Displaying publications 21 - 40 of 54 in total

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  1. Hamzah N, Narayanan V, Ramli N, Mustapha NA, Mohammad Tahir NA, Tan LK, et al.
    BMJ Open, 2019 09 18;9(9):e028711.
    PMID: 31537559 DOI: 10.1136/bmjopen-2018-028711
    OBJECTIVES: To measure the clinical, structural and functional changes of an individualised structured cognitive rehabilitation in mild traumatic brain injury (mTBI) population.

    SETTING: A single centre study, Malaysia.

    PARTICIPANTS: Adults aged between 18 and 60 years with mTBI as a result of road traffic accident, with no previous history of head trauma, minimum of 9 years education and abnormal cognition at 3 months will be included. The exclusion criteria include pre-existing chronic illness or neurological/psychiatric condition, long-term medication that affects cognitive/psychological status, clinical evidence of substance intoxication at the time of injury and major polytrauma. Based on multiple estimated calculations, the minimum intended sample size is 50 participants (Cohen's d effect size=0.35; alpha level of 0.05; 85% power to detect statistical significance; 40% attrition rate).

    INTERVENTIONS: Intervention group will receive individualised structured cognitive rehabilitation. Control group will receive the best patient-centred care for attention disorders. Therapy frequency for both groups will be 1 hour per week for 12 weeks.

    OUTCOME MEASURES: Primary: Neuropsychological Assessment Battery-Screening Module (S-NAB) scores. Secondary: Diffusion Tensor Imaging (DTI) parameters and Goal Attainment Scaling score (GAS).

    RESULTS: Results will include descriptive statistics of population demographics, CogniPlus cognitive program and metacognitive strategies. The effect of intervention will be the effect size of S-NAB scores and mean GAS T scores. DTI parameters will be compared between groups via repeated measure analysis. Correlation analysis of outcome measures will be calculated using Pearson's correlation coefficient.

    CONCLUSION: This is a complex clinical intervention with multiple outcome measures to provide a comprehensive evidence-based treatment model.

    ETHICS AND DISSEMINATION: The study protocol was approved by the Medical Research Ethics Committee UMMC (MREC ID NO: 2016928-4293). The findings of the trial will be disseminated through peer-reviewed journals and scientific conferences.

    TRIAL REGISTRATION NUMBER: NCT03237676.

  2. 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.
  3. 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.
  4. 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.

  5. Azlan CA, Wong JHD, Tan LK, A D Huri MSN, Ung NM, Pallath V, et al.
    Phys Med, 2020 Dec;80:10-16.
    PMID: 33070007 DOI: 10.1016/j.ejmp.2020.10.002
    PURPOSE: We present the implementation of e-learning in the Master of Medical Physics programme at the University of Malaya during a partial lockdown from March to June 2020 due to the COVID-19 pandemic.

    METHODS: Teaching and Learning (T&L) activities were conducted virtually on e-learning platforms. The students' experience and feedback were evaluated after 15 weeks.

    RESULTS: We found that while students preferred face-to-face, physical teaching, they were able to adapt to the new norm of e-learning. More than 60% of the students agreed that pre-recorded lectures and viewing videos of practical sessions, plus answering short questions, were beneficial. Certain aspects, such as hands-on practical and clinical experience, could never be replaced. The e-learning and study-from-home environment accorded a lot of flexibility. However, students also found it challenging to focus because of distractions, lack of engagement and mental stress. Technical problems, such as poor Internet connectivity and limited data plans, also compounded the problem.

    CONCLUSION: We expect e-learning to prevail in future. Hybrid learning strategies, which includes face-to-face classes and e-learning, will become common, at least in the medical physics programme of the University of Malaya even after the pandemic.

  6. 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.
  7. Hapuarachchi HC, Bandara KB, Sumanadasa SD, Hapugoda MD, Lai YL, Lee KS, et al.
    J Gen Virol, 2010 Apr;91(Pt 4):1067-76.
    PMID: 19955565 DOI: 10.1099/vir.0.015743-0
    Chikungunya fever swept across many South and South-east Asian countries, following extensive outbreaks in the Indian Ocean Islands in 2005. However, molecular epidemiological data to explain the recent spread and evolution of Chikungunya virus (CHIKV) in the Asian region are still limited. This study describes the genetic Characteristics and evolutionary relationships of CHIKV strains that emerged in Sri Lanka and Singapore during 2006-2008. The viruses isolated in Singapore also included those imported from the Maldives (n=1), India (n=2) and Malaysia (n=31). All analysed strains belonged to the East, Central and South African (ECSA) lineage and were evolutionarily more related to Indian than to Indian Ocean Islands strains. Unique genetic characteristics revealed five genetically distinct subpopulations of CHIKV in Sri Lanka and Singapore, which were likely to have emerged through multiple, independent introductions. The evolutionary network based on E1 gene sequences indicated the acquisition of an alanine to valine 226 substitution (E1-A226V) by virus strains of the Indian sublineage as a key evolutionary event that contributed to the transmission and spatial distribution of CHIKV in the region. The E1-A226V substitution was found in 95.7 % (133/139) of analysed isolates in 2008, highlighting the widespread establishment of mutated CHIKV strains in Sri Lanka, Singapore and Malaysia. As the E1-A226V substitution is known to enhance the transmissibility of CHIKV by Aedes albopictus mosquitoes, this observation has important implications for the design of vector control strategies to fight the virus in regions at risk of chikungunya fever.
  8. Roslan A, Kamsani SH, Nay TW, Tan KL, Hakim N, Tan AM, et al.
    Med J Malaysia, 2018 12;73(6):388-392.
    PMID: 30647209
    OBJECTIVE: Cardiac amyloidosis is under diagnosed and its prevalence is unknown. This is a retrospective, nonrandomised, single centre study of patients with endomyocardial biopsy-proven cardiac amyloidosis focusing on their echocardiographic and electrocardiogram (ECG) presentations. This is the first case series in Malaysia on this subject.

    METHODS: We identified all of our endomyocardial biopsyproven cardiac amyloidosis patients from January 2010 to January 2018 and reviewed their medical records. All patients echocardiographic and ECG findings reviewed and analysed comparing to basic mean population value.

    RESULTS: In total there are 13 biopsy-proven cardiac amyloidosis patients. All of the biopsies shows light chain (AL) amyloid. Majority of the patients (8, 61.5%) is male, and most of our patients (8, 61.5%) is Chinese. All seven patients on whom we performed deformation imaging have apical sparing pattern on longitudinal strain echocardiogram. Mean ejection fraction is 49.3%, (SD=7.9). All patients have concentric left ventricular hypertrophy and right ventricular hypertrophy. Diastolic dysfunction was present in all of our patients with nine out of 13 patients (69.2%) having restrictive filling patterns (E/A ≥2.0 E/e' ≥15). On electrocardiogram, 12 (92%) patients have prolonged PR interval (median 200ms, IQR 76.50ms) and 9 (69.2%) patients have pseudoinfarct pattern.

    CONCLUSION: Echocardiography plays an important role in diagnosing cardiac amyloidosis. The findings of concentric left ventricular hypertrophy with preserved ejection fraction without increased in loading condition should alert the clinician towards its possibility. This is further supported by right ventricular hypertrophy and particularly longitudinal strain imaging showing apical sparing pattern.

  9. Koo HC, Tan LK, Lim GP, Kee CC, Omar MA
    PMID: 36833764 DOI: 10.3390/ijerph20043058
    This study aimed to report the prevalence of obesity, classified using Asian cut-off, and its relationships with undiagnosed diabetes mellitus, high blood pressure, and hypercholesteremia. We analyzed the nationally representative data from 14,025 Malaysian adults who participated in the NHMS 2015. The relationship between obesity and undiagnosed diabetes mellitus, high blood pressure, and hypercholesteremia was determined using multivariable logistic regressions, and lifestyle risk factors and sociodemographic characteristics were adjusted. The undiagnosed high blood pressure group showed the highest proportionate of overweight/obese (80.0%, 95% CI: 78.1-81.8) and central obesity (61.8%, 95% CI: 59.3-64.2). Inverse association was observed between underweight with undiagnosed high blood pressure (aOR: 0.40, 95% CI: 0.26-0.61) and hypercholesterolemia (aOR: 0.75, 95% CI: 0.59-0.95) groups. In contrast, positive relationships were shown between overweight/obese and risk of undiagnosed diabetes mellitus (aOR: 1.65, 95% CI: 1.31-2.07), high blood pressure (aOR: 3.08, 95% CI: 2.60-3.63), and hypercholesterolemia (aOR: 1.37, 95% CI: 1.22-1.53). Likewise, central obesity was positively associated with a risk of undiagnosed diabetes mellitus (aOR: 1.40, 95% CI: 1.17-1.67), high blood pressure (aOR: 2.83, 95% CI: 2.45-3.26), and hypercholesterolemia (aOR: 1.26, 95% CI: 1.12-1.42). Our findings indicated the importance of periodical health examinations to assess the risk of non-communicable diseases among the general and abdominal obese Malaysian adults.
  10. 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.

  11. 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.

  12. Tan LK, Too CL, Diaz-Gallo LM, Wahinuddin S, Lau IS, Heselynn H, et al.
    Arthritis Res Ther, 2021 01 30;23(1):46.
    PMID: 33514426 DOI: 10.1186/s13075-021-02431-z
    BACKGROUND: Fine-mapping of human leukocyte antigen (HLA) region for rheumatoid arthritis (RA) risk factors has identified several HLA alleles and its corresponding amino acid residues as independent signals (i.e., HLA-A, HLA-B, HLA-DPB1, and HLA-DQA1 genes), in addition to the well-established genetic factor in HLA-DRB1 gene. However, this was mainly performed in the Caucasian and East Asian populations, and data from different Asian regions is less represented. We aimed to evaluate whether there are independent RA risk variants in both anti-citrullinated protein antibody (ACPA)-positive and ACPA-negative RA patients from the multi-ethnic Malaysian population, using the fine-mapping of HLA region strategy.

    METHODS: We imputed the classical HLA alleles, amino acids, and haplotypes using the Immunochip genotyping data of 1260 RA cases (i.e., 530 Malays, 259 Chinese, 412 Indians, and 59 mixed ethnicities) and 1571 controls (i.e., 981 Malays, 205 Chinese, 297 Indians, and 87 mixed ethnicities) from the Malaysian Epidemiological Investigation of Rheumatoid Arthritis (MyEIRA) population-based case-control study. Stepwise logistic regression was performed to identify the independent genetic risk factors for RA within the HLA region.

    RESULTS: We confirmed that the HLA-DRB1 amino acid at position 11 with valine residue conferred the strongest risk effect for ACPA-positive RA (OR = 4.26, 95% CI = 3.30-5.49, PGWAS = 7.22 × 10-29) in the Malays. Our study also revealed that HLA-DRB1 amino acid at position 96 with histidine residue was negatively associated with the risk of developing ACPA-positive RA in the Indians (OR = 0.48, 95% CI = 0.37-0.62, PGWAS = 2.58 × 10-08). Interestingly, we observed that HLA-DQB1*03:02 allele was inversely related to the risk of developing ACPA-positive RA in the Malays (OR = 0.17, 95% CI = 0.09-0.30, PGWAS = 1.60 × 10-09). No association was observed between the HLA variants and risk of developing ACPA-negative RA in any of the three major ethnic groups in Malaysia.

    CONCLUSIONS: Our results demonstrate that the RA-associated genetic factors in the multi-ethnic Malaysian population are similar to those in the Caucasian population, despite significant differences in the genetic architecture of HLA region across populations. A novel and distinct independent association between the HLA-DQB1*03:02 allele and ACPA-positive RA was observed in the Malays. In common with the Caucasian population, there is little risk from HLA region for ACPA-negative RA.

  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. Letchumanan N, Wong JHD, Tan LK, Ab Mumin N, Ng WL, Chan WY, et al.
    J Digit Imaging, 2023 Aug;36(4):1533-1540.
    PMID: 37253893 DOI: 10.1007/s10278-022-00753-1
    This study investigates the feasibility of using texture radiomics features extracted from mammography images to distinguish between benign and malignant breast lesions and to classify benign lesions into different categories and determine the best machine learning (ML) model to perform the tasks. Six hundred and twenty-two breast lesions from 200 retrospective patient data were segmented and analysed. Three hundred fifty radiomics features were extracted using the Standardized Environment for Radiomics Analysis (SERA) library, one of the radiomics implementations endorsed by the Image Biomarker Standardisation Initiative (IBSI). The radiomics features and selected patient characteristics were used to train selected machine learning models to classify the breast lesions. A fivefold cross-validation was used to evaluate the performance of the ML models and the top 10 most important features were identified. The random forest (RF) ensemble gave the highest accuracy (89.3%) and positive predictive value (66%) and likelihood ratio of 13.5 in categorising benign and malignant lesions. For the classification of benign lesions, the RF model again gave the highest likelihood ratio of 3.4 compared to the other models. Morphological and textural radiomics features were identified as the top 10 most important features from the random forest models. Patient age was also identified as one of the significant features in the RF model. We concluded that machine learning models trained against texture-based radiomics features and patient features give reasonable performance in differentiating benign versus malignant breast lesions. Our study also demonstrated that the radiomics-based machine learning models were able to emulate the visual assessment of mammography lesions, typically used by radiologists, leading to a better understanding of how the machine learning model arrive at their decision.
  15. Cheah PL, Krisnan T, Wong JHD, Rozalli FI, Fadzli F, Rahmat K, et al.
    J Magn Reson Imaging, 2021 02;53(2):437-444.
    PMID: 32918328 DOI: 10.1002/jmri.27354
    BACKGROUND: Charcot-Marie-Tooth (CMT) disease is diagnosed through clinical findings and genetic testing. While there are neurophysiological tools and clinical functional scales in CMT, objective disease biomarkers that can facilitate in monitoring disease progression are limited.

    PURPOSE: To investigate the utility of diffusion tensor imaging (DTI) in determining the microstructural integrity of sciatic and peroneal nerves and its correlation with the MRI grading of muscle atrophy severity and clinical function in CMT as determined by the CMT neuropathy score (CMTNS).

    STUDY TYPE: Prospective case-control.

    SUBJECTS: Nine CMT patients and nine age-matched controls.

    FIELD STRENGTH/SEQUENCE: 3 T T1 -weighted in-/out-of phase spoiled gradient recalled echo (SPGR) and DTI sequences.

    ASSESSMENT: Fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD), and mean diffusivity (MD) values for sciatic and peroneal nerves were obtained from DTI. Muscle atrophy was graded according to the Goutallier classification using in-/out-of phase SPGRs. DTI parameters and muscle atrophy grades were compared between CMT and controls, and the relationship between DTI parameters, muscle atrophy grades, and CMTNS were assessed.

    STATISTICAL TESTS: The Wilcoxon Signed Ranks test was used to compare DTI parameters between CMT and controls. The relationship between DTI parameters, muscle atrophy grades, and CMTNS were analyzed using the Spearman correlation. Receiver operating characteristic (ROC) analyses of DTI parameters that can differentiate CMT from healthy controls were done.

    RESULTS: There was a significant reduction in FA and increase in RD of both nerves (P 

  16. 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.

  17. 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 

  18. Low LS, Wong JHD, Tan LK, Chan WY, Jalaludin MY, Anuar Zaini A, et al.
    J Neuroradiol, 2023 Mar;50(2):271-277.
    PMID: 34800564 DOI: 10.1016/j.neurad.2021.11.004
    BACKGROUND: In subjects with isolated growth hormone deficiency (IGHD), recombinant human growth hormone (rhGH) is an approved method to achieve potential mid-parental height. However, data reporting rhGH treatment response in terms of brain structure volumes were scarce. We report the volumetric changes of the pituitary gland, basal ganglia, corpus callosum, thalamus, hippocampus and amygdala in these subjects post rhGH treatment.

    MATERIALS AND METHODS: This was a longitudinal study of eight IGHD subjects (2 males, 6 females) with a mean age of 11.1 ± 0.8 years and age-matched control groups. The pituitary gland, basal ganglia and limbic structures volumes were obtained using 3T MRI voxel-based morphology. The left-hand bone age was assessed using the Tanner-Whitehouse method. Follow-up imaging was performed after an average of 1.8 ± 0.4 years on rhGH.

    RESULTS: Subjects with IGHD had a smaller mean volume of the pituitary gland, right thalamus, hippocampus, and amygdala than the controls. After rhGH therapy, these volumes normalized to the age-matched controls. Corpus callosum of IGHD subjects had a larger mean volume than the controls and did not show much volume changes in response to rhGH therapy. There were changes towards normalization of bone age deficit of IGHD in response to rhGH therapy.

    CONCLUSION: The pituitary gland, hippocampus, and amygdala volumes in IGHD subjects were smaller than age-matched controls and showed the most response to rhGH therapy. Semi-automated volumetric assessment of pituitary gland, hippocampus, and amygdala using MRI may provide an objective assessment of response to rhGH therapy.

  19. Bakhtiar MF, Too CL, Tang MM, Sulaiman S, Tan LK, Ahmad-Fauzi NA, et al.
    Clin Exp Allergy, 2019 04;49(4):537-540.
    PMID: 30693574 DOI: 10.1111/cea.13347
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