2023
DOI: 10.1038/s41598-023-41807-w
|View full text |Cite
|
Sign up to set email alerts
|

2D/3D ultrasound diagnosis of pediatric distal radius fractures by human readers vs artificial intelligence

Jessica Knight,
Yuyue Zhou,
Christopher Keen
et al.

Abstract: Wrist trauma is common in children and generally requires radiography for exclusion of fractures, subjecting children to radiation and long wait times in the emergency department. Ultrasound (US) has potential to be a safer, faster diagnostic tool. This study aimed to determine how reliably US could detect distal radius fractures in children, to contrast the accuracy of 2DUS to 3DUS, and to assess the utility of artificial intelligence for image interpretation. 127 children were scanned with 2DUS and 3DUS on t… Show more

Help me understand this report
View preprint versions

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
2

Citation Types

0
4
0

Year Published

2023
2023
2024
2024

Publication Types

Select...
3
2
1

Relationship

1
5

Authors

Journals

citations
Cited by 7 publications
(4 citation statements)
references
References 28 publications
0
4
0
Order By: Relevance
“…It may also be useful to target a narrower age group for investigation in future studies as the anatomy of the elbow varies greatly between the ages of 0 and 17 and could have led to some difficulty for readers in determining expected normal anatomy, especially when blinded to all clinical data [18]. Similar to other MSK ultrasound applications, we expect that the elbow ultrasound data that we have collected will be highly amenable to real-time analysis and interpretation with AI [6]. In future research, we plan to investigate whether AI can decrease variability between readers and increase the accuracy and reproducibility of supracondylar fracture diagnosis using 2D POCUS.…”
Section: Discussionmentioning
confidence: 98%
See 3 more Smart Citations
“…It may also be useful to target a narrower age group for investigation in future studies as the anatomy of the elbow varies greatly between the ages of 0 and 17 and could have led to some difficulty for readers in determining expected normal anatomy, especially when blinded to all clinical data [18]. Similar to other MSK ultrasound applications, we expect that the elbow ultrasound data that we have collected will be highly amenable to real-time analysis and interpretation with AI [6]. In future research, we plan to investigate whether AI can decrease variability between readers and increase the accuracy and reproducibility of supracondylar fracture diagnosis using 2D POCUS.…”
Section: Discussionmentioning
confidence: 98%
“…Kappa values showed moderate agreement between readers, with the sensitivity of fracture detection by 2D POCUS and 3DUS ranging from 0.64 to 0.91 and 0.46 to 0.73, respectively. Given the operator-dependent nature of a US, this variability is likely to increase even further with limited user experience, as it does in similar MSK applications of POCUS [6].…”
Section: Discussionmentioning
confidence: 99%
See 2 more Smart Citations