RESULTS: VF position asymmetry (VFPa and VFRa) was greater (p=0.012; p=0.001) and overall mobility (VFAP) was lower (p=0.008) in UVFP patients compared with healthy participants. ICC of repeatability of all metrics was good, ranged from 0.82 to 0.95 except for the inter-session VFPa (0.44).
CONCLUSION: Cine-MRI is feasible for assessing VF abduction and adduction. Derived quantitative metrics have good repeatability.
KEY POINTS: • Cine-MRI is used to assess vocal folds (VFs) mobility: abduction and adduction. • New quantitative metrics are derived from VF position and abduction potential. • Cine-MRI able to depict the difference between normal and abnormal VF mobility. • Cine-MRI derived quantitative metrics have good repeatability.
METHODS: In this series, we looked into nine cases of CM with syringomyelia from clinical and radiological perspective before and after surgery. The radiological parameters were herniated tonsillar length, syrinx: cord ratio, syrinx length and diameter. Flow velocity and morphologic changes in Chiari were illustrated.
RESULTS: Seven patients showed either reduction in syrinx length, syrinx: cord ratio or both postoperatively. Clinical recovery somewhat varied in motor and sensory symptoms. Four patients gained better functional grade in modified Rankin scale (MRS) while the rest remained similar. The study highlighted the advantage of CSF flow dynamics information over MR anatomical radiographic improvement in addressing the neurologic and functional recovery. We also discussed the practicality of cine sequence in preoperative patient selection, syrinx analysis and postoperative flow evaluation in anticipation of clinical outcome.
CONCLUSION: Phase-contrast cine MRI is a useful tool dictated by resource availability. We recommend its routine use in preoperative analysis and subsequent observational follow-up after surgery.
PURPOSE: To examine relationship between ulam consumption and the working memory and cognitive flexibility among aging adults from low-income households who are more susceptible to cognitive decline.
STUDY TYPE: Cross-sectional.
POPULATION/SUBJECTS: Thirty-two aging adults (45-75 years old).
FIELD STRENGTH/SEQUENCE: Task-based fMRI, 3.0T, T1 -weighted anatomical images, T2 *-weighted imaging data.
ASSESSMENT: The dietary and ulam consumption were assessed using the respective validated Dietary History and semiquantitative Food Frequency questionnaires. Working memory and cognitive flexibility were evaluated by using neuropsychological batteries (ie, mini-mental state examination [MMSE], Digit Span, and Rey auditory verbal learning test [RAVLT]) and task-based fMRI (N-back and Stroop Color Word Test [SCWT]). Brodmann's areas 9 and 46 were the regions of interest (ROIs) of DLPFC activation.
STATISTICAL TESTS: Multiple linear regression used to understand the relationship between ulam consumption and the working memory and cognitive flexibility, while analysis of covariance (ANCOVA) was used to compare the difference of working memory and cognitive flexibility among four percentiles of ulam consumption, after age, gender, and education years adjustments. Significance was decided by two-sided, P
PURPOSE: To investigate the effects of stochastic resonance on lateralization of auditory working memory regions, and also to examine the brain-behavior relationship during stochastic resonance.
STUDY TYPE: Cross-sectional.
POPULATION/SUBJECTS: Forty healthy young adults (18-24 years old).
FIELD STRENGTH/SEQUENCE: 3.0T, T1 , and T2 *-weighted imaging.
ASSESSMENT: The auditory working memory performance was assessed using a backward recall task. Functional magnetic resonance imaging (fMRI) was used to measure brain activity during task performance. Functional MRI data were analyzed using SPM12 and WFU PickAtlas.
STATISTICAL TESTS: One-way independent analyses of variance (ANOVA) were conducted on the behavioral and functional data to examine the main effect of noise level on performance (P
OBJECTIVE: To determine the accuracy of pre-contrast abdominal MR imaging for lesion detection and characterization in pediatric oncology patients.
MATERIALS AND METHODS: We included 120 children (37 boys and 83 girls; mean age 8.94 years) referred by oncology services. Twenty-five had MRI for the first time and 95 were follow-up scans. Two authors independently reviewed pre-contrast MR images to note the following information about the lesions: location, number, solid vs. cystic and likely nature. Pre- and post-contrast imaging reviewed together served as the reference standard.
RESULTS: The overall sensitivity was 88% for the first reader and 90% for the second; specificity was 94% and 91%; positive predictive value was 96% and 94%; negative predictive value was 82% and 84%; accuracy of pre-contrast imaging for lesion detection as compared to the reference standard was 90% for both readers. The difference between mean number of lesions detected on pre-contrast imaging and reference standard was not significant for either reader (reader 1, P = 0.072; reader 2, P = 0.071). There was substantial agreement (kappa values of 0.76 and 0.72 for readers 1 and 2) between pre-contrast imaging and reference standard for determining solid vs. cystic lesion and likely nature of the lesion. The addition of post-contrast imaging increased confidence of both readers significantly (P
METHODS: In this article, we propose a new method based on simultaneous EEG-fMRI data and machine learning approach to classify the visual brain activity patterns. We acquired EEG-fMRI data simultaneously on the ten healthy human participants by showing them visual stimuli. Data fusion approach is used to merge EEG and fMRI data. Machine learning classifier is used for the classification purposes.
RESULTS: Results showed that superior classification performance has been achieved with simultaneous EEG-fMRI data as compared to the EEG and fMRI data standalone. This shows that multimodal approach improved the classification accuracy results as compared with other approaches reported in the literature.
CONCLUSIONS: The proposed simultaneous EEG-fMRI approach for classifying the brain activity patterns can be helpful to predict or fully decode the brain activity patterns.
METHODS: A systematic literature search of brain tumours in the context of fMRI methods applied to pre-operative mapping for language functional areas was conducted using PubMed/MEDLINE and Scopus electronic database following PRISMA guidelines. The article search was conducted between the earliest record and March 1, 2019. References and citations were checked in Google Scholar database.
RESULTS: Twenty-nine independent studies were identified, comprising 1031 adult participants with 976 patients characterised with different types and sizes of brain tumours, and the remaining 55 being healthy controls. These studies evaluated functional language areas in patients with brain tumours prior to surgical interventions using language-based fMRI. Results demonstrated that 86% of the studies used a Word Generation Task (WGT) to evoke functional language areas during pre-operative mapping. Fifty-seven percent of the studies that used language-based paradigms in conjunction with fMRI as a pre-operative mapping tool were in agreement with intra-operative results of language localization.
CONCLUSIONS: WGT was most commonly utilised and is proposed as a suitable and useful technique for a language-based paradigm fMRI for pre-operative mapping. However, based on available evidence, WGT alone is not sufficient. We propose a combination and convergence paradigms for a more sensitive and specific map of language function for pre-operative mapping. A standard guideline for clinical applications should be established.
PATIENTS AND METHODS: The institutional review board approved this prospective study. The brain MRI protocol, including sagittal T1-weighted, axial T2-weighted, coronal fluid-attenuated inversion recovery, and axial T1-weighted with contrast enhancement (T1WCE) sequences, was assessed in 26 patients divided into two groups: Medulloblastoma (n=22) and ependymoma (n=4). The quantified region of interest (ROI) values of tumors and their ratios to parenchyma were compared between the two groups. Multivariate logistic regression analysis was utilized to find significant factors influencing the differential diagnosis between the two groups. A generalized estimating equation (GEE) was used to create the predictive model for the discrimination of medulloblastoma from ependymoma.
RESULTS: Multivariate logistic regression analysis showed that the T2- and T1WCE-ROI values of tumors and the ratios of T1WCE-ROI values to parenchyma were the most significant factors influencing the diagnosis between these two groups. GEE produced the model: y=exn/(1+exn) with predictor xn=-8.773+0.012x1 - 0.032x2 - 13.228x3, where x1 was the T2-weighted signal intensity (SI) of tumor, x2 the T1WCE SI of tumor, and x3 the T1WCE SI ratio of tumor to parenchyma. The sensitivity, specificity, and area under the curve of the GEE model were 77.3%, 100%, and 92%, respectively.
CONCLUSION: The GEE predictive model can discriminate between medulloblastoma and ependymoma clinically. Further research should be performed to validate these findings.