In vivo characterization of pancreatic and lymph node tissue by using EUS spectrum analysis: a validation study

Abstract

Background: Quantitative spectral analysis of the radiofrequency (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, chronic pancreatitis, and pancreatic cancer.

Design and 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 a 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 versus malignant lymph nodes, midband fit and intercept (both with t test P < .058) provided classification with 67% accuracy and area under the receiver operating curve (AUC) of 0.86. For diseased versus normal pancreas, midband fit and correlation coefficient (both with analysis of variance P < .001) provided 93% accuracy and an AUC of 0.98. For pancreatic cancer versus chronic pancreatitis, the same parameters provided 77% accuracy and an 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 noninvasive method to quantitatively discriminate benign and malignant lymph nodes as well as normal and diseased pancreas.

Figure 1

Radio-frequency (RF) signal used for spectral calibration. A, Ultrasound pulse for the C5 mode of EUS system. B, Corresponding power spectrum. The usable bandwidth, defined by the range within −15 dB from the maximum of the spectrum, is 2 to 10.6 MHz or 8.6 MHz.

Figure 2

Linear discriminant analysis and receiver operating characteristics (ROC) curves for the lymph node data. A, Scatterplot of data from Study 1 (pilot study) and Study 2 (validation study) with coordinates given by midband fit and intercept. The dividing line between benign and malignant classification is based on linear discriminant analysis of Study 1 data only (training set). B, Corresponding binormal maximum likelihood estimate of the ROC curve with discriminant scores from Study 2 only (testing set). The area the curve is 0.86. (See Table 2 for the corresponding classification matrix.)

Figure 3

Linear discriminant analysis and receiver operating characteristics (ROC) curves for the pancreas data. A, Scatterplot of data from Study 1 (pilot study) and Study 2 (validation study) with coordinates given by midband fit and correlation coefficient R². The dividing lines for the classification of normal pancreas (NP) vs diseased pancreas (PC and CP together) [solid] and pancreatic cancer (PC) vs. chronic pancreatitis (CP) excluding NP [dashed] are based on linear discriminant analysis of Study 1 data only (training set). The legend indicates which tissue state and study number corresponds to each point. B, Corresponding binormal maximum likelihood estimates of the ROC curves for each classification with discriminant scores from Study 2 only (testing set). The area under each curve is given in the legend. (See Tables 4 and 5 for the corresponding classification matrices.)