Teoh Chai Ling, Tan Xiao Jian, Ab Rahman Khairul Shakir, Bakrin Ikmal Hisyam, Goh Kam Meng, Siet Joseph Jiun Wen, Wan Muhamad Wan Zuki Azman
Department of Electrical and Electronics Engineering, Faculty of Engineering and Technology, Tunku Abdul Rahman University of Management and Technology (TAR UMT), Jalan Genting Kelang, Setapak, Kuala Lumpur 53300, Malaysia.
Biomedical and Bioinformatics Engineering (BBE) Research Group, Centre for Multimodal Signal Processing, Department of Electrical and Electronic Engineering, Faculty of Engineering and Technology, Tunku Abdul Rahman University of Management and Technology (TAR UMT), Jalan Genting Kelang, Setapak, Kuala Lumpur 53300, Malaysia.
Diagnostics (Basel). 2024 Sep 14;14(18):2045. doi: 10.3390/diagnostics14182045.
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.
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 ESize, EShape, and EAppearance. These equations are then integrated into a unified model termed Harmonic Mean (). The 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.
The proposed 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.
In summary, this study proposes the equation as a novel feature for the precise quantification of nuclear pleomorphism in breast cancer.
背景/目的：核多形性是诺丁汉组织病理学分级（NHG）系统下乳腺癌分级的关键决定因素，但现有文献对其量化仍不充分。受此差距的推动，我们的研究旨在根据NHG系统，研究并建立不同核多形性评分的形态学特征之间的相关性。我们旨在量化这些评分中的核多形性，并将我们提出的测量方法与真实数据进行验证。
首先，我们将核多形性的描述解构为三个核心要素：大小、形状和外观。随后，这些要素被数学建模为方程，分别称为ESize、EShape和EAppearance。然后，这些方程被整合到一个统一的模型中，称为调和均值（）。对于表现出3级核多形性特征的细胞核，该方程产生的值接近1，而对于表现出1级核多形性特征的细胞核，该值接近0。
所提出的模型展示了有前景的性能指标，包括准确率、召回率、特异性、精确率和F1分数，其值分别为0.97、0.96、0.97、0.94和0.95。
总之，本研究提出该方程作为精确量化乳腺癌核多形性的一种新特征。
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