Review: Comparison of traditional and modern diagnostic methods in breast cancer

IF 5.2 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Measurement Pub Date : 2024-11-16 DOI:10.1016/j.measurement.2024.116258

Hussein Kareem Elaibi , Farah Fakhir Mutlag , Ebru Halvaci , Aysenur Aygun , Fatih Sen

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引用次数: 0

Abstract

The development of non-invasive sensor detection systems is crucial for the effective diagnosis of many types of cancer, including breast cancer. Currently, many diagnostic tools such as CT, mammography, MRI, and ultrasound are used, but more convenient and user-friendly sensors are under development. New sensors provide immediate and non-invasive ways to assess the impact of treatment on physiologic markers and overall disease progression. Innovative devices like iBreastExam, Skinsar™, and iTBra, include personalized sensors such as wearables and non-wearable sensors implanted inside the body. Early methods of detecting breast cancer can be accurate and cost-effective. Recurrence can be predicted and monitored through chemical sensors that detect tumor DNA or proteins circulating in the blood. In addition, monitoring patients with cancer using smart implants, thermal sensors, and image-based sensors provides capability at the level of tissue structure. This article provides an overview of the various sensors used in monitoring cancer patients.

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回顾：乳腺癌传统诊断方法与现代诊断方法的比较

开发无创传感器检测系统对于有效诊断包括乳腺癌在内的多种癌症至关重要。目前，许多诊断工具，如 CT、乳腺 X 射线照相术、核磁共振成像和超声波等都在使用，但更方便、更易操作的传感器正在开发中。新的传感器提供了即时、无创的方法来评估治疗对生理指标和整体疾病进展的影响。iBreastExam、Skinsar™ 和 iTBra 等创新设备包括个性化传感器，如植入体内的可穿戴和非可穿戴传感器。早期检测乳腺癌的方法既准确又经济。通过化学传感器检测血液中循环的肿瘤 DNA 或蛋白质，可以预测和监测复发情况。此外，利用智能植入物、热传感器和基于图像的传感器对癌症患者进行监测，可提供组织结构层面的能力。本文概述了用于监测癌症患者的各种传感器。

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

Measurement 工程技术-工程：综合

CiteScore

10.20

自引率

12.50%

发文量

1589

审稿时长

12.1 months

期刊介绍： Contributions are invited on novel achievements in all fields of measurement and instrumentation science and technology. Authors are encouraged to submit novel material, whose ultimate goal is an advancement in the state of the art of: measurement and metrology fundamentals, sensors, measurement instruments, measurement and estimation techniques, measurement data processing and fusion algorithms, evaluation procedures and methodologies for plants and industrial processes, performance analysis of systems, processes and algorithms, mathematical models for measurement-oriented purposes, distributed measurement systems in a connected world.