Slawomir Wozniak, Radoslaw Kempinski, Katarzyna Akutko, Tomasz Pytrus, Urszula Zaleska-Dorobisz
{"title":"EUS在儿童嗜酸性食管炎中的应用——一种测量食管总壁厚面积的新方法。人工智能应用可行性研究。一项初步研究。","authors":"Slawomir Wozniak, Radoslaw Kempinski, Katarzyna Akutko, Tomasz Pytrus, Urszula Zaleska-Dorobisz","doi":"10.15557/jou.2024.0020","DOIUrl":null,"url":null,"abstract":"<p><strong>Aim: </strong>In the study, we aimed to introduce a formula for measuring the oesophageal total wall thickness area, which could be used for developing an artificial intelligence-based algorithm for the detection of patients whose total wall thickness area exceeds the norms.</p><p><strong>Material and methods: </strong>Mathematical formulas for measuring the square area of the oesophageal total wall thickness area were introduced and applied. Children were grouped according to their weight in clusters. For each cluster, the range (minimal and maximal value) were established. The measurements were done by using the formula for the area of the circular ring according to the formula A = n (B2-b2); the product of n and subtraction square b (smaller radius) and square B (bigger radius). The basic data for our calculations were derived from papers published by Dalby <i>et al</i>., 2010 and Loff <i>et al</i>., 2022.</p><p><strong>Results: </strong>The square area (in mm<sup>2</sup>) of the oesophageal wall was calculated and proposed to be introduced for further analysis. This value set could be used for creating an algorithm for computer-aided analysis of patients diagnosed with sonographic examination and isolating patients for surveillance. Our newly introduced approach could be implemented in sonographic, computer tomography, and magnetic resonance examinations in eosinophilic oesophagitis and other oesophageal diseases.</p><p><strong>Conclusions: </strong>Total wall thickness area could be used for monitoring children with eosinophilic oesophagitis and other oesophageal diseases. The method could also be applied for adults. Therefore, it can be a foundation for further progress with applying artificial intelligence algorithms.</p>","PeriodicalId":45612,"journal":{"name":"Journal of Ultrasonography","volume":"24 97","pages":"1-6"},"PeriodicalIF":1.3000,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11687637/pdf/","citationCount":"0","resultStr":"{\"title\":\"EUS in children with eosinophilic oesophagitis - a new method of measuring oesophageal total wall thickness area. An artificial intelligence application feasibility study. A pilot study.\",\"authors\":\"Slawomir Wozniak, Radoslaw Kempinski, Katarzyna Akutko, Tomasz Pytrus, Urszula Zaleska-Dorobisz\",\"doi\":\"10.15557/jou.2024.0020\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Aim: </strong>In the study, we aimed to introduce a formula for measuring the oesophageal total wall thickness area, which could be used for developing an artificial intelligence-based algorithm for the detection of patients whose total wall thickness area exceeds the norms.</p><p><strong>Material and methods: </strong>Mathematical formulas for measuring the square area of the oesophageal total wall thickness area were introduced and applied. Children were grouped according to their weight in clusters. For each cluster, the range (minimal and maximal value) were established. The measurements were done by using the formula for the area of the circular ring according to the formula A = n (B2-b2); the product of n and subtraction square b (smaller radius) and square B (bigger radius). The basic data for our calculations were derived from papers published by Dalby <i>et al</i>., 2010 and Loff <i>et al</i>., 2022.</p><p><strong>Results: </strong>The square area (in mm<sup>2</sup>) of the oesophageal wall was calculated and proposed to be introduced for further analysis. This value set could be used for creating an algorithm for computer-aided analysis of patients diagnosed with sonographic examination and isolating patients for surveillance. Our newly introduced approach could be implemented in sonographic, computer tomography, and magnetic resonance examinations in eosinophilic oesophagitis and other oesophageal diseases.</p><p><strong>Conclusions: </strong>Total wall thickness area could be used for monitoring children with eosinophilic oesophagitis and other oesophageal diseases. The method could also be applied for adults. 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引用次数: 0
摘要
目的:在本研究中,我们旨在引入一个测量食管总壁厚面积的公式,该公式可用于开发一种基于人工智能的算法,用于检测总壁厚面积超过规范的患者。材料与方法:介绍并应用了食道总壁厚平方面积的数学公式。孩子们按体重分组。对于每个聚类,建立范围(最小值和最大值)。根据公式A = n (B2-b2)计算圆环的面积;n与减法的平方b(半径较小)和平方b(半径较大)的乘积。我们计算的基本数据来自Dalby et al.(2010)和Loff et al.(2022)发表的论文。结果:计算出食管壁的平方面积(mm2),拟引入进一步分析。该值集可用于创建一种算法,用于对超声检查诊断的患者进行计算机辅助分析和隔离患者进行监测。我们的新方法可应用于嗜酸性食管炎及其他食道疾病的超声、计算机断层及磁共振检查。结论:总壁厚面积可用于监测儿童嗜酸性粒细胞性食管炎及其他食管疾病。这种方法也适用于成年人。因此,它可以成为应用人工智能算法进一步取得进展的基础。
EUS in children with eosinophilic oesophagitis - a new method of measuring oesophageal total wall thickness area. An artificial intelligence application feasibility study. A pilot study.
Aim: In the study, we aimed to introduce a formula for measuring the oesophageal total wall thickness area, which could be used for developing an artificial intelligence-based algorithm for the detection of patients whose total wall thickness area exceeds the norms.
Material and methods: Mathematical formulas for measuring the square area of the oesophageal total wall thickness area were introduced and applied. Children were grouped according to their weight in clusters. For each cluster, the range (minimal and maximal value) were established. The measurements were done by using the formula for the area of the circular ring according to the formula A = n (B2-b2); the product of n and subtraction square b (smaller radius) and square B (bigger radius). The basic data for our calculations were derived from papers published by Dalby et al., 2010 and Loff et al., 2022.
Results: The square area (in mm2) of the oesophageal wall was calculated and proposed to be introduced for further analysis. This value set could be used for creating an algorithm for computer-aided analysis of patients diagnosed with sonographic examination and isolating patients for surveillance. Our newly introduced approach could be implemented in sonographic, computer tomography, and magnetic resonance examinations in eosinophilic oesophagitis and other oesophageal diseases.
Conclusions: Total wall thickness area could be used for monitoring children with eosinophilic oesophagitis and other oesophageal diseases. The method could also be applied for adults. Therefore, it can be a foundation for further progress with applying artificial intelligence algorithms.