Displaying publications 1 - 20 of 53 in total

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  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. 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.

  5. Fum WKS, Wong JHD, Tan LK
    Phys Med, 2021 Apr;84:228-240.
    PMID: 33849785 DOI: 10.1016/j.ejmp.2021.03.004
    PURPOSE: This systematic review aims to understand the dose estimation approaches and their major challenges. Specifically, we focused on state-of-the-art Monte Carlo (MC) methods in fluoroscopy-guided interventional procedures.

    METHODS: All relevant studies were identified through keyword searches in electronic databases from inception until September 2020. The searched publications were reviewed, categorised and analysed based on their respective methodology.

    RESULTS: Hundred and one publications were identified which utilised existing MC-based applications/programs or customised MC simulations. Two outstanding challenges were identified that contribute to uncertainties in the virtual simulation reconstruction. The first challenge involves the use of anatomical models to represent individuals. Currently, phantom libraries best balance the needs of clinical practicality with those of specificity. However, mismatches of anatomical variations including body size and organ shape can create significant discrepancies in dose estimations. The second challenge is that the exact positioning of the patient relative to the beam is generally unknown. Most dose prediction models assume the patient is located centrally on the examination couch, which can lead to significant errors.

    CONCLUSION: The continuing rise of computing power suggests a near future where MC methods become practical for routine clinical dosimetry. Dynamic, deformable phantoms help to improve patient specificity, but at present are only limited to adjustment of gross body volume. Dynamic internal organ displacement or reshaping is likely the next logical frontier. Image-based alignment is probably the most promising solution to enable this, but it must be automated to be clinically practical.

  6. 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.
  7. 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.
  8. 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.
  9. 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.
  10. 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
  11. 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.
  12. 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.

  13. 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 

  14. 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.
  15. Ramli N, Lim CH, Rajagopal R, Tan LK, Seow P, Ariffin H
    Pediatr Radiol, 2020 08;50(9):1277-1283.
    PMID: 32591982 DOI: 10.1007/s00247-020-04717-x
    BACKGROUND: Intrathecal and intravenous chemotherapy, specifically methotrexate, might contribute to neural microstructural damage.

    OBJECTIVE: To assess, by diffusion tensor imaging, microstructural integrity of white matter in paediatric patients with acute lymphoblastic leukaemia (ALL) following intrathecal and intravenous chemotherapy.

    MATERIALS AND METHODS: Eleven children diagnosed with de novo ALL underwent MRI scans of the brain with diffusion tensor imaging (DTI) prior to commencement of chemotherapy and at 12 months after diagnosis, using a 3-tesla (T) MRI scanner. We investigated the changes in DTI parameters in white matter tracts before and after chemotherapy using tract-based spatial statistics overlaid on the International Consortium of Brain Mapping DTI-81 atlas. All of the children underwent formal neurodevelopmental assessment at the two study time points.

    RESULTS: Whole-brain DTI analysis showed significant changes between the two time points, affecting several white matter tracts. The tracts demonstrated longitudinal changes of decreasing mean and radial diffusivity. The neurodevelopment of the children was near compatible for age at the end of ALL treatment.

    CONCLUSION: The quantification of white matter tracts changes in children undergoing chemotherapy showed improving longitudinal values in DTI metrics (stable fractional anisotropy, decreasing mean and radial diffusivity), which are incompatible with deterioration of microstructural integrity in these children.

  16. Goh CH, Tan LK, Lovell NH, Ng SC, Tan MP, Lim E
    Comput Methods Programs Biomed, 2020 Nov;196:105596.
    PMID: 32580054 DOI: 10.1016/j.cmpb.2020.105596
    BACKGROUND AND OBJECTIVES: Continuous monitoring of physiological parameters such as photoplethysmography (PPG) has attracted increased interest due to advances in wearable sensors. However, PPG recordings are susceptible to various artifacts, and thus reducing the reliability of PPG-driven parameters, such as oxygen saturation, heart rate, blood pressure and respiration. This paper proposes a one-dimensional convolution neural network (1-D-CNN) to classify five-second PPG segments into clean or artifact-affected segments, avoiding data-dependent pulse segmentation techniques and heavy manual feature engineering.

    METHODS: Continuous raw PPG waveforms were blindly allocated into segments with an equal length (5s) without leveraging any pulse location information and were normalized with Z-score normalization methods. A 1-D-CNN was designed to automatically learn the intrinsic features of the PPG waveform, and perform the required classification. Several training hyperparameters (initial learning rate and gradient threshold) were varied to investigate the effect of these parameters on the performance of the network. Subsequently, this proposed network was trained and validated with 30 subjects, and then tested with eight subjects, with our local dataset. Moreover, two independent datasets downloaded from the PhysioNet MIMIC II database were used to evaluate the robustness of the proposed network.

    RESULTS: A 13 layer 1-D-CNN model was designed. Within our local study dataset evaluation, the proposed network achieved a testing accuracy of 94.9%. The classification accuracy of two independent datasets also achieved satisfactory accuracy of 93.8% and 86.7% respectively. Our model achieved a comparable performance with most reported works, with the potential to show good generalization as the proposed network was evaluated with multiple cohorts (overall accuracy of 94.5%).

    CONCLUSION: This paper demonstrated the feasibility and effectiveness of applying blind signal processing and deep learning techniques to PPG motion artifact detection, whereby manual feature thresholding was avoided and yet a high generalization ability was achieved.

  17. 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.

  18. Ramli N, Yap A, Muridan R, Seow P, Rahmat K, Fong CY, et al.
    Clin Radiol, 2020 01;75(1):77.e15-77.e22.
    PMID: 31668796 DOI: 10.1016/j.crad.2019.09.134
    AIM: To evaluate the microstructural abnormalities of the white matter tracts (WMT) using diffusion tensor imaging (DTI) in children with global developmental delay (GDD).

    MATERIALS AND METHODS: Sixteen children with GDD underwent magnetic resonance imaging (MRI) and cross-sectional DTI. Formal developmental assessment of all GDD patients was performed using the Mullen Scales of Early Learning. An automated processing pipeline for the WMT assessment was implemented. The DTI-derived metrics of the children with GDD were compared to healthy children with normal development (ND).

    RESULTS: Only two out of the 17 WMT demonstrated significant differences (p<0.05) in DTI parameters between the GDD and ND group. In the uncinate fasciculus (UF), the GDD group had lower mean values for fractional anisotropy (FA; 0.40 versus 0.44), higher values for mean diffusivity (0.96 versus 0.91×10-3 mm2/s) and radial diffusivity (0.75 versus 0.68×10-3 mm2/s) compared to the ND group. In the superior cerebellar peduncle (SCP), mean FA values were lower for the GDD group (0.38 versus 0.40). Normal myelination pattern of DTI parameters was deviated against age for GDD group for UF and SCP.

    CONCLUSION: The UF and SCP WMT showed microstructural changes suggestive of compromised white matter maturation in children with GDD. The DTI metrics have potential as imaging markers for inadequate white matter maturation in GDD children.

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