Radiomics models to predict bone marrow metastasis of neuroblastoma using CT.

Background: Bone marrow is the leading site for metastasis from neuroblastoma and affects the prognosis of patients with neuroblastoma. However, the accurate diagnosis of bone marrow metastasis is limited by the high spatial and temporal heterogeneity of neuroblastoma. Radiomics analysis has been applied in various cancers to build accurate diagnostic models but has not yet been applied to bone marrow metastasis of neuroblastoma. Methods: We retrospectively collected information from 187 patients pathologically diagnosed with neuroblastoma and divided them into training and validation sets in a ratio of 7:3. A total of 2632 radiomics features were retrieved from venous and arterial phases of contrast-enhanced computed tomography (CT), and nine machine learning approaches were used to build radiomics models, including multilayer perceptron (MLP), extreme gradient boosting, and random forest. We also constructed radiomics-clinical models that combined radiomics features with clinical predictors such as age, gender, ascites, and lymph gland metastasis. The performance of the models was evaluated with receiver operating characteristics (ROC) curves, calibration curves, and risk decile plots. Results: The MLP radiomics model yielded an area under the ROC curve (AUC) of 0.97 (95% confidence interval [CI]: 0.95-0.99) on the training set and 0.90 (95% CI: 0.82-0.95) on the validation set. The radiomics-clinical model using an MLP yielded an AUC of 0.93 (95% CI: 0.89-0.96) on the training set and 0.91 (95% CI: 0.85-0.97) on the validation set. Conclusions: MLP-based radiomics and radiomics-clinical models can precisely predict bone marrow metastasis in patients with neuroblastoma.

Specific convulsions and brain damage in children hospitalized for Omicron BA.5 infection: an observational study using two cohorts.

BACKGROUND: SARS-CoV-2 continues to mutate over time, and reports on children infected with Omicron BA.5 are limited. We aimed to analyze the specific symptoms of Omicron-infected children and to improve patient care. METHODS: We selected 315 consecutively hospitalized children with Omicron BA.5 and 16,744 non-Omicron-infected febrile children visiting the fever clinic at our hospital between December 8 and 30, 2022. Specific convulsions and body temperatures were compared between the two cohorts. We analyzed potential associations between convulsions and vaccination, and additionally evaluated the brain damage among severe Omicron-infected children. RESULTS: Convulsion rates (97.5% vs. 4.3%, P < 0.001) and frequencies (median: 2.0 vs. 1.6, P < 0.001) significantly differed between Omicron-infected and non-Omicron-infected febrile children. The body temperatures of Omicron-infected children were significantly higher during convulsions than when they were not convulsing and those of non-Omicron-infected febrile children during convulsions (median: 39.5 vs. 38.2 and 38.6 °C, both P < 0.001). In the three Omicron-subgroups, the temperature during convulsions was proportional to the percentage of patients and significantly differed ( P < 0.001), while not in the three non-Omicron-subgroups ( P = 0.244). The convulsion frequency was lower in the 55 vaccinated children compared to the 260 non-vaccinated children (average: 1.8 vs. 2.1, P < 0.001). The vaccination dose and convulsion frequency in Omicron-infected children were significantly correlated ( P < 0.001). Fifteen of the 112 severe Omicron cases had brain damage. CONCLUSIONS: Omicron-infected children experience higher body temperatures and frequencies during convulsions than those of non-Omicron-infected febrile children. We additionally found evidence of brain damage caused by infection with omicron BA.5. Vaccination and prompt fever reduction may relieve symptoms.

Expanded ROS Generation and Hypoxia Reversal: Excipient-free Self-assembled Nanotheranostics for Enhanced Cancer Photodynamic Immunotherapy.

The efficacy of photodynamic therapy (PDT)-related cancer therapies is significantly restricted by two irreconcilable obstacles, i.e., low reactive oxygen species (ROS) generation capability and hypoxia which constrains the immune response. Herein, this work develops a self-assembled clinical photosensitizer indocyanine green (ICG) and the HSP90 inhibitor 17-dimethylaminoethylamino-17-demethoxygeldanamycin (17-DMAG) nanoparticles (ISDN) without any excipient. This work discovers that the hydrophobic interaction forces between ICG and 17-DMAG promote the photostability of ICG and its intersystem crossing (ISC) process, thereby improving the ROS quantum yield from 0.112 to 0.46. Augmented ROS generation enhances PDT efficacy and further enhances immunogenic cell death (ICD) effects. 17-DMAG inhibits the HSP90/hypoxia-inducible factor 1α (HIF-1α) axis to dramatically reverse the immunosuppressive tumor microenvironment caused by PDT-aggravated hypoxia. In a mouse model of pancreatic cancer, ISDN markedly improve cytotoxic T lymphocyte infiltration and MHC I and MHC II activation, demonstrating the superior ICD effects in situ tumor and the powerful systematic antitumor immunity generation, eventually achieving vigorous antitumor and recurrence resistance. This study proposes an unsophisticated and versatile strategy to significantly improve PDT efficacy for enhancing systemic antitumor immunity and potentially extending it to multiple cancers.

Promoting the application of pediatric radiomics via an integrated medical engineering approach.

Radiomics is widely used in adult tumors but has been rarely applied to the field of pediatrics. Promoting the application of radiomics in pediatric diseases, especially in the early diagnosis and stratified treatment of tumors, is of great value to the realization of the WHO 2030 "Global Initiative for Childhood Cancer." This paper discusses the general characteristics of radiomics, the particularity of its application to pediatric diseases, and the current status and prospects of pediatric radiomics. Radiomics is a data-driven science, and the combination of medicine and engineering plays a decisive role in improving data quality, data diversity, and sample size. Compared with adult radiomics, pediatric radiomics is significantly different in data type, disease spectrum, disease staging, and progression. Some progress has been made in the identification, classification, stratification, survival prediction, and prognosis of tumor diseases. In the future, big data applications from multiple centers and cross-talent training should be strengthened to improve the benefits for clinical workers and children.

Machine-learning radiomics to predict bone marrow metastasis of neuroblastoma using magnetic resonance imaging.

Background: Neuroblastoma is one common pediatric malignancy notorious for high temporal and spatial heterogeneities. More than half of its patients develop distant metastases involving vascularized organs, especially the bone marrow. It is thus necessary to have an economical, noninvasive method without much radiation for follow-ups. Radiomics has been used in many cancers to assist accurate diagnosis but not yet in bone marrow metastasis in neuroblastoma. Methods: A total of 182 patients with neuroblastoma were retrospectively collected and randomly divided into the training and validation sets. Five-hundred and seventy-two radiomics features were extracted from magnetic resonance imaging, among which 41 significant ones were selected via T-test for model development. We attempted 13 machine-learning algorithms and eventually chose three best-performed models. The integrative performance evaluations are based on the area under the curves (AUCs), calibration curves, risk deciles plots, and other indexes. Results: Extreme gradient boosting, random forest (RF), and adaptive boosting were the top three to predict bone marrow metastases in neuroblastoma while RF was the most accurate one. Its AUC was 0.90 (0.86-0.93), F1 score was 0.82, sensitivity was 0.76, and negative predictive value was 0.79 in the training set. The values were 0.82 (0.71-0.93), 0.80, 0.75, and 0.92 in the validation set, respectively. Conclusions: Radiomics models are likely to contribute more to metastatic diagnoses and the formulation of personalized healthcare strategies in clinics. It has great potential of being a revolutionary method to replace traditional interventions in the future.

A radiomics based approach using adrenal gland and periadrenal fat CT images to allocate COVID-19 health care resources fairly.

BACKGROUND: The value of radiomics features from the adrenal gland and periadrenal fat CT images for predicting disease progression in patients with COVID-19 has not been studied extensively. We assess the value of radiomics features from the adrenal gland and periadrenal fat CT images in predicting COVID-19 disease exacerbation. METHODS: A total of 1,245 patients (685 moderate and 560 severe patients) were enrolled in a retrospective study. We proposed a 3D V-net to segment adrenal glands in onset CT images automatically, and periadrenal fat was obtained using inflation operation around the adrenal gland. Next, we built a clinical model (CM), three radiomics models (adrenal gland model [AM], periadrenal fat model [PM], and fusion of adrenal gland and periadrenal fat model [FM]), and radiomics nomogram (RN) after radiomics features extracted. RESULTS: The auto-segmentation framework yielded a dice value 0.79 in the training set. CM, AM, PM, FM, and RN obtained AUCs of 0.717, 0.716, 0.736, 0.760, and 0.833 in the validation set. FM and RN had better predictive efficacy than CM (P < 0.0001) in the training set. RN showed that there was no significant difference in the validation set (mean absolute error [MAE] = 0.04) and test set (MAE = 0.075) between predictive and actual results. Decision curve analysis showed that if the threshold probability was between 0.4 and 0.8 in the validation set or between 0.3 and 0.7 in the test set, it could gain more net benefits using RN than FM and CM. CONCLUSIONS: Radiomics features extracted from the adrenal gland and periadrenal fat CT images are related to disease exacerbation in patients with COVID-19.

A Multicenter Study on Preoperative Assessment of Lymphovascular Space Invasion in Early-Stage Cervical Cancer Based on Multimodal MR Radiomics.

BACKGROUND: As lymphovascular space invasion (LVSI) was closely related to lymph node metastasis and prognosis, the preoperative assessment of LVSI in early-stage cervical cancer is crucial for patients. PURPOSE: To develop and validate nomogram based on multimodal MR radiomics to assess LVSI status in cervical cancer patients. STUDY TYPE: Retrospective. POPULATION: The study included 168 cervical cancer patients, of whom 129 cases (age 51.36 ± 9.99 years) from institution 1 were included as the training cohort and 39 cases (age 52.59 ± 10.23 years) from institution 2 were included as the external test cohort. FIELD STRENGTH/SEQUENCE: There were 1.5 T and 3.0 T MRI scans (T1-weighted imaging [T1WI], fat-saturated T2-weighted imaging [FS-T2WI], and contrast-enhanced [CE]). ASSESSMENT: Six machine learning models were built and selected to construct the radiomics signature. The nomogram model was constructed by combining the radiomics signature with the clinical signature, which was then validated for discrimination, calibration, and clinical usefulness. STATISTICAL TESTS: The clinical characteristics were compared using t-tests, Mann-Whitney U tests, or chi-square tests. The Spearman and LASSO methods were used to select radiomics features. The receiver operating characteristic (ROC) analysis was performed, and the area under the curve (AUC), accuracy, sensitivity, and specificity were calculated. RESULTS: The logistic regression (LR) model performed best in each sequence. The AUC of CE-T1-T2WI-combined was the highest in the LR model, with an AUC of 0.775 (95% CI: 0.570-0.979) in external test cohort. The nomogram showed high predictive performance in the training (AUC: 0.883 [95% CI: 0.823-0.943]) and test cohort (AUC: 0.830 [95% CI: 0.657-1.000]) for predicting LVSI. Decision curve analysis demonstrated that the nomogram was clinically useful. DATA CONCLUSION: Our findings suggest that the proposed nomogram model based on multimodal MRI of CE T1WI-T2WI-combined could be used to assess LVSI status in early cervical cancer. EVIDENCE LEVEL: 4. TECHNICAL EFFICACY: Stage 2.

Repolarizing tumor-associated macrophages by layered double hydroxide-based deacidification agent for tumor chemodynamic therapy and immunotherapy.

Tumor-associated macrophages (TAMs)-mediated immunotherapy has attracted extensive attention in tumor elimination. However, the acidic tumor microenvironment (TME) severely limits the phenotype of TAMs to pro-tumoral M2 state, suppressing immune response efficacy against tumors. Herein, novel poly(acrylic acid) (PAA)-coated, doxorubicin (DOX)-loaded layered double hydroxide (LDH) nanosheets (NSs) were developed as deacidification agent to repolarize TAMs from pro-tumoral M2 to anti-tumoral M1 phenotype for tumor elimination through combined chemodynamic therapy and immunotherapy. When located in tumor regions, LDH-PAA@DOX NSs display good deacidification capacity to neutralize acidic TME, achieving the repolarization of TAMs to M1 phenotype and further activating CD8+ T cells. During the deacidification process, these NSs are acid-responsive and degrade to release Fe3+ and DOX. The former can be reduced to Fe2+ by intracellular glutathione, meanwhile disrupting the antioxidant defense system of tumor cells. The latter can damage tumor cells directly and further stimulate the production of hydrogen peroxide, providing abundant substrate for the Fenton reaction. Toxic hydroxyl radical is excessively produced through Fe2+-mediated Fenton reaction to cause intratumoral oxidative stress. In vivo data revealed that significant tumor elimination can be achieved under LDH-PAA@DOX treatment. This work not only provides a promising paradigm for neutralizing acidic TME using deacidification agent but also highlights the effectiveness of combined chemodynamic therapy and immunotherapy in tumor treatment.

Low-dissipation optimization of the prefrontal cortex in the -12° head-down tilt position: A functional near-infrared spectroscopy study.

Introduction: Our present study set out to investigate the instant state of the prefrontal cortex (PFC) in healthy subjects before and after placement in the -12°head-down tilt (HDT) position in order to explore the mechanism behind the low-dissipation optimization state of the PFC. Methods: 40 young, right-handed healthy subjects (male: female = 20: 20) were enrolled in this study. Three resting state positions, 0°initial position, -12°HDT position, and 0°rest position were sequentially tested, each for 10 minutes. A continuous-wave functional near-infrared spectroscopy (fNIRS) instrument was used to assess the resting state hemodynamic data of the PFC. After preprocessing the hemodynamics data, we evaluated changes in resting-state functional connectivity (rsFC) level and beta values of PFC. The subjective visual analogue scale (VAS) was applied before and after the experiment. The presence of sleep changes or adverse reactions were also recorded. Results: Pairwise comparisons of the concentrations of oxyhemoglobin (HbO), deoxyhemoglobin (HbR), and hemoglobin (HbT) revealed significant differences in the aforementioned positions. Specifically, the average rsFC of PFC showed a gradual increase throughout the whole process. In addition, based on graph theory, the topological properties of brain network, such as small-world network and nodal degree centrality were analyzed. The results show that global efficiency and small-world sigma (σ) value were differences between 0°initial and 0°rest. Discussion: In this study, placement in the -12°HDT had a significant effect on PFC function, mainly manifested as self-inhibition, decreased concentration of HbO in the PFC, and improved rsFC, which may provide ideas to the understanding and explanation of neurological diseases.

Integrated endotoxin-adsorption and antibacterial properties of platelet-membrane-coated copper silicate hollow microspheres for wound healing.

Serious infection caused by drug-resistant gram-negative bacteria and their secreted toxins (e.g., lipopolysaccharide) is a serious threat to human health. Thus, treatment strategies that efficiently kill bacteria and reducing the impact of their toxins simultaneously are urgently required. Herein, a novel antibacterial platform composed of a mesoporous copper silicate microsphere (CSO) core and a platelet membrane (PM) shell was prepared (CSO@PM). CSO@PM specifically targets bacteria owing to formyl peptide receptors on the PM and, combined with photothermal therapy (PTT), exhibits highly effective bacter icidal activity. Importantly, CSO@PM can adsorb lipopolysaccharide secreted by gram-negative bacteria, resulting in inflammation reduction. Thus, CSO@PM stimulates re-epithelialization and granulation-tissue formation, promoting wound healing. Moreover, this antibacterial platform exhibits no obvious toxicity at all the test concentrations in vitro and in vivo. Thus, CSO@PM exhibits a robust antibacterial effect and a strong toxin-adsorption capacity, facilitating the clinical treatment of many bacterial infections and the development of next-generation antibacterial nanoagents.

Bimetallic palladium@copper nanoparticles: Lethal effect on the gram-negative bacterium Pseudomonas aeruginosa.

Infections by the gram-negative bacterium Pseudomonas aeruginosa are on the rise, and its antibiotic resistance is a tough challenge for clinical therapeutics worldwide. Therefore, it is an urgent to find alternative antibiotics that possess preferable bactericidal efficiency and are safer than silver (Ag) nanoparticles (Ag NPs). Here, we synthesized small palladium@copper (Pd1.9Cu) alloy NPs with preferable antibacterial functions. We also used a bacteria-infected skin wound mouse model to confirm the sterilization effect of Pd1.9Cu NPs. Pd1.9Cu NPs killed P. aeruginosa at a low concentration, displaying a more powerful bactericidal effect than Ag NPs in vitro. In addition, Pd1.9Cu NPs broke through the bacterial membrane, leading to DNA fragmentation and leakage of genomic DNA and proteins. The underlying mechanism was to trigger the burst of intracellular reactive oxygen species generation and accelerated ion release (Cu and Pd). Pd1.9Cu NPs were also more capable of disinfection than Ag NPs and ceftazidime in vivo, promoting speedy wound recovery. Simultaneously, the biocompatibility of Pd1.9Cu NPs was satisfactory both in vitro and in vivo. These results show that Pd1.9Cu NPs are a promising nanomedicine to treat P. aeruginosa infection.

An AI-based auxiliary empirical antibiotic therapy model for children with bacterial pneumonia using low-dose chest CT images.

PURPOSE: To construct an auxiliary empirical antibiotic therapy (EAT) multi-class classification model for children with bacterial pneumonia using radiomics features based on artificial intelligence and low-dose chest CT images. MATERIALS AND METHODS: Data were retrospectively collected from children with pathogen-confirmed bacterial pneumonia including Gram-positive bacterial pneumonia (122/389, 31%), Gram-negative bacterial pneumonia (159/389, 41%) and atypical bacterial pneumonia (108/389, 28%) from January 1 to June 30, 2019. Nine machine-learning models were separately evaluated based on radiomics features extracted from CT images; three optimal submodels were constructed and integrated to form a multi-class classification model. RESULTS: We selected five features to develop three radiomics submodels: a Gram-positive model, a Gram-negative model and an atypical model. The comprehensive radiomics model using support vector machine method yielded an average area under the curve (AUC) of 0.75 [95% confidence interval (CI), 0.65-0.83] and accuracy (ACC) of 0.58 [sensitivity (SEN), 0.57; specificity (SPE), 0.78] in the training set, and an average AUC of 0.73 (95% CI 0.61-0.79) and ACC of 0.54 (SEN, 0.52; SPE, 0.75) in the test set. CONCLUSION: This auxiliary EAT radiomics multi-class classification model was deserved to be researched in differential diagnosing bacterial pneumonias in children.

Bilateral striatum with high-signal intensity on T1-weighted MRI: A case of hemichorea induced by nonketotic hyperglycemia.

Hemichorea induced by nonketotic hyperglycemia is a rare complication of diabetes mellitus. Here we present a case of 80-year-old female patient. She had a history of involuntary movement of the left body. Imaging examination showed abnormal signs of bilateral basal ganglia. After relevant treatment was conducted, the patient's hemichorea symptoms were significantly improved. Imaging features of nonketotic hyperglycemia Hemichorea plays a very important role in diagnosing and treatment of this disease. Introduction: Hemichorea refers to the involuntary movements of one or more limbs of the same side. These movements are continuous and irregular, variable amplitude, and usually involve the arms and legs together. Stroke is the most common reason, hyperglycemia is relatively rare. Characteristic imaging findings can be very suggestive of diagnosis, and also closely related to the development of disease. Here we present a case of hemichorea induced by nonketotic hyperglycemia which was confirmed by bilateral abnormal signals of basal ganglia in MRI.

Chemoprophylaxis, diagnosis, treatments, and discharge management of COVID-19: An evidence-based clinical practice guideline (updated version).

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of a rapidly spreading illness, coronavirus disease 2019 (COVID-19), affecting more than seventeen million people around the world. Diagnosis and treatment guidelines for clinicians caring for patients are needed. In the early stage, we have issued "A rapid advice guideline for the diagnosis and treatment of 2019 novel coronavirus (2019-nCoV) infected pneumonia (standard version)"; now there are many direct evidences emerged and may change some of previous recommendations and it is ripe for develop an evidence-based guideline. We formed a working group of clinical experts and methodologists. The steering group members proposed 29 questions that are relevant to the management of COVID-19 covering the following areas: chemoprophylaxis, diagnosis, treatments, and discharge management. We searched the literature for direct evidence on the management of COVID-19, and assessed its certainty generated recommendations using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach. Recommendations were either strong or weak, or in the form of ungraded consensus-based statement. Finally, we issued 34 statements. Among them, 6 were strong recommendations for, 14 were weak recommendations for, 3 were weak recommendations against and 11 were ungraded consensus-based statement. They covered topics of chemoprophylaxis (including agents and Traditional Chinese Medicine (TCM) agents), diagnosis (including clinical manifestations, reverse transcription-polymerase chain reaction (RT-PCR), respiratory tract specimens, IgM and IgG antibody tests, chest computed tomography, chest x-ray, and CT features of asymptomatic infections), treatments (including lopinavir-ritonavir, umifenovir, favipiravir, interferon, remdesivir, combination of antiviral drugs, hydroxychloroquine/chloroquine, interleukin-6 inhibitors, interleukin-1 inhibitors, glucocorticoid, qingfei paidu decoction, lianhua qingwen granules/capsules, convalescent plasma, lung transplantation, invasive or noninvasive ventilation, and extracorporeal membrane oxygenation (ECMO)), and discharge management (including discharge criteria and management plan in patients whose RT-PCR retesting shows SARS-CoV-2 positive after discharge). We also created two figures of these recommendations for the implementation purpose. We hope these recommendations can help support healthcare workers caring for COVID-19 patients.

Chemoprophylaxis, diagnosis, treatments, and discharge management of COVID-19: an evidence-based clinical practice guideline (updated version)

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of a rapidly spreading illness, coronavirus disease 2019 (COVID-19), affecting more than seventeen million people around the world. Diagnosis and treatment guidelines for clinicians caring for patients are needed. In the early stage, we have issued "A rapid advice guideline for the diagnosis and treatment of 2019 novel coronavirus (2019-nCoV) infected pneumonia (standard version)"; now there are many direct evidences emerged and may change some of previous recommendations and it is ripe for develop an evidence-based guideline. We formed a working group of clinical experts and methodologists. The steering group members proposed 29 questions that are relevant to the management of COVID-19 covering the following areas: chemoprophylaxis, diagnosis, treatments, and discharge management. We searched the literature for direct evidence on the management of COVID-19, and assessed its certainty generated recommendations using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach. Recommendations were either strong or weak, or in the form of ungraded consensus-based statement. Finally, we issued 34 statements. Among them, 6 were strong recommendations for, 14 were weak recommendations for, 3 were weak recommendations against and 11 were ungraded consensus-based statement. They covered topics of chemoprophylaxis (including agents and Traditional Chinese Medicine (TCM) agents), diagnosis (including clinical manifestations, reverse transcription-polymerase chain reaction (RT-PCR), respiratory tract specimens, IgM and IgG antibody tests, chest computed tomography, chest x-ray, and CT features of asymptomatic infections), treatments (including lopinavir-ritonavir, umifenovir, favipiravir, interferon, remdesivir, combination of antiviral drugs, hydroxychloroquine/chloroquine, interleukin-6 inhibitors, interleukin-1 inhibitors, glucocorticoid, qingfei paidu decoction, lianhua qingwen granules/capsules, convalescent plasma, lung transplantation, invasive or noninvasive ventilation, and extracorporeal membrane oxygenation (ECMO)), and discharge management (including discharge criteria and management plan in patients whose RT-PCR retesting shows SARS-CoV-2 positive after discharge). We also created two figures of these recommendations for the implementation purpose. We hope these recommendations can help support healthcare workers caring for COVID19 patients

Type 2 Diabetes Mellitus May Exacerbate Gray Matter Atrophy in Patients With Early-Onset Mild Cognitive Impairment.

BACKGROUND: The precise physiopathological association between the courses of neurodegeneration and cognitive decline in type 2 diabetes mellitus (T2DM) remains unclear. This study sought to comprehensively investigate the distribution characteristics of gray matter atrophy in middle-aged T2DM patients with newly diagnosed mild cognitive impairment (MCI). METHODS: Four groups, including 28 patients with early-onset MCI, 28 patients with T2DM, 28 T2DM patients with early-onset MCI (T2DM-MCI), and 28 age-, sex-, and education-matched healthy controls underwent three-dimensional high-resolution structural magnetic resonance imaging. Cortical and subcortical gray matter volumes were calculated, and a structural covariance method was used to evaluate the morphological relationships within the default mode network (DMN). RESULTS: Overlapped and unique cortical/subcortical gray matter atrophy was found in patients with MCI, T2DM and T2DM-MCI in our study, and patients with T2DM-MCI showed lower volumes in several areas than patients with MCI or T2DM. Volume loss in subcortical areas (including the thalamus, putamen, and hippocampus), but not in cortical areas, was related to cognitive impairment in patients with MCI and T2DM-MCI. No associations between biochemical measurements and volumetric reductions were found. Furthermore, patients with MCI and those with T2DM-MCI showed disrupted structural connectivity within the DMN. CONCLUSION: These findings provide further evidence that T2DM may exacerbate atrophy of specific gray matter regions, which may be primarily associated with MCI. Impairments in gray matter volume related to T2DM or MCI are independent of cardiovascular risk factors, and subcortical atrophy may play a more pivotal role in cognitive impairment than cortical alterations in patients with MCI and T2DM-MCI. The enhanced structural connectivity within the DMN in patients with T2DM-MCI may suggest a compensatory mechanism for the chronic neurodegeneration.

Atrophic Corpus Callosum Associated with Altered Functional Asymmetry in Major Depressive Disorder.

PURPOSE: Impairments in intra- and inter-hemispheric information transfer circuits have been reported in patients with major depressive disorder (MDD). However, the specific anomalous connection (intra- and/or inter-hemispheric) and hemisphere (left and/or right) in which this connection plays a more dominant role in the pathogenic mechanism underlying MDD are still poorly understood. PATIENTS AND METHODS: Structural magnetic resonance imaging and resting-state functional magnetic resonance imaging were performed in 33 patients with MDD and 33 healthy controls. The intra- and inter-hemispheric functional connectivity (FC) strength in the default mode network areas and volume of the callosal subregions were computed using independent samples t-tests. The partial correlations between the volumes and FCs were also computed. RESULTS: The patients with MDD had smaller volumes in the genu of the corpus callosum than the controls. The intrahemispheric FCs of the bilateral posterior cingulate gyrus, left precuneus, left medial superior frontal gyrus, left medial orbitofrontal gyrus, left angular gyrus and left middle temporal gyrus, and interhemispheric FCs of the bilateral posterior cingulate gyrus in the patients with MDD were lower than those in the controls. Moreover, the intrahemispheric FCs of the precuneus and interhemispheric FCs of middle frontal gyrus, orbital middle frontal gyrus, and anterior cingulate gyrus in the patients with MDD showed right-lateralized asymmetry, which were opposite from the asymmetry patterns observed in the controls. The functional asymmetry of the anterior cingulate gyrus was correlated with the volume of the genu of the corpus callosum and disease duration. CONCLUSION: These findings provide robust evidence that intra- and inter-hemispheric disconnections are involved in MDD, and that functional disruptions in the left hemisphere may be more relevant to the pathophysiology of MDD. Furthermore, imbalanced interhemispheric exchanges may contribute to the anatomical deficits in the corpus callosum in patients with MDD.

Alterations of Brain Structural Network Connectivity in Type 2 Diabetes Mellitus Patients With Mild Cognitive Impairment.

Patients with type 2 diabetes mellitus (T2DM) are highly susceptible to developing dementia, especially for those with mild cognitive impairment (MCI), but its underlying cause is still unclear. This study aims to investigate the early detection of white matter structural network changes in T2DM patients with MCI and assess the relationship between cognitive impairment and structural network alterations in T2DM patients. In this study, we performed a battery of neuropsychological tests and diffusion tensor MRI in 30 T2MD-MCI patients, 30 T2DM patients with normal cognition (T2DM-NC) and 30 age-, sex-, and education-matched healthy control (HC) individuals. Cognitive performance exhibited obvious differences among the three groups. The structural network was significantly disrupted in both global and regional levels in T2DM patients. The T2DM-MCI group showed more severe impairment of global network efficiency, and lower nodal efficiency and fewer connections within multiple regions like the limbic system, basal ganglia, and several cortical structures. Moreover, a subnetwork impaired in T2DM-MCI patients was characterized by cortical-limbic fibers, and commissural fibers and pathways within the frontal, temporal, and occipital lobes. These altered global and nodal parameters were significantly correlated with cognitive function in T2DM-MCI patients. In particular, executive dysfunction and working memory impairment in T2DM-MCI patients correlated with nodal efficiency in the right opercular part and triangular part of the inferior frontal gyrus, which indicated that white matter disruption in these regions may act as potential biomarkers for T2DM-associated MCI detection. Our investigation provides a novel insight into the neuropathological effects of white matter network disruption on cognition impairments induced by T2DM.

Quantitative Iron Neuroimaging Can Be Used to Assess the Effects of Minocycline in an Intracerebral Hemorrhage Minipig Model.

Iron-mediated toxicity is a key factor causing brain injury after intracerebral hemorrhage (ICH). This study was performed to investigate the noninvasive neuroimaging method for quantifying brain iron content using a minipig ICH model and assess the effects of minocycline treatment on ICH-induced iron overload and brain injury. The minipig ICH model was established by injecting 2 ml of autologous blood into the right basal ganglia, which were then subjected to the treatments of minocycline and vehicle. Furthermore, the quantitative susceptibility mapping (QSM) was used to quantify iron content, and diffusion tensor imaging (DTI) was performed to evaluate white matter tract. Additionally, we also performed immunohistochemistry, Western blot, iron assay, Perl's staining, brain water content, and neurological score to evaluate the iron overload and brain injury. Interestingly, we found that the ICH-induced iron overload could be accurately quantified by the QSM. Moreover, the minocycline was quite beneficial for protecting brain injury by reducing the lesion volume and brain edema, preventing brain iron accumulation, downsizing ventricle enlargement, and alleviating white matter injury and neurological deficits. In summary, we suggest that the QSM be an accurate and noninvasive method for quantifying brain iron level, and the minocycline may be a promising therapeutic agent for patients with ICH.