Akhtar Munir, Siddique Muhammad Abubakar, Majid Muhammad Abdul, Parveen Shahida, Mehmood Rubaida, Ashraf Sumara, Fida Irum, Hatamleh Wesam Atef, Dad Muhammad Umar, Ullah Hafeez
Biophotonics Imaging Techniques Laboratory, Institute of Physics, The Islamia University of Bahawalpur, Bahawalpur, Pakistan.
Gynecology & Obs Dept. Ward No 17, Nishtar Medical University & Hospital, Multan, Pakistan.
Lasers Med Sci. 2025 Mar 1;40(1):122. doi: 10.1007/s10103-025-04285-2.
Among women worldwide, breast cancer is one of the most common cancers results from the growth of cancerous cells. This work investigates 87 patients using polarimetry in the visible spectral range (400-800 nm). Polarimetry is used for tissue characterization, particularly to prognosis cancer and biochemical quantification. Nine derived polarization properties were compared for both malignant and benign breast tissue. All nine polarimetric properties have high values for Grade III as compared to grade II and fibroadenoma. Benign tumours have higher anisotropy than malignant tumors. Ellipticity and orientation exhibit an inverse tendency. Hematology shows that moringa significantly improves the blood components of breast cancer. Pearson & Spearman correlation analysis was used with level of significance p < 0.05 where' p' is probability that the observed effect within the study would have occurred by chance. All parameters and components show significance level expect Leukocytes, Urea, Creatinine, SGOT and Bilirubin Total. Model training is a difficult procedure that determines the quality of application upon which it is deployed. Our data produces the accuracy 82.8%, with 1360 observations and 38 predictors. Thus a framework for breast cancer prognosis is provided by the combination of polarisation analysis, math and classification techniques.
在全球女性中,乳腺癌是由癌细胞生长导致的最常见癌症之一。这项研究对87名患者在可见光谱范围(400 - 800纳米)内使用偏振测量法进行了调查。偏振测量法用于组织表征,特别是用于癌症预后和生化定量分析。对恶性和良性乳腺组织的九种衍生偏振特性进行了比较。与二级和纤维腺瘤相比,所有九种偏振特性在三级时都具有较高的值。良性肿瘤比恶性肿瘤具有更高的各向异性。椭圆率和取向呈现相反的趋势。血液学研究表明,辣木能显著改善乳腺癌患者的血液成分。使用Pearson和Spearman相关性分析,显著性水平p < 0.05,其中“p”是研究中观察到的效应偶然发生的概率。除白细胞、尿素、肌酐、谷草转氨酶和总胆红素外,所有参数和成分均显示出显著性水平。模型训练是一个困难的过程,它决定了所部署应用程序的质量。我们的数据在1360次观察和38个预测因子的情况下,准确率达到了82.8%。因此,偏振分析、数学和分类技术的结合为乳腺癌预后提供了一个框架。