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Rapid detection of bone metastasis at thoracoabdominal CT: accuracy and efficiency of a new visualization algorithm.

Publication ,  Journal Article
Toth, DF; Töpker, M; Mayerhöfer, ME; Rubin, GD; Furtner, J; Asenbaum, U; Karanikas, G; Weber, M; Czerny, C; Herold, CJ; Ringl, H
Published in: Radiology
March 2014

PURPOSE: To retrospectively assess the use of a combination of cancellous bone reconstructions (CBR) and multiplanar reconstructions (MPRs) for the detection of bone metastases at thoracoabdominal computed tomography (CT) compared with the use of MPRs alone. MATERIALS AND METHODS: The study was approved by the local institutional review board. Included were 156 consecutive patients with confirmed cancer who underwent a whole-body positron emission tomography (PET)/CT examination for clinical purposes (93 male and 63 female patients; mean age ± standard deviation, 59.8 years ± 14.9; range, 11-85 years). Only the CT images were processed with the CBR algorithm, which segments the bones and removes the cortical layer from the images. The PET images served as part of the reference standard. Images from 15 patients were used as a training set. Four radiologists independently evaluated images of half of the remaining 141 patients by using CBRs and MPRs together, and the other half by using MPRs only. Radiologists were blinded to patient names, and patient order was randomized. Results for detection rates and reporting time were recorded and compared with a standard of reference for each patient that was created by one senior radiologist and one nuclear medicine specialist by using all available CT and PET data, CBRs, and follow-up examinations. General estimation equations were used for statistical analysis. RESULTS: There were 349 lesions found in 103 patients, with 203 classified as malignant. Each patient was assessed by two readers per method, leading to a total of 698 lesions. The detection rate for all bone lesions was 35% (247 of 698) for MPRs and 74% (520 of 698) when CBRs and MPRs were used together, which was significantly higher (P < .001). The average reading time decreased from 85 to 43 seconds (P < .001) when both reconstructions were used. CONCLUSION: Advanced visualization of cancellous bone significantly increased the detection of bone metastases and reduced the time for interpretation.

Duke Scholars

Published In

Radiology

DOI

EISSN

1527-1315

Publication Date

March 2014

Volume

270

Issue

3

Start / End Page

825 / 833

Location

United States

Related Subject Headings

  • Tomography, X-Ray Computed
  • Retrospective Studies
  • Radiographic Image Interpretation, Computer-Assisted
  • Nuclear Medicine & Medical Imaging
  • Middle Aged
  • Male
  • Humans
  • Female
  • Child
  • Bone Neoplasms
 

Citation

APA
Chicago
ICMJE
MLA
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Toth, D. F., Töpker, M., Mayerhöfer, M. E., Rubin, G. D., Furtner, J., Asenbaum, U., … Ringl, H. (2014). Rapid detection of bone metastasis at thoracoabdominal CT: accuracy and efficiency of a new visualization algorithm. Radiology, 270(3), 825–833. https://doi.org/10.1148/radiol.13130789
Toth, Daniel F., Michael Töpker, Marius E. Mayerhöfer, Geoffrey D. Rubin, Julia Furtner, Ulrika Asenbaum, Georgios Karanikas, et al. “Rapid detection of bone metastasis at thoracoabdominal CT: accuracy and efficiency of a new visualization algorithm.Radiology 270, no. 3 (March 2014): 825–33. https://doi.org/10.1148/radiol.13130789.
Toth DF, Töpker M, Mayerhöfer ME, Rubin GD, Furtner J, Asenbaum U, et al. Rapid detection of bone metastasis at thoracoabdominal CT: accuracy and efficiency of a new visualization algorithm. Radiology. 2014 Mar;270(3):825–33.
Toth, Daniel F., et al. “Rapid detection of bone metastasis at thoracoabdominal CT: accuracy and efficiency of a new visualization algorithm.Radiology, vol. 270, no. 3, Mar. 2014, pp. 825–33. Pubmed, doi:10.1148/radiol.13130789.
Toth DF, Töpker M, Mayerhöfer ME, Rubin GD, Furtner J, Asenbaum U, Karanikas G, Weber M, Czerny C, Herold CJ, Ringl H. Rapid detection of bone metastasis at thoracoabdominal CT: accuracy and efficiency of a new visualization algorithm. Radiology. 2014 Mar;270(3):825–833.

Published In

Radiology

DOI

EISSN

1527-1315

Publication Date

March 2014

Volume

270

Issue

3

Start / End Page

825 / 833

Location

United States

Related Subject Headings

  • Tomography, X-Ray Computed
  • Retrospective Studies
  • Radiographic Image Interpretation, Computer-Assisted
  • Nuclear Medicine & Medical Imaging
  • Middle Aged
  • Male
  • Humans
  • Female
  • Child
  • Bone Neoplasms