Design and Analysis of Surface Plasmon Resonance-Based Refractive Index Biosensor for Detection of Colorectal Cancer with Machine Learning Approach

IF 4.3 4区物理与天体物理 Q2 CHEMISTRY, PHYSICAL

Plasmonics Pub Date : 2025-02-05 DOI:10.1007/s11468-024-02720-8

Yahya Ali Abdelrahman Ali, Trupti Kamani, Shobhit K. Patel, Taoufik Saidani, Abdulkarem H. M. Almawgani, Basim Ahmad Alabsi

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引用次数: 0

Abstract

The preliminary detection of colon cancer serves as critically important in optimizing patient outcomes and chances of survival. A surface plasmon resonance-based refractive index biosensor provides an incredible approach to the non-invasive, superior sensitive detection of colon cancerous tumors. In this proposed work, the design and analysis of the SPR-based square within an incomplete circle refractive index biosensor (SWICRIB) for determination of the colorectal cancer has been reported. This innovative design integrates the advantages of the SPR method with a unique geometry configuration which enhances sensitivity and specificity. Our results demonstrate that SWICRIB’s superior performance in detecting low-concentration analytes makes it a promising tool for early diagnosis and monitoring of colon cancer biomarkers. This study explores the various applications of the SPR-based biosensor in identifying the refractive index contrast between normal colonic mucosa (cecum and sigmoid) and some different kinds of colorectal tumors such as tubulovillous adenomas and adenocarcinomas. The working range of the reported SWICRIB is 1870 nm to 1950 nm. By utilization of the SPR method, we measure the changes in the refractive index at the metal–dielectric interface demonstrating the potential for precise and early detection of colon cancerous cells. For the superior results with a sensitivity of 700 RIU/nm for detecting adenocarcinoma (Ad) cancer cell, the quality factor is 818.52 nm/RIU for tubulovillous adenoma (TA) cancer cell, and a figure of merit is 298.81 adenocarcinomas (Ad) cancer cell. The superior value 0.001631 has been achieved as a detection limit value. The outcomes suggest that reported SWICRIB can differentiate between healthy and cancerous tissues with high accuracy which paves the way for their integration into routine diagnostic techniques. In the reported sensor work, the machine learning (ML) functional on the width variation (4600–5200 nm) and highest R² evaluation explores 0.96.

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基于机器学习方法的表面等离子共振折射率生物传感器的设计与分析

结肠癌的初步检测对于优化患者的预后和生存机会至关重要。基于表面等离子共振的折射率生物传感器为非侵入性、高灵敏度的结肠癌肿瘤检测提供了一种令人难以置信的方法。本文报道了基于spr的方形不完全圆折射率生物传感器（SWICRIB）的设计和分析，用于结直肠癌的检测。这种创新的设计结合了SPR方法的优点和独特的几何结构，提高了灵敏度和特异性。我们的研究结果表明，SWICRIB在检测低浓度分析物方面的优越性能使其成为早期诊断和监测结肠癌生物标志物的有希望的工具。本研究探讨了基于spr的生物传感器在识别正常结肠粘膜（盲肠和乙状结肠）与不同类型结直肠肿瘤（如管绒毛状腺瘤和腺癌）的折射率对比中的各种应用。报道的SWICRIB的工作范围为1870 nm ~ 1950 nm。利用SPR方法，我们测量了金属-介电界面折射率的变化，证明了精确和早期检测结肠癌细胞的潜力。对腺癌（Ad）癌细胞的检测灵敏度为700 RIU/nm，对管绒毛腺瘤（TA）癌细胞的质量因子为818.52 nm/RIU，对腺癌（Ad）癌细胞的质量因子为298.81。检测极限值达到了优越值0.001631。结果表明，报道的SWICRIB可以高精度地区分健康组织和癌组织，这为将其整合到常规诊断技术中铺平了道路。在报告的传感器工作中，机器学习（ML）对宽度变化（4600-5200 nm）的功能和最高R2评估为0.96。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Plasmonics 工程技术-材料科学：综合

CiteScore

5.90

自引率

6.70%

发文量

164

审稿时长

2.1 months

期刊介绍： Plasmonics is an international forum for the publication of peer-reviewed leading-edge original articles that both advance and report our knowledge base and practice of the interactions of free-metal electrons, Plasmons. Topics covered include notable advances in the theory, Physics, and applications of surface plasmons in metals, to the rapidly emerging areas of nanotechnology, biophotonics, sensing, biochemistry and medicine. Topics, including the theory, synthesis and optical properties of noble metal nanostructures, patterned surfaces or materials, continuous or grated surfaces, devices, or wires for their multifarious applications are particularly welcome. Typical applications might include but are not limited to, surface enhanced spectroscopic properties, such as Raman scattering or fluorescence, as well developments in techniques such as surface plasmon resonance and near-field scanning optical microscopy.