Feasibility of Percutaneous Radiofrequency Ablation for Abdominal Wall Endometriosis: A Prospective Pilot Study.

STUDY OBJECTIVE: To assess the feasibility of percutaneous radiofrequency ablation (PRFA) of anterior abdominal wall endometriosis (AWE) lesions and to describe its efficacy on clinical symptoms and on the volume of the lesion. DESIGN: Interventional, prospective, non-comparative, phase 1 clinical trial. SETTING: Patients consulting at the multidisciplinary endometriosis expert center at Croix Rousse University Hospital (Hospices Civils de Lyon). PATIENTS: Ten patients with 1 to 3 AWE lesions treated by PRFA with 6 months follow-up. INTERVENTIONS: PRFA of AWE lesions were performed under ultrasound guidance. Initial power ranged from 3 to 10 W, with progressive increases in power. The thermal effect in the ablation zone was monitored in real time (appearance of hyperechoic signals). A contrast-enhanced ultrasound check was also carried out. We used multiShot technique until the entire nodule was covered by the hyperechogenic cloud. MEASUREMENTS AND MAIN RESULTS: Ten patients (12 nodules) were positively treated from 25/06/2020 to 27/07/2022, 8 under local anesthesia and 2 under general anesthesia, which represented 100% feasibility. Nine patients had previous caesarean section. At 6 months the nodule pain at palpation disappeared for 9 patients (90%), mean cyclic pain VAS significantly decreased from 5.7 points (0.9 SD 0.9 VS 6.6 SD 3.2 p=.03) and non-cyclic pain from 3.8 points (0.8 SD 1.3 vs 4.6 SD 3.3 p=.02). Patients reported a significant improvement of their quality of life at 6 months (SF36 total score increase by 218 points p<.01). We observed a significant reduction of 78% in the volume of the nodule at 6 months on MRI (1.2cm3 SD 1.3 vs 5.4cm3 SD 8.2 p<.01); 11/12 treated nodules were non-vascularized/enhanced on post-procedure MRI. All Patients were treated on an outpatient basis. We report one severe adverse event (incisional hernia). CONCLUSION: PRFA is feasible and may be a clinically effective treatment for AWE. https://clinicaltrials.gov/study/NCT04333017 Clinical trial registry number: NCT04333017.

Incidental pulmonary nodules: Natural language processing analysis of radiology reports.

BACKGROUND: Pulmonary nodules are a common incidental finding on chest Computed Tomography scans (CT), most of the time outside of lung cancer screening (LCS). We aimed to evaluate the number of incidental pulmonary nodules (IPN) found in 1 year in our hospital, as well as the follow-up (FUP) rate and the clinical and radiological features associated with FUP. METHODS: We trained a Natural Language Processing (NLP) tool to identify the transcripts mentioning the presence of a pulmonary nodule, among a large population of patients from a French hospital. We extracted nodule characteristics using keyword analysis. NLP algorithm accuracy was determined through manual reading from a sample of our population. Electronic health database and medical record analysis by clinician allowed us to obtain information about FUP and cancer diagnoses. RESULTS: In this retrospective observational study, we analyzed 101,703 transcripts corresponding to the entire CTs performed in 2020. We identified 1,991 (2 %) patients with an IPN. NLP accuracy for nodule detection in CT reports was 99 %. Only 41 % received a FUP between January 2020 and December 2021. Patient age, nodule size, and the mention of the nodule in the impression part were positively associated with FUP, while nodules diagnosed in the context of COVID-19 were less followed. 36 (2 %) lung cancers were subsequently diagnosed, with 16 (45 %) at a non-metastatic stage. CONCLUSIONS: We identified a high prevalence of IPN with a low FUP rate, encouraging the implementation of IPN management program. We also highlighted the potential of NLP for database analysis in clinical research.

Weakly-supervised learning-based pathology detection and localization in 3D chest CT scans.

BACKGROUND: Recent advancements in anomaly detection have paved the way for novel radiological reading assistance tools that support the identification of findings, aimed at saving time. The clinical adoption of such applications requires a low rate of false positives while maintaining high sensitivity. PURPOSE: In light of recent interest and development in multi pathology identification, we present a novel method, based on a recent contrastive self-supervised approach, for multiple chest-related abnormality identification including low lung density area ("LLDA"), consolidation ("CONS"), nodules ("NOD") and interstitial pattern ("IP"). Our approach alerts radiologists about abnormal regions within a computed tomography (CT) scan by providing 3D localization. METHODS: We introduce a new method for the classification and localization of multiple chest pathologies in 3D Chest CT scans. Our goal is to distinguish four common chest-related abnormalities: "LLDA", "CONS", "NOD", "IP" and "NORMAL". This method is based on a 3D patch-based classifier with a Resnet backbone encoder pretrained leveraging recent contrastive self supervised approach and a fine-tuned classification head. We leverage the SimCLR contrastive framework for pretraining on an unannotated dataset of randomly selected patches and we then fine-tune it on a labeled dataset. During inference, this classifier generates probability maps for each abnormality across the CT volume, which are aggregated to produce a multi-label patient-level prediction. We compare different training strategies, including random initialization, ImageNet weight initialization, frozen SimCLR pretrained weights and fine-tuned SimCLR pretrained weights. Each training strategy is evaluated on a validation set for hyperparameter selection and tested on a test set. Additionally, we explore the fine-tuned SimCLR pretrained classifier for 3D pathology localization and conduct qualitative evaluation. RESULTS: Validated on 111 chest scans for hyperparameter selection and subsequently tested on 251 chest scans with multi-abnormalities, our method achieves an AUROC of 0.931 (95% confidence interval [CI]: [0.9034, 0.9557], p $ p$ -value < 0.001) and 0.963 (95% CI: [0.952, 0.976], p $ p$ -value < 0.001) in the multi-label and binary (i.e., normal versus abnormal) settings, respectively. Notably, our method surpasses the area under the receiver operating characteristic (AUROC) threshold of 0.9 for two abnormalities: IP (0.974) and LLDA (0.952), while achieving values of 0.853 and 0.791 for NOD and CONS, respectively. Furthermore, our results highlight the superiority of incorporating contrastive pretraining within the patch classifier, outperforming Imagenet pretraining weights and non-pretrained counterparts with uninitialized weights (F1 score = 0.943, 0.792, and 0.677 respectively). Qualitatively, the method achieved a satisfactory 88.8% completeness rate in localization and maintained an 88.3% accuracy rate against false positives. CONCLUSIONS: The proposed method integrates self-supervised learning algorithms for pretraining, utilizes a patch-based approach for 3D pathology localization and develops an aggregation method for multi-label prediction at patient-level. It shows promise in efficiently detecting and localizing multiple anomalies within a single scan.

Association Between Aortic Wall Thrombus and Thromboembolic Events After Transfemoral Transcatheter Aortic Valve Replacement.

BACKGROUND: Thromboembolic events, particularly strokes, remain a major complication of transcatheter aortic valve replacement (TAVR). Embolic protection devices have failed to show significant clinical benefit in large randomized clinical trials. Aortic wall thrombus (AWT) is often observed on multidetector computed tomography during TAVR work-up, but its prognostic significance is uncertain. OBJECTIVES: This study sought to evaluate the association between the presence of AWT and the incidence of thromboembolic outcomes in patients undergoing transfemoral (TF) TAVR for severe aortic stenosis. METHODS: This was a prospective cohort study of consecutive patients who underwent TF TAVR for severe aortic stenosis between January 2011 and April 2022. A dedicated scale (range: 0-10) was qualitatively used to assess AWT. The primary outcome was a composite of procedural thromboembolic events defined as ischemic stroke, blue toe syndrome, bowel ischemia, or other solid organ infarction. The secondary endpoints were ischemic strokes and procedural death. RESULTS: Of the 641 patients included, severe AWT (score ≥8) was identified in 73 (11.4%). The presence of severe AWT was strongly associated with an increase in the primary outcome (OR: 8.48; 95% CI: 3.36-21.40; P < 0.001). This relationship persisted following multivariable analysis, which adjusted for comorbidities and procedural characteristics. The presence of severe AWT was also found to be associated with an increased incidence of stroke and procedural death (OR: 5.66; 95% CI: 2.00-15.30; P = 0.002 and OR: 4.66; 95% CI: 1.80-11.30; P = 0.002, respectively). CONCLUSIONS: The presence of severe AWT on preprocedural multidetector computed tomography is strongly associated with thromboembolic complications including stroke and mortality after TF TAVR.

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 P s < 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 P s < 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.

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.

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.

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.

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.

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.

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.

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.

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.