In Vivo Characterization of Pancreatic and Lymph Node Tissue using Endoscopic Ultrasound Spectrum Analysis: Validation Study

Abstract

Background—Quantitative spectral analysis of the radio-frequency (RF) signals that underlie grayscale EUS images can be used to provide additional, objective information about tissue state. Objective—Our purpose was to validate RF spectral analysis as a method to distinguish between (1) benign and malignant lymph nodes and (2) normal pancreas (NP), chronic pancreatitis (CP) and pancreatic cancer (PC). Design & Setting—A prospective validation study of eligible patients was conducted to compare with pilot study RF data. Patients—Forty-three patients underwent EUS of the esophagus, stomach, pancreas, and surrounding intra-abdominal and mediastinal lymph nodes (19 from previous pilot study and 24 additional patients). Main Outcome Measurements—Midband fit, slope, intercept, and correlation coefficient from a linear regression of the calibrated RF power spectra were determined. Results—Discriminant analysis of mean pilot-study parameters was then performed to classify validation-study parameters. For benign vs. malignant lymph nodes, midband-fit and intercept (both with t-test p < 0.058) provided classification with 67% accuracy and area under ROC curve (AUC) of 0.86. For diseased vs. NP, midband-fit and correlation coefficient (both with ANOVA p < 0.001) provided 93% accuracy and AUC of 0.98. For PC vs. CP, the same parameters provided 77% accuracy and AUC of 0.89. Results improved further when classification was performed with all data. Limitations—Moderate sample size and spatial averaging inherent to the technique. Conclusions—This study confirms that mean spectral parameters provide a non-invasive method to quantitatively discriminate benign and malignant lymph nodes as well as normal and diseased pancreas.