Probucol mitigates high-fat diet-induced cognitive and social impairments by regulating brain redox and insulin resistance.

Probucol has been utilized as a cholesterol-lowering drug with antioxidative properties. However, the impact and fundamental mechanisms of probucol in obesity-related cognitive decline are unclear. In this study, male C57BL/6J mice were allocated to a normal chow diet (NCD) group or a high-fat diet (HFD) group, followed by administration of probucol to half of the mice on the HFD regimen. Subsequently, the mice were subjected to a series of behavioral assessments, alongside the measurement of metabolic and redox parameters. Notably, probucol treatment effectively alleviates cognitive and social impairments induced by HFD in mice, while exhibiting no discernible influence on mood-related behaviors. Notably, the beneficial effects of probucol arise independently of rectifying obesity or restoring systemic glucose and lipid homeostasis, as evidenced by the lack of changes in body weight, serum cholesterol levels, blood glucose, hyperinsulinemia, systemic insulin resistance, and oxidative stress. Instead, probucol could regulate the levels of nitric oxide and superoxide-generating proteins, and it could specifically alleviate HFD-induced hippocampal insulin resistance. These findings shed light on the potential role of probucol in modulating obesity-related cognitive decline and urge reevaluation of the underlying mechanisms by which probucol exerts its beneficial effects.

Predicting post-resection recurrence by integrating imaging-based surrogates of distinct vascular patterns of hepatocellular carcinoma.

Background & Aims: Distinct vascular patterns, including microvascular invasion (MVI) and vessels encapsulating tumour clusters (VETC), are associated with poor outcomes of hepatocellular carcinoma (HCC). Imaging surrogates of these vascular patterns potentially help to predict post-resection recurrence. Herein, a prognostic model integrating imaging-based surrogates of these distinct vascular patterns was developed to predict postoperative recurrence-free survival (RFS) in patients with HCC. Methods: Clinico-radiological data of 1,285 patients with HCC from China undergoing surgical resection were retrospectively enrolled from seven medical centres between 2014 and 2020. A prognostic model using clinical data and imaging-based surrogates of MVI and VETC patterns was developed (n = 297) and externally validated (n = 373) to predict RFS. The surrogates (i.e. MVI and VETC scores) were individually built from preoperative computed tomography using two independent cohorts (n = 360 and 255). Whether the model's stratification was associated with postoperative recurrence following anatomic resection was also evaluated. Results: The MVI and VETC scores demonstrated effective performance in their respective training and validation cohorts (AUC: 0.851-0.883 for MVI and 0.834-0.844 for VETC). The prognostic model incorporating serum alpha-foetoprotein, tumour multiplicity, MVI score, and VETC score achieved a C-index of 0.748-0.764 for the developing and external validation cohorts and generated three prognostically distinct strata. For patients at model-predicted medium risk, anatomic resection was associated with improved RFS (p <0.05). By contrast, anatomic resection had no impact on RFS in patients at model-predicted low or high risk (both p >0.05). Conclusions: The proposed model integrating imaging-based surrogates of distinct vascular patterns enabled accurate prediction for RFS. It can potentially be used to identify HCC surgical candidates who may benefit from anatomic resection. Impact and implications: MVI and VETC are distinct vascular patterns of HCC associated with aggressive biological behaviour and poor outcomes. Our multicentre study provided a model incorporating imaging-based surrogates of these patterns for preoperatively predicting RFS. The proposed model, which uses imaging detection to estimate the risk of MVI and VETC, offers an opportunity to help shed light on the association between tumour aggressiveness and prognosis and to support the selection of the appropriate type of surgical resection.

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.

Personalized pancreatic cancer therapy: from the perspective of mRNA vaccine.

Pancreatic cancer is characterized by inter-tumoral and intra-tumoral heterogeneity, especially in genetic alteration and microenvironment. Conventional therapeutic strategies for pancreatic cancer usually suffer resistance, highlighting the necessity for personalized precise treatment. Cancer vaccines have become promising alternatives for pancreatic cancer treatment because of their multifaceted advantages including multiple targeting, minimal nonspecific effects, broad therapeutic window, low toxicity, and induction of persistent immunological memory. Multiple conventional vaccines based on the cells, microorganisms, exosomes, proteins, peptides, or DNA against pancreatic cancer have been developed; however, their overall efficacy remains unsatisfactory. Compared with these vaccine modalities, messager RNA (mRNA)-based vaccines offer technical and conceptional advances in personalized precise treatment, and thus represent a potentially cutting-edge option in novel therapeutic approaches for pancreatic cancer. This review summarizes the current progress on pancreatic cancer vaccines, highlights the superiority of mRNA vaccines over other conventional vaccines, and proposes the viable tactic for designing and applying personalized mRNA vaccines for the precise treatment of pancreatic cancer.

Effect of hydrostatic pressure on the structural, elastic, and optoelectronic properties of vacancy-ordered double perovskite Cs2PdBr6.

The vacancy-ordered double perovskite Cs2PdBr6 has the advantages of good optoelectronic properties, environmental friendliness, and high stability. It has been experimentally confirmed by researchers as an optoelectronic material with broad application prospects and research value, and is regarded as a potential substitute for lead halide perovskites. In this paper, based on the first-principles calculations in the framework of density functional theory, the crystal structure, elastic, electronic, and optical properties of Cs2PdBr6 under hydrostatic pressure of 0-6 GPa have been investigated with a step size of 0.5 GPa. The calculated results obtained under the condition of 0 GPa hydrostatic pressure are in good agreement with the existing experimental values. When the hydrostatic pressure is applied, the crystal structure parameters of Cs2PdBr6 appear nonlinear changes, but it can still maintain a stable cubic crystal structure. With the increase of pressure, the bulk modulus, shear modulus, and Young's modulus of Cs2PdBr6 increase gradually, and its ductility also improves gradually. Hydrostatic pressure can reduce the bandgap value of Cs2PdBr6, thereby enhancing the optoelectronic properties such as absorption and conductivity. In summary, hydrostatic pressure can change the bandgap value of Cs2PdBr6, improve its optoelectronic performance, and make it more suitable for use as the light-absorbing layer in solar cells.

Insulin Resistance and Cognitive Impairment: Evidence From Neuroimaging.

Insulin is a peptide well known for its role in regulating glucose metabolism in peripheral tissues. Emerging evidence from human and animal studies indicate the multifactorial role of insulin in the brain, such as neuronal and glial metabolism, glucose regulation, and cognitive processes. Insulin resistance (IR), defined as reduced sensitivity to the action of insulin, has been consistently proposed as an important risk factor for developing neurodegeneration and cognitive impairment. Although the exact mechanism of IR-related cognitive impairment still awaits further elucidation, neuroimaging offers a versatile set of novel contrasts to reveal the subtle cerebral abnormalities in IR. These imaging contrasts, including but not limited to brain volume, white matter (WM) microstructure, neural function and brain metabolism, are expected to unravel the nature of the link between IR, cognitive decline, and brain abnormalities, and their changes over time. This review summarizes the current neuroimaging studies with multiparametric techniques, focusing on the cerebral abnormalities related to IR and therapeutic effects of IR-targeting treatments. According to the results, brain regions associated with IR pathophysiology include the medial temporal lobe, hippocampus, prefrontal lobe, cingulate cortex, precuneus, occipital lobe, and the WM tracts across the globe. Of these, alterations in the temporal lobe are highly reproducible across different imaging modalities. These structures have been known to be vulnerable to Alzheimer's disease (AD) pathology and are critical in cognitive processes such as memory and executive functioning. Comparing to asymptomatic subjects, results are more mixed in patients with metabolic disorders such as type 2 diabetes and obesity, which might be attributed to a multifactorial mechanism. Taken together, neuroimaging, especially MRI, is beneficial to reveal early abnormalities in cerebral structure and function in insulin-resistant brain, providing important evidence to unravel the underlying neuronal substrate that reflects the cognitive decline in IR. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 2.

mRNA vaccine development for cholangiocarcinoma: a precise pipeline.

Cholangiocarcinoma (CHOL) is one of the most aggressive tumors worldwide and cannot be effectively treated by conventional and novel treatments, including immune checkpoint blockade therapy. The mRNA vaccine-based immunotherapeutic strategy has attracted much attention for various diseases, however, its application in CHOL is limited due to the thoughtlessness in the integration of vaccine design and patient selection. A recent study established an integrated path for identifying potent CHOL antigens for mRNA vaccine development and a precise stratification for identifying CHOL patients who can benefit from the mRNA vaccines. In spite of a promising prospect, further investigations should identify immunogenic antigens and onco-immunological characteristics of CHOL to guide the clinical application of CHOL mRNA vaccines in the future.

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.

Theoretical exploration of mechanical, electronic structure and optical properties of aluminium based double halide perovskite.

The mechanical, electronic structure and optical properties of aluminium based double halide perovskite were calculated by density functional theory. The formation energy and elastic constant confirm the stability of the cubic perovskite materials. The materials are all ductile and suitable for flexible photovoltaic and optoelectronic devices. The band gap values vary from 0.773 eV to 3.430 eV, exactly corresponding to the range of ideal band gap values for good photoresponse. The band structure analysis shows that all the materials possess small effective mass, which indicates a good transport of carriers. And these materials have a broad energy range of optical absorption for utilization and a detector of photons. Moreover, less expensive K2AgAlBr6 were investigated for comparison with materials containing a cesium element, and according to the results, is also a candidate for photoelectronic devices due to the similar properties.

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.

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.

Disrupted Amygdala Connectivity Is Associated With Elevated Anxiety in Sensorineural Hearing Loss.

Background and Purpose: Hearing loss is associated with rising risks of emotional impairments, suggesting emotional processing networks might be involved in the neural plasticity after hearing loss. This study was conducted to explore how functional connectivity of the amygdala reconfigures in the auditory deprived brain and better understand the neural mechanisms underlying hearing loss-related emotional disturbances. Methods: In total, 38 chronic sensorineural hearing loss (SNHL) patients and 37 healthy controls were recruited for multimodal magnetic resonance imaging scanning and neuropsychological assessments. Voxel-wise functional connectivity (FC) maps of both the left and right amygdala were conducted and compared between the SNHL patients and healthy controls. The uncinate fasciculus (UF), an association fiber pathway, was reconstructed in both groups. The track number, mean track length, fractional anisotropy (FA) and mean diffusion values of the left and right UF were further quantified, respectively. Besides, Pearson's correlation analyses were conducted to investigate the relationship between the functional/structural abnormalities and the negative emotional states in SNHL patients. Results: The SNHL patients presented higher depressive and anxious levels compared to the healthy controls. Decreased FCs were detected between the amygdala and the auditory cortex, striatum, multimodal processing areas, and frontoparietal control areas in the SNHL patients. The amygdala was found to be structurally connected with several FC decreased regions through the UF. Moreover, the hypo-synchronization and the white matter impairment were both found to be associated with patients' elevated anxious status. Conclusions: These functional and structural findings depicted the reconfiguration of the amygdala in SNHL, which provided a new perspective toward the functional circuit mechanisms targeting the emotional impairments related to hearing loss.

Radiomics Analysis on Multiphase Contrast-Enhanced CT: A Survival Prediction Tool in Patients With Hepatocellular Carcinoma Undergoing Transarterial Chemoembolization.

Patients with HCC receiving TACE have various clinical outcomes. Several prognostic models have been proposed to predict clinical outcomes for patients with hepatocellular carcinomas (HCC) undergoing transarterial chemoembolization (TACE), but establishing an accurate prognostic model remains necessary. We aimed to develop a radiomics signature from pretreatment CT to establish a combined radiomics-clinic (CRC) model to predict survival for these patients. We compared this CRC model to the existing prognostic models in predicting patient survival. This retrospective study included multicenter data from 162 treatment-naïve patients with unresectable HCC undergoing TACE as an initial treatment from January 2007 and March 2017. We randomly allocated patients to a training cohort (n = 108) and a testing cohort (n = 54). Radiomics features were extracted from intra- and peritumoral regions on both the arterial phase and portal venous phase CT images. A radiomics signature (Rad-signature) for survival was constructed using the least absolute shrinkage and selection operator method in the training cohort. We used univariate and multivariate Cox regressions to identify associations between the Rad- signature and clinical factors of survival. From these, a CRC model was developed, validated, and further compared with previously published prognostic models including four-and-seven criteria, six-and-twelve score, hepatoma arterial-embolization prognostic scores, and albumin-bilirubin grade. The CRC model incorporated two variables: The Rad-signature (composed of features extracted from intra- and peritumoral regions on the arterial phase and portal venous phase) and tumor number. The CRC model performed better than the other seven well-recognized prognostic models, with concordance indices of 0.73 [95% confidence interval (CI) 0.68-0.79] and 0.70 [95% CI 0.62-0.82] in the training and testing cohorts, respectively. Among the seven models tested, the six-and-12 score and four-and-seven criteria performed better than the other models, with C-indices of 0.64 [95% CI 0.58-0.70] and 0.65 [95% CI 0.55-0.75] in the testing cohort, respectively. The CT radiomics signature represents an independent biomarker of survival in patients with HCC undergoing TACE, and the CRC model displayed improved predictive performance.

Collateral Status at Single-Phase and Multiphase CT Angiography versus CT Perfusion for Outcome Prediction in Anterior Circulation Acute Ischemic Stroke.

Background Collateral status assessed with single- or multiphase CT angiography can be used to predict outcome in patients with acute ischemic stroke (AIS); however, little is known about whether these measures could be comparable with CT perfusion parameters. Purpose To compare the predictive ability of collateral score systems assessed with single- or multiphase CT angiography and CT perfusion parameters in determining clinical outcomes in patients with AIS. Materials and Methods In this retrospective study, data obtained from October 2017 to August 2018 in consecutive patients with AIS caused by isolated anterior circulation large artery occlusion and that were obtained within 24 hours after onset were reviewed. The collateral score was assessed by using established scoring systems described by Menon et al. The correlations between single- and multiphase collateral scores, hypoperfusion, and ischemic core volume and final infarct volume (FIV) determined by follow-up diffusion-weighted imaging or unenhanced CT were studied. Receiver operating characteristic curves and multivariable logistic regression analysis were performed to assess the predictive ability of scoring systems and CT perfusion parameters for a favorable clinical outcome. Results A total of 119 patients (median age, 75 years; interquartile range, 66-82 years; 74 men) were included. Both single- and multiphase Menon scores had a moderate negative correlation with FIV (r = -0.43, P < .001; r = -0.44, P < .001). Receiver operating characteristic curve analysis revealed the multiphase Menon score performed better than the single-phase Menon score (area under the curve [AUC], 0.72 vs 0.64; P = .045) in the prediction of a favorable 90-day modified Rankin scale score. There was no difference between multiphase Menon score and hypoperfusion volume (AUC, 0.72 vs 0.72; P = .97) or ischemic core volume (AUC, 0.72 vs 0.71; P = .94). Multivariable analysis showed multiphase Menon score was an independent predictor of good clinical outcomes (odds ratio = 3.04, P = .001). Conclusion Multiphase Menon score performed better than single-phase Menon score and was comparable with CT perfusion parameters in determining clinical outcomes in patients with acute ischemic stroke. © RSNA, 2020.

Penumbra-based radiomics signature as prognostic biomarkers for thrombolysis of acute ischemic stroke patients: a multicenter cohort study.

BACKGROUND AND PURPOSE: This study aimed at developing a radiomics signature (R score) as prognostic biomarkers based on penumbra quantification and to validate the radiomics nomogram to predict the clinical outcomes for thrombolysis for acute ischemic stroke (AIS) patients. METHODS: In total, 168 patients collected from seven centers were retrospectively included. A score of mismatch was defined as MIS. Based on a short-term clinical label, 456 radiomics features were evaluated with feature selection methods. R score was constructed with the selected features. To compare the predictive capabilities of the clinical factors, MIS, and R score, three nomograms were developed and evaluated, according to the short-term clinical assessment on day 7. Finally, the radiomics nomogram was validated by predicting the 3-month clinical outcomes of AIS patients, in an external cohort. RESULTS: R scores were found to be significantly higher in patients with favorable clinical outcomes in both training and validation datasets. The predictive value of the radiomics nomogram estimating favorable clinical outcomes was modest, with a concordance index (C-index) of 0.695 [95% confidence interval (CI) 0.667-0.723) in an external validation dataset. In addition, the area under curve (AUC) of the radiomics nomogram predicting favorable clinical outcome reached 0.886 (95% CI 0.809-0.963) on day 7 and 0.777 (95% CI 0.666-0.888) at 3 months. CONCLUSIONS: The radiomics signature is an independent biomarker for estimating the clinical outcomes in AIS patients. By improving the individualized prediction of the clinical outcome for AIS patients 3 months after onset, the radiomics nomogram adds more value to the current clinical decision-making process.

Abnormal Cingulum Bundle Induced by Type 2 Diabetes Mellitus: A Diffusion Tensor Tractography Study.

Purpose: In Type 2 diabetes (T2DM), white matter (WM) pathology has been suggested to play an important role in the etiology of T2DM-related cognitive impairment. This study aims to investigate the integrity of the cingulum bundle (CB), a major WM tract, in T2DM patients using diffusion tensor tractography. Methods: Thirty-seven T2DM patients and 34 age-, sex- and education matched healthy controls were included and underwent diffusion tensor imaging. Tractography of bilateral CB tracts was performed and diffusion measurements were compared between the two groups. Next, brain regions with significant group differences on fractional anisotropy (FA) values were set as the region of interest (ROI), and the CB fibers that passed through were identified. Diffusion measures were extracted from these fibers to investigate their correlations with the cognitive performances and endocrine parameters. Results: T2DM patients exhibited decreased FA in bilateral CB, increased mean diffusion (MD) in the right CB, and decreased length in the left CB. Through voxel-wise comparison, the most prominent FA difference was identified in the posterior segment of the CB and the reconstructed tract was part of the retrosplenial component. Importantly, the diffusion measurements of the tract were significantly correlated with the impaired performance in executive functioning and elevated insulin resistance (IR) in the T2DM group, instead of the control group. Conclusions: The diffusion measurements in bilateral CB were altered in T2DM patients, which might reflect important neuropathologic changes in the fibers. Our study adds to knowledge about how the cingulum changes structurally along its entire length in T2DM and highlights the relationship between WM and cognitive performance. Besides, IR might be an important risk factor that warrants further exploration.

Study on the properties of perovskite materials under light and different temperatures and electric fields based on DFT.

The photoelectric conversion efficiency of perovskite solar cells has improved rapidly, but their stability is poor, which is an important factor that restricts their commercial production. This paper studies the physical and chemical stability of perovskite solar cells based on first principles. It is well known that methylamido lead iodide compounds and methylamino lead iodide compounds are easily degraded into NH2CH[double bond, length as m-dash]NH2I, CH3NH3I and PbI2. First, the chemical stability of the above two perovskite-type solar cell materials is discussed by calculating the binding energy. Then, their phonon scattering lines, state density and thermodynamic properties are calculated and analyzed, and the work functions of different types of crystals along different planes such as [1 0 0], [0 1 0 0], [0 0 1] and [1 1 1] are calculated. The results show that the work function of the methylamine iodized lead compound is greater than that of the methylamidine iodized lead compound, which means that the electrons of the methylamidine iodized lead compound escape more easily and the carrier transfer efficiency is higher under the same conditions. Finally, the effects of different temperatures, different electric fields and light on the two kinds of crystal materials are analyzed. This provides theoretical guidance for us to improve the stability of perovskite materials experimentally.

Development of a Novel Multiparametric MRI Radiomic Nomogram for Preoperative Evaluation of Early Recurrence in Resectable Pancreatic Cancer.

BACKGROUND: In pancreatic cancer, methods to predict early recurrence (ER) and identify patients at increased risk of relapse are urgently required. PURPOSE: To develop a radiomic nomogram based on MR radiomics to stratify patients preoperatively and potentially improve clinical practice. STUDY TYPE: Retrospective. POPULATION: We enrolled 303 patients from two medical centers. Patients with a disease-free survival ≤12 months were assigned as the ER group (n = 130). Patients from the first medical center were divided into a training cohort (n = 123) and an internal validation cohort (n = 54). Patients from the second medical center were used as the external independent validation cohort (n = 126). FIELD STRENGTH/SEQUENCE: 3.0T axial T1 -weighted (T1 -w), T2 -weighted (T2 -w), contrast-enhanced T1 -weighted (CET1 -w). ASSESSMENT: ER was confirmed via imaging studies as MRI or CT. Risk factors, including clinical stage, CA19-9, and radiomic-related features of ER were assessed. In addition, to determine the intra- and interobserver reproducibility of radiomic features extraction, the intra- and interclass correlation coefficients (ICC) were calculated. STATISTICAL TESTS: The area under the receiver-operator characteristic (ROC) curve (AUC) was used to evaluate the predictive accuracy of the radiomic signature in both the training and test groups. The results of decision curve analysis (DCA) indicated that the radiomic nomogram achieved the most net benefit. RESULTS: The AUC values of ER evaluation for the radiomics signature were 0.80 (training cohort), 0.81 (internal validation cohort), and 0.78 (external validation cohort). Multivariate logistic analysis identified the radiomic signature, CA19-9 level, and clinical stage as independent parameters of ER. A radiomic nomogram was then developed incorporating the CA19-9 level and clinical stage. The AUC values for ER risk evaluation using the radiomic nomogram were 0.87 (training cohort), 0.88 (internal validation cohort), and 0.85 (external validation cohort). DATA CONCLUSION: The radiomic nomogram can effectively evaluate ER risks in patients with resectable pancreatic cancer preoperatively, which could potentially improve treatment strategies and facilitate personalized therapy in pancreatic cancer. LEVEL OF EVIDENCE: 4 Technical Efficacy: Stage 4 J. Magn. Reson. Imaging 2020;52:231-245.