Wan Zuki Azman Wan Muhamad
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Preferred name
Wan Zuki Azman Wan Muhamad
Official Name
Wan Zuki Azman, Wan Muhamad
Alternative Name
Azman, Wan Zuki
Wan Ahmad, Wan Zuki Azman
Muhamad, Wan Zuki Azmanwan
Main Affiliation
Scopus Author ID
55860800560
Researcher ID
R-4128-2019

Research Output
Now showing 1 - 2 of 2
  • Publication
    A comprehensive review of tubule formation in histopathology images: advancement in tubule and tumor detection techniques
    (Springer, 2024-09-11)
    Joseph Jiun Wen Siet
    ;
    Xiao Jian Tan
    ;
    Wai Loon Cheor
    ;
    Khairul Shakir Ab Rahman
    ;
    Cheng Ee Meng
    ;
    Wan Zuki Azman Wan Muhamad
    ;
    Sook Yee Yip
    Breast cancer, the earliest documented cancer in history, stands as a foremost cause of mortality, accounting for 684,996 deaths globally in 2020 (15.5% of all female cancer cases). Irrespective of socioeconomic factors, geographic locations, race, or ethnicity, breast cancer ranks as the most frequently diagnosed cancer in women. The standard grading for breast cancer utilizes the Nottingham Histopathology Grading (NHG) system, which considers three crucial features: mitotic counts, nuclear pleomorphism, and tubule formation. Comprehensive reviews on features, for example, mitotic count and nuclear pleomorphism have been available thus far. Nevertheless, a thorough investigation specifically focusing on tubule formation aligned with the NHG system is currently lacking. Motivated by this gap, the present study aims to unravel tubule formation in histopathology images via a comprehensive review of detection approaches involving tubule and tumor features. Without temporal constraints, a structured methodology is established in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, resulting in 12 articles for tubule detection and 67 included articles for tumor detection. Despite the primary focus on breast cancer, the structured search string extends beyond this domain to encompass any cancer type utilizing histopathology images as input, focusing on tubule and tumor detection. This broadened scope is essential. Insights from approaches in tubule and tumor detection for various cancers can be assimilated, integrated, and contributed to an enhanced understanding of tubule formation in breast histopathology images. This study compiles evidence-based analyses into a cohesive document, offering comprehensive information to a diverse audience, including newcomers, experienced researchers, and stakeholders interested in the subject matter.
  • Publication
    A quantitative measurement method for nuclear-pleomorphism scoring in breast cancer
    (MDPI, 2024-09)
    Chai Teoh
    ;
    Xiao Tan
    ;
    Khairul Ab Rahman
    ;
    Ikmal Bakrin
    ;
    Kam Goh
    ;
    Joseph Siet
    ;
    Wan Zuki Azman Wan Muhamad
    Background/Objectives: Nuclear pleomorphism, a crucial determinant of breast cancer grading under the Nottingham Histopathology Grading (NHG) system, remains inadequately quantified in the existing literature. Motivated by this gap, our study seeks to investigate and establish correlations among morphological features across various scores of nuclear pleomorphism, as per the NHG system. We aim to quantify nuclear pleomorphism across these scores and validate our proposed measurement method against ground-truth data. Methods: Initially, we deconstruct the descriptions of nuclear pleomorphism into three core elements: size, shape, and appearance. These elements are subsequently mathematically modeled into equations, termed (Formula presented.), (Formula presented.), and (Formula presented.). These equations are then integrated into a unified model termed Harmonic Mean (HM). The HM equation yields a value approaching 1 for nuclei demonstrating characteristics of score-3 nuclear pleomorphism and near 0 for those exhibiting features of score-1 nuclear pleomorphism. Results: The proposed HM model demonstrates promising performance metrics, including Accuracy, Recall, Specificity, Precision, and F1-score, with values of 0.97, 0.96, 0.97, 0.94, and 0.95, respectively. Conclusions: In summary, this study proposes the HM equation as a novel feature for the precise quantification of nuclear pleomorphism in breast cancer.