Application effect of 18F-FDG PET/CT technique in diagnosis and prognosis evaluation of lymphoma

IF 2.5 4区医学 Q3 BIOCHEMICAL RESEARCH METHODS SLAS Technology Pub Date : 2024-08-14 DOI:10.1016/j.slast.2024.100176

Chao Huang , Haihua Hu , Xuesheng Zheng

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Abstract

The objective of the study was to research diagnostic and prognostic values of 18F fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) in patients with diffuse large B-cell lymphoma (DLBCL). The diagnostic sensitivity (Sen) of PET/CT (94.75 %) was remarkably higher than 83.56 % of B-US. Age ≥ 65 years old, maximum focal diameter ≥5 cm, clinical stages III-IV, systemic symptoms, increased lactate dehydrogenase level, high modified international prognostic index score, Ecog score ≥1, B-cell lymphoma 2 (Bcl-2) gene, MYC protein expression rate, metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were all factors that influenced the recurrence or progression of DLBCL. With higher MTV and TLG, patients would have a greater probability of recurrence or progression. 18F-FDG PET/CT showed a high diagnostic Sen in lymphoma lesions, and could accurately guide clinical staging. Combined with clinical parameters, laboratory indicators, and metabolic parameters, prognostic indicators of patients could be evaluated more accurately.

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18F-FDG PET/CT 技术在淋巴瘤诊断和预后评估中的应用效果

该研究旨在研究18F氟脱氧葡萄糖（FDG）正电子发射断层扫描（PET）/计算机断层扫描（CT）对弥漫大B细胞淋巴瘤（DLBCL）患者的诊断和预后价值。PET/CT 的诊断灵敏度（Sen）（94.75%）明显高于 B-US 的 83.56%。年龄≥65岁、病灶最大直径≥5厘米、临床分期Ⅲ-Ⅳ期、全身症状、乳酸脱氢酶水平升高、改良国际预后指数评分高、Ecog评分≥1、B细胞淋巴瘤2（Bcl-2）基因、MYC蛋白表达率、代谢性肿瘤体积（MTV）和病灶总糖酵解（TLG）都是影响DLBCL复发或进展的因素。MTV和TLG越高，患者复发或进展的可能性就越大。18F-FDG PET/CT 对淋巴瘤病变有很高的诊断价值，能准确指导临床分期。结合临床指标、实验室指标和代谢指标，可以更准确地评估患者的预后指标。

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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.