Resting‐state functional magnetic resonance imaging (rsfMRI) has been developed as a method of investigating spontaneous neural activity. Based on its low‐frequency signal synchronization, rsfMRI has ...made it possible to identify multiple macroscopic structures termed resting‐state networks (RSNs) on a single scan of less than 10 minutes. It is easy to implement even in clinical practice, in which assigning tasks to patients can be challenging. These advantages have accelerated the adoption and growth of rsfMRI. Recently, studies on the global rsfMRI signal have attracted increasing attention. Because it primarily arises from physiological events, less attention has hitherto been paid to the global signal than to the local network (i.e., RSN) component. However, the global signal is not a mere nuisance or a subsidiary component. On the contrary, it is quantitatively the dominant component that accounts for most of the variance in the rsfMRI signal throughout the brain and provides rich information on local hemodynamics that can serve as an individual‐level diagnostic biomarker. Moreover, spatiotemporal analyses of the global signal have revealed that it is closely and fundamentally associated with the organization of RSNs, thus challenging the basic assumptions made in conventional rsfMRI analyses and views on RSNs. This review introduces new concepts emerging from rsfMRI spatiotemporal analyses focusing on the global signal and discusses how they may contribute to future clinical medicine.
Evidence Level
5
Technical Efficacy
Stage 1
Background
Longitudinal magnetic resonance imaging (MRI) studies have become increasingly important to assess the changes in brain morphology during normal aging and neurodegenerative disorders. ...However, the reliability of longitudinal morphometric changes has not been fully evaluated.
Purpose
To examine the reliability of longitudinal (2‐year) changes in brain morphology determined by longitudinal voxel‐based morphometry (VBM) in healthy elderly subjects, patients with mild cognitive impairment (MCI), and patients with Alzheimer's disease (AD).
Study Type
Retrospective analysis.
Subjects
Twenty‐four healthy elderly subjects, 28 MCI patients, and 16 AD patients.
Field Strength/Sequence
A 1.5 T, magnetization‐prepared rapid gradient‐echo.
Assessment
Longitudinal (2‐year) changes in gray matter volume determined by longitudinal VBM processing, and visual assessment of image quality.
Statistical Tests
Intraclass correlation coefficient (ICC) and Kruskal–Wallis test.
Results
The ICC maps differed among the three groups. The mean ICC was 0.81 overall (0.86 for healthy elderly subjects, 0.75 for MCI patients, and 0.76 for AD patients). The reliability was good to excellent (ICC, 0.60–1.00) for 92% of voxels (99% for healthy elderly subjects, 83% for MCI patients, and 83% for AD patients). The image quality differed significantly among the three groups (P < 0.05).
Data Conclusion
These results indicate that the reliability of longitudinal gray matter volume changes by VBM is good to excellent for most voxels. However, reliability may be affected by the disease, possibly due to differences in head motion during imaging.
Evidence Level
3
Technical Efficacy
Stage 1
Background
Scan acceleration such as parallel imaging reduces scan time, but shorter scan time may reduce the signal‐to‐noise ratio and affect image quality. The reproducibility of longitudinal ...changes in the brain structure between non‐accelerated and accelerated imaging by surface‐based analysis is unclear.
Purpose
To determine the reproducibility of longitudinal changes in cortical thickness, measured by surface‐based morphometry, between non‐accelerated and accelerated structural T1‐weighted imaging in the healthy elderly and those with mild cognitive impairment (MCI) and Alzheimer's disease (AD).
Study Type
Retrospective.
Subjects
Fifty healthy elderly subjects (age = 73 ± 5 years, 29 females, 21 males), 54 MCI patients (age = 71 ± 7 years, 23 females, 31 males), and 8 AD patients (age = 78 ± 6 years, 6 females, 2 males).
Field Strength/Sequence
3 T, magnetization‐prepared rapid gradient‐echo.
Assessment
Longitudinal changes in cortical thickness estimated by the longitudinal stream in FreeSurfer from 2‐year interval data, and visual assessment of image quality by three radiologists.
Statistical Tests
Intraclass correlation coefficient (ICC) and Kruskal–Wallis test. A P value <0.05 was considered significant.
Results
Healthy elderly subjects, MCI patients, and AD patients showed different patterns in the ICC maps. For the smoothing of 20 mm full width at half maximum, the mean ICC was 0.45 overall (healthy elderly, 0.33; MCI patients, 0.49; AD patients, 0.31). The within‐subject SDs of the symmetrized percent changes were similar between healthy elderly subjects (mean, 1.3%/year) and MCI patients (mean, 1.3%/year) but larger in AD patients (mean, 1.7%/year). Image quality did not significantly differ per group (P = 0.18).
Data Conclusion
The results of this study indicate the reproducibility of longitudinal changes in cortical thickness measured by surface‐based morphometry between non‐accelerated and accelerated imaging, and that the reproducibility varies by disease and region.
Level of Evidence
3
Technical Efficacy
Stage 1
Blood oxygenation level-dependent (BOLD) contrast is sensitive to local hemodynamic changes and thus is applicable to imaging perfusion or vascular reactivity. However, knowledge about its ...measurement characteristics compared to reference standard perfusion imaging is limited. This study longitudinally evaluated perfusion in patients with steno-occlusive disease using resting-state functional MRI (rsfMRI) acquired before and within nine days of anterior circulation revascularization in patients with large cerebral artery steno-occlusive diseases. The reliability and sensitivity to longitudinal changes of rsfMRI temporal correlation (Rc) and time delay (TDc) relative to the cerebellar signal were examined voxel-wise in comparison with single-photon emission CT (SPECT) cerebral blood flow (CBF) using the within-subject standard deviation (Sw) and intraclass correlation coefficients (ICCs). For statistical comparisons, the standard deviation (SD) of longitudinal changes within the cerebellum, the number of voxels with significant changes in the left middle cerebral artery territory ipsilateral to surgery, and their average changes relative to the cerebellar SD were evaluated. The test-retest reliability of the fMRI metrics was also similarly evaluated using the human connectome project (HCP) healthy young adult dataset. The test-retest time interval was 31 ± 18 days. Test-retest reliability was significantly higher for SPECT (cerebellar SD: -2.59 ± 0.20) than for fMRI metrics (cerebellar SD: Rc, -2.34 ± 0.24, p = 0.04; TDc, -2.19 ± 0.21, p = 0.003). Sensitivity to postoperative changes, which was evaluated as the number of voxels, was significantly higher for fMRI TDc (8.78 ± 0.72) than for Rc (7.42 ± 1.48, p = 0.03) or SPECT CBF (6.88 ± 0.67, p < 0.001). The ratio between the average Rc, TDc, and SPECT CBF changes within the left MCA target region and cerebellar SD was also significantly higher for fMRI TDc (1.21 ± 0.79) than Rc (0.48 ± 0.94, p = 0.006) or SPECT CBF (0.23 ± 0.57, p = 0.001). The measurement variability of time delay was also larger than that of temporal correlation in HCP data within the cerebellum (t = -8.7, p < 0.001) or in the whole-brain (t = -27.4, p < 0.001) gray matter. These data suggest that fMRI time delay is more sensitive to the hemodynamic changes than SPECT CBF, although the reliability is lower. The implication for fMRI connectivity studies is that temporal correlation can be significantly decreased due to altered hemodynamics, even in cases with normal CBF.
To examine whether feature-fusion (FF) method improves single-shot detector's (SSD's) detection of small brain metastases on contrast-enhanced (CE) T1-weighted MRI.
The study included 234 MRI ...scans from 234 patients (64.3 years±12.0; 126 men). The ground-truth annotation was performed semiautomatically. SSDs with and without an FF module were developed and trained using 178 scans. The detection performance was evaluated at the SSDs' 50% confidence threshold using sensitivity, positive-predictive value (PPV), and the false-positive (FP) per scan with the remaining 56 scans.
FF-SSD achieved an overall sensitivity of 86.0% (95% confidence interval CI: 83.0%, 85.6%; 196/228) and 46.8% PPV (95% CI: 42.0%, 46.3%; 196/434), with 4.3 FP (95% CI: 4.3, 4.9). Lesions smaller than 3 mm had 45.8% sensitivity (95% CI: 36.1%, 45.5%; 22/48) with 2.0 FP (95% CI: 1.9, 2.1). Lesions measuring 3-6 mm had 92.3% sensitivity (95% CI: 86.5%, 92.0%; 48/52) with 1.8 FP (95% CI: 1.7, 2.2). Lesions larger than 6 mm had 98.4% sensitivity (95% CI: 97.8%, 99.4%; 126/128) 0.5 FP (95% CI: 0.5, 0.8) per scan. FF-SSD had a significantly higher sensitivity for lesions < 3 mm (p = 0.008, t = 3.53) than the baseline SSD, while the overall PPV was similar (p = 0.06, t = -2.16). A similar trend was observed even when the detector's confidence threshold was varied as low as 0.2, for which the FF-SSD's sensitivity was 91.2% and the FP was 9.5.
The FF-SSD algorithm identified brain metastases on CE T1-weighted MRI with high accuracy.
Neuropsychiatric disorders are diagnosed based on behavioral criteria, which makes the diagnosis challenging. Objective biomarkers such as neuroimaging are needed, and when coupled with machine ...learning, can assist the diagnostic decision and increase its reliability. Sixty-four schizophrenia, 36 autism spectrum disorder (ASD), and 106 typically developing individuals were analyzed. FreeSurfer was used to obtain the data from the participant's brain scans. Six classifiers were utilized to classify the subjects. Subsequently, 26 ultra-high risk for psychosis (UHR) and 17 first-episode psychosis (FEP) subjects were run through the trained classifiers. Lastly, the classifiers' output of the patient groups was correlated with their clinical severity. All six classifiers performed relatively well to distinguish the subject groups, especially support vector machine (SVM) and Logistic regression (LR). Cortical thickness and subcortical volume feature groups were most useful for the classification. LR and SVM were highly consistent with clinical indices of ASD. When UHR and FEP groups were run with the trained classifiers, majority of the cases were classified as schizophrenia, none as ASD. Overall, SVM and LR were the best performing classifiers. Cortical thickness and subcortical volume were most useful for the classification, compared to surface area. LR, SVM, and DT's output were clinically informative. The trained classifiers were able to help predict the diagnostic category of both UHR and FEP Individuals.
The objective of this study is to verify the accuracy of 3D-printed hollow models of visceral aneurysms created from CT angiography (CTA) data, by evaluating the sizes and shapes of aneurysms and ...related arteries.
From March 2006 to August 2015, 19 true visceral aneurysms were embolized via interventional radiologic treatment provided by the radiology department at our institution; aneurysms with bleeding (n = 3) or without thin-slice (< 1 mm) preembolization CT data (n = 1) were excluded. A total of 15 consecutive true visceral aneurysms from 11 patients (eight women and three men; mean age, 61 years; range, 53-72 years) whose aneurysms were embolized via endovascular procedures were included in this study. Three-dimensional-printed hollow models of aneurysms and related arteries were fabricated from CTA data. The accuracies of the sizes and shapes of the 3D-printed hollow models were evaluated using the nonparametric Wilcoxon signed rank test and the Dice coefficient index.
Aneurysm sizes ranged from 138 to 18,691 mm
(diameter, 6.1-35.7 mm), and no statistically significant difference was noted between patient data and 3D-printed models (p = 0.56). Shape analysis of whole aneurysms and related arteries indicated a high level of accuracy (Dice coefficient index value, 84.2-95.8%; mean ± SD, 91.1 ± 4.1%).
The sizes and shapes of 3D-printed hollow visceral aneurysm models created from CTA data were accurate. These models can be used for simulations of endovascular treatment and precise anatomic information.
Resting-state functional magnetic resonance imaging (rsfMRI) has been widely applied to investigate spontaneous neural activity, often based on its macroscopic organization that is termed ...resting-state networks (RSNs). Although the neurophysiological mechanisms underlying the RSN organization remain largely unknown, accumulating evidence points to a substantial contribution from the global signals to their structured synchronization. This study further explored the phenomenon by taking advantage of the inter- and intra-subject variations of the time delay and correlation coefficient of the signal timeseries in each region using the global mean signal as the reference signal. Consistent with the hypothesis based on the empirical and theoretical findings, the time lag and correlation, which have consistently been proven to represent local hemodynamic status, were shown to organize networks equivalent to RSNs. The results not only provide further evidence that the local hemodynamic status could be the direct source of the RSNs’ spatial patterns but also explain how the regional variations in the hemodynamics, combined with the changes in the global events’ power spectrum, lead to the observations. While the findings pose challenges to interpretations of rsfMRI studies, they further support the view that rsfMRI can offer detailed information related to global neurophysiological phenomena as well as local hemodynamics that would have great potential as biomarkers.
Autism spectrum disorder is a prevalent neurodevelopmental disorder with no established pharmacological treatment for its core symptoms. Although previous literature has shown that single-dose ...administration of oxytocin temporally mitigates autistic social behaviours in experimental settings, it remains in dispute whether such potentially beneficial responses in laboratories can result in clinically positive effects in daily life situations, which are measurable only in long-term observations of individuals with the developmental disorder undergoing continual oxytocin administration. Here, to address this issue, we performed an exploratory, randomized, double-blind, placebo-controlled, crossover trial including 20 high-functional adult males with autism spectrum disorder. Data obtained from 18 participants who completed the trial showed that 6-week intranasal administration of oxytocin significantly reduced autism core symptoms specific to social reciprocity, which was clinically evaluated by Autism Diagnostic Observation Scale (P = 0.034, PFDR < 0.05, Cohen's d = 0.78). Critically, the improvement of this clinical score was accompanied by oxytocin-induced enhancement of task-independent resting-state functional connectivity between anterior cingulate cortex and dorso-medial prefrontal cortex (rho = -0.60, P = 0.011), which was measured by functional magnetic resonance imaging. Moreover, using the same social-judgement task as used in our previous single-dose oxytocin trial, we confirmed that the current continual administration also significantly mitigated behavioural and neural responses during the task, both of which were originally impaired in autistic individuals (judgement tendency: P = 0.019, d = 0.62; eye-gaze effect: P = 0.03, d = 0.56; anterior cingulate activity: P = 0.00069, d = 0.97; dorso-medial prefrontal activity: P = 0.0014, d = 0.92; all, PFDR < 0.05). Furthermore, despite its longer administration, these effect sizes of the 6-week intervention were not larger than those seen in our previous single-dose intervention. These findings not only provide the evidence for clinically beneficial effects of continual oxytocin administration on the core social symptoms of autism spectrum disorder with suggesting its underlying biological mechanisms, but also highlight the necessity to seek optimal regimens of continual oxytocin treatment in future studies.
Interest has recently grown in multi-center studies, which have more power than smaller studies in conducting sophisticated evaluations of basic neuroanatomy and neurodegenerative disorders. The ...large number of subjects that result from pooling multi-center datasets increases sensitivity, but also introduces a between-center variance component. Taking sex differences as an example, we examined the effects of different ratios of cases to controls (males to females) between scanners in multi-scanner morphometric studies, using voxel-based morphometry and data obtained on two scanners of the exact same model. Each subject was scanned twice with both scanners. Using the image obtained on either of the two scanners for each subject, voxel-based analyses were repeated with different ratios of males to females for each scanner. As the ratio of males to females became more imbalanced between the scanners, the differences between the two scanners more strongly affected the results of analyses of sex differences. When the ratio of males to females was balanced, the inclusion of scanner as a covariate in the statistical analysis had almost no influence on the results of analyses of sex differences. When the ratio of males to females was ill-balanced, the inclusion of scanner as a covariate suppressed scanner effects on the results, but made sex differences less likely to become significant. The present results suggest that as long as the ratio of cases to controls is well-balanced across different scanners, it is not always necessary to include scanner as a covariate in the statistical analysis, and that when the ratio of cases to controls is ill-balanced across scanners, the inclusion of scanner as a covariate in the statistical analysis can suppress scanner effects, but may make differences less likely to be detected.
•We examined the effects of different ratios of cases to controls between scanners.•We used VBM and MRI data obtained on two scanners of the exact same model.•The more imbalanced the sex ratio, the stronger scanner differences affected results.•Including scanner as a covariate suppressed the effects of scanner variability.•But it made differences less likely to be detected when the sex ratio was imbalanced.
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