人工智能增强超声(AI-US)在重度肥胖产妇中的应用1例。

IF 3.4 Q2 Medicine
Christian Compagnone, Giulia Borrini, Alberto Calabrese, Mario Taddei, Valentina Bellini, Elena Bignami
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引用次数: 4

摘要

背景:由于妊娠后的解剖和生理改变,肥胖孕妇的轴向麻醉具有挑战性;这导致脊柱超声在这一人群中越来越受欢迎,以简化地标识别和程序执行。人工智能与超声(AI-US)图像增强和分析的集成提高了临床医生在具有挑战性解剖构象的患者中定位椎体结构的能力。病例介绍:我们报告了一例极度肥胖的孕妇,其体重指数(BMI) = 64.5 kg/m2,其中人工智能支持的图像识别允许成功放置硬膜外导管。结论:AI-US实施的好处是多方面的:解剖结构的即时识别增加了首次尝试的成功率,与传统的触诊方法相比,使脊髓麻醉的执行过程更容易,减少了脊髓麻醉的置针时间,并预测了硬膜外麻醉的最佳针头方向和目标结构深度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Artificial intelligence enhanced ultrasound (AI-US) in a severe obese parturient: a case report.

Artificial intelligence enhanced ultrasound (AI-US) in a severe obese parturient: a case report.

Background: Neuraxial anesthesia in obese parturients can be challenging due to anatomical and physiological modifications secondary to pregnancy; this led to growing popularity of spine ultrasound in this population for easing landmark identification and procedure execution. Integration of Artificial Intelligence with ultrasound (AI-US) for image enhancement and analysis has increased clinicians' ability to localize vertebral structures in patients with challenging anatomical conformation.

Case presentation: We present the case of a parturient with extremely severe obesity, with a Body Mass Index (BMI) = 64.5 kg/m2, in which the AI-Enabled Image Recognition allowed a successful placing of an epidural catheter.

Conclusions: Benefits gained from AI-US implementation are multiple: immediate recognition of anatomical structures leads to increased first-attempt success rate, making easier the process of spinal anesthesia execution compared to traditional palpation methods, reducing needle placement time for spinal anesthesia and predicting best needle direction and target structure depth in peridural anesthesia.

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来源期刊
Ultrasound Journal
Ultrasound Journal Health Professions-Radiological and Ultrasound Technology
CiteScore
6.80
自引率
2.90%
发文量
45
审稿时长
22 weeks
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