Early left ventricular microvascular dysfunction in diabetic pigs: a longitudinal quantitative myocardial perfusion CMR study.

BACKGROUND: Microvascular pathology is one of the main characteristics of diabetic cardiomyopathy; however, the early longitudinal course of diabetic microvascular dysfunction remains uncertain. This study aimed to investigate the early dynamic changes in left ventricular (LV) microvascular function in diabetic pig model using the cardiac magnetic resonance (CMR)-derived quantitative perfusion technique. METHODS: Twelve pigs with streptozotocin-induced diabetes mellitus (DM) were included in this study, and longitudinal CMR scanning was performed before and 2, 6, 10, and 16 months after diabetic modeling. CMR-derived semiquantitative parameters (upslope, maximal signal intensity, perfusion index, and myocardial perfusion reserve index [MPRI]) and fully quantitative perfusion parameters (myocardial blood flow [MBF] and myocardial perfusion reserve [MPR]) were analyzed to evaluate longitudinal changes in LV myocardial microvascular function. Pearson correlation was used to analyze the relationship between LV structure and function and myocardial perfusion function. RESULTS: With the progression of DM duration, the upslope at rest showed a gradually increasing trend (P = 0.029); however, the upslope at stress and MBF did not change significantly (P > 0.05). Regarding perfusion reserve function, both MPRI and MPR showed a decreasing trend with the progression of disease duration (MPRI, P = 0.001; MPR, P = 0.042), with high consistency (r = 0.551, P < 0.001). Furthermore, LV MPR is moderately associated with LV longitudinal strain (r = - 0.353, P = 0.022), LV remodeling index (r = - 0.312, P = 0.033), fasting blood glucose (r = - 0.313, P = 0.043), and HbA1c (r = - 0.309, P = 0.046). Microscopically, pathological results showed that collagen volume fraction increased gradually, whereas no significant decrease in microvascular density was observed with the progression of DM duration. CONCLUSIONS: Myocardial microvascular reserve function decreased gradually in the early stage of DM, which is related to both structural (but not reduced microvascular density) and functional abnormalities of microvessels, and is associated with increased blood glucose, reduced LV deformation, and myocardial remodeling.

Accelerated 3D MR neurography of the brachial plexus using deep learning-constrained compressed sensing.

OBJECTIVES: To explore the use of deep learning-constrained compressed sensing (DLCS) in improving image quality and acquisition time for 3D MRI of the brachial plexus. METHODS: Fifty-four participants who underwent contrast-enhanced imaging and forty-one participants who underwent unenhanced imaging were included. Sensitivity encoding with an acceleration of 2 × 2 (SENSE4x), CS with an acceleration of 4 (CS4x), and DLCS with acceleration of 4 (DLCS4x) and 8 (DLCS8x) were used for MRI of the brachial plexus. Apparent signal-to-noise ratios (aSNRs), apparent contrast-to-noise ratios (aCNRs), and qualitative scores on a 4-point scale were evaluated and compared by ANOVA and the Friedman test. Interobserver agreement was evaluated by calculating the intraclass correlation coefficients. RESULTS: DLCS4x achieved higher aSNR and aCNR than SENSE4x, CS4x, and DLCS8x (all p < 0.05). For the root segment of the brachial plexus, no statistically significant differences in the qualitative scores were found among the four sequences. For the trunk segment, DLCS4x had higher scores than SENSE4x (p = 0.04) in the contrast-enhanced group and had higher scores than SENSE4x and DLCS8x in the unenhanced group (all p < 0.05). For the divisions, cords, and branches, DLCS4x had higher scores than SENSE4x, CS4x, and DLCS8x (all p ≤ 0.01). No overt difference was found among SENSE4x, CS4x, and DLCS8x in any segment of the brachial plexus (all p > 0.05). CONCLUSIONS: In three-dimensional MRI for the brachial plexus, DLCS4x can improve image quality compared with SENSE4x and CS4x, and DLCS8x can maintain the image quality compared to SENSE4x and CS4x. CLINICAL RELEVANCE STATEMENT: Deep learning-constrained compressed sensing can improve the image quality or accelerate acquisition of 3D MRI of the brachial plexus, which should be benefit in evaluating the brachial plexus and its branches in clinical practice. KEY POINTS: •Deep learning-constrained compressed sensing showed higher aSNR, aCNR, and qualitative scores for the brachial plexus than SENSE and CS at the same acceleration factor with similar scanning time. •Deep learning-constrained compressed sensing at acceleration factor of 8 had comparable aSNR, aCNR, and qualitative scores to SENSE4x and CS4x with approximately half the examination time. •Deep learning-constrained compressed sensing may be helpful in clinical practice for improving image quality and acquisition time in three-dimensional MRI of the brachial plexus.

C3-Alkylation of Imidazo[1,2-a]pyridines via Three-Component Aza-Friedel-Crafts Reaction Catalyzed by Y(OTf)3.

As an important class of nitrogen-containing fused heterocyclic compounds, imidazo[1,2-a]pyridines often exhibit significant biological activities, such as analgesic, anticancer, antiosteoporosis, anxiolytic, etc. Using Y(OTf)3 as a Lewis acid catalyst, a simple and efficient method has been developed for the synthesis of C3-alkylated imidazo[1,2-a]pyridines through the three-component aza-Friedel-Crafts reaction of imidazo[1,2-a]pyridines, aldehydes, and amines in the normal air atmosphere without the protection of inert gas and special requirements for anhydrous and anaerobic conditions. A series of imidazo[1,2-a]pyridine derivatives were obtained with moderate to good yields, and their structures were confirmed by 1H NMR, 13C NMR, and HRMS. Furthermore, this conversion has the advantages of simple operation, excellent functional group tolerance, high atomic economy, broad substrate scope, and can achieve gram-level reactions. Notably, this methodology may be conveniently applied to the further design and rapid synthesis of potential biologically active imidazo[1,2-a]pyridines with multifunctional groups.

MRI-based multiregional radiomics for preoperative prediction of tumor deposit and prognosis in resectable rectal cancer: a bicenter study.

OBJECTIVE: To build T2WI-based multiregional radiomics for predicting tumor deposit (TD) and prognosis in patients with resectable rectal cancer. MATERIALS AND METHODS: A total of 208 patients with pathologically confirmed rectal cancer from two hospitals were prospectively enrolled. Intra- and peritumoral features were extracted separately from T2WI images and the least absolute shrinkage and selection operator was used to screen the most valuable radiomics features. Clinical-radiomics nomogram was developed by radiomics signatures and the most predictive clinical parameters. Prognostic model for 3-year recurrence-free survival (RFS) was constructed using univariate and multivariate Cox analysis. RESULTS: For TD, the area under the receiver operating characteristic curve (AUC) for intratumoral radiomics model was 0.956, 0.823, and 0.860 in the training cohort, test cohort, and external validation cohort, respectively. AUC for the peritumoral radiomics model was 0.929, 0.906, and 0.773 in the training cohort, test cohort, and external validation cohort, respectively. The AUC for combined intra- and peritumoral radiomics model was 0.976, 0.918, and 0.874 in the training cohort, test cohort, and external validation cohort, respectively. The AUC for clinical-radiomics nomogram was 0.989, 0.777, and 0.870 in the training cohort, test cohort, and external validation cohort, respectively. The prognostic model constructed by combining intra- and peritumoral radiomics signature score (radscore)-based TD and MRI-reported lymph nodes metastasis (LNM) indicated good performance for predicting 3-year RFS, with AUC of 0.824, 0.865, and 0.738 in the training cohort, test cohort and external validation cohort, respectively. CONCLUSION: Combined intra- and peritumoral radiomics model showed good performance for predicting TD. Combining intra- and peritumoral radscore-based TD and MRI-reported LNM indicated the recurrence risk. CLINICAL RELEVANCE STATEMENT: Combined intra- and peritumoral radiomics model could help accurately predict tumor deposits. Combining this predictive model-based tumor deposits with MRI-reported lymph node metastasis was associated with relapse risk of rectal cancer after surgery. KEY POINTS: • Combined intra- and peritumoral radiomics model provided better diagnostic performance than that of intratumoral and peritumoral radiomics model alone for predicting TD in rectal cancer. • The predictive performance of the clinical-radiomics nomogram was not improved compared with the combined intra- and peritumoral radiomics model for predicting TD. • The prognostic model constructed by combining intra- and peritumoral radscore-based TD and MRI-reported LNM showed good performance for assessing 3-year RFS.

Association Between Heart Failure With Preserved Left Ventricular Ejection Fraction and Impaired Left Atrial Phasic Function in Hypertrophic Cardiomyopathy: Evaluation by Cardiac MRI Feature Tracking.

BACKGROUND: The majority of heart failure (HF) in hypertrophic cardiomyopathy (HCM) manifests as a phenotype with preserved left ventricular (LV) ejection fraction; however, the exact contribution of left atrial (LA) phasic function to HF with preserved ejection fraction (HFpEF) in HCM remains unresolved. PURPOSE: To define the association between LA function and HFpEF in HCM patients using cardiac magnetic resonance imaging (MRI) feature tracking. STUDY TYPE: Retrospective. POPULATION: One hundred and fifty-four HCM patients (HFpEF vs. non-HF: 55 [34 females] vs. 99 [43 females]). FIELD STRENGTH/SEQUENCE: 3.0 T/balanced steady-state free precession. ASSESSMENT: LA reservoir function (reservoir strain [εs ], total ejection fraction [EF]), conduit function (conduit strain [εe ], passive EF), booster-pump function (booster strain [εa ] and active EF), LA volume index, and LV global longitudinal strain (LV GLS) were evaluated in HCM patients. STATISTICAL TESTS: Chi-square test, Student's t-test, Mann-Whitney U test, multivariate linear regression, logistic regression, and net reclassification analysis were used. Two-sided P < 0.05 was considered statistically significant. RESULTS: No significant difference was found in LV GLS between the non-HF and HFpEF group (-10.67 ± 3.14% vs. -10.14 ± 4.01%, P = 0.397), whereas the HFpEF group had more severely impaired LA phasic strain (εs : 27.40 [22.60, 35.80] vs. 18.15 [11.98, 25.90]; εe : 13.80 [9.20, 18.90] vs. 7.95 [4.30, 14.35]; εa : 13.50 [9.90, 17.10] vs. 7.90 [5.40, 14.15]). LA total EF (37.91 [29.54, 47.94] vs. 47.49 [39.18, 55.01]), passive EF (14.70 [7.41, 21.49] vs. 18.07 [9.32, 24.78]), and active EF (27.19 [17.79, 36.60] vs. 36.64 [26.63, 42.71]) were all significantly decreased in HFpEF patients compared with non-HF patients. LA reservoir (ß = 0.90 [0.85, 0.96]), conduit (ß = 0.93 [0.87, 0.99]), and booster (ß = 0.86 [0.78, 0.95]) strain were independently associated with HFpEF in HCM patients. The model including reservoir strain (Net Reclassification Index [NRI]: 0.260) or booster strain (NRI: 0.325) improved the reclassification of HFpEF based on LV GLS and minimum left atrial volume index (LAVImin ). DATA CONCLUSION: LA phasic function was severely impaired in HCM patients with HFpEF, whereas LV function was not further impaired compared with non-HF patients. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY: Stage 3.

Automatic machine learning based on native T1 mapping can identify myocardial fibrosis in patients with hypertrophic cardiomyopathy.

OBJECTIVES: To investigate the feasibility of automatic machine learning (autoML) based on native T1 mapping to predict late gadolinium enhancement (LGE) status in hypertrophic cardiomyopathy (HCM). METHODS: Ninety-one HCM patients and 44 healthy controls who underwent cardiovascular MRI were enrolled. The native T1 maps of HCM patients were classified as LGE ( +) or LGE (-) based on location-matched LGE images. An autoML pipeline was implemented using the tree-based pipeline optimization tool (TPOT) for 3 binary classifications: LGE ( +) and LGE (-), LGE (-) and control, and HCM and control. TPOT modeling was repeated 10 times to obtain the optimal model for each classification. The diagnostic performance of the best models by slice and by case was evaluated using sensitivity, specificity, accuracy, and microaveraged area under the curve (AUC). RESULTS: Ten prediction models were generated by TPOT for each of the 3 binary classifications. The diagnostic accuracy obtained with the best pipeline in detecting LGE status in the testing cohort of HCM patients was 0.80 by slice and 0.79 by case. In addition, the TPOT model also showed discriminability between LGE (-) patients and control (accuracy: 0.77 by slice; 0.78 by case) and for all HCM patients and controls (accuracy: 0.88 for both). CONCLUSIONS: Native T1 map analysis based on autoML correlates with LGE ( +) or (-) status. The TPOT machine learning algorithm could be a promising method for predicting myocardial fibrosis, as reflected by the presence of LGE in HCM patients without the need for late contrast-enhanced MRI sequences. KEY POINTS: • The tree-based pipeline optimization tool (TPOT) is a machine learning algorithm that could help predict late gadolinium enhancement (LGE) status in patients with hypertrophic cardiomyopathy. • The TPOT could serve as an adjuvant method to detect LGE by using information from native T1 maps, thus avoiding the need for contrast agent. • The TPOT also detects native T1 map alterations in LGE-negative patients with hypertrophic cardiomyopathy.

The application of apparent diffusion coefficients derived from intratumoral and peritumoral zones for assessing pathologic prognostic factors in rectal cancer.

OBJECTIVE: To investigate the diagnostic performance of the apparent diffusion coefficient (ADC) derived from intratumoral and peritumoral zones for assessing pathologic prognostic factors in rectal cancer. MATERIALS AND METHODS: One hundred forty-six patients with rectal cancer who underwent preoperative MRI were prospectively enrolled. Two radiologists independently placed free-hand regions of interest (ROIs) in the largest tumor cross section and three small ROIs on the peritumoral zone adjacent to the tumor contour. Maximum values of tumor ADC (ADCtmax), minimum values of tumor ADC (ADCtmin), mean values of tumor ADC (ADCtmean), mean values of peritumor ADC (ADCpmean), and ADCpmean/ADCtmean (ADC ratio) were obtained on ADC maps and correlated with prognostic factors using uni- and multivariate logistic regression, and receiver operating characteristic curve (ROC) analysis. RESULTS: Interobserver agreement was excellent for ADCtmax and ADCtmean (intraclass correlation coefficient [ICC], 0.915-0.958), and were good for ADCtmin, ADCpmean, and ADC ratio (ICC, 0.774-0.878). The ADC ratio was significantly higher in the poor differentiation, T3-4 stage, lymph node metastasis (LNM)-positive, extranodal extension (ENE)-positive, tumor deposit (TD)-positive, and lymphovascular invasion (LVI)-positive groups than that in the well-moderate differentiation, T1-2 stage, LNM-negative, ENE-negative, TD-negative, and LVI-negative groups (p = 0.008, < 0.001, < 0.001, 0.001, < 0.001, and < 0.001, respectively). The area under the ROC curve (AUC) of the ADC ratio was the highest for assessing poor differentiation (0.700), T3-4 stage (0.707), LNM-positive (0.776), TD-positive (0.848), and LVI-positive (0.778). Both the ADC ratio (AUC = 0.677) and ADCpmean (AUC = 0.686) showed higher diagnostic performance for assessing ENE. CONCLUSION: The ADC ratio could provide better predictive performance for assessing preoperative prognostic factors in resectable rectal cancer. KEY POINTS: • Both the peritumor/tumor ADC ratio and ADCpmean are correlated with important prognostic factors of resectable rectal cancer. • Both peritumor ADC and peritumor/tumor ADC ratio had higher diagnostic performance than tumor ADC for assessment of prognostic factors in resectable rectal cancer. • Peritumor/tumor ADC ratio showed the most capability for the assessment of prognostic factors in resectable rectal cancer.

Cdc42 Promotes Axonogenesis of Primary Hippocampal Neurons by Inhibiting Glycogen Synthase Kinase-3ß.

BACKGROUND: Progressive axon degeneration is a common pathological feature of neurodegenerative diseases. Cdc42 is a member of the Rho GTPase family that participates in axonogenesis. GSK-3ß is a serine/threonine kinase highly implicated in neuronal development and neurodegeneration. This study aimed to examine whether cdc42 promotes axonogenesis by regulating GSK-3ß activity. METHODS: Hippocampal neurons were isolated from neonatal Sprague-Dawley rats and transfected with designated plasmid vectors to alter the activities of cdc42 and GSK-3ß. LiCl treatment was used to inhibit the GSK-3ß activity in primary neurons. GSK-3ß activity was determined by an enzyme activity assay kit. Immunofluorescence staining was used to detect axons stained with anti-Tau-1 antibody and dendrites stained with anti-MAP2 antibody. RESULTS: Transfection with an active cdc42 mutant (cdc42F28L) decreased the activity of GSK-3ß and induced axonogenesis in primary rat hippocampal neurons, while transfection with a negative cdc42 mutant (cdc42N17) resulted an opposite effect. Moreover, transfection with plasmid vectors carrying wild-type GSK-3ß or a constitutively active GSK3ß mutant (GSK-3ß S9A) increased the activity of GSK-3ß and attenuated axonogenesis of primary hippocampal neurons with excessive cdc42 activity, whereas inhibition of GSK-3ß by LiCl abolished the inhibitory effect of the negative cdc42 mutant on axonogenesis. CONCLUSIONS: This study suggests that cdc42 induces axonogenesis of primary rat hippocampal neurons via inhibiting GSK-3ß activity. These findings support further investigation into the mechanisms of cdc42/GSK-3ß-mediated axonogenesis.

[Application of Diffusion-Weighted Imaging and Hepatobiliary-Specific Contrast Agent Gd-EOB-DTPA in the Diagnosis and Differential Diagnosis of Focal Liver Lesions].

There are many types of focal liver lesions (FLL) presenting different lesion signs and their diagnosis and differential diagnosis are relatively difficult. It is of great clinical significance to accurately detect, classify and characterize focal liver lesions as soon as possible. Diffusion-weighted imaging (DWI) provides information on liver cell density, microstructure, and microcirculation perfusion. Gadolinium-ethoxibenzyl-diethylenetriamine pentaacetic acid (Gd-EOB-DTPA) is a hepatobiliary-specific contrast agent. Gd-EOB-DTPA-enhanced MRI examination of liver provides information on the blood perfusion of lesions and specific information on the uptake function of normal liver cells. The combined application of the two can significantly improve the sensitivity and diagnostic accuracy in the detection of FLL. Herein, we reviewed the research findings on the application of DWI and Gd-EOB-DTPA in FLL diagnosis in order to provide reference for further clinical application. Most of the existing studies only made comparison and discussion of the DWI image quality of different b values and their fitted apparent diffusion coefficient (ADC) values before and after Gd-EOB-DTPA enhancement, and the reported findings are not only varied, but also inconsistent. Whether Gd-EOB-DTPA will affect DWI images is still been debated. Future research should focus on quantitative comparison, discussion and verification of the enhancement effect after injection of Gd-EOB-DTPA, as well as the changes in the ADC value corresponding to different b values before and after enhancement, in order to provide more objective and consistent research results for clinical application.

[Using Quantitative Computed Tomography to Study the Correlation Between Physical Composition and Grip Strength in Young People].

Objective: To study with quantitative computed tomography (QCT) the correlation between grip strength and physical composition and waist and hip circumferences in young people with different body mass indexes (BMIs). Methods: A total of 1310 young people who came to West China Hospital, Sichuan University for physical checkups and underwent chest QCT at our hospital from April to July 2021 were included in the study. Their data were collected and their BMIs were calculated. The subjects were divided according to their BMIs into 4 groups, underweight group (BMI<18.5 kg/m 2), normal-weight group (18.5 kg/m 2≤BMI<24 kg/m 2), overweight group (24 kg/m 2≤BMI<28 kg/m 2), and obesity group (BMI≥28 kg/m 2). The raw data were uploaded to QCT Mindways Pro 6.1 software to be processed for measurement of the fat content (area) of the physical components of the L2 vertebral body, including total adipose tissue (TAT), visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), and abdominal fat ratio, or VAT/SAT. Grip strength was measured with CAMRY EH101 digital grip dynamometer. Statistical analysis of the data was performed, and the correlations between grip strength and various physical components, waist circumference, and hip circumference in subjects of different BMIs were examined. In addition, stratified analysis of normal-weight and overweight subjects of different age groups was conducted. Results: In the normal-weight group, height, body mass, hip circumference and grip strength were positively correlated with grip strength in males aged 21-40 years, SAT was negatively correlated with grip strength in males aged 36-40 years, and VAT/SAT was positively correlated with grip strength in males aged 36-40 years. In normal-weight females aged 21-25 years, SAT was negatively correlated with grip strength, while VAT and VAT/SAT were positively correlated with grip strength. In normal-weight females aged 26-40 years, height, body mass, and hip circumference were positively correlated with grip strength. In normal-weight females aged 36-40 years, VAT/SAT was positively correlated with grip strength. In overweight males aged 21-25 years, hip circumference and body mass were positively correlated with grip strength. In overweight males aged 26-30 years, TAT, waist-to-hip ratio, and waist-to-height ratio were negatively correlated with grip strength. In overweight males aged 31-40 years, height and body mass were positively correlated with grip strength, while waist-to-hip ratio and waist-to-height ratio were negatively correlated with grip strength. In addition, hip circumference was positively correlated with grip strength in overweight males aged 31-35 years. In overweight females aged 21-25 years, waist circumference, hip circumference, and waist-to-height ratio were positively correlated with grip strength. In overweight females aged 26-30 years, height and body mass were positively correlated with grip strength. In overweight females aged 31-35 years, TAT, SAT, waist circumference, waist-to-hip ratio, and waist-to-height ratio were negatively correlated with grip strength. In overweight females aged 36-40 years, SAT and waist-to-height ratio were negatively correlated with grip strength, while VAT, VAT/SAT, height and body mass were positively correlated with grip strength. The height and body mass of males and females in the underweight group were positively correlated with grip strength, and the hip circumference of females in the underweight group was also positively correlated with grip strength. In the obesity group, TAT, VAT, and waist-to-height ratio were negatively correlated with grip strength in males, but no such correlation was observed in females. Conclusion: There is a close association between abdominal fat content and grip strength in young people with different BMIs, indicating that young people should control abdominal fat content and hip fat content in order to maintain the strength of corresponding muscles.

[Clinical Application of "Three-Low" Technique Combined with Artificial Intelligence Iterative Reconstruction Algorithm in Aortic CT Angiography].

Objective: To explore the application value of the "three-low" technique (low radiation dose, low contrast agent dosage and low contrast agent flow rate) combined with artificial intelligence iterative reconstruction (AIIR) in aortic CT angiography (CTA). Methods: A total of 33 patients who underwent aortic CTA were prospectively enrolled. Based on the time of their follow-up examinations, the imaging data were divided into Group A and Group B, with Group A being the control group (100 kV, 0.8 mL/kg, 5 mL/s) and Group B being the "three-low" technique group (70 kV, 0.5 mL/kg, 3 mL/s). In group A, the images were reconstructed by Karl iterative algorithm. Group B was divided into B1 and B2 subgroups, with their images being reconstructed by Karl iterative algorithm and AIIR, respectively. The CT and SD values of the ascending aorta, descending aorta, abdominal aorta, left common iliac artery and right common iliac artery were measured, and the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated. The subjective scoring of image quality was performed. The radiation dose parameters were documented. Results: Differences in the CT value, SD value, SNR and CNR of the three groups were statistically significant ( P<0.001). The CT value, SNR and CNR of group B2 were significantly higher than those of group B1, while the SD value of group B2 was significantly lower than that of group B1 ( P<0.017). There was no significant difference between the CT values of group A and those of group B2 ( P>0.017). The SD values, SNR and CNR in group B2 were better than those in group A ( P>0.017). There was significant difference in the subjective evaluation of image quality among the three groups ( P<0.05), but there was no significant difference between group A and group B2 ( P>0.017). The radiation dose and contrast medium dosage in group B decreased 84.14% and 37.08%, respectively, compared with those of group A. Conclusion: With the "three-low" technique combined with AIIR algorithm, the image quality of aortic CTA obtained is comparable to that of conventional dose scanning, while the radiation dose, contrast agent dosage and contrast agent flow rate of patients are significantly reduced.

Noninvasive oxygenation assessment after acute myocardial infarction with breathing maneuvers-induced oxygenation-sensitive magnetic resonance imaging.

The safety profiles when performing stress oxygenation-sensitive magnetic resonance imaging (OS-MRI) have raised concerns in clinical practice. Adenosine infusion can cause side effects such as chest pain, dyspnea, arrhythmia, and even cardiac death. The aim of this study was to investigate the feasibility of breathing maneuvers-induced OS-MRI in acute myocardial infarction (MI). This was a prospective study, which included 14 healthy rabbits and nine MI rabbit models. This study used 3 T MRI/modified Look-Locker inversion recovery sequence for native T1 mapping, balanced steady-state free precession sequence for OS imaging, and phase-sensitive inversion recovery sequence for late gadolinium enhancement. The changes in myocardial oxygenation (ΔSI) were assessed under two breathing maneuvers protocols in healthy rabbits: a series of extended breath-holding (BH), and a combined maneuver of hyperventilation followed by the extended BH (HVBH). Subsequently, OS-MRI with HVBH in acute MI rabbits was performed, and the ΔSI was compared with that of adenosine stress protocol. Student's t-test, Wilcoxon rank test, and Friedman test were used to compare ΔSI in different subgroups. Pearson and Spearman correlation was used to obtain the association of ΔSI between breathing maneuvers and adenosine stress. Bland-Altman analysis was used to assess the bias of ΔSI between HVBH and adenosine stress. In healthy rabbits, BH maneuvers from 30 to 50 s induced significant increase in SI compared with the baseline (all p < 0.05). By contrast, hyperventilation for 60 s followed by 10 s-BH (HVBH 10 s) exhibited a comparable ΔSI to that of stress test (p = 0.07). In acute MI rabbits, HVBH 10 s-induced ΔSIs among infarcted, salvaged, and the remote myocardial area were no less effectiveness than adenosine stress when performing OS-MRI (r = 0.84; p < 0.05). Combined breathing maneuvers with OS-MRI have the potential to be used as a nonpharmacological alternative for assessing myocardial oxygenation in patients with acute MI. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY STAGE: 2.

Cdc42 Facilitates Axonogenesis by Enhancing Microtubule Stabilization in Primary Hippocampal Neurons.

The establishment of polarity is an essential process in early neuronal development. Cdc42, a GTPase of the Rho family, is a key regulator of cytoskeletal dynamics and neuronal polarity. However, the mechanisms underlying the action of cdc42 in regulating axonogenesis have not been elucidated. Here, we expressed wild-type cdc42, a constitutively active cdc42 mutant (cdc42F28L) and a dominant negative cdc42 mutant (cdc42N17), respectively, in the primary hippocampal neurons to alter the activity of cdc42. We found that cdc42 activities were paralleled with the capacities to promote axonogenesis in the cultured neurons. Cdc42 also enhanced microtubule stability in the cultured neurons. Pharmacologically stabilizing microtubules significantly abrogated the defective axonogenesis induced by cdc42 inhibition. Moreover, cdc42 promoted the dephosphorylation of collapsing response mediator protein-2 (CRMP-2) at Thr514 by increasing GSK-3ß phosphorylation at Ser9 in the cultured neurons. These findings suggest that cdc42 may facilitate axonogenesis by promoting microtubule stabilization in rat primary hippocampal neurons.

Increased oxygenation is associated with myocardial inflammation and adverse regional remodeling after acute ST-segment elevation myocardial infarction.

OBJECTIVES: To explore the relationships between oxygenation signal intensity (SI) with myocardial inflammation and regional left ventricular (LV) remodeling in reperfused acute ST-segment elevation myocardial infarction (STEMI) using oxygenation-sensitive cardiovascular magnetic resonance (OS-CMR). METHODS: Thirty-three STEMI patients and 22 age- and sex-matched healthy volunteers underwent CMR. The protocol included cine function, OS imaging, precontrast T1 mapping, T2 mapping, and late gadolinium enhancement (LGE) imaging. A total of 880 LV segments were included for analysis based on the American Heart Association 16-segment model. For validation, 15 pigs (10 myocardial infarction (MI) model animals and 5 controls) received CMR and were sacrificed for immunohistochemical analysis. RESULTS: In the patient study, the acute oxygenation SI showed a stepwise rise among remote, salvaged, and infarcted segments compared with healthy myocardium. At convalescence, all oxygenation SI values besides those in infarcted segments with microvascular obstruction decreased to similar levels. Acute oxygenation SI was associated with early myocardial injury (T1: r = 0.38; T2: r = 0.41; all p < 0.05). Segments with higher acute oxygenation SI values exhibited thinner diastolic walls and decreased wall thickening during follow-up. Multivariable regression modeling indicated that acute oxygenation SI (ß = 2.66; p < 0.05) independently predicted convalescent segment adverse remodeling (LV wall thinning). In the animal study, alterations in oxygenation SI were correlated with histological inflammatory infiltrates (r = 0.59; p < 0.001). CONCLUSIONS: Myocardial oxygenation by OS-CMR could be used as a quantitative imaging biomarker to assess myocardial inflammation and predict convalescent segment adverse remodeling after STEMI. KEY POINTS: • Oxygenation signal intensity (SI) may be an imaging biomarker of inflammatory infiltration that could be used to assess the response to anti-inflammatory therapies in the future. • Oxygenation SI early after myocardial infarction (MI) was associated with left ventricular segment injury at acute phase and could predict regional functional recovery and adverse remodeling late after acute MI. • Oxygenation SI demonstrated a stepwise increase among remote, salvaged, and infarcted segments. Infarcted zones with microvascular obstruction demonstrated a higher oxygenation SI than those without. However, the former showed less pronounced changes over time.

[A Preliminary Study of Applying Geometric Deep Learning in Brain Morphometry for Diagnosis of Alzheimer's Disease].

OBJECTIVE: A predictive model of Alzheimer's disease (AD) was established based on brain surface meshes and geometric deep learning, and its performance was evaluated. METHODS: Seventy-six clinically diagnosed AD patients and 83 healthy older adults were enrolled and randomly assigned to the training set and the test set according to a 4-to-1 ratio. Brain surface mesh was constructed from 3-D T1-weighted high-resolution structural MR volumes of each participant. After applying a series of simplification to the surface meshes, the training set was fed into the geometric deep neural network for training. The performance of the prediction model was evaluated with the test set, and the evaluation metrics included accuracy, sensitivity and specificity. RESULTS: The prediction model trained on the right brain surface meshes with 6 000 faces achieved the best performance, with accuracy reaching 93.8%, sensitivity, 91.7%, and specificity, 94.1%. The evolution of the brain surface meshes during convolution and pooling revealed that AD patients had diffuse brain tissue loss compared with healthy older adults. CONCLUSION: Morphological brain analysis based on mesh data and geometric deep learning has great potential in the differential diagnosis of AD.

[Application of MRI-based Radiomics Models in the Assessment of Hepatic Metastasis of Rectal Cancer].

OBEJECTIVE: To explore the clinical value of using radiomics models based on different MRI sequences in the assessment of hepatic metastasis of rectal cancer. METHODS: 140 patients with pathologically confirm edrectal cancer were included in the study. They underwent baseline magnetic resonance imaging (MRI) between April 2015 and May 2018 before receiving any treatment. According to the results of liver biopsy, surgical pathology, and imaging, patients were put into two groups, the patients with hepatic metastasis and those without. T2 weighted images (T2WI), diffusion weighted images (DWI) and apparent diffusion coefficient (ADC) images were used to draw the region of interest (ROI) of primary lesions on consecutive slices on ITK-SNAP. 3-D ROIs were generated and loaded into Artificial Intelligent Kit for extraction of radiomics features and 396 features were extracted for each sequence. The feature data were preprocessed on Python and the samples were oversampled, using Support Vector Machine-Synthetic Minority Over-Sampling Technique (SVM-SMOTE) to balance the number of samples in the group with liver metastasis and the group with no liver metastasis at the end of the follow-up. Then, the samples were divided into the training cohort and the test cohort at a ratio of 2∶1. The logistic regression models were developed with selected radionomic features on R software. The receiver operating characteristics (ROC) curves and calibration curves were used to evaluate the performance of the models. RESULTS: In total, 52 patients with liver metastasis and 88 patients without liver metastasis at the end of follow-up were enrolled. Carcinoembryonic antigen (CEA) and T stage and N stage evaluated on the MRI images showed statistically significant difference between the two groups ( P<0.05). After data preprocessing and selecting, except for 17 non-radiomic features, the model combining T2WI, DWI and ADC features, the model of T2WI features alone, the model of DWI features alone and the model of ADC features alone were developed with 32 features, 10 features, 30 features and 15 features, respectively. The combined model (T2WI+DWI+ADC), the T2WI model, and the ADC model can assess hepatic metastasis accurately, with the area under curve ( AUC) on the train set reaching 93.5%, 89.2%, 90.6% and that of the test set reaching 80.8%, 80.5%, 81.4%, respectively. The combined model did not show a higher AUC than those of the T2WI and ADC alone models. Model based on DWI features has a slightly insufficient AUC of 90.3% in the train set and 75.1% in the test set. The calibration curve showed the smallest fluctuation in the combined model, which is closest fit to the diagonal reference line. The fluctuation in the three independent data set models were similar. The calibration curves of all the four models showed that as the risk increased, the prediction of the models turned from an underestimation to an overestimating the risk. In brief, the combined model showed the best performance, with the best fit to the diagonal reference line in calibration curve and high AUC comparable to the AUC of the T2WI model and ADC model. The performance of T2WI and ADC alone models were second to that of the combined model, while the DWI alone model showed relatively poor performance. CONCLUSION: Radiomics models based on MRI could be effectively used in assessing liver metastasis in rectal cancer, which may help determine clinical staging and treatment.

[Feasibility Study of Ultra-High-Resolution Low-Dose Temporal Bone CT with 1 024×1 024 Reconstruction Matrix Size].

OBJECTIVE: To investigate the feasibility of low-dose CT scan of the temporal bone combined with reconstruction matrix size of 1 024×1 024 and the effect of the reconstruction matrix size on image quality. METHODS: Normal-dose and low-dose bilateral temporal bone CT scans were performed on twelve adult male cadaveric skull specimens using the 160-slice multi-detector CT scanning of United Imaging Healthcare. Normal-dose CT images were reconstructed with matrix sizes of 512×512 and 1 024×1 024, while low-dose CT images were reconstructed with the matrix size of 1 024×1 024. CT value, noise, signal-to-noise ratio, contrast-to-noise ratio, the visualization scoring of 15 anatomical structures of the temporal bone, and the result of three-dimensional reconstruction of the ossicular chain were compared among the three groups. RESULTS: The radiation dose of low-dose CT scanning was reduced by about 50% compared with that of normal-dose CT. There was no significant difference in CT values of air, soft tissues and bones among the three groups. Low-dose temporal bone CT with the matrix size of 1 024×1 024 had higher noise, but much better visualization of temporal bone structure than the normal-dose temporal bone CT with matrix size of 512×512. Both the three-dimensional reconstructions of normal-dose and low-dose 1 024×1 024 matrix images were satisfactory and showed no significant difference. The morphology, size and relative position of malleus, incus, stapes, cochlea, and labyrinth, as well as the location of the ossicular chain in the cranium were all clearly displayed. CONCLUSION: Low-dose temporal bone CT with the matrix size of 1 024×1 024 can be used to effectively reduce the radiation dose and significantly improve the spatial resolution and the visualization of the temporal bone anatomical structures compared with the normal-dose temporal bone CT with a matrix size of 512×512.

[Early Assessment of Myocardial Fibrosis of Hypertrophic Cardiomyopathy with Native-T1-Mapping-Based Deep Learning: A Preliminary Study].

OBJECTIVE: To explore the diagnostic performance of deep learning (DL) model in early detection of the interstitial myocardial fibrosis using native T1 maps of hypertrophic cardiomyopathy (HCM) without late gadolinium enhancement (LGE). METHODS: Sixty HCM patients and 44 healthy volunteers who underwent cardiac magnetic resonance were enrolled in this study. Each native T1 map was labeled according to its LGE status. Then, native T1 maps of LGE (-) and those of the controls were preprocessed and entered in the SE-ResNext-50 model as the matrix for the DL model for training, validation and testing. RESULTS: A total of 241 native T1 maps were entered in the SE-ResNext-50 model. The model achieved a specificity of 0.87, sensitivity of 0.79, and area under curve ( AUC) of 0.83 ( P<0.05) in distinguishing native T1 maps of LGE (-) from those of the controls in the testing set. CONCLUSION: The DL model based on SE-ResNext-50 could be used for identifying native T1 maps of LGE (-) with relatively high accuracy. It is a promising approach for early detection of myocardial fibrosis in HCM without the use of contrast agent.

[Noise Reduction Effect of Deep-learning-based Image Reconstruction Algorithms in Thin-section Chest CT].

OBJECTIVE: To evaluate the noise reduction effect of deep learning-based reconstruction algorithms in thin-section chest CT images by analyzing images reconstructed with filtered back projection (FBP), adaptive statistical iterative reconstruction (ASIR), and deep learning image reconstruction (DLIR) algorithms. METHODS: The chest CT scan raw data of 47 patients were included in this study. Images of 0.625 mm were reconstructed using six reconstruction methods, including FBP, ASIR hybrid reconstruction (ASIR50%, ASIR70%), and deep learning low, medium and high modes (DL-L, DL-M, and DL-H). After the regions of interest were outlined in the aorta, skeletal muscle and lung tissue of each group of images, the CT values, SD values and signal-to-noise ratio (SNR) of the regions of interest were measured, and two radiologists evaluated the image quality. RESULTS: CT values, SD values and SNR of the images obtained by the six reconstruction methods showed statistically significant difference ( P<0.001). There were statistically significant differences in the image quality scores of the six reconstruction methods ( P<0.001). Images reconstruced with DL-H have the lowest noise and the highest overall quality score. CONCLUSION: The model based on deep learning can effectively reduce the noise of thin-section chest CT images and improve the image quality. Among the three deep-learning models, DL-H showed the best noise reduction effect.

[The Application Value of Artificial Intelligence-based Filtering and Interpolated Image Reconstruction Algorithm in Abdominal Magnetic Resonance Image Denoising].

OBJECTIVE: To compare the noise reduction performance of conventional filtering and artificial intelligence-based filtering and interpolation (AIFI) and to explore for optimal parameters of applying AIFI in the noise reduction of abdominal magnetic resonance imaging (MRI). METHODS: Sixty patients who underwent upper abdominal MRI examination in our hospital were retrospectively included. The raw data of T1-weighted image (T1WI), T2-weighted image (T2WI), and dualecho sequences were reconstructed with two image denoising techniques, conventional filtering and AIFI of different levels of intensity. The difference in objective image quality indicators, peak signal-to-noise ratio (pSNR) and image sharpness, of the different denoising techniques was compared. Two radiologists evaluated the image noise, contrast, sharpness, and overall image quality. Their scores were compared and the interobserver agreement was calculated. RESULTS: Compared with the original images, improvement of varying degrees were shown in the pSNR and the sharpness of the images of the three sequences, T1W1, T2W2, and dual echo sequence, after denoising filtering and AIFI were used (all P<0.05). In addition, compared with conventional filtering, the objective quality scores of the reconstructed images were improved when conventional filtering was combined with AIFI reconstruction methods in T1WI sequence, AIFI level≥3 was used in T2WI and echo1 sequence, and AIFI level≥4 was used in echo2 sequence (all P<0.05). The subjective scores given by the two radiologists for the image noise, contrast, sharpness, and overall image quality in each sequence of conventional filtering reconstruction, AIFI reconstruction (except for AIFI level=1), and two-method combination reconstruction were higher than those of the original images (all P<0.05). However, the image contrast scores were reduced for AIFI level=5. There was good interobserver agreement between the two radiologists (all r>0.75, P<0.05). After multidimensional comparison, the optimal parameters of using AIFI technique for noise reduction in abdominal MRI were conventional filtering+AIFI level=3 in the T1WI sequence and AIFI level=4 in the T2WI and dualecho sequences. CONCLUSION: AIFI is superior to filtering in imaging denoising at medium and high levels. It is a promising noise reduction technique. The optimal parameters of using AIFI for abdominal MRI are Filtering+AIFI level=3 in the T1WI sequence and AIFI level=4 in T2WI and dualecho sequences.