Noninvasive Magnetic Resonance Imaging Measures of Glymphatic System Activity.

The comprehension of the glymphatic system, a postulated mechanism responsible for the removal of interstitial solutes within the central nervous system (CNS), has witnessed substantial progress recently. While direct measurement techniques involving fluorescence and contrast agent tracers have demonstrated success in animal studies, their application in humans is invasive and presents challenges. Hence, exploring alternative noninvasive approaches that enable glymphatic research in humans is imperative. This review primarily focuses on several noninvasive magnetic resonance imaging (MRI) techniques, encompassing perivascular space (PVS) imaging, diffusion tensor image analysis along the PVS, arterial spin labeling, chemical exchange saturation transfer, and intravoxel incoherent motion. These methodologies provide valuable insights into the dynamics of interstitial fluid, water permeability across the blood-brain barrier, and cerebrospinal fluid flow within the cerebral parenchyma. Furthermore, the review elucidates the underlying concept and clinical applications of these noninvasive MRI techniques, highlighting their strengths and limitations. It addresses concerns about the relationship between glymphatic system activity and pathological alterations, emphasizing the necessity for further studies to establish correlations between noninvasive MRI measurements and pathological findings. Additionally, the challenges associated with conducting multisite studies, such as variability in MRI systems and acquisition parameters, are addressed, with a suggestion for the use of harmonization methods, such as the combined association test (COMBAT), to enhance standardization and statistical power. Current research gaps and future directions in noninvasive MRI techniques for assessing the glymphatic system are discussed, emphasizing the need for larger sample sizes, harmonization studies, and combined approaches. In conclusion, this review provides invaluable insights into the application of noninvasive MRI methods for monitoring glymphatic system activity in the CNS. It highlights their potential in advancing our understanding of the glymphatic system, facilitating clinical applications, and paving the way for future research endeavors in this field. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 5.

Deep Learning-Driven Transformation: A Novel Approach for Mitigating Batch Effects in Diffusion MRI Beyond Traditional Harmonization.

BACKGROUND: "Batch effect" in MR images, due to vendor-specific features, MR machine generations, and imaging parameters, challenges image quality and hinders deep learning (DL) model generalizability. PURPOSE: We aim to develop a DL model using contrast adjustment and super-resolution to reduce diffusion-weighted images (DWIs) diversity across magnetic field strengths and imaging parameters. STUDY TYPE: Retrospective. SUBJECTS: The DL model was built using an open dataset from one individual. The MR machine identification model was trained and validated on a dataset of 1134 adults (54% females, 46% males), with 1050 subjects showing no DWI abnormalities and 84 with conditions like stroke and tumors. The 21,000 images were divided into 80% for training, 20% for validation, and 3500 for testing. FIELD STRENGTH/SEQUENCE: Seven MR scanners from four manufacturers with 1.5 T and 3 T magnetic field strengths. DWIs were acquired using spin-echo sequences and high-resolution T2WIs using the T2-SPACE sequence. ASSESSMENT: An experienced, board-certified radiologist evaluated the effectiveness of restoring high-resolution T2WI and harmonizing diverse DWI with metrics such as PSNR and SSIM, and the texture and frequency attributes were further analyzed using gray-level co-occurrence matrix and 1-dimensional power spectral density. The model's impact on machine-specific characteristics was gauged through the performance metrics of a ResNet-50 model. Comprehensive statistical tests were employed for statistical robustness, including McNemar's test and the Dice index. RESULTS: Our DL protocol reduced DWI contrast and resolution variation. ResNet-50 model's accuracy decreased from 0.9443 to 0.5786, precision from 0.9442 to 0.6494, recall from 0.9443 to 0.5786, and F1 score from 0.9438 to 0.5587. The t-SNE visualization indicated more consistent image features across multiple MR devices. Autoencoder halved learning iterations; Dice coefficient >0.74 confirmed signal reproducibility in 84 lesions. CONCLUSION: This study presents a DL strategy to mitigate batch effects in diffusion MR images, improving their quality and generalizability. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 1.

Feasibility of Quantitative MRI Using 3D-QALAS for Discriminating Immunohistochemical Status in Invasive Ductal Carcinoma of the Breast.

BACKGROUND: Two-dimensional synthetic MRI of the breast has limited spatial coverage. Three-dimensional (3D) synthetic MRI could provide volumetric quantitative parameters that may reflect the immunohistochemical (IHC) status in invasive ductal carcinoma (IDC) of the breast. PURPOSE: To evaluate the feasibility of 3D synthetic MRI using an interleaved Look-Locker acquisition sequence with a T2 preparation pulse (QALAS) for discriminating the IHC status, including hormone receptor (HR), human epidermal growth factor receptor 2 (HER 2), and Ki-67 expression in IDC. STUDY TYPE: Prospective observational study. POPULATION: A total of 33 females with IDC of the breast (mean, 52.3 years). FIELD STRENGTH/SEQUENCE: A 3-T, 3D-QALAS gradient-echo and fat-suppressed T1-weighted 3D fast spoiled gradient-echo sequences. ASSESSMENT: Two radiologists semiautomatically delineated 3D regions of interest (ROIs) of the whole tumors on the dynamic MRI that was registered to the synthetic T1-weighted images acquired from 3D-QALAS. The mean T1 and T2 were measured for each IDC. STATISTICAL TESTS: Intraclass correlation coefficient for assessing interobserver agreement. Mann-Whitney U test to determine the relationship between the mean T1 or T2 and the IHC status. Multivariate logistic regression analysis followed by receiver operating characteristics (ROC) analysis for discriminating IHC status. A P value <0.05 was considered statistically significant. RESULTS: The interobserver agreement was good to excellent. There was a significant difference in the mean T1 between HR-positive and HR-negative lesions, while the mean T2 value differed between HR-positive and HR-negative lesions, between the triple-negative and HR-positive or HER2-positive lesions, and between the Ki-67 level > 14% and ≤ 14%. Multivariate analysis showed that the mean T2 was higher in HR-negative IDC than in HR-positive IDC. ROC analysis revealed that the mean T2 was predictive for discriminating HR status, triple-negative status, and Ki-67 level. DATA CONCLUSION: 3D synthetic MRI using QALAS may be useful for discriminating IHC status in IDC of the breast. EVIDENCE LEVEL: 1. TECHNICAL EFFICACY: Stage 2.

Feasibility of the fat-suppression image-subtraction method using deep learning for abnormality detection on knee MRI.

Purpose: To evaluate the feasibility of using a deep learning (DL) model to generate fat-suppression images and detect abnormalities on knee magnetic resonance imaging (MRI) through the fat-suppression image-subtraction method. Material and methods: A total of 45 knee MRI studies in patients with knee disorders and 12 knee MRI studies in healthy volunteers were enrolled. The DL model was developed using 2-dimensional convolutional neural networks for generating fat-suppression images and subtracting generated fat-suppression images without any abnormal findings from those with normal/abnormal findings and detecting/classifying abnormalities on knee MRI. The image qualities of the generated fat-suppression images and subtraction-images were assessed. The accuracy, average precision, average recall, F-measure, sensitivity, and area under the receiver operator characteristic curve (AUROC) of DL for each abnormality were calculated. Results: A total of 2472 image datasets, each consisting of one slice of original T1WI, original intermediate-weighted images, generated fat-suppression (FS)-intermediate-weighted images without any abnormal findings, generated FS-intermediate-weighted images with normal/abnormal findings, and subtraction images between the generated FS-intermediate-weighted images at the same cross-section, were created. The generated fat-suppression images were of adequate image quality. Of the 2472 subtraction-images, 2203 (89.1%) were judged to be of adequate image quality. The accuracies for overall abnormalities, anterior cruciate ligament, bone marrow, cartilage, meniscus, and others were 89.5-95.1%. The average precision, average recall, and F-measure were 73.4-90.6%, 77.5-89.4%, and 78.4-89.4%, respectively. The sensitivity was 57.4-90.5%. The AUROCs were 0.910-0.979. Conclusions: The DL model was able to generate fat-suppression images of sufficient quality to detect abnormalities on knee MRI through the fat-suppression image-subtraction method.

Radiomics with 3-dimensional magnetic resonance fingerprinting: influence of dictionary design on repeatability and reproducibility of radiomic features.

OBJECTIVES: We aimed to investigate the influence of magnetic resonance fingerprinting (MRF) dictionary design on radiomic features using in vivo human brain scans. METHODS: Scan-rescans of three-dimensional MRF and conventional T1-weighted imaging were performed on 21 healthy volunteers (9 males and 12 females; mean age, 41.3 ± 14.6 years; age range, 22-72 years). Five patients with multiple sclerosis (3 males and 2 females; mean age, 41.2 ± 7.3 years; age range, 32-53 years) were also included. MRF data were reconstructed using various dictionaries with different step sizes. First- and second-order radiomic features were extracted from each dataset. Intra-dictionary repeatability and inter-dictionary reproducibility were evaluated using intraclass correlation coefficients (ICCs). Features with ICCs > 0.90 were considered acceptable. Relative changes were calculated to assess inter-dictionary biases. RESULTS: The overall scan-rescan ICCs of MRF-based radiomics ranged from 0.86 to 0.95, depending on dictionary step size. No significant differences were observed in the overall scan-rescan repeatability of MRF-based radiomic features and conventional T1-weighted imaging (p = 1.00). Intra-dictionary repeatability was insensitive to dictionary step size differences. MRF-based radiomic features varied among dictionaries (overall ICC for inter-dictionary reproducibility, 0.62-0.99), especially when step sizes were large. First-order and gray level co-occurrence matrix features were the most reproducible feature classes among different step size dictionaries. T1 map-derived radiomic features provided higher repeatability and reproducibility among dictionaries than those obtained with T2 maps. CONCLUSION: MRF-based radiomic features are highly repeatable in various dictionary step sizes. Caution is warranted when performing MRF-based radiomics using datasets containing maps generated from different dictionaries. KEY POINTS: • MRF-based radiomic features are highly repeatable in various dictionary step sizes. • Use of different MRF dictionaries may result in variable radiomic features, even when the same MRF acquisition data are used. • Caution is needed when performing radiomic analysis using data reconstructed from different dictionaries.

Multiple sclerosis plaques may undergo continuous myelin degradation: a cross-sectional study with myelin and axon-related quantitative magnetic resonance imaging metrics.

PURPOSE: We hypothesize that myelin is more susceptible to damage over time than axons. We investigated the association between the estimated duration from the onset of multiple sclerosis (MS) plaques and myelin- and axon-related quantitative synthetic magnetic resonance imaging (SyMRI) and neurite orientation dispersion and density imaging (NODDI) metrics. METHODS: We analyzed 31 patients with MS with 73 newly appeared plaques. Simple linear regression analysis was performed to assess the association between the estimated duration from the onset of plaques and quantitative MRI metrics. These metrics included the myelin volume fraction (MVF), axon volume fraction, and g-ratio in plaque and normal-appearing white matter. RESULTS: MS plaques with a longer estimated duration from onset were significantly correlated with a lower MVF (slope = - 0.0070, R2 = 0.0970), higher g-ratio (slope = 0.0078, R2 = 0.0842) (all P values < 0.05). CONCLUSION: These results suggested that myelin in plaques undergoes continuous damage, more so than axons. Myelin imaging with SyMRI and NODDI may be useful for the quantitative assessment of temporal changes in MS plaques.

Connectome analysis of male world-class gymnasts using probabilistic multishell, multitissue constrained spherical deconvolution tracking.

In athletes, long-term intensive training has been shown to increase unparalleled athletic ability and might induce brain plasticity. We evaluated the structural connectome of world-class gymnasts (WCGs), as mapped by diffusion-weighted magnetic resonance imaging probabilistic tractography and a multishell, multitissue constrained spherical deconvolution method to increase the precision of tractography at the tissue interfaces. The connectome was mapped in 10 Japanese male WCGs and in 10 age-matched male controls. Network-based statistic identified subnetworks with increased connectivity density in WCGs, involving the sensorimotor, default mode, attentional, visual, and limbic areas. It also revealed a significant association between the structural connectivity of some brain structures with functions closely related to the gymnastic skills and the D-score, which is used as an index of the gymnasts' specific physical abilities for each apparatus. Furthermore, graph theory analysis demonstrated the characteristics of brain anatomical topology in the WCGs. They displayed significantly increased global connectivity strength with decreased characteristic path length at the global level and higher nodal strength and degree in the sensorimotor, default mode, attention, and limbic/subcortical areas at the local level as compared with controls. Together, these findings extend the current understanding of neural mechanisms that distinguish WCGs from controls and suggest brain anatomical network plasticity in WCGs resulting from long-term intensive training. Future studies should assess the contribution of genetic or early-life environmental factors in the brain network organization of WCGs. Furthermore, the indices of brain topology (i.e., connection density and graph theory indices) could become markers for the objective evaluation of gymnastic performance.

Neurocognitive and psychiatric disorders-related axonal degeneration in Parkinson's disease.

Neurocognitive and psychiatric disorders have significant consequences for quality of life in patients with Parkinson's disease (PD). In the current study, we evaluated microstructural white matter (WM) alterations associated with neurocognitive and psychiatric disorders in PD using neurite orientation dispersion and density imaging (NODDI) and linked independent component analysis (LICA). The indices of NODDI were compared between 20 and 19 patients with PD with and without neurocognitive and psychiatric disorders, respectively, and 25 healthy controls using tract-based spatial statistics and tract-of-interest analyses. LICA was applied to model inter-subject variability across measures. A widespread reduction in axonal density (indexed by intracellular volume fraction [ICVF]) was demonstrated in PD patients with and without neurocognitive and psychiatric disorders, as compared with healthy controls. Compared with patients without neurocognitive and psychiatric disorders, patients with neurocognitive and psychiatric disorders exhibited more extensive (posterior predominant) decreases in axonal density. Using LICA, ICVF demonstrated the highest contribution (59% weight) to the main effects of diagnosis that reflected widespread decreases in axonal density. These findings suggest that axonal loss is a major factor underlying WM pathology related to neurocognitive and psychiatric disorders in PD, whereas patients with neurocognitive and psychiatric disorders had broader axonal pathology, as compared with those without. LICA suggested that the ICVF can be used as a useful biomarker of microstructural changes in the WM related to neurocognitive and psychiatric disorders in PD.

Scan-rescan and inter-vendor reproducibility of neurite orientation dispersion and density imaging metrics.

PURPOSE: The reproducibility of neurite orientation dispersion and density imaging (NODDI) metrics in the human brain has not been explored across different magnetic resonance (MR) scanners from different vendors. This study aimed to evaluate the scan-rescan and inter-vendor reproducibility of NODDI metrics in white and gray matter of healthy subjects using two 3-T MR scanners from two vendors. METHODS: Ten healthy subjects (7 males; mean age 30 ± 7 years, range 23-37 years) were included in the study. Whole-brain diffusion-weighted imaging was performed with b-values of 1000 and 2000 s/mm2 using two 3-T MR scanners from two different vendors. Automatic extraction of the region of interest was performed to obtain NODDI metrics for whole and localized areas of white and gray matter. The coefficient of variation (CoV) and intraclass correlation coefficient (ICC) were calculated to assess the scan-rescan and inter-vendor reproducibilities of NODDI metrics. RESULTS: The scan-rescan and inter-vendor reproducibility of NODDI metrics (intracellular volume fraction and orientation dispersion index) were comparable with those of diffusion tensor imaging (DTI) metrics. However, the inter-vendor reproducibilities of NODDI (CoV = 2.3-14%) were lower than the scan-rescan reproducibility (CoV: scanner A = 0.8-3.8%; scanner B = 0.8-2.6%). Compared with the finding of DTI metrics, the reproducibility of NODDI metrics was lower in white matter and higher in gray matter. CONCLUSION: The lower inter-vendor reproducibility of NODDI in some brain regions indicates that data acquired from different MRI scanners should be carefully interpreted.

Evaluation of white matter microstructure in patients with Parkinson's disease using microscopic fractional anisotropy.

PURPOSE: Micro fractional anisotropy (µFA) is more accurate than conventional fractional anisotropy (FA) for assessing microscopic tissue properties and can overcome limitations related to crossing white matter fibres. We compared µFA and FA for evaluating white matter changes in patients with Parkinson's disease (PD). METHODS: We compared FA and µFA measures between 25 patients with PD and 25 age- and gender-matched healthy controls using tract-based spatial statistics (TBSS) analysis. We also examined potential correlations between changes, revealed by conventional FA or µFA, and disease duration or Unified Parkinson's Disease Rating Scale (UPDRS)-III scores. RESULTS: Compared with healthy controls, patients with PD had significantly reduced µFA values, mainly in the anterior corona radiata (ACR). In the PD group, µFA values (primarily those from the ACR) were significantly negatively correlated with UPDRS-III motor scores. No significant changes or correlations with disease duration or UPDRS-III scores with tissue properties were detected using conventional FA. CONCLUSION: µFA can evaluate microstructural changes that occur during white matter degeneration in patients with PD and may overcome a key limitation of FA.

3D quantitative synthetic MRI-derived cortical thickness and subcortical brain volumes: Scan-rescan repeatability and comparison with conventional T1 -weighted images.

BACKGROUND: Previous quantitative synthetic MRI of the brain has been solely performed in 2D. PURPOSE: To evaluate the feasibility of the recently developed sequence 3D-QALAS for brain cortical thickness and volumetric analysis. STUDY TYPE: Reproducibility/repeatability study. SUBJECTS: Twenty-one healthy volunteers (35.6 ± 13.8 years). FIELD STRENGTH/SEQUENCE: 3D T1 -weighted fast spoiled gradient recalled echo (FSPGR) sequence was performed once, and 3D-QALAS sequence was performed twice with a 3T scanner. ASSESSMENT: FreeSurfer and FIRST were used to measure cortical thickness and volume of subcortical structures, respectively. Agreement with FSPGR and scan-rescan repeatability were evaluated for 3D-QALAS. STATISTICAL TESTS: Percent relative difference and intraclass correlation coefficient (ICC) were used to assess reproducibility and scan-rescan repeatability of the 3D-QALAS sequence-derived measurements. RESULTS: Percent relative difference compared with FSPGR in cortical thickness of the whole cortex was 3.1%, and 89% of the regional areas showed less than 10% relative difference in cortical thickness. The mean ICC across all regions was 0.65, and 74% of the structures showed substantial to almost perfect agreement. For volumes of subcortical structures, the median percent relative differences were lower than 10% across all subcortical structures, except for the accumbens area, and all structures showed ICCs of substantial to almost perfect agreement. For the scan-rescan test, percent relative difference in cortical thickness of the whole cortex was 2.3%, and 97% of the regional areas showed less than 10% relative difference in cortical thickness. The mean ICC across all regions was 0.73, and 80% showed substantial to almost perfect agreement. For volumes of subcortical structures, relative differences were less than 10% across all subcortical structures except for the accumbens area, and all structures showed ICCs of substantial to almost perfect agreement. DATA CONCLUSION: 3D-QALAS could be reliably used for measuring cortical thickness and subcortical volumes in most brain regions. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;50:1834-1842.

White matter alterations in adult with autism spectrum disorder evaluated using diffusion kurtosis imaging.

PURPOSE: Autism spectrum disorder (ASD) is related to impairment in various white matter (WM) pathways. Utility of the recently developed two-compartment model of diffusion kurtosis imaging (DKI) to analyse axial diffusivity of WM is restricted by several limitations. The present study aims to validate the utility of model-free DKI in the evaluation of WM alterations in ASD and analyse the potential relationship between DKI-evident WM alterations and personality scales. METHODS: Overall, 15 participants with ASD and 15 neurotypical (NT) controls were scanned on a 3 T magnetic resonance (MR) scanner, and scores for autism quotient (AQ), systemising quotient (SQ) and empathising quotient (EQ) were obtained for both groups. Multishell diffusion-weighted MR data were acquired using two b-values (1000 and 2000 s/mm2). Differences in mean kurtosis (MK), radial kurtosis (RK) and axial kurtosis (AK) between the groups were evaluated using tract-based spatial statistics (TBSS). Finally, the relationships between the kurtosis indices and personality quotients were examined. RESULTS: The ASD group demonstrated significantly lower AK in the body and splenium of corpus callosum than the NT group; however, no other significant differences were identified. Negative correlations were found between AK and AQ or SQ, predominantly in WM areas related to social-emotional processing such as uncinate fasciculus, inferior fronto-occipital fasciculus, and inferior and superior longitudinal fasciculi. CONCLUSIONS: Model-free DKI and its indices may represent a novel, objective method for detecting the disease severity and WM alterations in patients with ASD.

Convolutional neural network-based segmentation can help in assessing the substantia nigra in neuromelanin MRI.

PURPOSE: This study aimed to evaluate the accuracy and diagnostic test performance of the U-net-based segmentation method in neuromelanin magnetic resonance imaging (NM-MRI) compared to the established manual segmentation method for Parkinson's disease (PD) diagnosis. METHODS: NM-MRI datasets from two different 3T-scanners were used: a "principal dataset" with 122 participants and an "external validation dataset" with 24 participants, including 62 and 12 PD patients, respectively. Two radiologists performed SNpc manual segmentation. Inter-reader precision was determined using Dice coefficients. The U-net was trained with manual segmentation as ground truth and Dice coefficients used to measure accuracy. Training and validation steps were performed on the principal dataset using a 4-fold cross-validation method. We tested the U-net on the external validation dataset. SNpc hyperintense areas were estimated from U-net and manual segmentation masks, replicating a previously validated thresholding method, and their diagnostic test performances for PD determined. RESULTS: For SNpc segmentation, U-net accuracy was comparable to inter-reader precision in the principal dataset (Dice coefficient: U-net, 0.83 ± 0.04; inter-reader, 0.83 ± 0.04), but lower in external validation dataset (Dice coefficient: U-net, 079 ± 0.04; inter-reader, 0.85 ± 0.03). Diagnostic test performances for PD were comparable between U-net and manual segmentation methods in both principal (area under the receiver operating characteristic curve: U-net, 0.950; manual, 0.948) and external (U-net, 0.944; manual, 0.931) datasets. CONCLUSION: U-net segmentation provided relatively high accuracy in the evaluation of the SNpc in NM-MRI and yielded diagnostic performance comparable to that of the established manual method.

An updated review on pathophysiology and management of burning mouth syndrome with endocrinological, psychological and neuropathic perspectives.

Burning mouth syndrome (BMS) is a chronic oro-facial pain disorder of unknown cause. It is more common in peri- and post-menopausal women, and sex hormone dysregulation is believed to be an important causative factor. Psychosocial events often trigger or exacerbate symptoms, and persons with BMS appear to be predisposed towards anxiety and depression. Atrophy of small nerve fibres in the tongue epithelium has been reported, and potential neuropathic mechanisms for BMS are now widely investigated. Historically, BMS was thought to comprise endocrinological, psychosocial and neuropathic components. Neuroprotective steroids and glial cell line-derived neurotrophic factor family ligands may have pivotal roles in the peripheral mechanisms associated with atrophy of small nerve fibres. Denervation of chorda tympani nerve fibres that innervate fungiform buds leads to alternative trigeminal innervation, which results in dysgeusia and burning pain when eating hot foods. With regard to the central mechanism of BMS, depletion of neuroprotective steroids alters the brain network-related mood and pain modulation. Peripheral mechanistic studies support the use of topical clonazepam and capsaicin for the management of BMS, and some evidence supports the use of cognitive behavioural therapy. Hormone replacement therapy may address the causes of BMS, although adverse effects prevent its use as a first-line treatment. Selective serotonin reuptake inhibitors (SSRIs) and serotonin and noradrenaline reuptake inhibitors (SNRIs) may have important benefits, and well-designed controlled studies are expected. Other treatment options to be investigated include brain stimulation and TSPO (translocator protein 18 kDa) ligands.

[Efficacy and Safety of Gefitinib as First-Line Chemotherapy for Elderly Patients with Advanced Non-Small Cell Lung Cancer(NSCLC)].

Epidermalgrowth factor receptor tyrosine kinase inhibitor(EGFR-TKI)is the first choice for the treatment of EGFR mutation- positive advanced non-small cell lung cancer(NSCLC). There have been few reports on the efficacy and safety of gefitinib in elderly patients with EGFR mutation-positive advanced NSCLC. We retrospectively assessed the efficacy and safety of gefitinib as first-line chemotherapy in 22 patients with advanced NSCLC aged 75 years or older and who were treated with gefitinib. The response rate was 81.8%, and the disease controlrate was 95.5%. The median progression-free survivaltime was 14.2 months, and the median survivaltime was 30.7 months. The common adverse events were skin toxicities(50.0%), liver dysfunction(18.2%), and diarrhea(18.2%). The dose of gefitinib was reduced in 36.3% of the patients, and the treatment of gefitinib was discontinued in 18.2% of the patients. Gefitinib is effective and safe for elderly patients with advanced NSCLC.

A lysosomal protein negatively regulates surface T cell antigen receptor expression by promoting CD3zeta-chain degradation.

Modulation of surface T cell antigen receptor (TCR) expression is an important mechanism for the regulation of immune responses and the prevention of T cell hyperactivation and autoimmunity. The TCR is rapidly internalized after antigen stimulation and then degraded in lysosomes. However, few of the molecules involved in this process have been identified. We demonstrate that the lysosomal protein LAPTM5 negatively regulated surface TCR expression by specifically interacting with the invariant signal-transducing CD3zeta chain and promoting its degradation without affecting other CD3 proteins, CD3epsilon, CD3delta, or CD3gamma. TCR downmodulation required the polyproline-tyrosine motifs and the ubiquitin-interacting motif of LAPTM5. LAPTM5 deficiency resulted in elevated TCR expression on both CD4(+)CD8(+) thymocytes and spleen T cells after CD3 stimulation, as well as enhanced T cell responses in vitro and in vivo. These results identify a lysosomal protein important for CD3zeta degradation and illustrate a unique mechanism for the control of surface TCR expression and T cell activation.

Altered structural connectivity of pain-related brain network in burning mouth syndrome-investigation by graph analysis of probabilistic tractography.

PURPOSE: Burning mouth syndrome (BMS) is a chronic intraoral pain syndrome featuring idiopathic oral pain and burning discomfort despite clinically normal oral mucosa. The etiology of chronic pain syndrome is unclear, but preliminary neuroimaging research has suggested the alteration of volume, metabolism, blood flow, and diffusion at multiple brain regions. According to the neuromatrix theory of Melzack, pain sense is generated in the brain by the network of multiple pain-related brain regions. Therefore, the alteration of pain-related network is also assumed as an etiology of chronic pain. In this study, we investigated the brain network of BMS brain by using probabilistic tractography and graph analysis. METHODS: Fourteen BMS patients and 14 age-matched healthy controls underwent 1.5T MRI. Structural connectivity was calculated in 83 anatomically defined regions with probabilistic tractography of 60-axis diffusion tensor imaging and 3D T1-weighted imaging. Graph theory network analysis was used to evaluate the brain network at local and global connectivity. RESULTS: In BMS brain, a significant difference of local brain connectivity was recognized at the bilateral rostral anterior cingulate cortex, right medial orbitofrontal cortex, and left pars orbitalis which belong to the medial pain system; however, no significant difference was recognized at the lateral system including the somatic sensory cortex. A strengthened connection of the anterior cingulate cortex and medial prefrontal cortex with the basal ganglia, thalamus, and brain stem was revealed. CONCLUSION: Structural brain network analysis revealed the alteration of the medial system of the pain-related brain network in chronic pain syndrome.

[A CASE OF SPINAL TUBERCULOSIS WITH NEUROPATHY AMELIORATED BY DRAINING A TUBERCULOUS ILIOPSOAS ABSCESS WITHOUT SPINAL SURGERY].

A 75-year-old woman was referred to our hospital after a health check-up disclosed abnormal shadows in the bilateral lungs. The patient was admitted to our hospital after being diagnosed with pulmonary tuberculosis. A physical examination showed a mass in the left inguinal area. Enhanced computed tomography revealed that the tuberculosis involved several regions including the lumber vertebrae, iliopsoas muscles, and left inguinal area. A therapeutic regimen consisting of INH, RFP, EB, and PZA was begun. Neuropathy in the lower extremities and dysuria indicated a spinal lesion, and spinal surgery was considered. However, the patient's history indicated that these symptoms were likely due to an iliopsoas abscess rather than a spinal lesion. This hypothesis was confirmed when the patient's symptoms improved with no sequelae after the abscess was drained. Our case demonstrates that spinal lesions as well as iliopsoas abscesses can cause neuropathy, and underscores the importance of obtaining a patient's history to correctly diagnose the disease and determine the appropriate treatment options.

Up-regulation of NaV1.7 sodium channels expression by tumor necrosis factor-α in cultured bovine adrenal chromaffin cells and rat dorsal root ganglion neurons.

BACKGROUND: Tumor necrosis factor-α (TNF-α) is not only a key regulator of inflammatory response but also an important pain modulator. TNF-α enhances both tetrodotoxin-sensitive (TTX-S) and tetrodotoxin-resistant Na channel currents in dorsal root ganglion (DRG) neurons. However, it remains unknown whether TNF-α affects the function and expression of the TTX-S NaV1.7 Na channel, which plays crucial roles in pain generation. METHODS: We used cultured bovine adrenal chromaffin cells expressing the NaV1.7 Na channel isoform and compared them with cultured rat DRG neurons. The expression of TNF receptor 1 and 2 (TNFR1 and TNFR2) in adrenal chromaffin cells was studied by Semiquantitative reverse transcription-polymerase chain reaction. The effects of TNF-α on the expression of NaV1.7 were examined with reverse transcription-polymerase chain reaction and Western blot analysis. Results were expressed as mean ± SEM. RESULTS: TNFR1 and TNFR2 were expressed in adrenal chromaffin cells, as well as reported in DRG neurons. TNF-α up-regulated NaV1.7 mRNA by 132% ± 9% (N = 5, P = 0.004) in adrenal chromaffin cells, as well as 117% ± 2% (N = 5, P < 0.0001) in DRG neurons. Western blot analysis showed that TNF-α increased NaV1.7 protein up to 166% ± 24% (N = 5, corrected P < 0.0001) in adrenal chromaffin cells, concentration- and time-dependently. CONCLUSIONS: TNF-α up-regulated NaV1.7 mRNA in both adrenal chromaffin cells and DRG neurons. In addition, TNF-α up-regulated the protein expression of the TTX-S NaV1.7 channel in adrenal chromaffin cells. Our findings may contribute to understanding the peripheral nociceptive mechanism of TNF-α.

[A case of antitubercular drug-induced toxic epidermal necrosis in a systemic lupus erythematosus patient during treatment for pulmonary tuberculosis].

A 48-year-old woman, who had been suffering from systemic lupus erythematosus for one year and receiving steroid therapy, was admitted to our hospital because of pulmonary tuberculosis. The tuberculosis was treated with INH, RFP, EB, and PZA after having doubled the dose of steroid, but terminated three weeks later due to the appearance of erythema exsudativum multiforme. Treatment was resumed with PZA, SM, and LVFX after resolution of the eruption. However, the addition of INH to the regimen provoked a recurrence of the eruption, which progressed rapidly to toxic epidermal necrolysis (TEN). Steroid pulse therapy stopped progression of the TEN, and treatment for tuberculosis was resumed. Although the choice of drug was rendered difficult by other adverse reactions, the patient was able to complete her tuberculosis treatment with RFP, EB, and TH. INH was most likely to be the offending agent in this case. Eruptions induced by antitubercular drugs are often seen, but there are few reports of severe toxic epidermal necrolysis.