EP24.30: Pilot study of intra‐ and interoperator agreement of a proposed image quality scoring system for transvaginal ultrasound images

This study aimed to test the intra- and interoperator reliability of a proposed scoring system to quantify TVUS image quality, which could be used in the development of artificial intelligence(AI) tools for diagnosis of endometriosis. A proposed three-point scoring system was developed from review of existing literature and expert assessment. A core of 1-3 was assigned, where 1 = image quality is poor, 2 = image quality is suboptimal and 3= image quality is optimal. If the image was deemed to be inaccurate, it was assigned a score of 0 and rejected. Six raters (two sonologists, two sonographers and two radiologists) assigned 150 images (50 cases [50 uterus and 100 ovaries]) a score of 0-3. This was repeated after a period of at least one week. Interobserver reliability was calculated with an Intraclass correlation coefficient (ICC) and intraobserver reliability was calculated with a weighted kappa (k). Poor levels of interobserver agreement were obtained between all six raters for all 150 images (ICC = .480), and for uterus only (ICC = .359). Moderate levels of agreement were achieved for images of the ovaries (ICC = .531). Agreement between the paired sonologists and sonographers was poor for all images (ICC = .336 and .425) as well as uterus (ICC = .253 and .299) and ovaries (ICC= .400 and .469) only. Moderate levels of agreement were achieved between the paired radiologists overall (ICC = .600) and for the uterus (ICC = .538) and ovaries (ICC = .621). Intraobserver agreement was weak to moderate among each of the raters overall (range k = 0.533-0.718, ICC = 0.636-0.819) and for the ovaries (range k = 0.467-0.751, ICC = 0.596-0.862). Weak to strong agreement was seen for the uterus (range k = 0.568-0.808, ICC = 0.546-0.983). All measures were statistically significant (p < .001). The proposed scoring system produced poor-moderate interobserver reliability and mostly weak to moderate levels of intraobserver reliability. More refinement of the scoring system may be needed to improve reliability.

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Publication Details

Journal
Ultrasound in Obstetrics and Gynecology
Published
2024-09-01
DOI
https://doi.org/10.1002/uog.29036
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
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article

EP24.30: Pilot study of intra‐ and interoperator agreement of a proposed image quality scoring system for transvaginal ultrasound images

Steven Knox, Catrina Panuccio, G. Condous, Shae Maple et al.
Ultrasound in Obstetrics and Gynecology
Radiomics and Machine Learning in Medical Imaging
article

EP24.30: Pilot study of intra‐ and interoperator agreement of a proposed image quality scoring system for transvaginal ultrasound images

Steven Knox, Catrina Panuccio, G. Condous, Shae Maple, Alison Deslandes, Rebecca O’Hara, M. Leonardi, Hsiang‐Ting Chen, Jodie Avery, Glen Lo, M. Louise Hull
article en

Abstract

This study aimed to test the intra- and interoperator reliability of a proposed scoring system to quantify TVUS image quality, which could be used in the development of artificial intelligence(AI) tools for diagnosis of endometriosis. A proposed three-point scoring system was developed from review of existing literature and expert assessment. A core of 1-3 was assigned, where 1 = image quality is poor, 2 = image quality is suboptimal and 3= image quality is optimal. If the image was deemed to be inaccurate, it was assigned a score of 0 and rejected. Six raters (two sonologists, two sonographers and two radiologists) assigned 150 images (50 cases [50 uterus and 100 ovaries]) a score of 0-3. This was repeated after a period of at least one week. Interobserver reliability was calculated with an Intraclass correlation coefficient (ICC) and intraobserver reliability was calculated with a weighted kappa (k). Poor levels of interobserver agreement were obtained between all six raters for all 150 images (ICC = .480), and for uterus only (ICC = .359). Moderate levels of agreement were achieved for images of the ovaries (ICC = .531). Agreement between the paired sonologists and sonographers was poor for all images (ICC = .336 and .425) as well as uterus (ICC = .253 and .299) and ovaries (ICC= .400 and .469) only. Moderate levels of agreement were achieved between the paired radiologists overall (ICC = .600) and for the uterus (ICC = .538) and ovaries (ICC = .621). Intraobserver agreement was weak to moderate among each of the raters overall (range k = 0.533-0.718, ICC = 0.636-0.819) and for the ovaries (range k = 0.467-0.751, ICC = 0.596-0.862). Weak to strong agreement was seen for the uterus (range k = 0.568-0.808, ICC = 0.546-0.983). All measures were statistically significant (p < .001). The proposed scoring system produced poor-moderate interobserver reliability and mostly weak to moderate levels of intraobserver reliability. More refinement of the scoring system may be needed to improve reliability.

Ultrasound in Obstetrics and GynecologyVol. 64(S1)
South Australia Pathology (AU), The University of Sydney (AU), University of South Australia (AU), Curtin University (AU), Nepean Hospital (AU), Sir Charles Gairdner Hospital (AU), The University of Adelaide (AU), McMaster University (CA)
Openalex Percentile: Top 75%
Radiomics and Machine Learning in Medical Imaging
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