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Automated segmentation of metal stent and bioresorbable vascular scaffold in intravascular optical coherence tomography images using deep learning architectures

Lau YS, Tan LK, Chan CK, Chee KH, Liew YM

Phys Med Biol, 2021 Dec 31;66(24).
PMID: 34911053 DOI: 10.1088/1361-6560/ac4348

Percutaneous coronary intervention (PCI) with stent placement is a treatment effective for coronary artery diseases. Intravascular optical coherence tomography (OCT) with high resolution is used clinically to visualize stent deployment and restenosis, facilitating PCI operation and for complication inspection. Automated stent struts segmentation in OCT images is necessary as each pullback of OCT images could contain thousands of stent struts. In this paper, a deep learning framework is proposed and demonstrated for the automated segmentation of two major clinical stent types: metal stents and bioresorbable vascular scaffolds (BVS). U-Net, the current most prominent deep learning network in biomedical segmentation, was implemented for segmentation with cropped input. The architectures of MobileNetV2 and DenseNet121 were also adapted into U-Net for improvement in speed and accuracy. The results suggested that the proposed automated algorithm's segmentation performance approaches the level of independent human obsevers and is feasible for both types of stents despite their distinct appearance. U-Net with DenseNet121 encoder (U-Dense) performed best with Dice's coefficient of 0.86 for BVS segmentation, and precision/recall of 0.92/0.92 for metal stent segmentation under optimal crop window size of 256.
Automatic localization of the left ventricular blood pool centroid in short axis cardiac cine MR images

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.
Neurometabolites Alteration in the Acute Phase of Mild Traumatic Brain Injury (mTBI): An In Vivo Proton Magnetic Resonance Spectroscopy (1H-MRS) Study

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
Fulltext Linear-regression convolutional neural network for fully automated coronary lumen segmentation in intravascular optical coherence tomography

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.
Fully automated segmentation of the left ventricle in cine cardiac MRI using neural network regression

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.
Fulltext Whole mitochondrial genome sequencing of Malaysian patients with cardiomyopathy

Kuan SW, Chua KH, Tan EW, Tan LK, Loch A, Kee BP

PeerJ, 2022;10:e13265.
PMID: 35441061 DOI: 10.7717/peerj.13265

Cardiomyopathy (CMP) constitutes a diverse group of myocardium diseases affecting the pumping ability of the heart. Genetic predisposition is among the major factors affecting the development of CMP. Globally, there are over 100 genes in autosomal and mitochondrial DNA (mtDNA) that have been reported to be associated with the pathogenesis of CMP. However, most of the genetic studies have been conducted in Western countries, with limited data being available for the Asian population. Therefore, this study aims to investigate the mutation spectrum in the mitochondrial genome of 145 CMP patients in Malaysia. Long-range PCR was employed to amplify the entire mtDNA, and whole mitochondrial genome sequencing was conducted on the MiSeq platform. Raw data was quality checked, mapped, and aligned to the revised Cambridge Reference Sequence (rCRS). Variants were named, annotated, and filtered. The sequencing revealed 1,077 variants, including 18 novel and 17 CMP and/or mitochondrial disease-associated variants after filtering. In-silico predictions suggested that three of the novel variants (m.8573G>C, m.11916T>A and m.11918T>G) in this study are potentially pathogenic. Two confirmed pathogenic variants (m.1555A>G and m.11778G>A) were also found in the CMP patients. The findings of this study shed light on the distribution of mitochondrial mutations in Malaysian CMP patients. Further functional studies are required to elucidate the role of these variants in the development of CMP.
Preliminary study of longitudinal changes in the pituitary and brain of children on growth hormone therapy

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.
Fulltext Obesity and Its Association with Undiagnosed Diabetes Mellitus, High Blood Pressure and Hypercholesterolemia in the Malaysian Adult Population: A National Cross-Sectional Study Using NHMS Data

Koo HC, Tan LK, Lim GP, Kee CC, Omar MA

Int J Environ Res Public Health, 2023 Feb 09;20(4).
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.
A Radiomics Study: Classification of Breast Lesions by Textural Features from Mammography Images

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.
Fulltext Does Awareness of Malaysian Healthy Plate Associate with Adequate Fruit and Vegetable Intake among Malaysian Adults with Non-Communicable Diseases?

Tan LK, Chua EH, Mohd Ghazali S, Cheah YK, Jayaraj VJ, Kee CC

Nutrients, 2023 Dec 08;15(24).
PMID: 38140302 DOI: 10.3390/nu15245043

The healthy eating plate concept has been introduced in many countries, including Malaysia, as a visual guide for the public to eat healthily. The relationship between Malaysian Healthy Plate (MHP) and adequate fruit and vegetable (FV) intake among morbid Malaysian adults is unknown. Hence, we investigated the relationship between awareness of the MHP and FV intake among morbid Malaysian adults. National survey data on 9760 morbid Malaysian adults aged 18 years and above were analyzed. The relationship between awareness of MHP and FV intake among Malaysian adults with obesity, diabetes mellitus, hypertension, and hypercholesterolemia were determined using multivariable logistic regression controlling for sociodemographic characteristics and lifestyle risk factors. Our data demonstrated that MHP awareness is associated with adequate FV intake among the Malaysian adults with abdominal obesity (adjusted odds ratio (aOR): 1.86, 95% confidence interval (CI): 1.05-3.29), diabetes mellitus (aOR: 4.88, 95% CI: 2.13-22.18), hypertension (aOR: 4.39, 95% CI: 1.96-9.83), and hypercholesterolemia (aOR: 4.16, 95% CI: 1.48-11.72). Our findings indicated the necessity for ongoing efforts by policymakers, healthcare professionals, and nutrition educators to promote the concept of MHP and ensure that morbid Malaysian adults consume a sufficient intake of FV or adopt a healthy eating pattern to achieve and maintain optimal health.
Improved diagnostic accuracy in differentiating malignant and benign lesions using single-voxel proton MRS of the breast at 3 T MRI

Suppiah S, Rahmat K, Mohd-Shah MN, Azlan CA, Tan LK, Aziz YF, et al.

Clin Radiol, 2013 Sep;68(9):e502-10.
PMID: 23706826 DOI: 10.1016/j.crad.2013.04.002

To investigate the diagnostic accuracy of single-voxel proton magnetic resonance spectroscopy (SV (1)H MRS) by quantifying total choline-containing compounds (tCho) in differentiating malignant from benign lesions, and subsequently, to analyse the relationship of tCho levels in malignant breast lesions with their histopathological subtypes.
Prevalence and characterization of multidrug-resistant and extended-spectrum beta-lactamase-producing Escherichia coli from pediatric wards of a Malaysian hospital

Ho WS, Balan G, Puthucheary S, Kong BH, Lim KT, Tan LK, et al.

Microb Drug Resist, 2012 Aug;18(4):408-16.
PMID: 22394084 DOI: 10.1089/mdr.2011.0222

The emergence of Escherichia coli resistant to extended-spectrum cephalosporins (ESCs) is of concern as ESC is often used to treat infections by Gram-negative bacteria. One-hundred and ten E. coli strains isolated in 2009-2010 from children warded in a Malaysian tertiary hospital were analyzed for their antibiograms, carriage of extended-spectrum beta-lactamase (ESBL) and AmpC genes, possible inclusion of the beta-lactamase genes on an integron platform, and their genetic relatedness. All E. coli strains were sensitive to carbapenems. About 46% of strains were multidrug resistant (MDR; i.e., resistant to ≥3 antibiotic classes) and almost half (45%) were nonsusceptible to ESCs. Among the MDR strains, high resistance rates were observed for ampicillin (98%), tetracycline (75%), and trimethoprim/sulfamethoxazole (73%). Out of 110 strains, bla(TEM-1) (49.1%), bla(CTX-M) (11.8%), and bla(CMY-2) (6.4%) were detected. Twenty-one strains were ESBL producers. CTX-M-15 was the predominant CTX-M variant found and this is the first report of a CTX-M-27-producing E. coli strain from Malaysia. Majority (3.1%) of the strains harbored class 1 integron-encoded integrases with a predominance of aadA and dfr genes within the integron variable region. No gene cassette encoding ESBL genes was found and integrons were not significantly associated with ESBL or non-ESBL producers. Possible clonal expansion was observed for few CTX-M-15-positive strains but the O25-ST131 E. coli clone known to harbor CTX-M-15 was not detected while CMY-2-positive strains were genetically diverse.
Motion corrected LV quantification based on 3D modelling for improved functional assessment in cardiac MRI

Liew YM, McLaughlin RA, Chan BT, Abdul Aziz YF, Chee KH, Ung NM, et al.

Phys Med Biol, 2015 Apr 7;60(7):2715-33.
PMID: 25768708 DOI: 10.1088/0031-9155/60/7/2715

Cine MRI is a clinical reference standard for the quantitative assessment of cardiac function, but reproducibility is confounded by motion artefacts. We explore the feasibility of a motion corrected 3D left ventricle (LV) quantification method, incorporating multislice image registration into the 3D model reconstruction, to improve reproducibility of 3D LV functional quantification. Multi-breath-hold short-axis and radial long-axis images were acquired from 10 patients and 10 healthy subjects. The proposed framework reduced misalignment between slices to subpixel accuracy (2.88 to 1.21 mm), and improved interstudy reproducibility for 5 important clinical functional measures, i.e. end-diastolic volume, end-systolic volume, ejection fraction, myocardial mass and 3D-sphericity index, as reflected in a reduction in the sample size required to detect statistically significant cardiac changes: a reduction of 21-66%. Our investigation on the optimum registration parameters, including both cardiac time frames and number of long-axis (LA) slices, suggested that a single time frame is adequate for motion correction whereas integrating more LA slices can improve registration and model reconstruction accuracy for improved functional quantification especially on datasets with severe motion artefacts.
Fulltext Incidental pharmacogenetics findings in an HLA-related research: Considerations for primary prevention

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
Microstructural Integrity of Peripheral Nerves in Charcot-Marie-Tooth Disease: An MRI Evaluation Study

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
Segmentation of left ventricle in late gadolinium enhanced MRI through 2D-4D registration for infarct localization in 3D patient-specific left ventricular model

Leong CO, Lim E, Tan LK, Abdul Aziz YF, Sridhar GS, Socrates D, et al.

Magn Reson Med, 2019 02;81(2):1385-1398.
PMID: 30230606 DOI: 10.1002/mrm.27486

PURPOSE: To evaluate a 2D-4D registration-cum-segmentation framework for the delineation of left ventricle (LV) in late gadolinium enhanced (LGE) MRI and for the localization of infarcts in patient-specific 3D LV models.
METHODS: A 3-step framework was proposed, consisting of: (1) 3D LV model reconstruction from motion-corrected 4D cine-MRI; (2) Registration of 2D LGE-MRI with 4D cine-MRI; (3) LV contour extraction from the intersection of LGE slices with the LV model. The framework was evaluated against cardiac MRI data from 27 patients scanned within 6 months after acute myocardial infarction. We compared the use of local Pearson's correlation (LPC) and normalized mutual information (NMI) as similarity measures for the registration. The use of 2 and 6 long-axis (LA) cine-MRI scans was also compared. The accuracy of the framework was evaluated using manual segmentation, and the interobserver variability of the scar volume derived from the segmented LV was determined using Bland-Altman analysis.
RESULTS: LPC outperformed NMI as a similarity measure for the proposed framework using 6 LA scans, with Hausdorrf distance (HD) of 1.19 ± 0.53 mm versus 1.51 ± 2.01 mm (endocardial) and 1.21 ± 0.48 mm versus 1.46 ± 1.78 mm (epicardial), respectively. Segmentation using 2 LA scans was comparable to 6 LA scans with a HD of 1.23 ± 0.70 mm (endocardial) and 1.25 ± 0.74 mm (epicardial). The framework yielded a lower interobserver variability in scar volumes compared with manual segmentation.
CONCLUSION: The framework showed high accuracy and robustness in delineating LV in LGE-MRI and allowed for bidirectional mapping of information between LGE- and cine-MRI scans, crucial in personalized model studies for treatment planning.
Fulltext Human leucocyte antigens profiling in Malay female patients with systemic lupus erythematosus: are we the same or different?

Selvaraja M, Too CL, Tan LK, Koay BT, Abdullah M, Shah AM, et al.

Lupus Sci Med, 2022 Feb;9(1).
PMID: 35105721 DOI: 10.1136/lupus-2021-000554

OBJECTIVE: SLE is a heterogeneous autoimmune disease, in terms of clinical presentation, incidence and severity across diverse ethnic populations. We investigated the human leucocyte antigens (HLA) profile (ie, HLA-A, HLA-B and HLA-C, HLA-DRB1, HLA-DQA1, HLA-DQB1, HLA-DPA1 and HLA-DPB1) in Malaysian Malay female patients with SLE and determined the generalisability of the published HLA risk factors across different ethnic populations globally including Malaysia.
METHODS: One hundred Malay female patients with SLE were recruited between January 2016 and October 2017 from a nephrology clinic. All patients were genotyped for HLA-A, HLA-B, HLA-C, HLA-DRB1, HLA-DQA1, HLA-DQB1, HLA-DPA1 and HLA-DPB1 alleles using PCR sequence-specific oligonucleotides method on Luminex platform. A total of 951 HLA genotyped population-based Malay control subjects was used for association testing by means of OR with 95% CIs.
RESULTS: Our findings convincingly validated common associations between HLA-A*11 (OR=1.65, p=3.36×10-3, corrected P (Pc)=4.03×10-2) and DQB1*05:01 (OR=1.56, p=2.02×10-2, Pc=non-significant) and SLE susceptibility in the Malay population. In contrast, DQB1*03:01 (OR=0.51, p=4.06×10-4, Pc=6.50×10-3) were associated with decreased risk of SLE in Malay population. Additionally, we also detected novel associations of susceptibility HLA genes (ie, HLA-B*38:02, DPA1*02:02, DPB1*14:01) and protective HLA genes (ie, DPA1*01:03). When comparing the current data with data from previously published studies from Caucasian, African and Asian populations, DRB1*15 alleles, DQB1*03:01 and DQA1*01:02 were corroborated as universal susceptibility and protective genes.
CONCLUSIONS: This study reveals multiple HLA alleles associated with susceptibility and protection against risk of developing SLE in Malay female population with renal disorders. In addition, the published data from different ethnic populations together with our study further support the notion that the genetic effects from association with DRB1*15:01/02, DQB1*03:01 and DQA1*01:02 alleles are generalised to multiple ethnic populations of Caucasian, African and Asian descents.
Assessing Complex Left Ventricular Adaptations in Aortic Stenosis Using Personalized 3D + time Cardiac MRI Modeling

Chuah SH, Md Sari NA, Tan LK, Chiam YK, Chan BT, Abdul Aziz YF, et al.

J Cardiovasc Transl Res, 2023 Oct;16(5):1110-1122.
PMID: 37022611 DOI: 10.1007/s12265-023-10375-9

Left ventricular adaptations can be a complex process under the influence of aortic stenosis (AS) and comorbidities. This study proposed and assessed the feasibility of using a motion-corrected personalized 3D + time LV modeling technique to evaluate the adaptive and maladaptive LV response to aid treatment decision-making. A total of 22 AS patients were analyzed and compared against 10 healthy subjects. The 3D + time analysis showed a highly distinct and personalized pattern of remodeling in individual AS patients which is associated with comorbidities and fibrosis. Patients with AS alone showed better wall thickening and synchrony than those comorbid with hypertension. Ischemic heart disease in AS caused impaired wall thickening and synchrony and systolic function. Apart from showing significant correlations to echocardiography and clinical MRI measurements (r: 0.70-0.95; p
Generation of fluoroscopy-alike radiographs as alternative datasets for deep learning in interventional radiology

Fum WKS, Md Shah MN, Raja Aman RRA, Abd Kadir KA, Wen DW, Leong S, et al.

Phys Eng Sci Med, 2023 Dec;46(4):1535-1552.
PMID: 37695509 DOI: 10.1007/s13246-023-01317-5

In fluoroscopy-guided interventions (FGIs), obtaining large quantities of labelled data for deep learning (DL) can be difficult. Synthetic labelled data can serve as an alternative, generated via pseudo 2D projections of CT volumetric data. However, contrasted vessels have low visibility in simple 2D projections of contrasted CT data. To overcome this, we propose an alternative method to generate fluoroscopy-like radiographs from contrasted head CT Angiography (CTA) volumetric data. The technique involves segmentation of brain tissue, bone, and contrasted vessels from CTA volumetric data, followed by an algorithm to adjust HU values, and finally, a standard ray-based projection is applied to generate the 2D image. The resulting synthetic images were compared to clinical fluoroscopy images for perceptual similarity and subject contrast measurements. Good perceptual similarity was demonstrated on vessel-enhanced synthetic images as compared to the clinical fluoroscopic images. Statistical tests of equivalence show that enhanced synthetic and clinical images have statistically equivalent mean subject contrast within 25% bounds. Furthermore, validation experiments confirmed that the proposed method for generating synthetic images improved the performance of DL models in certain regression tasks, such as localizing anatomical landmarks in clinical fluoroscopy images. Through enhanced pseudo 2D projection of CTA volume data, synthetic images with similar features to real clinical fluoroscopic images can be generated. The use of synthetic images as an alternative source for DL datasets represents a potential solution to the application of DL in FGIs procedures.
Re-emergence of Chikungunya virus in South-east Asia: virological evidence from Sri Lanka and Singapore

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.

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