Deformable mapping technique to correlate lesions in digital breast tomosynthesis and automated breast ultrasound images

Crystal A. Green, Mitchell M. Goodsitt, Kristy K. Brock, Cynthia L. Davis, Eric D. Larson, Jasmine H. Lau, Paul L. Carson

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Purpose: To develop a deformable mapping technique to match corresponding lesions between digital breast tomosynthesis (DBT) and automated breast ultrasound (ABUS) images. Methods: External fiducial markers were attached to the surface of two CIRS multi-modality compressible breast phantoms (A and B) containing multiple simulated lesions. Both phantoms were imaged with DBT (upright positioning with cranial-caudal compression) and ABUS (supine positioning with anterior-to-chest wall compression). The lesions and markers were manually segmented by three different readers. Reader segmentation similarity and reader reproducibility were assessed using Dice similarity coefficients (DSC) and distances between centers of mass (dCOM). For deformable mapping between the modalities each reader's segmented dataset was processed with an automated deformable mapping algorithm as follows: First, Morfeus, a finite element (FE) based multi-organ deformable image registration platform, converted segmentations into triangular surface meshes. Second, Altair HyperMesh, a FE pre-processor, created base FE models for the ABUS and DBT data sets. All deformation is performed on the DBT image data; the ABUS image sets remain fixed throughout the process. Deformation was performed on the external skin contour (DBT image set) to match the external skin contour on the ABUS set, and the locations of the external markers were used to morph the skin contours to be within a user-defined distance. Third, the base DBT-FE model was deformed with the FE analysis solver, Optistruct. Deformed DBT lesions were correlated with matching lesions in the base ABUS FE model. Performance (lesion correlation) was assessed with dCOM for all corresponding lesions and lesion overlap. Analysis was performed to determine the minimum number of external fiducial markers needed to create the desired correlation and the improvement of correlation with the use of external markers. Results: Average DSC for reader similarity ranged from 0.88 to 0.91 (ABUS) and 0.57 to 0.83 (DBT). Corresponding dCOM ranged from 0.20 to 0.36 mm (ABUS) and 0.11 to 1.16 mm (DBT). Lesion correlation is maximized when all corresponding markers are within a maximum distance of 5 mm. For deformable mapping of phantom A, without the use of external markers, only two of six correlated lesions showed overlap with an average lesion dCOM of 6.8 ± 2.8 mm. With use of three external fiducial markers, five of six lesions overlapped and average dCOM improved to 4.9 ± 2.4 mm. For deformable mapping of Phantom B without external markers analysis, four lesions were correlated of seven with overlap between only one of seven lesions, and an average lesion dCOM of 9.7 ± 3.5 mm. With three external markers, all seven possible lesions were correlated with overlap between four of seven lesions. The average dCOM was 8.5 ± 4.0 mm. Conclusion: This work demonstrates the potential for a deformable mapping technique to relate corresponding lesions in DBT and ABUS images by showing improved lesion correspondence and reduced lesion registration errors with the use of external fiducial markers. The technique should improve radiologists’ characterization of breast lesions which can reduce patient callbacks, misdiagnoses and unnecessary biopsies.

Original languageEnglish (US)
Pages (from-to)4402-4417
Number of pages16
JournalMedical Physics
Volume45
Issue number10
DOIs
StateAccepted/In press - Jan 1 2018
Externally publishedYes

Keywords

  • biomechanical modeling
  • breast ultrasound
  • deformable registration
  • digital breast tomosynthesis

ASJC Scopus subject areas

  • Biophysics
  • Radiology Nuclear Medicine and imaging

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