Prone to Supine Surface Based Registration Workflow for Breast Tumor Localization in Surgical Planning

Breast cancer is the most frequent cancer in women worldwide. Screening programs and imaging improvements have increased the detection of clinically occult non-palpable lesions requiring preoperative localization. Image-guided wire localization (WGL) is the current standard of care for the excision of non-palpable carcinomas during breast conserving surgery (BCS). Due to the current limitations of intraoperative tumor localization approaches, the integration of the information from multimodal imaging may be especially relevant in surgical planning. This work presents a workflow to perform a prone image-to-surgical physical data alignment in order to determine the correspondence between the tumor identified in the preoperative image and the final position of the tumor in the surgical position. The evaluation of the methodology has been carried out in 18 cases achieving an average localization error of 10.40 mm and 9.84 mm in 11 small lesion cases (less than 1 cm in diameter).

[1]  Umberto Veronesi,et al.  Twenty-year follow-up of a randomized study comparing breast-conserving surgery with radical mastectomy for early breast cancer. , 2002, The New England journal of medicine.

[2]  Richard Sposto,et al.  Palpable Breast Cancers Are Inherently Different From Nonpalpable Breast Cancers , 2001, Annals of Surgical Oncology.

[3]  Daniel Rueckert,et al.  Nonrigid registration using free-form deformations: application to breast MR images , 1999, IEEE Transactions on Medical Imaging.

[4]  J. G. Schuler,et al.  The new era in breast cancer. Invasion, size, and nodal involvement dramatically decreasing as a result of mammographic screening. , 1996, Archives of surgery.

[5]  David J. Hawkes,et al.  A Framework for Image-Guided Breast Surgery , 2006, MIAR.

[6]  Keith D. Paulsen,et al.  Supine Breast MRI and 3D Optical Scanning: A Novel Approach to Improve Tumor Localization for Breast Conserving Surgery , 2014, Annals of Surgical Oncology.

[7]  David J. Hawkes,et al.  MR Navigated Breast Surgery: Method and Initial Clinical Experience , 2008, MICCAI.

[8]  Michael Unser,et al.  Fast parametric elastic image registration , 2003, IEEE Trans. Image Process..

[9]  A. Jemal,et al.  Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries , 2018, CA: a cancer journal for clinicians.

[10]  Sébastien Ourselin,et al.  A Nonlinear Biomechanical Model Based Registration Method for Aligning Prone and Supine MR Breast Images , 2014, IEEE Transactions on Medical Imaging.

[11]  D B Kopans,et al.  Migration of breast biopsy localization wire. , 1988, AJR. American journal of roentgenology.

[12]  Mert R. Sabuncu,et al.  VoxelMorph: A Learning Framework for Deformable Medical Image Registration , 2018, IEEE Transactions on Medical Imaging.

[13]  Muneer Ahmed,et al.  Systematic review of radioguided versus wire-guided localization in the treatment of non-palpable breast cancers , 2013, Breast Cancer Research and Treatment.

[14]  María J. Ledesma-Carbayo,et al.  Tumor localization using prone to supine surface based registration for breast cancer surgical planning , 2018, 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018).

[15]  Olga Sorkine-Hornung,et al.  On Linear Variational Surface Deformation Methods , 2008, IEEE Transactions on Visualization and Computer Graphics.