A semi-automated volumetric software for segmentation and perfusion parameter quantification of brain tumors using 320-row multidetector computed tomography: a validation study.
Purpose: We developed a semi-automated volumetric software, NPerfusion, to segment brain tumors and quantify perfusion parameters on whole-brain CT perfusion (WBCTP) images. The purpose of this study was to assess the feasibility of the software and to validate its performance compared with manual s...
| Published in: | Neuroradiology Vol. 59; no. 5; pp. 461 - 470 |
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| Main Authors: | , , , , , , |
| Format: | diagnostic images research tables/charts Journal Article |
| Published: |
Springer Nature
May2017
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=122560495&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 122560495 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00283940 NYZ jtl: Neuroradiology issn: 00283940 maglogo: N pubinfo: dt: May2017 vid: 59 iid: 5 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 122560495 122560495 144012355 122560495 10.1007/s00234-017-1790-6 122560495 ppf: 461 ppct: 9 formats: fmt: @attributes: type: P tig: atl: A semi-automated volumetric software for segmentation and perfusion parameter quantification of brain tumors using 320-row multidetector computed tomography: a validation study. aug: au: Chae, Soo Suh, Sangil Ryoo, Inseon Park, Arim Noh, Kyoung Shim, Hackjoon Seol, Hae affil: Department of Radiology , Korea University Guro Hospital , 148 Gurodong-ro, Guro-gu Seoul South Korea sug: subj: Brain Neoplasms Radiography Software Methods Perfusion Imaging Methods Tomography, X-Ray Computed Methods Human Correlation Coefficient Cerebral Blood Volume Validation Studies Hemodynamics Comparative Studies ab: Purpose: We developed a semi-automated volumetric software, NPerfusion, to segment brain tumors and quantify perfusion parameters on whole-brain CT perfusion (WBCTP) images. The purpose of this study was to assess the feasibility of the software and to validate its performance compared with manual segmentation. Methods: Twenty-nine patients with pathologically proven brain tumors who underwent preoperative WBCTP between August 2012 and February 2015 were included. Three perfusion parameters, arterial flow (AF), equivalent blood volume (EBV), and Patlak flow (PF, which is a measure of permeability of capillaries), of brain tumors were generated by a commercial software and then quantified volumetrically by NPerfusion, which also semi-automatically segmented tumor boundaries. The quantification was validated by comparison with that of manual segmentation in terms of the concordance correlation coefficient and Bland-Altman analysis. Results: With NPerfusion, we successfully performed segmentation and quantified whole volumetric perfusion parameters of all 29 brain tumors that showed consistent perfusion trends with previous studies. The validation of the perfusion parameter quantification exhibited almost perfect agreement with manual segmentation, with Lin concordance correlation coefficients ( ρ ) for AF, EBV, and PF of 0.9988, 0.9994, and 0.9976, respectively. On Bland-Altman analysis, most differences between this software and manual segmentation on the commercial software were within the limit of agreement. Conclusions: NPerfusion successfully performs segmentation of brain tumors and calculates perfusion parameters of brain tumors. We validated this semi-automated segmentation software by comparing it with manual segmentation. NPerfusion can be used to calculate volumetric perfusion parameters of brain tumors from WBCTP. pubtype: Academic Journal doctype: diagnostic images research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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