Background
Spectral analysis of the radiofrequency (RF) signals that underlie grayscale EUS images has been used to provide quantitative,
Conclusions
This study shows that mean spectral parameters of the backscattered signals obtained by using electronic array echoendoscopes can provide a noninvasive method to quantitatively discriminate between CP and PC.
Objective
Our purpose was to validate RF spectral analysis as a method to distinguish between chronic pancreatitis (CP) and pancreatic cancer (PC). Design and setting: A prospective study of eligible patients was conducted to analyze the RF data obtained by using electronic array echoendoscopes. Patients: Pancreatic images were obtained by using electronic array echoendoscopes from 41 patients in a prospective study, including 15 patients with PC, 15 with CP, and 11 with a normal pancreas. Main outcome measurements: Midband fit, slope, intercept, correlation coefficient, and root mean square deviation from a linear regression of the calibrated power spectra were determined and compared among the groups.
Results
Statistical analysis showed that significant differences were observable between groups for mean midband fit, intercept, and root mean square deviation (t test, P < .05). Discriminant analysis of these parameters was then performed to classify the data. For CP (n = 15) versus PC (n = 15), the same parameters provided 83% accuracy and an area under the curve of 0.83. Limitations: Moderate sample size and spatial averaging inherent in the technique. Conclusions: This study shows that mean spectral parameters of the backscattered signals obtained by using electronic array echoendoscopes can provide a noninvasive method to quantitatively discriminate between CP and PC.