Chen Hanwei, Jiang Jinzhao, Gao Junling, Liu Dan, Axelsson Jan, Cui Minyi, Gong Nan-Jie, Feng Shi-Ting, Luo Liangping, Huang Bingsheng
From the *Department of Radiology, Guangzhou Panyu Central Hospital; †Medical Imaging Center, The First Affiliated Hospital of Jinan University, Guangzhou; ‡Department of Radiology, Peking University Shenzhen Hospital, Shenzhen; §Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong Special Administrative Region, China; ∥Department of Radiation Sciences, Radiation Physics, Umeå University, Umeå, Sweden; ¶Department of Radiology, Hospital of Stomatology, Guanghua School of Stomatology; #Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China; and **Shenzhen University, Shenzhen, China.
J Comput Assist Tomogr. 2014 Mar-Apr;38(2):209-15. doi: 10.1097/RCT.0000000000000017.
The objective of this study was to compare the accuracy of calculating the primary tumor volumes using a gradient-based method and fixed threshold methods on the standardized uptake value (SUV) maps and the net influx of FDG (Ki) maps from positron emission tomography-computed tomography (PET-CT) images.
Newly diagnosed patients with head and neck cancer were recruited, and dynamic PET-CT scan and T2-weighted magnetic resonance imaging were performed. The maps of Ki and SUV were calculated from PET-CT images. The tumor volumes were calculated using a gradient-based method and a fixed threshold method at 40% of maximal SUV or maximal Ki. Four kinds of volumes, VOLKi-Gra (from the Ki maps using the gradient-based method), VOLKi-40% (from the Ki maps using the threshold of 40% maximal Ki), VOLSUV-Gra (from the SUV maps using the gradient-based method), and VOLSUV-40% (from the SUV maps using the threshold of 40% maximal SUV), were acquired and compared with VOLMRI (the volumes acquired on T2-weighted images) using the Pearson correlation, paired t test, and similarity analysis.
Eighteen patients were studied, of which 4 had poorly defined tumors (PDT). The positron emission tomography-derived volumes were as follows: VOLSUV-40%, 2.1 to 41.2 cm (mean [SD], 12.3 [10.6]); VOLSUV-Gra, 2.2 to 28.1 cm (mean [SD], 13.2 [8.4]); VOLKi-Gra, 2.4 to 17.0 cm (mean [SD], 9.5 [4.6]); and VOLKi-40%, 2.7 to 20.3 cm (mean [SD], 12.0 [6.0]). The VOLMRI ranged from 2.9 to 18.1 cm (mean [SD], 9.1 [3.9]). The VOLKi-Gra significantly correlated with VOLMRI with the highest correlation coefficient (PDT included, R = 0.673, P = 0.002; PDT excluded, R = 0.841, P < 0.001) and presented no difference from VOLMRI (P = 0.672 or 0.561, respectively, PDT included and excluded). The difference between VOLKi-Gra and VOLMRI was also the smallest.
The tumor volumes delineated on the Ki maps using the gradient-based method are more accurate than those on the SUV maps and using the fixed threshold methods.
本研究的目的是比较基于梯度的方法和固定阈值方法在正电子发射断层扫描-计算机断层扫描（PET-CT）图像的标准化摄取值（SUV）图和氟代脱氧葡萄糖（FDG）净流入量（Ki）图上计算原发性肿瘤体积的准确性。
招募新诊断的头颈癌患者，进行动态PET-CT扫描和T2加权磁共振成像。从PET-CT图像计算Ki和SUV图。使用基于梯度的方法和在最大SUV或最大Ki的40%处的固定阈值方法计算肿瘤体积。获取四种体积，即VOLKi-Gra（使用基于梯度的方法从Ki图得出）、VOLKi-40%（使用最大Ki的40%阈值从Ki图得出）、VOLSUV-Gra（使用基于梯度的方法从SUV图得出）和VOLSUV-40%（使用最大SUV的40%阈值从SUV图得出），并使用Pearson相关性分析、配对t检验和相似性分析将其与VOLMRI（在T2加权图像上获取的体积）进行比较。
研究了18例患者，其中4例肿瘤边界不清（PDT）。PET衍生的体积如下：VOLSUV-40%，2.1至41.2 cm（均值[标准差]，12.3 [10.6]）；VOLSUV-Gra，2.2至28.1 cm（均值[标准差]，13.2 [8.4]）；VOLKi-Gra，2.4至17.0 cm（均值[标准差]，9.5 [4.6]）；以及VOLKi-40%，2.7至20.3 cm（均值[标准差]，12.0 [6.0]）。VOLMRI范围为2.9至18.1 cm（均值[标准差]，9.1 [3.9]）。VOLKi-Gra与VOLMRI显著相关，相关系数最高（包括PDT，R = 0.673，P = 0.002；排除PDT，R = 0.841，P < 0.001），且与VOLMRI无差异（分别包括和排除PDT时，P = 0.672或0.561）。VOLKi-Gra与VOLMRI之间的差异也最小。
使用基于梯度的方法在Ki图上勾勒出的肿瘤体积比在SUV图上和使用固定阈值方法更准确。
