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

Young Han Lee, Sungjun Kim, Daekeon Lim, Jin Suck Suh, Ho Taek Song

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)

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 99mTc-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.

Original languageEnglish
Pages (from-to)458-464
Number of pages7
JournalActa Radiologica
Volume56
Issue number4
DOIs
Publication statusPublished - 2015 Apr 1

All Science Journal Classification (ASJC) codes

  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging

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