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  1. Fulltext Reliability, technical error of measurements and validity of length and weight measurements for children under two years old in Malaysia
    Jamaiyah H, Geeta A, Safiza MN, Khor GL, Wong NF, Kee CC, et al.
    Med J Malaysia, 2010 Jun;65 Suppl A:131-7.
    PMID: 21488474
    The National Health and Morbidity Survey III 2006 wanted to perform anthropometric measurements (length and weight) for children in their survey. However there is limited literature on the reliability, technical error of measurement (TEM) and validity of these two measurements. This study assessed the above properties of length (LT) and weight (WT) measurements in 130 children age below two years, from the Hospital Universiti Kebangsaan Malaysia (HUKM) paediatric outpatient clinics, during the period of December 2005 to January 2006. Two trained nurses measured WT using Tanita digital infant scale model 1583, Japan (0.01kg) and Seca beam scale, Germany (0.01 kg) and LT using Seca measuring mat, Germany (0.1cm) and Sensormedics stadiometer model 2130 (0.1cm). Findings showed high inter and intra-examiner reliability using 'change in the mean' and 'intraclass correlation' (ICC) for WT and LT. However, LT was found to be less reliable using the 'Bland and Altman plot'. This was also true using Relative TEMs, where the TEM value of LT was slightly more than the acceptable limit. The test instruments were highly valid for WT using 'change in the mean' and 'ICC' but was less valid for LT measurement. In spite of this we concluded that, WT and LT measurements in children below two years old using the test instruments were reliable and valid for a community survey such as NHMS III within the limits of their error. We recommend that LT measurements be given special attention to improve its reliability and validity.
    Study site: Paediatric clinic, Pusat Perubatan Universiti Kebangsaan Malaysia (PPUKM), Kuala Lumpur, Malaysia
  2. Fulltext A national database on children and adolescent with diabetes (e-DiCARE): results from April 2006 to June 2007
    Fuziah MZ, Hong JY, Zanariah H, Harun F, Chan SP, Rokiah P, et al.
    Med J Malaysia, 2008 Sep;63 Suppl C:37-40.
    PMID: 19230245
    In Malaysia, Diabetes in Children and Adolescents Registry (DiCARE) was launched nationwide in August 2006 to determine and monitor the number, the time trend of diabetes mellitus (DM) patients, their socio-demographic profiles, outcome of intervention and facilitate research using this registry. This is an on going real time register of diabetic patients < or = 20 years old via the e-DiCARE, an online registration system. To date were 240 patients notified from various states in Malaysia. The mean age was 12.51 years (1.08-19.75) and 46.4% were boys. The mean age at diagnosis was 8.31 +/- 4.13 years old with an estimated duration of diabetes of 4.32 +/- 3.55 years. A total of 166/240 (69.2%) have T1DM, 42/240 (17.5%) have T2DM and 18/240 (7.5%) have other types of DM. Basis of diagnosis was known in 162 patients with T1DM and 41 patients with T2DM. In T1DM patients, 6.0% of the girls and 19.1% boys were overweight or obese. As for T2DM, 64.3% had their BMI reported: 66.7% girls and 91.6% boys were overweight or obese. Most patients (80.4%) practiced home blood glucose monitoring. Patients were seen by dietitian (66.7%), diabetes educator (50.0%), and optometrist or ophthalmologist (45.0%). Only 10.8% attended diabetic camps. In the annual census of 117 patients, the mean HbAlc level was 10.0% + 2.2 (range 5.2 to 17.0%). The early results of DiCARE served as a starting point to improve the standard of care of DM among the young in the country.
  3. Landslide spatial modelling using novel bivariate statistical based Naïve Bayes, RBF Classifier, and RBF Network machine learning algorithms
    He Q, Shahabi H, Shirzadi A, Li S, Chen W, Wang N, et al.
    Sci Total Environ, 2019 May 01;663:1-15.
    PMID: 30708212 DOI: 10.1016/j.scitotenv.2019.01.329
    Landslides are major hazards for human activities often causing great damage to human lives and infrastructure. Therefore, the main aim of the present study is to evaluate and compare three machine learning algorithms (MLAs) including Naïve Bayes (NB), radial basis function (RBF) Classifier, and RBF Network for landslide susceptibility mapping (LSM) at Longhai area in China. A total of 14 landslide conditioning factors were obtained from various data sources, then the frequency ratio (FR) and support vector machine (SVM) methods were used for the correlation and selection the most important factors for modelling process, respectively. Subsequently, the resulting three models were validated and compared using some statistical metrics including area under the receiver operating characteristics (AUROC) curve, and Friedman and Wilcoxon signed-rank tests The results indicated that the RBF Classifier model had the highest goodness-of-fit and performance based on the training and validation datasets. The results concluded that the RBF Classifier model outperformed and outclassed (AUROC = 0.881), the NB (AUROC = 0.872) and the RBF Network (AUROC = 0.854) models. The obtained results pointed out that the RBF Classifier model is a promising method for spatial prediction of landslide over the world.
  4. Fulltext Author Correction: Novel Hybrid Evolutionary Algorithms for Spatial Prediction of Floods
    Bui DT, Panahi M, Shahabi H, Singh VP, Shirzadi A, Chapi K, et al.
    Sci Rep, 2021 Jul 20;11(1):15152.
    PMID: 34285263 DOI: 10.1038/s41598-021-93957-4
  5. GIS-based groundwater potential analysis using novel ensemble weights-of-evidence with logistic regression and functional tree models
    Chen W, Li H, Hou E, Wang S, Wang G, Panahi M, et al.
    Sci Total Environ, 2018 Sep 01;634:853-867.
    PMID: 29653429 DOI: 10.1016/j.scitotenv.2018.04.055
    The aim of the current study was to produce groundwater spring potential maps using novel ensemble weights-of-evidence (WoE) with logistic regression (LR) and functional tree (FT) models. First, a total of 66 springs were identified by field surveys, out of which 70% of the spring locations were used for training the models and 30% of the spring locations were employed for the validation process. Second, a total of 14 affecting factors including aspect, altitude, slope, plan curvature, profile curvature, stream power index (SPI), topographic wetness index (TWI), sediment transport index (STI), lithology, normalized difference vegetation index (NDVI), land use, soil, distance to roads, and distance to streams was used to analyze the spatial relationship between these affecting factors and spring occurrences. Multicollinearity analysis and feature selection of the correlation attribute evaluation (CAE) method were employed to optimize the affecting factors. Subsequently, the novel ensembles of the WoE, LR, and FT models were constructed using the training dataset. Finally, the receiver operating characteristic (ROC) curves, standard error, confidence interval (CI) at 95%, and significance level P were employed to validate and compare the performance of three models. Overall, all three models performed well for groundwater spring potential evaluation. The prediction capability of the FT model, with the highest AUC values, the smallest standard errors, the narrowest CIs, and the smallest P values for the training and validation datasets, is better compared to those of other models. The groundwater spring potential maps can be adopted for the management of water resources and land use by planners and engineers.
  6. Modeling flood susceptibility using data-driven approaches of naïve Bayes tree, alternating decision tree, and random forest methods
    Chen W, Li Y, Xue W, Shahabi H, Li S, Hong H, et al.
    Sci Total Environ, 2020 Jan 20;701:134979.
    PMID: 31733400 DOI: 10.1016/j.scitotenv.2019.134979
    Floods are one of the most devastating types of disasters that cause loss of lives and property worldwide each year. This study aimed to evaluate and compare the prediction capability of the naïve Bayes tree (NBTree), alternating decision tree (ADTree), and random forest (RF) methods for the spatial prediction of flood occurrence in the Quannan area, China. A flood inventory map with 363 flood locations was produced and partitioned into training and validation datasets through random selection with a ratio of 70/30. The spatial flood database was constructed using thirteen flood explanatory factors. The probability certainty factor (PCF) method was used to analyze the correlation between the factors and flood occurrences. Consequently, three flood susceptibility maps were produced using the NBTree, ADTree, and RF methods. Finally, the area under the curve (AUC) and statistical measures were used to validate the flood susceptibility models. The results indicated that the RF method is an efficient and reliable model in flood susceptibility assessment, with the highest AUC values, positive predictive rate, negative predictive rate, sensitivity, specificity, and accuracy for the training (0.951, 0.892, 0.941, 0.945, 0.886, and 0.915, respectively) and validation (0.925, 0.851, 0.938, 0.945, 0.835, and 0.890, respectively) datasets.
  7. Fulltext Novel Hybrid Evolutionary Algorithms for Spatial Prediction of Floods
    Bui DT, Panahi M, Shahabi H, Singh VP, Shirzadi A, Chapi K, et al.
    Sci Rep, 2018 Oct 18;8(1):15364.
    PMID: 30337603 DOI: 10.1038/s41598-018-33755-7
    Adaptive neuro-fuzzy inference system (ANFIS) includes two novel GIS-based ensemble artificial intelligence approaches called imperialistic competitive algorithm (ICA) and firefly algorithm (FA). This combination could result in ANFIS-ICA and ANFIS-FA models, which were applied to flood spatial modelling and its mapping in the Haraz watershed in Northern Province of Mazandaran, Iran. Ten influential factors including slope angle, elevation, stream power index (SPI), curvature, topographic wetness index (TWI), lithology, rainfall, land use, stream density, and the distance to river were selected for flood modelling. The validity of the models was assessed using statistical error-indices (RMSE and MSE), statistical tests (Friedman and Wilcoxon signed-rank tests), and the area under the curve (AUC) of success. The prediction accuracy of the models was compared to some new state-of-the-art sophisticated machine learning techniques that had previously been successfully tested in the study area. The results confirmed the goodness of fit and appropriate prediction accuracy of the two ensemble models. However, the ANFIS-ICA model (AUC = 0.947) had a better performance in comparison to the Bagging-LMT (AUC = 0.940), BLR (AUC = 0.936), LMT (AUC = 0.934), ANFIS-FA (AUC = 0.917), LR (AUC = 0.885) and RF (AUC = 0.806) models. Therefore, the ANFIS-ICA model can be introduced as a promising method for the sustainable management of flood-prone areas.
  8. Fulltext Shallow Landslide Susceptibility Mapping: A Comparison between Logistic Model Tree, Logistic Regression, Naïve Bayes Tree, Artificial Neural Network, and Support Vector Machine Algorithms
    Nhu VH, Shirzadi A, Shahabi H, Singh SK, Al-Ansari N, Clague JJ, et al.
    Int J Environ Res Public Health, 2020 04 16;17(8).
    PMID: 32316191 DOI: 10.3390/ijerph17082749
    Shallow landslides damage buildings and other infrastructure, disrupt agriculture practices, and can cause social upheaval and loss of life. As a result, many scientists study the phenomenon, and some of them have focused on producing landslide susceptibility maps that can be used by land-use managers to reduce injury and damage. This paper contributes to this effort by comparing the power and effectiveness of five machine learning, benchmark algorithms-Logistic Model Tree, Logistic Regression, Naïve Bayes Tree, Artificial Neural Network, and Support Vector Machine-in creating a reliable shallow landslide susceptibility map for Bijar City in Kurdistan province, Iran. Twenty conditioning factors were applied to 111 shallow landslides and tested using the One-R attribute evaluation (ORAE) technique for modeling and validation processes. The performance of the models was assessed by statistical-based indexes including sensitivity, specificity, accuracy, mean absolute error (MAE), root mean square error (RMSE), and area under the receiver operatic characteristic curve (AUC). Results indicate that all the five machine learning models performed well for shallow landslide susceptibility assessment, but the Logistic Model Tree model (AUC = 0.932) had the highest goodness-of-fit and prediction accuracy, followed by the Logistic Regression (AUC = 0.932), Naïve Bayes Tree (AUC = 0.864), ANN (AUC = 0.860), and Support Vector Machine (AUC = 0.834) models. Therefore, we recommend the use of the Logistic Model Tree model in shallow landslide mapping programs in semi-arid regions to help decision makers, planners, land-use managers, and government agencies mitigate the hazard and risk.
  9. Fulltext Diagnosis and outcomes of cachexia in Asia: Working Consensus Report from the Asian Working Group for Cachexia
    Arai H, Maeda K, Wakabayashi H, Naito T, Konishi M, Assantachai P, et al.
    J Cachexia Sarcopenia Muscle, 2023 Oct;14(5):1949-1958.
    PMID: 37667992 DOI: 10.1002/jcsm.13323
    Chronic diseases often lead to metabolic disorders, causing anabolic resistance and increased energy consumption, which result in cachexia. Cachexia, in turn, can lead to major clinical consequences such as impaired quality of life, shortened life expectancy, and increased healthcare expenditure. Existing international diagnostic criteria for cachexia employ thresholds derived from Western populations, which may not apply to Asians due to differing body compositions. To address this issue, the Asian Working Group for Cachexia (AWGC) was initiated. The AWGC comprises experts in cachexia research and clinical practice from various Asian countries and aims to develop a consensus on diagnostic criteria and significant clinical outcomes for cachexia in Asia. The AWGC, composed of experts in cachexia research and clinical practice from several Asian countries, undertook three-round Delphi surveys and five meetings to reach a consensus. Discussions were held on etiological diseases, essential diagnostic items for cachexia, including subjective and objective symptoms and biomarkers, and significant clinical outcomes. The consensus highlighted the importance of multiple diagnostic factors for cachexia, including chronic diseases, either or both weight loss or low body mass index, and at least one of the following: anorexia, decreased grip strength (<28 kg in men and <18 kg in women), or elevated C-reactive protein levels (>5 mg/L [0.5 mg/dL]). The AWGC proposed a significant weight change of 2% or more over a 3-6 month period and suggested a tentative cut-off value of 21 kg/m2 for low body mass index in diagnosing cachexia. Critical clinical outcomes were determined to be mortality, quality of life as assessed by tools such as EQ-5D or the Functional Assessment of Anorexia/Cachexia Therapy, and functional status as measured by the Clinical Frailty Scale or Barthel Index, with significant emphasis on patient-reported outcomes. The AWGC consensus offers a comprehensive definition and user-friendly diagnostic criteria for cachexia, tailored specifically for Asian populations. This consensus is set to stimulate future research and enhance the multidisciplinary approach to managing cachexia. With plans to develop further guidelines for the optimal treatment, prevention, and care of cachexia in Asians, the AWGC criteria are expected to drive research across chronic co-morbidities and cancer in Asia, leading to future refinement of diagnostic criteria.
  10. Extensive intragenomic variations of the 18S rDNA V4 region in the toxigenic diatom species Pseudo-nitzschia multistriata revealed through high-throughput sequencing
    Wang H, Liu K, He Z, Chen Y, Hu Z, Chen W, et al.
    Mar Pollut Bull, 2024 Apr;201:116198.
    PMID: 38428045 DOI: 10.1016/j.marpolbul.2024.116198
    Metabarcoding analysis is an effective technique for monitoring the domoic acid-producing Pseudo-nitzschia species in marine environments, uncovering high-levels of molecular diversity. However, such efforts may result in the overinterpretation of Pseudo-nitzschia species diversity, as molecular diversity not only encompasses interspecies and intraspecies diversities but also exhibits extensive intragenomic variations (IGVs). In this study, we analyzed the V4 region of the 18S rDNA of 30 strains of Pseudo-nitzschia multistriata collected from the coasts of China. The results showed that each P. multistriata strain harbored about a hundred of unique 18S rDNA V4 sequence varieties, of which each represented by a unique amplicon sequence variant (ASV). This study demonstrated the extensive degree of IGVs in P. multistriata strains, suggesting that IGVs may also present in other Pseudo-nitzschia species and other phytoplankton species. Understanding the scope and levels of IGVs is crucial for accurately interpreting the results of metabarcoding analysis.
  11. Novel cellular evidence of oviduct secretions in the Chinese soft-shelled turtle Pelodiscus sinensis
    Waqas MY, Lisi H, Yang P, Ullah S, Zhang L, Zhang Q, et al.
    J Exp Zool A Ecol Genet Physiol, 2015 Nov;323(9):655-65.
    PMID: 26350585 DOI: 10.1002/jez.1957
    The oviduct is the location of fertilization and sperm storage. We examined the ultrastructure of the oviduct epithelium and its glandular secretions in the isthmus, uterus and vagina of Chinese soft-shelled turtle Pelodiscus sinensis using light and transmission electron microscopy. The epithelium in these segments is lined with ciliated, secretory and other cells; the first two cell types span the entire epithelium, with secretory cells being predominant. The ciliated cells are characterized by the presence of a secretory vacuole that releases apocrine secretions into the lumen, whereas the secretory cells contain typical biphasic granules with both dark and light aspects. The third type of cells observed have wider proximal portion, abundant mitochondria, vacuoles, and narrow nuclei. The storage of spermatozoa is restricted to the isthmus, uterus, and vagina. In addition, the gland cells show prominent features, including the presence of granules of different shapes, sizes, and electron densities. The synthesis of these granules is described for the first time in this study. Mitochondria appear to play an important role in the formation of dense granules, the rough endoplasmic reticulum and microfilaments may also play a role in the maturation of these dense granules. After completing the maturation process, these granules are released into the lumen of the gland cells.
  12. Fulltext Distribution of axial length, anterior chamber depth, and corneal curvature in an aged population in South China
    Chen H, Lin H, Lin Z, Chen J, Chen W
    BMC Ophthalmol, 2016 May 01;16(1):47.
    PMID: 27138378 DOI: 10.1186/s12886-016-0221-5
    BACKGROUND: Ocular biometry is important for preoperative assessment in cataract and anterior segment surgery. The purpose of this study was to investigate normative ocular biometric parameters and their associations in an older Chinese population.

    METHODS: This was a cross-sectional observational study. From 2013 to 2014, we recruited inhabitants aged 50 years or older in Guangzhou, China. Among 1,117 participants in the study, data from 1,015 phakic right eyes were used for analyses. Ocular parameters including axial length (AL), anterior chamber depth (ACD), and corneal curvature (K) were measured using an IOL Master.

    RESULTS: The mean AL, ACD, and K were 23.48 mm [95 % confidence interval (CI), 23.40-23.55], 3.03 mm (CI, 3.01-3.05), and 44.20 mm (CI, 44.11-44.29), respectively. A mean reduction in ACD with age was observed (P = 0.002) in male subjects but not in female subjects (P = 0.558). Male subjects had significantly longer ALs (23.68 mm versus 23.23 mm, P 

  13. Fulltext Spatial and temporal evolution of Guangdong tourism economic network structure from the perspective of social networks
    Zhang L, Marzuki A, Liao Z, Zhao K, Huang Z, Chen W
    Heliyon, 2023 Aug;9(8):e18570.
    PMID: 37520942 DOI: 10.1016/j.heliyon.2023.e18570
    This study uses social network analysis and modified gravity model methods to empirically analyse the network spatial correlation structure and spatiotemporal development trend of 21 cities in Guangdong Province from 2000 to 2020 based on tourism economic development data. The findings show that, first, Zhuhai has the greatest potential for growth as the centre of the spatial and temporal evolution trend of the network structure of the tourism economy in Guangdong Province, ahead of Shenzhen, Huizhou, Zhaoqing, Zhongshan, Jiangmen and Dongguan. However, Guangzhou, the capital city of Guangdong Province, is experiencing a decline in such influence and development. Second, there is a counter-trend growth in the number of tourism-related economic links among the 21 cities. Although Guangdong's tourism economic network intensity is strong, there is still room for further optimisation. Third, the results of the overall network indicators show that there is a need for further improvement in network density, grade and efficiency to help reduce the relative development gap of the cities' tourism and effectively improve the overall development of Guangdong's tourism economy. Finally, based on the core-periphery structure, this study proposes relevant suggestions for the sustainable development of Guangdong's tourism industry.
  14. Fulltext Loss-free tensile ductility of dual-structure titanium composites via an interdiffusion and self-organization strategy
    Liu L, Li S, Pan D, Hui D, Zhang X, Li B, et al.
    Proc Natl Acad Sci U S A, 2023 Jul 11;120(28):e2302234120.
    PMID: 37399391 DOI: 10.1073/pnas.2302234120
    The deformation-coordination ability between ductile metal and brittle dispersive ceramic particles is poor, which means that an improvement in strength will inevitably sacrifice ductility in dispersion-strengthened metallic materials. Here, we present an inspired strategy for developing dual-structure-based titanium matrix composites (TMCs) that achieve 12.0% elongation comparable to the matrix Ti6Al4V alloys and enhanced strength compared to homostructure composites. The proposed dual-structure comprises a primary structure, namely, a TiB whisker-rich region engendered fine grain Ti6Al4V matrix with a three-dimensional micropellet architecture (3D-MPA), and an overall structure consisting of evenly distributed 3D-MPA "reinforcements" and a TiBw-lean titanium matrix. The dual structure presents a spatially heterogeneous grain distribution with 5.8 μm fine grains and 42.3 μm coarse grains, which exhibits excellent hetero-deformation-induced (HDI) hardening and achieves a 5.8% ductility. Interestingly, the 3D-MPA "reinforcements" show 11.1% isotropic deformability and 66% dislocation storage, which endows the TMCs with good strength and loss-free ductility. Our enlightening method uses an interdiffusion and self-organization strategy based on powder metallurgy to enable metal matrix composites with the heterostructure of the matrix and the configuration of reinforcement to address the strength-ductility trade-off dilemma.
  15. Fulltext Dengue antibodies in a suburban community in Malaysia
    Chen WS, Wong CH, Cillekens L
    Med J Malaysia, 2003 Mar;58(1):142-3.
    PMID: 14556343
  16. Fulltext Reliability and technical error of calf circumference and mid-half arm span measurements for nutritional status assessment of elderly Persons in Malaysia
    Jamaiyah H, Geeta A, Safiza MN, Wong NF, Kee CC, Ahmad AZ, et al.
    Malays J Nutr, 2008 Sep;14(2):137-50.
    PMID: 22691771 MyJurnal
    This study sought to examine the reliability of two measurements; Calf Circumference (CC) and Mid-half Arm Span (MHAS). A sample of 130 elderly persons aged 60 years and above seen consecutively in the Kuala Lumpur Hospital outpatient clinic during the period of December 2005 to January 2006, upon consent, were recruited to the study. There was a high degree of reliability for both inter- and intra-examiner (r close to 1). For inter-examiner, on average the CC measurements taken by the first examiner were 0.3 cm lower than that of the second examiner. The upper and lower limit of the differences were +0.4 to -0.9 cm respectively. Inter-examiner MHAS measurements on average by the first examiner were 0.2 cm lower than that of the second examiner. The limits were +1.7 to -2.1 cm. By comparison, the inter-examiner CC measurements were more reliable than the MHAS measurements. For intra-examiner, on average the CC measurements at Time 1 were consistent with Time 2 (mean difference=0) with limits of the difference at + 0.5 cm. MHAS measurements at Time 1 were on average 0.1 cm less than at Time 2 with limits at +1.7 and -1.8 cm. The technical error of measurement (TEM) and coefficient of variation of CC and MHAS for both interexaminer and intra-examiner measurements were within acceptable limits with the exception of MHAS TEM. This study suggests that CC and MHAS measured in elderly persons 60 years and above, using Seca Circumference Tape ® 206, Germany (0.05 cm) are reliable and can be used in a community survey.

    Study site: Outpatient clinic, Hospital Kuala Lumpur
  17. Fulltext The Tsinghua-Lancet Commission on Healthy Cities in China: unlocking the power of cities for a healthy China
    Yang J, Siri JG, Remais JV, Cheng Q, Zhang H, Chan KKY, et al.
    Lancet, 2018 05 26;391(10135):2140-2184.
    PMID: 29678340 DOI: 10.1016/S0140-6736(18)30486-0
  18. Fulltext Computer-assisted quantification of CD3+ T cells in follicular lymphoma
    Abas FS, Shana'ah A, Christian B, Hasserjian R, Louissaint A, Pennell M, et al.
    Cytometry A, 2017 06;91(6):609-621.
    PMID: 28110507 DOI: 10.1002/cyto.a.23049
    The advance of high resolution digital scans of pathology slides allowed development of computer based image analysis algorithms that may help pathologists in IHC stains quantification. While very promising, these methods require further refinement before they are implemented in routine clinical setting. Particularly critical is to evaluate algorithm performance in a setting similar to current clinical practice. In this article, we present a pilot study that evaluates the use of a computerized cell quantification method in the clinical estimation of CD3 positive (CD3+) T cells in follicular lymphoma (FL). Our goal is to demonstrate the degree to which computerized quantification is comparable to the practice of estimation by a panel of expert pathologists. The computerized quantification method uses entropy based histogram thresholding to separate brown (CD3+) and blue (CD3-) regions after a color space transformation. A panel of four board-certified hematopathologists evaluated a database of 20 FL images using two different reading methods: visual estimation and manual marking of each CD3+ cell in the images. These image data and the readings provided a reference standard and the range of variability among readers. Sensitivity and specificity measures of the computer's segmentation of CD3+ and CD- T cell are recorded. For all four pathologists, mean sensitivity and specificity measures are 90.97 and 88.38%, respectively. The computerized quantification method agrees more with the manual cell marking as compared to the visual estimations. Statistical comparison between the computerized quantification method and the pathologist readings demonstrated good agreement with correlation coefficient values of 0.81 and 0.96 in terms of Lin's concordance correlation and Spearman's correlation coefficient, respectively. These values are higher than most of those calculated among the pathologists. In the future, the computerized quantification method may be used to investigate the relationship between the overall architectural pattern (i.e., interfollicular vs. follicular) and outcome measures (e.g., overall survival, and time to treatment). © 2017 International Society for Advancement of Cytometry.
  19. Fulltext Classification of follicular lymphoma: the effect of computer aid on pathologists grading
    Fauzi MF, Pennell M, Sahiner B, Chen W, Shana'ah A, Hemminger J, et al.
    BMC Med Inform Decis Mak, 2015;15:115.
    PMID: 26715518 DOI: 10.1186/s12911-015-0235-6
    Follicular lymphoma (FL) is one of the most common lymphoid malignancies in the western world. FL cases are stratified into three histological grades based on the average centroblast count per high power field (HPF). The centroblast count is performed manually by the pathologist using an optical microscope and hematoxylin and eosin (H&E) stained tissue section. Although this is the current clinical practice, it suffers from high inter- and intra-observer variability and is vulnerable to sampling bias.
  20. Fulltext Nuclear IHC enumeration: A digital phantom to evaluate the performance of automated algorithms in digital pathology
    Niazi MKK, Abas FS, Senaras C, Pennell M, Sahiner B, Chen W, et al.
    PLoS One, 2018;13(5):e0196547.
    PMID: 29746503 DOI: 10.1371/journal.pone.0196547
    Automatic and accurate detection of positive and negative nuclei from images of immunostained tissue biopsies is critical to the success of digital pathology. The evaluation of most nuclei detection algorithms relies on manually generated ground truth prepared by pathologists, which is unfortunately time-consuming and suffers from inter-pathologist variability. In this work, we developed a digital immunohistochemistry (IHC) phantom that can be used for evaluating computer algorithms for enumeration of IHC positive cells. Our phantom development consists of two main steps, 1) extraction of the individual as well as nuclei clumps of both positive and negative nuclei from real WSI images, and 2) systematic placement of the extracted nuclei clumps on an image canvas. The resulting images are visually similar to the original tissue images. We created a set of 42 images with different concentrations of positive and negative nuclei. These images were evaluated by four board certified pathologists in the task of estimating the ratio of positive to total number of nuclei. The resulting concordance correlation coefficients (CCC) between the pathologist and the true ratio range from 0.86 to 0.95 (point estimates). The same ratio was also computed by an automated computer algorithm, which yielded a CCC value of 0.99. Reading the phantom data with known ground truth, the human readers show substantial variability and lower average performance than the computer algorithm in terms of CCC. This shows the limitation of using a human reader panel to establish a reference standard for the evaluation of computer algorithms, thereby highlighting the usefulness of the phantom developed in this work. Using our phantom images, we further developed a function that can approximate the true ratio from the area of the positive and negative nuclei, hence avoiding the need to detect individual nuclei. The predicted ratios of 10 held-out images using the function (trained on 32 images) are within ±2.68% of the true ratio. Moreover, we also report the evaluation of a computerized image analysis method on the synthetic tissue dataset.
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