BACKGROUND: Spectral analysis of the radiofrequency (RF) signals that underlie grayscale EUS images has been used to provide quantitative, objective information about tissue histology. 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.
BACKGROUND: Spectral analysis of the radiofrequency (RF) signals that underlie grayscale EUS images has been used to provide quantitative, objective information about tissue histology. 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.
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Authors: Ronald E Kumon; Michael J Pollack; Ashley L Faulx; Kayode Olowe; Farees T Farooq; Victor K Chen; Yun Zhou; Richard C K Wong; Gerard A Isenberg; Michael V Sivak; Amitabh Chak; Cheri X Deng Journal: Gastrointest Endosc Date: 2009-11-17 Impact factor: 9.427
Authors: Ronald E Kumon; Kayode Olowe; Ashley L Faulx; Farees T Farooq; Victor K Chen; Yun Zhou; Richard C K Wong; Gerard A Isenberg; Michael V Sivak; Amitabh Chak; Cheri X Deng Journal: Gastrointest Endosc Date: 2007-10-29 Impact factor: 9.427
Authors: Lawrence Mj Best; Vishal Rawji; Stephen P Pereira; Brian R Davidson; Kurinchi Selvan Gurusamy Journal: Cochrane Database Syst Rev Date: 2017-04-17
Authors: Madhu Sudhan Reddy Gudur; Rameshwar R Rao; Alexis W Peterson; David J Caldwell; Jan P Stegemann; Cheri X Deng Journal: PLoS One Date: 2014-01-22 Impact factor: 3.240