子宫颈癌淋巴结转移的诊断：结合磁共振图像与临床发现综合评估的计算机辅助诊断的效用

Diagnosis of lymph node metastasis in uterine cervical cancer: usefulness of computer-aided diagnosis with comprehensive evaluation of MR images and clinical findings.

作者信息

Kim Mi-hyun, Kim Jeong Kon, Lee Youngjoo, Park Bum-Woo, Lee Chang Kyung, Kim Namkug, Cho Gyunggoo, Choi Hyuck Jae, Cho Kyoung-Sik

机构信息

Department of Radiology, Research Institute of Radiology, Medical Imaging Laboratory, Asan Medical Center, University of Ulsan College of Medicine, Seoul.

出版信息

Acta Radiol. 2011 Dec 1;52(10):1175-83. doi: 10.1258/ar.2011.110202. Epub 2011 Oct 3.

DOI:10.1258/ar.2011.110202

PMID:21969698

Abstract

BACKGROUND

Lymph node (LN) status is an important parameter for determining the treatment strategy and for predicting the prognosis for patients with uterine cervical cancer. Computer-aided diagnosis (CAD) can be feasible for differentiating metastatic from non-metastatic lymph nodes in patients with uterine cervical cancer.

PURPOSE

To determine the usefulness of CAD that comprehensively evaluates MR images and clinical findings for detecting LN metastasis in uterine cervical cancer.

MATERIAL AND METHODS

In 680 LNs from 143 patients who underwent radical hysterectomy for uterine cervical cancer, the CAD system using the Bayesian classifier estimated the probability of metastasis based on MR findings and clinical findings. We compared the diagnostic accuracy for detecting metastatic LNs in the CAD and MR findings.

RESULTS

Metastasis was diagnosed in 70 (12%) LNs from 34 (24%) patients. The area under ROC curves of CAD (0.924) was greater than those of the mean ADC (0.854), minimum ADC (0.849), maximum ADC (0.827), short-axis diameter (0.856) and long-axis diameter (0.753) (P < 0.05). The specificity and accuracy of the CAD (86%, 86%) were greater than those of the mean ADC (77%, 77%), maximum ADC (77%, 77%), minimum ADC (68%, 70%), and short-axis diameter (65%, 67%) (P < 0.05).

CONCLUSION

CAD system can improve the diagnostic performance of MR for detecting metastatic LNs in uterine cervical cancer.

摘要

背景

淋巴结（LN）状态是决定子宫颈癌患者治疗策略和预测预后的重要参数。计算机辅助诊断（CAD）对于鉴别子宫颈癌患者的转移性和非转移性淋巴结可能是可行的。

目的

确定综合评估磁共振成像（MR）图像和临床发现的CAD在检测子宫颈癌淋巴结转移中的有用性。

材料与方法

在143例行子宫颈癌根治性子宫切除术患者的680个淋巴结中，使用贝叶斯分类器的CAD系统根据MR表现和临床发现估计转移概率。我们比较了CAD和MR表现检测转移性淋巴结的诊断准确性。

结果

在34例（24%）患者的70个（12%）淋巴结中诊断出转移。CAD的ROC曲线下面积（0.924）大于平均表观扩散系数（ADC）（0.854）、最小ADC（0.849）、最大ADC（0.827）、短轴直径（0.856）和长轴直径（0.753）的曲线下面积（P<0.05）。CAD的特异性和准确性（86%，86%）大于平均ADC（77%，77%）、最大ADC（77%，77%）、最小ADC（68%，70%）和短轴直径（65%，67%）的特异性和准确性（P<0.05）。