Fully automated hybrid approach on conventional MRI for triaging clinically significant liver fibrosis: A multi-center cohort study.

Establishing reliable noninvasive tools to precisely diagnose clinically significant liver fibrosis (SF, ≥F2) remains an unmet need. We aimed to build a combined radiomics-clinic (CoRC) model for triaging SF and explore the additive value of the CoRC model to transient elastography-based liver stiffness measurement (FibroScan, TE-LSM). This retrospective study recruited 595 patients with biopsy-proven liver fibrosis at two centers between January 2015 and December 2021. At Center 1, the patients before December 2018 were randomly split into training (276) and internal test (118) sets, the remaining were time-independent as a temporal test set (96). Another data set (105) from Center 2 was collected for external testing. Radiomics scores were built with selected features from Deep learning-based (ResUNet) automated whole liver segmentations on MRI (T2FS and delayed enhanced-T1WI). The CoRC model incorporated radiomics scores and relevant clinical variables with logistic regression, comparing routine approaches. Diagnostic performance was evaluated by the area under the receiver operating characteristic curve (AUC). The additive value of the CoRC model to TE-LSM was investigated, considering necroinflammation. The CoRC model achieved AUCs of 0.79 (0.70, 0.86), 0.82 (0.73, 0.89), and 0.81 (0.72-0.91), outperformed FIB-4, APRI (all p < 0.05) in the internal, temporal, and external test sets and maintained the discriminatory power in G0-1 subgroups (AUCs range, 0.85-0.86; all p < 0.05). The AUCs of joint CoRC-LSM model were 0.86 (0.79-0.94), and 0.81 (0.72-0.90) in the internal and temporal sets (p = 0.01). The CoRC model was useful for triaging SF, and may add value to TE-LSM.

Predicting Microvascular Invasion in Hepatocellular Carcinoma Using CT-based Radiomics Model.

Background Prediction of microvascular invasion (MVI) may help determine treatment strategies for hepatocellular carcinoma (HCC). Purpose To develop a radiomics approach for predicting MVI status based on preoperative multiphase CT images and to identify MVI-associated differentially expressed genes. Materials and Methods Patients with pathologically proven HCC from May 2012 to September 2020 were retrospectively included from four medical centers. Radiomics features were extracted from tumors and peritumor regions on preoperative registration or subtraction CT images. In the training set, these features were used to build five radiomics models via logistic regression after feature reduction. The models were tested using internal and external test sets against a pathologic reference standard to calculate area under the receiver operating characteristic curve (AUC). The optimal AUC radiomics model and clinical-radiologic characteristics were combined to build the hybrid model. The log-rank test was used in the outcome cohort (Kunming center) to analyze early recurrence-free survival and overall survival based on high versus low model-derived score. RNA sequencing data from The Cancer Image Archive were used for gene expression analysis. Results A total of 773 patients (median age, 59 years; IQR, 49-64 years; 633 men) were divided into the training set (n = 334), internal test set (n = 142), external test set (n = 141), outcome cohort (n = 121), and RNA sequencing analysis set (n = 35). The AUCs from the radiomics and hybrid models, respectively, were 0.76 and 0.86 for the internal test set and 0.72 and 0.84 for the external test set. Early recurrence-free survival (P < .01) and overall survival (P < .007) can be categorized using the hybrid model. Differentially expressed genes in patients with findings positive for MVI were involved in glucose metabolism. Conclusion The hybrid model showed the best performance in prediction of MVI. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Summers in this issue.

Preoperative Microvascular Invasion Prediction to Assist in Surgical Plan for Single Hepatocellular Carcinoma: Better Together with Radiomics.

BACKGROUND: Prediction models with or without radiomic analysis for microvascular invasion (MVI) in hepatocellular carcinoma (HCC) have been reported, but the potential for model-predicted MVI in surgical planning is unclear. Therefore, we aimed to explore the effect of predicted MVI on early recurrence after anatomic resection (AR) and non-anatomic resection (NAR) to assist surgical strategies. METHODS: Patients with a single HCC of 2-5 cm receiving curative resection were enrolled from 2 centers. Their data were used to develop (n = 230) and test (n = 219) two prediction models for MVI using clinical factors and preoperative computed tomography images. The two prediction models, clinico-radiologic model and clinico-radiologic-radiomic (CRR) model (clinico-radiologic variables + radiomic signature), were compared using the Delong test. Early recurrence based on model-predicted high-risk MVI was evaluated between AR (n = 118) and NAR (n = 85) via propensity score matching using patient data from another 2 centers for external validation. RESULTS: The CRR model showed higher area under the curve values (0.835-0.864 across development, test, and external validation) but no statistically significant improvement over the clinico-radiologic model (0.796-0.828). After propensity score matching, difference in 2-year recurrence between AR and NAR was found in the CRR model predicted high-risk MVI group (P = 0.005) but not in the clinico-radiologic model predicted high-risk MVI group (P = 0.31). CONCLUSIONS: The prediction model incorporating radiomics provided an accurate preoperative estimation of MVI, showing the potential for choosing the more appropriate surgical procedure between AR and NAR.

Disturbed Interhemispheric Functional and Structural Connectivity in Type 2 Diabetes.

BACKGROUND: Type 2 diabetes mellitus (T2DM) is associated with cognitive decline and altered brain structure and function. However, the interhemispheric coordination of T2DM patients is unclear. PURPOSE: To investigate interhemispheric functional and anatomic connectivity in T2DM, and their associations with cognitive performance and endocrine parameters. STUDY TYPE: Prospective. SUBJECTS: 38 T2DM patients and 42 matched controls. FIELD STRENGTH/SEQUENCES: 3.0 T magnetic resonance imaging (MRI) scanner; magnetization-prepared rapid acquisition gradient echo sequence; fluid-attenuated inversion recovery sequence; single-shot, gradient-recalled echo-planar imaging sequence (resting-state functional MRI); and diffusion-weighted spin-echo-based echo-planar sequence (diffusion tensor imaging). ASSESSMENT: Voxel-mirrored homotopic connectivity (VMHC) value was calculated based on the functional images. Fibers passing through the regions with significant VMHC differences were identified using an atlas-guided track recognition. The mean fractional anisotropy (FA), mean diffusivity (MD), and fiber length were extracted and compared between the two groups. Finally, correlational analyses were performed to examine the relationships between abnormal interhemispheric connectivity, cognitive performances, and endocrine parameters. STATISTICAL TESTS: Two-sample t-tests were performed controlling for confounding factors, with partial correlation analysis. False discovery rate (FDR) correction was used for multiple comparisons. A P value <0.05 was considered statistically significant. RESULTS: T2DM patients exhibited significantly decreased VMHC between bilateral lingual gyrus and sensorimotor cortex. The fibers connecting lingual gyrus in patients showed significantly lower FA (P = 0.011) and shorter fiber length (P < 0.001), while the differences in sensorimotor fibers were insignificant (P = 0.096 for FA, P = 0.739 for fiber length and P = 0.150 for MD). The FA value in the lingual fibers was negatively correlated with insulin resistance (IR) level in T2DM group after FDR correction (R = -0.635). DATA CONCLUSION: We noted disruptions in interhemispheric coordination in T2DM patients, involving both functional and anatomical connectivities. IR might be a promising therapeutic target in the intervention of T2DM-related cognitive impairment. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY STAGE: 2.

Beyond collaterals: brain frailty additionally improves prediction of clinical outcome in acute ischemic stroke.

OBJECTIVES: We aimed to investigate the additional significance of cerebral small vessel disease (SVD) beyond collaterals in determining the clinical outcome after acute ischemic stroke (AIS). METHODS: We retrospectively reviewed large vessel-involved stroke patients who had baseline CTA within 24 h after symptom onset and had an MRI scan 5 days after admission from October 1, 2018, to October 31, 2021. Collaterals and SVD markers (including atrophy, leukoaraiosis, lacunes, and perivascular space) were graded on CT angiography and MR images, respectively. Modified Rankin Scale (mRS) score at 90 days was recorded, and mRS ≤ 2 was regarded as a good clinical outcome. The associations between SVD markers, collaterals, and mRS were analyzed using logistic and causal mediation regression. RESULTS: We finally enrolled 119 patients (70 ± 13 years). The multivariable regression showed atrophy (evidence: OR 0.05 [95% CI 0.01-0.31], p = 0.002; severe: OR 0.08 [95% CI 0.01-0.44], p = 0.007) and evidence of lacune (OR 0.30 [95% CI 0.08-0.96], p = 0.049) were associated with poor clinical outcomes after correcting covariables. Collaterals mediated 25.74% of the effect of atrophy on poor clinical outcomes (p < 0.001), while lacune impacted clinical outcomes without collaterals' mediation effect (p = 0.54). The classification model with atrophy and lacune had a significantly higher AUC than without markers to distinguish good and poor outcomes (p = 0.036). CONCLUSIONS: Beyond collaterals, brain frailty, specifically assessed by atrophy and lacune, was essential in evaluating stroke patients and could additionally improve the stroke outcome prediction. KEY POINTS: • Beyond collaterals, brain frailty, specifically assessed by brain atrophy and lacune, was still an independent risk factor of unfavorable clinical outcomes after AIS. • Adding brain atrophy and lacune into the model has an extra benefit in predicting stroke outcomes. • The effect of atrophy on stroke outcomes was proportionally mediated through collaterals, but about three-quarters of the effect of brain atrophy and the total effect of lacune directly impacted stroke outcomes without a mediation effect of collaterals.

Measuring Brown Fat Using MRI and Implications in the Metabolic Syndrome.

Metabolic syndrome is presently becoming a global health concern. Brown adipose tissue (BAT) has the potential for managing the risk factors of metabolic syndrome by adjusting plasma lipids and glucose. Magnetic resonance imaging (MRI) is a noninvasive and radiation-free imaging modality for BAT research and clinical applications in both animals and humans. In the past decade, MRI technologies for detecting and characterizing BAT have developed rapidly, with progress in MRI sequencing and the emerging understanding of BAT. In this review, we focus on the main MRI methods for BAT including currently used imaging techniques and new methods and their implications for the symptoms and complications of metabolic syndrome. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY STAGE: 2.

Comparison of MRI and CT for the Prediction of Microvascular Invasion in Solitary Hepatocellular Carcinoma Based on a Non-Radiomics and Radiomics Method: Which Imaging Modality Is Better?

BACKGROUND: Computed tomography (CT) and magnetic resonance imaging (MRI) are both capable of predicting microvascular invasion (MVI) in hepatocellular carcinoma (HCC). However, which modality is better is unknown. PURPOSE: To intraindividually compare CT and MRI for predicting MVI in solitary HCC and investigate the added value of radiomics analyses. STUDY TYPE: Retrospective. SUBJECTS: Included were 402 consecutive patients with HCC (training set:validation set = 300:102). FIELD STRENGTH/SEQUENCE: T2-weighted, diffusion-weighted, and contrast-enhanced T1-weighted imaging MRI at 3.0T and contrast-enhanced CT. ASSESSMENT: CT- and MR-based radiomics signatures (RS) were constructed using the least absolute shrinkage and selection operator regression. CT- and MR-based radiologic (R) and radiologic-radiomics (RR) models were developed by univariate and multivariate logistic regression. The performance of the RS/models was compared between two modalities. To investigate the added value of RS, the performance of the R models was compared with the RR models in HCC of all sizes and 2-5 cm in size. STATISTICAL TESTS: Model performance was quantified by the area under the receiver operating characteristic curve (AUC) and compared using the Delong test. RESULTS: Histopathologic MVI was identified in 161 patients (training set:validation set = 130:31). MRI-based RS/models tended to have a marginally higher AUC than CT-based RS/models (AUCs of CT vs. MRI, P: RS, 0.801 vs. 0.804, 0.96; R model, 0.809 vs. 0.832, 0.09; RR model, 0.835 vs. 0.872, 0.54). The improvement of RR models over R models in all sizes was not significant (P = 0.21 at CT and 0.09 at MRI), whereas the improvement in 2-5 cm was significant at MRI (P < 0.05) but not at CT (P = 0.16). DATA CONCLUSION: CT and MRI had a comparable predictive performance for MVI in solitary HCC. The RS of MRI only had significant added value for predicting MVI in HCC of 2-5 cm. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.

Dynamic evolution of COVID-19 on chest computed tomography: experience from Jiangsu Province of China.

OBJECTIVES: To determine the patterns of chest computed tomography (CT) evolution according to disease severity in a large coronavirus disease 2019 (COVID-19) cohort in Jiangsu Province, China. METHODS: This retrospective cohort study was conducted from January 10, 2020, to February 18, 2020. All patients diagnosed with COVID-19 in Jiangsu Province were included, retrospectively. Quantitative CT measurements of pulmonary opacities including volume, density, and location were extracted by deep learning algorithm. Dynamic evolution of these measurements was investigated from symptom onset (day 1) to beyond day 15. Comparison was made between severity groups. RESULTS: A total of 484 patients (median age of 47 years, interquartile range 33-57) with 954 CT examinations were included, and each was assigned to one of the three groups: asymptomatic/mild (n = 63), moderate (n = 378), severe/critically ill (n = 43). Time series showed different evolution patterns of CT measurements in the groups. Following disease onset, posteroinferior subpleural area of the lung was the most common location for pulmonary opacities. Opacity volume continued to increase beyond 15 days in the severe/critically ill group, compared with peaking on days 13-15 in the moderate group. Asymptomatic/mild group had the lowest opacity volume which almost resolved after 15 days. The opacity density began to drop from day 10 to day 12 for moderately ill patients. CONCLUSIONS: Volume, density, and location of the pulmonary opacity and their evolution on CT varied with disease severity in COVID-19. These findings are valuable in understanding the nature of the disease and monitoring the patient's condition during the course of illness. KEY POINTS: • Volume, density, and location of the pulmonary opacity on CT change over time in COVID-19. • The evolution of CT appearance follows specific pattern, varying with disease severity.

Diabetes risk assessment with imaging: a radiomics study of abdominal CT.

OBJECTIVES: To identify CT markers for screening of early type 2 diabetes and assessment of the risk of incident diabetes using a radiomics method. METHODS: The medical records of 26,947 inpatients were reviewed. A total of 690 patients were selected and allocated to a primary cohort, a validation cohort, and a prediction cohort and used to build prediction models for diabetes. Three radiomics signatures were constructed using CT image features extracted from three regions of interest, i.e., in the pancreas, liver, and psoas major muscle. By incorporating radiomics signatures and other markers, we built a radiomics nomogram that could be used to screen for early diabetes and predict future diabetes. RESULTS: Of the three abdominal organs for which radiomics signature were constructed, that of the pancreas showed the best discriminatory power for early diabetes screening and prediction (C-statistics of 0.833, 0.846, and 0.899 for the primary cohort, validation cohort, and prediction cohort, respectively). The sensitivity and specificity of the nomogram for prediction of 3-year incident diabetes were 0.827 and 0.807, respectively. CONCLUSIONS: This study presents alternative radiomics markers that have potential for use in screening for undiagnosed type 2 diabetes and prediction of 3-year incident diabetes. KEY POINTS: • CT images may provide useful information to evaluate the risk of developing diabetes. • Radiomics score for diabetes prediction is based on subtle changes of abdominal organs detected by CT. • The radiomics signature of pancreas, a combination of five features of CT images, is efficient for early diabetes screening and prediction of future diabetes (AUC > 0.8).

The Accuracy of Renal Function Measurements in Obstructive Hydronephrosis Using Dynamic Contrast-Enhanced MR Renography.

OBJECTIVE. The objective of our study was to assess the accuracy of glomerular filtration rate (GFR) evaluation in patients with obstructive hydronephrosis using dynamic contrast-enhanced MR renography (DCE-MRR). MATERIALS AND METHODS. A group of 28 adult volunteers were enrolled in this study: 13 without hydronephrosis, eight with low-grade hydronephrosis, and seven with high-grade hydronephrosis. The GFR obtained from DCE-MRR (GFRMRR) and the GFR obtained from renal scintigraphy (GFRRS) were compared with the reference GFR (GFRRef) acquired using the two plasma sample method. The correlation and agreement between GFRMRR and GFRRef, GFRRS and GFRRef, and single-kidney GFRMRR (skGFRMRR) and single-kidney GFRRS (skGFRRS) were assessed. The interrater reliability of DCE-MRR and the interrater reliability of renal scintigraphy (RS) were measured. RESULTS. Both GFRMRR and GFRRS correlated well with GFRRef. In patients with hydronephrosis, DCE-MRR and RS overestimated GFR by 12.8 ± 13.9 mL/min (mean ± SD) and 11.5 ± 12.3 mL/min, respectively. The skGFRRS was higher than skGFRMRR by 5.7 ± 3.8 mL/min in high-grade hydronephrotic kidneys (p = 0.004). Good interrater reliability was observed for skGFRMRR (intraclass correlation coefficient [ICC] = 0.82-0.92) and skGFRRS (ICC = 0.79-0.90) for both nonhydronephrotic kidneys and hydronephrotic kidneys. The overall mean SDs of repeated measurements from three investigators were 4.0 and 3.8 mL/min for skGFRMRR and skGFRRS, respectively. CONCLUSION. Both DCE-MRR and RS tend to overestimate GFR in patients with hydronephrosis. RS-derived skGFR is slightly higher than that of DCE-MRR in kidneys with high-grade hydronephrosis. DCE-MRR is comparable to RS and may serve as an alternative noninvasive method for GFR measurement.

Noninvasive Identification of Renal Hypoxia in Experimental Myocardial Infarctions of Different Sizes by Using BOLD MR Imaging in a Mouse Model.

Purpose To test the feasibility of using blood oxygen level-dependent (BOLD) magnetic resonance (MR) imaging to measure alterations in renal oxygenation in a mouse model with experimental myocardial infarctions (MIs) of different sizes. Materials and Methods The study was approved by the local animal ethics committee. One hundred eighty-nine male C57BL/6 J mice were randomly subjected to MI surgery (with different locations of left anterior descending coronary artery occlusion) or sham surgery, defined as the exposure of the heart but no ligation. Mice with MI underwent late gadolinium enhancement imaging 1 day after occlusion to confirm infarct size. Mice were sorted into three groups: those with large MI (n = 48), those with small MI (n = 48), and those with sham operation (n = 36). Renal BOLD MR imaging was performed before and 1, 7, 14, 28, and 60 days after MI, and histologic analysis of renal hypoxia-inducible factor-1α (HIF-1α) and kidney injury molecule-1 (KIM-1) was performed to evaluate tissue hypoxia and kidney injury in subgroups imaged at each time point. The relationships between the BOLD R2* and HIF-1α expression and between HIF-1α and KIM-1 expression were assessed. Statistical analyses were performed with one-way analysis of variance or the Kruskal-Wallis test and Spearman correlation test. Results A significant elevation in R2* was detected in the MI groups compared with the sham group in the cortex (P < .001 for large MI vs sham group; P = .007 for small MI vs sham group) and medulla (P < .001 for large MI vs sham group; P = .003 for small MI vs sham group) on day 60, and R2* was higher in the large MI group than in the small MI group (P < .001). Renal HIF-1α expression was increased after MI and showed linear correlation with R2* in the cortex (R2 = 0.56) and medulla (R2 = 0.63). In addition, an increase in renal KIM-1 was observed in the MI groups compared with the sham group on day 60 (sham group, 53.9 × 103 arbitrary units [au] ± 35.2; large MI group, 389.3 × 103 au ± 99.8; and small MI group, 185.8 × 103 au ± 91.9; P < .001 for large MI group vs sham group; P = .037 for small MI group vs sham group), and renal KIM-1 showed a positive correlation with HIF-1α (R2 = 0.68). Conclusion The magnitude of renal hypoxia with MIs of different sizes can be noninvasively measured with BOLD MR imaging, and increased renal hypoxia is a potential risk factor for progressive tubulointerstitial injury in mouse kidneys. © RSNA, 2017 Online supplemental material is available for this article.

Renal Functional MRI and Its Application.

Renal function varies according to the nature and stage of diseases. Renal functional magnetic resonance imaging (fMRI), a technique considered superior to the most common method used to estimate the glomerular filtration rate, allows for noninvasive, accurate measurements of renal structures and functions in both animals and humans. It has become increasingly prevalent in research and clinical applications. In recent years, renal fMRI has developed rapidly with progress in MRI hardware and emerging postprocessing algorithms. Function-related imaging markers can be acquired via renal fMRI, encompassing water molecular diffusion, perfusion, and oxygenation. This review focuses on the progression and challenges of the main renal fMRI methods, including dynamic contrast-enhanced MRI, blood oxygen level-dependent MRI, diffusion-weighted imaging, diffusion tensor imaging, arterial spin labeling, fat fraction imaging, and their recent clinical applications. LEVEL OF EVIDENCE: 5 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;48:863-881.

Renal fat fraction and diffusion tensor imaging in patients with early-stage diabetic nephropathy.

OBJECTIVE: To investigate the renal fat fraction and water molecular diffusion features in patients with early-stage DN using Dixon imaging and diffusion tensor imaging (DTI). METHODS: Sixty-one type 2 diabetics (normoalbuminuria: n = 40; microalbuminuria: n = 21) and 34 non-diabetic volunteers were included. All participants received three-point Dixon imaging and DTI using a 3.0-T magnetic resonance imager. The fat fraction [FF] and DTI features [fractional anisotropy (FA), apparent diffusion coefficient (ADC), tract counts and length from DTI tractography] were collected. All image features were compared between cohorts using one-way ANOVA with Bonferroni post-hoc analysis. RESULTS: Renal FF in the microalbuminuric group was significantly higher than in the normoalbuminuric and control groups (5.6% ± 1.3%, 4.7% ± 1.1% and 4.3% ± 0.5%, respectively; p < 0.001). Medullary FA in the microalbuminuric group was the lowest (0.31 ± 0.06) in all cohorts. The tract counts and length in the renal medulla were significantly lower in the microalbuminuric group than in the other two groups. CONCLUSIONS: Dixon imaging and DTI are able to detect renal lipid deposition and water molecule diffusion abnormalities in patients with early-stage DN. Both techniques have the potential to noninvasively evaluate early renal impairment in type 2 diabetes. KEY POINTS: • Dixon imaging demonstrated renal fat deposition in early-stage DN; • Renal fractional anisotropy decreased in patients with early-stage DN; • Renal tractography demonstrated reduced track counts and length in early-stage DN.

Myocardial T1 rho mapping of patients with end-stage renal disease and its comparison with T1 mapping and T2 mapping: A feasibility and reproducibility study.

PURPOSE: To evaluate the feasibility of T1 rho mapping in myocardium at 3T and to determine whether T1 rho mapping could better characterize myocardial injury in end-stage renal disease (ESRD) patients compared to T1 and T2 mapping. MATERIALS AND METHODS: T1 rho mapping, T1 mapping, and T2 mapping were performed at 3T on 35 healthy volunteers (15 males, 20 females, 40.7 ± 13.6 years) and 32 ESRD patients (16 males, 16 females, 48.6 ± 11.9 years). The mean T1 rho, T1 , and T2 values were compared using Student's t-test and correlated with cardiac function parameters, including peak ejection rate (PER), short-axis percent thickening (SAPT), peak filling rate (PFR), and time to peak filling (TTPF). RESULTS: The mean T1 rho values (49.4 ± 2.6 msec vs. 52.2 ± 4.0 msec, P = 0.001) and T2 values (50.5 ± 2.5 msec vs. 54.1 ± 4.0 msec, P < 0.001) were significantly different between the volunteers and patients, but there were no significant differences between the two groups in the T1 values (1253.1 ± 71.6 msec vs. 1273.4 ± 41.7 msec, P = 0.157). The mean T1 rho values were negatively correlated with the PER (r = -0.397; P = 0.03), SAPT (r = -0.688; P < 0.001), and PFR (r = -0.537; P = 0.002), whereas positively correlated with the TTPF (r = 0.677; P < 0.001). The mean T2 values were negatively correlated only with the SAPT (r = -0.427; P = 0.019) in the ESRD patients. CONCLUSION: T1 rho mapping of the myocardium is feasible at 3T. T1 rho values are higher in ESRD patients and relate to cardiac function, which may better characterize myocardial injury than can T1 and T2 . J. Magn. Reson. Imaging 2016;44:723-731.

BmSPP is a virus resistance gene in Bombyx mori.

Introduction: Signal peptide peptidase (SPP) is an intramembrane protease involved in a variety of biological processes, it participates in the processing of signal peptides after the release of the nascent protein to regulate the endoplasmic reticulum associated degradation (ERAD) pathway, binds misfolded membrane proteins, and aids in their clearance process. Additionally, it regulates normal immune surveillance and assists in the processing of viral proteins. Although SPP is essential for many viral infections, its role in silkworms remains unclear. Studying its role in the silkworm, Bombyx mori , may be helpful in breeding virus-resistant silkworms. Methods: First, we performed RT-qPCR to analyze the expression pattern of BmSPP. Subsequently, we inhibited BmSPP using the SPP inhibitor 1,3-di-(N-carboxybenzoyl-L-leucyl-L-leucylaminopropanone ((Z-LL)2-ketone) and downregulated the expression of BmSPP using CRISPR/Cas9 gene editing. Furthermore, we assessed the impact of these interventions on the proliferation of Bombyx mori nucleopolyhedrovirus (BmNPV). Results: We observed a decreased in the expression of BmSPP during viral proliferation. It was found that higher concentration of the inhibitor resulted in greater inhibition of BmNPV proliferation. The down-regulation of BmSPP in both in vivo and in vitro was found to affect the proliferation of BmNPV. In comparison to wild type silkworm, BmSPPKO silkworms exhibited a 12.4% reduction in mortality rate. Discussion: Collectively, this work demonstrates that BmSPP plays a negative regulatory role in silkworm resistance to BmNPV infection and is involved in virus proliferation and replication processes. This finding suggests that BmSPP servers as a target gene for BmNPV virus resistance in silkworms and can be utilized in resistance breeding programs.

TPA: Two-stage progressive attention segmentation framework for hepatocellular carcinoma on multi-modality MRI.

BACKGROUND: Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) plays a crucial role in the diagnosis and measurement of hepatocellular carcinoma (HCC). The multi-modality information contained in the multi-phase images of DCE-MRI is important for improving segmentation. However, this remains a challenging task due to the heterogeneity of HCC, which may cause one HCC lesion to have varied imaging appearance in each phase of DCE-MRI. In particular, some phases exhibit inconsistent sizes and boundaries will result in a lack of correlation between modalities, and it may pose inaccurate segmentation results. PURPOSE: We aim to design a multi-modality segmentation model that can learn meaningful inter-phase correlation for achieving HCC segmentation. METHODS: In this study, we propose a two-stage progressive attention segmentation framework (TPA) for HCC based on the transformer and the decision-making process of radiologists. Specifically, the first stage aims to fuse features from multi-phase images to identify HCC and provide localization region. In the second stage, a multi-modality attention transformer module (MAT) is designed to focus on the features that can represent the actual size. RESULTS: We conduct training, validation, and test in a single-center dataset (386 cases), followed by external test on a batch of multi-center datasets (83 cases). Furthermore, we analyze a subgroup of data with weak inter-phase correlation in the test set. The proposed model achieves Dice coefficient of 0.822 and 0.772 in the internal and external test sets, respectively, and 0.829, 0.791 in the subgroup. The experimental results demonstrate that our model outperforms state-of-the-art models, particularly within subgroup. CONCLUSIONS: The proposed TPA provides best segmentation results, and utilizing clinical prior knowledge for network design is practical and feasible.

Effects of Low-Osmolar Contrast Media on Long-Term Renal Impairment After Coronary Angiography: Iohexol Versus Iopromide.

To investigate the long-term effects of 2 commonly used low-osmolar contrast media, iohexol and iopromide, on renal function and survival in patients who underwent coronary angiography. A total of 14,141 cardiology patients from 2006 to 2013 were recruited, of whom 1,793 patients (679 patients on iohexol and 1,114 on iopromide) were evaluated for long-term renal impairment and 5,410 patients (1,679 patients on iohexol and 3,731 on iopromide) were admitted for survival analyses spanning as long as 15 years. Univariate and multivariate logistic regression were used to explore the risk factors for long-term renal impairment. Cox proportional hazard regression was used to investigate the risk factors affecting survival. Propensity score matching and inverse probability of treatment weighting were applied to balance the baseline clinical characteristics. Patients receiving iohexol demonstrated a greater occurrence of renal impairment compared with those who received iopromide. Such difference remained consistent both before and after propensity score matching or inverse probability of treatment weighting, with a statistical significance of p <0.05. Among clinical variables, receiving contrast-enhanced contrast tomography/magnetic resonance imaging during follow-up, antihypertensive medication usage, presence of proteinuria, and anemia were identified as risk factors for long-term renal impairment (p = 0.041, 0.049, 0.006, and 0.029, respectively). During survival analyses, the difference was insignificant after propensity score matching and inverse probability of treatment weighting. In conclusion, administration of iohexol was more likely to induce long-term renal impairment than iopromide, particularly among patients diagnosed with anemia and proteinuria and those taking antihypertensive medication and with additional contrast exposure. The all-cause mortality, however, showed no significant difference between iohexol and iopromide administration.

Diagnostic performance of MRI for residual or recurrent hepatocellular carcinoma after locoregional treatment according to contrast agent type: a systematic review and meta­analysis.

PURPOSE: The ideal contrast agent for imaging patients with hepatocellular carcinoma (HCC) following locoregional therapies (LRT) remains uncertain. We conducted a meta-analysis to assess the diagnostic performance of magnetic resonance imaging with extracellular contrast agent (ECA-MRI) and hepatobiliary agent (EOB-MRI) in detecting residual or recurrence HCC following LRT. METHODS: Original studies comparing the diagnostic performance of ECA-MRI and EOB-MRI were systematically identified through comprehensive searches in PubMed, EMBASE, Cochrane Library and Web of Science databases. The pooled sensitivity and specificity of ECA-MRI and EOB-MRI were calculated using a bivariate-random-effects model. Subgroup-analyses were conducted to compare the diagnostic performance of ECA-MRI and EOB-MRI according to different variables. Meta-regression analysis was employed to explore potential sources of study heterogeneity. RESULTS: A total of 15 eligible studies encompassing 803 patients and 1018 lesions were included. Comparative analysis revealed no significant difference between ECA-MRI and EOB-MRI in the overall pooled sensitivity (87% vs. 79%) and specificity (92% vs. 96%) for the detection of residual or recurrent HCC after LRT (P = 0.41), with comparable areas under the HSROC of 0.95 and 0.92. Subgroup analyses indicated no significant diagnostic performance differences between ECA-MRI and EOB-MRI according to study design, type of LRT, most common etiology of liver disease, baseline lesion size, time of post-treated examination and MRI field strength (All P > 0.05). CONCLUSION: ECA-MRI exhibited overall comparable diagnostic performance to EOB-MRI in assessing residual or recurrent HCC after LRT.

From gut to brain: understanding the role of microbiota in inflammatory bowel disease.

With the proposal of the "biological-psychological-social" model, clinical decision-makers and researchers have paid more attention to the bidirectional interactive effects between psychological factors and diseases. The brain-gut-microbiota axis, as an important pathway for communication between the brain and the gut, plays an important role in the occurrence and development of inflammatory bowel disease. This article reviews the mechanism by which psychological disorders mediate inflammatory bowel disease by affecting the brain-gut-microbiota axis. Research progress on inflammatory bowel disease causing "comorbidities of mind and body" through the microbiota-gut-brain axis is also described. In addition, to meet the needs of individualized treatment, this article describes some nontraditional and easily overlooked treatment strategies that have led to new ideas for "psychosomatic treatment".

Corrigendum to 'Predicting post-resection recurrence by integrating imaging-based surrogates of distinct vascular patterns of hepatocellular carcinoma' (JHEP Reports 5 [2023] 100806).

[This corrects the article DOI: 10.1016/j.jhepr.2023.100806.].