基于磁性纳米粒子的磁共振成像技术在前列腺癌诊断和预后评估中的应用。

IF 2.5 4区医学 Q3 BIOCHEMICAL RESEARCH METHODS

SLAS Technology Pub Date : 2024-11-22 DOI:10.1016/j.slast.2024.100225

Wanhui Wang , Xiaodan Liu , Xuedong Li , Bo Geng , Enyang Zhao

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引用次数: 0

摘要

目标目标：前列腺癌是男性最常见的恶性肿瘤之一：前列腺癌是男性最常见的恶性肿瘤之一。早期诊断和预后评估对前列腺癌的治疗和预防具有重要意义。本研究旨在探讨基于磁纳米粒子的磁共振成像技术在前列腺癌诊断和预后评估中的应用。选取我院2018年9月-2021年1月共81例患者作为研究对象，均为疑似前列腺癌患者，在磁共振成像和直肠超声的引导下进行前列腺检测，根据病理结果将患者分为前列腺癌群组和良性前列腺增生组。前列腺癌的成像是通过磁性纳米粒子对磁场的反应来实现的。患者的磁共振成像图像由专业软件采集和分析。该技术可提供高分辨率图像，准确检测和定位肿瘤，还可评估前列腺癌的严重程度，预测患者的预后。

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Application of MRI imaging technology based on magnetic nanoparticles in diagnosis and prognosis evaluation of prostate cancer

Objective: Objective: Prostate cancer is one of the most common malignant tumors in men. Early diagnosis and prognosis evaluation are of great significance for the treatment and prevention of prostate cancer. The purpose of this study was to explore the application of magnetic nanoparticle-based MRI imaging technology in the diagnosis and prognosis assessment of prostate cancer. A total of 81 patients in our hospital from September 2018 to January 2021 were selected as the study objects, all suspected prostate cancer patients, and prostate detection was performed under the guidance of MRI and rectal ultrasound.According to the pathological results, the patients were divided into prostate cancer cluster group and benign prostatic hyperplasia group. Imaging of prostate cancer is achieved by the response of magnetic nanoparticles to magnetic fields. MRI images of patients were collected and analyzed using professional software. It can provide high-resolution images that enable accurate detection and localization of tumors, and the technology can also assess the severity of prostate cancer and predict a patient's prognosis.

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来源期刊

SLAS Technology Computer Science-Computer Science Applications

CiteScore

6.30

自引率

7.40%

发文量

审稿时长

106 days

期刊介绍： SLAS Technology emphasizes scientific and technical advances that enable and improve life sciences research and development; drug-delivery; diagnostics; biomedical and molecular imaging; and personalized and precision medicine. This includes high-throughput and other laboratory automation technologies; micro/nanotechnologies; analytical, separation and quantitative techniques; synthetic chemistry and biology; informatics (data analysis, statistics, bio, genomic and chemoinformatics); and more.