Improving Ultrasound Detection of Uterine Adenomyosis Through Computational Texture Analysis

Joseph Konrad, Derek Merck, Jie Ying Wu, Adam Tuomi, Michael Beland, Michael D. Beland
Ultrasound quarterly · 2017 · vol. 34(1) , pp. 29–31 · doi:10.1097/ruq.0000000000000322 · PMID:29112637 · W2767224393
article OA: closed CC0 ⤵ 3 in-corpus citations
View on OpenAlex View on PubMed View at publisher
⚙ AI-generated summary by claude@2026-06, 2026-06-07 ⓘ

Computational texture analysis of ultrasound images achieved a 75% success rate in diagnosing uterine adenomyosis, significantly outperforming initial radiologist interpretations.

One-sentence paraphrase of the abstract; not a substitute for reading it. No clinical advice. How this works

Abstract

The purpose of our study was to determine if a textural analysis metric can be implemented to improve diagnosis of adenomyosis by ultrasound.We retrospectively identified 38 patients with a magnetic resonance imaging (MRI) diagnosis of uterine adenomyosis that also had a pelvic ultrasound within 6 months. We also identified 50 normal pelvic ultrasound examinations confirmed by a normal pelvic MRI within 6 months as a control group. A region of interest (ROI) was subsequently placed on the study population ultrasound image corresponding to the area of adenomyosis on MRI. An ROI was placed in the area of the junctional zone in the normal controls. The abnormal and normal ROIs were then compared against trained normal and abnormal distributions to determine the success rate, sensitivity, specificity, and negative and positive predictive values of our computer metric. The ultrasound reports performed before MRI were also reviewed to determine the radiologist correct/incorrect interpretation rate for comparison with our textural analysis metric.Using a training population of 50 normal ultrasound examinations (confirmed with a normal MRI) and 38 abnormal ultrasound examinations (MRI confirmed adenomyosis), we had an overall 75% (66/88 accurately diagnosed) success rate with a sensitivity, specificity, and negative and positive predictive values of 70%, 79%, 73%, and 76%, respectively (P < .0001). The sensitivity and false-negative rate of the initial ultrasound interpretation were 26% (10/38) and 74% (28/38), respectively.

My notes (saved in your browser only)

Condition tags

adenomyosis

MeSH descriptors

Adenomyosis Ultrasonography Adenomyosis Adult False Negative Reactions Female Humans Magnetic Resonance Imaging Middle Aged Proof of Concept Study Retrospective Studies Sensitivity and Specificity

Citation neighborhood

Papers in the corpus that this work cites (lower rings, blue) and that cite this one (upper rings, green). Dot size scales with the paper's in-corpus citation count — bigger dot = more influential within the endo/adeno field. Click a dot to open that paper. [ expand to 2 hops ] — adds papers reached through this work's immediate citers/citees. Heavier; up to 60 extra dots.

References (12)

Cited by (3)

Source provenance

europepmc
last seen: 2026-06-04T01:30:01.192114+00:00
openalex
last seen: 2026-06-04T00:00:01.174412+00:00
pubmed
last seen: 2026-05-13T22:20:07.505861+00:00
unpaywall
last seen: 2026-06-02T02:00:03.124865+00:00
License: CC0 · commercial use OK