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ROI for outlining an entire tumor is a reliable approach for quantification of lung cancer tumor vascular parameters using CT perfusion

Authors Ma E, An R, Gao B, Yang M, Zhao Q, Wang W, Li K

Received 11 October 2015

Accepted for publication 1 March 2016

Published 27 April 2016 Volume 2016:9 Pages 2377—2384

DOI https://doi.org/10.2147/OTT.S98060

Checked for plagiarism Yes

Review by Single-blind

Peer reviewers approved by Dr Ram Prasad

Peer reviewer comments 2

Editor who approved publication: Professor Min Li


Ensen Ma,1 An Ren,1 Baoxiang Gao,1 Minxing Yang,1 Qichao Zhao,1 Wu Wang,1 Kefeng Li2

1Department of Radiology, China–Japan Friendship Hospital, Beijing, People’s Republic of China; 2Department of Medicine, School of Medicine, University of California, San Diego, CA, USA
 
Objective: To investigate the effect of position and size of tumor region of interest (ROI) on the estimation of lung cancer vascular parameters using 256-slice computed tomography (CT) perfusion.
Methods: After institutional review board approval and written informed consent, 16 men and 11 women with lung cancer were enrolled in this CT perfusion study. Perfusion, blood volume, and peak enhancement were determined for 60 or 120 mm2 circular ROIs placed at the edge, center, and around (outlining) the visible tumor. Average values were obtained by performing ROI analysis twice by the same observers without any procedural changes.
Results: Perfusion, blood volume, and peak enhancement measurements were substantially higher at the edge than at the center for both 60 and 120 mm2 ROIs (all P<0.05). Measurements varied substantially depending on the ROI size. Perfusion, blood volume, and peak enhancement for the ROIs outlining tumor were intermediate between those at the tumor edge and center. There were significant correlations between median values and interquartile ranges as follows; perfusion (12.51 [7.91–28.10] mL·min−1·100 mL−1), blood volume (29.31 [21.82–37.65] mL·100 g−1), peak enhancement (12.93 [2.42–22.50]) for the ROIs outlining the tumor, and microvascular density ([19.43±8.78] vessels/0.74 mm2), respectively (r values were 0.732, 0.590, and 0.544 respectively, all P<0.05).
Conclusion: Spatial and size selection of ROI significantly affects CT perfusion analysis. ROI outlining of entire tumor provides efficient and reliable measurements for clinical assessment of lung cancer using CT perfusion.

Keywords: lung carcinoma, position, size, tomography, X-ray computed, dynamic enhancement, microvessel density

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