Neurovascular compression syndrome (NVCS), characterized by cranial nerve compression due to adjacent blood vessels at the root entry zone, frequently presents as trigeminal neuralgia (TN), hemifacial spasm (HFS), or glossopharyngeal neuralgia (GN). Despite its prevalence in NVCS assessment, Magnetic Resonance Tomographic Angiography (MRTA)\'s limited sensitivity to small vessels and veins poses challenges. This study aims to refine vessel localization and surgical planning for NVCS patients using a novel 3D multimodal fusion imaging (MFI) technique incorporating computed tomography angiography and venography (CTA/CTV). A retrospective analysis was conducted on 76 patients who underwent MVD surgery and were diagnosed with single-site primary TN, HFS, or GN. Imaging was obtained from MRTA and CTA/CTV sequences, followed by image processing and 3D-MFI using FastSurfer and 3DSlicer. The CTA/CTV-3D-MFI showed higher sensitivity than MRTA-3D-MFI in predicting responsible vessels (98.6% vs. 94.6%) and NVC severity (98.6% vs. 90.8%). Kappa coefficients revealed strong agreement with MRTA-3D-MFI (0.855 for vessels, 0.835 for NVC severity) and excellent agreement with CTA/CTV-3D-MFI (0.951 for vessels, 0.952 for NVC). Resident neurosurgeons significantly preferred CTA/CTV-3D-MFI due to its better correlation with surgical reality, clearer depiction of surgical anatomy, and optimized visualization of approaches (p < 0.001). Implementing CTA/CTV-3D-MFI significantly enhanced diagnostic accuracy and surgical planning for NVCS, outperforming MRTA-3D-MFI in identifying responsible vessels and assessing NVC severity. This innovative imaging modality can potentially improve outcomes by guiding safer and more targeted surgeries, particularly in cases where MRTA may not adequately visualize crucial neurovascular structures.

BACKGROUND: The aim of this study (EPIDIAB) was to assess the relationship between epicardial adipose tissue (EAT) and the micro and macrovascular complications (MVC) of type 2 diabetes (T2D).
METHODS: EPIDIAB is a post hoc analysis from the AngioSafe T2D study, which is a multicentric study aimed at determining the safety of antihyperglycemic drugs on retina and including patients with T2D screened for diabetic retinopathy (DR) (n = 7200) and deeply phenotyped for MVC. Patients included who had undergone cardiac CT for CAC (Coronary Artery Calcium) scoring after inclusion (n = 1253) were tested with a validated deep learning segmentation pipeline for EAT volume quantification.
RESULTS: Median age of the study population was 61 [54;67], with a majority of men (57%) a median duration of the disease 11 years [5;18] and a mean HbA1c of7.8 ± 1.4%. EAT was significantly associated with all traditional CV risk factors. EAT volume significantly increased with chronic kidney disease (CKD vs no CKD: 87.8 [63.5;118.6] vs 82.7 mL [58.8;110.8], p = 0.008), coronary artery disease (CAD vs no CAD: 112.2 [82.7;133.3] vs 83.8 mL [59.4;112.1], p = 0.0004, peripheral arterial disease (PAD vs no PAD: 107 [76.2;141] vs 84.6 mL[59.2; 114], p = 0.0005 and elevated CAC score (> 100 vs  < 100 AU: 96.8 mL [69.1;130] vs 77.9 mL [53.8;107.7], p < 0.0001). By contrast, EAT volume was neither associated with DR, nor with peripheral neuropathy. We further evidenced a subgroup of patients with high EAT volume and a null CAC score. Interestingly, this group were more likely to be composed of young women with a high BMI, a lower duration of T2D, a lower prevalence of microvascular complications, and a higher inflammatory profile.
CONCLUSIONS: Fully-automated EAT volume quantification could provide useful information about the risk of both renal and macrovascular complications in T2D patients.

UNASSIGNED: Pulmonary embolism (PE) is a serious and potentially life-threatening condition that requires prompt diagnosis and treatment. Identifying risk factors and diagnostic markers can aid in the early detection and management of this condition.
UNASSIGNED: This case-control study examined 10,077 patients admitted to Shenzhen Kangning Hospital\'s psychiatry facility in 2020. Among these, 65 patients were diagnosed with PE, including 50 new cases. After survival sampling for controls and age-and-gender matching, the study included 41 new PE cases and 41 age-and-gender-matched controls. Data on demographics, comorbidities, and medication use were extracted from electronic records. Conditional logistic regression analyses were performed to determine the association between each predictor and PE risk. Additionally, the sensitivity and specificity of the d-dimer diagnostic tool were assessed.
UNASSIGNED: In univariable conditional logistic regression, active alcoholism was associated with a higher PE risk (OR=3.675, 95% CI 1.02-13.14, P=0.046). A history of physical restraint (OR=4.33, 95% CI 1.24-15.21, P=0.022) and chemical restraint (OR 4.67, 95% CI 1.34-16.24, p=0.015) also increased PE risk, as did benzodiazepine use (OR=3.33, 95% CI 1.34-8.30, P=0.010). Conversely, psychotropic medication before admission was associated with a lower risk of PE (OR=0.07, 95% CI 0.01-0.59, P=0.013). Stepwise multivariable forward conditional regression identified two subsets of psychiatric patients at higher risk of PE: new psychiatric cases without medication at admission who were chemically restrained, and cases without medication at admission who were started on antipsychotics and benzodiazepines. The d-dimer diagnostic tool, with an optimal threshold of 570 ng/ml determined by the Youden index (J statistic of 0.6098), showed a sensitivity of 73.17% and specificity of 87.80% for detecting PE, with an AUC of 0.833 (95% CI: 0.735-0.906).
UNASSIGNED: Our findings suggest that a history of restraint, alcoholism, and the use of antipsychotics and benzodiazepines are important predictors of PE in psychiatric inpatients. Conversely, psychotropic medications at admission may be linked to a lower PE risk. The d-dimer diagnostic tool shows good value for screening PE in psychiatric inpatients. These predictors and diagnostic markers could help clinicians identify high-risk patients and implement appropriate prevention strategies.

BACKGROUND: We compared ultra-high resolution (UHR), standard resolution (SR), and virtual non-calcium (VNCa) reconstruction for coronary artery stenosis evaluation using photon-counting computed tomography (PC-CT).
METHODS: One vessel phantom (4-mm diameter) containing solid calcified lesions with 25% and 50% stenoses inside a thorax phantom with motion simulation underwent PC-CT using UHR (0.2-mm slice thickness) and SR (0.6-mm slice thickness) at heart rates of 60 beats per minute (bpm), 80 bpm, and 100 bpm. A paired t-test or Wilcoxon test with Bonferroni correction was used.
RESULTS: For 50% stenosis, differences in percent mean diameter stenosis between UHR and SR at 60 bpm (51.0 vs 60.3), 80 bpm (51.7 vs 59.6), and 100 bpm (53.7 vs 59.0) (p ≤ 0.011), as well as between VNCa and SR at 60 bpm (50.6 vs 60.3), 80 bpm (51.5 vs 59.6), and 100 bpm (53.7 vs 59.0) were significant (p ≤ 0.011), while differences between UHR and VNCa at all heart rates (p ≥ 0.327) were not significant. For 25% stenosis, differences between UHR and SR at 60 bpm (28.0 vs 33.7), 80 bpm (28.4 vs 34.3), and VNCa vs SR at 60 bpm (29.1 vs 33.7) were significant (p ≤ 0.015), while differences for UHR vs SR at 100 bpm (29.9 vs 34.0), as well as for VNCa vs SR at 80 bpm (30.7 vs 34.3) and 100 bpm (33.1 vs 34.0) were not significant (p ≥ 0.028).
CONCLUSIONS: Stenosis quantification accuracy with PC-CT improved using either UHR acquisition or VNCa reconstruction.
CONCLUSIONS: PC-CT offers to scan with UHR mode and the reconstruction of VNCa images both of them could provide improved coronary stenosis quantification at increased heart rates, allowing a more accurate stenosis grading at low and high heart rates compared to SR.
CONCLUSIONS: Evaluation of coronary stenosis with conventional CT is challenging at high heart rates. PC-CT allows for scanning with ECG-gated UHR and SR modes. UHR and VNCa images were compared in a dynamic phantom. UHR improves stenosis quantification up to 100 bpm. VNCa reconstruction improves stenosis evaluation up to 80 bpm.

BACKGROUND: The aim of this study is to explore the clinical value of computed tomography angiography (CTA) in the diagnosis of aortic aneurysm.
METHODS: The imaging data of 60 patients suspected of having aortic aneurysms who were examined in the Radiology Department of the First Affiliated Hospital of Nanjing Medical University from April 2017 to April 2020 were analyzed retrospectively. CTA and digital subtraction angiography (DSA) were used to examine the patients, and CTA image findings were collected and compared with DSA findings.
RESULTS: There was no significant difference in the accuracy of diagnosing aortic aneurysms (P > 0.05) between DSA [98.33% (59/60)] and CTA [95.00% (57/60)]. There was no significant difference in the diagnosis of image features (e.g., typing, site, form) of aortic aneurysms (P > 0.05).
CONCLUSIONS: CTA can be used to successfully confirm if patients suffer from an aortic aneurysm; it produces quality images with high specificity, sensitivity, and accuracy and can be promoted in clinical practice.

BACKGROUND: Menopausal vasomotor symptoms (VMS) are increasingly emphasized as a potentially important cardiovascular risk factor, but their role is still unclear. We assessed the association between VMS and subclinical atherosclerotic cardiovascular disease in peri- and postmenopausal women.
RESULTS: Using a cross-sectional study design, questionnaire data were collected from a population-based sample of women aged 50 to 64. The questionnaire asked whether menopause was/is associated with bothersome VMS. A 4-point severity scale was used: (1) never, (2) mild, (3) moderate, and (4) severe. The VMS duration and time of onset were also assessed. Associations with subclinical atherosclerotic cardiovascular disease, detected via coronary computed tomography angiography, coronary artery calcium score, and carotid ultrasound were assessed using the outcome variables \"any coronary atherosclerosis,\" \"segmental involvement score >3,\" \"coronary artery calcium score >100,\" and \"any carotid plaque,\" using logistic regression. Covariate adjustments included socioeconomic, lifestyle, and clinical factors. Of 2995 women, 14.2% reported ever severe, 18.1% ever moderate, and 67.7% ever mild/never VMS. Using the latter as reference, ever severe VMS were significantly associated with coronary computed tomography angiography-detected coronary atherosclerosis (multivariable adjusted odds ratio, 1.33 [95% CI, 1.02-1.72]). Corresponding results for ever severe VMS persisting >5 years or beginning before the final menstrual period were 1.50 (95% CI, 1.07-2.11) and 1.66 (95% CI, 1.10-2.50), respectively. No significant association was observed with segmental involvement score >3, coronary artery calcium score >100, or with any carotid plaque.
CONCLUSIONS: Ever occurring severe, but not moderate, VMS were significantly associated with subclinical coronary computed tomography angiography-detected atherosclerosis, independent of a broad range of cardiovascular risk factors and especially in case of long durations or early onset.

Background Deep learning (DL) could improve the labor-intensive, challenging processes of diagnosing cerebral aneurysms but requires large multicenter data sets. Purpose To construct a DL model using a multicenter data set for accurate cerebral aneurysm segmentation and detection on CT angiography (CTA) images and to compare its performance with radiology reports. Materials and Methods Consecutive head or head and neck CTA images of suspected unruptured cerebral aneurysms were gathered retrospectively from eight hospitals between February 2018 and October 2021 for model development. An external test set with reference standard digital subtraction angiography (DSA) scans was obtained retrospectively from one of the eight hospitals between February 2022 and February 2023. Radiologists (reference standard) assessed aneurysm segmentation, while model performance was evaluated using the Dice similarity coefficient (DSC). The model\'s aneurysm detection performance was assessed by sensitivity and comparing areas under the receiver operating characteristic curves (AUCs) between the model and radiology reports in the DSA data set with use of the DeLong test. Results Images from 6060 patients (mean age, 56 years ± 12 [SD]; 3375 [55.7%] female) were included for model development (training: 4342; validation: 1086; and internal test set: 632). Another 118 patients (mean age, 59 years ± 14; 79 [66.9%] female) were included in an external test set to evaluate performance based on DSA. The model achieved a DSC of 0.87 for aneurysm segmentation performance in the internal test set. Using DSA, the model achieved 85.7% (108 of 126 aneurysms [95% CI: 78.1, 90.1]) sensitivity in detecting aneurysms on per-vessel analysis, with no evidence of a difference versus radiology reports (AUC, 0.93 [95% CI: 0.90, 0.95] vs 0.91 [95% CI: 0.87, 0.94]; P = .67). Model processing time from reconstruction to detection was 1.76 minutes ± 0.32 per scan. Conclusion The proposed DL model could accurately segment and detect cerebral aneurysms at CTA with no evidence of a significant difference in diagnostic performance compared with radiology reports. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Payabvash in this issue.

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BACKGROUND: There is limited understanding of the pathomechanistic relationship between leptomeningeal collateral formation and ischaemic stroke aetiology. We aimed to assess the association of leptomeningeal collateral status and ischaemic stroke aetiology, using the widely recognised \"Trial of Org 10172 in Acute Stroke Treatment\" (TOAST) classification categorising strokes into five distinct aetiologies.
METHODS: Retrospective study of consecutively admitted adult ischaemic stroke patients at a Swiss stroke centre. Leptomeningeal collateral status was assessed on admission with single-phase CT-angiographies using a validated 4-point score. Patients were categorised into large-artery atherosclerosis (LAA), cardioembolic (CE), small-vessel disease (SVD) and cryptogenic (CG) according to the TOAST classification. We performed ordinal and binary (poor [collaterals filling ≤50% of the occluded territory] vs good [collaterals filling >50% of the occluded territory] collateralisation) logistic regression to evaluate the impact of TOAST aetiology on collateral status.
RESULTS: Among 191 patients, LAA patients had better collateral status compared to non-LAA aetiology (LAA: 2 vs CE: 2 vs SVD: 3 vs CG: 2, pLAA vs non-LAA = 0.04). In weighted multivariate logistic regression, LAA and SVD independently predicted better collateral status (binary models [adjusted odds ratio; aOR]: LAA: 3.72 [1.21-11.44] and SVD: 4.19 [1.21-14.52]; ordinal models [adjusted common odds ratio; acOR]: LAA: 2.26 [95% CI: 1.23-4.15] and SVD: 1.94 [1.03-3.66]), while CE predicted worse collateral status (binary models [aOR]: CE: 0.17 [0.07-0.41]; ordinal models [acOR]: CE: 0.24 [0.11-0.51]).
CONCLUSIONS: The aetiology of ischaemic stroke is associated with leptomeningeal collateral status on single-phase CT-angiography, with LAA and SVD predicting better and CE predicting worse collateral status.

OBJECTIVE: To validate the image quality of low-dose ultra-high-resolution (UHR) scanning mode of photon-counting detector CT (PCD-CT) for visceral artery computed tomography angiography (CTA).
METHODS: We prospectively enrolled 57 patients each in the full dose (FD) and low-dose (LD) protocols, respectively, to undergo abdominal CT scans using the UHR mode on a PCD-CT system (NAEOTOM Alpha), between April 2023 and September 2023. Both the FD data and LD data were then reconstructed into two series of images: (a) 0.2 mm slice thickness, reconstruction kernel Bv48, quantum iterative reconstruction (QIR) 4; (b)1 mm slice thickness, Bv40, QIR 3. The signal-to-noise ratios (SNRs) and contrast-to-noise ratios (CNRs) of seven arteries were objectively measured. The image noise, vessel sharpness, overall quality, and visibility of nine arteries were subjectively assessed by three radiologists.
RESULTS: The SNRs and CNRs of 0.2 mm reconstruction set was inferior to that of 1 mm reconstruction set (p < 0.001 for all the arteries and noise), however, the image quality of 0.2 mm reconstruction set was higher than that of 1 mm reconstruction set in qualitative evaluation especially for tiny arteries in Volume-rendered (VR) image (p < 0.001). The SNRs and CNRs were not significantly higher for FD group than LD group on the same slice thickness except for SNRs of common hepatic artery, splenic artery and bilateral renal arteries in 0.2 mm reconstruction set. In the comparison on image quality between normal weight and overweight patients within the same reconstruction set, the results showed that low-dose scan did not significantly impact the image quality in overweight patients. The ratings of visibility of nine visceral arteries were not significantly different among FD and LD at the same thickness reconstruction set except for superior mesenteric artery (p = 0.002 and 0.007 for 0.2 mm and 1 mm reconstruction set in axial image; p = 0.002 and 0.007 for 0.2 mm and 1 mm reconstruction set in coronal image, respectively) and left gastric artery (p = 0.002 and p < 0.001 for 0.2 mm and 1 mm reconstruction set in VR image, respectively).
CONCLUSIONS: The low-dose UHR scanning mode of PCD-CT has proven to be adequate for the clinical evaluation of visceral arteries. Utilizing a reconstruction with a slice thickness of 0.2 mm could enhance arterial depiction, particularly for small vessels.