{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Nhat PTH"],"funding":["Wellcome Trust"],"pagination":["14798"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11208490"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["14(1)"],"pubmed_abstract":["Muscle ultrasound has been shown to be a valid and safe imaging modality to assess muscle wasting in critically ill patients in the intensive care unit (ICU). This typically involves manual delineation to measure the rectus femoris cross-sectional area (RFCSA), which is a subjective, time-consuming, and laborious task that requires significant expertise. We aimed to develop and evaluate an AI tool that performs automated recognition and measurement of RFCSA to support non-expert operators in measurement of the RFCSA using muscle ultrasound. Twenty patients were recruited between Feb 2023 and July 2023 and were randomized sequentially to operators using AI (n = 10) or non-AI (n = 10). Muscle loss during ICU stay was similar for both methods: 26 ± 15% for AI and 23 ± 11% for the non-AI, resp"],"journal":["Scientific reports"],"pubmed_title":["Clinical evaluation of AI-assisted muscle ultrasound for monitoring muscle wasting in ICU patients."],"pmcid":["PMC11208490"],"funding_grant_id":["217650/Z/19/Z"],"pubmed_authors":["Chanh HQ","Karlen W","Denehy L","Gomez A","Anh NH","Van Hien H","Phong NT","Duc TM","Moser N","Thao DP","Dung NTP","Phu NH","McKnight J","Duc DH","Perez BH","Ming D","Van Hao N","Chau LB","Yen LM","Hoang VT","Van Nuil JI","Trung TN","Van NTT","Paton C","Thu LNM","Hill-Cawthorne K","Thwaites G","Turner H","Pisani L","Georgiou P","Phuong LT","English M","Hagenah J","Van Vinh Chau N","Van Khoa LD","Nguyen NT","Duong HTH","Ngoc NT","Thwaites L","Thao TTP","Khanh PNQ","Dung NT","Thao LTM","Zhu T","Xochicale M","Manzano JR","Trinh NTD","Geskus R","Van Thanh Duoc N","Qui PT","Oanh PKN","Trinh DHK","Trieu HT","Canas L","Vuong NL","Anh NTK","Holmes A","Khiem DP","Hung TM","Quyen NTH","Lam PK","VITAL Consortium","Rollinson T","Viet NQ","Tho PV","Khanh LTT","Nhat PTH","Nghia HDT","Kestelyn E","Lu P","Razavi R","Karolcik S","Kien DT","Thuy DB","Hai HB","Mcbride A","Yacoub S","Kieu PT","Schultz M","Modat M","Van PTH","Thy DBX","Huyen VNT","King AP","Toan LM","Ali N","Clifton D","Giang NT","King A","Thao NTP","An LP","Tam CT","Huy NQ","Tai LTH","Tran LHB","Le Thanh NT","Kerdegari H"],"additional_accession":[]},"is_claimable":false,"name":"Clinical evaluation of AI-assisted muscle ultrasound for monitoring muscle wasting in ICU patients.","description":"Muscle ultrasound has been shown to be a valid and safe imaging modality to assess muscle wasting in critically ill patients in the intensive care unit (ICU). This typically involves manual delineation to measure the rectus femoris cross-sectional area (RFCSA), which is a subjective, time-consuming, and laborious task that requires significant expertise. We aimed to develop and evaluate an AI tool that performs automated recognition and measurement of RFCSA to support non-expert operators in measurement of the RFCSA using muscle ultrasound. Twenty patients were recruited between Feb 2023 and July 2023 and were randomized sequentially to operators using AI (n = 10) or non-AI (n = 10). Muscle loss during ICU stay was similar for both methods: 26 ± 15% for AI and 23 ± 11% for the non-AI, resp","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Jun","modification":"2026-06-02T21:17:34.122Z","creation":"2025-04-04T21:21:53.361Z"},"accession":"S-EPMC11208490","cross_references":{"pubmed":["38926427"],"doi":["10.1038/s41598-024-64564-w"]}}