Reasons why it is time to change imaging guidelines on endometriosis.

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Title: Reasons why it is time to change imaging guidelines on endometriosis.
Authors: Thomassin-Naggara, Isabelle1,2 (AUTHOR) Isabelle.thomassin@aphp.fr, Rousset, Pascal3 (AUTHOR), Touboul, Cyril2,4 (AUTHOR), Razakamanantsoa, Leo1,2 (AUTHOR), Manganaro, Lucia5 (AUTHOR)
Source: European Radiology. Sep2024, Vol. 34 Issue 9, p6175-6181. 7p.
Subjects: Transvaginal ultrasonography, Image recognition (Computer vision), Magnetic resonance imaging, Laparoscopic surgery, Endometriosis
Abstract: In light of the rising number of patients referred for magnetic resonance imaging (MRI) due to suspected endometriosis and the high expectations of these patients, there is a need for new imaging guidelines to optimally protocol and indicate MRI and transvaginal ultrasonography (TVUS) examinations. This is crucial for accurately addressing the inquiries of gynecologists, encompassing complete mapping and preoperative staging, and facilitating effective communication with patients. In this context, the development of a standardized lexicon, as well as dedicated imaging classifications, is recommended to aid in the comprehensive management of patients. Clinical relevance statement: The radiologist should use a standardized lexicon and provide a score along with details about the specific compartments affected by endometriosis disease. This helps in offering clearer guidance to the surgeon. Key Points: • An optimal staging is based on the combination of clinical examination, transvaginal US, and MRI. • MRI is able to detect location that is hidden at the beginning of a laparoscopic surgery and thus the need for dedicated MR classifications to correctly stage the disease. • Deep pelvic endometriosis index (dPEI) classification is externally validated and highly correlated with operating time, hospital stay, and postoperative complications. [ABSTRACT FROM AUTHOR]
Copyright of European Radiology is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Reasons why it is time to change imaging guidelines on endometriosis.
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  Data: <searchLink fieldCode="AR" term="%22Thomassin-Naggara%2C+Isabelle%22">Thomassin-Naggara, Isabelle</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> Isabelle.thomassin@aphp.fr</i><br /><searchLink fieldCode="AR" term="%22Rousset%2C+Pascal%22">Rousset, Pascal</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Touboul%2C+Cyril%22">Touboul, Cyril</searchLink><relatesTo>2,4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Razakamanantsoa%2C+Leo%22">Razakamanantsoa, Leo</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Manganaro%2C+Lucia%22">Manganaro, Lucia</searchLink><relatesTo>5</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22European+Radiology%22">European Radiology</searchLink>. Sep2024, Vol. 34 Issue 9, p6175-6181. 7p.
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  Data: <searchLink fieldCode="DE" term="%22Transvaginal+ultrasonography%22">Transvaginal ultrasonography</searchLink><br /><searchLink fieldCode="DE" term="%22Image+recognition+%28Computer+vision%29%22">Image recognition (Computer vision)</searchLink><br /><searchLink fieldCode="DE" term="%22Magnetic+resonance+imaging%22">Magnetic resonance imaging</searchLink><br /><searchLink fieldCode="DE" term="%22Laparoscopic+surgery%22">Laparoscopic surgery</searchLink><br /><searchLink fieldCode="DE" term="%22Endometriosis%22">Endometriosis</searchLink>
– Name: Abstract
  Label: Abstract
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  Data: In light of the rising number of patients referred for magnetic resonance imaging (MRI) due to suspected endometriosis and the high expectations of these patients, there is a need for new imaging guidelines to optimally protocol and indicate MRI and transvaginal ultrasonography (TVUS) examinations. This is crucial for accurately addressing the inquiries of gynecologists, encompassing complete mapping and preoperative staging, and facilitating effective communication with patients. In this context, the development of a standardized lexicon, as well as dedicated imaging classifications, is recommended to aid in the comprehensive management of patients. Clinical relevance statement: The radiologist should use a standardized lexicon and provide a score along with details about the specific compartments affected by endometriosis disease. This helps in offering clearer guidance to the surgeon. Key Points: • An optimal staging is based on the combination of clinical examination, transvaginal US, and MRI. • MRI is able to detect location that is hidden at the beginning of a laparoscopic surgery and thus the need for dedicated MR classifications to correctly stage the disease. • Deep pelvic endometriosis index (dPEI) classification is externally validated and highly correlated with operating time, hospital stay, and postoperative complications. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of European Radiology is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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        Value: 10.1007/s00330-024-10595-w
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      – Code: eng
        Text: English
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        Type: general
      – SubjectFull: Image recognition (Computer vision)
        Type: general
      – SubjectFull: Magnetic resonance imaging
        Type: general
      – SubjectFull: Laparoscopic surgery
        Type: general
      – SubjectFull: Endometriosis
        Type: general
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            NameFull: Rousset, Pascal
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            NameFull: Touboul, Cyril
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            NameFull: Razakamanantsoa, Leo
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            NameFull: Manganaro, Lucia
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            – D: 01
              M: 09
              Text: Sep2024
              Type: published
              Y: 2024
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