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Biotechnology - Oncology - Radiology and Medical Imaging


An Open Environment CT-US Fusion for Tissue Segmentation during Interventional Guidance
Published: Wednesday, November 23, 2011
Author: Charles F. Caskey et al.

by Charles F. Caskey, Mario Hlawitschka, Shengping Qin, Lisa M. Mahakian, Robert D. Cardiff, John M. Boone, Katherine W. Ferrara

Therapeutic ultrasound (US) can be noninvasively focused to activate drugs, ablate tumors and deliver drugs beyond the blood brain barrier. However, well-controlled guidance of US therapy requires fusion with a navigational modality, such as magnetic resonance imaging (MRI) or X-ray computed tomography (CT). Here, we developed and validated tissue characterization using a fusion between US and CT. The performance of the CT/US fusion was quantified by the calibration error, target registration error and fiducial registration error. Met-1 tumors in the fat pads of 12 female FVB mice provided a model of developing breast cancer with which to evaluate CT-based tissue segmentation. Hounsfield units (HU) within the tumor and surrounding fat pad were quantified, validated with histology and segmented for parametric analysis (fat: -300 to 0 HU, protein-rich: 1 to 300 HU, and bone: HU>300). Our open source CT/US fusion system differentiated soft tissue, bone and fat with a spatial accuracy of ~1 mm. Region of interest (ROI) analysis of the tumor and surrounding fat pad using a 1 mm2 ROI resulted in mean HU of 68±44 within the tumor and -97±52 within the fat pad adjacent to the tumor (p<0.005). The tumor area measured by CT and histology was correlated (r2?=?0.92), while the area designated as fat decreased with increasing tumor size (r2?=?0.51). Analysis of CT and histology images of the tumor and surrounding fat pad revealed an average percentage of fat of 65.3% vs. 75.2%, 36.5% vs. 48.4%, and 31.6% vs. 38.5% for tumors <75 mm3, 75–150 mm3 and >150 mm3, respectively. Further, CT mapped bone-soft tissue interfaces near the acoustic beam during real-time imaging. Combined CT/US is a feasible method for guiding interventions by tracking the acoustic focus within a pre-acquired CT image volume and characterizing tissues proximal to and surrounding the acoustic focus.
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