Skip to main content
Journal cover image

Diagnostic accuracy of clinically reported adenomyosis on pelvic ultrasound and MRI compared to surgical pathology.

Publication ,  Journal Article
Zanolli, NC; Cline, BC; Befera, NT; Martin, JG
Published in: Clin Imaging
February 2022

BACKGROUND: Adenomyosis is a common gynecologic pathology that relies on diagnostic imaging to guide treatment. Accuracy of both pelvic ultrasound and magnetic resonance imaging (MRI) when specifically evaluating for the presence of adenomyosis is high. However, the accuracy of reported rates in clinical practice is less well understood. PURPOSE: To demonstrate the accuracy in reporting of adenomyosis on pelvic ultrasound and MRI compared to histopathology in common clinical practice. BASIC PROCEDURES: An institutional database was searched for women with a pelvic ultrasound and a pelvic MRI with a subsequent hysterectomy. Findings were extracted from radiology and pathology reports, and the documented presence or absence of adenomyosis was recorded for each modality. Blinded radiologists viewed each imaging pair to directly evaluate for adenomyosis. MAIN FINDINGS: Compared to prior published data, imaging had lower accuracy in clinical practice when adenomyosis was not specifically evaluated for. For the finding of adenomyosis, pelvic ultrasound had a sensitivity of 10.9%, a specificity of 98.3%, positive predictive value (PPV) of 77.8%, negative predictive value (NPV) of 66.7%, an accuracy of 67.2%, and a diagnostic odds ratio (DOR) of 7. Pelvic MRI had a sensitivity of 29.7%, specificity of 85.3%, PPV of 52.8%, NPV of 68.8%, an accuracy of 65.6%, and DOR of 2.5. Overall accuracy of MRI improved when adenomyosis was directly evaluated for (82.4% vs 65.6%). PRINCIPLE CONCLUSIONS: Without direct communication to evaluate for adenomyosis, pelvic ultrasound and MRI may underestimate or misreport adenomyosis. Providers should be aware of these discrepancies when relying on radiology reports to guide treatment and potential interventions when diagnosing and managing adenomyosis.

Duke Scholars

Altmetric Attention Stats
Dimensions Citation Stats

Published In

Clin Imaging

DOI

EISSN

1873-4499

Publication Date

February 2022

Volume

82

Start / End Page

117 / 120

Location

United States

Related Subject Headings

  • Ultrasonography
  • Sensitivity and Specificity
  • Pathology, Surgical
  • Nuclear Medicine & Medical Imaging
  • Magnetic Resonance Imaging
  • Humans
  • Female
  • Endometriosis
  • Adenomyosis
  • 3202 Clinical sciences
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Zanolli, N. C., Cline, B. C., Befera, N. T., & Martin, J. G. (2022). Diagnostic accuracy of clinically reported adenomyosis on pelvic ultrasound and MRI compared to surgical pathology. Clin Imaging, 82, 117–120. https://doi.org/10.1016/j.clinimag.2021.11.012
Zanolli, Nicole C., Brendan C. Cline, Nicholas T. Befera, and Jonathan G. Martin. “Diagnostic accuracy of clinically reported adenomyosis on pelvic ultrasound and MRI compared to surgical pathology.Clin Imaging 82 (February 2022): 117–20. https://doi.org/10.1016/j.clinimag.2021.11.012.
Zanolli NC, Cline BC, Befera NT, Martin JG. Diagnostic accuracy of clinically reported adenomyosis on pelvic ultrasound and MRI compared to surgical pathology. Clin Imaging. 2022 Feb;82:117–20.
Zanolli, Nicole C., et al. “Diagnostic accuracy of clinically reported adenomyosis on pelvic ultrasound and MRI compared to surgical pathology.Clin Imaging, vol. 82, Feb. 2022, pp. 117–20. Pubmed, doi:10.1016/j.clinimag.2021.11.012.
Zanolli NC, Cline BC, Befera NT, Martin JG. Diagnostic accuracy of clinically reported adenomyosis on pelvic ultrasound and MRI compared to surgical pathology. Clin Imaging. 2022 Feb;82:117–120.
Journal cover image

Published In

Clin Imaging

DOI

EISSN

1873-4499

Publication Date

February 2022

Volume

82

Start / End Page

117 / 120

Location

United States

Related Subject Headings

  • Ultrasonography
  • Sensitivity and Specificity
  • Pathology, Surgical
  • Nuclear Medicine & Medical Imaging
  • Magnetic Resonance Imaging
  • Humans
  • Female
  • Endometriosis
  • Adenomyosis
  • 3202 Clinical sciences