Arterial Imaging Research Articles

CT radiomics for noninvasively predicting NQO1 expression levels in hepatocellular carcinoma.

Using noninvasive radiomics to predict pathological biomarkers is an innovative work worthy of exploration. This retrospective cohort study aimed to analyze the correlation between NAD(P)H quinone oxidoreductase 1 (NQO1) expression levels and the prognosis of patients with hepatocellular carcinoma (HCC) and to construct radiomic models to predict the expression levels of NQO1 prior to surgery. Data of patients with HCC from The Cancer Genome Atlas (TCGA) and the corresponding arterial phase-enhanced CT images from The Cancer Imaging Archive were obtained for prognosis analysis, radiomic feature extraction, and model development. In total, 286 patients with HCC from TCGA were included. According to the cut-off value calculated using R, patients were divided into high-expression (n = 143) and low-expression groups (n = 143). Kaplan-Meier survival analysis showed that higher NQO1 expression levels were significantly associated with worse prognosis in patients with HCC (p = 0.017). Further multivariate analysis confirmed that high NQO1 expression was an independent risk factor for poor prognosis (HR = 1.761, 95% CI: 1.136-2.73, p = 0.011). Based on the arterial phase-enhanced CT images, six radiomic features were extracted, and a new bi-regional radiomics model was established, which could noninvasively predict higher NQO1 expression with good performance. The area under the curve (AUC) was 0.9079 (95% CI 0.8127-1.0000). The accuracy, sensitivity, and specificity were 0.86, 0.88, and 0.84, respectively, with a threshold value of 0.404. The data verification of our center showed that this model has good predictive efficiency, with an AUC of 0.8791 (95% CI 0.6979-1.0000). In conclusion, there existed a significant correlation between the CT image features and the expression level of NQO1, which could indirectly reflect the prognosis of patients with HCC. The predictive model based on arterial phase CT imaging features has good stability and diagnostic efficiency and is a potential means of identifying the expression level of NQO1 in HCC tissues before surgery.

Improved cerebral blood flow and hippocampal blood flow in stroke-free patients after catheter ablation of atrial fibrillation.

Atrial fibrillation (AF) is a risk factor for reduced cerebral blood flow (CBF) and cognitive dysfunction, even in stroke-free patients. We aimed to test the hypothesis that CBF and hippocampal blood flow (HBF), measured with arterial spin labeling magnetic resonance imaging (MRI), improve after catheter ablation of AF to achieve sinus rhythm (SR). A total of 84 stroke-free patients (63.1 ± 9.1 years; paroxysmal AF, n = 50; non-paroxysmal AF, n = 34) undergoing AF catheter ablation were included. MRI studies were done before, 3 months, and 12 months after the procedure with CBF and HBF measurements. Baseline CBF and HBF values in 50 paroxysmal AF patients were used as controls. Baseline CBF was higher in patients with paroxysmal AF than with non-paroxysmal AF (100 ± 32% vs. 86 ± 28%, p = .04). Patients with non-paroxysmal AF had increased CBF 3 months after AF ablation (86 ± 28% to 99 ± 34%, p = .03). Differences in CBF and HBF were greater in the group with AF restored to SR (p < .01). Both CBF and HBF levels at 12 months were unchanged from the 3 months level. Successful rhythm control by catheter ablation was an independent predictor of an increase in CBF > 17.5%. The Mini-Mental State Examination score improved after ablation (p = .02). SR restoration with catheter ablation was associated with improved CBF and HBF at 3 months, maintenance of blood flow, and improved cognitive function at 12 months.

Daytime Variation in Kidney Perfusion, Oxygenation, and Sodium Concentration Assessed by Multiparametric MRI in Healthy Volunteers.

MRI can provide information on kidney structure, perfusion, and oxygenation. Furthermore, it allows for the assessment of kidney sodium concentrations and handling, allowing multiparametric evaluation of kidney physiology. Multiparametric MRI is promising for establishing prognosis and monitoring treatment responses in kidney diseases, but its intraindividual variation during the day is unresolved. To investigate the variation in multiparametric MRI measurements from the morning to the evening. Prospective. Ten healthy volunteers, aged 29 ± 5 without history of kidney disease. 3 T/T1 mapping, blood-oxygen level dependent imaging, arterial spin labeling perfusion imaging, diffusion weighted imaging, and sodium imaging. A multiparametric MRI protocol, yielding T1, R2*, ADC, renal blood flow and renal sodium levels, was acquired in the morning, noon, and evening. The participants were fasting prior to the first examination. Urine biochemical analyses were performed to complement MRI data. The cortex and medulla were analyzed separately in a semi-automatic fashion, and gradients of total sodium concentration (TSC) and R2* gradients were calculated from outer cortex to inner medulla. Analyses of variance and mixed-effects models to estimate differences from time of day. Coefficients of variation to assess variability within and between participants. A P-value <0.05 was considered statistically significant. The coefficients of variation varied from 5% to 18% for proton-based parametric sequences, while it was 38% for TSC over a day. Multiparametric MRI is stable over the day. The coefficients of variation over a day were lower for proton multiparametric MRI, but higher for sodium MRI. 2 TECHNICAL EFFICACY: Stage 2.

Regression of periventricular anastomosis after indirect revascularization in pediatric patients with moyamoya disease.

The aim of this study was to evaluate whether indirect revascularization in pediatric patients with moyamoya disease leads to periventricular anastomosis (PVA) regression, which is markedly developed in moyamoya vessels and is regarded as a risk factor for hemorrhage. Pediatric patients with moyamoya disease treated with indirect revascularization from 2011 to 2021 were included in this study. Magnetic resonance angiography and arterial spin labeling images acquired before and 1 year after surgery were assessed to obtain a visual scale of postoperative collateral artery formation, moyamoya vessels, PVA, and quantitative values of cerebral blood flow (CBF). The relationship between background information (age, sex, RNF213 p.R4810K variant status, and preoperative CBF) and postoperative collateral artery formation, as well as postoperative CBF improvement and regression of moyamoya vessels and PVA, was evaluated. Of 89 hemispheres in 58 patients (34 females; mean [SD] patient age 8.0 [3.4] years), 74.2% showed good postoperative collateral artery formation and a significant increase in CBF (p < 0.001). Postoperative PVA showed significant regression (postoperative score 1.46 [1.06] vs 2.02 [1.69], p = 0.001), especially in those arising from choroidal arteries (postoperative score 0.28 [0.50] vs 0.72 [0.67], p < 0.001). Compared with hemispheres without good collateral artery formation, those with good collateral artery formation were more likely to show a higher increase in CBF (9.74 [12.44] ml/min/100 g vs -4.86 [9.68] ml/min/100 g, p < 0.001) and regression of PVA (54.5% [36/66] vs 30.4% [7/23], p = 0.015). Although not statistically significant, patients with postoperative PVA progression were younger than those with regression (6.75 [3.03] years vs 8.18 [3.17] years, p = 0.188), and patients with the RNF213 p.R4810K variant were more likely to show regression (28/57 [49.1%] hemispheres vs 5/13 [38.5%] hemispheres, p = 0.069). Indirect revascularization in pediatric patients with moyamoya disease resulted in good collateral extracranial artery formation and an increase in CBF and PVA regression, especially of vessels arising from choroidal arteries. With good postoperative collateral artery development, patients were more likely to show improved CBF and regression of moyamoya vessels, including PVA. Whether postoperative PVA changes reduce future hemorrhage risk requires further investigation.

Identification of an Ultra-High-Risk Subgroup of Neuroblastoma Patients within the High-Risk Cohort Using a Computed Tomography-Based Radiomics Approach

To identify ultra-high-risk (UHR) neuroblastoma patients who experienced disease-related mortality within 18 months of diagnosis within the high-risk cohort using computed tomography (CT)-based radiomics analysis. A retrospective analysis was conducted on 105 high-risk neuroblastoma patients, divided into a training set (n=74) and a test set (n=31). Radiomics features were extracted and selected from arterial phase CT images, and an optimal radiomics signature was established using the support vector machine algorithm. Evaluation metrics, including area under the curve (AUC) and 95% confidence interval (CI), were calculated. Furthermore, the fit and clinical benefit of the signature, along with its correlation with overall survival (OS), were analyzed. The optimal radiomics signature comprised 11 features. In the training set, AUC and accuracy were 0.911 (95% CI: 0.840-0.982) and 0.892, respectively. In the test set, AUC and accuracy were 0.828 (95% CI: 0.669-0.987) and 0.839, respectively. There was no significant difference between predicted probability and actual probability, and the signature demonstrated net benefit. The concordance index of this signature for predicting OS was 0.743 (95% CI: 0.672-0.814) in the training set and 0.688 (95% CI: 0.566-0.810) in the test set. Moreover, the signature achieved AUC values of 0.832, 0.863, and 0.721 for 1-year, 2-year, and 3-year OS in the training set, and 0.870, 0.836, and 0.638 in the test set for the respective time periods. The utilization of CT-based radiomics signature to identify an UHR subgroup of neuroblastoma patients within the high-risk cohort can help aid in predicting early disease progression.

Applications of Near-Infrared Fluorescence Imaging and Angiography of Inferior Vesical Artery in Laparoscopic Lateral Lymph Node Dissection: A Prospective Nonrandomized Controlled Study

BACKGROUND: Near-infrared imaging with indocyanine green has been used to guide lateral lymph node dissection, yet its efficacy and benefits need further investigation. OBJECTIVE: To investigate the efficacy and feasibility of near-infrared fluorescence imaging and angiography of the inferior vesical artery in laparoscopic lateral lymph node dissection. DESIGN: A prospective nonrandomized controlled study. SETTINGS: Single-center study. PATIENTS: Patients with lower rectal cancer who underwent total mesorectal excision plus lateral lymph node dissection. MAIN OUTCOME MEASURES: A cohort of 108 patients was enrolled. After propensity score matching, 29 patients in the near-infrared group and 50 patients in the non–near-infrared group were matched. The total number of harvested lateral lymph nodes, positive lateral lymph nodes, inferior vesical artery preservation, and postoperative urinary function were compared. RESULTS: After propensity score matching, both groups had similar baseline characteristics. The total number of harvested lateral lymph nodes in the near-infrared group was significantly higher (12 vs 9, p = 0.013), but positive lateral lymph nodes were similar between the 2 groups (1 vs 1, p = 0.439). The inferior vesical artery preservation ratio was significantly increased with the aid of indocyanine green angiography (93.1% vs 56.0%, p &lt; 0.001). The non–near-infrared group required more days for urinary catheter removal than the near-infrared group (5 vs 4, p = 0.046). Urinary recatheterization tended to occur more frequently in the non–near-infrared group, with a marginally significant trend (16% vs 0%, p = 0.059). The non–near-infrared group tended to have more cases with residual urine volume ≥50 mL than the near-infrared group (20.0% vs 3.4%, p = 0.087), especially in the bilateral dissection subgroup (41.2% vs 0%, p = 0.041). LIMITATIONS: Small sample size. CONCLUSIONS: Near-infrared imaging increased the number of harvested lateral lymph nodes, whereas real-time indocyanine green fluorescence angiography ensured the preservation of the inferior vesical artery and tended to improve postoperative urinary function.

Heritability of cerebral blood flow in adolescent and young adult twins: an arterial spin labeling perfusion imaging study.

Blood perfusion is a fundamental physiological property of all organs and is closely linked to brain metabolism. Genetic factors were reported to have important influences on cerebral blood flow. However, the profile of genetic contributions to cerebral blood flow in adolescents or young adults was underexplored. In this study, we recruited a sample of 65 pairs of same-sex adolescent or young adult twins undergoing resting arterial spin labeling imaging to conduct heritability analyses. Our findings indicate that genetic factors modestly affect cerebral blood flow in adolescents or young adults in the territories of left anterior cerebral artery and right posterior cerebral artery, with the primary contribution being to the frontal regions, cingulate gyrus, and striatum, suggesting a profile of genetic contributions to specific brain regions. Notably, the regions in the left hemisphere demonstrate the highest heritability in most regions examined. These results expand our knowledge of the genetic basis of cerebral blood flow in the developing brain and emphasize the importance of regional analysis in understanding the heritability of cerebral blood flow. Such insights may contribute to our understanding of the underlying genetic mechanism of brain functions and altered cerebral blood flow observed in youths with brain disorders.

Multimodal Classification Framework Based on Hypergraph Latent Relation for End-Stage Renal Disease Associated with Mild Cognitive Impairment.

Combined arterial spin labeling (ASL) and functional magnetic resonance imaging (fMRI) can reveal more comprehensive properties of the spatiotemporal and quantitative properties of brain networks. Imaging markers of end-stage renal disease associated with mild cognitive impairment (ESRDaMCI) will be sought from these properties. The current multimodal classification methods often neglect to collect high-order relationships of brain regions and remove noise from the feature matrix. A multimodal classification framework is proposed to address this issue using hypergraph latent relation (HLR). A brain functional network with hypergraph structural information is constructed by fMRI data. The feature matrix is obtained through graph theory (GT). The cerebral blood flow (CBF) from ASL is selected as the second modal feature matrix. Then, the adaptive similarity matrix is constructed by learning the latent relation between feature matrices. Latent relation adaptive similarity learning (LRAS) is introduced to multi-task feature learning to construct a multimodal feature selection method based on latent relation (LRMFS). The experimental results show that the best classification accuracy (ACC) reaches 88.67%, at least 2.84% better than the state-of-the-art methods. The proposed framework preserves more valuable information between brain regions and reduces noise among feature matrixes. It provides an essential reference value for ESRDaMCI recognition.

Differences in distribution and features of carotid and middle cerebral artery plaque in patients with pial infarction and perforating artery infarction: A 3D vessel wall imaging study

PurposeAtherosclerotic plaques of carotid artery (CA) and middle cerebral artery (MCA) are important causes of acute ischemic stroke (AIS). This study was designed to jointly assess the plaque distribution and features of CA and MCA in AIS patients with pial infarction (PI) and perforating artery infarction (PAI), and to investigate the associations between plaque characteristics and ischemic infarction patterns. MethodsImaging data of sixty-five patients from a cross-sectional study were reviewed. All the patients had acute infarction in the MCA territory on diffusion weighted imaging (DWI) and underwent CA and MCA vessel wall imaging (VWI). The CA and MCA plaque presence and high-risk features on the ipsilateral side of infarction were analyzed. The brain infarction lesions were divided into PI group vs. non-PI group, and PAI group vs. non-PAI group. Different plaque distribution types and plaque features were compared in each two groups, and their associations were investigated using binary logistic regression. ResultsSixty-five patients (mean age, 54.6 ± 10.1 years; 61 men) were included. The CA high-risk plaque (OR: 5.683 [1.409–22.929], P = 0.015) and MCA plaque presence (OR: 3.949 [1.397–11.162], P = 0.010) were significantly associated with PI. MCA plaques that involved the orifice of the perforating arteries were significantly associated with PAI (OR: 15.167 [1.851–124.257], P = 0.011). ConclusionCA and MCA plaques show distinct distribution and high-risk features in patients with PI and PAI. Combined intracranial and extracranial arteries imaging should be considered for the evaluation of the symptomatic ischemic patients.

Defective hippocampal neurogenesis underlies cognitive impairment by carotid stenosis-induced cerebral hypoperfusion in mice.

Chronic cerebral hypoperfusion due to carotid artery stenosis is a major cause of vascular cognitive impairment and dementia (VCID). Bilateral carotid artery stenosis (BCAS) in rodents is a well-established model of VCID where most studies have focused on white matter pathology and subsequent cognitive deficit. Therefore, our aim was to study the implication of adult hippocampal neurogenesis in hypoperfusion-induced VCID in mice, and its relationship with cognitive hippocampal deficits. Mice were subjected to BCAS; 1 and 3 months later, hippocampal memory and neurogenesis/cell death were assessed, respectively, by the novel object location (NOL) and spontaneous alternation performance (SAP) tests and by immunohistology. Hypoperfusion was assessed by arterial spin labeling-magnetic resonance imaging (ASL-MRI). Hypoperfused mice displayed spatial memory deficits with decreased NOL recognition index. Along with the cognitive deficit, a reduced number of newborn neurons and their aberrant morphology indicated a remarkable impairment of the hippocampal neurogenesis. Both increased cell death in the subgranular zone (SGZ) and reduced neuroblast proliferation rate may account for newborn neurons number reduction. Our data demonstrate quantitative and qualitative impairment of adult hippocampal neurogenesis disturbances associated with cerebral hypoperfusion-cognitive deficits in mice. These findings pave the way for novel diagnostic and therapeutic targets for VCID.

Diffusion-weighted magnetic resonance imaging for the diagnosis of giant cell arteritis: a comparison with T1-weighted black-blood imaging.

To investigate the diagnostic performance of diffusion-weighted imaging (DWI) of the superficial cranial arteries in the diagnosis of GCA. Retrospectively, 156 patients with clinically suspected GCA were included. A new 4-point ordinal DWI rating scale was developed. A post-contrast, fat-suppressed, T1-weighted 'black-blood' sequence (T1-BB) was rated for comparison. Ten arterial segments were assessed: common superficial temporal arteries, temporal and parietal branches, occipital and posterior auricular arteries bilaterally. The expert clinical diagnosis after ≥6 months of follow-up was the diagnostic reference standard. Diagnostic accuracy was evaluated for different rating methods. The study cohort consisted of 87 patients with and 69 without GCA. For DWI, the area under the curve was 0.90. For a cut-off of ≥2 consecutive pathological slices, DWI showed a sensitivity of 75.9%, a specificity of 94.2% and a positive likelihood ratio of 13.09. With a cut-off of ≥3 consecutive pathological slices, sensitivity was 70.1%, specificity was 98.6% and the positive likelihood ratio was 48.38. For the T1-BB, values were 88.5%, 88.4% and 7.63, respectively. The inter-rater analysis for DWI with a cut-off of ≥2 pathological slices showed a kappa of 1.00 on the patient level and 0.85 on the arterial segment level. For the T1-BB the kappa was 0.78 and 0.79, respectively. DWI of the superficial cranial arteries demonstrates a good diagnostic accuracy and reliability for the diagnosis of GCA. DWI is widely available and can be used immediately in clinical practice for patients with suspected GCA.

Arterial spin-labeled magnetic resonance perfusion imaging in prediction of pediatric brain tumors grading: inter-observer agreement

BackgroundPediatric brain tumors are a major concern with many variable management options. Arterial spin-labeled magnetic resonance perfusion imaging is a relatively new and noninvasive technique that can help in predicting tumor grades and provide us with physiological data about the tumors which significantly aids in all stages of tumor care, including diagnosis, therapy, and follow-up.Aim of the studyTo determine agreement between independent observers in the assessment and prediction of brain tumor grading in pediatrics by arterial spin-labeled (ASL) magnetic resonance perfusion imaging.MethodsThirty-two patients (21 boys and 11 girls; mean age of (10.28 ± 4.31) years) with brain tumors were evaluated by ASL MRI perfusion. Image analysis was performed by two reviewers for quantifying absolute and relative tumoral blood flow (aTBF and rTBF) as well as qualitative assessment of the tumors in ASL color map images.ResultsThe inter-observer agreement for the mean aTBF and the mean rTBF values of the studied lesions was almost perfect (inter-class correlation coefficient (ICC) = 0.978, 0.997). There was substantial agreement between both observers for the qualitative assessment of the studied lesions in color ASL images (Kappa = 0.779, with % of agreement = 87.0%). The mean aTBF for grade I tumors was (24.64 ± 3.45 ml/100 g/min), for grade II tumors it was (33.81 ± 3.59 ml/100 g/min), while for high-grade tumors (grade III and IV tumors) it was (75.60 ± 20.0 ml/100 g/min) with (p < 0.001). The mean rTBF of grade I, II, and III/IV tumors was (1.01 ± 0.17); (1.07 ± 0.31); and (3.12 ± 0.24) with (p < 0.001).ConclusionsArterial spin-labeled perfusion MRI can help in the challenge of prediction of brain tumor grading in pediatrics with accurate quantitative and semi-quantitative measurements of perfusion parameters of the tumors as well as qualitative and visual assessment of the tumors.

Deep learning-based coronary computed tomography analysis to predict functionally significant coronary artery stenosis.

Fractional flow reserve derived from coronary CT (FFR-CT) is a noninvasive physiological technique that has shown a good correlation with invasive FFR. However, the use of FFR-CT is restricted by strict application standards, and the diagnostic accuracy of FFR-CT analysis may potentially be decreased by severely calcified coronary arteries because of blooming and beam hardening artifacts. The aim of this study was to evaluate the utility of deep learning (DL)-based coronary computed tomography (CT) data analysis in predicting invasive fractional flow reserve (FFR), especially in cases with severely calcified coronary arteries. We analyzed 184 consecutive cases (241 coronary arteries) which underwent coronary CT and invasive coronary angiography, including invasive FFR, within a three-month period. Mean coronary artery calcium scores were 963 ± 1226. We evaluated and compared the vessel-based diagnostic accuracy of our proposed DL model and a visual assessment to evaluate functionally significant coronary artery stenosis (invasive FFR < 0.80). A deep neural network was trained with consecutive short axial images of coronary arteries on coronary CT. Ninety-one coronary arteries of 89 cases (48%) had FFR-positive functionally significant stenosis. On receiver operating characteristics (ROC) analysis to predict FFR-positive stenosis using the trained DL model, average area under the curve (AUC) of the ROC curve was 0.756, which was superior to the AUC of visual assessment of significant (≥ 70%) coronary artery stenosis on CT (0.574, P = 0.011). The sensitivity, specificity, positive and negative predictive value (PPV and NPV), and accuracy of the DL model and visual assessment for detecting FFR-positive stenosis were 82 and 36%, 68 and 78%, 59 and 48%, 87 and 69%, and 73 and 63%, respectively. Sensitivity and NPV for the prediction of FFR-positive stenosis were significantly higher with our DL model than visual assessment (P = 0.0004, and P = 0.024). DL-based coronary CT data analysis has a higher diagnostic accuracy for functionally significant coronary artery stenosis than visual assessment.

The Effect of PCSK9 Inhibition on the Stabilization of Atherosclerotic Plaque Determined by Biochemical and Diagnostic Imaging Methods.

Atherosclerosis is a multifactorial, progressive, chronic inflammatory disease. Ultrasound and magnetic resonance imaging are the most accurate predictors of atherosclerotic plaque instability (MRI). Cytokines such as osteopontin, osteoprotegerin, and metalloproteinase 9 could be used as the most recent markers to identify and track the efficacy of anti-atherosclerotic therapy. Patients with USG and MRI-verified unstable atherosclerotic plaque were included in the study. Biomarker concentrations were measured and compared before and after PCSK9 inhibitor therapy. Additionally, concentrations prior to treatment were correlated with MRI images of the carotid artery. After treatment with alirocumab, the concentrations of MMP-9 (p < 0.01) and OPN, OPG (p < 0.05) decreased significantly. Furthermore, the results of OPN, OPG, and MMP 9 varied significantly depending on the type of atherosclerotic plaque in the MRI assay. In stable atherosclerotic plaques, the concentrations of OPN and OPG were greater (p < 0.01), whereas the concentration of MMP9 correlated with the instability of the plaque (p < 0.05). We demonstrated, probably for the first time, that alirocumab therapy significantly decreased the serum concentration of atherosclerotic plaque markers. In addition, we demonstrated the relationship between the type of atherosclerotic plaque as determined by carotid MRI and the concentration of these markers.

A Machine Learning Model for the prediction of the progression of carotid arterial stenoses.

Atherosclerotic carotid plaque development results in a steady narrowing of the artery lumen, which may eventually trigger catastrophic plaque rupture leading to thromboembolism and stroke. The primary cause of ischemic stroke in the EU is carotid artery disease, which increases the demand for tools for risk stratification and patient management in carotid artery disease. Additionally, advancements in cardiovascular modeling over the past few years have made it possible to build accurate three-dimensional models of patient-specific primary carotid arteries. Computational models then incorporate the aforementioned 3D models to estimate either the development of atherosclerotic plaque or a number of flow-related parameters that are linked to risk assessment. This work presents an attempt to provide a carotid artery stenosis prognostic model, utilizing non-imaging and imaging data, as well as simulated hemodynamic data. The overall methodology was trained and tested on a dataset of 41 cases with 23 carotid arteries with stable stenosis and 18 carotids with increasing stenosis degree. The highest accuracy of 71% was achieved using a neural network classifier. The novel aspect of our work is the definition of the problem that is solved, as well as the amount of simulated data that are used as input for the prognostic model.Clinical Relevance-A prognostic model for the prediction of the trajectory of carotid artery atherosclerosis is proposed, which can support physicians in critical treatment decisions.

Chest pain in cardiac amyloidosis: occurrence, causes and prognostic significance

BackgroundChest pain is experienced by patients with cardiac amyloidosis (CA), but a systematic investigation of its frequency, underlying etiologies and clinical significance is lacking. MethodsClinical, echocardiographic, laboratory characteristics, available coronary arteries imaging and endomyocardial biopsy (EMB) findings of 174 patients with CA (n = 104 with transthyretin, ATTR; n = 70 with light chains, AL) were analyzed. ResultsChest pain was reported in 66 (38%) CA patients. Compared to those without, patients with chest pain had more frequently a history of coronary artery disease (CAD) (27% vs 15%, p = 0.048) and heart failure (HF) symptoms (62% vs 43%, p = 0.015), higher high sensitivity troponin I (hs-cTnI, 101 vs 65 ng/L, p = 0.032) and higher brain natriuretic peptide (597 vs 407 ng/L, p = 0.024). Among CA patients with chest pain undergoing coronary arteries imaging (n = 37), obstructive CAD was detected in 14 (38%), 13 of whom with ATTR-CA. Of these 37 patients, EMB was available in 10 and vascular/perivascular amyloid deposition was detected in 4/5 (80%) of AL-CA patients and 1/5 ATTR-CA. Among patients with suspected acute coronary syndrome (n = 22), obstructive CAD was detected in 9/17 (53%) ATTR-CA and 0/5 AL-CA; hs-cTnI levels were similar between those with and without obstructive CAD. During a follow-up of 17 (8–34) months, chest pain was a significant predictor of HF hospitalization (HR1.86, 95% CI 1.02–3.39, p = 0.042), even after adjustment for CA subtype and CAD. ConclusionChest pain is a common symptom in patients with CA, reflects a more advanced cardiac impairment and predicts future HF hospitalization. The etiology of chest pain seems to differ, with obstructive CAD more frequent in ATTR-CA whilst amyloid vascular/perivascular involvement more common in AL-CA.

Coronary stent imaging in photon counting computed Tomography: Optimization of reconstruction kernels in a phantom

PurposeImaging stents and in-stent stenosis remains a challenge in coronary computed tomography angiography (CCTA). In comparison to conventional Computed Tomography, Photon Counting CT (PCCT) provides decisive clinical advantages, among other things by providing low dose ultra-high resolution imaging of coronary arteries. This work investigates the image quality in CCTA using clinically established kernels and those optimized for the imaging of cardiac stents in PCCT, both for in-vitro stent imaging in 400 μm standard resolution mode (SRM) and 200 μm Ultra High Resolution Mode (UHR). MethodsBased on experimental scans, vascular reconstruction kernels (Bv56, Bv64, Bv72) were optimized. In an established phantom, 10 different coronary stents with 3 mm diameter were scanned in the first clinically available PCCT. Scans were reconstructed with clinically established and optimized kernels. Four readers measured visible stent lumen, performed ROI-based density measurements and rated image quality. ResultsRegarding the visible stent lumen, UHR is significantly superior to SRM (p < 0.001). In all levels, the optimized kernels are superior to the clinically established kernels (p < 0.001). One optimized kernel showed a significant reduction of noise compared to the clinically established kernels. Overall image quality is improved with optimized kernels. ConclusionsIn a phantom study PCCT UHR with optimized kernels for stent imaging significantly improves the ability to assess the in-stent lumen of small cardiac stents. We recommend using UHR with an optimized sharp vascular reconstruction kernel (Bv72uo) for imaging of cardiac stent.

CT-based radiomics nomogram for prediction of survival after transarterial chemoembolization with drug-eluting beads in patients with hepatocellular carcinoma and portal vein tumor thrombus.

To develop and validate a CT-based radiomics model for the prediction of the overall survival (OS) of patients with hepatocellular carcinoma (HCC) and portal vein tumor thrombus (PVTT) treated with drug-eluting beads transarterial chemoembolization (DEB-TACE). Patients were retrospectively enrolled from two institutions for the constitution of training (n = 69) and validation (n = 31) cohorts with a median follow-up of 15months. A total of 396 radiomics features were extracted from each baseline CT image. Features selected by variable importance and minimal depth were used for random survival forest model construction. The performance of the model was assessed using the concordance index (C-index), calibration curves, integrated discrimination index (IDI), net reclassification index (NRI), and decision curve analysis. Type of PVTT and tumor number were proved to be significant clinical indicators for OS. Arterial phase images were used to extract radiomics features. Three radiomics features were selected for model construction. The C-index for the radiomics model was 0.759 in the training cohort and 0.730 in the validation cohort. To improve the predictive performance, clinical indicators were integrated into the radiomics model to form a combined model with a C-index of 0.814 in the training cohort and 0.792 in the validation cohort. The IDI was significant in both cohorts for the combined model versus the radiomics model in predicting 12-month OS. Type of PVTT and tumor number affected the OS of HCC patients with PVTT treated with DEB-TACE. Moreover, the combined clinical-radiomics model had a satisfactory performance. A CT-based radiomics nomogram, which consisted of 3 radiomics features and 2 clinical indicators, was recommended to predict 12-month overall survival of patients with hepatocellular carcinoma and portal vein tumor thrombus initially treated with drug-eluting beads transarterial chemoembolization. • Type of portal vein tumor thrombus and tumor number were significant predictors of the OS. • Integrated discrimination index and net reclassification index provided a quantitative evaluation of the incremental impact added by new indicators for the radiomics model. • A nomogram based on a radiomics signature and clinical indicators showed satisfactory performance in predicting OS after DEB-TACE.

Sweet taste preference is associated with greater hypothalamic response to glucose and longitudinal weight gain

The hypothalamus has an abundant expression of sweet taste receptors that play a role in glucose sensing and energy homeostasis. Evidence suggests that liking “sweets” can be associated with weight gain, but the relationship between sweet taste preference and hypothalamic regulation of appetite is unknown. This study tested the hypothesis that sweet taste preference is associated with increased hypothalamic activation in response to glucose (a purported neural marker for weight gain risk) and greater longitudinal increases in body mass index (BMI). Fifty-four adults aged 18–35 years with a mean (± SD) BMI of 27.99 ± 5.32 kg/m2 completed the study. Height and weight were measured at baseline and 6–12 months later in a subset of 36 participants. Sweet taste preference was assessed via the Monell 2-series, forced-choice tracking procedure. Arterial spin labeling magnetic resonance imaging was performed before and after oral glucose ingestion to determine hypothalamic blood flow response to glucose. Linear models were used to examine relationships between sweet taste preference and the hypothalamic response to glucose and longitudinal changes in BMI, adjusting for age, sex, and baseline BMI. Sweet taste preference was positively associated with glucose-linked hypothalamic blood flow (beta = 0.017, p = 0.043), adjusted for age, sex and BMI. We also observed a positive association between sweet taste preference and longitudinal change in BMI (beta = 0.088, p = 0.015), adjusted for age, sex and baseline BMI. These findings suggest that heightened sweet taste preference is associated with glucose-linked hypothalamic activation and may be linked to increased susceptibility for weight gain.

Factors related to unfavorable outcome in minor ischemic stroke

BackgroundStroke recurrence and disability are important challenges to overcome in patients with minor ischemic stroke. The aim of our study was to determine the factors associated with unfavorable outcomes in patients with minor ischemic stroke. MethodsThis was a prospective cohort study including patients with minor ischemic stroke with a National Institutes of Health Stroke Scale (NIHSS) score ≤ 4 who were treated at the Bach Mai Hospital stroke center from June 15, 2021, to September 15, 2022. Unfavorable outcome was defined as mRS 2-6 at 90 days. Multivariable logistic regression analysis was conducted to assess risk factors related to clinical outcomes. ResultsOf 678 patients presenting with minor ischemic stroke, there were 90 (13.3%, 90/678) patients with no intracranial artery imaging. Hence, 588 were patients analyzed, of whom 6.0% received thrombolytic therapy, 8.5% developed NIHSS > 4 in 24 hours, and 30.4% had intracranial stenosis > 50%. Compared with the group of unfavorable outcomes, the favorable outcome group had more NIHSS 0-1 (29.9% vs.8.7%, P<0.001), lower cardioembolic (3.2% vs.7.9%, P=0.021), low IV-tPA ratio (4.8% vs.10.3%, P=0.019), lower NIHSS progression > 4 in the first 24 hours (3.9% vs.25.4%, P<0.001), and lower ICAS rate (28.1% vs.38.9%, P=0.02). Multivariable regression analysis of factors affecting unfavorable outcomes included baseline NIHSS 2-4 (OR, 3.85; 95% CI, 1.97-7.52), NIHSS progression > 4 (OR, 7.57; 95% CI, 3.80-15.10), and ICAS (OR 1.68; 95%CI, 1.07-2.64). ConclusionsIn patients with minor ischemic stroke, unfavorable outcomes were associated with baseline NIHSS 2-4, NIHSS progression > 4 points in 24 hours, and ICAS. These factors may identify a patient population in need of close monitoring and at higher risk of adverse outcomes.