{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,23]],"date-time":"2025-10-23T21:01:32Z","timestamp":1761253292578,"version":"3.41.0"},"reference-count":48,"publisher":"Wiley","issue":"10","license":[{"start":{"date-parts":[[2018,8,31]],"date-time":"2018-08-31T00:00:00Z","timestamp":1535673600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/100014126","name":"GE Global Research","doi-asserted-by":"crossref","award":["15-PAF04328"],"award-info":[{"award-number":["15-PAF04328"]}],"id":[{"id":"10.13039\/100014126","id-type":"DOI","asserted-by":"crossref"}]},{"name":"The Science, Mathematics and Research for Transformation (SMART) Scholarship for Service Program","award":["HQ0034-16-C-0008"],"award-info":[{"award-number":["HQ0034-16-C-0008"]}]}],"content-domain":{"domain":["aapm.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Medical Physics"],"published-print":{"date-parts":[[2018,10]]},"abstract":"<jats:sec><jats:title>Purpose<\/jats:title><jats:p>To develop a deformable mapping technique to match corresponding lesions between digital breast tomosynthesis (DBT) and automated breast ultrasound (ABUS) images.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>External fiducial markers were attached to the surface of two CIRS multi\u2010modality compressible breast phantoms (A and B) containing multiple simulated lesions. Both phantoms were imaged with DBT (upright positioning with cranial\u2010caudal compression) and ABUS (supine positioning with anterior\u2010to\u2010chest 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 (d<jats:sub>COM<\/jats:sub>). 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\u2010organ deformable image registration platform, converted segmentations into triangular surface meshes. Second, Altair HyperMesh, a FE pre\u2010processor, 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\u2010defined distance. Third, the base DBT\u2010FE 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 d<jats:sub>COM<\/jats:sub>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.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Average DSC for reader similarity ranged from 0.88 to 0.91 (ABUS) and 0.57 to 0.83 (DBT). Corresponding d<jats:sub>COM<\/jats:sub>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 d<jats:sub>COM<\/jats:sub>of 6.8 \u00b1 2.8 mm. With use of three external fiducial markers, five of six lesions overlapped and average d<jats:sub>COM<\/jats:sub>improved to 4.9 \u00b1 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 d<jats:sub>COM<\/jats:sub>of 9.7 \u00b1 3.5 mm. With three external markers, all seven possible lesions were correlated with overlap between four of seven lesions. The average d<jats:sub>COM<\/jats:sub>was 8.5 \u00b1 4.0 mm.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>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\u2019 characterization of breast lesions which can reduce patient callbacks, misdiagnoses and unnecessary biopsies.<\/jats:p><\/jats:sec>","DOI":"10.1002\/mp.13113","type":"journal-article","created":{"date-parts":[[2018,8,1]],"date-time":"2018-08-01T14:14:37Z","timestamp":1533132877000},"page":"4402-4417","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Deformable mapping technique to correlate lesions in digital breast tomosynthesis and automated breast ultrasound images"],"prefix":"10.1002","volume":"45","author":[{"given":"Crystal A.","family":"Green","sequence":"first","affiliation":[{"name":"Department of Nuclear Engineering and Radiological Sciences University of Michigan Ann Arbor MI 48109 USA"},{"name":"Department of Radiology University of Michigan Health System Ann Arbor MI 48109 USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mitchell M.","family":"Goodsitt","sequence":"additional","affiliation":[{"name":"Department of Nuclear Engineering and Radiological Sciences University of Michigan Ann Arbor MI 48109 USA"},{"name":"Department of Radiology University of Michigan Health System Ann Arbor MI 48109 USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kristy K.","family":"Brock","sequence":"additional","affiliation":[{"name":"Department of Nuclear Engineering and Radiological Sciences University of Michigan Ann Arbor MI 48109 USA"},{"name":"Imaging Physics University of Texas MD Anderson Cancer Center Houston TX 77030 USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cynthia L.","family":"Davis","sequence":"additional","affiliation":[{"name":"GE Global Research Niskayuna NY 12309 USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Eric D.","family":"Larson","sequence":"additional","affiliation":[{"name":"Department of Radiology University of Michigan Health System Ann Arbor MI 48109 USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jasmine H.","family":"Lau","sequence":"additional","affiliation":[{"name":"Department of Radiology University of Michigan Health System Ann Arbor MI 48109 USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Paul L.","family":"Carson","sequence":"additional","affiliation":[{"name":"Department of Radiology University of Michigan Health System Ann Arbor MI 48109 USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2018,8,31]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.1148\/radiology.177.2.2217759"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0301-5629(01)00491-4"},{"key":"e_1_2_8_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(15)00774-6"},{"key":"e_1_2_8_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejrad.2016.06.004"},{"key":"e_1_2_8_6_1","doi-asserted-by":"publisher","DOI":"10.2214\/AJR.15.15367"},{"key":"e_1_2_8_7_1","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.14132832"},{"key":"e_1_2_8_8_1","doi-asserted-by":"publisher","DOI":"10.2214\/AJR.09.3244"},{"key":"e_1_2_8_9_1","doi-asserted-by":"publisher","DOI":"10.3348\/kjr.2015.16.2.229"},{"key":"e_1_2_8_10_1","doi-asserted-by":"publisher","DOI":"10.1148\/radiology.181.1.1653441"},{"key":"e_1_2_8_11_1","doi-asserted-by":"publisher","DOI":"10.7863\/jum.2007.26.5.645"},{"key":"e_1_2_8_12_1","doi-asserted-by":"crossref","unstructured":"SinhaSP RoubidouxMA HelvieMA et al.Multi\u2010modality 3d breast imaging with X\u2010ray tomosynthesis and automated ultrasound. 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