4.1 Article

Contrast-enhanced harmonic endoscopic ultrasound using time-intensity curve analysis predicts pathological grade of pancreatic neuroendocrine neoplasm

Journal

JOURNAL OF MEDICAL ULTRASONICS
Volume 46, Issue 4, Pages 449-458

Publisher

SPRINGER JAPAN KK
DOI: 10.1007/s10396-019-00967-x

Keywords

Contrast-enhanced harmonic endoscopic ultrasound (CH-EUS); Pancreatic neuroendocrine neoplasm (PNEN); Time-intensity curve (TIC) analysis

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Purpose Histological grading is important for the treatment algorithm in pancreatic neuroendocrine neoplasms (PNEN). The present study examined the efficacy of contrast-enhanced harmonic endoscopic ultrasound (CH-EUS) and time-intensity curve (TIC) analysis of PNEN diagnosis and grading. Methods TIC analysis was performed in 30 patients using data obtained from CH-EUS, and a histopathological diagnosis was made via EUS-guided fine-needle aspiration or surgical resection. The TIC parameters were analyzed by dividing them into G1/G2 and G3/NEC groups. Then, patients were classified into non-aggressive and aggressive groups and evaluated. Results Twenty-six patients were classified as G1/G2, and four as G3/NEC. From the TIC analysis, five parameters were obtained (I: echo intensity change, II: time for peak enhancement, III: speed of contrast, IV: decrease rate for enhancement, and V: enhancement ratio for node/pancreatic parenchyma). Three of these parameters (I, IV, and V) showed high diagnostic performance. Using the cutoff value obtained from the receiver-operating characteristic (ROC) analysis, the correct diagnostic rates of parameters I, IV, and V were 96.7%, 100%, and 100%, respectively, between G1/G2 and G3/NEC. A total of 21 patients were classified into the non-aggressive group, and nine into the aggressive group. Using the cutoff value obtained from the ROC analysis, the accurate diagnostic rates of I, IV, and V were 86.7%, 86.7%, and 88.5%, respectively, between the non-aggressive and aggressive groups. Conclusion CH-EUS and TIC analysis showed high diagnostic accuracy for grade diagnosis of PNEN. Quantitative perfusion analysis is useful to predict PNEN grade diagnosis preoperatively.

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