Chae Soo Young, Suh Sangil, Ryoo Inseon, Park Arim, Noh Kyoung Jin, Shim Hackjoon, Seol Hae Young
Department of Radiology, Korea University Guro Hospital, 148 Gurodong-ro, Guro-gu, Seoul, South Korea.
Department of Electronic Engineering, Soonchunhyang University, Asan, South Korea.
Neuroradiology. 2017 May;59(5):461-469. doi: 10.1007/s00234-017-1790-6. Epub 2017 Mar 24.
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.
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.
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.
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.
我们开发了一种半自动容积软件NPerfusion，用于在全脑CT灌注（WBCTP）图像上分割脑肿瘤并量化灌注参数。本研究的目的是评估该软件的可行性，并与手动分割相比验证其性能。
纳入2012年8月至2015年2月期间接受术前WBCTP检查且病理证实为脑肿瘤的29例患者。通过商业软件生成脑肿瘤的三个灌注参数，即动脉血流量（AF）、等效血容量（EBV）和Patlak血流（PF，一种衡量毛细血管通透性的指标），然后由NPerfusion进行容积量化，该软件还能半自动分割肿瘤边界。通过一致性相关系数和Bland-Altman分析，将量化结果与手动分割的结果进行比较以验证其准确性。
使用NPerfusion，我们成功地对所有29例脑肿瘤进行了分割，并量化了其全容积灌注参数，这些参数与先前研究显示出一致的灌注趋势。灌注参数量化的验证结果显示与手动分割几乎完全一致，AF、EBV和PF的Lin一致性相关系数（ρ）分别为0.9988、0.9994和0.9976。在Bland-Altman分析中，该软件与商业软件上手动分割之间的大多数差异均在一致性界限内。
NPerfusion成功地实现了脑肿瘤的分割并计算了脑肿瘤的灌注参数。我们通过与手动分割进行比较验证了这种半自动分割软件。NPerfusion可用于从WBCTP计算脑肿瘤的容积灌注参数。
