Kumon Ronald E, Pollack Michael J, Faulx Ashley L, Olowe Kayode, Farooq Farees T, Chen Victor K, Zhou Yun, Wong Richard C K, Isenberg Gerard A, Sivak Michael V, Chak Amitabh, Deng Cheri X
Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, USA.
Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:1949-52. doi: 10.1109/IEMBS.2009.5333462.
This study assessed the ability of spectral analysis of endoscopic ultrasound (EUS) RF signals acquired in humans in vivo to distinguish between (1) benign and malignant intraabdominal and mediastinal lymph nodes and (2) pancreatic cancer, chronic pancreatitis, and normal pancreas. Mean midband fit, slope, intercept, and correlation coefficient from a linear regression of the calibrated RF power spectra were computed over regions of interest defined by the endoscopist. Linear discriminant analysis was then performed to develop a classification of the resulting spectral parameters. For lymph nodes, classification based on the midband fit and intercept provided 67% sensitivity, 82% specificity, and 73% accuracy for malignant vs. benign nodes. For pancreas, classification based on midband fit and correlation coefficient provided 95% sensitivity, 93% specificity, and 93% accuracy for diseased vs. normal pancreas and 85% sensitivity, 71% specificity, and 85% accuracy for pancreatic cancer vs. chronic pancreatitis. These promising results suggest that mean spectral parameters can provide a non-invasive method to quantitatively characterize pancreatic cancer and lymph malignancy in vivo.
本研究评估了在人体体内获取的内镜超声（EUS）射频信号的频谱分析能力，以区分：（1）良性和恶性腹内及纵隔淋巴结；（2）胰腺癌、慢性胰腺炎和正常胰腺。在校定的射频功率谱线性回归中，计算内镜医师定义的感兴趣区域的平均中频拟合度、斜率、截距和相关系数。然后进行线性判别分析，以对所得频谱参数进行分类。对于淋巴结，基于中频拟合度和截距的分类对恶性与良性淋巴结的敏感性为67%，特异性为82%，准确率为73%。对于胰腺，基于中频拟合度和相关系数的分类对患病与正常胰腺的敏感性为95%，特异性为93%，准确率为93%；对胰腺癌与慢性胰腺炎的敏感性为85%，特异性为71%，准确率为85%。这些有前景的结果表明，平均频谱参数可提供一种在体内定量表征胰腺癌和淋巴结恶性病变的非侵入性方法。
