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FDG PET metabolic tumor volume segmentation and pathologic volume of primary human solid tumors.

Publication ,  Journal Article
Sridhar, P; Mercier, G; Tan, J; Truong, MT; Daly, B; Subramaniam, RM
Published in: AJR Am J Roentgenol
May 2014

OBJECTIVE: The purpose of this study was to establish the correlation and reliability among the pathologic tumor volume and gradient and fixed threshold segmentations of (18)F-FDG PET metabolic tumor volume of human solid tumors. MATERIALS AND METHODS: There were 52 patients included in the study who had undergone baseline PET/CT with subsequent resection of head and neck, lung, and colorectal tumors. The pathologic volume was calculated from three dimensions of the gross tumor specimen as a reference standard. The primary tumor metabolic tumor volume was segmented using gradient and 30%, 40%, and 50% maximum standardized uptake value (SUVmax) threshold methods. Pearson correlation coefficient, intraclass correlation coefficient, and Bland-Altman analyses were performed to establish the correlation and reliability among the pathologic volume and segmented metabolic tumor volume. RESULTS: The mean pathologic volume; gradient-based metabolic tumor volume; and 30%, 40%, and 50% SUVmax threshold metabolic tumor volumes were 13.46, 13.75, 15.47, 10.63, and 7.57 mL, respectively. The intraclass correlation coefficients among the pathologic volume and the gradient-based and 30%, 40%, and 50% SUVmax threshold metabolic tumor volumes were 0.95, 0.85, 0.80, and 0.76, respectively. The Bland-Altman biases were -0.3, -2.0, 2.82, and 5.9 mL, respectively. Of the small tumors (< 10 mL), 23 of the 35 patients had PET segmented volume outside 50% of the pathologic volume, and among the large tumors (≥ 10 mL) three of the 17 patients had PET segmented volumes that were outside 50% of pathologic volume. CONCLUSION: FDG PET metabolic tumor volume estimated using gradient segmentation had superior correlation and reliability with the estimated ellipsoid pathologic volume of the tumors compared with threshold method segmentation.

Duke Scholars

Published In

AJR Am J Roentgenol

DOI

EISSN

1546-3141

Publication Date

May 2014

Volume

202

Issue

5

Start / End Page

1114 / 1119

Location

United States

Related Subject Headings

  • Tumor Burden
  • Retrospective Studies
  • Reproducibility of Results
  • Radiopharmaceuticals
  • Positron-Emission Tomography
  • Nuclear Medicine & Medical Imaging
  • Neoplasms
  • Multimodal Imaging
  • Middle Aged
  • Male
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Sridhar, P., Mercier, G., Tan, J., Truong, M. T., Daly, B., & Subramaniam, R. M. (2014). FDG PET metabolic tumor volume segmentation and pathologic volume of primary human solid tumors. AJR Am J Roentgenol, 202(5), 1114–1119. https://doi.org/10.2214/AJR.13.11456
Sridhar, Praveen, Gustavo Mercier, Josenia Tan, Minh Tam Truong, Benedict Daly, and Rathan M. Subramaniam. “FDG PET metabolic tumor volume segmentation and pathologic volume of primary human solid tumors.AJR Am J Roentgenol 202, no. 5 (May 2014): 1114–19. https://doi.org/10.2214/AJR.13.11456.
Sridhar P, Mercier G, Tan J, Truong MT, Daly B, Subramaniam RM. FDG PET metabolic tumor volume segmentation and pathologic volume of primary human solid tumors. AJR Am J Roentgenol. 2014 May;202(5):1114–9.
Sridhar, Praveen, et al. “FDG PET metabolic tumor volume segmentation and pathologic volume of primary human solid tumors.AJR Am J Roentgenol, vol. 202, no. 5, May 2014, pp. 1114–19. Pubmed, doi:10.2214/AJR.13.11456.
Sridhar P, Mercier G, Tan J, Truong MT, Daly B, Subramaniam RM. FDG PET metabolic tumor volume segmentation and pathologic volume of primary human solid tumors. AJR Am J Roentgenol. 2014 May;202(5):1114–1119.

Published In

AJR Am J Roentgenol

DOI

EISSN

1546-3141

Publication Date

May 2014

Volume

202

Issue

5

Start / End Page

1114 / 1119

Location

United States

Related Subject Headings

  • Tumor Burden
  • Retrospective Studies
  • Reproducibility of Results
  • Radiopharmaceuticals
  • Positron-Emission Tomography
  • Nuclear Medicine & Medical Imaging
  • Neoplasms
  • Multimodal Imaging
  • Middle Aged
  • Male