Purpose <p>Pelvic MRI is increasingly performed as a second-line investigation in suspected complex cases of endometriosis, to precisely localize lesions and to optimise surgical planning. To facilitate MRI evaluation and inter-disciplinary communication, several standardized structured image analysis and radiologic reporting classification systems have been proposed, including the mr#ENZIAN classification, whose applicability needs further proving.</p> Materials and methods <p>In an attempt to further validate the #ENZIAN classification applicability to MRI, we retrospectively evaluated the results of structured and unstructured MRI analysis by #ENZIAN compartment, considering both sole lesion-detection and #ENZIAN grading, using the corresponding op#ENZIAN score as a reference and evaluating inter-rater agreement of structured mr#ENZIAN results. In total, 83 patients with surgically/histopathologically confirmed endometriosis who received a pelvic MRI within 8 months prior to surgery between 2018 and 2022 were included.</p> Results <p>Concordance of mr#ENZIAN and op#ENZIAN results proved to be highly dependent on #ENZIAN-compartment: almost perfect agreement in locations FU, FI and others (FO); substantial agreement for lesion detection and grading in O, C and P; moderate to substantial agreement in T; moderate agreement in FB; moderate to fair agreement in A and only fair to poor agreement in B and FA. Inter-rater agreement between expert radiologists proved to be almost perfect to substantial for lesion detection and grading in most compartments, with exception of A, B and FA. There were no significant differences between results of structured and unstructured MRI evaluation.</p> Conclusion <p>We recommend a simplification of the mr#ENZIAN classification regarding DE, with clearer rules to differentiate and measure lesions affecting the A and B compartments.</p>

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Retrospective evaluation of the mr#ENZIAN classification’s applicability in the pre-operative assessment of complex endometriosis: a compartment-dependent challenge

  • Dagmar Morell-Hofert,
  • Christian Kremser,
  • Ena Josip-Caleta,
  • Michaela Plaikner,
  • Peter Schullian,
  • Beata Seeber,
  • Benjamin Henninger

摘要

Purpose

Pelvic MRI is increasingly performed as a second-line investigation in suspected complex cases of endometriosis, to precisely localize lesions and to optimise surgical planning. To facilitate MRI evaluation and inter-disciplinary communication, several standardized structured image analysis and radiologic reporting classification systems have been proposed, including the mr#ENZIAN classification, whose applicability needs further proving.

Materials and methods

In an attempt to further validate the #ENZIAN classification applicability to MRI, we retrospectively evaluated the results of structured and unstructured MRI analysis by #ENZIAN compartment, considering both sole lesion-detection and #ENZIAN grading, using the corresponding op#ENZIAN score as a reference and evaluating inter-rater agreement of structured mr#ENZIAN results. In total, 83 patients with surgically/histopathologically confirmed endometriosis who received a pelvic MRI within 8 months prior to surgery between 2018 and 2022 were included.

Results

Concordance of mr#ENZIAN and op#ENZIAN results proved to be highly dependent on #ENZIAN-compartment: almost perfect agreement in locations FU, FI and others (FO); substantial agreement for lesion detection and grading in O, C and P; moderate to substantial agreement in T; moderate agreement in FB; moderate to fair agreement in A and only fair to poor agreement in B and FA. Inter-rater agreement between expert radiologists proved to be almost perfect to substantial for lesion detection and grading in most compartments, with exception of A, B and FA. There were no significant differences between results of structured and unstructured MRI evaluation.

Conclusion

We recommend a simplification of the mr#ENZIAN classification regarding DE, with clearer rules to differentiate and measure lesions affecting the A and B compartments.