Displaying publications 1 - 20 of 34 in total

  1. Chia BL, Tan LK
    Am. J. Cardiol., 1984 May 01;53(9):1413.
    PMID: 6538741
  2. Thong KL, Tan LK, Ooi PT
    J. Sci. Food Agric., 2018 Jan;98(1):87-95.
    PMID: 28542807 DOI: 10.1002/jsfa.8442
    BACKGROUND: The objectives of the present study were to determine the antimicrobial resistance, virulotypes and genetic diversity of Yersinia enterocolitica isolated from uncooked porcine food and live pigs in Malaysia.

    RESULTS: Thirty-two non-repeat Y. enterocolitica strains of three bioserotypes (3 variant/O:3, n = 27; 1B/O:8, n = 3; 1A/O:5, n = 2) were analysed. Approximately 90% of strains were multidrug-resistant with a multiple antibiotic resistance index < 0.2 and the majority of the strains were resistant to nalidixic acid, clindamycin, ampicillin, ticarcillin, tetracycline and amoxicillin. Yersinia enterocolitica could be distinguished distinctly into three clusters by pulsed-field gel electrophoresis, with each belonging to a particular bioserotype. Strains of 3 variant/O:3 were more heterogeneous than others. Eleven of the 15 virulence genes tested (hreP, virF, rfbC, myfA, sat, inv, ail, ymoA, ystA, tccC, yadA) and pYV virulence plasmid were present in all the bioserotpe 3 variant/03 strains.

    CONCLUSION: The occurrence of virulent strains of Y. enterocolitica in pigs and porcine products reiterated that pigs are important reservoirs for Y. enterocolitica. The increasing trend of multidrug resistant strains is a public health concern. This is the first report on the occurrence of potential pathogenic and resistant strains of Y. enterocolitica in pigs in Malaysia. © 2017 Society of Chemical Industry.

  3. Tan LK, Ooi PT, Carniel E, Thong KL
    PLoS ONE, 2014;9(8):e106329.
    PMID: 25170941 DOI: 10.1371/journal.pone.0106329
    Y. enterocolitica and Y. pseudotuberculosis are important food borne pathogens. However, the presence of competitive microbiota makes the isolation of Y. enterocolitica and Y. pseudotuberculosis from naturally contaminated foods difficult. We attempted to evaluate the performance of a modified Cefsulodin-Irgasan-Novobiocin (CIN) agar in the differentiation of Y. enterocolitica from non-Yersinia species, particularly the natural intestinal microbiota. The modified CIN enabled the growth of Y. enterocolitica colonies with the same efficiency as CIN and Luria-Bertani agar. The detection limits of the modified CIN for Y. enterocolitica in culture medium (10 cfu/ml) and in artificially contaminated pork (10(4) cfu/ml) were also comparable to those of CIN. However, the modified CIN provided a better discrimination of Yersinia colonies from other bacteria exhibiting Yersinia-like colonies on CIN (H2S-producing Citrobacter freundii, C. braakii, Enterobacter cloacae, Aeromonas hydrophila, Providencia rettgeri, and Morganella morganii). The modified CIN exhibited a higher recovery rate of Y. enterocolitica from artificially prepared bacterial cultures and naturally contaminated samples compared with CIN. Our results thus demonstrated that the use of modified CIN may be a valuable means to increase the recovery rate of food borne Yersinia from natural samples, which are usually contaminated by multiple types of bacteria.
  4. Sidek S, Ramli N, Rahmat K, Ramli NM, Abdulrahman F, Tan LK
    Eur J Radiol, 2014 Aug;83(8):1437-41.
    PMID: 24908588 DOI: 10.1016/j.ejrad.2014.05.014
    To evaluate whether MR diffusion tensor imaging (DTI) of the optic nerve and optic radiation in glaucoma patients provides parameters to discriminate between mild and severe glaucoma and to determine whether DTI derived indices correlate with retinal nerve fibre layer (RNFL) thickness.
  5. Loh KB, Ramli N, Tan LK, Roziah M, Rahmat K, Ariffin H
    Eur Radiol, 2012 Jul;22(7):1413-26.
    PMID: 22434420 DOI: 10.1007/s00330-012-2396-3
    OBJECTIVES: The degree and status of white matter myelination can be sensitively monitored using diffusion tensor imaging (DTI). This study looks at the measurement of fractional anistropy (FA) and mean diffusivity (MD) using an automated ROI with an existing DTI atlas.

    METHODS: Anatomical MRI and structural DTI were performed cross-sectionally on 26 normal children (newborn to 48 months old), using 1.5-T MRI. The automated processing pipeline was implemented to convert diffusion-weighted images into the NIfTI format. DTI-TK software was used to register the processed images to the ICBM DTI-81 atlas, while AFNI software was used for automated atlas-based volumes of interest (VOIs) and statistical value extraction.

    RESULTS: DTI exhibited consistent grey-white matter contrast. Triphasic temporal variation of the FA and MD values was noted, with FA increasing and MD decreasing rapidly early in the first 12 months. The second phase lasted 12-24 months during which the rate of FA and MD changes was reduced. After 24 months, the FA and MD values plateaued.

    CONCLUSION: DTI is a superior technique to conventional MR imaging in depicting WM maturation. The use of the automated processing pipeline provides a reliable environment for quantitative analysis of high-throughput DTI data.

    KEY POINTS: Diffusion tensor imaging outperforms conventional MRI in depicting white matter maturation. • DTI will become an important clinical tool for diagnosing paediatric neurological diseases. • DTI appears especially helpful for developmental abnormalities, tumours and white matter disease. • An automated processing pipeline assists quantitative analysis of high throughput DTI data.

  6. Radhakrishnan AK, Raj VL, Tan LK, Liam CK
    Biomed Res Int, 2013;2013:981012.
    PMID: 23865080 DOI: 10.1155/2013/981012
    Asthma susceptibility genes are mapped to a region on human chromosome 5q31-q33, which contains a cluster of proinflammatory cytokine genes such as interleukin-13 (IL-13), which is associated with asthma. This study investigated the allele frequencies of two single nucleotide polymorphisms (SNPs) (-1111C>T and 4257C>A) in the IL-13 gene between asthmatics and healthy volunteers as well as the relationship between these SNPs and IL-13 production. DNA extracted from buffy coat of asthmatic and control subjects was genotyped using the PCR-RFLP method. Amount of IL-13 produced by mitogen-stimulated peripheral blood leucocytes PBLs (PBLs) was determined by ELISA. The frequencies of the -1111C and 4257G wild-type alleles were 0.52 and 0.55 in asthmatics and were 0.67 and 0.56 in controls. A significant (P < 0.05) association was found between genotype and allele frequencies of SNP at position -1111C>T between asthmatic and control groups (OR, 1.810; 95% CI = 1.184 to 2.767; P < 0.05). The mitogen-stimulated PBLs from asthmatics produced higher amounts of IL-13 production (P < 0.001). The 4257GA heterozygous and 4257AA homozygous mutant alleles were associated with higher IL-13 production in asthmatics (P < 0.05). Our results show that the -1111T mutant allele are associated with asthma and the 4257A mutant alleles are associated with elevated IL-13 production.
  7. Tan LK, Wong JH, Ng KH
    AJR Am J Roentgenol, 2006 Mar;186(3):898-901.
    PMID: 16498128
    The purpose of this article was to develop a low-cost method for high-quality remote capturing and recording of multimedia presentations.
  8. Tan LK, Liew YM, Lim E, McLaughlin RA
    Med Image Anal, 2017 Apr 12;39:78-86.
    PMID: 28437634 DOI: 10.1016/j.media.2017.04.002
    Automated left ventricular (LV) segmentation is crucial for efficient quantification of cardiac function and morphology to aid subsequent management of cardiac pathologies. In this paper, we parameterize the complete (all short axis slices and phases) LV segmentation task in terms of the radial distances between the LV centerpoint and the endo- and epicardial contours in polar space. We then utilize convolutional neural network regression to infer these parameters. Utilizing parameter regression, as opposed to conventional pixel classification, allows the network to inherently reflect domain-specific physical constraints. We have benchmarked our approach primarily against the publicly-available left ventricle segmentation challenge (LVSC) dataset, which consists of 100 training and 100 validation cardiac MRI cases representing a heterogeneous mix of cardiac pathologies and imaging parameters across multiple centers. Our approach attained a .77 Jaccard index, which is the highest published overall result in comparison to other automated algorithms. To test general applicability, we also evaluated against the Kaggle Second Annual Data Science Bowl, where the evaluation metric was the indirect clinical measures of LV volume rather than direct myocardial contours. Our approach attained a Continuous Ranked Probability Score (CRPS) of .0124, which would have ranked tenth in the original challenge. With this we demonstrate the effectiveness of convolutional neural network regression paired with domain-specific features in clinical segmentation.
  9. Veeramuthu V, Hariri F, Narayanan V, Tan LK, Ramli N, Ganesan D
    J. Oral Maxillofac. Surg., 2016 Jun;74(6):1197.e1-1197.e10.
    PMID: 26917201 DOI: 10.1016/j.joms.2016.01.042
    The aim of the present study was to establish the incidence of maxillofacial (MF) injury accompanying mild traumatic brain injury (mTBI) and the associated neurocognitive deficits and white matter changes.
  10. 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 

  11. Ng CG, Tan LK, Gill JS, Koh OH, Jambunathan S, Pillai SK, et al.
    Asia Pac Psychiatry, 2013 Apr;5 Suppl 1:118-22.
    PMID: 23857847 DOI: 10.1111/appy.12056
    INTRODUCTION: This study aims to examine the validity and reliability of the Malay version of Attitudes toward Lesbians and Gay Men (MVATL/MVATG) among a group of medical students in Malaysia.
    METHODS: It is a cross-sectional study of 173 medical students in the Faculty of Medicine, University of Kuala Lumpur, Malaysia. The participants were given the MVATL/MVATG, Index of Attitudes toward Homosexuals (IATH), Homosexuality Attitude Scale (HAS) and the English version of Attitude toward Lesbians and Gay Men. Two weeks later, these students were given the MVATLG again.
    RESULTS: Significant correlation was found between the individual scores of MVATL and MVATG with IATH and HAS in the results. The scale was able to differentiate Muslim and Non-Muslim subjects. The internal consistency (Cronbach's alpha) of both the MVATL and MVATG were good, at 0.76 and 0.82, respectively. The parallel form reliability (Pearson's correlation) of MVATL was 0.0.73 and 0.74 for MVATG. The test-retest reliability of MVATL/MVATG was good (Intraclass correlation coefficient, ICC = 0.67 for MVATL and 0.60 for MVATG).
    DISCUSSION: The MVATLG demonstrated good psychometric properties in measuring attitudes toward homosexuality among a group of medical students in Malaysia and it could be used as a simple instrument on young educated Malaysian adults.
    KEYWORDS: Malaysia; attitude; gay men; homosexuality; lesbians; validation
  12. Ho WS, Tan LK, Ooi PT, Yeo CC, Thong KL
    BMC Vet. Res., 2013;9:109.
    PMID: 23731465 DOI: 10.1186/1746-6148-9-109
    Postweaning diarrhea caused by pathogenic Escherichia coli, in particular verotoxigenic E. coli (VTEC), has caused significant economic losses in the pig farming industry worldwide. However, there is limited information on VTEC in Malaysia. The objective of this study was to characterize pathogenic E. coli isolated from post-weaning piglets and growers with respect to their antibiograms, carriage of extended-spectrum beta-lactamases, pathotypes, production of hemolysins and fimbrial adhesins, serotypes, and genotypes.
  13. Nair SR, Tan LK, Mohd Ramli N, Lim SY, Rahmat K, Mohd Nor H
    Eur Radiol, 2013 Jun;23(6):1459-66.
    PMID: 23300042 DOI: 10.1007/s00330-012-2759-9
    OBJECTIVE: To develop a decision tree based on standard magnetic resonance imaging (MRI) and diffusion tensor imaging to differentiate multiple system atrophy (MSA) from Parkinson's disease (PD).

    METHODS: 3-T brain MRI and DTI (diffusion tensor imaging) were performed on 26 PD and 13 MSA patients. Regions of interest (ROIs) were the putamen, substantia nigra, pons, middle cerebellar peduncles (MCP) and cerebellum. Linear, volumetry and DTI (fractional anisotropy and mean diffusivity) were measured. A three-node decision tree was formulated, with design goals being 100 % specificity at node 1, 100 % sensitivity at node 2 and highest combined sensitivity and specificity at node 3.

    RESULTS: Nine parameters (mean width, fractional anisotropy (FA) and mean diffusivity (MD) of MCP; anteroposterior diameter of pons; cerebellar FA and volume; pons and mean putamen volume; mean FA substantia nigra compacta-rostral) showed statistically significant (P < 0.05) differences between MSA and PD with mean MCP width, anteroposterior diameter of pons and mean FA MCP chosen for the decision tree. Threshold values were 14.6 mm, 21.8 mm and 0.55, respectively. Overall performance of the decision tree was 92 % sensitivity, 96 % specificity, 92 % PPV and 96 % NPV. Twelve out of 13 MSA patients were accurately classified.

    CONCLUSION: Formation of the decision tree using these parameters was both descriptive and predictive in differentiating between MSA and PD.

    KEY POINTS: • Parkinson's disease and multiple system atrophy can be distinguished on MR imaging. • Combined conventional MRI and diffusion tensor imaging improves the accuracy of diagnosis. • A decision tree is descriptive and predictive in differentiating between clinical entities. • A decision tree can reliably differentiate Parkinson's disease from multiple system atrophy.

  14. Yong YL, Tan LK, McLaughlin RA, Chee KH, Liew YM
    J Biomed Opt, 2017 12;22(12):1-9.
    PMID: 29274144 DOI: 10.1117/1.JBO.22.12.126005
    Intravascular optical coherence tomography (OCT) is an optical imaging modality commonly used in the assessment of coronary artery diseases during percutaneous coronary intervention. Manual segmentation to assess luminal stenosis from OCT pullback scans is challenging and time consuming. We propose a linear-regression convolutional neural network to automatically perform vessel lumen segmentation, parameterized in terms of radial distances from the catheter centroid in polar space. Benchmarked against gold-standard manual segmentation, our proposed algorithm achieves average locational accuracy of the vessel wall of 22 microns, and 0.985 and 0.970 in Dice coefficient and Jaccard similarity index, respectively. The average absolute error of luminal area estimation is 1.38%. The processing rate is 40.6 ms per image, suggesting the potential to be incorporated into a clinical workflow and to provide quantitative assessment of vessel lumen in an intraoperative time frame.
  15. Wong YQ, Tan LK, Seow P, Tan MP, Abd Kadir KA, Vijayananthan A, et al.
    PLoS ONE, 2017;12(6):e0179895.
    PMID: 28658309 DOI: 10.1371/journal.pone.0179895
    OBJECTIVES: This study assesses the whole brain microstructural integrity of white matter tracts (WMT) among older individuals with a history of falls compared to non-fallers.

    METHODS: 85 participants (43 fallers, 42 non-fallers) were evaluated with conventional MRI and diffusion tensor imaging (DTI) sequences of the brain. DTI metrics were obtained from selected WMT using tract-based spatial statistics (TBSS) method. This was followed by binary logistic regression to investigate the clinical variables that could act as confounding elements on the outcomes. The TBSS analysis was then repeated, but this time including all significant predictor variables from the regression analysis as TBSS covariates.

    RESULTS: The mean diffusivity (MD) and axial diffusivity (AD) and to a lesser extent radial diffusivity (RD) values of the projection fibers and commissural bundles were significantly different in fallers (p < 0.05) compared to non-fallers. However, the final logistic regression model obtained showed that only functional reach, white matter lesion volume, hypertension and orthostatic hypotension demonstrated statistical significant differences between fallers and non-fallers. No significant differences were found in the DTI metrics when taking into account age and the four variables as covariates in the repeated analysis.

    CONCLUSION: This DTI study of 85 subjects, do not support DTI metrics as a singular factor that contributes independently to the fall outcomes. Other clinical and imaging factors have to be taken into account.

  16. Tan LK, McLaughlin RA, Lim E, Abdul Aziz YF, Liew YM
    J Magn Reson Imaging, 2018 07;48(1):140-152.
    PMID: 29316024 DOI: 10.1002/jmri.25932
    BACKGROUND: Left ventricle (LV) structure and functions are the primary assessment performed in most clinical cardiac MRI protocols. Fully automated LV segmentation might improve the efficiency and reproducibility of clinical assessment.

    PURPOSE: To develop and validate a fully automated neural network regression-based algorithm for segmentation of the LV in cardiac MRI, with full coverage from apex to base across all cardiac phases, utilizing both short axis (SA) and long axis (LA) scans.

    STUDY TYPE: Cross-sectional survey; diagnostic accuracy.

    SUBJECTS: In all, 200 subjects with coronary artery diseases and regional wall motion abnormalities from the public 2011 Left Ventricle Segmentation Challenge (LVSC) database; 1140 subjects with a mix of normal and abnormal cardiac functions from the public Kaggle Second Annual Data Science Bowl database.

    FIELD STRENGTH/SEQUENCE: 1.5T, steady-state free precession.

    ASSESSMENT: Reference standard data generated by experienced cardiac radiologists. Quantitative measurement and comparison via Jaccard and Dice index, modified Hausdorff distance (MHD), and blood volume.

    STATISTICAL TESTS: Paired t-tests compared to previous work.

    RESULTS: Tested against the LVSC database, we obtained 0.77 ± 0.11 (Jaccard index) and 1.33 ± 0.71 mm (MHD), both metrics demonstrating statistically significant improvement (P < 0.001) compared to previous work. Tested against the Kaggle database, the signed difference in evaluated blood volume was +7.2 ± 13.0 mL and -19.8 ± 18.8 mL for the end-systolic (ES) and end-diastolic (ED) phases, respectively, with a statistically significant improvement (P < 0.001) for the ED phase.

    DATA CONCLUSION: A fully automated LV segmentation algorithm was developed and validated against a diverse set of cardiac cine MRI data sourced from multiple imaging centers and scanner types. The strong performance overall is suggestive of practical clinical utility.

    LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018.

  17. Tan LK, Liew YM, Lim E, Abdul Aziz YF, Chee KH, McLaughlin RA
    Med Biol Eng Comput, 2018 Jun;56(6):1053-1062.
    PMID: 29147835 DOI: 10.1007/s11517-017-1750-7
    In this paper, we develop and validate an open source, fully automatic algorithm to localize the left ventricular (LV) blood pool centroid in short axis cardiac cine MR images, enabling follow-on automated LV segmentation algorithms. The algorithm comprises four steps: (i) quantify motion to determine an initial region of interest surrounding the heart, (ii) identify potential 2D objects of interest using an intensity-based segmentation, (iii) assess contraction/expansion, circularity, and proximity to lung tissue to score all objects of interest in terms of their likelihood of constituting part of the LV, and (iv) aggregate the objects into connected groups and construct the final LV blood pool volume and centroid. This algorithm was tested against 1140 datasets from the Kaggle Second Annual Data Science Bowl, as well as 45 datasets from the STACOM 2009 Cardiac MR Left Ventricle Segmentation Challenge. Correct LV localization was confirmed in 97.3% of the datasets. The mean absolute error between the gold standard and localization centroids was 2.8 to 4.7 mm, or 12 to 22% of the average endocardial radius. Graphical abstract Fully automated localization of the left ventricular blood pool in short axis cardiac cine MR images.
  18. Veeramuthu V, Seow P, Narayanan V, Wong JHD, Tan LK, Hernowo AT, et al.
    Acad Radiol, 2018 09;25(9):1167-1177.
    PMID: 29449141 DOI: 10.1016/j.acra.2018.01.005
    RATIONALE AND OBJECTIVES: Magnetic resonance spectroscopy is a noninvasive imaging technique that allows for reliable assessment of microscopic changes in brain cytoarchitecture, neuronal injuries, and neurochemical changes resultant from traumatic insults. We aimed to evaluate the acute alteration of neurometabolites in complicated and uncomplicated mild traumatic brain injury (mTBI) patients in comparison to control subjects using proton magnetic resonance spectroscopy (1H magnetic resonance spectroscopy).

    MATERIAL AND METHODS: Forty-eight subjects (23 complicated mTBI [cmTBI] patients, 12 uncomplicated mTBI [umTBI] patients, and 13 controls) underwent magnetic resonance imaging scan with additional single voxel spectroscopy sequence. Magnetic resonance imaging scans for patients were done at an average of 10 hours (standard deviation 4.26) post injury. The single voxel spectroscopy adjacent to side of injury and noninjury regions were analysed to obtain absolute concentrations and ratio relative to creatine of the neurometabolites. One-way analysis of variance was performed to compare neurometabolite concentrations of the three groups, and a correlation study was done between the neurometabolite concentration and Glasgow Coma Scale.

    RESULTS: Significant difference was found in ratio of N-acetylaspartate to creatine (NAA/Cr + PCr) (χ2(2) = 0.22, P 

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