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.
Artificial intelligence enhanced ultrasound (AI-US) in a severe obese parturient: a case report / Compagnone, Christian; Borrini, Giulia; Calabrese, Alberto; Taddei, Mario; Bellini, Valentina; Bignami, Elena. - In: THE ULTRASOUND JOURNAL. - ISSN 2524-8987. - 14:1(2022), p. 34. [10.1186/s13089-022-00283-5]
Artificial intelligence enhanced ultrasound (AI-US) in a severe obese parturient: a case report
Compagnone, Christian;Borrini, Giulia;Calabrese, Alberto;Taddei, Mario;Bellini, Valentina;Bignami, Elena
2022-01-01
Abstract
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.