Tumor deformation correction for an image guidance system in breast conserving surgery

Winona L. Richey; Jon Heiselman; Morgan Ringel; Ingrid M. Meszoely; Michael I. Miga

doi:10.1117/12.2611570

4 April 2022 Tumor deformation correction for an image guidance system in breast conserving surgery

Winona L. Richey, Jon Heiselman, Morgan Ringel, Ingrid M. Meszoely, Michael I. Miga

Proceedings Volume 12034, Medical Imaging 2022: Image-Guided Procedures, Robotic Interventions, and Modeling; 120340K (2022) https://doi.org/10.1117/12.2611570
Event: SPIE Medical Imaging, 2022, San Diego, California, United States

Abstract

Breast cancer is the most common cancer in women, and surgical resection is standard of care for the majority of breast cancer patients. Unfortunately, current reoperation rates are 10-29%. Uncertainty in lesion localization is one of the main factors contributing to these high reoperation rates. This work uses the linearized iterative boundary reconstruction approach to model patient breast deformation due to abduction of the ipsilateral arm. A preoperative supine magnetic resonance (MR) image was obtained with the patient’s arms down near the torso. A mock intraoperative breast shape was measured from a supine MR image obtained with the patient’s arm up near the head. Sparse data was subsampled from the full volumetric image to represent realistic intraoperative data collection: surface fiducial points, the intrafiducial skin surface, and the chest wall as measured with 7 tracked ultrasound images. The deformed preoperative armdown data was compared to the ground truth arm-up data. From rigid registration to model correction the tumor centroid distance improves from 7.3 mm to 3.3 mm, average surface fiducial error across 9 synthetic fiducials and the nipple improves from 7.4 ± 2.2 to 1.3 ± 0.7, and average subsurface error across 14 corresponding features improves from 6.2 ± 1.4 mm to 3.5 ± 1.1 mm. Using preoperative supine MR imaging and sparse data in the deformed position, this modeling framework can correct for breast shape changes between imaging and surgery to more accurately predict intraoperative position of the tumor as well as 10 surface fiducials and 14 subsurface features.

Conference Presentation

Citation Download Citation

Winona L. Richey, Jon Heiselman, Morgan Ringel, Ingrid M. Meszoely, and Michael I. Miga "Tumor deformation correction for an image guidance system in breast conserving surgery", Proc. SPIE 12034, Medical Imaging 2022: Image-Guided Procedures, Robotic Interventions, and Modeling, 120340K (4 April 2022); https://doi.org/10.1117/12.2611570

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