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Spectral parametric segmentation of contrast-enhanced dual-energy CT to detect bone metastasis: feasibility sensitivity study using whole-body bone scintigraphy

Authors
 Young Han Lee  ;  Sungjun Kim  ;  Daekeon Lim  ;  Jin-Suck Suh  ;  Ho-Taek Song 
Citation
 Acta Radiologica, Vol.56(4) : 458-464, 2015 
Journal Title
 Acta Radiologica 
ISSN
 0284-1851 
Issue Date
2015
Abstract
BACKGROUND: Dual-energy computed tomography (DECT) images may be underutilized for the evaluation of skeletal metastasis. Spectral parametric segmentation of DECT can produce bone-iodine separated images, which have the potential to detect bone metastases. PURPOSE: To evaluate the potential of bone-iodine separation in the detection of bone metastasis with spectral parametric segmentation of DECT images which are acquired at clinical follow-up for patients with prior malignancy. MATERIAL AND METHODS: The institutional review board approved the protocol of this retrospective review. Chest DECT scans using fast kV-switching between 80 and 140 kVp were included in this study. Bone-iodine separated reformatted images were produced by spectral parametric segmentation of synthesized monochromatic images. All chest CT images of 702 metastatic lesions from 54 patients were retrospectively evaluated in terms of visualization of metastatic lesions compared with (99m)Tc-MDP (methylene diphosphonate) whole-body bone scintigraphy (WBBS) as reference standard of diagnosis. RESULTS: Spectral parametric segmentation images of DECT visualized metastatic lesions in 92.3% (n = 648/702). Osteoblastic metastases were delineated as subtle enhancing lesions on DECT in comparison to WBBS. CONCLUSION: Spectral parametric segmentation of iodine from cortical and medullary bone allowed visualization of bone metastasis. DECT might be utilized for the screening or detection of bone metastases.
Full Text
http://acr.sagepub.com/content/56/4/458.long
DOI
10.1177/0284185114530105
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Radiology (영상의학교실) > 1. Journal Papers
Yonsei Authors
Kim, Sungjun(김성준) ORCID logo https://orcid.org/0000-0002-7876-7901
Suh, Jin Suck(서진석) ORCID logo https://orcid.org/0000-0001-9455-9240
Song, Ho Taek(송호택) ORCID logo https://orcid.org/0000-0002-6655-2575
Lee, Young Han(이영한) ORCID logo https://orcid.org/0000-0002-5602-391X
Lim, Dae Keon(임대건)
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URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/140065
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