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Tumor Tissue Detection using Blood-Oxygen-Level-Dependent Functional MRI based on Independent Component Analysis.

Wed, 11/28/2018 - 19:45
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Tumor Tissue Detection using Blood-Oxygen-Level-Dependent Functional MRI based on Independent Component Analysis.

Sci Rep. 2018 01 19;8(1):1223

Authors: Huang H, Lu J, Wu J, Ding Z, Chen S, Duan L, Cui J, Chen F, Kang D, Qi L, Qiu W, Lee SW, Qiu S, Shen D, Zang YF, Zhang H

Abstract
Accurate delineation of gliomas from the surrounding normal brain areas helps maximize tumor resection and improves outcome. Blood-oxygen-level-dependent (BOLD) functional MRI (fMRI) has been routinely adopted for presurgical mapping of the surrounding functional areas. For completely utilizing such imaging data, here we show the feasibility of using presurgical fMRI for tumor delineation. In particular, we introduce a novel method dedicated to tumor detection based on independent component analysis (ICA) of resting-state fMRI (rs-fMRI) with automatic tumor component identification. Multi-center rs-fMRI data of 32 glioma patients from three centers, plus the additional proof-of-concept data of 28 patients from the fourth center with non-brain musculoskeletal tumors, are fed into individual ICA with different total number of components (TNCs). The best-fitted tumor-related components derived from the optimized TNCs setting are automatically determined based on a new template-matching algorithm. The success rates are 100%, 100% and 93.75% for glioma tissue detection for the three centers, respectively, and 85.19% for musculoskeletal tumor detection. We propose that the high success rate could come from the previously overlooked ability of BOLD rs-fMRI in characterizing the abnormal vascularization, vasomotion and perfusion caused by tumors. Our findings suggest an additional usage of the rs-fMRI for comprehensive presurgical assessment.

PMID: 29352123 [PubMed - indexed for MEDLINE]

Non-invasive evaluation of cerebral perfusion in patients with transient ischemic attack: an fMRI study.

Sun, 11/18/2018 - 21:16
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Non-invasive evaluation of cerebral perfusion in patients with transient ischemic attack: an fMRI study.

J Neurol. 2018 Nov 16;:

Authors: Lv Y, Wei W, Song Y, Han Y, Zhou C, Zhou D, Zhang F, Xue Q, Liu J, Zhao L, Zhang C, Li L, Zang YF, Han X

Abstract
Detection of hypoperfused tissue due to the ischemia is considered to be important in understanding the cerebral perfusion status and may be helpful in guiding therapeutic decisions for patients with transient ischemic attack (TIA). We hypothesized that the combination of two non-invasive fMRI techniques: resting-state BOLD-fMRI time-shift analysis (TSA) approach and 3D ASL, could detect the cerebral hemodynamic status in TIA patients noninvasively. From April 2015 to June 2016, 51 TIA patients were recruited in this study. We calculated the time delay between the resting-state BOLD signal at each voxel and the whole-brain signal using TSA approach and compared the results to CBF map derived from ASL. Out of the 51 patients, 24 patients with normal arrival time and CBF were in Stage 0; 14 patients who showed delayed arrival time and normal CBF which indicated elevated CBV were in Stage I; the other 13 patients who had both delayed arrival time and decreased CBF were in Stage II, the group average spatial overlap, i.e., Dice coefficient, of the two measurements was 0.55. Four patients in Stage 0 (17.4%), three patients in Stage I (23.1%) and five patients in Stage II (45.5%) suffered ischemic stroke or TIA symptoms in 1 year after MRI scan. The patients in Stage II was at highest risk of subsequent events when compared to other two stages. The combination of resting-state BOLD-fMRI and ASL hold the potential to noninvasively identify the hemodynamic status in TIA patients and help predict the risk of subsequent events.

PMID: 30446964 [PubMed - as supplied by publisher]

Consistent decreased activity in the putamen in Parkinson's disease: a meta-analysis and an independent validation of resting-state fMRI.

Sun, 11/18/2018 - 21:16
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Consistent decreased activity in the putamen in Parkinson's disease: a meta-analysis and an independent validation of resting-state fMRI.

Gigascience. 2018 06 01;7(6):

Authors: Wang J, Zhang JR, Zang YF, Wu T

Abstract
Background: Resting-state functional magnetic resonance imaging (RS-fMRI) has frequently been used to investigate local spontaneous brain activity in Parkinson's disease (PD) in a whole-brain, voxel-wise manner. To quantitatively integrate these studies, we conducted a coordinate-based (CB) meta-analysis using the signed differential mapping method on 15 studies that used amplitude of low-frequency fluctuation (ALFF) and 11 studies that used regional homogeneity (ReHo). All ALFF and ReHo studies compared PD patients with healthy controls. We also performed a validation RS-fMRI study of ALFF and ReHo in a frequency-dependent manner for a novel dataset consisting of 49 PD and 49 healthy controls.
Findings: Decreased ALFF was found in the left putamen in PD by meta-analysis. This finding was replicated in our independent validation dataset in the 0.027-0.073 Hz band but not in the conventional frequency band of 0.01-0.08 Hz.
Conclusions: Findings from the current study suggested that decreased ALFF in the putamen of PD patients is the most consistent finding. RS-fMRI is a promising technique for the precise localization of abnormal spontaneous activity in PD. However, more frequency-dependent studies using the same analytical methods are needed to replicate these results. Trial registration: NCT NCT03439163. Registered 20 February 2018, retrospectively registered.

PMID: 29917066 [PubMed - indexed for MEDLINE]

Differences in Cortical Gray Matter Atrophy of Paraplegia and Tetraplegia after Complete Spinal Cord Injury.

Sat, 11/17/2018 - 15:02
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Differences in Cortical Gray Matter Atrophy of Paraplegia and Tetraplegia after Complete Spinal Cord Injury.

J Neurotrauma. 2018 Nov 15;:

Authors: Karunakaran KD, He J, Zhao J, Cui JL, Zang YF, Zhang Z, Biswal BB

Abstract
Anatomical studies of SCI using Magnetic Resonance Imaging (MRI) report diverging observations, from 'no changes' to 'tissue atrophy in motor and non-motor regions.' These discrepancies among studies can be attributed to heterogeneity in extent, level and post-injury duration observed within the SCI population. But, no studies have investigated structural changes associated with different levels of injury (paraplegia vs. tetraplegia). High-resolution MRI images were processed using Voxel-Based Morphometry technique to compare regional GM volume (GMV) between 16 complete paraplegia and 7 complete tetraplegia SCI subjects scanned within two years of injury when compared to 22 age-matched healthy controls using one-way Analysis of Covariance (ANCOVA). A post-hoc analysis using region of interest based approach was employed to quantify GMV differences between healthy controls and subgroups of SCI. A voxel-wise one sample t-test was also performed to evaluate the mean effect of post-injury duration on GMV of SCI group. ANCOVA resulted in altered GMV in inferior frontal gyrus, bilateral mid orbital gyrus extending to rectal gyrus and anterior cingulate cortex. Post-hoc analysis, in general, indicated GM atrophy after SCI but tetraplegia showed a greater decrease in GMV when compared to paraplegia and healthy controls. Further, the GMV of the middle frontal gyrus, superior frontal gyrus, inferior frontal gyrus, insula, mid-orbital gyrus and middle temporal gyrus was positively correlated with post-injury duration in both paraplegia and tetraplegia groups. GM atrophy after SCI is affected by the level of cord injury, with higher levels of injury resulting in greater loss of GMV. The magnitude of GMV loss in the frontal cortex after SCI also appears to be dynamic within the first two years of injury. Understanding the effect of injury level and injury duration on structural changes following SCI can help better understand the mechanisms leading to positive and negative clinical outcome in SCI patients.

PMID: 30430910 [PubMed - as supplied by publisher]

Associations of brain entropy (BEN) to cerebral blood flow and fractional amplitude of low-frequency fluctuations in the resting brain.

Mon, 10/15/2018 - 09:37
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Associations of brain entropy (BEN) to cerebral blood flow and fractional amplitude of low-frequency fluctuations in the resting brain.

Brain Imaging Behav. 2018 Sep 12;:

Authors: Song D, Chang D, Zhang J, Ge Q, Zang YF, Wang Z

Abstract
Entropy is a fundamental trait of human brain. Using fMRI-based brain entropy (BEN) mapping, interesting findings have been increasingly revealed in normal brain and neuropsychiatric disorders. As BEN is still relatively new, an often-raised question is how much new information can this measure tell about the brain compared to other more established brain activity measures. The study aimed to address that question by examining the relationship between BEN and cerebral blood flow (CBF) and the fractional amplitude of low-frequency fluctuations (fALFF), two widely used resting state brain state measures. fMRI data acquired from a large cohort of normal subjects were used to calculate the three metrics; inter-modality associations were assessed at each voxel through the Pearson correlation analysis. A moderate to high positive BEN-CBF and BEN-fALFF correlations were found in orbito-frontal cortex (OFC) and posterior inferior temporal cortex (ITC); Strong negative BEN-fALFF correlations were found in visual cortex (VC), anterior ITC, striatum, motor network, precuneus, and lateral parietal cortex. Positive CBF-fALFF correlations were found in medial OFC (MOFC), medial prefrontal cortex (MPFC), left angular gyrus, and left precuneus. Significant gender effects were observed for all three metrics and their correlations. Our data clearly demonstrated that BEN provides unique information that cannot be revealed by CBF and fALFF.

PMID: 30209786 [PubMed - as supplied by publisher]