Early Learning Curve in the Assessment of Deep Pelvic Endometriosis for Ultrasound and Magnetic Resonance Imaging
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An ultrasound trainee showed positive learning curves for more pelvic endometriosis locations than a radiology trainee, with both improving over 35 cases.
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Abstract
Purpose . We aimed to compare the learning curves of an ultrasound trainee (obstetrics and gynecology resident) and a radiology trainee when assessing pelvic endometriosis. Methods . Consecutive patients with suspected endometriosis were prospectively enrolled in a tertiary center. They underwent an ultrasound and magnetic resonance imaging preoperatively, which was reported according to the International Deep Endometriosis Analysis (IDEA) group consensus. Trainees reported on deep endometriosis (DE), endometriomas, frozen pelvis, and adenomyosis. Using the Kappa agreement, their findings were compared against laparoscopy/histology and expert findings. The learning curve was considered positive when performance improved over time and indeterminate in all other cases. Results . Reports from thirty‐five women were divided chronologically into 3 equal blocks to assess the learning curve. For ultrasound, trainee versus expert showed a positive learning curve in overall pelvic DE assessment. There was an excellent agreement for adenomyosis (Kappa = 1.00, p = 0.09), frozen pelvis (Kappa = 0.90, p = 0.01), bowel (Kappa = 1.00, p = 0.01), and bladder DE assessment (Kappa = 1.00, p = 0.01). Endometrioma and uterosacral ligament assessment showed an indeterminate curve. For radiology, trainee versus expert showed a positive curve when detecting adenomyosis (Kappa = 0.42, p = 0.09) and bladder DE (Kappa = 1.00, p = 0.01). The assessment of endometriomas, frozen pelvis, overall pelvic DE, bowel, and uterosacral ligament DE showed indeterminate curve. Agreement between trainees and laparoscopy/histology showed a positive curve for bladder (both) and frozen pelvis (ultrasound only). Conclusion . A positive learning curve can be seen in some areas of pelvic endometriosis mapping after as little as 35 cases, but a bigger caseload is required to demonstrate the curve in full. The ultrasound trainee had positive learning curves in more anatomical locations (bladder, adenomyosis, overall bowel DE, frozen pelvis) than the radiology trainee (bladder, adenomyosis), which could be down to individual factors, differences in training, or the imaging method itself.
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References (12)
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Cited by (14)
- Letter to the Editor Regarding Abbreviated MRI protocols for endometriosis: clinical value, limitations, and the role of sagittal T2-weighted imaging (sagT2W) 2025
- Diagnostic Tools for Endometriosis in Poland: A Comparative Assessment of Reliability and Out-of-Pocket Costs 2025
- ACR Appropriateness Criteria® Endometriosis 2024
- Society of Radiologists in Ultrasound Consensus on Routine Pelvic US for Endometriosis 2024
- Directive clinique no 449 : Directive canadienne sur le diagnostic et les impacts de l’endométriose 2024
- Guideline No. 449: Diagnosis and Impact of Endometriosis - A Canadian Guideline 2024
- Role of Ultrasonography in the Diagnosis of Endometriosis in Infertile Women: Ovarian Endometrioma, Deep Endometriosis, and Superficial Endometriosis 2024
- DSOG Guideline Bulletin: Diagnostic approach for patients with endometriosis 2024
- Multi-Scale Deep Learning Ensemble for Segmentation of Endometriotic Lesions 2023
- Application of Deep Learning Model in the Sonographic Diagnosis of Uterine Adenomyosis 2023
- What is the accuracy of transvaginal ultrasound for endometriosis mapping prior to surgery when performed by a sonographer within an outpatient women's imaging centre? 2022
- Accuracy of combined physical examination, transvaginal ultrasonography, and magnetic resonance imaging to diagnose deep endometriosis 2022
- Application of deep learning model in the sonographic diagnosis of uterine adenomyosis 2022
- Indirect and atypical imaging signals of endometriosis: A wide range of manifestations 2021
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