BACKGROUND: EUS elastography was reported to offer supplemental information that allows a better characterization of tissue, and that might enhance conventional EUS imaging. OBJECTIVE: Our purpose was to apply real-time elastography during EUS examinations and to assess the accuracy of the differentiation of benign versus malignant lymph nodes. DESIGN: Prospective cross-sectional feasibility study. SETTING: Department of Surgical Gastroenterology, Gentofte University Hospital, Hellerup, Denmark. PATIENTS: Patients diagnosed by EUS with cervical, mediastinal, or abdominal lymph nodes were included, with a total number of 78 lymph nodes examined. The final diagnosis of the type of lymph node was obtained by EUS-FNA cytologic analysis or by surgical pathologic examination and by a minimum 6 months of follow-up. INTERVENTIONS: Hue histogram analysis of the average images computed from EUS elastography movies was used to assess the color information inside the region of interest and to consequently differentiate benign and malignant lymph nodes. MAIN OUTCOME MEASUREMENTS: Differentiate between malignant and benign lymph nodes. RESULTS: By using mean hue histogram values, the sensitivity, specificity, and accuracy for the differential diagnosis were 85.4%, 91.9%, and 88.5%, respectively, on the basis of a cutoff level of 166 (middle of green-blue rainbow scale). The proposed method might be useful to avoid color perception errors, moving artifacts, or possible selection bias induced by analysis of still images. LIMITATIONS: Lack of the surgical standard in all cases. CONCLUSIONS: Computer-enhanced dynamic analysis based on hue histograms of the EUS elastography movies represents a promising method that allows the differential diagnosis of benign and malignant lymph nodes, offering complementary information added to conventional EUS imaging.
BACKGROUND: EUS elastography was reported to offer supplemental information that allows a better characterization of tissue, and that might enhance conventional EUS imaging. OBJECTIVE: Our purpose was to apply real-time elastography during EUS examinations and to assess the accuracy of the differentiation of benign versus malignant lymph nodes. DESIGN: Prospective cross-sectional feasibility study. SETTING: Department of Surgical Gastroenterology, Gentofte University Hospital, Hellerup, Denmark. PATIENTS: Patients diagnosed by EUS with cervical, mediastinal, or abdominal lymph nodes were included, with a total number of 78 lymph nodes examined. The final diagnosis of the type of lymph node was obtained by EUS-FNA cytologic analysis or by surgical pathologic examination and by a minimum 6 months of follow-up. INTERVENTIONS: Hue histogram analysis of the average images computed from EUS elastography movies was used to assess the color information inside the region of interest and to consequently differentiate benign and malignant lymph nodes. MAIN OUTCOME MEASUREMENTS: Differentiate between malignant and benign lymph nodes. RESULTS: By using mean hue histogram values, the sensitivity, specificity, and accuracy for the differential diagnosis were 85.4%, 91.9%, and 88.5%, respectively, on the basis of a cutoff level of 166 (middle of green-blue rainbow scale). The proposed method might be useful to avoid color perception errors, moving artifacts, or possible selection bias induced by analysis of still images. LIMITATIONS: Lack of the surgical standard in all cases. CONCLUSIONS: Computer-enhanced dynamic analysis based on hue histograms of the EUS elastography movies represents a promising method that allows the differential diagnosis of benign and malignant lymph nodes, offering complementary information added to conventional EUS imaging.
Authors: Xin-Wu Cui; Christian Jenssen; Adrian Saftoiu; Andre Ignee; Christoph F Dietrich Journal: World J Gastroenterol Date: 2013-08-14 Impact factor: 5.742
Authors: Xin-Wu Cui; Jian-Min Chang; Quan-Cheng Kan; Liliana Chiorean; Andre Ignee; Christoph F Dietrich Journal: World J Gastroenterol Date: 2015-12-21 Impact factor: 5.742
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