Sonographers' self‐reported visualization of normal postmenopausal ovaries on transvaginal ultrasound is not reliable: results of expert review of archived images from UKCTOCS

Abstract

ObjectiveIn 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.MethodsA 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.ResultsThe 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.ConclusionsOur 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.

Audit of transvaginal sonography of normal postmenopausal ovaries by sonographers from the United Kingdom Collaborative Trial of Ovarian Cancer Screening (UKCTOCS)

“…We have previously reported on the Quality Control (QC) of UKCTOCS TVS scanning with similar exam selection criteria (ovaries were seen and normal) 7 . A single expert reviewed 1000 randomly chosen TVS examinations which had been performed by 96 sonographers.…”

“…A metric commonly used in the quality control (QC) of TVS is self-reported visualisation rate (VR), defined as the number of examinations in which the ovaries were visualized as a proportion of all examinations performed by the sonographer 7 . In 2008, UKCTOCS implemented an accreditation programme which included the monitoring of individual sonographer VR over a 3 month period 8 .…”

Biomarkers and Strategies for Early Detection of Ovarian Cancer

“…While well-trained imagers can obtain concordant results, 78 re-review of 1,000 archived cases with apparently normal morphology from the early years of the UKCTOCS indicated unsatisfactory visualization of the ovaries and tubes in 50% of cases. 79 Imaging of the fallopian tubes, the site of origin of at least one third of high grade serous ovarian cancers, can be particularly difficult in the absence of conditions that cause thickening of the tube or accumulation of intra-luminal fluid. Even in the most expert centers, fallopian tubes could not be visualized in 23% of 549 healthy women.…”

Expression levels of MRP1, GST-π, and GSK3β in ovarian cancer and the relationship with drug resistance and prognosis of patients

“…Studies have shown that multidrug resistance-associated protein 1 (MRP1), glutathione S-transferase π (GST-π), and glycogen synthase kinase-3β (GSK3β) may be associated with chemotherapy resistance and prognosis of ovarian cancer (6–8). As a transmembrane protein-encoding gene, MRP1 is able to cause drug resistance mainly by reducing the intracellular concentration of drugs (9).…”