Glymphatic system impairment in sleep disruption: diffusion tensor image analysis along the perivascular space (DTI-ALPS).

PURPOSE: This study aimed to evaluate the relationship between sleep quality as assessed using the Pittsburgh Sleep Quality Index (PSQI) and the index of diffusivity along the perivascular space (ALPS index), a possible indirect indicator of glymphatic system activity. MATERIALS AND METHODS: This study included the diffusion magnetic resonance imaging (MRI) data of 317 people with sleep disruption and 515 healthy controls (HCs) from the Human Connectome Project (WU-MINN HCP 1200). The ALPS index was calculated automatically based on diffusion tensor image analysis (DTI)-ALPS of diffusion MRI. The ALPS index of the sleep disruption and HC groups was compared using general linear model (GLM) analysis with covariates, such as age, sex, level of education, and intracranial volume. In addition, to confirm the relationship between sleep quality and the ALPS index in the sleep disruption group as well as evaluate the effect of each PSQI component on the ALPS index, correlation analyses between the ALPS indices and PSQI scores of all the components and between the ALPS index and each PSQI component was performed using GLM analysis with the abovementioned covariates, respectively. RESULTS: The ALPS index was significantly lower in the sleep disruption group than in the HC group (p = 0.001). Moreover, the ALPS indices showed significant negative correlations with the PSQI scores of all the components (false discovery rate [FDR]-corrected p < 0.001). Two significant negative correlations were also found between the ALPS index and PSQI component 2 (sleep latency, FDR-corrected p < 0.001) and 6 (the use of sleep medication, FDR-corrected p < 0.001). CONCLUSION: Our findings suggest that glymphatic system impairment contributes to sleep disruption in young adults.

Automation of a Rule-based Workflow to Estimate Age from Brain MR Imaging of Infants and Children Up to 2 Years Old Using Stacked Deep Learning.

PURPOSE: Myelination-related MR signal changes in white matter are helpful for assessing normal development in infants and children. A rule-based myelination evaluation workflow regarding signal changes on T1-weighted images (T1WIs) and T2-weighted images (T2WIs) has been widely used in radiology. This study aimed to simulate a rule-based workflow using a stacked deep learning model and evaluate age estimation accuracy. METHODS: The age estimation system involved two stacked neural networks: a target network-to extract five myelination-related images from the whole brain, and an age estimation network from extracted T1- and T2WIs separately. A dataset was constructed from 119 children aged below 2 years with two MRI systems. A four-fold cross-validation method was adopted. The correlation coefficient (CC), mean absolute error (MAE), and root mean squared error (RMSE) of the corrected chronological age of full-term birth, as well as the mean difference and the upper and lower limits of 95% agreement, were measured. Generalization performance was assessed using datasets acquired from different MR images. Age estimation was performed in Sturge-Weber syndrome (SWS) cases. RESULTS: There was a strong correlation between estimated age and corrected chronological age (MAE: 0.98 months; RMSE: 1.27 months; and CC: 0.99). The mean difference and standard deviation (SD) were -0.15 and 1.26, respectively, and the upper and lower limits of 95% agreement were 2.33 and -2.63 months. Regarding generalization performance, the performance values on the external dataset were MAE of 1.85 months, RMSE of 2.59 months, and CC of 0.93. Among 13 SWS cases, 7 exceeded the limits of 95% agreement, and a proportional bias of age estimation based on myelination acceleration was exhibited below 12 months of age (P = 0.03). CONCLUSION: Stacked deep learning models automated the rule-based workflow in radiology and achieved highly accurate age estimation in infants and children up to 2 years of age.

Simultaneous fMRI-EEG-DTI recording of MMN in patients with schizophrenia.

Functional magnetic resonance imaging (fMRI), electroencephalogram (EEG), and diffusion tensor imaging (DTI) recording have complementary spatiotemporal resolution limitations but can be powerful methods when used together to enable both functional and anatomical modeling, with each neuroimaging procedure used to maximum advantage. We recorded EEGs during event-related fMRI followed by DTI in 15 healthy volunteers and 12 patients with schizophrenia using an omission mismatch negativity (MMN) paradigm. Blood oxygenation level-dependent (BOLD) signal changes were calculated in a region of interest (ROI) analysis, and fractional anisotropy (FA) in the white matter fibers related to each area was compared between groups using tract-specific analysis. Patients with schizophrenia had reduced BOLD activity in the left middle temporal gyrus, and BOLD activity in the right insula and right parahippocampal gyrus significantly correlated with positive symptoms on the Positive and Negative Syndrome Scale (PANSS) and hostility subscores. BOLD activation of Heschl's gyri also correlated with the limbic system, including the insula. FA values in the left anterior cingulate cortex (ACC) significantly correlated with changes in the BOLD signal in the right superior temporal gyrus (STG), and FA values in the right ACC significantly correlated with PANSS scores. This is the first study to examine MMN using simultaneous fMRI, EEG, and DTI recording in patients with schizophrenia to investigate the potential implications of abnormalities in the ACC and limbic system, including the insula and parahippocampal gyrus, as well as the STG. Structural changes in the ACC during schizophrenia may represent part of the neural basis for the observed MMN deficits. The deficits seen in the feedback/feedforward connections between the prefrontal cortex and STG modulated by the ACC and insula may specifically contribute to impaired MMN generation and clinical manifestations.

Detection of residual metastatic tumor in the brain following Gamma Knife radiosurgery using a single or a series of magnetic resonance imaging scans: An autopsy study.

The aim of the present study was to investigate the usefulness of magnetic resonance image (MRI) for the detection of residual tumors following Gamma Knife radiosurgery (GKR) for brain metastases based on autopsy cases. The study investigated two hypotheses: i) Whether a single MRI may detect the existence of a tumor; and ii) whether a series of MRIs may detect the existence of a tumor. The study is a retrospective case series in a single institution. A total of 11 brain metastases in 6 patients were treated with GKR between 2002 and 2011. Histopathological specimens from autopsy were compared with reconstructed follow-up MRIs. The maximum diameters of the lesions on MRI series were measured, and the size changes classified. The primary sites in the patients were the kidneys (n=2), lung (n=1), breast (n=1) and colon (n=1), as well as 1 adenocarcinoma of unknown origin. The median prescribed dose for radiosurgery was 20 Gy (range, 18-20 Gy), and median time interval between GKR and autopsy was 10 months (range, 1.6-20 months). The pathological outcomes included 7 remissions and 4 failures. Enhanced areas on gadolinium-enhanced MRI contained various components: Viable tumor cells, tumor necrosis, hemorrhage, inflammation and vessels. Regarding the first hypothesis, it was impossible to distinguish pathological failure from remission with a single MRI scan due to the presence of various components. Conversely, in treatment response (remission or failure), on time-volume curves of MRI scans were in agreement with pathological findings, with the exception of progressive disease in the acute phase (0-3 months). Thus, regarding the second hypothesis, time-volume curves were useful for predicting treatment responses. In conclusion, it was difficult to predict treatment response using a single MRI, and a series of MRI scans were required to detect the existence of a tumor.

A clinical model to identify patients with high-risk plaque by coronary computed tomography angiography.

OBJECTIVES: Current clinical models predict the pre-test probability of obstructive coronary artery disease, but these models do not predict the presence of high-risk plaques. Thus the objective of this study was to propose a model to predict high-risk plaque assessed by coronary computed tomography (CT) angiography. METHODS: This study was a retrospective cross-sectional study. A clinical model was derived from 2392 patients and verified by 733 patients who underwent coronary CT suspected of coronary artery disease. High-risk plaque was defined as a plaque with positive remodeling (remodeling index>1.1), low attenuation (<30Hounsfield units) and napkin-ring sign. The risk score was calculated from the following 6 variables with a maximum of 24 points: age, sex, hemoglobin A1c, systolic blood pressure, high-density lipoprotein and smoking status. RESULTS: The proportion of patients with high-risk plaque was 11% and 17% in the derivation and validation cohort, respectively. The area under the receiver operation characteristic curve was 0.71 (95% confidence interval (CI): 0.68 to 0.74) in the derivation cohort and 0.75 (95% CI: 0.70 to 0.79) in the validation cohort. The frequency of high-risk plaques was 4% in the low-risk group (≤8 points) while it was 53% in the high-risk group (≥17 points) of the derivation cohort. CONCLUSIONS: We propose a scoring system to detect high-risk plaque assessed by coronary CT. Patients in the high-risk group have a high prevalence of high-risk plaque and might benefit from lipid lowering therapy.

Improving the diagnostic performance of the real world coronary computed tomography angiography including uninterpretable segments.

OBJECTIVES: The purpose was to investigate the diagnostic performance of coronary computed tomography angiography (CTA) when non-calcified uninterpretable segments were determined as either obstructive or patent. We also investigated the factors that could improve the diagnosis of CTA. METHODS: A total of 268 patients without known coronary artery disease who were clinically indicated for coronary angiogram (CAG) within 50days of coronary CTA were retrospectively included. The diagnostic performance of CTA was assessed with CAG as a reference, whereas stenosis of ≥50% was considered obstructive. We compared the results when non-calcified uninterpretable segments were determined as obstructive or patent. Coronary risk factors as well as contrast medium arrival time adjusted by heart rate (CATHR) were investigated for improvement of CTA diagnosis. RESULTS: Area under the receiver operating characteristic curve (AUC) improved when uninterpretable segments were determined as patent rather than obstructive (0.79 vs 0.73, p=0.02). Multivariate analysis showed that CATHR was a predictor of CAG stenosis (odds ratio 1.13, p=0.046) while other risk factors were not. Adding CATHR further improved the AUC to 0.82 (p=0.003). The accuracy, sensitivity, specificity, positive predictive value and negative predictive value of CTA stenosis (uninterpretable segments as obstructive) were 72%, 99%, 32%, 68% and 95%. The values were 78%, 89%, 61%, 77% and 80% when CATHR was added and uninterpretable segments determined as patent. CONCLUSIONS: The diagnostic performance of coronary CTA improved when non-calcified uninterpretable segments were determined as patent rather than obstructive. Adding CATHR could further improve the specificity.

Depressive symptoms and neuroanatomical structures in community-dwelling women: A combined voxel-based morphometry and diffusion tensor imaging study with tract-based spatial statistics.

Depressive symptoms, even at a subclinical level, have been associated with structural brain abnormalities. However, previous studies have used regions of interest or small sample sizes, limiting the ability to generalize the results. In this study, we examined neuroanatomical structures of both gray matter and white matter associated with depressive symptoms across the whole brain in a large sample. A total of 810 community-dwelling adult participants underwent measurement of depressive symptoms with the Center for Epidemiologic Studies Depression Scale (CES-D). The participants were not demented and had no neurological or psychiatric history. To examine the gray and white matter volume, we used structural MRI scans and voxel-based morphometry (VBM); to examine the white matter integrity, we used diffusion tensor imaging with tract-based spatial statistics (TBSS). In female participants, VBM revealed a negative correlation between bilateral anterior cingulate gray matter volume and the CES-D score. TBSS showed a CES-D-related decrease in fractional anisotropy and increase in radial and mean diffusivity in several white matter regions, including the right anterior cingulum. In male participants, there was no significant correlation between gray or white matter volume or white matter integrity and the CES-D score. Our results indicate that the reduction in gray matter volume and differences in white matter integrity in specific brain regions, including the anterior cingulate, are associated with depressive symptoms in women.

Anterior cingulate abnormality as a neural correlate of mismatch negativity in schizophrenia.

BACKGROUND: Limbic circuitry, especially the anterior cingulate gyrus, has been implicated in the pathophysiology and cognitive changes of schizophrenia. Previous diffusion tensor imaging studies have demonstrated that the integrity of the anterior cingulum (AC) is abnormal in schizophrenia. However, the relationship between the abnormal AC tract integrity and the pathophysiology of schizophrenia has not been fully studied. METHODS: We performed a voxelwise group comparison of white matter fractional anisotropy (FA) by using tract-based spatial statistics in 9 patients with schizophrenia and 9 matched controls. We then measured FA specifically in the AC by using a tract-specific measurement. The latency and amplitude of the mismatch negativity (MMN) were also evaluated in all subjects. RESULTS: In patients with schizophrenia, tract-based spatial statistics showed a reduction in FA in broad white matter areas, including the bilateral AC, compared with controls. Tract-specific measurements confirmed the specific reduction of FA in the region of the bilateral AC. The decreased FA in the AC was correlated with prolonged MMN latency in the patient group. CONCLUSION: Our study of AC structure and electrophysiological changes in schizophrenia suggest that the disruption of limbic-cortical structural networks may be part of the neural basis underlying the changes in MMN in schizophrenia.

Structural brain abnormalities in women with subclinical depression, as revealed by voxel-based morphometry and diffusion tensor imaging.

BACKGROUND: Brain structural changes accompany major depressive disorder, but whether subclinical depression is accompanied by similar changes in brain volume and white matter integrity is unknown. By using voxel-based morphometry (VBM) of the gray matter and tract-specific analysis based on diffusion tensor imaging (DTI) of the white matter, we explored the extent to which abnormalities could be identified in specific brain structures of healthy adults with subclinical depression. METHODS: The subjects were 21 community-dwelling adults with subclinical depression, as measured by their Center for Epidemiologic Studies Depression Scale (CES-D) scores. They were not demented and had no neurological or psychiatric history. We collected brain magnetic resonance images of the patients and of 21 matched control subjects, and we used VBM to analyze the differences in regional gray matter volume between the two groups. Moreover, we examined the white matter integrity by using tract-specific analysis based on the gray matter volume changes revealed by VBM. RESULTS: VBM revealed that the volumes of both anterior cingulate gyri and the right rectal gyrus were smaller in subclinically depressed women than in control women. Calculation of DTI measures in the anterior cingulum bundle revealed a positive correlation between CES-D scale score and radial diffusivity in the right anterior cingulum in subclinically depressed women. LIMITATIONS: The small sample size limits the stability of the reported findings. CONCLUSIONS: Gray matter volume reduction and white matter integrity change in specific frontal brain regions may be associated with depressive symptoms in women, even at a subclinical level.

Emotion recognition from stimuli in different sensory modalities in post-encephalitic patients.

Emotion recognition from facial and non-facial stimuli was investigated in two post-encephalitic patients a few months after the onset of the disease. One patient who had a lesion relatively restricted to the amygdala and hippocampus experienced difficulty in recognizing fear from facial expressions. In contrast, the other patient who had a lesion that extended beyond the amygdala experienced difficulty in recognizing fear from non-facial (prosodic and written verbal) stimuli. We showed that impairment of emotion recognition was evident within a short duration after encephalitis and that recognizing emotion from different sensory modalities relies partly on integration of different neural systems.

Patient setup error and day-to-day esophageal motion error analyzed by cone-beam computed tomography in radiation therapy.

UNLABELLED: Little has been reported on the errors of setup and daily organ motion that occur during radiation therapy (RT) for esophageal cancer. The purpose of this paper was to determine the margins of esophageal motion during RT. METHODS AND MATERIALS: The shift of the esophagus was analyzed in 20 consecutive patients treated with RT for esophageal cancer from November 2007. CT images for RT planning were used as the primary image series. Computed tomography (CT) images were acquired using an Elekta Synergy System, equipped with a kilovoltage-based cone-beam CT (CBCT) unit. The subsequent CBCT image series used for daily RT setup were compared with the primary image series to analyze esophageal motion. CBCT was performed before treatment sessions a total of 10 times in each patient twice a week. The outer esophageal wall was contoured on the CBCT images of all 200 sets. RESULTS: In the 200 sets of CBCT images, the mean (absolute) +/- standard deviation (SD) of setup errors were 2 +/- 2 mm (max, 8 mm) in the lateral direction, 4 +/- 3 mm (max, 11 mm) in the longitudinal direction, and 4 +/- 3 mm (max, 13 mm) in the vertical direction. Additionally, the mean +/- SD values of daily esophageal motion comparing the CBCT with RT planning CT were 5 +/- 3 mm (max, 15 mm) in the lateral direction and 5 +/- 3 mm (max, 15 mm) in the vertical direction. CONCLUSIONS: Our data support the use of target margins (between the clinical target volume and planning target volume) of 9 mm for day-to-day esophageal motion and 8 mm for patient setup in all directions, respectively.