Breast Magnetic Resonance Image Analysis for Surgeons Using Virtual Reality: A Comparative Study

Author:

El Beheiry Mohamed1ORCID,Gaillard Thomas2ORCID,Girard Noémie2ORCID,Darrigues Lauren2ORCID,Osdoit Marie2ORCID,Feron Jean-Guillaume2,Sabaila Anne2,Laas Enora2ORCID,Fourchotte Virginie2,Laki Fatima2,Lecuru Fabrice2ORCID,Couturaud Benoit2,Binder Jean-Philippe2,Masson Jean-Baptiste1ORCID,Reyal Fabien23ORCID,Malhaire Caroline45ORCID

Affiliation:

1. Decision and Bayesian Computation, USR 3756 (C3BI/DBC) and Neuroscience Department CNRS UMR 3571, Institut Pasteur and CNRS, Paris, France

2. Surgery Department, Institut Curie, PSL Research University, Paris, France

3. U932, Immunity and Cancer, INSERM, Institut Curie, Paris, France

4. Department of Medical Imaging, Institut Curie, PSL Research University, Paris, France

5. Institut Curie, INSERM, LITO Laboratory, Orsay, France

Abstract

PURPOSE The treatment of breast cancer, the leading cause of cancer and cancer mortality among women worldwide, is mainly on the basis of surgery. In this study, we describe the use of a medical image visualization tool on the basis of virtual reality (VR), entitled DIVA, in the context of breast cancer tumor localization among surgeons. The aim of this study was to evaluate the speed and accuracy of surgeons using DIVA for medical image analysis of breast magnetic resonance image (MRI) scans relative to standard image slice-based visualization tools. MATERIALS AND METHODS In our study, residents and practicing surgeons used two breast MRI reading modalities: the common slice-based radiology interface and the DIVA system in its VR mode. Metrics measured were compared in relation to postoperative anatomical-pathologic reports. RESULTS Eighteen breast surgeons from the Institut Curie performed all the analysis presented. The MRI analysis time was significantly lower with the DIVA system than with the slice-based visualization for residents, practitioners, and subsequently the entire group ( P < .001). The accuracy of determination of which breast contained the lesion significantly increased with DIVA for residents ( P = .003) and practitioners ( P = .04). There was little difference between the DIVA and slice-based visualization for the determination of the number of lesions. The accuracy of quadrant determination was significantly improved by DIVA for practicing surgeons ( P = .01) but not significantly for residents ( P = .49). CONCLUSION This study indicates that the VR visualization of medical images systematically improves surgeons' analysis of preoperative breast MRI scans across several different metrics irrespective of surgeon seniority.

Publisher

American Society of Clinical Oncology (ASCO)

Subject

General Medicine

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