Sonographers' self‐reported visualization of normal postmenopausal ovaries on transvaginal ultrasound is not reliable: results of expert review of archived images from UKCTOCS. (7th March 2018)

• Record Type: Journal Article
• Authors: Stott, W.; Campbell, S.; Franchini, A.; Blyuss, O.; Zaikin, A.; Ryan, A.; Jones, C.; Gentry‐Maharaj, A.; Fletcher, G.; Kalsi, J.; Skates, S.; Parmar, M.; Amso, N.; Jacobs, I.; Menon, U.
• Is Part Of: Ultrasound in obstetrics & gynecology. Volume 51:Number 3(2018)
• Page Start: 401
• Page End: 408
• Publication Date: 2018-03-07
• Subjects: automated image analysis -- expert review -- ovarian cancer screening -- quality control -- transvaginal sonography -- UKCTOCS -- ultrasound -- visualization rate; Ultrasonics in obstetrics -- Periodicals; Generative organs, Female -- Diseases -- Diagnosis -- Periodicals; Diagnosis, Ultrasonic -- Periodicals; Genital Diseases, Female -- ultrasonography -- Periodicals; Ultrasonography, Prenatal -- Periodicals; 618.047543
• DOI: 10.1002/uog.18836
• Languages: English
• ISSNs: 0960-7692

Abstract

ABSTRACT: Objective: In the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS), self‐reported visualization rate (VR) of the ovaries by the sonographer on annual transvaginal sonographic (TVS) examinations was a key quality control (QC) metric. The objective of this study was to assess self‐reported VR using expert review of a random sample of archived images of TVS examinations from UKCTOCS, and then to develop software for measuring VR automatically. Methods: A single expert reviewed images archived from 1000 TVS examinations selected randomly from 68 931 TVS scans performed in UKCTOCS between 2008 and 2011 with ovaries reported as 'seen and normal'. Software was developed to identify the exact images used by the sonographer to measure the ovaries. This was achieved by measuring caliper dimensions in the image and matching them to those recorded by the sonographer. A logistic regression classifier to determine visualization was trained and validated using ovarian dimensions and visualization data reported by the expert. Results: The expert reviewer confirmed visualization of both ovaries (VR‐Both) in 50.2% (502/1000) of the examinations. The software identified the measurement image in 534 exams, which were split 2:1:1 providing training, validation and test data. Classifier mean accuracy on validation data was 70.9% (95% CI, 70.0–71.8%). Analysis of test data (133 exams) provided a sensitivity of 90.5% (95% CI, 80.9–95.8%) and specificity of 47.5% (95% CI, 34.5–60.8%) in detecting expert confirmed visualization of both ovaries. Conclusions: Our results suggest that, in a significant proportion of TVS annual screens, the sonographers may have mistaken other structures for normal ovaries. It is uncertain whether or not this affected the sensitivity and stage at detection of ovarian cancer in the ultrasound arm of UKCTOCS, but we conclude that QC metrics based on self‐reported visualization of normal ovaries are unreliable. The classifier shows some potential for addressing this problem, though further research is needed. © 2017 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of the International Society of Ultrasound in Obstetrics and Gynecology.