Displaying publications 61 - 80 of 116 in total

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  1. Accuracy of pre-contrast imaging in abdominal magnetic resonance imaging of pediatric oncology patients
    Mohd Zaki F, Moineddin R, Grant R, Chavhan GB
    Pediatr Radiol, 2016 Nov;46(12):1684-1693.
    PMID: 27406610
    BACKGROUND: Safety concerns are increasingly raised regarding the use of gadolinium-based contrast media for MR imaging.

    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 

    Matched MeSH terms: Magnetic Resonance Imaging/methods*
  2. Fulltext Determination of an optimally sensitive and specific chemical exchange saturation transfer MRI quantification metric in relevant biological phantoms
    Ray KJ, Larkin JR, Tee YK, Khrapitchev AA, Karunanithy G, Barber M, et al.
    NMR Biomed, 2016 11;29(11):1624-1633.
    PMID: 27686882 DOI: 10.1002/nbm.3614
    The purpose of this study was to develop realistic phantom models of the intracellular environment of metastatic breast tumour and naïve brain, and using these models determine an analysis metric for quantification of CEST MRI data that is sensitive to only labile proton exchange rate and concentration. The ability of the optimal metric to quantify pH differences in the phantoms was also evaluated. Novel phantom models were produced, by adding perchloric acid extracts of either metastatic mouse breast carcinoma cells or healthy mouse brain to bovine serum albumin. The phantom model was validated using 1 H NMR spectroscopy, then utilized to determine the sensitivity of CEST MRI to changes in pH, labile proton concentration, T1 time and T2 time; six different CEST MRI analysis metrics (MTRasym , APT*, MTRRex , AREX and CESTR* with and without T1 /T2 compensation) were compared. The new phantom models were highly representative of the in vivo intracellular environment of both tumour and brain tissue. Of the analysis methods compared, CESTR* with T1 and T2 time compensation was optimally specific to changes in the CEST effect (i.e. minimal contamination from T1 or T2 variation). In phantoms with identical protein concentrations, pH differences between phantoms could be quantified with a mean accuracy of 0.6 pH units. We propose that CESTR* with T1 and T2 time compensation is the optimal analysis method for these phantoms. Analysis of CEST MRI data with T1 /T2 time compensated CESTR* is reproducible between phantoms, and its application in vivo may resolve the intracellular alkalosis associated with breast cancer brain metastases without the need for exogenous contrast agents.
    Matched MeSH terms: Magnetic Resonance Imaging/methods
  3. Amyloid imaging using fluorine-19 magnetic resonance imaging ((19)F-MRI)
    Tooyama I, Yanagisawa D, Taguchi H, Kato T, Hirao K, Shirai N, et al.
    Ageing Res Rev, 2016 09;30:85-94.
    PMID: 26772439 DOI: 10.1016/j.arr.2015.12.008
    The formation of senile plaques followed by the deposition of amyloid-β is the earliest pathological change in Alzheimer's disease. Thus, the detection of senile plaques remains the most important early diagnostic indicator of Alzheimer's disease. Amyloid imaging is a noninvasive technique for visualizing senile plaques in the brains of Alzheimer's patients using positron emission tomography (PET) or magnetic resonance imaging (MRI). Because fluorine-19 ((19)F) displays an intense nuclear magnetic resonance signal and is almost non-existent in the body, targets are detected with a higher signal-to-noise ratio using appropriate fluorinated contrast agents. The recent introduction of high-field MRI allows us to detect amyloid depositions in the brain of living mouse using (19)F-MRI. So far, at least three probes have been reported to detect amyloid deposition in the brain of transgenic mouse models of Alzheimer's disease; (E,E)-1-fluoro-2,5-bis-(3-hydroxycarbonyl-4-hydroxy)styrylbenzene (FSB), 1,7-bis(4'-hydroxy-3'-trifluoromethoxyphenyl)-4-methoxycarbonylethyl-1,6-heptadiene3,5-dione (FMeC1, Shiga-Y5) and 6-(3',6',9',15',18',21'-heptaoxa-23',23',23'-trifluorotricosanyloxy)-2-(4'-dimethylaminostyryl)benzoxazole (XP7, Shiga-X22). This review presents the recent advances in amyloid imaging using (19)F-MRI, including our own studies.
    Matched MeSH terms: Magnetic Resonance Imaging/methods*
  4. Fulltext Novel application of chemical shift gradient echo in- and opposed-phase sequences in 3 T MRI for the detection of H-MRS visible lipids and grading of glioma
    Ramli N, Khairy AM, Seow P, Tan LK, Wong JH, Ganesan D, et al.
    Eur Radiol, 2016 Jul;26(7):2019-29.
    PMID: 26560718 DOI: 10.1007/s00330-015-4045-0
    OBJECTIVES: We evaluated the feasibility of using chemical shift gradient-echo (GE) in- and opposed-phase (IOP) imaging to grade glioma.

    METHODS: A phantom study was performed to investigate the correlation of (1)H MRS-visible lipids with the signal loss ratio (SLR) obtained using IOP imaging. A cross-sectional study approved by the institutional review board was carried out in 22 patients with different glioma grades. The patients underwent scanning using IOP imaging and single-voxel spectroscopy (SVS) using 3T MRI. The brain spectra acquisitions from solid and cystic components were obtained and correlated with the SLR for different grades.

    RESULTS: The phantom study showed a positive linear correlation between lipid quantification at 0.9 parts per million (ppm) and 1.3 ppm with SLR (r = 0.79-0.99, p 

    Matched MeSH terms: Magnetic Resonance Imaging/methods*
  5. Correlation between subjective and objective assessment of magnetic resonance (MR) images
    Chow LS, Rajagopal H, Paramesran R, Alzheimer's Disease Neuroimaging Initiative
    Magn Reson Imaging, 2016 07;34(6):820-831.
    PMID: 26969762 DOI: 10.1016/j.mri.2016.03.006
    Medical Image Quality Assessment (IQA) plays an important role in assisting and evaluating the development of any new hardware, imaging sequences, pre-processing or post-processing algorithms. We have performed a quantitative analysis of the correlation between subjective and objective Full Reference - IQA (FR-IQA) on Magnetic Resonance (MR) images of the human brain, spine, knee and abdomen. We have created a MR image database that consists of 25 original reference images and 750 distorted images. The reference images were distorted with six types of distortions: Rician Noise, Gaussian White Noise, Gaussian Blur, DCT compression, JPEG compression and JPEG2000 compression, at various levels of distortion. Twenty eight subjects were chosen to evaluate the images resulting in a total of 21,700 human evaluations. The raw scores were then converted to Difference Mean Opinion Score (DMOS). Thirteen objective FR-IQA metrics were used to determine the validity of the subjective DMOS. The results indicate a high correlation between the subjective and objective assessment of the MR images. The Noise Quality Measurement (NQM) has the highest correlation with DMOS, where the mean Pearson Linear Correlation Coefficient (PLCC) and Spearman Rank Order Correlation Coefficient (SROCC) are 0.936 and 0.938 respectively. The Universal Quality Index (UQI) has the lowest correlation with DMOS, where the mean PLCC and SROCC are 0.807 and 0.815 respectively. Student's T-test was used to find the difference in performance of FR-IQA across different types of distortion. The superior IQAs tested statistically are UQI for Rician noise images, Visual Information Fidelity (VIF) for Gaussian blur images, NQM for both DCT and JPEG compressed images, Peak Signal-to-Noise Ratio (PSNR) for JPEG2000 compressed images.
    Matched MeSH terms: Magnetic Resonance Imaging/methods*
  6. Simultaneous EEG-fMRI for working memory of the human brain
    Ahmad RF, Malik AS, Kamel N, Reza F, Abdullah JM
    Australas Phys Eng Sci Med, 2016 Jun;39(2):363-78.
    PMID: 27043850 DOI: 10.1007/s13246-016-0438-x
    Memory plays an important role in human life. Memory can be divided into two categories, i.e., long term memory and short term memory (STM). STM or working memory (WM) stores information for a short span of time and it is used for information manipulations and fast response activities. WM is generally involved in the higher cognitive functions of the brain. Different studies have been carried out by researchers to understand the WM process. Most of these studies were based on neuroimaging modalities like fMRI, EEG, MEG etc., which use standalone processes. Each neuroimaging modality has some pros and cons. For example, EEG gives high temporal resolution but poor spatial resolution. On the other hand, the fMRI results have a high spatial resolution but poor temporal resolution. For a more in depth understanding and insight of what is happening inside the human brain during the WM process or during cognitive tasks, high spatial as well as high temporal resolution is desirable. Over the past decade, researchers have been working to combine different modalities to achieve a high spatial and temporal resolution at the same time. Developments of MRI compatible EEG equipment in recent times have enabled researchers to combine EEG-fMRI successfully. The research publications in simultaneous EEG-fMRI have been increasing tremendously. This review is focused on the WM research involving simultaneous EEG-fMRI data acquisition and analysis. We have covered the simultaneous EEG-fMRI application in WM and data processing. Also, it adds to potential fusion methods which can be used for simultaneous EEG-fMRI for WM and cognitive tasks.
    Matched MeSH terms: Magnetic Resonance Imaging/methods*
  7. Contrast media induced transient cortical blindness
    Balasingam S, Azman RR, Nazri M
    QJM, 2016 Feb;109(2):121-2.
    PMID: 26101228 DOI: 10.1093/qjmed/hcv121
    Matched MeSH terms: Magnetic Resonance Imaging/methods
  8. Fulltext Automatic Region-Based Brain Classification of MRI-T1 Data
    Yazdani S, Yusof R, Karimian A, Mitsukira Y, Hematian A
    PLoS One, 2016;11(4):e0151326.
    PMID: 27096925 DOI: 10.1371/journal.pone.0151326
    Image segmentation of medical images is a challenging problem with several still not totally solved issues, such as noise interference and image artifacts. Region-based and histogram-based segmentation methods have been widely used in image segmentation. Problems arise when we use these methods, such as the selection of a suitable threshold value for the histogram-based method and the over-segmentation followed by the time-consuming merge processing in the region-based algorithm. To provide an efficient approach that not only produce better results, but also maintain low computational complexity, a new region dividing based technique is developed for image segmentation, which combines the advantages of both regions-based and histogram-based methods. The proposed method is applied to the challenging applications: Gray matter (GM), White matter (WM) and cerebro-spinal fluid (CSF) segmentation in brain MR Images. The method is evaluated on both simulated and real data, and compared with other segmentation techniques. The obtained results have demonstrated its improved performance and robustness.
    Matched MeSH terms: Magnetic Resonance Imaging/methods*
  9. Endoscopic transpterygoidal repair of a large cranial defect with cerebrospinal fluid leak in a patient with extensive osteoradionecrosis of the skull base: case report and technical note
    Brand Y, Lim E, Waran V, Prepageran N
    J Laryngol Otol, 2015 Dec;129(12):1243-7.
    PMID: 26412297 DOI: 10.1017/S0022215115002601
    Endoscopic endonasal techniques have recently become the method of choice in dealing with cerebrospinal fluid leak involving the anterior cranial fossa. However, most surgeons prefer an intracranial approach when leaks involve the middle cranial fossa. This case report illustrates the possibilities of using endoscopic techniques for cerebrospinal fluid leaks involving the middle fossa.
    Matched MeSH terms: Magnetic Resonance Imaging/methods
  10. Improving magnetic resonance imaging (MRI) examinations: Development and evaluation of an intervention to reduce movement in scanners and facilitate scan completion
    Powell R, Ahmad M, Gilbert FJ, Brian D, Johnston M
    Br J Health Psychol, 2015 Sep;20(3):449-65.
    PMID: 25639980 DOI: 10.1111/bjhp.12132
    The movement of patients in magnetic resonance imaging (MRI) scanners results in motion artefacts which impair image quality. Non-completion of scans leads to delay in diagnosis and increased costs. This study aimed to develop and evaluate an intervention to enable patients to stay still in MRI scanners (reducing motion artefacts) and to enhance scan completion. Successful scan outcome was deemed to be completing the scan with no motion artefacts.
    Matched MeSH terms: Magnetic Resonance Imaging/methods*
  11. An online open-source tool for automated quantification of liver and myocardial iron concentrations by T2* magnetic resonance imaging
    Git KA, Fioravante LA, Fernandes JL
    Br J Radiol, 2015 Sep;88(1053):20150269.
    PMID: 26118302 DOI: 10.1259/bjr.20150269
    To assess whether an online open-source tool would provide accurate calculations of T2(*) values for iron concentrations in the liver and heart compared with a standard reference software.
    Matched MeSH terms: Magnetic Resonance Imaging/methods*
  12. Boosting diagnosis accuracy of Alzheimer's disease using high dimensional recognition of longitudinal brain atrophy patterns
    Farzan A, Mashohor S, Ramli AR, Mahmud R
    Behav Brain Res, 2015 Sep 1;290:124-30.
    PMID: 25889456 DOI: 10.1016/j.bbr.2015.04.010
    Boosting accuracy in automatically discriminating patients with Alzheimer's disease (AD) and normal controls (NC), based on multidimensional classification of longitudinal whole brain atrophy rates and their intermediate counterparts in analyzing magnetic resonance images (MRI).
    Matched MeSH terms: Magnetic Resonance Imaging/methods*
  13. Alpha shape theory for 3D visualization and volumetric measurement of brain tumor progression using magnetic resonance images
    Hamoud Al-Tamimi MS, Sulong G, Shuaib IL
    Magn Reson Imaging, 2015 Jul;33(6):787-803.
    PMID: 25865822 DOI: 10.1016/j.mri.2015.03.008
    Resection of brain tumors is a tricky task in surgery due to its direct influence on the patients' survival rate. Determining the tumor resection extent for its complete information via-à-vis volume and dimensions in pre- and post-operative Magnetic Resonance Images (MRI) requires accurate estimation and comparison. The active contour segmentation technique is used to segment brain tumors on pre-operative MR images using self-developed software. Tumor volume is acquired from its contours via alpha shape theory. The graphical user interface is developed for rendering, visualizing and estimating the volume of a brain tumor. Internet Brain Segmentation Repository dataset (IBSR) is employed to analyze and determine the repeatability and reproducibility of tumor volume. Accuracy of the method is validated by comparing the estimated volume using the proposed method with that of gold-standard. Segmentation by active contour technique is found to be capable of detecting the brain tumor boundaries. Furthermore, the volume description and visualization enable an interactive examination of tumor tissue and its surrounding. Admirable features of our results demonstrate that alpha shape theory in comparison to other existing standard methods is superior for precise volumetric measurement of tumor.
    Matched MeSH terms: Magnetic Resonance Imaging/methods*
  14. Regional assessment of LV wall in infarcted heart using tagged MRI and cardiac modelling
    Jahanzad Z, Liew YM, Bilgen M, McLaughlin RA, Leong CO, Chee KH, et al.
    Phys Med Biol, 2015 May 21;60(10):4015-31.
    PMID: 25919317 DOI: 10.1088/0031-9155/60/10/4015
    A segmental two-parameter empirical deformable model is proposed for evaluating regional motion abnormality of the left ventricle. Short-axis tagged MRI scans were acquired from 10 healthy subjects and 10 postinfarct patients. Two motion parameters, contraction and rotation, were quantified for each cardiac segment by fitting the proposed model using a non-rigid registration algorithm. The accuracy in motion estimation was compared to a global model approach. Motion parameters extracted from patients were correlated to infarct transmurality assessed with delayed-contrast-enhanced MRI. The proposed segmental model allows markedly improved accuracy in regional motion analysis as compared to the global model for both subject groups (1.22-1.40 mm versus 2.31-2.55 mm error). By end-systole, all healthy segments experienced radial displacement by ~25-35% of the epicardial radius, whereas the 3 short-axis planes rotated differently (basal: 3.3°; mid:  -1° and apical:  -4.6°) to create a twisting motion. While systolic contraction showed clear correspondence to infarct transmurality, rotation was nonspecific to either infarct location or transmurality but could indicate the presence of functional abnormality. Regional contraction and rotation derived using this model could potentially aid in the assessment of severity of regional dysfunction of infarcted myocardium.
    Matched MeSH terms: Magnetic Resonance Imaging/methods*
  15. Differentiating multiple-system atrophy from Parkinson's disease
    Ramli N, Nair SR, Ramli NM, Lim SY
    Clin Radiol, 2015 May;70(5):555-64.
    PMID: 25752581 DOI: 10.1016/j.crad.2015.01.005
    The purpose of this review is to illustrate the differentiating features of multiple-system atrophy from Parkinson's disease at MRI. The various MRI sequences helpful in the differentiation will be discussed, including newer methods, such as diffusion tensor imaging, MR spectroscopy, and nuclear imaging.
    Matched MeSH terms: Magnetic Resonance Imaging/methods*
  16. The effects of aging on the brain activation pattern during a speech perception task: an fMRI study
    Manan HA, Franz EA, Yusoff AN, Mukari SZ
    Aging Clin Exp Res, 2015 Feb;27(1):27-36.
    PMID: 24906677 DOI: 10.1007/s40520-014-0240-0
    In the present study, brain activation associated with speech perception processing was examined across four groups of adult participants with age ranges between 20 and 65 years, using functional MRI (fMRI). Cognitive performance demonstrates that performance accuracy declines with age. fMRI results reveal that all four groups of participants activated the same brain areas. The same brain activation pattern was found in all activated areas (except for the right superior temporal gyrus and right middle temporal gyrus); brain activity was increased from group 1 (20-29 years) to group 2 (30-39 years). However, it decreased in group 3 (40-49 years) with further decreases in group 4 participants (50-65 years). Result also reveals that three brain areas (superior temporal gyrus, Heschl's gyrus and cerebellum) showed changes in brain laterality in the older participants, akin to a shift from left-lateralized to right-lateralized activity. The onset of this change was different across brain areas. Based on these findings we suggest that, whereas all four groups of participants used the same areas in processing, the engagement and recruitment of those areas differ with age as the brain grows older. Findings are discussed in the context of corroborating evidence of neural changes with age.
    Matched MeSH terms: Magnetic Resonance Imaging/methods*
  17. Multinuclear MR and multilevel data processing: an insight into morphologic assessment of in vivo knee articular cartilage
    Hani AF, Kumar D, Malik AS, Walter N, Razak R, Kiflie A
    Acad Radiol, 2015 Jan;22(1):93-104.
    PMID: 25481518 DOI: 10.1016/j.acra.2014.08.008
    Quantitative assessment of knee articular cartilage (AC) morphology using magnetic resonance (MR) imaging requires an accurate segmentation and 3D reconstruction. However, automatic AC segmentation and 3D reconstruction from hydrogen-based MR images alone is challenging because of inhomogeneous intensities, shape irregularity, and low contrast existing in the cartilage region. Thus, the objective of this research was to provide an insight into morphologic assessment of AC using multilevel data processing of multinuclear ((23)Na and (1)H) MR knee images.
    Matched MeSH terms: Magnetic Resonance Imaging/methods*
  18. Non-invasive and in vivo assessment of osteoarthritic articular cartilage: a review on MRI investigations
    Hani AF, Kumar D, Malik AS, Ahmad RM, Razak R, Kiflie A
    Rheumatol Int, 2015 Jan;35(1):1-16.
    PMID: 24879325 DOI: 10.1007/s00296-014-3052-9
    Early detection of knee osteoarthritis (OA) is of great interest to orthopaedic surgeons, rheumatologists, radiologists, and researchers because it would allow physicians to provide patients with treatments and advice to slow the onset or progression of the disease. Early detection can be achieved by identifying early changes in selected features of degenerative articular cartilage (AC) using non-invasive imaging modalities. Magnetic resonance imaging (MRI) is becoming the standard for assessment of OA. The aim of this paper was to review the influence of MRI on the selection, detection, and measurement of AC features associated with early OA. Our review of the literature indicates that the changes associated with early OA are in cartilage thickness, cartilage volume, cartilage water content, and proteoglycan content that can be accurately, consistently, and non-invasively measured using MRI. Choosing an MR pulse sequence that provides the capability to assess cartilage physiology and morphology in a single acquisition and advanced multi-nuclei MRI is desirable. The results of the review indicate that using an ultra-high magnetic strength, MR imager does not affect early OA detection. In conclusion, MRI is currently the most suitable modality for early detection of knee OA, and future research should focus on the quantitative evaluation of early OA features using advances in MR hardware, software, and data processing with sophisticated image/pattern recognition techniques.
    Matched MeSH terms: Magnetic Resonance Imaging/methods*
  19. Fulltext An Automated and Intelligent Medical Decision Support System for Brain MRI Scans Classification
    Siddiqui MF, Reza AW, Kanesan J
    PLoS One, 2015;10(8):e0135875.
    PMID: 26280918 DOI: 10.1371/journal.pone.0135875
    A wide interest has been observed in the medical health care applications that interpret neuroimaging scans by machine learning systems. This research proposes an intelligent, automatic, accurate, and robust classification technique to classify the human brain magnetic resonance image (MRI) as normal or abnormal, to cater down the human error during identifying the diseases in brain MRIs. In this study, fast discrete wavelet transform (DWT), principal component analysis (PCA), and least squares support vector machine (LS-SVM) are used as basic components. Firstly, fast DWT is employed to extract the salient features of brain MRI, followed by PCA, which reduces the dimensions of the features. These reduced feature vectors also shrink the memory storage consumption by 99.5%. At last, an advanced classification technique based on LS-SVM is applied to brain MR image classification using reduced features. For improving the efficiency, LS-SVM is used with non-linear radial basis function (RBF) kernel. The proposed algorithm intelligently determines the optimized values of the hyper-parameters of the RBF kernel and also applied k-fold stratified cross validation to enhance the generalization of the system. The method was tested by 340 patients' benchmark datasets of T1-weighted and T2-weighted scans. From the analysis of experimental results and performance comparisons, it is observed that the proposed medical decision support system outperformed all other modern classifiers and achieves 100% accuracy rate (specificity/sensitivity 100%/100%). Furthermore, in terms of computation time, the proposed technique is significantly faster than the recent well-known methods, and it improves the efficiency by 71%, 3%, and 4% on feature extraction stage, feature reduction stage, and classification stage, respectively. These results indicate that the proposed well-trained machine learning system has the potential to make accurate predictions about brain abnormalities from the individual subjects, therefore, it can be used as a significant tool in clinical practice.
    Matched MeSH terms: Magnetic Resonance Imaging/methods
  20. Breast cancer detection from MR images through an auto-probing discrete Fourier transform system
    Sim KS, Chia FK, Nia ME, Tso CP, Chong AK, Abbas SF, et al.
    Comput Biol Med, 2014 Jun;49:46-59.
    PMID: 24736203 DOI: 10.1016/j.compbiomed.2014.03.003
    A computer-aided detection auto-probing (CADAP) system is presented for detecting breast lesions using dynamic contrast enhanced magnetic resonance imaging, through a spatial-based discrete Fourier transform. The stand-alone CADAP system reduces noise, refines region of interest (ROI) automatically, and detects the breast lesion with minimal false positive detection. The lesions are then classified and colourised according to their characteristics, whether benign, suspicious or malignant. To enhance the visualisation, the entire analysed ROI is constructed into a 3-D image, so that the user can diagnose based on multiple views on the ROI. The proposed method has been applied to 101 sets of digital images, and the results compared with the biopsy results done by radiologists. The proposed scheme is able to identify breast cancer regions accurately and efficiently.
    Matched MeSH terms: Magnetic Resonance Imaging/methods*
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