Automatic vein measurement by ultrasonography to prevent peripheral intravenous catheter failure for clinical practice using artificial intelligence: development and evaluation study of an automatic detection method based on deep learning.

ABSTRACT:

Objectives

Complications due to peripheral intravenous catheters (PIVC) can be assessed using ultrasound imaging; however, it is not routinely conducted due to the need for training in image reading techniques. This study aimed to develop and validate a system that automatically measures blood vessel diameters on ultrasound images using artificial intelligence (AI) and provide recommendations for selecting an implantation site.

Design

Pilot study.

Setting

The University of Tokyo Hospital, Japan.

Primary and secondary outcome measures

First, based on previous studies, the vessel diameter was calculated as the mean value of the maximum long diameter plus the maximum short diameter orthogonal to it. Second, the size of the PIVC to be recommended was evaluated base

SUBMITTER: Takahashi T 

PROVIDER: S-EPMC9174762 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature