Bayesian network analysis of factors influencing type 2 diabetes, coronary heart disease, and their comorbidities.

OBJECTIVE: Bayesian network (BN) models were developed to explore the specific relationships between influencing factors and type 2 diabetes mellitus (T2DM), coronary heart disease (CAD), and their comorbidities. The aim was to predict disease occurrence and diagnose etiology using these models, thereby informing the development of effective prevention and control strategies for T2DM, CAD, and their comorbidities. METHOD: Employing a case-control design, the study compared individuals with T2DM, CAD, and their comorbidities (case group) with healthy counterparts (control group). Univariate and multivariate Logistic regression analyses were conducted to identify disease-influencing factors. The BN structure was learned using the Tabu search algorithm, with parameter estimation achieved through maximum likelihood estimation. The predictive performance of the BN model was assessed using the confusion matrix, and Netica software was utilized for visual prediction and diagnosis. RESULT: The study involved 3,824 participants, including 1,175 controls, 1,163 T2DM cases, 982 CAD cases, and 504 comorbidity cases. The BN model unveiled factors directly and indirectly impacting T2DM, such as age, region, education level, and family history (FH). Variables like exercise, LDL-C, TC, fruit, and sweet food intake exhibited direct effects, while smoking, alcohol consumption, occupation, heart rate, HDL-C, meat, and staple food intake had indirect effects. Similarly, for CAD, factors with direct and indirect effects included age, smoking, SBP, exercise, meat, and fruit intake, while sleeping time and heart rate showed direct effects. Regarding T2DM and CAD comorbidities, age, FBG, SBP, fruit, and sweet intake demonstrated both direct and indirect effects, whereas exercise and HDL-C exhibited direct effects, and region, education level, DBP, and TC showed indirect effects. CONCLUSION: The BN model constructed using the Tabu search algorithm showcased robust predictive performance, reliability, and applicability in forecasting disease probabilities for T2DM, CAD, and their comorbidities. These findings offer valuable insights for enhancing prevention and control strategies and exploring the application of BN in predicting and diagnosing chronic diseases.

Associations between dietary inflammatory index and stroke risk: based on NHANES 2005-2018.

The dietary inflammatory index (DII) is a measure of the inflammatory potential of the diet and is closely associated with insulin resistance (IR) and stroke. And IR may play an important role in the development of stroke. Therefore, this study aimed to evaluate the relationship between DII and stroke risk while delving into the potential role of IR in this association. We analyzed data from the National Health and Nutrition Examination Survey (NHANES) from 2005 to 2018, performing weighted univariate analyses, logistic regression, and mediation analyses. At baseline, 3.89% of participants developed stroke, and we observed stroke patients exhibited higher DII scores. After adjusting for covariates, compared to participants in the first quartile of DII scores, those in the third quartile and fourth quartile had increased odds of experiencing a stroke (OR: 1.78, 95% CI: 1.18-2.68) and (OR: 1.70, 95% CI: 1.16-2.50), respectively. Moreover, a significant dose-response relationship was observed (P-trend < 0.05). However, there was no observed interaction between DII and homeostatic model assessment-IR (HOMA-IR) concerning stroke risk, and HOMA-IR did not mediate the association between DII and stroke. In summary, our study elucidated the significant association between DII and stroke risk, independent of IR. This insight suggests that an anti-inflammatory diet may serve as an effective strategy for stroke prevention.

Role of remnant cholesterol in the relationship between physical activity and diabetes mellitus: an intermediary analysis.

Objective: The purpose of this investigation was to evaluate the potential link between physical activity (PA) and the heightened susceptibility to diabetes mellitus (DM), by examining whether remnant cholesterol (RC) might act as a mediator in this correlation. Methods: The research utilized data from the National Health and Nutrition Examination Survey, spanning from 2005 to 2018. Various statistical analyses were conducted for continuous and categorical variables, including the t-test, ANOVA, and χ2 test. Logistic regression was employed to analyze the association between PA and DM across three distinct models. Mediation analysis was also conducted to assess the potential mediation effects of RC. Results: The study encompassed a total of 9,149 participants, and it was observed that individuals with DM exhibited lower levels of PA. Furthermore, PA levels were found to be associated with all participant characteristics except poverty income ratio, fasting blood glucose, and HOMA-IR (p < 0.05). After adjusting for covariates (Model 3), individuals with high PA levels demonstrated a decreased likelihood of developing DM compared to those in the low PA group (OR: 0.73, 95%CI: 0.54-0.99). A significant dose-response relationship was identified (p < 0.05). No interaction between PA and RC in relation to DM risk was detected, and RC was found to serve as a mediator in the connection between PA and DM. After considering covariates, the mediating effect of RC between PA and DM weakens. Discussion: Our findings suggest that higher levels of PA are linked to a reduced risk of DM in U.S. adults, with RC likely playing a mediating role.

Effects of low-dose furosemide combined with aminophylline on the renal function in septic shock patients.

BACKGROUND: To investigate the effects of low-dose furosemide and aminophylline on the renal function in patients with septic shock. METHODS AND RESULTS: A total of 109 eligible septic shock patients in the intensive care unit were randomly divided into a control group (n = 55) and an intervention group (n = 54). The control group received normal saline, and the intervention group received low-dose furosemide (0.048 mg/kg.h-1) with aminophylline (0.3 mg/kg.h-1). The primary outcomes included the levels of serum creatinine (Scr), creatinine clearance rate (Ccr), blood urea nitrogen (BUN), glomerular filtration rate (GFR), and urine output on admission and on days 3, 7 and 14. The secondary outcomes were the sequential organ failure assessment (SOFA) scores, continuous renal replacement therapy (CRRT) time and intensive care unit (ICU) mortality, hospital mortality and 28-day mortality. There were no significant differences in the levels of Scr, Ccr, BUN, or GFR between the two groups, while the urine output was higher in the intervention group on days 3, 7, and 14. Compared with the control group, the SOFA scores, ICU mortality, hospital mortality and 28-day mortality were significantly lower in the intervention group on days 3, 7, and 14, the CRRT time was shorter, and the cumulative fluid balance was lower on days 3 and 7 in the intervention group. CONCLUSIONS: Although low-dose furosemide and aminophylline have fewer protective effects on the renal function in septic shock patients, they could reduce the CRRT time and improve the prognosis.

TREM-1 induces pyroptosis in cardiomyocytes by activating NLRP3 inflammasome through the SMC4/NEMO pathway.

Sepsis often causes cell death via pyroptosis and hence results in septic cardiomyopathy. Triggering receptors expressed in myeloid cells-1 (TREM-1) may initiate cellular cascade pathways and, in turn, induce cell death and vital organ dysfunction in sepsis, but the evidence is limited. We set to investigate the role of TREM-1 on nucleotide-binding oligomerization domain-like receptors with pyrin domain-3 (NLRP3) inflammasome activation and cardiomyocyte pyroptosis in sepsis models using cardiac cell line (HL-1) and mice. In this study, TREM-1 was found to be significantly increased in HL-1 cells challenged with lipopolysaccharide (LPS). Pyroptosis was also significantly increased in the HL-1 cells challenged with lipopolysaccharide and an NLRP3 inflammasome activator, nigericin. The close interaction between TREM-1 and structural maintenance of chromosome 4 (SMC4) was also identified. Furthermore, inhibition of TREM-1 or SMC4 prevented the upregulation of NLRP3 and decreased Gasdermin-D, IL-1ß and caspase-1 cleavage. In mice subjected to caecal ligation and puncture, the TREM-1 inhibitor LR12 decreased the expression of NLRP3 and attenuated cardiomyocyte pyroptosis, leading to improved cardiac function and prolonged survival of septic mice. Our work demonstrates that, under septic conditions, TREM-1 plays a critical role in cardiomyocyte pyroptosis. Targeting TREM-1 and its associated molecules may therefore lead to novel therapeutic treatments for septic cardiomyopathy.

Genetically predicted lifestyle factors, socioeconomic status and risk of coronary artery disease in individuals with diabetes: a Mendelian randomization study.

Background: This study explores the causal links between genetically predicted lifestyle factors, socioeconomic status, and coronary artery disease (CAD) risk in individuals with diabetes using a bidirectional Mendelian-randomization approach. Methods: This study explored the potential causal relationships of lifestyle factors and socioeconomic status with the risk of CAD in diabetes patients by a bidirectional, two-sample Mendelian-randomization (MR) analysis. Results: Genetically predicted smoking initiation (p = 0.005, 95% CI: 1.08-1.55) and insomnia (p = 0.001, 95% CI: 1.06-1.29) were associated with a higher risk of CAD in individuals with diabetes, whereas educational attainment (p = 0.0001, 95% CI: 0.47-0.78) was associated with a lower risk of CAD. The lifetime smoking index (p = 0.016, 95% CI: 1.12-3.03) was suggestively associated with a higher risk of CAD, while household income before taxes (p = 0.048, 95% CI: 0.41-1.00) was suggestively associated with a lower risk of CAD. In addition, we observed a suggestive negative association between the genetically predicted risk of CAD and the lifetime smoking index (p = 0.016, 95% CI: 0.98-0.99) and a significant causal relationship between the risk of CAD and household income before taxes (p = 0.006, 95% CI: 0.97-0.99). Conclusion: The results of this study provide evidence that smoking initiation, lifetime smoking index and insomnia are associated with an increased risk of CAD in individuals with diabetes, educational attainment and household income before taxes are associated with a reduced risk of CAD in individuals with diabetes, and the possible role of lifetime smoking index and household income before taxes on the risk of CAD in individuals with diabetes. It provides an opportunity for the prevention and management of CAD in individuals with diabetes.

Association between systemic immune-inflammatory index and diabetes mellitus: mediation analysis involving obesity indicators in the NHANES.

Background: Inflammation and obesity have been widely recognized to play a key role in Diabetes mellitus (DM), and there exists a complex interplay between them. We aimed to clarify the relationship between inflammation and DM, as well as the mediating role of obesity in the relationship. Methods: Based on the National Health and Nutrition Examination Survey (NHANES) 2005-2018. Univariate analyses of continuous and categorical variables were performed using t-test, linear regression, and χ2 test, respectively. Logistic regression was used to analyze the relationship between Systemic Immune-Inflammatory Index (SII) or natural logarithm (Ln)-SII and DM in three different models. Mediation analysis was used to determine whether four obesity indicators, including body mass index (BMI), waist circumference (WC), visceral adiposity index (VAI) and lipid accumulation product index (LAP), mediated the relationship between SII and DM. Results: A total of 9,301 participants were included, and the levels of SII and obesity indicators (BMI, WC, LAP, and VAI) were higher in individuals with DM (p < 0.001). In all three models, SII and Ln-SII demonstrated a positive correlation with the risk of DM and a significant dose-response relationship was found (p-trend <0.05). Furthermore, BMI and WC were associated with SII and the risk of DM in all three models (p < 0.001). Mediation analysis showed that BMI and WC mediated the relationship between SII with DM, as well as Ln-SII and DM, with respective mediation proportions of 9.34% and 12.14% for SII and 10.23% and 13.67% for Ln-SII (p < 0.001). Conclusion: Our findings suggest that increased SII levels were associated with a higher risk of DM, and BMI and WC played a critical mediating role in the relationship between SII and DM.

ATL I, Acts as a SIRT6 Activator to Alleviate Hepatic Steatosis in Mice via Suppression of NLRP3 Inflammasome Formation.

Accumulating evidence has highlighted that sirtuin-6 (SIRT6) plays an important role in hepatic gluconeogenesis and lipogenesis. We aim to investigate the underlying mechanisms and pharmacological interventions of SIRT6 on hepatic steatosis treatment. Herein, our results showed that atractylenolide I (ATL I) activated the deacetylase activity of SIRT6 to promote peroxisome proliferator-activated receptor alpha (PPARα) transcription and translation, while suppressing nuclear factor NF-kappa-B (NFκB)-induced NACHT, LRR, and PYD domains containing protein 3 (NLRP3) inflammasome formation. Together, these decreased the infiltration of F4/80 and CD11B positive macrophages, accompanied by decreased mRNA expression and serum levels of tumor necrosis factor alpha (TNF-α), interleukin-6 (IL6), and interleukin-1 beta (IL1ß). Additionally, these changes decreased sterol regulatory element-binding protein-1c (SREBP-1c) expression, while restoring carnitine O-palmitoyltransferase 1a (Cpt1a) expression, to decrease the size of adipocytes and adipose deposition, which, in turn, reversed high-fat diet (HFD)-induced liver weight and body weight accumulation in C57 mice. SIRT6 knockout or hepatic SIRT6 knockout in C57 mice largely abolished the effect of ATL I on ameliorating hepatic steatosis. Taken together, our results suggest that ATL I acts as a promising compound that activates SIRT6/PPARα signaling and attenuates the NLRP3 inflammasome to ameliorate hepatic inflammation and steatosis.

Ginsenoside Rc attenuates DSS-induced ulcerative colitis, intestinal inflammatory, and barrier function by activating the farnesoid X receptor.

Objectives: Farnesoid X receptor (FXR) activation is involved in ameliorating inflammatory bowel disease (IBD), such as ulcerative colitis (UC), and inflammatory regulation may be involved in its mechanism. Ginsenoside Rc (Rc) is a major component of Panax ginseng, and it plays an excellent role in the anti-inflammatory processes. Our aim is to explore the alleviative effect of Rc on dextran sulfate sodium (DSS)-induced inflammation and deficiencies in barrier function based on FXR signaling. Materials and Methods: In vitro, we treated human intestinal epithelial cell lines (LS174T) with LPS to explore the anti-inflammatory effect of Rc supplementation. In vivo, a DSS-induced IBD mice model was established, and the changes in inflammatory and barrier function in colons after Rc treatment were measured using the disease activity index (DAI), hematoxylin and eosin (H&E) staining, immunofluorescence, ELISA, and qPCR. Molecular docking analysis, luciferase reporter gene assay, and qPCR were then used to analyze the binding targets of Rc. DSS-induced FXR-knockout (FXR-/-) mice were used for further validation. Results: Rc significantly recovered the abnormal levels of inflammation indexes (TNF-α, IL-6, IL-1ß, and NF-KB) induced by LPS in LS174T. DSS-induced C57BL/6 mice exhibited a significantly decreased body weight and elevated DAI, as well as a decrease in colon weight and length. Increased inflammatory markers (TNF-α, IL-6, IL-1ß, ICAM1, NF-KB, F4/80, and CD11b displayed an increased expression) and damaged barrier function (Claudin-1, occludin, and ZO-1 displayed a decreased expression) were observed in DSS-induced C57BL/6 mice. Nevertheless, supplementation with Rc mitigated the increased inflammatory and damaged barrier function associated with DSS. Further evaluation revealed an activation of FXR signaling in Rc-treated LS174T, with FXR, BSEP, and SHP found to be upregulated. Furthermore, molecular docking indicated that there is a clear interaction between Rc and FXR, while Rc activated transcriptional expression of FXR in luciferase reporter gene assay. However, these reversal abilities of Rc were not observed in DSS-induced FXR-/- mice. Conclusion: Our findings suggest that Rc may ameliorate inflammation and barrier function in the intestine, which in turn leads to the attenuation of DSS-induced UC, in which Rc may potentially activate FXR signaling to protect the intestines from DSS-induced injury.

Molecular recognition of the interaction between ApoE and the TREM2 protein.

Alzheimer's disease (AD) is the most common type of dementia. The ε4 allele of the apolipoprotein E (ApoE) gene is the strongest known genetic risk factor for late-onset AD. Triggering receptor expressed on myeloid cells 2 (TREM2) is another important risk factor affecting the AD process after ApoE. Emerging evidence has identified TREM2 as a putative receptor for ApoE, raising the possibility that interactions between ApoE and TREM2 modulate the pathogenesis of AD. In this study, we performed molecular docking and molecular dynamics (MD) analyses to characterize the ApoE-TREM2 interaction and further investigated the effect of the major TREM2 disease-associated mutation (R47H) on the affinity of TREM2 for ApoE. The results indicate that the binding energy between ApoE and TREM2 occurs in an isoform-dependent manner with the following potency rank order: ApoE4 > ApoE3 > ApoE2. In addition, the R47H mutant reduced the interaction between ApoE and TREM2 protein, which may be attributed to decreased hydrogen-bonding interactions, hydrophobic interactions, and electrostatic forces between ApoE and TREM2. Our study analyzed the molecular pattern of the interactions between ApoE and TREM2 and how the variants affect these interactions based on in silico modeling, and the results might help to elucidate the interaction mechanism between ApoE and TREM2. Additional experimental studies will be needed to verify and explore the current findings.

Course of illness and outcomes in older COVID-19 patients treated with HFNC: a retrospective analysis.

Coronavirus disease-2019 (COVID-19) has rapidly spread worldwide and causes high mortality of elderly patients. High-flow nasal cannula therapy (HFNC) is an oxygen delivery method for severely ill patients. We retrospectively analyzed the course of illness and outcomes in 110 elderly COVID-19 patients (≥65 years) treated with HFNC from 6 hospitals. 38 patients received HFNC (200 mmHg < PaO2/FiO2 ≤ 300 mmHg, early HFNC group), and 72 patients received HFNC (100 mmHg < PaO2/FiO2 ≤ 200 mmHg, late HFNC group). There were no significant differences of sequential organ failure assessment (SOFA) scores and APECH II scores between early and late HFNC group on admission. Compared with the late HFNC group, patients in the early HFNC group had a lower likelihood of developing severe acute respiratory distress syndrome (ARDS), longer time from illness onset to severe ARDS and shorter duration of viral shedding after illness onset, as well as shorter lengths of ICU and hospital stay. 24 patients died during hospitalization, of whom 22 deaths (30.6%) were in the late HFNC group and 2 (5.3%) in the early HFNC group. The present study suggested that the outcomes were better in severely ill elderly patients with COVID-19 receiving early compared to late HFNC.

Acute fatty liver of pregnancy causes severe acute pancreatitis and stillborn fetus: A case report.

RATIONALE: Acutefatty liver of pregnancy (AFLP) is a potentially fatal obstetric emergency characterized by acute hepatic failure secondary to fatty infiltration. The resultant effects include coagulopathy, electrolyte abnormalities, and multisystem organ dysfunction. Pancreatitis typically develops after the onset of renal and hepatic dysfunction. Pancreatitis has been suggested as a poor prognostic indicator because it is associated with more adverse outcomes. PATIENT CONCERNS: A 29-year-old Chinese woman at 34.7 weeks pregnancy was admitted to hospital due to paroxysmal hypogastric pain and massive colporrhagia for 1 day. DIAGNOSIS: Laboratory tests revealed hepatic and renal impairment, coagulopathy. Thoracoabdominal computed tomography (CT) scanning showed pleural and peritoneal effusion, fatty liver, and pancreatitis. She was diagnosed with AFLP, severe acute pancreatitis (SAP), multiple organ dysfunction syndrome (MODS), and intrauterine fetal death. INTERVENTIONS: The patient was treated with blood component transfusions, plasma exchange combined with renal replacement therapy, antibiotic de-escalation, gastric and pancreatic secretion inhibitor, and enteral nutrition. OUTCOMES: After successful management, the patient was discharged without any complications on day 35 of admission. At 10 months follow-up, thoracoabdominal enhanced CT revealed was normal and laboratory tests revealed normal liver and kidney function. LESSONS: Once AFLP is highly suspected or confirmed, the pregnancy should be terminated in time and active symptomatic management should be given.

Normalized averaged range (nAR), a robust quantification method for MPIO-content.

Micron-sized paramagnetic iron oxide particles (MPIO) are commonly used as contrast agents in magnetic resonance imaging (MRI) that produce negative contrast enhancement, i.e. darkening, on T2*-weighted images. However, estimation and quantification of MPIO in vivo is still challenging. This limitation mainly arises from smearing and displacement of the negative contrast of the MPIO, so-called blooming, potentially leading to false-positive detection. Further, the bias field induced by the MR coils also hinders visualization and quantification of the MPIO. To mitigate these drawbacks, a positive contrast image can be generated, for example by using a frequency offset technique, which can significantly improve the accuracy of quantification methods. In this research, we introduce the normalized average range (nAR) as a new way to quantify the relative MPIO content within a study. The method compares the average value of test ROIs to that of a control ROI in range filtered images. The nAR can be used on both positive and negative contrast images. The nAR was tested on agar phantoms containing various MPIO concentrations, and on a rostral migration model for MPIO labeled stem cells in mice. The amount of MPIO was quantified for biased and unbiased data, and both for positive and negative contrast images. In addition, the presence of MPIOs in the olfactory bulb was verified by histology. The results show the nAR can indicate the presence and relative content of MPIO for both negative and positive images. However, the nAR showed slightly higher sensitivity in optimized positive contrast images compared to negative contrast images. In all cases, the bias field played a minor role in the quantification, making debiasing less of a concern. The dependency of the nAR values on the MPIO content in the ROI was further validated histologically. Thus, the nAR provides a robust and reliable tool for quantification of MPIO in mice.

Diffusion kurtosis imaging allows the early detection and longitudinal follow-up of amyloid-ß-induced pathology.

BACKGROUND: Alzheimer's disease (AD) is a progressive neurodegenerative disorder and the most common cause of dementia in the elderly population. In this study, we used the APP/PS1 transgenic mouse model to explore the feasibility of using diffusion kurtosis imaging (DKI) as a tool for the early detection of microstructural changes in the brain due to amyloid-ß (Aß) plaque deposition. METHODS: We longitudinally acquired DKI data of wild-type (WT) and APP/PS1 mice at 2, 4, 6 and 8 months of age, after which these mice were sacrificed for histological examination. Three additional cohorts of mice were also included at 2, 4 and 6 months of age to allow voxel-based co-registration between diffusion tensor and diffusion kurtosis  metrics and immunohistochemistry. RESULTS: Changes were observed in diffusion tensor (DT) and diffusion kurtosis (DK) metrics in many of the 23 regions of interest that were analysed. Mean and axial kurtosis were greatly increased owing to Aß-induced pathological changes in the motor cortex of APP/PS1 mice at 4, 6 and 8 months of age. Additionally, fractional anisotropy (FA) was decreased in APP/PS1 mice at these respective ages. Linear discriminant analysis of the motor cortex data indicated that combining diffusion tensor and diffusion kurtosis metrics permits improved separation of WT from APP/PS1 mice compared with either diffusion tensor or diffusion kurtosis metrics alone. We observed that mean kurtosis and FA are the critical metrics for a correct genotype classification. Furthermore, using a newly developed platform to co-register the in vivo diffusion-weighted magnetic resonance imaging with multiple 3D histological stacks, we found high correlations between DK metrics and anti-Aß (clone 4G8) antibody, glial fibrillary acidic protein, ionised calcium-binding adapter molecule 1 and myelin basic protein immunohistochemistry. Finally, we observed reduced FA in the septal nuclei of APP/PS1 mice at all ages investigated. The latter was at least partially also observed by voxel-based statistical parametric mapping, which showed significantly reduced FA in the septal nuclei, as well as in the corpus callosum, of 8-month-old APP/PS1 mice compared with WT mice. CONCLUSIONS: Our results indicate that DKI metrics hold tremendous potential for the early detection and longitudinal follow-up of Aß-induced pathology.

Interleukin-13 immune gene therapy prevents CNS inflammation and demyelination via alternative activation of microglia and macrophages.

Detrimental inflammatory responses in the central nervous system are a hallmark of various brain injuries and diseases. With this study we provide evidence that lentiviral vector-mediated expression of the immune-modulating cytokine interleukin 13 (IL-13) induces an alternative activation program in both microglia and macrophages conferring protection against severe oligodendrocyte loss and demyelination in the cuprizone mouse model for multiple sclerosis (MS). First, IL-13 mediated modulation of cuprizone induced lesions was monitored using T2 -weighted magnetic resonance imaging and magnetization transfer imaging, and further correlated with quantitative histological analyses for inflammatory cell influx, oligodendrocyte death, and demyelination. Second, following IL-13 immune gene therapy in cuprizone-treated eGFP+ bone marrow chimeric mice, we provide evidence that IL-13 directs the polarization of both brain-resident microglia and infiltrating macrophages towards an alternatively activated phenotype, thereby promoting the conversion of a pro-inflammatory environment toward an anti-inflammatory environment, as further evidenced by gene expression analyses. Finally, we show that IL-13 immune gene therapy is also able to limit lesion severity in a pre-existing inflammatory environment. In conclusion, these results highlight the potential of IL-13 to modulate microglia/macrophage responses and to improve disease outcome in a mouse model for MS. GLIA 2016;64:2181-2200.

Robust edge-directed interpolation of magnetic resonance images.

Image interpolation is intrinsically a severely under-determined inverse problem. Traditional non-adaptive interpolation methods do not account for local image statistics around the edges of image structures. In practice, this results in artifacts such as jagged edges, blurring and/or edge halos. To overcome this shortcoming, edge-directed interpolation has been introduced in different forms. One variant, new edge-directed interpolation (NEDI), has successfully exploited the 'geometric duality' that links the low-resolution image to its corresponding high-resolution image. It has been demonstrated that for scalar images, NEDI is able to produce better results than non-adaptive traditional methods, both visually and quantitatively. In this work, we return to the root of NEDI as a least-squares estimation method of neighborhood patterns and propose a robust scheme to improve it. The improvement is twofold: firstly, a robust least-squares technique is used to improve NEDI's performance to outliers and noise; secondly, the NEDI algorithm is extended with the recently proposed non-local mean estimation scheme. Moreover, the edge-directed concept is applied to the interpolation of multi-valued diffusion-weighted images. The framework is tested on phantom scalar images and real diffusion images, and is shown to achieve better results than the non-adaptive methods as well as NEDI, in terms of visual quality as well as quantitative measures.

Bias field reduction by localized Lloyd-Max quantization.

Bias field reduction is a common problem in medical imaging. A bias field usually manifests itself as a smooth intensity variation across the image. The resulting image inhomogeneity is a severe problem for posterior image processing and analysis techniques such as registration or segmentation. In this article, we present a novel debiasing technique based on localized Lloyd-Max quantization (LMQ). The local bias is modeled as a multiplicative field and is assumed to be slowly varying. The method is based on the assumption that the global, undegraded histogram is characterized by a limited number of gray values. The goal is then to find the discrete intensity values such that spreading those values according to the local bias field reproduces the global histogram as good as possible. We show that our method is capable of efficiently reducing (even strong) bias fields in 3D volumes.

Diffusion tensor image up-sampling: a registration-based approach.

Diffusion weighted images (DWI), from which the corresponding diffusion tensor images (DTI) are estimated, are commonly acquired with anisotropic discretizations. Traditional methods to up-sample diffusion weighted images generally rely on scene-based interpolation and do not exploit structural information from the images. In this study, a DTI up-sampling framework is presented that incorporates the underlying anatomical shape information by means of non-rigid inter-slice registration. A strategy is proposed to reorient the interpolated tensor in order to maintain its proper orientation. Tests on phantom as well as on real data sets show that the proposed method is able to produce better results compared to scene based interpolation methods in terms of the accuracy of DWI/DTI interpolation, especially when diffusion tensor orientation is taken into account.