title: An open environment CT-US fusion for tissue segmentation during interventional guidance.
abstract: 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 mm(2) 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 (r(2) = 0.92), while the area designated as fat decreased with increasing tumor size (r(2) = 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 mm(3), 75-150 mm(3) and >150 mm(3), 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.
authors: Department of Biomedical Engineering, University of California Davis, Davis, California, United States of America. cfcaskey@ucdavis.edu
authors: Charles F
authors: CF
authors: Caskey
authors: Mario
authors: M
authors: Hlawitschka
authors: Shengping
authors: S
authors: Qin
authors: Lisa M
authors: LM
authors: Mahakian
authors: Robert D
authors: RD
authors: Cardiff
authors: John M
authors: JM
authors: Boone
authors: Katherine W
authors: KW
authors: Ferrara
mesh_terms: D000273:Adipose Tissue / Q000000981:diagnostic imaging; D000818:Animals; D001331:Automation; D002138:Calibration; D004574:Electromagnetic Fields; D005240:Feasibility Studies; D005260:Female; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D051379:Mice; D009369:Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology; D009928:Organ Specificity; D014057:Tomography, X-Ray Computed / Q000379:methods*; D014463:Ultrasonography