Application of a Diabetic Foot Smart APP in the measurement of diabetic foot ulcers

被引:3
作者
Zhao, Nan [1 ,2 ]
Yu, Ling [1 ]
Fu, Xiaoai [1 ]
Dai, Weiwei [1 ,3 ]
Han, Huiwu [1 ,4 ]
Bai, Jiaojiao [5 ]
Xu, Jingcan [1 ,4 ]
Hu, Jianzhong [6 ]
Zhou, Qiuhong [1 ]
机构
[1] Cent South Univ, Xiangya Hosp, Teaching & Res Sect Clin Nursing, Changsha 410008, Peoples R China
[2] Zhengzhou Shuqing Med Coll, Zhengzhou 450052, Henan, Peoples R China
[3] Cent South Univ, Xiangya Hosp, Dept Stoma Wound Care Ctr, Changsha 410008, Peoples R China
[4] Cent South Univ, Xiangya Hosp, Dept Nursing, Changsha 410008, Peoples R China
[5] Fudan Univ, Dept Nursing, Huadong Hosp, Shanghai 200040, Peoples R China
[6] Cent South Univ, Xiangya Hosp, Changsha 410008, Peoples R China
关键词
Diabetic foot ulcer; Wound measurement; Deep learning; Application; RETINOPATHY; VALIDATION; WOUNDS;
D O I
10.1016/j.ijotn.2024.101095
中图分类号
R47 [护理学];
学科分类号
1011 ;
摘要
Aims: In the early stage, we developed an intelligent measurement APP for diabetic foot ulcers, named Diabetic Foot Smart APP. This study aimed to validate the APP in the measurement of ulcer area for diabetic foot ulcer (DFU). Methods: We selected 150 DFU images to measure the ulcer areas using three assessment tools: the Smart APP software package, the ruler method, and the gold standard Image J software, and compared the measurement results and measurement time of the three tools. The intra-rater and inter-rater reliability were described by Pearson correlation coefficient, intra-group correlation coefficient, and coefficient of variation. Results: The Image J software showed a median ulcer area of 4.02 cm(2), with a mean measurement time of 66.37 +/- 7.95 s. The ruler method showed a median ulcer area of 5.14 cm(2), with a mean measurement time of 171.47 +/- 46.43 s. The APP software showed a median ulcer area of 3.70 cm(2), with a mean measurement time of 38.25 +/- 6.81 s. There were significant differences between the ruler method and the golden standard Image J software (Z = -4.123, p < 0.05), but no significant difference between the APP software and the Image J software (Z = 1.103, p > 0.05). The APP software also showed good inter-rater reliability and intra-rater reliability, with both reaching 0.99. Conclusion: The Diabetic Foot Smart APP is a fast and reliable measurement tool with high measurement accuracy that can be easily used in clinical practice for the measurement of ulcer areas of DFU.
引用
收藏
页数:6
相关论文
共 21 条
[1]   Artificial Intelligence Applications in Type 2 Diabetes Mellitus Care: Focus on Machine Learning Methods [J].
Abhari, Shahabeddin ;
Kalhori, Sharareh R. Niakan ;
Ebrahimi, Mehdi ;
Hasannejadasl, Hajar ;
Garavand, Ali .
HEALTHCARE INFORMATICS RESEARCH, 2019, 25 (04) :248-261
[2]   ImageJ: A Free, Easy, and Reliable Method to Measure Leg Ulcers Using Digital Pictures [J].
Aragon-Sanchez, Javier ;
Quintana-Marrero, Yurena ;
Aragon-Hernandez, Cristina ;
Jose Hernandez-Herero, Maria .
INTERNATIONAL JOURNAL OF LOWER EXTREMITY WOUNDS, 2017, 16 (04) :269-273
[3]   The global burden of diabetic foot disease [J].
Boulton, AJM ;
Vileikyte, L ;
Ragnarson-Tennvall, G ;
Apelqvist, J .
LANCET, 2005, 366 (9498) :1719-1724
[4]   Dermatologist-level classification of skin cancer with deep neural networks [J].
Esteva, Andre ;
Kuprel, Brett ;
Novoa, Roberto A. ;
Ko, Justin ;
Swetter, Susan M. ;
Blau, Helen M. ;
Thrun, Sebastian .
NATURE, 2017, 542 (7639) :115-+
[5]   Instruments of Choice for Assessment and Monitoring Diabetic Foot: A Systematic Review [J].
Fernandez-Torres, Raul ;
Ruiz-Munoz, Maria ;
Perez-Panero, Alberto J. ;
Garcia-Romero, Jeronimo ;
Gonzalez-Sanchez, Manuel .
JOURNAL OF CLINICAL MEDICINE, 2020, 9 (02)
[6]   Automated Identification of Diabetic Retinopathy Using Deep Learning [J].
Gargeya, Rishab ;
Leng, Theodore .
OPHTHALMOLOGY, 2017, 124 (07) :962-969
[7]   Segmentation and Measurement of Chronic Wounds for Bioprinting [J].
Gholami, Peyman ;
Ahmadi-pajouh, Mohammad Ali ;
Abolftahi, Nabiollah ;
Hamarneh, Ghassan ;
Kayvanrad, Mohammad .
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 2018, 22 (04) :1269-1277
[8]   Robust Methods for Real-Time Diabetic Foot Ulcer Detection and Localization on Mobile Devices [J].
Goyal, Manu ;
Reeves, Neil D. ;
Rajbhandari, Satyan ;
Yap, Moi Hoon .
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 2019, 23 (04) :1730-1741
[9]   Using image J to document healing in ulcers of the foot in diabetes [J].
Jeffcoate, William J. ;
Musgrove, Alison J. ;
Lincoln, Nadina B. .
INTERNATIONAL WOUND JOURNAL, 2017, 14 (06) :1137-1139
[10]   Validation of three-dimensional wound measurements using a novel 3D-WAM camera [J].
Jorgensen, Line Bisgaard ;
Skov-Jeppesen, Sune Moller ;
Halekoh, Ulrich ;
Rasmussen, Benjamin Schnack ;
Sorensen, Jens Ahm ;
Jemec, Gregor B. E. ;
Yderstraede, Knud Bonnet .
WOUND REPAIR AND REGENERATION, 2018, 26 (06) :456-462