磁共振表观扩散系数成像在鉴别肺癌和肺良性病变中的应用

郝永杰, 邓军吉, 冯坤, 杜汉旺, 陈伟, 魏瑶, 崔传水

湖南师范大学学报医学版 ›› 2024, Vol. 21 ›› Issue (1) : 98-102.

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湖南师范大学学报医学版 ›› 2024, Vol. 21 ›› Issue (1) : 98-102.
临床医学

磁共振表观扩散系数成像在鉴别肺癌和肺良性病变中的应用

  • 郝永杰1, 邓军吉1, 冯坤2, 杜汉旺2, 陈伟1, 魏瑶1, 崔传水1
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Application of magnetic resonance apparent diffusion coefficient imaging in differentiating lung cancer from benign lung lesions

  • HAO Yongjie1, DENG Junji1, FENG Kun2, DU Hanwang2, CHEN Wei1, WEI Yao1, CUI Chuanshui1
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摘要

目的 评估基于表观扩散系数的磁共振扩散加权成像不同模型在鉴别肺癌和肺良性病变中的应用效果。方法 这项回顾性单中心研究选择2020年1月―2021年6月49例患者为研究对象,包括肺癌组(n=32)和良性病变组(n=17)。所有患者在手术或活检前均接受了扩散加权成像(DWI)检查。ADC直方图参数,包括平均值、百分位值(第10位和第90位)、峰态和偏度,由两名放射科医生独立计算。比较肺癌患者和良性病变患者的直方图参数。构建接收者操作特征曲线以评估这些参数的诊断性能。结果 肺癌组中的ADC平均值、ADC10th 、D平均值和D10th 显著低于良性病变组,并且ADC偏度和D偏度显著高于良性病变组。D10th和ADC10th诊断良性病变能力最好。D10th的曲线下面积(AUC)为0.851,在0.453×10-3 mm/s的最佳临界值下的准确率为79.6%;ADC10th的AUC为0.814,在0.504×10-3 mm/s最佳临界值下的准确率为83.4%。结论 使用DWI单指数和双指数模型得出的ADC参数进行全病灶直方图分析可以区分肺癌与良性病灶。

Abstract

Objective To evaluate the application effect of different MRI diffusion-weighted imaging models based on the apparent diffusion coefficient in distinguishing lung cancer from benign lung lesions. Methods This retrospective single-center study selected 49 patients from January 2020 to June 2021 as the study subjects, including the lung cancer group (n=32) and the benign disease group (n=17). All patients underwent diffusion-weighted imaging (DWI) before surgery or biopsy. ADC histogram parameters, including mean, percentile values (10th and 90th), kurtosis, and skewness, were calculated independently by two radiologists. The histogram parameters were compared between patients with lung cancer and benign lesions. ROC curves were constructed to evaluate the diagnostic performance. Results The ADCmean, ADC10th, Dmean and D10th in the lung cancer group were significantly lower than the benign lesion group, and the ADCskewness and Dskewness were significantly higher than the benign lesion group. D10th and ADC10th had the best ability to diagnose benign lesions. The area under the curve (AUC) of D10th was 0.851, and the accuracy was 79.6% at the best critical value of 0.453×10-3 mm/s; the AUC of ADC10th was 0.814, and the accuracy was 83.4% at the best critical value of 0.504×10-3 mm/s. Conclusions Whole-lesion histogram analysis of ADC parameters derived from the DWI single-index and double-index models can distinguish lung cancer from benign lesions.

关键词

弥散加权磁共振成像 / 磁共振成像 / 肺癌 / 肺良性病变 / 表观扩散系数 / ADC直方图

Key words

diffusion-weighted magnetic resonance imaging / magnetic resonance imaging / lung cancer / lung benign lesion / apparent diffusion coefficient / ADC histogram

引用本文

导出引用
郝永杰, 邓军吉, 冯坤, 杜汉旺, 陈伟, 魏瑶, 崔传水. 磁共振表观扩散系数成像在鉴别肺癌和肺良性病变中的应用[J]. 湖南师范大学学报医学版. 2024, 21(1): 98-102
HAO Yongjie, DENG Junji, FENG Kun, DU Hanwang, CHEN Wei, WEI Yao, CUI Chuanshui. Application of magnetic resonance apparent diffusion coefficient imaging in differentiating lung cancer from benign lung lesions[J]. Journal of Hunan Normal University(Medical Science). 2024, 21(1): 98-102
中图分类号: R734   

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基金

山东省卫生健康委员会科研项目“磁共振表观扩散系数成像在不同模型在鉴别肺癌和肺良性病变中的应用”(20200125); 2020年度潍坊市卫健委科研项目计划“磁共振表观扩散系数成像在不同模型在鉴别肺癌和肺良性病变中的应用”(WFWSJK-2020-103)

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