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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 Artifici...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9349326/ https://www.ncbi.nlm.nih.gov/pubmed/35920947 http://dx.doi.org/10.1186/s13089-022-00283-5 |
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author | Compagnone, Christian Borrini, Giulia Calabrese, Alberto Taddei, Mario Bellini, Valentina Bignami, Elena |
author_facet | Compagnone, Christian Borrini, Giulia Calabrese, Alberto Taddei, Mario Bellini, Valentina Bignami, Elena |
author_sort | Compagnone, Christian |
collection | PubMed |
description | 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/m(2), 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. |
format | Online Article Text |
id | pubmed-9349326 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-93493262022-08-05 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 Ultrasound J 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/m(2), 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. Springer International Publishing 2022-08-03 /pmc/articles/PMC9349326/ /pubmed/35920947 http://dx.doi.org/10.1186/s13089-022-00283-5 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Case Report Compagnone, Christian Borrini, Giulia Calabrese, Alberto Taddei, Mario Bellini, Valentina Bignami, Elena Artificial intelligence enhanced ultrasound (AI-US) in a severe obese parturient: a case report |
title | Artificial intelligence enhanced ultrasound (AI-US) in a severe obese parturient: a case report |
title_full | Artificial intelligence enhanced ultrasound (AI-US) in a severe obese parturient: a case report |
title_fullStr | Artificial intelligence enhanced ultrasound (AI-US) in a severe obese parturient: a case report |
title_full_unstemmed | Artificial intelligence enhanced ultrasound (AI-US) in a severe obese parturient: a case report |
title_short | Artificial intelligence enhanced ultrasound (AI-US) in a severe obese parturient: a case report |
title_sort | artificial intelligence enhanced ultrasound (ai-us) in a severe obese parturient: a case report |
topic | Case Report |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9349326/ https://www.ncbi.nlm.nih.gov/pubmed/35920947 http://dx.doi.org/10.1186/s13089-022-00283-5 |
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