PMID- 31806500
OWN - NLM
STAT- MEDLINE
DCOM- 20210812
LR  - 20210812
IS  - 1879-291X (Electronic)
IS  - 0301-5629 (Linking)
VI  - 46
IP  - 3
DP  - 2020 Mar
TI  - Deformable Mapping Method to Relate Lesions in Dedicated Breast CT Images to 
      Those in Automated Breast Ultrasound and Digital Breast Tomosynthesis Images.
PG  - 750-765
LID - S0301-5629(19)31553-4 [pii]
LID - 10.1016/j.ultrasmedbio.2019.10.016 [doi]
AB  - This work demonstrates the potential for using a deformable mapping method to 
      register lesions between dedicated breast computed tomography (bCT) and both 
      automated breast ultrasound (ABUS) and digital breast tomosynthesis (DBT) images 
      (craniocaudal [CC] and mediolateral oblique [MLO] views). Two multi-modality 
      breast phantoms with external fiducial markers attached were imaged by the three 
      modalities. The DBT MLO view was excluded for the second phantom. The automated 
      deformable mapping algorithm uses biomechanical modeling to determine 
      corresponding lesions based on distances between their centers of mass (d(COM)) 
      in the deformed bCT model and the reference model (DBT or ABUS). For bCT to ABUS, 
      the mean d(COM) was 5.2 +/- 2.6 mm. For bCT to DBT (CC), the mean d(COM) was 5.1 +/- 
      2.4 mm. For bCT to DBT (MLO), the mean d(COM) was 4.7 +/- 2.5 mm. This application 
      could help improve a radiologist's efficiency and accuracy in breast lesion 
      characterization, using multiple imaging modalities.
CI  - Copyright (c) 2019 World Federation for Ultrasound in Medicine & Biology. Published 
      by Elsevier Inc. All rights reserved.
FAU - Green, Crystal A
AU  - Green CA
AD  - Department of Nuclear Engineering and Radiological Sciences, University of 
      Michigan, Ann Arbor, MI, USA; Department of Radiology, University of Michigan 
      Health System, Ann Arbor, MI, USA. Electronic address: canngree@umich.edu.
FAU - Goodsitt, Mitchell M
AU  - Goodsitt MM
AD  - Department of Nuclear Engineering and Radiological Sciences, University of 
      Michigan, Ann Arbor, MI, USA; Department of Radiology, University of Michigan 
      Health System, Ann Arbor, MI, USA.
FAU - Lau, Jasmine H
AU  - Lau JH
AD  - Department of Radiology, University of Michigan Health System, Ann Arbor, MI, 
      USA.
FAU - Brock, Kristy K
AU  - Brock KK
AD  - Department of Imaging Physics, University of Texas MD Anderson Cancer Center, 
      Houston, TX, USA.
FAU - Davis, Cynthia L
AU  - Davis CL
AD  - General Electric Global Research, Niskayuna, NY, USA.
FAU - Carson, Paul L
AU  - Carson PL
AD  - Department of Radiology, University of Michigan Health System, Ann Arbor, MI, 
      USA.
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20191202
PL  - England
TA  - Ultrasound Med Biol
JT  - Ultrasound in medicine & biology
JID - 0410553
SB  - IM
MH  - *Algorithms
MH  - Breast Neoplasms/*diagnostic imaging
MH  - *Image Processing, Computer-Assisted
MH  - Mammography/*methods
MH  - Phantoms, Imaging
MH  - Tomography, X-Ray Computed/*methods
MH  - Ultrasonography, Mammary/*methods
OTO - NOTNLM
OT  - Automated breast ultrasound
OT  - Biomechanical modeling
OT  - Breast CT
OT  - Breast imaging
OT  - Deformable registration
OT  - Digital breast tomosynthesis
OT  - External markers
OT  - Multi-modality
COIS- Conflict of interest disclosure M. Goodsitt is a co-investigator on a grant 
      funded by GE Healthcare. C. Davis is an employee of General Electric Corporation 
      and holds several US patents on medical imaging. M. Goodsitt and P. Carson are 
      collaborators on research with GE Global Research, Niskayuna, NY.
EDAT- 2019/12/07 06:00
MHDA- 2021/08/13 06:00
CRDT- 2019/12/07 06:00
PHST- 2019/01/04 00:00 [received]
PHST- 2019/10/03 00:00 [revised]
PHST- 2019/10/18 00:00 [accepted]
PHST- 2019/12/07 06:00 [pubmed]
PHST- 2021/08/13 06:00 [medline]
PHST- 2019/12/07 06:00 [entrez]
AID - S0301-5629(19)31553-4 [pii]
AID - 10.1016/j.ultrasmedbio.2019.10.016 [doi]
PST - ppublish
SO  - Ultrasound Med Biol. 2020 Mar;46(3):750-765. doi: 
      10.1016/j.ultrasmedbio.2019.10.016. Epub 2019 Dec 2.