDA-DL. The Pearson correlation coefficient of the I3M scores between the expert and a U-Net model was 0.93 when combined with TDA and 0.89 with TDA-DL. This pilot study illustrates the potential feasibility to automate an I3M solution combining a deep learning and a topological approach, with 95% accuracy in comparison with an expert.

Virtual monochromatic images for coronary artery imaging with a spectral photon-counting CT in comparison to dual-layer CT systems: a phantom and a preliminary human study.

OBJECTIVES: To evaluate the quality of virtual monochromatic images (VMIs) from spectral photon-counting CT (SPCCT) and two energy-integrating detector dual-energy CT (EID-DECT) scanners from the same manufacturer, for the coronary lumen. METHODS: A 21-cm section of the Mercury v4.0 phantom was scanned using a cardiac CT protocol. VMIs from 40 to 90 keV were reconstructed using high-resolution (HR) parameters for EID-DECT and SPCCT (CB and HRB kernels at 0.67 mm slice thickness, respectively). Ultra-high-resolution (UHR) parameters were used in addition to SPCCT (detailed-2 kernel, 0.43 mm slice thickness). Noise-power-spectrum (NPS), task-based transfer function (TTF), and detectability index (d') were computed for 2-mm-diameter lumen detection. In consensus, two radiologists analyzed the quality of the images from 8 patients who underwent coronary CTA on both CT systems. RESULTS: For all keV images, fpeak, f50, and d' were higher with SPCCT. The fpeak and f50 were higher with UHR-SPCCT with greater noise and lower d' compared to those of the HR-SPCCT images. Noise magnitude was constant for all energy levels (keV) with both systems, and lower with HR images, and d' decreased as keV decreased. Subjective analysis showed greater lumen sharpness and overall quality for HR and UHR-SPCCT images using all keV, with a greater difference at low keV compared to HR-EID-DECT images. CONCLUSION: HR and UHR-SPCCT images gave greater detectability of the coronary lumen for 40 to 90 keV VMIs compared to two EID-DECT systems, with benefits of higher lumen sharpness and overall quality. KEY POINTS: • Compared with 2 dual-energy CT systems, spectral photon-counting CT (SPCCT) improved spatial resolution, noise texture, noise magnitude, and detectability of the coronary lumen. • Use of ultra-high-resolution parameters with SPCCT improved spatial resolution and noise texture and provided high detectability of the coronary lumen, despite an increase in noise magnitude. • In eight patients, radiologists found greater overall image quality with SPCCT for all virtual monochromatic images with a greater difference at low keV, compared with dual-energy CT systems.

Lung Dual-Energy CT Perfusion Blood Volume as a Marker of Severity in Chronic Thromboembolic Pulmonary Hypertension.

In chronic thromboembolic pulmonary hypertension (CTEPH), assessment of severity requires right heart catheterization (RHC) through cardiac index (CI). Previous studies have shown that dual-energy CT allows a quantitative assessment of the lung perfusion blood volume (PBV). Therefore, the objective was to evaluate the quantitative PBV as a marker of severity in CTEPH. In the present study, thirty-three patients with CTEPH (22 women, 68.2 ± 14.8 years) were included from May 2017 to September 2021. Mean quantitative PBV was 7.6% ± 3.1 and correlated with CI (r = 0.519, p = 0.002). Mean qualitative PBV was 41.1 ± 13.4 and did not correlate with CI. Quantitative PBV AUC values were 0.795 (95% CI: 0.637-0.953, p = 0.013) for a CI ≥ 2 L/min/m2 and 0.752 (95% CI: 0.575-0.929, p = 0.020) for a CI ≥ 2.5 L/min/m2. In conclusion, quantitative lung PBV outperformed qualitative PBV for its correlation with the cardiac index and may be used as a non-invasive marker of severity in CTPEH patients.

High-resolution synchrotron K-edge subtraction CT allows tracking and quantifying therapeutic cells and their scaffold in a rat model of focal cerebral injury and can serve as a reference for spectral photon counting CT.

Background: The objective of this study was to demonstrate that synchrotron K-edge subtraction tomography (SKES-CT) can simultaneously track therapeutic cells and their encapsulating carrier, in vivo, in a rat model of focal brain injury using a dual-contrast agent approach. The second objective was to determine if SKES-CT could be used as a reference method for spectral photon counting tomography (SPCCT). Methods: Phantoms containing different concentrations of gold and iodine nanoparticles (AuNPS/INPs) were imaged with SKES-CT and SPCCT to assess their performances. A pre-clinical study was performed in rats with focal cerebral injury which intracerebrally received AuNPs-labelled therapeutic cells encapsulated in a INPs-labelled scaffold. Animals were imaged in vivo with SKES-CT and back-to-back with SPCCT. Results: SKES-CT revealed to be reliable for quantification of gold and iodine, whether alone or mixed. In the preclinical model, SKES-CT showed that AuNPs remained at the site of cell injection, while INPs expanded within and/or along the lesion border, suggesting dissociation of both components in the first days post-administration. Compared to SKES-CT, SPCCT was able to correctly locate gold, but not completely located iodine. When SKES-CT was used as reference, SPCCT gold quantification appeared very accurate both in vitro and in vivo. Iodine quantification by SPCCT was also quite accurate, albeit less so than for gold. Conclusion: We here provide the proof-of-concept that SKES-CT is a novel method of choice for performing dual-contrast agent imaging in the context of brain regenerative therapy. SKES-CT may also serve as ground truth for emerging technologies such as multicolour clinical SPCCT.

Precision of CT-derived alveolar recruitment assessed by human observers and a machine learning algorithm in moderate and severe ARDS.

BACKGROUND: Assessing measurement error in alveolar recruitment on computed tomography (CT) is of paramount importance to select a reliable threshold identifying patients with high potential for alveolar recruitment and to rationalize positive end-expiratory pressure (PEEP) setting in acute respiratory distress syndrome (ARDS). The aim of this study was to assess both intra- and inter-observer smallest real difference (SRD) exceeding measurement error of recruitment using both human and machine learning-made lung segmentation (i.e., delineation) on CT. This single-center observational study was performed on adult ARDS patients. CT were acquired at end-expiration and end-inspiration at the PEEP level selected by clinicians, and at end-expiration at PEEP 5 and 15 cmH2O. Two human observers and a machine learning algorithm performed lung segmentation. Recruitment was computed as the weight change of the non-aerated compartment on CT between PEEP 5 and 15 cmH2O. RESULTS: Thirteen patients were included, of whom 11 (85%) presented a severe ARDS. Intra- and inter-observer measurements of recruitment were virtually unbiased, with 95% confidence intervals (CI95%) encompassing zero. The intra-observer SRD of recruitment amounted to 3.5 [CI95% 2.4-5.2]% of lung weight. The human-human inter-observer SRD of recruitment was slightly higher amounting to 5.7 [CI95% 4.0-8.0]% of lung weight, as was the human-machine SRD (5.9 [CI95% 4.3-7.8]% of lung weight). Regarding other CT measurements, both intra-observer and inter-observer SRD were close to zero for the CT-measurements focusing on aerated lung (end-expiratory lung volume, hyperinflation), and higher for the CT-measurements relying on accurate segmentation of the non-aerated lung (lung weight, tidal recruitment…). The average symmetric surface distance between lung segmentation masks was significatively lower in intra-observer comparisons (0.8 mm [interquartile range (IQR) 0.6-0.9]) as compared to human-human (1.0 mm [IQR 0.8-1.3] and human-machine inter-observer comparisons (1.1 mm [IQR 0.9-1.3]). CONCLUSIONS: The SRD exceeding intra-observer experimental error in the measurement of alveolar recruitment may be conservatively set to 5% (i.e., the upper value of the CI95%). Human-machine and human-human inter-observer measurement errors with CT are of similar magnitude, suggesting that machine learning segmentation algorithms are credible alternative to humans for quantifying alveolar recruitment on CT.

First Experience With a Whole-Body Spectral Photon-Counting CT Clinical Prototype.

ABSTRACT: Spectral photon-counting computed tomography (SPCCT) technology holds great promise for becoming the next generation of computed tomography (CT) systems. Its technical characteristics have many advantages over conventional CT imaging. For example, SPCCT provides better spatial resolution, greater dose efficiency for ultra-low-dose and low-dose protocols, and tissue contrast superior to that of conventional CT. In addition, SPCCT takes advantage of several known approaches in the field of spectral CT imaging, such as virtual monochromatic imaging and material decomposition imaging. In addition, SPCCT takes advantage of a new approach in this field, known as K-edge imaging, which allows specific and quantitative imaging of a heavy atom-based contrast agent. Hence, the high potential of SPCCT systems supports their ongoing investigation in clinical research settings. In this review, we propose an overview of our clinical research experience of a whole-body SPCCT clinical prototype, to give an insight into the potential benefits for clinical human imaging on image quality, diagnostic confidence, and new approaches in spectral CT imaging.

Bicolor K-edge spectral photon-counting CT imaging for the diagnosis of thoracic endoleaks: A dynamic phantom study.

PURPOSE: The purpose of this study was to investigate the feasibility of identifying and characterizing the three most common types of endoleaks within a thoracic aorta aneurysm model using bicolor K-edge imaging with a spectral photon-counting computing tomography (SPCCT) system in combination with a biphasic contrast agent injection. MATERIALS AND METHODS: Three types of thoracic endoleaks (type 1, 2 and 3) were created in a dynamic anthropomorphic thoracic aorta phantom. Protocol consisted in an injection of an iodinated contrast material followed 80 seconds after an injection of a gadolinium-based contrast agent (GBCA). The phantom was scanned using a clinical prototype SPCCT during bicolor phase imaging consisting in an early distribution of GBCA and a late distribution of iodine. Conventional and spectral images were reconstructed for differentiating between the contrast agents and measuring their respective attenuation values and concentrations inside and outside the stent graft. RESULTS: Conventional images failed to provide specific dynamic imaging contrast agents in the aneurysmal sac and outside the stent graft while spectral images differentiated their specific distribution. In type 1 and 3 thoracic endoleaks, GBCA concentration was measured outside the stent graft at 6.1 ± 3.7 (standard deviation [SD]) mg/mL and 6.0 ± 4.0 (SD) mg/mL, respectively, in favor of an early blood flow. In type 2 thoracic endoleak, iodine was measured outside the stent graft at 24.3 ± 5.5 (SD) mg/mL in favor of a late blood flow in the aneurysmal sac. CONCLUSION: Bicolor K-edge imaging enabled SPCCT allows a bicolor characterization of thoracic aorta endoleaks in a single acquisition in combination with a biphasic contrast agent injection.

Effect of contrast material injection protocol on first-pass myocardial perfusion assessed by dual-energy dual-layer computed tomography.

Background: Dual-energy dual-layer computed tomography (CT) scanners can provide useful tools, such as iodine maps and virtual monochromatic images (VMI), for the evaluation of myocardial perfusion defects. Data about the influence of acquisition protocols and normal values are still lacking. Methods: Clinically indicated coronary CT-angiographies performed between January-October 2018 in a single university hospital with dual-energy dual-layer CT (DE-DLCT) and different injection protocols were retrospectively evaluated. The two protocols were: 35 mL in patients <80 kg and 0.5 mL/kg in patients >80 kg at 2.5 mL/s (group A) or double contrast dose at 5 mL/s (group B). Patients with coronary stenosis >50% were excluded. Regions of interest were manually drawn on 16 myocardial segments and iodine concentration was measured in mg/mL. Signal-to-noise, contrast-to-noise ratios (CNR) and image noise were measured on conventional images and VMI. Results: A total of 30 patients were included for each protocol. With iodine concentrations of 1.38±0.41 mg/mL for protocol A and 2.07±0.73 mg/mL for protocol B, the two groups were significantly different (P<0.001). No significant iodine concentration differences were found between the 16 segments (P=0.47 and P=0.09 for group A and B respectively), between basal, mid and apical segments for group A and B (P=0.28 and P=0.12 for group A and B respectively) and between wall regions for group A (P=0.06 on normalised data). In group B, iodine concentration was significantly different between three wall regions [highest values for the lateral wall, median =2.03 (1.06) mg/mL]. Post-hoc analysis showed highest contrast-to-noise and signal-to-noise in VMI at 40 eV (P<0.05). Conclusions: Iodine concentration in left ventricular myocardium of patients without significant coronary artery stenosis varied depending on the injection protocol and appeared more heterogeneous in different wall regions at faster injection rate and greater iodine load. Signal-to-noise and contrast-to-noise gradually improved when decreasing VMI energy, although at the expenses of higher noise, demonstrating the potential of DE-DLCT to enhance objective image quality.

Response to PEEP in COVID-19 ARDS patients with and without extracorporeal membrane oxygenation. A multicenter case-control computed tomography study.

BACKGROUND: PEEP selection in severe COVID-19 patients under extracorporeal membrane oxygenation (ECMO) is challenging as no study has assessed the alveolar recruitability in this setting. The aim of the study was to compare lung recruitability and the impact of PEEP on lung aeration in moderate and severe ARDS patients with or without ECMO, using computed tomography (CT). METHODS: We conducted a two-center prospective observational case-control study in adult COVID-19-related patients who had an indication for CT within 72 h of ARDS onset in non-ECMO patients or within 72  h after ECMO onset. Ninety-nine patients were included, of whom 24 had severe ARDS under ECMO, 59 severe ARDS without ECMO and 16 moderate ARDS. RESULTS: Non-inflated lung at PEEP 5 cmH2O was significantly greater in ECMO than in non-ECMO patients. Recruitment induced by increasing PEEP from 5 to 15 cmH2O was not significantly different between ECMO and non-ECMO patients, while PEEP-induced hyperinflation was significantly lower in the ECMO group and virtually nonexistent. The median [IQR] fraction of recruitable lung mass between PEEP 5 and 15 cmH2O was 6 [4-10]%. Total superimposed pressure at PEEP 5 cmH2O was significantly higher in ECMO patients and amounted to 12 [11-13] cmH2O. The hyperinflation-to-recruitment ratio (i.e., a trade-off index of the adverse effects and benefits of PEEP) was significantly lower in ECMO patients and was lower than one in 23 (96%) ECMO patients, 41 (69%) severe non-ECMO patients and 8 (50%) moderate ARDS patients. Compliance of the aerated lung at PEEP 5 cmH2O corrected for PEEP-induced recruitment (CBABY LUNG) was significantly lower in ECMO patients than in non-ECMO patients and was linearly related to the logarithm of the hyperinflation-to-recruitment ratio. CONCLUSIONS: Lung recruitability of COVID-19 pneumonia is not significantly different between ECMO and non-ECMO patients, with substantial interindividual variations. The balance between hyperinflation and recruitment induced by PEEP increase from 5 to 15 cmH2O appears favorable in virtually all ECMO patients, while this PEEP level is required to counteract compressive forces leading to lung collapse. CBABY LUNG is significantly lower in ECMO patients, independently of lung recruitability.

Hemodynamic Changes Before and After Endovascular Treatment of Type B Aortic Dissection by 4D Flow MRI.

Objective: The standard treatment for complicated Stanford type B aortic dissection (TBAD) is thoracic endovascular aortic repair (TEVAR). Functional parameters, specifically blood flow, are not measured in the clinical assessment of TEVAR, yet they are of outmost importance in patient outcome. Consequently, we investigated the impact of TEVAR on the flows in the aorta and its branches in TBAD using 4D Phase-Contrast Magnetic Resonance Imaging (4D Flow MRI). Methods: Seven patients with TBAD scheduled for TEVAR underwent pre and post-operative 4D Flow MRI. An experienced reader assessed the presence of helical flow in the false lumen (FL) using streamlines and measured net flow at specific locations. In addition, forward and reverse flows, stasis, helicity, and absolute helicity were computed automatically along the aorta centerline. Average values were then computed in the segmented vessels. Impact of TEVAR on these parameters was assessed with a Wilcoxon signed rank test. Impact of the metallic stent on the velocity quantification was assessed using intra-class correlation coefficient (ICC) between velocities measured intra-stent and in adjacent stent-free regions. Results: FL helical flow was observed proximally in 6 cases and distally in 2 cases pre-operatively. Helical flow disappeared post-TEVAR proximally, but developed distally for 2 patients. Intra-stent measures were similar to stent-free with a median difference of 0.1 L/min and an ICC equal to 0.967 (p < 0.01). Forward flow increased from 59.9 to 81.6% in the TL and significantly decreased in the FL from 15.9 to 3.3%. Similarly, reverse flow increased in the TL from 4.36 to 10.8% and decreased in the FL from 10.3 to 4.6%. No significant changes were observed in net flow for aortic branches (p > 0.05). A significant increase in FL stasis was observed (p = 0.04). Discussion: TEVAR significantly increased forward flow in the TL and significantly decreased both forward and reverse flows in the FL. Interestingly, reverse flow in the TL increased post-TEVAR, which could be due to increased rigidity of the wall, due to the metallic stent. User independent helicity quantification enabled detection of elevated helicity at the level of secondary entry tears which had been missed by streamline visualization.

French Imaging Database Against Coronavirus (FIDAC): A large COVID-19 multi-center chest CT database.

PURPOSE: During the first wave of the COVID-19 pandemic, the French Society of Radiology and the French College of Radiology, in partnership with NEHS Digital, have set up a system to collect chest computed tomography (CT) examinations with clinical, virological and radiological metadata, from patients clinically suspected of COVID-19 pneumonia. This allowed the constitution of an anonymized multicenter database, named FIDAC (French Imaging Database Against Coronavirus). The aim of this report was to describe the content of this public database. MATERIALS AND METHODS: Twenty-two French radiology centers participated to the data collection. The data collected were chest CT examinations in DICOM format associated with the following metadata: patient age and sex, originating facility identifier, originating facility region, time from symptom onset to CT examination, indication for CT examination, reverse transcription-polymerase chain reaction (RT-PCR) results and normalized CT report performed by a senior radiologist. All the data were anonymized and sent through a NEHS Digital system to a centralized data center. RESULTS: A total of 5944 patients were included from the 22 centers aggregated into 8 regions with a mean number of patients of 743 ± 603.3 [SD] per region (range: 102-1577 patients). Reasons for CT examination and normalized CT reports were provided for all patients. RT-PCR results were provided in 5574 patients (93.77%) with a positive result of RT-PCR in 44.6% of patients. CONCLUSION: The FIDAC project allowed the creation of a large database of chest CT images and metadata available, under conditions, in open access through the CERF-SFR website.

Virtual monoenergetic images from photon-counting spectral computed tomography to assess knee osteoarthritis.

BACKGROUND: Dual-energy computed tomography has shown a great interest for musculoskeletal pathologies. Photon-counting spectral computed tomography (PCSCT) can acquire data in multiple energy bins with the potential to increase contrast, especially for soft tissues. Our objectives were to assess the value of PCSST to characterise cartilage and to extract quantitative measures of subchondral bone integrity. METHODS: Seven excised human knees (3 males and 4 females; 4 normal and 3 with osteoarthritis; age 80.6 ± 14 years, mean ± standard deviation) were scanned using a clinical PCSCT prototype scanner. Tomographic image reconstruction was performed after Compton/photoelectric decomposition. Virtual monoenergetic images were generated from 40 keV to 110 keV every 10 keV (cubic voxel size 250 × 250 × 250 µm3). After selecting an optimal virtual monoenergetic image, we analysed the grey level histograms of different tissues and extracted quantitative measurements on bone cysts. RESULTS: The optimal monoenergetic images were obtained for 60 keV and 70 keV. Visual inspection revealed that these images provide sufficient spatial resolution and soft-tissue contrast to characterise surfaces, disruption, calcification of cartilage, bone osteophytes, and bone cysts. Analysis of attenuation versus energy revealed different energy fingerprint according to tissues. The volumes and numbers of bone cyst were quantified. CONCLUSIONS: Virtual monoenergetic images may provide direct visualisation of both cartilage and bone details. Thus, unenhanced PCSCT appears to be a new modality for characterising the knee joint with the potential to increase the diagnostic capability of computed tomography for joint diseases and osteoarthritis.

Coronary CT Angiography with Photon-counting CT: First-In-Human Results.

Background Spatial resolution, soft-tissue contrast, and dose-efficient capabilities of photon-counting CT (PCCT) potentially allow a better quality and diagnostic confidence of coronary CT angiography (CCTA) in comparison to conventional CT. Purpose To compare the quality of CCTA scans obtained with a clinical prototype PCCT system and an energy-integrating detector (EID) dual-layer CT (DLCT) system. Materials and Methods In this prospective board-approved study with informed consent, participants with coronary artery disease underwent retrospective electrocardiographically gated CCTA with both systems after injection of 65-75 mL of 400 mg/mL iodinated contrast agent at 5 mL/sec. A prior phantom task-based quality assessment of the detectability index of coronary lesions was performed. Ultra-high-resolution parameters were used for PCCT (1024 matrix, 0.25-mm section thickness) and EID DLCT (512 matrix, 0.67-mm section thickness). Three cardiac radiologists independently performed a blinded analysis using a five-point quality score (1 = insufficient, 5 = excellent) for overall image quality, diagnostic confidence, and diagnostic quality of calcifications, stents, and noncalcified plaques. A logistic regression model, adjusted for radiologists, was used to evaluate the proportion of improvement in scores with the best method. Results Fourteen consecutive participants (12 men; mean age, 61 years ± 17) were enrolled. Scores of overall quality and diagnostic confidence were higher with PCCT images with a median of 5 (interquartile range [IQR], 2) and 5 (IQR, 1) versus 4 (IQR, 1) and 4 (IQR, 3) with EID DLCT images, using a mean tube current of 255 mAs ± 0 versus 349 mAs ± 111 for EID DLCT images (P < .01). Proportions of improvement with PCCT images for quality of calcification, stent, and noncalcified plaque were 100%, 92% (95% CI: 71, 98), and 45% (95% CI: 28, 63), respectively. In the phantom study, detectability indexes were 2.3-fold higher for lumen and 2.9-fold higher for noncalcified plaques with PCCT images. Conclusion Coronary CT angiography with a photon-counting CT system demonstrated in humans an improved image quality and diagnostic confidence compared with an energy-integrating dual-layer CT. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Sandfort and Bluemke in this issue.