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Congress: ECR24
Poster Number: C-13770
Type: EPOS Radiologist (scientific)
Authorblock: S. Bottazzi, L. Russo, K. Zormpas-Petridis, G. Avesani, M. Miccò, L. D'Erme, E. Oliva, B. Gui, E. Sala; Roma/IT
Disclosures:
Silvia Bottazzi: Nothing to disclose
Luca Russo: Nothing to disclose
Konstantinos Zormpas-Petridis: Nothing to disclose
Giacomo Avesani: Nothing to disclose
Maura Miccò: Nothing to disclose
Luca D'Erme: Nothing to disclose
Eleonora Oliva: Nothing to disclose
Benedetta Gui: Nothing to disclose
Evis Sala: Nothing to disclose
Keywords: Artificial Intelligence, Genital / Reproductive system female, Oncology, MR, Diagnostic procedure, Statistics, Cancer
References

 

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  2. Hosny A, Parmar C, Quackenbush J, Schwartz LH, Aerts H. Artificial intelligence in radiology. Nat Rev Cancer. Aug 2018;18(8):500-510. doi:10.1038/s41568-018-0016-5
  3. Recht MP, Dewey M, Dreyer K, et al. Integrating artificial intelligence into the clinical practice of radiology: challenges and recommendations. Eur Radiol. Jun 2020;30(6):3576-3584. doi:10.1007/s00330-020-06672-5
  4. Lambin P, Leijenaar RTH, Deist TM, et al. Radiomics: the bridge between medical imaging and personalized medicine. Nat Rev Clin Oncol. Dec 2017;14(12):749-762. doi:10.1038/nrclinonc.2017.141
  5. Sung H, Ferlay J, Siegel RL, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. May 2021;71(3):209-249. doi:10.3322/caac.21660
  6. Berek JS, Matias-Guiu X, Creutzberg C, et al. FIGO staging of endometrial cancer: 2023. Int J Gynaecol Obstet. Aug 2023;162(2):383-394. doi:10.1002/ijgo.14923
  7. Lefebvre TL, Ueno Y, Dohan A, et al. Development and Validation of Multiparametric MRI-based Radiomics Models for Preoperative Risk Stratification of Endometrial Cancer. Radiology. Nov 2022;305(2):375-386. doi:10.1148/radiol.212873
  8. Yan BC, Li Y, Ma FH, et al. Preoperative Assessment for High-Risk Endometrial Cancer by Developing an MRI- and Clinical-Based Radiomics Nomogram: A Multicenter Study. J Magn Reson Imaging. Dec 2020;52(6):1872-1882. doi:10.1002/jmri.27289
  9. Celli V, Guerreri M, Pernazza A, et al. MRI- and Histologic-Molecular-Based Radio-Genomics Nomogram for Preoperative Assessment of Risk Classes in Endometrial Cancer. Cancers (Basel). Nov 29 2022;14(23)doi:10.3390/cancers14235881
  10. Micco M, Gui B, Russo L, et al. Preoperative Tumor Texture Analysis on MRI for High-Risk Disease Prediction in Endometrial Cancer: A Hypothesis-Generating Study. J Pers Med. Nov 7 2022;12(11)doi:10.3390/jpm12111854
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