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Purpose To develop a support vector machine (SVM) classifier using CT texture-based analysis in differentiating focal-type autoimmune pancreatitis (AIP) and pancreatic duct carcinoma (PD), and to assess the radiologists’ diagnostic performance with or without SVM. Materials and methods This retrospective study included 50 patients (20 patients with focal-type AIP and 30 patients with PD) who underwent dynamic contrast-enhanced CT. Sixty-two CT texture-based features were extracted from 2D images of the arterial and portal phase CTs. We conducted data compression and feature selections using principal component analysis (PCA) and produced the SVM classifier. Four readers participated in this observer performance study and the statistical significance of differences with and without the SVM was assessed by receiver operating characteristic (ROC) analysis. Results The SVM performance indicated a high performance in differentiating focal-type AIP and PD (AUC = 0.920). The AUC for all 4 readers increased significantly from 0.827 to 0.911 when using the SVM outputs (p = 0.010). The AUC for inexperienced readers increased significantly from 0.781 to 0.905 when using the SVM outputs (p = 0.310). The AUC for experienced readers increased from 0.875 to 0.912 when using the SVM outputs, however, there was no significant difference (p = 0.018). Conclusion The use of SVM classifier using CT texture-based features improved the diagnostic performance for differentiating focal-type AIP and PD on CT.

Complex networks inside the hippocampus could provide new insights into hippocampal abnormalities in various psychiatric disorders and dementia. However, evaluating intra-networks in the hippocampus using MRI is challenging. Here, we employed a high spatial resolution of conventional structural imaging and independent component analysis to investigate intra-networks structural covariance in the hippocampus. We extracted the intra-networks based on the intrinsic connectivity of each 0.9 mm isotropic voxel to every other voxel using a data-driven approach. With a total volume of 3 cc, the hippocampus contains 4115 voxels for a 0.9 mm isotropic voxel size or 375 voxels for a 2 mm isotropic voxel of high-resolution functional or diffusion tensor imaging. Therefore, the novel method presented in the current study could evaluate the hippocampal intra-networks in detail. Furthermore, we investigated the abnormality of the intra-networks in major depressive disorders. A total of 77 patients with first-episode drug-naïve major depressive disorder and 79 healthy subjects were recruited. The independent component analysis extracted seven intra-networks from hippocampal structural images, which were divided into four bilateral networks and three networks along the longitudinal axis. A significant difference was observed in the bilateral hippocampal tail network between patients with major depressive disorder and healthy subjects. In the logistic regression analysis, two bilateral networks were significant predictors of major depressive disorder, with an accuracy of 78.1%. In conclusion, we present a novel method for evaluating intra-networks in the hippocampus. One advantage of this method is that a detailed network can be estimated using conventional structural imaging. In addition, we found novel bilateral networks in the hippocampus that were disturbed in patients with major depressive disorders, and these bilateral networks could predict major depressive disorders.

Although tumor localization and 3,4-dihydroxy-6-18F-fluoro-l-phenylalanine (FDOPA) uptake may have an association, preferential tumor localization in relation to FDOPA uptake is yet to be investigated in lower-grade gliomas (LGGs). This study aimed to identify differences in the frequency of tumor localization between FDOPA hypometabolic and hypermetabolic LGGs using a probabilistic radiographic atlas. Fifty-one patients with newly diagnosed LGG (WHO grade II, 29; III, 22; isocitrate dehydrogenase wild-type, 21; mutant 1p19q non-codeleted,16; mutant codeleted, 14) who underwent FDOPA positron emission tomography (PET) were retrospectively selected. Semiautomated tumor segmentation on FLAIR was performed. Patients with LGGs were separated into two groups (FDOPA hypometabolic and hypermetabolic LGGs) according to the normalized maximum standardized uptake value of FDOPA PET (a threshold of the uptake in the striatum) within the segmented regions. Spatial normalization procedures to build a 3D MRI-based atlas using each segmented region were validated by an analysis of differential involvement statistical mapping. Superimposition of regions of interest showed a high number of hypometabolic LGGs localized in the frontal lobe, while a high number of hypermetabolic LGGs was localized in the insula, putamen, and temporal lobe. The statistical mapping revealed that hypometabolic LGGs occurred more frequently in the superior frontal gyrus (close to the supplementary motor area), while hypermetabolic LGGs occurred more frequently in the insula. Radiographic atlases revealed preferential frontal lobe localization for FDOPA hypometabolic LGGs, which may be associated with relatively early detection.

Purpose: To identify correlations of gliomas between 18F-fluorodihydroxyphenylalanine (FDOPA) uptake and physiological magnetic resonance imaging (MRI) including relative cerebral blood volume (rCBV) and apparent diffusion coefficient (ADC) with different molecular subtypes, and to evaluate their prognostic values. Methods: Sixty-eight treatment-naive glioma patients who underwent FDOPA positron emission tomography (PET) and physiological MRI were retrospectively selected (isocitrate dehydrogenase wild-type [IDHwt], 36; mutant 1p/19q non-codeleted [IDHm-non-codel], 16; mutant codeleted [IDHm-codel], 16). Fluid-attenuated inversion recovery hyperintense areas were segmented and used as regions-of-interest. For voxel-wise and patient-wise analyses, Pearson’s correlation coefficients (rvoxel-wise and rpatient-wise) between the normalized standardized uptake value (nSUV), rCBV, and ADC were evaluated. Cox regression analysis was performed to investigate the associations between the overall survival (OS) and rvoxel-wise, max/median nSUV, median CBV, or median ADC. Results: For IDHwt and IDHm-non-codel gliomas, nSUV demonstrated significant positive correlations with rCBV (rvoxel-wise = 0.25 and 0.31, and rpatient-wise = 0.50 and 0.70, respectively), and negative correlations with ADC (rvoxel-wise = −0.19 and −0.19, and rpatient-wise = −0.58 and −0.61, respectively) in both voxel-wise and patient-wise analyses. IDHm-codel gliomas only demonstrated a significant positive correlation between nSUV and ADC in voxel-wise analysis (rvoxel-wise = 0.18). In Cox regression analysis, only rvoxel-wise between nSUV and rCBV (hazard ratio [HR] = 28.82) or ADC (HR = 0.085) had significant associations with OS for IDHwt gliomas. Conclusion: IDHm-codel gliomas showed distinctive patterns of correlations between amino acid PET and physiological MRI. Stronger correlations of nSUV and rCBV or ADC may result in worse prognosis for IDHwt gliomas.

Objective Recently, a genome-wide association study successfully identified genetic variants associated with major depressive disorder (MDD). The study identified 17 independent single-nucleotide polymorphisms (SNPs) significantly associated with diagnosis of MDD. These SNPs were predicted to be enriched in genes that are expressed in the central nervous system and function in transcriptional regulation associated with neurodevelopment. The study aimed to investigate associations between 17 SNPs and brain morphometry using magnetic resonance imaging (MRI) in drug-naive patients with MDD and healthy controls (HCs). Methods Forty-seven patients with MDD and 42 HCs were included. All participants underwent T1-weighted structural MRI and genotyping. The genotype–diagnosis interactions associated with regional cortical thicknesses were evaluated using voxel-based morphometry for the 17 SNPs. Results Regarding rs301806, an SNP in the RERE genomic regions, we found a significant difference in a genotype effect in the right-lateral orbitofrontal and postcentral lobes between diagnosis groups. After testing every possible diagnostic comparison, the genotype–diagnosis interaction in these areas revealed that the cortical thickness reductions in the MDD group relative to those in the HC group were significantly larger in T/T individuals than in C-carrier ones. For the other SNPs, no brain area was noted where a genotype effect significantly differed between the two groups. Conclusions We found that a RERE gene SNP was associated with cortical thickness reductions in the right-lateral orbitofrontal and postcentral lobes in drug-naive patients with MDD. The effects of RERE gene polymorphism and gene–environment interactions may exist in brain structures of patients with MDD.

Purpose: Compared with healthy subjects (HS), patients with major depressive disorder (MDD) exhibit volume differences that affect the volume changes in several areas such as the limbic, cortical, subcortical, and white matter. Catechol-O-methyltransferase (COMT) is a methylation enzyme that catalyzes endogenous catecholamines. The Val158Met polymorphism of COMT has been reported to affect the dopamine (DA) levels, which plays an important role in psychiatric diseases. However, the relationships among both DA levels, COMT genotype, and brain morphology are complicated and controversial. In previous studies that investigated the hippocampal subfields, the greatest brain abnormalities in MDD patients were observed in Cornu Ammonis (CA)1 and the subiculum, followed by that in CA2-3. We have prospectively demonstrated the relationship between the single-nucleotide polymorphism of the Val158Met COMT gene (rs4680) and the hippocampal subfields in drug-naive MDD patients. Patients and methods: In this study, we compared 27 MDD patients and 42 HS who were divided into groups based on their COMT genotype. The effects of the diagnosis, genotype, and genotype-diagnosis interaction related to CA1 and the subiculum volumes, as well as the whole-brain cortical thickness, were evaluated by performing a FreeSurfer statistical analysis of high-resolution magnetic resonance imaging (MRI) findings. Results: The results revealed that there was a statistically significant interaction between the effects of diagnosis and genotype on the right subiculum (a component of the hippocampus). Conclusion: This Val158Met COMT polymorphism may influence the subiculum volume in drug-naive, first-episode MDD patients.

Understanding the neural correlates of the neurotic brain is important because neuroticism is a risk factor for the development of psychopathology. We examined the correlation between brain structural networks and neuroticism based on NEO Five-Factor Inventory (NEO-FFI) scores. Fifty-one healthy participants (female, n = 18; male, n = 33; mean age, 38.5 ± 11.7 years) underwent the NEO-FFI test and magnetic resonance imaging (MRI), including diffusion tensor imaging and 3D T1WI. Using MRI data, for each participant, we constructed whole-brain interregional connectivity matrices by deterministic tractography and calculated the graph theoretical network measures, including the characteristic path length, global clustering coefficient, small-worldness, and betweenness centrality (BET) in 83 brain regions from the Desikan-Killiany atlas with subcortical segmentation using FreeSurfer. In relation to the BET, neuroticism score had a negative correlation in the left isthmus cingulate cortex, left superior parietal, left superior temporal, right caudal middle frontal, and right entorhinal cortices, and a positive correlation in the bilateral frontal pole, left caudal anterior cingulate cortex, and left fusiform gyrus. No other measurements showed significant correlations. Our results imply that the brain regions related to neuroticism exist in various regions, and that the neuroticism trait is likely formed as a result of interactions among these regions. This work was supported by a Grant-in-Aid for Scientific Research on Innovative Areas (Comprehensive Brain Science Network) from the Ministry of Education, Science, Sports and Culture of Japan.

PurposeAlthough tumor localization and 3,4-dihydroxy-6-18F-fluoro-L-phenylalanine (FDOPA) uptake may have an association, preferential tumor localization in relation to FDOPA uptake is yet to be investigated in lower-grade gliomas (LGGs). This study aimed to identify differences in the frequency of tumor localization between FDOPA hypometabolic and hypermetabolic LGGs using a probabilistic radiographic atlas.MethodsFifty-one patients with newly diagnosed LGG (WHO grade II, 29; III, 22; isocitrate dehydrogenase wild-type, 21; mutant 1p19q non-codeleted ,16; mutant codeleted, 14) who underwent FDOPA positron emission tomography (PET) were retrospectively selected. Semiautomated tumor segmentation on FLAIR was performed. Patients with LGGs were separated into two groups (FDOPA hypometabolic and hypermetabolic LGGs) according to the normalized maximum standardized uptake value of FDOPA PET (a threshold of the uptake in the striatum) within the segmented regions. Spatial normalization procedures to build a 3D MRI-based atlas using each segmented region were validated by an analysis of differential involvement statistical mapping.ResultsSuperimposition of regions of interest showed a high number of hypometabolic LGGs localized in the frontal lobe, while a high number of hypermetabolic LGGs was localized in the insula, putamen, and temporal lobe. The statistical mapping revealed that hypometabolic LGGs occurred more frequently in the superior frontal gyrus (close to the supplementary motor area), while hypermetabolic LGGs occurred more frequently in the insula. ConclusionRadiographic atlases revealed preferential frontal lobe localization for FDOPA hypometabolic LGGs, which may be associated with relatively early detection.

PURPOSE: Although tumor localization and 3,4-dihydroxy-6-(18)F-fluoro-L-phenylalanine (FDOPA) uptake may have an association, preferential tumor localization in relation to FDOPA uptake is yet to be investigated in lower-grade gliomas (LGGs). This study aimed to identify differences in the frequency of tumor localization between FDOPA hypometabolic and hypermetabolic LGGs using a probabilistic radiographic atlas. METHODS: Fifty-one patients with newly diagnosed LGG (WHO grade II, 29; III, 22; isocitrate dehydrogenase wild-type, 21; mutant 1p19q non-codeleted,16; mutant codeleted, 14) who underwent FDOPA positron emission tomography (PET) were retrospectively selected. Semiautomated tumor segmentation on FLAIR was performed. Patients with LGGs were separated into two groups (FDOPA hypometabolic and hypermetabolic LGGs) according to the normalized maximum standardized uptake value of FDOPA PET (a threshold of the uptake in the striatum) within the segmented regions. Spatial normalization procedures to build a 3D MRI-based atlas using each segmented region were validated by an analysis of differential involvement statistical mapping. RESULTS: Superimposition of regions of interest showed a high number of hypometabolic LGGs localized in the frontal lobe, while a high number of hypermetabolic LGGs was localized in the insula, putamen, and temporal lobe. The statistical mapping revealed that hypometabolic LGGs occurred more frequently in the superior frontal gyrus (close to the supplementary motor area), while hypermetabolic LGGs occurred more frequently in the insula. CONCLUSION: Radiographic atlases revealed preferential frontal lobe localization for FDOPA hypometabolic LGGs, which may be associated with relatively early detection.

This study aims to investigate hippocampal subfield volumes in patients with hippocampal sclerosis (HS) without visually detectable MRI abnormalities and to determine the diagnostic accuracy using hippocampal subfield volumes. We examined 46 patients with unilateral HS who had a histopathological diagnosis, and 54 controls. The patients were divided into two groups; visually detectable HS (n = 26) and undetectable HS (n = 20) on MRI. The volumes of hippocampal subfield using FreeSurfer were compared among the three groups. Diagnostic accuracy was calculated as the AUC of ROC using cutoff values for each individual subfield. Compared with the controls, visually detectable HS showed significantly reduced volumes of all the hippocampal subfields and entire hippocampus, whereas visually undetectable HS showed significant atrophy only in the CA3 and hippocampus-amygdala-transition-area. To diagnose visually undetectable HS, the CA3 volumes had AUC of 0.719, which was higher than AUC of 0.614 based on the entire hippocampal volumes. Visually undetectable HS demonstrated volume reductions in the CA3. Further, the CA3 volumes was more useful to diagnose visually undetectable HS compared with the entire hippocampal volumes.

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To assess atrophy differences among brain regions and time-dependent changes after whole-brain radiation therapy (WBRT). Twenty patients with lung cancer who underwent both WBRT and chemotherapy (WBRT group) and 18 patients with lung cancer who underwent only chemotherapy (control group) were recruited. Three-dimensional T1WI were analyzed to calculate volume reduction ratio after WBRT in various brain structures. The volume reduction ratio of the hippocampus was compared among following 3 periods: 0–3, 4–7, and 8–11 months after WBRT. The volume reduction ratio of the hippocampus was significantly higher in the WBRT group than in the control group (p

Objective Recently, a genome-wide association study successfully identified genetic variants associated with major depressive disorder (MDD). The study identified 17 independent single-nucleotide polymorphisms (SNPs) significantly associated with diagnosis of MDD. These SNPs were predicted to be enriched in genes that are expressed in the central nervous system and function in transcriptional regulation associated with neurodevelopment. The study aimed to investigate associations between 17 SNPs and brain morphometry using magnetic resonance imaging (MRI) in drug-naïve patients with MDD and healthy controls (HCs). Methods Forty-seven patients with MDD and 42 HCs were included. All participants underwent T1-weighted structural MRI and genotyping. The genotype–diagnosis interactions associated with regional cortical thicknesses were evaluated using voxel-based morphometry for the 17 SNPs. Results Regarding rs301806, an SNP in the RERE genomic regions, we found a significant difference in a genotype effect in the right-lateral orbitofrontal and postcentral lobes between diagnosis groups. After testing every possible diagnostic comparison, the genotype–diagnosis interaction in these areas revealed that the cortical thickness reductions in the MDD group relative to those in the HC group were significantly larger in T/T individuals than in C-carrier ones. For the other SNPs, no brain area was noted where a genotype effect significantly differed between the two groups. Conclusions We found that a RERE gene SNP was associated with cortical thickness reductions in the right-lateral orbitofrontal and postcentral lobes in drug-naïve patients with MDD. The effects of RERE gene polymorphism and gene–environment interactions may exist in brain structures of patients with MDD.

To evaluate the potential of full-iterative reconstruction (IR) for improving image quality of the cystic artery on CT angiography and to assess observer performance. Thirty patients who underwent both liver dynamic CT and conventional angiography were included in this retrospective study. All CT data were reconstructed through filtered back projection (FBP), adaptive iterative dose reduction 3D (AIDR3D), and forward-projected, model-based, iterative reconstruction solution (FIRST), respectively. In objective study, we analyzed mean ΔCT numbers (the difference between the HU peak of the vessel and the background) and full-width at tenth-maximum (FWTM) of three parts of the cystic artery by profile curve method comparing the three reconstructions. Subjectively, visualization was evaluated using a four-point scale performed by two blinded observers. ANOVA was used for statistical analysis. In all parts of the cystic artery, the mean ΔCT number of FIRST was shown to be significantly better than that of FBP and AIDR3D (p

Purpose: Compared with healthy subjects (HS), patients with major depressive disorder (MDD) exhibit volume differences that affect the volume changes in several areas such as the limbic, cortical, subcortical, and white matter. Catechol-O-methyltransferase (COMT) is a methylation enzyme that catalyzes endogenous catecholamines. The Val158Met polymorphism of COMT has been reported to affect the dopamine (DA) levels, which plays an important role in psychiatric diseases. However, the relationships among both DA levels, COMT genotype, and brain morphology are complicated and controversial. In previous studies that investigated the hippocampal subfields, the greatest brain abnormalities in MDD patients were observed in Cornu Ammonis (CA)1 and the subiculum, followed by that in CA2-3. We have prospectively demonstrated the relationship between the single-nucleotide polymorphism of the Val158Met COMT gene (rs4680) and the hippocampal subfields in drug-naive MDD patients. Patients and methods: In this study, we compared 27 MDD patients and 42 HS who were divided into groups based on their COMT genotype. The effects of the diagnosis, genotype, and genotype–diagnosis interaction related to CA1 and the subiculum volumes, as well as the whole-brain cortical thickness, were evaluated by performing a FreeSurfer statistical analysis of high-resolution magnetic resonance imaging (MRI) findings. Results: The results revealed that there was a statistically significant interaction between the effects of diagnosis and genotype on the right subiculum (a component of the hippocampus). Conclusion: This Val158Met COMT polymorphism may influence the subiculum volume in drug-naive, first-episode MDD patients.

BackgroundHigher daytime cortisol levels because of a hyperactive hypothalamic–pituitary–adrenal axis have been reported in patients with major depressive disorder (MDD). The elevated glucocorticoids inhibit the proliferation of the oligodendrocytes that are responsible for myelinating the axons of white matter fibre tracts.AimsTo evaluate the relationship between white matter integrity and serum cortisol levels during a first depressive episode in drug-naive patients with MDD (MDD group) using a tract-based spatial statistics (TBSS) method.MethodThe MDD group (n= 29) and a healthy control group (n= 47) underwent diffusion tensor imaging (DTI) scans and an analysis was conducted using TBSS. Morning blood samples were obtained from both groups for cortisol measurement.ResultsCompared with the controls, the MDD group had significantly reduced fractional anisotropy values (PPConclusionsOur findings indicate that the elevated cortisol levels in the MDD group may injure the white matter integrity in the frontal–subcortical and frontal–limbic circuits.

Purpose: In multiple sclerosis (MS), a juxtacortical lesion at the border between the gray matter (GM) and subcortical white matter (WM) may often involve the GM. A recently developed, phase-weighted magnetic resonance imaging (MRI) technique “phase difference enhanced imaging (PADRE)” can delineate the GM and WM clearly due to the difference in myelin concentration. We evaluated whether PADRE is useful for the detection of GM involvement in the juxtacortical MS lesions. Methods: One neuroradiologist reviewed the conventional MRI in 13 MS patients and selected 48 juxtacortical lesions. At the first reading session with the conventional MRI alone (T2-weighted imaging, and two-dimensional and three-dimensional fluid-attenuated inversion recovery), two other neuroradiologists classified the lesions into three patterns according to their anatomical locations: (a) subcortical WM lesions involving the subcortical WM alone; (b) intracortical (IC) lesions involving the GM alone; (c) mixed GM/subcortical WM (mixed) lesions involving the both subcortical WM and GM. We defined the subcortical WM as a WM within a distance of 10 mm from inner edge of the GM. For the analyses, we excluded the white matter lesions further than 10 mm from inner edge of the GM. At the second reading session MRI and PADRE were available and the radiologists re-evaluated their prior classification. Results: At the first reading session, 27 lesions were classified as (a), 1 as (b), and 20 as (c). Therefore, a total of 21 lesions (44%) were judged to involve the GM. At the second reading session, the classification of 15 (31%) lesions changed; all 15 lesions were judged to involve the GM on the PADRE. Interobserver agreement (kappa value) was 0.84 for the first- and 0.95 for the second reading session. Conclusion: PADRE is useful for detecting GM involvement of the juxtacortical MS lesions.

The purpose of our study is to develop deep convolutional neural network (DCNN) for detecting hip fractures using CT and MRI as a gold standard, and to evaluate the diagnostic performance of 7 readers with and without DCNN.The study population consisted of 327 patients who underwent pelvic CT or MRI and were diagnosed with proximal femoral fractures. All radiographs were manually checked and annotated by radiologists referring to CT and MRI for selecting ROI. At first, a DCNN with the GoogLeNet model was trained by 302 cases. The remaining 25 cases and 25 control subjects were used for the observer performance study and for the testing of DCNN. Seven readers took part in this study. A continuous rating scale was used to record each observer's confidence level. Subsequently, each observer interpreted with the DCNN outputs and rated them again. The area under the curve (AUC) was used to compare the fracture detection.The average AUC of the 7 readers was 0.832. The AUC of DCNN alone was 0.905. The average AUC of the 7 readers with DCNN outputs was 0.876. The AUC of readers with DCNN output were higher than those without(p 0.05). The AUC of the 2 experienced readers with DCNN output exceeded the AUC of DCNN alone.For detecting the hip fractures on radiographs, DCNN developed using CT and MRI as a gold standard by radiologists improved the diagnostic performance including the experienced readers.

Background Although structural correlation network (SCN) analysis is an approach to evaluate brain networks, the neurobiological interpretation of SCNs is still problematic. Brain-derived neurotrophic factor (BDNF) is well-established as a representative protein related to neuronal differentiation, maturation, and survival. Since a valine-to-methionine substitution at codon 66 of the BDNF gene (BDNF Val66Met single nucleotide polymorphism (SNP)) is well-known to have effects on brain structure and function, we hypothesized that SCNs are affected by the BDNF Val66Met SNP. To gain insight into SCN analysis, we investigated potential differences between BDNF valine (Val) homozygotes and methionine (Met) carriers in the organization of their SCNs derived from inter-regional cortical thickness correlations. Methods Forty-nine healthy adult subjects (mean age = 41.1 years old) were divided into two groups according to their genotype (n: Val homozygotes = 16, Met carriers = 33). We obtained regional cortical thickness from their brain T1 weighted images. Based on the inter-regional cortical thickness correlations, we generated SCNs and used graph theoretical measures to assess differences between the two groups in terms of network integration, segregation, and modularity. Results The average local efficiency, a measure of network segregation, of BDNF Met carriers’ network was significantly higher than that of the Val homozygotes’ (permutation p-value = 0.002). Average shortest path lengths (a measure of integration), average local clustering coefficient (another measure of network segregation), small-worldness (a balance between integration and segregation), and modularity (a representative measure for modular architecture) were not significantly different between group (permutation p-values ≧ 0.01). Discussion and Conclusion Our results suggest that the BDNF Val66Met polymorphism may potentially influence the pattern of brain regional morphometric (cortical thickness) correlations. Comparing networks derived from inter-regional cortical thickness correlations, Met carrier SCNs have denser connections with neighbors and are more distant from random networks than Val homozygote networks. Thus, it may be necessary to consider potential effects of BDNF gene mutations in SCN analyses. This is the first study to demonstrate a difference between Val homozygotes and Met carriers in brain SCNs.

There has been a growing interest in the abnormality of networks across the brain in major depressive disorder (MDD). We aimed to investigate the structural covariance networks in patients with first-episode and drug-naïve MDD using structural imaging. A total of 77 patients with first-episode and drug-naïve MDD and 79 healthy subjects (HS) were recruited, from whom high-resolution T1-weighted images were analysed. Incident component analysis was used to calculate the brain networks based on grey matter volume covariance. There were significant differences in salience network, medial temporal lobe network, default mode network and central executive network between MDD and HS (p 0.05). Further, the disturbance of medial temporal lobe network was significantly correlated with the severity of depressive symptoms (p 0.05). In conclusion, we found a novel abnormality in the brain network in the medial temporal lobe primarily involving the hippocampus and parahippocampal gyrus in patients with first-episode and treatment-naïve MDD.

Recently, accumulated evidence has indicated a role of inflammation in the pathogenesis of major depressive disorder (MDD). Therefore, we evaluated the relationship between white matter integrity and serum cytokine levels during the first depressive episode in drug-naive MDD patients, using a tract-based spatial statistics (TBSS) method. A total of 35 drug-naive MDD patients with a first depressive episode and 35 healthy subjects (HS) underwent diffusion tensor imaging, and an analysis was conducted using TBSS. We measured serum cytokine levels (interleukin [IL]-1β, IL-6, interferon-γ, and tumor necrosis factor-α). Fractional anisotropy (FA) values of the bilateral inferior fronto-occipital fasciculus (IFOF) and genu of the corpus callosum in MDD patients were decreased significantly to the HS (p < 0.05 with family-wise error [FWE] correction) and were significantly inversely correlated with the IL-1β levels (p < 0.05, with FWE correction). No regions showed a correlation between FA values and other serum cytokine levels. Our results suggested that the microstructural changes in IFOF and genu of the corpus callosum are associated with the high IL-1β levels in the early stage of MDD.

Vascular endothelial growth factor (VEGF) is involved in the development of major depressive disorder (MDD). Recently, a genome-wide association study has revealed that four VEGF-related single nucleotide polymorphisms (SNPs) (i.e., rs4416670, rs6921438, rs6993770 and rs10738760) were independently associated with circulating VEGF levels. The current study investigated the relationship between brain volume and these four SNPs in first-episode drug-naive MDD patients. A total of 38 first-episode drug-naive MDD patients and 39 healthy subjects (HS) were recruited and underwent high-resolution T1-weighted imaging. Blood samples were collected from all the participants for serum VEGF assays and VEGF-related SNPs genotyping. Genotype–diagnosis interactions related to whole-brain cortical thickness and hippocampal subfield volumes were evaluated for the four SNPs. The results revealed a genotype–diagnosis interaction only for rs6921438 (i.e., the MDD patients and HS with the G/G genotype versus the MDD patients and HS with A-carrier genotype) in the subiculum of the left hippocampus (p

There is a growing body of evidence to support the involvement of proinflammatory cytokines in the pathophysiology of depression; however, no previous studies have examined the relationship between cytokines and the brain morphology of patients with major depressive disorder (MDD). We therefore evaluated the relationship between serum cytokine levels and cortical thinning during the first depressive episode in drug-naïve patients with MDD. We measured the serum cytokine levels (IL-1β, IL-6, IFN-γ, and TNFα), and whole-brain cortical thickness and hippocampal subfield volumes on brain magnetic resonance imaging (MRI) using surface-based morphometry in 40 patients with MDD and 47 healthy volunteers (controls). Only the serum IL-6 level was significantly higher in patients with MDD than in controls. The prefrontal cortex (PFC) thickness was significantly reduced in patients with MDD, and showed a significant inverse correlation with the serum IL-6 level. Although high serum IL-6 levels were correlated with reduced left subiculum and right CA1, CA3, CA4, GC-DG, subiculum, and whole hippocampus volumes, the presence or absence of MDD had no effect on the volume of any hippocampal subfields. Our results suggest that IL-6 may play a key role in the morphological changes in the PFC during the early stage of MDD.

Objective In major depressive disorder (MDD) patients, higher morning cortisol levels due to a hyperactive hypothalamic–pituitary–adrenal (HPA) axis have been reported. The aim of the present study was to evaluate the relationship between cortical thinning and the serum cortisol levels during the first depressive episode in drug-naive MDD patients using an automated surface-based morphometry (SBM) method. Methods The institutional review board approved this prospective study. MR imaging data were obtained using a 3T scanner by a three-dimensional fast-spoiled gradient recalled acquisition with steady state (3D-FSPGR). Thirty drug-naive patients with MDD and 41 age- and gender-matched healthy subjects (controls) were enrolled. We then used the SBM method (Freesurfer) to generate cortical thickness maps, and measured the cortical thickness in each subject. Morning blood samples were drawn from all participants for cortisol measurements. Results We found the serum cortisol levels were significantly higher in the MDD patients than in the controls. The MDD patients manifested significant thinning of the left lateral orbitofrontal cortex compared with the controls. There was a significant negative linear correlation between the thickness of the left lateral orbitofrontal cortex and the serum cortisol levels in the MDD patients. Conclusions In the early stage of MDD, the thickness of the lateral orbitofrontal cortex was significantly reduced, and also showed a significant inverse correlation with the serum cortisol levels. Since the lateral orbitofrontal cortex contains a high concentration of glucocorticoid receptor, glucocorticoid receptor-mediated signaling transductions could contribute to neurotoxicity, which might occur when there are high cortisol levels in patients with MDD.

To evaluate whether quantitative susceptibility mapping (QSM) can be employed to detect abnormalities within normal-appearing basal ganglia on conventional MRI in patients with neuropsychiatric systemic lupus erythematosus (NPSLE). For 33 SLE patients (13 NPSLE and 20 non-NPSLE patients) and 23 age/sex-matched controls, two radiologists independently measured the mean QSM and R2* values in various brain structures that appeared to be normal on conventional MR images. These values in each brain structure were compared among the two SLE groups and controls. Regarding the putamen, the NPSLE patients showed significantly higher QSM values than the non-NPSLE patients and controls (p

Background Earlier studies implicated norepinephrine transporter (NET) gene (SLC6A2) polymorphisms in the etiology of major depressive disorder (MDD). Recently, two single nucleotide SLC6A2 polymorphisms, G1287A in exon 9 and T-182C in the promoter region, were found to be associated with MDD in different populations. We investigated the relationship between the brain volume and these two polymorphisms of the SLC6A2 in MDD patients. Methods We obtained 3D high-resolution T1-weighted images of 30 first-episode MDD patients and 48 age- and sex-matched healthy subjects (HS). All were divided into 4 groups based on polymorphism of either the G1287A or the T-182C genotype. VBM analysis examined the effects of diagnosis, genotype, and genotype-diagnosis interactions. Results Diagnosis effects on the brain morphology were found in the left superior temporal cortex. No significant genotype effects were found in the T-182C and the G1287A. A significant genotype (G1287A)–diagnosis interaction was found in the left dorsolateral prefrontal cortex. No significant genotype (T-182C)–diagnosis interaction effects were observed in any brain region. Conclusions In MDD patients there seems to be a relationship between the volume of the dorsolateral prefrontal cortex and polymorphism of the SLC6A2 G1287A gene.

In major depressive disorder (MDD) patients, higher morning cortisol levels due to a hyperactive hypothalamic-pituitary-adrenal (HPA) axis have been reported. The aim of the present study was to evaluate the relationship between cortical thinning and the serum cortisol levels during the first depressive episode in drug-naïve MDD patients using an automated surface-based morphometry (SBM) method.The institutional review board approved this prospective study. MR imaging data were obtained using a 3T scanner by a three-dimensional fast-spoiled gradient recalled acquisition with steady state (3D-FSPGR). Thirty drug-naïve patients with MDD and 41 age- and gender-matched healthy subjects (controls) were enrolled. We then used the SBM method (Freesurfer) to generate cortical thickness maps, and measured the cortical thickness in each subject. Morning blood samples were drawn from all participants for cortisol measurements.We found the serum cortisol levels were significantly higher in the MDD patients than in the controls. The MDD patients manifested significant thinning of the left lateral orbitofrontal cortex compared with the controls. There was a significant negative linear correlation between the thickness of the left lateral orbitofrontal cortex and the serum cortisol levels in the MDD patients.In the early stage of MDD, the thickness of the lateral orbitofrontal cortex was significantly reduced, and also showed a significant inverse correlation with the serum cortisol levels. Since the lateral orbitofrontal cortex contains a high concentration of glucocorticoid receptor, glucocorticoid receptor-mediated signaling transductions could contribute to neurotoxicity, which might occur when there are high cortisol levels in patients with MDD.

We experienced a rare case of gallbladder metastasis from renal cell carcinoma (RCC). Ultrasound, computed tomographic, and magnetic resonance findings showed a hypervascular polypoid mass and correlated well with histopathologic findings. The mass showed high intensity on diffusion-weighted images, and the apparent diffusion coefficient was relatively low. These imaging findings are considered characteristic and may assist preoperative diagnosis in patients with history of RCC.

The aim of this study was to assess the susceptibility change in medial and lateral globus pallidus (GPm and GPl) related to age separately, using quantitative susceptibility mapping (QSM) and to determine whether QSM can depict GPm in Parkinson's disease (PD) patients.QSM was performed in 19 PD patients and in 41 normal control (NC) subjects. First, we quantitatively analysed age-related changes in QSM value in NC for GPl and GPm by a manual region of interest (ROI) technique. Then, in PD patients and age-matched NC subjects, we evaluated the depiction of GPm on QSM images qualitatively.In NC, the QSM value within GPl significantly increased gradually with age (r = 0.32, p = 0.04), whereas it did not change with age in GPm. The average QSM value was significantly larger for GPl than for GPm (205 vs 191, p 0.05). In both PD patients and age-matched NC, the depiction of GPm on QSM images was good in most cases (87 %, 33 of 38 sides in PD patients) mainly because of the differences in susceptibility between GPm and GPl.The QSM value in GPl increases gradually with age, which allows for the identification of GPm in elderly PD subjects.

Kenji Hayashi,1 Reiji Yoshimura,1 Shingo Kakeda,2 Taro Kishi,3 Osamu Abe,4 Wakako Umene-Nakano,1 Asuka Katsuki,1 Hikaru Hori,1 Atsuko Ikenouchi-Sugita,1 Keita Watanabe,2 Satoru Ide,2 Issei Ueda,2 Junji Moriya,2 Nakao Iwata,3 Yukunori Korogi,2 Marek Kubicki,5 Jun Nakamura1 1Department of Psychiatry, 2Department of Radiology, University of Occupational and Environmental Health, Kitakyushu, Japan; 3Department of Psychiatry, Fujita Health University, Toyoake, Japan; 4Department of Radiology, Nihon University School of Medicine, Tokyo, Japan; 5Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA Abstract: We investigated the association between the Val158Met polymorphism of the catechol-O-methyltransferase (COMT) gene, the Val66Met polymorphism of the brain-derived neurotrophic factor (BDNF) gene, and white matter changes in patients with major depressive disorder (MDD) and healthy subjects using diffusion tensor imaging (DTI). We studied 30 patients with MDD (17 males and 13 females, with mean age ± standard deviation [SD] =44±12 years) and 30 sex- and age-matched healthy controls (17 males and 13 females, aged 44±13 years). Using DTI analysis with a tract-based spatial statistics (TBSS) approach, we investigated the differences in fractional anisotropy, radial diffusivity, and axial diffusivity distribution among the three groups (patients with the COMT gene Val158Met, those with the BDNF gene Val66Met, and the healthy subjects). In a voxel-wise-based group comparison, we found significant decreases in fractional anisotropy and axial diffusivity within the temporal lobe white matter in the Met-carriers with MDD compared with the controls (P

The brain-derived neurotrophic factor (BDNF) relates to basic neuronal functions, such as cell survival, axonal outgrowth, and dendritic growth. The Val66Met polymorphism of the BDNF gene may affect genetic susceptibility to major depressive disorder (MDD). We prospectively investigated the relationship between the Val66Met BDNF genotype and voxel-based morphometry (VBM) findings for first episode and drug-naive MDD patients and healthy subjects (HS). Participants comprised 38 MDD patients and 42 age- and sex-matched HS were divided into groups based on their BDNF genotype. The effects of diagnosis and genotype, as well as the genotype–diagnosis interaction, in relation to brain morphology were evaluated using a voxel-by-voxel statistical analysis of high-resolution magnetic resonance imaging (MRI) findings. Among the Met-carriers, the volume of the left middle frontal gyrus (composition of the prefrontal cortex [PFC]) was significantly smaller for MDD patients than for the HS, i.e., there was a significant genotype–diagnosis interaction effect on brain morphology noted in the left PFC. The BDNF polymorphism was associated with atrophy of the PFC in MDD patients, which suggests that the BDNF Val66Met polymorphism may play an important role in the pathogenesis of early stages of MDD.

In the present study, we aimed to investigate the difference in white matter between smokers and nonsmokers. In addition, we examined relationships between white matter integrity and nicotine dependence parameters in smoking subjects. Nineteen male smokers were enrolled in this study. Eighteen age-matched non-smokers with no current or past psychiatric history were included as controls. Diffusion tensor imaging scans were performed, and the analysis was conducted using a tract-based special statistics approach. Compared with nonsmokers, smokers exhibited a significant decrease in fractional anisotropy (FA) throughout the whole corpus callosum. There were no significant differences in radial diffusivity or axial diffusivity between the two groups. There was a significant negative correlation between FA in the whole corpus callosum and the amount of tobacco use (cigarettes/day; R = − 0.580, p = 0.023). These results suggest that the corpus callosum may be one of the key areas influenced by chronic smoking.