Artificial intelligence model for enhancing the accuracy of transvaginal ultrasound in detecting endometrial cancer and endometrial atypical hyperplasia

Ilaria Capasso; Giuseppe Cucinella; Darryl E Wright; Hiroaki Takahashi; Luigi Antonio De Vitis; Adriana V Gregory; Bohyun Kim; Evelyn Reynolds; Diletta Fumagalli; Tommaso Occhiali; Angela J Fought; Michaela E McGree; Annie T Packard; Pamela I Causa Andrieu; Francesco Fanfani; Giovanni Scambia; Carrie L Langstraat; Abimbola Famuyide; Daniel M Breitkopf; Andrea Mariani; Gretchen E Glaser; Timothy L Kline

doi:10.1136/ijgc-2024-005652

Article info

Original research

Artificial intelligence model for enhancing the accuracy of transvaginal ultrasound in detecting endometrial cancer and endometrial atypical hyperplasia

Authors

Ilaria Capasso Department of Women, Children and Public Health Sciences, Gynecologic Oncology Unit, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Roma, ItalyDepartment of Obstetrics and Gynecology, Division of Gynecologic Oncology, Mayo Clinic, Rochester, Minnesota, USA PubMed articles Google scholar articles
Giuseppe Cucinella Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, Mayo Clinic, Rochester, Minnesota, USADepartment of Precision Medicine in Medical, Surgical and Critical Care (Me.Pre.C.C.), University of Palermo, Palermo, Italy PubMed articles Google scholar articles
Darryl E Wright Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA PubMed articles Google scholar articles
Hiroaki Takahashi Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA PubMed articles Google scholar articles
Luigi Antonio De Vitis Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, Mayo Clinic, Rochester, Minnesota, USADepartment of Gynecology, Istituto Europeo di Oncologia, Milano, Italy PubMed articles Google scholar articles
Adriana V Gregory Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA PubMed articles Google scholar articles
Bohyun Kim Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA PubMed articles Google scholar articles
Evelyn Reynolds Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, Mayo Clinic, Rochester, Minnesota, USA PubMed articles Google scholar articles
Diletta Fumagalli Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, Mayo Clinic, Rochester, Minnesota, USAGynecologic Surgery, IRCCS San Gerardo dei Tintori Foundation Hospital, Monza, Italy PubMed articles Google scholar articles
Tommaso Occhiali Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, Mayo Clinic, Rochester, Minnesota, USADepartment of Obstetrics and Gynecology, Santa Maria della Misericordia University Hospital, Udine, Italy PubMed articles Google scholar articles
Angela J Fought Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota, USA PubMed articles Google scholar articles
Michaela E McGree Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota, USA PubMed articles Google scholar articles
Annie T Packard Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA PubMed articles Google scholar articles
Pamela I Causa Andrieu Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA PubMed articles Google scholar articles
Francesco Fanfani Department of Women, Children and Public Health Sciences, Gynecologic Oncology Unit, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Roma, Italy PubMed articles Google scholar articles
Giovanni Scambia Department of Women, Children and Public Health Sciences, Gynecologic Oncology Unit, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Roma, Italy PubMed articles Google scholar articles
Carrie L Langstraat Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, Mayo Clinic, Rochester, Minnesota, USA PubMed articles Google scholar articles
Abimbola Famuyide Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, Mayo Clinic, Rochester, Minnesota, USA PubMed articles Google scholar articles
Daniel M Breitkopf Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, Mayo Clinic, Rochester, Minnesota, USA PubMed articles Google scholar articles
Andrea Mariani Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, Mayo Clinic, Rochester, Minnesota, USA PubMed articles Google scholar articles
Gretchen E Glaser Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, Mayo Clinic, Rochester, Minnesota, USA PubMed articles Google scholar articles
Timothy L Kline Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA PubMed articles Google scholar articles

Correspondence to Dr Timothy L Kline, Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA; kline.timothy{at}mayo.edu

View Full Text

Citation

Capasso I, Cucinella G, Wright DE, et al

Artificial intelligence model for enhancing the accuracy of transvaginal ultrasound in detecting endometrial cancer and endometrial atypical hyperplasia

International Journal of Gynecologic Cancer Published Online First: 31 July 2024. doi: 10.1136/ijgc-2024-005652

Publication history

Received April 24, 2024
Accepted July 19, 2024
First published July 31, 2024.

Request permissions

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

Main menu

Authors

Citation

Publication history

Request permissions

Copyright information

Log in using your username and password

Main menu

Log in using your username and password

You are here

Authors

Citation

Publication history

Request permissions

Copyright information

Read the full text or download the PDF:

Log in using your username and password