The value of computed tomography angiography for evaluation of left atrial enlargement in patients with persistent atrial fibrillation.

BACKGROUND: The post-processing technology of CTA offers significant advantages in evaluating left atrial enlargement (LAE) in patients with persistent atrial fibrillation (PAF). This study aims to identify parameters for rapidly and accurately diagnosing LAE in patients with PAF using CT cross-sections. METHODS: Left atrial pulmonary venous (PV) CT was performed to 300 PAF patients with dual-source CT, and left atrial volume (LAV), left atrial anteroposterior diameter (LAD1), left atrial transverse diameter (LAD2), and left atrial area (LAA) were measured in the ventricular end systolic (ES) and middle diastolic (MD). LA index (LAI) = LA parameter/body surface area (BSA). Left atrial volume index (LAVIES) > 77.7 ml/m2 was used as the reference standard for the LAE diagnosis. RESULTS: 227 patients were enrolled in the group, 101 (44.5%) of whom had LAE. LAVES and LAVMD (r = 0.983), LAVIES and LAVIMD (r = 0.984), LAAES and LAVIES (r = 0.817), LAAMD and LAVIES (r = 0.814) had strong positive correlations. The area under curve (AUC) showed that all measured parameters were suitable for diagnosing LAE, and the diagnostic efficacy was compared as follows: LAA/LAAI> LAD> the relative value index of LAD, LAD2> LAD1. LAA and LAAI demonstrated comparable diagnostic efficacy, with LAA being more readily available than LAAI. CONCLUSIONS: The axial LAA measured by CTA can be served as a parameter for the rapid and accurate diagnosis of LAE in patients with PAF.

Application of predictive model based on CT radiomics and machine learning in diagnosis for occult locally advanced esophageal squamous cell carcinoma before treatment: A two-center study.

PURPOSE: Development and validation of a radiomics model for predicting occult locally advanced esophageal squamous cell carcinoma (LA-ESCC) on computed tomography (CT) radiomic features before implementation of treatment. METHODS: The study retrospectively collected 574 patients with esophageal squamous cell carcinoma (ESCC) from two medical centers, which were divided into three cohorts for training, internal and external validation. After delineating volume of interest (VOI), radiomics features were extracted and subjected to feature selection using three robust methods. Subsequently, 10 machine learning models were constructed, among which the optimal model was utilized to establish a radiomics signature. Furthermore, a predictive nomogram incorporating both clinical and radiomics signatures was developed. The performance of these models was evaluated through receiver operating characteristic curves, calibration curves, decision curve analysis as well as measures including accuracy, sensitivity, and specificity. RESULTS: A total of 19 radiomics features were selected. The multilayer perceptron (MLP), which was found to be optimal, achieved an AUC of 0.919, 0.864 and 0.882 in the training, internal and external validation cohorts, respectively. Similarly, MLP showed good accuracy in distinguish occult LA-ESCC in subgroup of cT1-2N0M0 diagnosed by clinicians with 0.803 and 0.789 in two validation cohorts respectively. By incorporating the radiomics signature with clinical signature, a predictive nomogram demonstrated superior prediction performance with an AUC of 0.877 and accuracy of 0.85 in external validation cohort. CONCLUSION: The radiomics and machine learning model can offers improved accuracy in prediction of occult LA-ESCC, providing valuable assistance to clinicians when choosing treatment plans.

A nomogram model of spectral CT quantitative parameters and clinical characteristics predicting lymphovascular invasion of gastric cancer.

Objective: The study established a nomogram based on quantitative parameters of spectral computed tomography (CT) and clinical characteristics, aiming to evaluate its predictive value for preoperative lymphovascular invasion (LVI) in gastric cancer (GC). Methods: From December 2019 to December 2021, 171 patients with pathologically confirmed GC were retrospectively collected with corresponding clinical data and spectral CT quantitative data. Patients were divided into LVI-positive and LVI-negative groups based on their pathological results. The univariate and multivariate logistic regression analyses were used to identify the risk factors and construct a nomogram. The calibration curve and receiver operating characteristic (ROC) curve were adopted to evaluate the predictive accuracy of nomogram. Results: Four clinical characteristics or spectral CT quantitative parameters, including Borrmann classification (P = 0.039), CA724 (P = 0.007), tumor thickness (P = 0.031), and iodine concentration in the venous phase (VIC) (P = 0.004) were identified as independent factors for LVI in GC patients. The nomogram was established based on the four factors, which had a potent predictive accuracy in the training, internal validation and external validation cohorts, with the area under the ROC curve (AUC) of 0.864 (95% CI, 0.798-0.930), 0.964 (95% CI, 0.903-1.000) and 0.877 (95% CI, 0.759-0.996), respectively. Conclusion: This study constructed a comprehensive nomogram consisting spectral CT quantitative parameters and clinical characteristics of GC, which exhibited a robust efficiency in predicting LVI in GC patients.

Preoperative prediction of lymphovascular and perineural invasion in gastric cancer using spectral computed tomography imaging and machine learning.

BACKGROUND: Lymphovascular invasion (LVI) and perineural invasion (PNI) are important prognostic factors for gastric cancer (GC) that indicate an increased risk of metastasis and poor outcomes. Accurate preoperative prediction of LVI/PNI status could help clinicians identify high-risk patients and guide treatment decisions. However, prior models using conventional computed tomography (CT) images to predict LVI or PNI separately have had limited accuracy. Spectral CT provides quantitative enhancement parameters that may better capture tumor invasion. We hypothesized that a predictive model combining clinical and spectral CT parameters would accurately preoperatively predict LVI/PNI status in GC patients. AIM: To develop and test a machine learning model that fuses spectral CT parameters and clinical indicators to predict LVI/PNI status accurately. METHODS: This study used a retrospective dataset involving 257 GC patients (training cohort, n = 172; validation cohort, n = 85). First, several clinical indicators, including serum tumor markers, CT-TN stages and CT-detected extramural vein invasion (CT-EMVI), were extracted, as were quantitative spectral CT parameters from the delineated tumor regions. Next, a two-step feature selection approach using correlation-based methods and information gain ranking inside a 10-fold cross-validation loop was utilized to select informative clinical and spectral CT parameters. A logistic regression (LR)-based nomogram model was subsequently constructed to predict LVI/PNI status, and its performance was evaluated using the area under the receiver operating characteristic curve (AUC). RESULTS: In both the training and validation cohorts, CT T3-4 stage, CT-N positive status, and CT-EMVI positive status are more prevalent in the LVI/PNI-positive group and these differences are statistically significant (P < 0.05). LR analysis of the training group showed preoperative CT-T stage, CT-EMVI, single-energy CT values of 70 keV of venous phase (VP-70 keV), and the ratio of standardized iodine concentration of equilibrium phase (EP-NIC) were independent influencing factors. The AUCs of VP-70 keV and EP-NIC were 0.888 and 0.824, respectively, which were slightly greater than those of CT-T and CT-EMVI (AUC = 0.793, 0.762). The nomogram combining CT-T stage, CT-EMVI, VP-70 keV and EP-NIC yielded AUCs of 0.918 (0.866-0.954) and 0.874 (0.784-0.936) in the training and validation cohorts, which are significantly higher than using each of single independent factors (P < 0.05). CONCLUSION: The study found that using portal venous and EP spectral CT parameters allows effective preoperative detection of LVI/PNI in GC, with accuracy boosted by integrating clinical markers.

Clinical application of super-low-positioned intestinal decompression tube in the treatment of intestinal obstruction: a pilot study.

OBJECTIVE: This study aimed to evaluate the clinical application and efficacy of a super-low-positioned intestinal decompression tube in the treatment of intestinal obstruction. METHODS: A total of 130 patients with postoperative small bowel obstruction were included in this study. The patients were divided into a super-low-positioned intestinal decompression group and a conventional intestinal decompression group. The clinical data, treatment outcomes, and complications were compared between the two groups. RESULTS: The technical success rate of placing the super-low-positioned intestinal decompression tube was 100%, with no intraoperative complications. The patients in the super-low-positioned intestinal decompression group had a significantly shorter hospital stay (8.3 ± 5.2 vs 17.7 ± 13.3, P < 0.001) and a higher non-operative treatment success rate (83.6% vs 57.9%, P = 0.001) compared to the conventional intestinal decompression group. Multivariate logistic regression analysis showed that the placement of a super-low-positioned intestinal decompression tube was an independent protective factor for treatment outcomes (P = 0.001). The hospital stay was significantly shorter in the super-low-positioned intestinal decompression group compared to the conventional group in both successful non-operative treatment patients (6.9 ± 3.0 vs 11.2 ± 7.5, P < 0.001) and failed non-operative treatment patients (16.2 ± 7.4 vs 26.6 ± 14.4, P < 0.001). The super-low-positioned intestinal decompression tube effectively relieved the "Self-strangulation" phenomenon in patients with intestinal obstruction. CONCLUSION: The super-low-positioned intestinal decompression tube is a safe and effective method for the treatment of intestinal obstruction, with better treatment outcomes and shorter hospital stays compared to conventional intestinal decompression. Further prospective studies are needed to validate these findings.

Short-term outcomes of a new gastrointestinal decompression tube combined with conservative treatment in patients with esophagojejunal anastomotic leakage after total gastrectomy.

To compare the short-term outcomes of a new gastrointestinal decompression tube combined with conservative treatment in patients with esophagojejunal anastomotic leakage (EJAL) after total gastrectomy. We retrospectively analyzed the data of 81 patients with EJAL who had undergone total gastrectomy and Roux-en-Y reconstruction at Fujian Medical University Union Hospital between January 2014 and December 2021. The patients were divided into experimental (12 patients with new gastrointestinal decompression tube plus conservative treatment) and control (69 patients with conservative treatment) groups, according to the different treatment methods they received. Anatomic defect size linearly correlated with time to clinical success, hospital stay, and hospital cost in the control group. The two groups showed no significant differences in anastomotic defect size, time of defect after surgery, hospitalization cost, and time of antibiotic use. However, the time to clinical success was significantly shorter in the experimental group than in the control group (16.0 ± 8.3 vs. 23.6 ± 17.8, P = 0.04), as was the length of hospital stay (30.1 ± 6.3 vs. 36.8 ± 16.7, P = 0.017). Furthermore, when the defect size was ≥ 4 mm, the time to clinical success, hospital stay, and hospital cost in the experimental group were lower than those in the control group (P < 0.05). Placement of a new gastrointestinal decompression tube is a safe treatment. When the defect size is ≥ 4 mm, the time to clinical success, length of hospital stay, and hospital cost can be reduced.

Role of pyroglutamic acid in cumulus cells of women with polycystic ovary syndrome.

PURPOSE: Polycystic ovary syndrome is a complex heterogeneous endocrine disorder associated with established metabolic abnormalities and is a common cause of infertility in females. Glutathione metabolism in the cumulus cells (CCs) of women with PCOS may be correlated to the quality of oocytes for infertility treatment; therefore, we used a metabolomics approach to examine changes in CCs from women with PCOS and oocyte quality. METHODS: Among 135 women undergoing fertility treatment in the present study, there were 43 women with PCOS and 92 without. CCs were collected from the two groups and levels of pyroglutamic acid were measured using LC-MS/MS followed by qPCR and Western blot analysis to examine genes and proteins involved in pyroglutamic acid metabolism related to glutathione synthesis. RESULTS: Women with PCOS showed increased levels of L-pyroglutamic acid, L-glutamate, and L-phenylalanine and decreased levels of Cys-Gly and N-acetyl-L-methionine. Gene expression of OPLAH, involved in pyroglutamic synthesis, was significantly increased in women with PCOS compared with those without. Gene expression of GSS was significantly decreased in women with PCOS and synthesis of glutathione synthetase protein was decreased. Expression of nuclear factor erythroid 2-related factor 2, involved in resistance to oxidative stress, was significantly increased in women with PCOS. CONCLUSIONS: CCs of women with PCOS showed high concentrations of pyroglutamic acid and reduced glutathione synthesis, which causes oxidative stress in CCs, suggesting that decreased glutathione synthesis due to high levels of pyroglutamic acid in CCs may be related to the quality of oocytes in women with PCOS.

Effect of Cerebral Ischemic Strokes in Different Cerebral Artery Regions on Left Ventricular Function.

Objectives: The relationship between cerebral ischemic stroke and left ventricular function evaluated by echocardiography has been emphasized. Whether lesions in different cerebral artery regions would result in left ventricular dysfunction remains uncertain. Methods: Patients were divided into middle cerebral artery (MCA) (n = 79), posterior cerebral artery (PCA) (n = 64), basilar artery (BA) regions (n = 66), and no-ischemic stroke group (n = 209). We retrospectively collected demographic characteristics, hematologic parameters, and ECG results, and a comparison of echocardiographic parameters was performed to determine the relationship between ischemic stroke and left ventricular function. Results: A total of 418 patients were included. Demographic characteristics did not significantly differ between the ischemic stroke and non-ischemic stroke groups, except for a history of drinking (p < 0.001). Homocysteine levels in the MCA group were higher than those in the PCA and BA groups (p < 0.05). The highly sensitive C-reactive protein (hs-CRP) level was higher in the ischemic stroke group than in the non-ischemic stroke one (p = 0.001). A higher incidence of ST-T changes in the ECG and lower levels of potassium and magnesium in the ischemic stroke group were found. Significant differences in diastolic function between groups were noted, and the early mitral inflow velocity, annular early diastolic velocity, and ratio between the mitral annular early diastolic velocity and mitral annulus atrial inflow velocity in the MCA group were lower than those in the BA group (p < 0.05). Conclusions: Ischemic strokes exhibited a negative effect on left ventricular diastolic function by echocardiography, especially in MCA region infarcts. These results are of great importance for neurologists as they highlight the need for left ventricular function evaluation after stroke to regulate therapy strategies in time.

Abnormal cerebral microstructures revealed by diffusion kurtosis imaging in amyotrophic lateral sclerosis.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease in which cerebral structural impairment is a consistent feature. PURPOSE: To investigate cerebral microstructural changes in ALS using diffusion kurtosis imaging (DKI) for the first time. STUDY TYPE: Prospective. SUBJECTS: Eighteen ALS patients and 20 healthy controls. FIELD STRENGTH/SEQUENCE: DKI images were obtained by a spin-echo echo-planar imaging sequence on a 3T MRI scanner, with three b-values (0, 1000, and 2000 s/mm2 ) and 64 diffusion encoding directions. ASSESSMENT: The revised ALS Functional Rating Scale (ALSFRS-R) was administered to assess disease severity, and the symptom duration and disease progression rate were also recorded. Voxel-based analysis was applied to examine the alteration of DKI metrics (ie, mean kurtosis metrics [MK], axial kurtosis [AK], and radial kurtosis [RK]) and the conventional diffusion metrics (ie, fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity). STATISTICAL TESTS: Student's t-test, chi-square test, and Pearson correlation analysis. RESULTS: ALS patients showed MK reductions in gray matter areas, including the bilateral precentral gyrus, bilateral paracentral lobule, and left anterior cingulate gyrus; they also showed decreased MK values in white matter (WM) in the bilateral precentral gyrus, bilateral corona radiata, bilateral middle corpus callosum, left occipital lobe, and right superior parietal lobule. The spatial distribution of the regions with reduced RK was similar to those with decreased MK. No significant AK difference was found between groups. The correlation analysis revealed significant associations between DKI metrics and clinical assessments such as ALSFRS-R score and disease duration. Additionally, several WM regions showed between-group differences in conventional diffusion metrics; but the spatial extent was smaller than that with reduced DKI metrics. DATA CONCLUSION: The reduction in DKI metrics indicates decreased microstructural complexity in ALS, involving both motor-related areas and extramotor regions. DKI metrics can serve as potential biomarkers for assessing disease severity. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2020;51:554-562.

Brain white matter abnormalities and correlation with severity in amyotrophic lateral sclerosis: An atlas-based diffusion tensor imaging study.

OBJECTIVES: To assess microstructural alterations in white matter (WM) in amyotrophic lateral sclerosis (ALS) using diffusion tensor imaging (DTI). METHODS: DTI data were collected from 34 subjects (18 patients with ALS and 16 healthy controls). The atlas-based region of interest (ROI) analysis was conducted to assess WM microstructure in ALS by combining intra-voxel metrics, which included fractional anisotropy (FA) and mean diffusivity (MD), and an inter-voxel metric, i.e., local diffusion homogeneity (LDH). Correlation analysis of diffusion values and clinical factors was also performed. RESULTS: ALS group showed a significant FA reduction in bilateral corticospinal tract (CST) as well as right uncinate fasciculus (RUF). The areas with higher MD were situated in right corticospinal tract (RCST), left cingulum hippocampus (LCH), RUF, and right superior longitudinal fasciculus (RSLF). Additionally, ALS patients showed decreased LDH in bilateral anterior thalamic radiation (ATR), bilateral CST and left inferior frontal-occipital fasciculus (LIFOF). Significant correlations were observed between ALSFRS-R (revised ALS Functional Rating Scale) scores or progression rate and FA in bilateral CST, as well as between disease duration and LDH in right CST. Receiver operating characteristic (ROC) analysis revealed the feasibility of employing diffusion metrics along the CST to distinguish two groups (AUC = 0.792-0.868, p < .005 for all). CONCLUSIONS: WM microstructural alteration is a common pathology in ALS, which can be detected by both intra- and inter-voxel diffusion metrics. The extent of abnormalities in several WM tracts such as ATR and LIFOF may be better assessed through the inter-voxel diffusion measurement.