Clinical evaluation of AI-assisted muscle ultrasound for monitoring muscle wasting in ICU patients
Nhat PTH., Van Hao N., Yen LM., Anh NH., Khiem DP., Kerdegari H., Phuong LT., Hoang VT., Ngoc NT., Thu LNM., Trung TN., Pisani L., Canas L., Gomez A., Kerdegari H., King A., Modat M., Razavi R., Xochicale M., Thao DP., Kien DT., Thy DBX., Trinh DHK., Duc DH., Geskus R., Hai HB., Chanh HQ., Van Hien H., Trieu HT., Kestelyn E., Van Khoa LD., Khanh LTT., Tran LHB., An LP., Mcbride A., Vuong NL., Huy NQ., Quyen NTH., Giang NT., Trinh NTD., Le Thanh NT., Dung NTP., Thao NTP., Van NTT., Kieu PT., Khanh PNQ., Lam PK., Thwaites G., Thwaites L., Duc TM., Hung TM., Turner H., Van Nuil JI., Huyen VNT., Yacoub S., Tam CT., Thuy DB., Duong HTH., Nghia HDT., Chau LB., Toan LM., Thu LNM., Thao LTM., Tai LTH., Phu NH., Viet NQ., Dung NT., Nguyen NT., Phong NT., Anh NTK., Van Hao N., Van Thanh Duoc N., Oanh PKN., Van PTH., Qui PT., Tho PV., Thao TTP., Pisani L., Schultz M., Ali N., Clifton D., English M., Hagenah J., Lu P., McKnight J., Paton C., Zhu T., Denehy L., Rollinson T., Georgiou P., Perez BH., Hill-Cawthorne K., Holmes A., Karolcik S., Ming D., Moser N., Manzano JR., Karlen W., Razavi R., Yacoub S., Van Vinh Chau N., King AP., Thwaites L., Denehy L., Gomez A.
AbstractMuscle 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, respectively (p = 0.13). In total 59 ultrasound examinations were carried out (30 without AI and 29 with AI). When assisted by our AI tool, the operators showed less variability between measurements with higher intraclass correlation coefficients (ICCs 0.999 95% CI 0.998–0.999 vs. 0.982 95% CI 0.962–0.993) and lower Bland Altman limits of agreement (± 1.9% vs. ± 6.6%) compared to not using the AI tool. The time spent on scans reduced significantly from a median of 19.6 min (IQR 16.9–21.7) to 9.4 min (IQR 7.2–11.7) compared to when using the AI tool (p < 0.001). AI-assisted muscle ultrasound removes the need for manual tracing, increases reproducibility and saves time. This system may aid monitoring muscle size in ICU patients assisting rehabilitation programmes.