Distinguishing gastric anisakiasis from non-anisakiasis using unenhanced computed tomography

Ashida, Hirokazu; Igarashi, Takao; Morikawa, Kazuhiko; Motohashi, Kenji; Fukuda, Kunihiko; Tamai, Naoto

doi:10.1007/s00261-017-1214-4

Cited by 4 publications

(3 citation statements)

References 27 publications

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“…Furthermore, a diagnostic tool such as "anisakiasis diagnostic score (ADS)" might be instrumental in avoiding bias, leading to correct and appropriate treatment strategy selection Case Reports in Gastroenterology [14]. In the ADS study, cases that required emergency gastroduodenal endoscopy and noncontrast computed tomography (CT) were retrospectively investigated, and a score, which was indicative of the number of positive findings from five indicative CT findings (circumferential gastric wall thickening, gastric wall thickening extending more than two segments, bulky and low-density gastric wall thickening, increase in peri-gastric fat density, and ascites), was developed.…”

Section: Discussionmentioning

confidence: 99%

“…In the ADS study, cases that required emergency gastroduodenal endoscopy and noncontrast computed tomography (CT) were retrospectively investigated, and a score, which was indicative of the number of positive findings from five indicative CT findings (circumferential gastric wall thickening, gastric wall thickening extending more than two segments, bulky and low-density gastric wall thickening, increase in peri-gastric fat density, and ascites), was developed. The optimal cutoff score of 4 points indicated high sensitivity and specificity of 91% and 84%, respectively [ 14 ]. Although this ADS only focuses on CT findings, a more generally applicable risk stratification tool that focuses on clinical symptoms and blood test results is warranted.…”

Section: Discussionmentioning

confidence: 99%

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A Case of Nonagenarian Gastric Anisakiasis with Atypical Presentation

Arai,

Saito,

Kinebuchi

et al. 2024

Case Rep Gastroenterol

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Introduction: Anisakiasis is a parasitic disease caused by larvae from anisakid nematodes. In recent years, there has been an increase in cases of anisakiasis, a relatively uncommon medical condition. Case Presentation: A 93-year-old woman with chronic heart failure developed hives and nausea 6 h after eating silver flounder sashimi, leading to suspicion of fish allergy. Despite treatment, symptoms persisted and progressed to abdominal pain. An upper gastrointestinal endoscopy revealed an Anisakis larva in her stomach, an unusual finding given her age. After endoscopic removal of the living worm, the patient’s symptoms were relieved. Conclusion: A case of atypical anisakiasis in a 93-year-old patient was demonstrated. This case underscores the importance of considering atypical presentations in clinical decision-making.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

A Case of Nonagenarian Gastric Anisakiasis with Atypical Presentation

Arai,

Saito,

Kinebuchi

et al. 2024

Case Rep Gastroenterol

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“…CT is widely used for the diagnosis and preoperative examination of gastric diseases in clinical practice. 15 – 17 Therefore, as a noninvasive and economic imaging modality, CT is an optimal method to differentiate these two diseases.…”

Section: Introductionmentioning

confidence: 99%

Differentiation of gastric glomus tumor from small gastric stromal tumor by computed tomography

Wang

Liu

et al. 2020

J Int Med Res

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Objective This study was performed to investigate the value of computed tomography (CT) in the differentiation of gastric glomus tumors (GGTs) and small gastric stromal tumors (GSTs). Methods Fifty-nine patients with pathologically confirmed GGTs (n = 11) and GSTs (n = 48) from 2006 to 2019 were retrospectively evaluated. All patients’ preoperative CT imaging features were analyzed. Results The following features were significantly different between GGTs and small GSTs: location in the antrum, endophytic growth, heterogeneous enhancement in the arterial phase, CT value in the arterial phase of ≥60.7 Hounsfield units (HU), CT value in the portal phase of ≥87.6 HU, degree of enhancement in the arterial phase of ≥29.9 HU, and degree of enhancement in the portal phase of ≥49.0 HU. A model including four randomly selected features among these seven criteria was built to differentiate GGTs from small GSTs with a sensitivity and specificity of 90.9% (10/11) and 100% (48/48), respectively. Conclusion We identified seven features that are useful for differentiating GGTs from small GSTs. A combination of four of these seven criteria may increase the diagnostic accuracy.

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