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Review
. 2023 Oct 29;12(21):6833.
doi: 10.3390/jcm12216833.

Evolving the Era of 5D Ultrasound? A Systematic Literature Review on the Applications for Artificial Intelligence Ultrasound Imaging in Obstetrics and Gynecology

Elena Jost  1 , Philipp Kosian  1 , Jorge Jimenez Cruz  1 , Shadi Albarqouni  2   3 , Ulrich Gembruch  1 , Brigitte Strizek  1 , Florian Recker  1
Affiliations
Review

Evolving the Era of 5D Ultrasound? A Systematic Literature Review on the Applications for Artificial Intelligence Ultrasound Imaging in Obstetrics and Gynecology

Elena Jost et al. J Clin Med. .

Abstract

Artificial intelligence (AI) has gained prominence in medical imaging, particularly in obstetrics and gynecology (OB/GYN), where ultrasound (US) is the preferred method. It is considered cost effective and easily accessible but is time consuming and hindered by the need for specialized training. To overcome these limitations, AI models have been proposed for automated plane acquisition, anatomical measurements, and pathology detection. This study aims to overview recent literature on AI applications in OB/GYN US imaging, highlighting their benefits and limitations. For the methodology, a systematic literature search was performed in the PubMed and Cochrane Library databases. Matching abstracts were screened based on the PICOS (Participants, Intervention or Exposure, Comparison, Outcome, Study type) scheme. Articles with full text copies were distributed to the sections of OB/GYN and their research topics. As a result, this review includes 189 articles published from 1994 to 2023. Among these, 148 focus on obstetrics and 41 on gynecology. AI-assisted US applications span fetal biometry, echocardiography, or neurosonography, as well as the identification of adnexal and breast masses, and assessment of the endometrium and pelvic floor. To conclude, the applications for AI-assisted US in OB/GYN are abundant, especially in the subspecialty of obstetrics. However, while most studies focus on common application fields such as fetal biometry, this review outlines emerging and still experimental fields to promote further research.

Keywords: application; artificial intelligence; deep learning; fetal echocardiography; gynecology; obstetrics; systematic review; ultrasound imaging.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
PRISMA flow diagram for the screening process of reports included in this review.
Figure 2
Figure 2
Overview of the distribution of research topics in the analyzed literature (a total of 148 articles) for AI applications in US imaging in the subspecialty of obstetrics. Figure adapted from Servier Medical Art.
Figure 3
Figure 3
Overview of the distribution of research topics in the analyzed literature (a total of 41 articles) for AI applications in US imaging in the subspecialty of gynecology. Figure adapted from Servier Medical Art.
See this image and copyright information in PMC

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Grants and funding

This work was supported by the Open Access Publication Fund of the University of Bonn.