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To assess the impact of a new artificial intelligence deep-learning reconstruction (Precise Image; AI-DLR) algorithm on image quality against a hybrid iterative reconstruction (IR) algorithm in abdominal CT for different clinical indications.Acquisitions on phantoms were performed at 5 dose levels (CTDIFrom Standard to Smoother levels, noise magnitude and average NPS spatial frequency decreased and the detectability (d') of all simulated lesions increased. For both inserts, TTF values were similar for all three AI-DLR levels from 13 to 6 mGy but decreased from Standard to Smoother levels at 1.8 mGy. Compared to the i4 used in clinical practice, d' values were higher using the Smoother and Smooth levels and close for the Standard level. For all dose levels, except at 1.8 mGy, radiologists considered images satisfactory for clinical use for the 3 levels of AI-DLR, but rated images too smooth using the Smoother level.Use of the Smooth and Smoother levels of AI-DLR reduces the image noise and improves the detectability of lesions and spatial resolution for standard and low-dose levels. Using the Smooth level is apparently the best compromise between the lowest dose level and adequate image quality.• Evaluation of the impact of a new artificial intelligence deep-learning reconstruction (AI-DLR) on image quality and dose compared to a hybrid iterative reconstruction (IR) algorithm. • The Smooth and Smoother levels of AI-DLR reduced the image noise and improved the detectability of lesions and spatial resolution for standard and low-dose levels. • The Smooth level seems the best compromise between the lowest dose level and adequate image quality.

To compare the spectral performance of three rapid kV switching dual-energy CT (DECT) systems on virtual monoenergetic images (VMIs) at low-energy levels on abdominal imaging.A multi-energy phantom was scanned on three DECT systems equipped with three different gemstone spectral imaging (GSI) platforms: GSI (1st generation, GSI-1st), GSI-Pro (2nd generation, GSI-2nd ), and GSI-Xtream (3rd generation, GSI-3rd). Acquisitions on the phantom were performed with a CTDIFor all GSI platforms, the noise magnitude decreased from 40 to 70 keV, and using AV50 compared to FBP. The average NPS spatial frequency (fDifferences in image quality were found between the GSI platforms for VMIs at low keV. The new DLR algorithm on the GSI-3rd platform reduced noise and improved spatial resolution and detectability without changing the noise texture for VMIs at low keV. The choice of the best energy level in VMIs depends on the platform and the reconstruction algorithm.

Recently, computed tomography (CT) manufacturers have developed deep-learning-based reconstruction algorithms to compensate for the limitations of iterative reconstruction (IR) algorithms, such as image smoothing and the spatial resolution's dependence on contrast and dose levels.To assess the impact of an artificial intelligence deep-learning reconstruction (AI-DLR) algorithm on image quality and dose reduction compared with a hybrid IR algorithm in chest CT for different clinical indications.Acquisitions on the CT American College of Radiology (ACR) 464 and CT Torso CTU-41 phantoms were performed at five dose levels (CTDIFrom Standard to Smoother levels, on average, the noise magnitude decreased (for all dose levels: -66.3% ± 0.5% for mediastinal images and -63.1% ± 0.1% for parenchymal images), the average NPS spatial frequency decreased (for all dose levels: -35.3% ± 2.2% for mediastinal images and -13.3% ± 2.2% for parenchymal images), and the detectability (d') of the three lesions increased. The opposite pattern was found from Standard to Sharper levels. From Smoother to Sharper levels, the spatial resolution increased for the low-contrast polyethylene insert and the opposite for the high-contrast air insert. Compared to the i4 used in clinical practice, d' values were higher using Smoother (mean for all dose levels: 338.7% ± 29.4%), Smooth (103.4% ± 11.2%), and Standard (34.1% ± 6.6%) levels for the LCN on mediastinal images and Smoother (169.5% ± 53.2% for GGO and 136.9% ± 1.6% for HCP) and Smooth (36.4% ± 22.1% and 24.1% ± 0.9%, respectively) levels for parenchymal images. Radiologists considered the images satisfactory for clinical use at these levels, but adaptation to the dose level of the protocol is required.With AI-DLR, the smoothest levels reduced the noise and improved the detectability of chest lesions but increased the image smoothing. The opposite was found with the sharpest levels. The choice of level depends on the dose level and type of image: mediastinal or parenchymal.

Ischaemic conditioning in rectal cancer surgery by preoperative embolization of the inferior mesenteric artery is feasible and safe. It seems to protect from ischaemic stress during the surgical procedure.

The purpose of this study was to analyze the dose to the uterus (UD) calculated for pregnant women per computed tomography (CT) acquisition and per CT examination in our Institution.Consecutive pregnant women who underwent CT examination from June 2014 to February 2022 and for whom UD calculation was performed by a medical physicist were retrospectively included. UDs were computed per CT acquisition using the CT Expo 2.4 software and were summed up to obtain the total UD per CT examination. The CTDIA total of 256 pregnant women with a mean age of 29.4 ± 5.5 (SD) years (range: 18-48) at 24.5 ± 10.4 (SD) weeks of amenorrhea (range: 1-40) were included. UDs were computed for 339 CT acquisitions. The CTDIGreatest UDs during CT examinations are observed when the pelvis is directly exposed to X-rays. With current dose levels and in optimized practices, UDs per CT acquisition and CT examination are always below 100 mGy. UD calculations cannot be performed for CT examinations that do not directly expose the pelvis (i.e., those1 mGy).

BACKGROUND: To assess the spectral performance of rapid kV switching dual-energy CT (KVSCT-Canon) equipped with a Deep-Learning spectral reconstruction algorithm on virtual-monoenergetic images at low-energy levels and to compare its performances with four other dual-energy CT (DECT) platforms equipped with iterative reconstruction algorithms. METHODS: Two CT phantoms were scanned on five DECT platforms: KVSCT-Canon, fast kV-switching CT (KVSCT-GE), split filter CT, dual-source CT (DSCT), and dual-layer CT (DLCT). The classical parameters of abdomen-pelvic examinations were used for all phantom acquisitions, and a CTDI(vol) close to 10 mGy. For KVSCT-Canon, virtual-monoenergetic images were reconstructed with a clinical slice thickness of 0.5 and 1.5 mm to be close to other platforms. Noise power spectrum (NPS) and task-based transfer function (TTF) were evaluated from 40 to 80 keV of virtual-monoenergetic images. A detectability index (d’) was computed to model the detection task of two contrast-enhanced lesions as function of keV. RESULTS: For KVSCT-Canon, the noise magnitude and average NPS spatial frequency (f(av)) decreased from 40 to 70 keV and increased thereafter. Similar noise magnitude outcomes were found for KVSCT-GE but the opposite for f(av). For the other DECT platforms, the noise magnitude decreased as the keV increased. For split filter CT, DSCT and DLCT, the f(av) values increased from 40 to 80 keV. For all DECT platforms, TTF at 50% (f(50)) decreased as the keV increased, decreasing spatial resolution. For KVSCT-Canon, d’ values peaked at 60 and 70 keV for both simulated lesions and from 50 to 70 keV for KVSCT-GE. d’ decreased between 40 and 70 keV for DSCT, DLCT and split filter CT. For KVSCT-Canon, the increase in slice thickness decreases noise magnitude, f(av) and f(50) and increases d’ values. The highest d’ values were found for DLCT at 40 and 50 keV and for KVSCT-Canon at 1.5 mm for other keV. CONCLUSIONS: For KVSCT-Canon, the detectability of contrast-enhanced lesions was highest at 60 keV. The highest d’ values were found for DLCT at 40 and 50 keV and for KVSCT-Canon at 1.5 mm for other keV.

International audience; Background: Ultra low dose chest computed tomography (CT) acquisitions have been used for selected emergency room patients with acute dyspnea or minor thoracic trauma. The purpose of this study was to evaluate the diagnostic performance of ultra-low-dose (ULD) chest CT for detecting viral pneumonia patterns compared to standard (STD) dose chest CT.Methods: All consecutive adult patients with two non-enhanced chest CT acquisitions, one STD and one ULD, for suspicion of viral pneumonia between March 5th and April 2nd 2020 were included. CT results were divided into two groups: non-viral pneumonia CT or compatible with viral pneumonia CT based on viral pneumonia CT patterns: ground-glass opacity (GGO), consolidation, crazy paving, air bronchogram signs and fibrous stripes. The diagnostic performance of ULD CT for suspicion of viral pneumonia was evaluated. For CTs compatible with viral pneumonia, CT pattern detection on ULD CT was assessed and STD CT was used as a reference.Results: The study included 380 patients with 97 CTs (25.5%) compatible with viral pneumonia. The mean effective doses (EDs) were 1.66 (1.29; 2.18) mSv for STD and 0.20 (0.18; 0.22) mSv for ULD CT (P

Purpose A need remains for alternative devices for aerosol drug delivery that are low cost, convenient and easy to use for the patient, but also capable of producing small-sized aerosol particles. This study investigated the potential of recent high power electronic nicotine delivery systems (ENDS) as aerosol generation devices for inhaled bronchodilators. Methods The particle size distribution was measured using a cascade impactor. The delivery of terbutaline sulfate, a current bronchodilator used for asthma or COPD therapy by inhalation, was studied. This drug was quantified by liquid chromatography coupled with tandem mass spectrometry. Results The particle size distribution in terms of mass frequency (in two ways, gravimetrically and quantitatively through drug assay on each stage) and the terbutaline sulfate concentration in the aerosol were elucidated. The mass median aerodynamic diameter (MMAD) and the drug delivery rose when the power level increased, to reach 5.6 ± 0.4 μg/puff with a MMAD of 0.78 ± 0.03 μm at 25 W. Conclusion New generation high-power ENDS are very efficient to generate carrier-droplets in the submicron range containing drug molecules with a constant drug concentration whatever the size-fractions. ENDS appear to be highly patient-adaptive.