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Computer-aided polyp characterization in colonoscopy: sufficient performance or not?
Natalie Halvorsen, Yuichi Mori
Clin Endosc 2024;57(1):18-23.   Published online January 5, 2024
DOI: https://doi.org/10.5946/ce.2023.092
AbstractAbstract PDFPubReaderePub
Computer-assisted polyp characterization (computer-aided diagnosis, CADx) facilitates optical diagnosis during colonoscopy. Several studies have demonstrated high sensitivity and specificity of CADx tools in identifying neoplastic changes in colorectal polyps. To implement CADx tools in colonoscopy, there is a need to confirm whether these tools satisfy the threshold levels that are required to introduce optical diagnosis strategies such as “diagnose-and-leave,” “resect-and-discard” or “DISCARD-lite.” In this article, we review the available data from prospective trials regarding the effect of multiple CADx tools and discuss whether they meet these thresholds.
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Diagnosing Gastric Mesenchymal Tumors by Digital Endoscopic Ultrasonography Image Analysis
Moon Won Lee, Gwang Ha Kim
Clin Endosc 2021;54(3):324-328.   Published online June 18, 2020
DOI: https://doi.org/10.5946/ce.2020.061
AbstractAbstract PDFPubReaderePub
Gastric mesenchymal tumors (GMTs) are incidentally discovered in national gastric screening programs in Korea. Endoscopic ultrasonography (EUS) is the most useful diagnostic modality for evaluating GMTs. The differentiation of gastrointestinal stromal tumors from benign mesenchymal tumors, such as schwannomas or leiomyomas, is important to ensure appropriate clinical management. However, this is difficult and operator dependent because of the subjective interpretation of EUS images. Digital image analysis computes the distribution and spatial variation of pixels using texture analysis to extract useful data, enabling the objective analysis of EUS images and decreasing interobserver and intraobserver agreement in EUS image interpretation. This review aimed to summarize the usefulness and future of digital EUS image analysis for GMTs based on published reports and our experience.

Citations

Citations to this article as recorded by  
  • Schwannoma gástrico. Reporte de un caso
    Darío Montes N, Nixon Cevallos R, Rubén Montes N
    Oncología (Ecuador).2024; 34(1): 52.     CrossRef
  • Artificial Intelligence-Based Diagnosis of Gastric Mesenchymal Tumors Using Digital Endosonography Image Analysis
    Dong Chan Joo, Gwang Ha Kim, Moon Won Lee, Bong Eun Lee, Ji Woo Kim, Kwang Baek Kim
    Journal of Clinical Medicine.2024; 13(13): 3725.     CrossRef
  • A combined radiomic model distinguishing GISTs from leiomyomas and schwannomas in the stomach based on endoscopic ultrasonography images
    Xian‐Da Zhang, Ling Zhang, Ting‐Ting Gong, Zhuo‐Ran Wang, Kang‐Li Guo, Jun Li, Yuan Chen, Jian‐Tao Zhang, Ben‐Gong Ye, Jin Ding, Jian‐Wei Zhu, Feng Liu, Duan‐Min Hu, JianGang Chen, Chun‐Hua Zhou, Duo‐Wu Zou
    Journal of Applied Clinical Medical Physics.2023;[Epub]     CrossRef
  • An Esophageal Leiomyoma with Cystic Degeneration Mimicking a Malignant Neoplasm
    Gwang Ha Kim, Dong Chan Joo, Moon Won Lee, Bong Eun Lee, Kyungbin Kim
    The Ewha Medical Journal.2023;[Epub]     CrossRef
  • Advancements in the Diagnosis of Gastric Subepithelial Tumors
    Osamu Goto, Mitsuru Kaise, Katsuhiko Iwakiri
    Gut and Liver.2022; 16(3): 321.     CrossRef
  • Schwannoma gástrico. Diagnóstico diferencial de tumores submucosos
    M. Reyes Busta Nistal, Noelia Alcaide Suarez, Luis Fernández Salazar, Daniel Corrales Cruz
    Gastroenterología y Hepatología.2021;[Epub]     CrossRef
  • Scoring systems for differentiating gastrointestinal stromal tumors and schwannomas from leiomyomas in the stomach
    Shotaro Okanoue, Masaya Iwamuro, Takehiro Tanaka, Takuya Satomi, Kenta Hamada, Hiroyuki Sakae, Makoto Abe, Yoshiyasu Kono, Hiromitsu Kanzaki, Seiji Kawano, Yoshiro Kawahara, Hiroyuki Okada
    Medicine.2021; 100(40): e27520.     CrossRef
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