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Radiology
11, 2022;305 (2): 375-386.

Development and Validation of Multiparametric MRI-based Radiomics Models for Preoperative Risk Stratification of Endometrial Cancer.

Thierry L Lefebvre, Yoshiko Ueno, Anthony Dohan, Avishek Chatterjee, Martin Vallières, Eric Winter-Reinhold, Sameh Saif, Ives R Levesque, Xing Ziggy Zeng, Reza Forghani, Jan Seuntjens, Philippe Soyer, Peter Savadjiev, Caroline Reinhold
Author Information
  1. Thierry L Lefebvre: From the Medical Physics Unit, Department of Oncology (T.L.L., A.C., M.V., I.R.L., J.S.), Department of Diagnostic Radiology (Y.U., S.S., R.F., P. Savadjiev, C.R.), and School of Computer Science (P. Savadjiev), McGill University, Montreal General Hospital Site, 1650 Cedar Ave, Montreal, QC, Canada H3G 1A4; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, England (T.L.L.); Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan (Y.U.); Department of Radiology, Cochin Hospital, AP-HP.Centre, Paris, France (A.D., P. Soyer); Université de Paris, Faculté de Médecine, Paris, France (A.D., P. Soyer); Department of Precision Medicine, GROW-School for Oncology and Developmental Biology, Maastricht University, Maastricht, the Netherlands (A.C.); Department of Computer Science, Université de Sherbrooke, Sherbrooke, Quebec, Canada (M.V.); Augmented Intelligence & Precision Health Laboratory (E.W.R., R.F., C.R.), Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada; Department of Obstetrics and Gynecology, McGill University Health Centre, Montreal, Quebec, Canada (X.Z.Z.); and Montreal Imaging Experts, Montreal, Quebec, Canada (R.F., C.R.). ORCID
  2. Yoshiko Ueno: From the Medical Physics Unit, Department of Oncology (T.L.L., A.C., M.V., I.R.L., J.S.), Department of Diagnostic Radiology (Y.U., S.S., R.F., P. Savadjiev, C.R.), and School of Computer Science (P. Savadjiev), McGill University, Montreal General Hospital Site, 1650 Cedar Ave, Montreal, QC, Canada H3G 1A4; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, England (T.L.L.); Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan (Y.U.); Department of Radiology, Cochin Hospital, AP-HP.Centre, Paris, France (A.D., P. Soyer); Université de Paris, Faculté de Médecine, Paris, France (A.D., P. Soyer); Department of Precision Medicine, GROW-School for Oncology and Developmental Biology, Maastricht University, Maastricht, the Netherlands (A.C.); Department of Computer Science, Université de Sherbrooke, Sherbrooke, Quebec, Canada (M.V.); Augmented Intelligence & Precision Health Laboratory (E.W.R., R.F., C.R.), Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada; Department of Obstetrics and Gynecology, McGill University Health Centre, Montreal, Quebec, Canada (X.Z.Z.); and Montreal Imaging Experts, Montreal, Quebec, Canada (R.F., C.R.). ORCID
  3. Anthony Dohan: From the Medical Physics Unit, Department of Oncology (T.L.L., A.C., M.V., I.R.L., J.S.), Department of Diagnostic Radiology (Y.U., S.S., R.F., P. Savadjiev, C.R.), and School of Computer Science (P. Savadjiev), McGill University, Montreal General Hospital Site, 1650 Cedar Ave, Montreal, QC, Canada H3G 1A4; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, England (T.L.L.); Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan (Y.U.); Department of Radiology, Cochin Hospital, AP-HP.Centre, Paris, France (A.D., P. Soyer); Université de Paris, Faculté de Médecine, Paris, France (A.D., P. Soyer); Department of Precision Medicine, GROW-School for Oncology and Developmental Biology, Maastricht University, Maastricht, the Netherlands (A.C.); Department of Computer Science, Université de Sherbrooke, Sherbrooke, Quebec, Canada (M.V.); Augmented Intelligence & Precision Health Laboratory (E.W.R., R.F., C.R.), Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada; Department of Obstetrics and Gynecology, McGill University Health Centre, Montreal, Quebec, Canada (X.Z.Z.); and Montreal Imaging Experts, Montreal, Quebec, Canada (R.F., C.R.). ORCID
  4. Avishek Chatterjee: From the Medical Physics Unit, Department of Oncology (T.L.L., A.C., M.V., I.R.L., J.S.), Department of Diagnostic Radiology (Y.U., S.S., R.F., P. Savadjiev, C.R.), and School of Computer Science (P. Savadjiev), McGill University, Montreal General Hospital Site, 1650 Cedar Ave, Montreal, QC, Canada H3G 1A4; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, England (T.L.L.); Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan (Y.U.); Department of Radiology, Cochin Hospital, AP-HP.Centre, Paris, France (A.D., P. Soyer); Université de Paris, Faculté de Médecine, Paris, France (A.D., P. Soyer); Department of Precision Medicine, GROW-School for Oncology and Developmental Biology, Maastricht University, Maastricht, the Netherlands (A.C.); Department of Computer Science, Université de Sherbrooke, Sherbrooke, Quebec, Canada (M.V.); Augmented Intelligence & Precision Health Laboratory (E.W.R., R.F., C.R.), Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada; Department of Obstetrics and Gynecology, McGill University Health Centre, Montreal, Quebec, Canada (X.Z.Z.); and Montreal Imaging Experts, Montreal, Quebec, Canada (R.F., C.R.). ORCID
  5. Martin Vallières: From the Medical Physics Unit, Department of Oncology (T.L.L., A.C., M.V., I.R.L., J.S.), Department of Diagnostic Radiology (Y.U., S.S., R.F., P. Savadjiev, C.R.), and School of Computer Science (P. Savadjiev), McGill University, Montreal General Hospital Site, 1650 Cedar Ave, Montreal, QC, Canada H3G 1A4; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, England (T.L.L.); Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan (Y.U.); Department of Radiology, Cochin Hospital, AP-HP.Centre, Paris, France (A.D., P. Soyer); Université de Paris, Faculté de Médecine, Paris, France (A.D., P. Soyer); Department of Precision Medicine, GROW-School for Oncology and Developmental Biology, Maastricht University, Maastricht, the Netherlands (A.C.); Department of Computer Science, Université de Sherbrooke, Sherbrooke, Quebec, Canada (M.V.); Augmented Intelligence & Precision Health Laboratory (E.W.R., R.F., C.R.), Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada; Department of Obstetrics and Gynecology, McGill University Health Centre, Montreal, Quebec, Canada (X.Z.Z.); and Montreal Imaging Experts, Montreal, Quebec, Canada (R.F., C.R.). ORCID
  6. Eric Winter-Reinhold: From the Medical Physics Unit, Department of Oncology (T.L.L., A.C., M.V., I.R.L., J.S.), Department of Diagnostic Radiology (Y.U., S.S., R.F., P. Savadjiev, C.R.), and School of Computer Science (P. Savadjiev), McGill University, Montreal General Hospital Site, 1650 Cedar Ave, Montreal, QC, Canada H3G 1A4; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, England (T.L.L.); Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan (Y.U.); Department of Radiology, Cochin Hospital, AP-HP.Centre, Paris, France (A.D., P. Soyer); Université de Paris, Faculté de Médecine, Paris, France (A.D., P. Soyer); Department of Precision Medicine, GROW-School for Oncology and Developmental Biology, Maastricht University, Maastricht, the Netherlands (A.C.); Department of Computer Science, Université de Sherbrooke, Sherbrooke, Quebec, Canada (M.V.); Augmented Intelligence & Precision Health Laboratory (E.W.R., R.F., C.R.), Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada; Department of Obstetrics and Gynecology, McGill University Health Centre, Montreal, Quebec, Canada (X.Z.Z.); and Montreal Imaging Experts, Montreal, Quebec, Canada (R.F., C.R.).
  7. Sameh Saif: From the Medical Physics Unit, Department of Oncology (T.L.L., A.C., M.V., I.R.L., J.S.), Department of Diagnostic Radiology (Y.U., S.S., R.F., P. Savadjiev, C.R.), and School of Computer Science (P. Savadjiev), McGill University, Montreal General Hospital Site, 1650 Cedar Ave, Montreal, QC, Canada H3G 1A4; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, England (T.L.L.); Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan (Y.U.); Department of Radiology, Cochin Hospital, AP-HP.Centre, Paris, France (A.D., P. Soyer); Université de Paris, Faculté de Médecine, Paris, France (A.D., P. Soyer); Department of Precision Medicine, GROW-School for Oncology and Developmental Biology, Maastricht University, Maastricht, the Netherlands (A.C.); Department of Computer Science, Université de Sherbrooke, Sherbrooke, Quebec, Canada (M.V.); Augmented Intelligence & Precision Health Laboratory (E.W.R., R.F., C.R.), Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada; Department of Obstetrics and Gynecology, McGill University Health Centre, Montreal, Quebec, Canada (X.Z.Z.); and Montreal Imaging Experts, Montreal, Quebec, Canada (R.F., C.R.). ORCID
  8. Ives R Levesque: From the Medical Physics Unit, Department of Oncology (T.L.L., A.C., M.V., I.R.L., J.S.), Department of Diagnostic Radiology (Y.U., S.S., R.F., P. Savadjiev, C.R.), and School of Computer Science (P. Savadjiev), McGill University, Montreal General Hospital Site, 1650 Cedar Ave, Montreal, QC, Canada H3G 1A4; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, England (T.L.L.); Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan (Y.U.); Department of Radiology, Cochin Hospital, AP-HP.Centre, Paris, France (A.D., P. Soyer); Université de Paris, Faculté de Médecine, Paris, France (A.D., P. Soyer); Department of Precision Medicine, GROW-School for Oncology and Developmental Biology, Maastricht University, Maastricht, the Netherlands (A.C.); Department of Computer Science, Université de Sherbrooke, Sherbrooke, Quebec, Canada (M.V.); Augmented Intelligence & Precision Health Laboratory (E.W.R., R.F., C.R.), Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada; Department of Obstetrics and Gynecology, McGill University Health Centre, Montreal, Quebec, Canada (X.Z.Z.); and Montreal Imaging Experts, Montreal, Quebec, Canada (R.F., C.R.). ORCID
  9. Xing Ziggy Zeng: From the Medical Physics Unit, Department of Oncology (T.L.L., A.C., M.V., I.R.L., J.S.), Department of Diagnostic Radiology (Y.U., S.S., R.F., P. Savadjiev, C.R.), and School of Computer Science (P. Savadjiev), McGill University, Montreal General Hospital Site, 1650 Cedar Ave, Montreal, QC, Canada H3G 1A4; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, England (T.L.L.); Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan (Y.U.); Department of Radiology, Cochin Hospital, AP-HP.Centre, Paris, France (A.D., P. Soyer); Université de Paris, Faculté de Médecine, Paris, France (A.D., P. Soyer); Department of Precision Medicine, GROW-School for Oncology and Developmental Biology, Maastricht University, Maastricht, the Netherlands (A.C.); Department of Computer Science, Université de Sherbrooke, Sherbrooke, Quebec, Canada (M.V.); Augmented Intelligence & Precision Health Laboratory (E.W.R., R.F., C.R.), Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada; Department of Obstetrics and Gynecology, McGill University Health Centre, Montreal, Quebec, Canada (X.Z.Z.); and Montreal Imaging Experts, Montreal, Quebec, Canada (R.F., C.R.).
  10. Reza Forghani: From the Medical Physics Unit, Department of Oncology (T.L.L., A.C., M.V., I.R.L., J.S.), Department of Diagnostic Radiology (Y.U., S.S., R.F., P. Savadjiev, C.R.), and School of Computer Science (P. Savadjiev), McGill University, Montreal General Hospital Site, 1650 Cedar Ave, Montreal, QC, Canada H3G 1A4; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, England (T.L.L.); Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan (Y.U.); Department of Radiology, Cochin Hospital, AP-HP.Centre, Paris, France (A.D., P. Soyer); Université de Paris, Faculté de Médecine, Paris, France (A.D., P. Soyer); Department of Precision Medicine, GROW-School for Oncology and Developmental Biology, Maastricht University, Maastricht, the Netherlands (A.C.); Department of Computer Science, Université de Sherbrooke, Sherbrooke, Quebec, Canada (M.V.); Augmented Intelligence & Precision Health Laboratory (E.W.R., R.F., C.R.), Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada; Department of Obstetrics and Gynecology, McGill University Health Centre, Montreal, Quebec, Canada (X.Z.Z.); and Montreal Imaging Experts, Montreal, Quebec, Canada (R.F., C.R.). ORCID
  11. Jan Seuntjens: From the Medical Physics Unit, Department of Oncology (T.L.L., A.C., M.V., I.R.L., J.S.), Department of Diagnostic Radiology (Y.U., S.S., R.F., P. Savadjiev, C.R.), and School of Computer Science (P. Savadjiev), McGill University, Montreal General Hospital Site, 1650 Cedar Ave, Montreal, QC, Canada H3G 1A4; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, England (T.L.L.); Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan (Y.U.); Department of Radiology, Cochin Hospital, AP-HP.Centre, Paris, France (A.D., P. Soyer); Université de Paris, Faculté de Médecine, Paris, France (A.D., P. Soyer); Department of Precision Medicine, GROW-School for Oncology and Developmental Biology, Maastricht University, Maastricht, the Netherlands (A.C.); Department of Computer Science, Université de Sherbrooke, Sherbrooke, Quebec, Canada (M.V.); Augmented Intelligence & Precision Health Laboratory (E.W.R., R.F., C.R.), Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada; Department of Obstetrics and Gynecology, McGill University Health Centre, Montreal, Quebec, Canada (X.Z.Z.); and Montreal Imaging Experts, Montreal, Quebec, Canada (R.F., C.R.). ORCID
  12. Philippe Soyer: From the Medical Physics Unit, Department of Oncology (T.L.L., A.C., M.V., I.R.L., J.S.), Department of Diagnostic Radiology (Y.U., S.S., R.F., P. Savadjiev, C.R.), and School of Computer Science (P. Savadjiev), McGill University, Montreal General Hospital Site, 1650 Cedar Ave, Montreal, QC, Canada H3G 1A4; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, England (T.L.L.); Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan (Y.U.); Department of Radiology, Cochin Hospital, AP-HP.Centre, Paris, France (A.D., P. Soyer); Université de Paris, Faculté de Médecine, Paris, France (A.D., P. Soyer); Department of Precision Medicine, GROW-School for Oncology and Developmental Biology, Maastricht University, Maastricht, the Netherlands (A.C.); Department of Computer Science, Université de Sherbrooke, Sherbrooke, Quebec, Canada (M.V.); Augmented Intelligence & Precision Health Laboratory (E.W.R., R.F., C.R.), Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada; Department of Obstetrics and Gynecology, McGill University Health Centre, Montreal, Quebec, Canada (X.Z.Z.); and Montreal Imaging Experts, Montreal, Quebec, Canada (R.F., C.R.). ORCID
  13. Peter Savadjiev: From the Medical Physics Unit, Department of Oncology (T.L.L., A.C., M.V., I.R.L., J.S.), Department of Diagnostic Radiology (Y.U., S.S., R.F., P. Savadjiev, C.R.), and School of Computer Science (P. Savadjiev), McGill University, Montreal General Hospital Site, 1650 Cedar Ave, Montreal, QC, Canada H3G 1A4; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, England (T.L.L.); Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan (Y.U.); Department of Radiology, Cochin Hospital, AP-HP.Centre, Paris, France (A.D., P. Soyer); Université de Paris, Faculté de Médecine, Paris, France (A.D., P. Soyer); Department of Precision Medicine, GROW-School for Oncology and Developmental Biology, Maastricht University, Maastricht, the Netherlands (A.C.); Department of Computer Science, Université de Sherbrooke, Sherbrooke, Quebec, Canada (M.V.); Augmented Intelligence & Precision Health Laboratory (E.W.R., R.F., C.R.), Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada; Department of Obstetrics and Gynecology, McGill University Health Centre, Montreal, Quebec, Canada (X.Z.Z.); and Montreal Imaging Experts, Montreal, Quebec, Canada (R.F., C.R.). ORCID
  14. Caroline Reinhold: From the Medical Physics Unit, Department of Oncology (T.L.L., A.C., M.V., I.R.L., J.S.), Department of Diagnostic Radiology (Y.U., S.S., R.F., P. Savadjiev, C.R.), and School of Computer Science (P. Savadjiev), McGill University, Montreal General Hospital Site, 1650 Cedar Ave, Montreal, QC, Canada H3G 1A4; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, England (T.L.L.); Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan (Y.U.); Department of Radiology, Cochin Hospital, AP-HP.Centre, Paris, France (A.D., P. Soyer); Université de Paris, Faculté de Médecine, Paris, France (A.D., P. Soyer); Department of Precision Medicine, GROW-School for Oncology and Developmental Biology, Maastricht University, Maastricht, the Netherlands (A.C.); Department of Computer Science, Université de Sherbrooke, Sherbrooke, Quebec, Canada (M.V.); Augmented Intelligence & Precision Health Laboratory (E.W.R., R.F., C.R.), Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada; Department of Obstetrics and Gynecology, McGill University Health Centre, Montreal, Quebec, Canada (X.Z.Z.); and Montreal Imaging Experts, Montreal, Quebec, Canada (R.F., C.R.). ORCID
PMID: 35819326 DOI: 10.1148/radiol.212873

Abstract

Background Stratifying high-risk histopathologic features in endometrial carcinoma is important for treatment planning. Radiomics analysis at preoperative MRI holds potential to identify high-risk phenotypes. Purpose To evaluate the performance of multiparametric MRI three-dimensional radiomics-based machine learning models for differentiating low- from high-risk histopathologic markers-deep myometrial invasion (MI), lymphovascular space invasion (LVSI), and high-grade status-and advanced-stage endometrial carcinoma. Materials and Methods This dual-center retrospective study included women with histologically proven endometrial carcinoma who underwent 1.5-T MRI before hysterectomy between January 2011 and July 2015. Exclusion criteria were tumor diameter less than 1 cm, missing MRI sequences or histopathology reports, neoadjuvant therapy, and malignant neoplasms other than endometrial carcinoma. Three-dimensional radiomics features were extracted after tumor segmentation at MRI (T2-weighted, diffusion-weighted, and dynamic contrast-enhanced MRI). Predictive features were selected in the training set with use of random forest (RF) models for each end point, and trained RF models were applied to the external test set. Five board-certified radiologists conducted MRI-based staging and deep MI assessment in the training set. Areas under the receiver operating characteristic curve (AUCs) were reported with balanced accuracies, and radiologists' readings were compared with radiomics with use of McNemar tests. Results In total, 157 women were included: 94 at the first institution (training set; mean age, 66 years ± 11 [SD]) and 63 at the second institution (test set; 67 years ± 12). RF models dichotomizing deep MI, LVSI, high grade, and International Federation of Gynecology and Obstetrics (FIGO) stage led to AUCs of 0.81 (95% CI: 0.68, 0.88), 0.80 (95% CI: 0.67, 0.93), 0.74 (95% CI: 0.61, 0.86), and 0.84 (95% CI: 0.72, 0.92), respectively, in the test set. In the training set, radiomics provided increased performance compared with radiologists' readings for identifying deep MI (balanced accuracy, 86% vs 79%; = .03), while no evidence of a difference was observed in performance for advanced FIGO stage (80% vs 78%; = .27). Conclusion Three-dimensional radiomics can stratify patients by using preoperative MRI according to high-risk histopathologic end points in endometrial carcinoma and provide nonsignificantly different or higher performance than radiologists in identifying advanced stage and deep myometrial invasion, respectively. © RSNA, 2022 See also the editorial by Kido and Nishio in this issue.

MeSH Term

Humans
Female
Multiparametric Magnetic Resonance Imaging
Retrospective Studies
Endometrial Neoplasms
Magnetic Resonance Imaging
Risk Assessment
Journal Article Research Support, Non-U.S. Gov't
Article has an altmetric score of 13

Word Cloud

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