Yang Zhen, Zan Yunlong, Zheng Xiujuan, Hai Wangxi, Chen Kewei, Huang Qiu, Xu Yuhong, Peng Jinliang
School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
Department Automation, School of Electrical and Information, Sichuan University, Chengdu, Sichuan, China.
PLoS One. 2015 Sep 30;10(9):e0139089. doi: 10.1371/journal.pone.0139089. eCollection 2015.
[18F]fluoro-2-deoxy-D-glucose positron emission tomography (FDG-PET) has been widely used in oncologic procedures such as tumor diagnosis and staging. However, false-positive rates have been high, unacceptable and mainly caused by inflammatory lesions. Misinterpretations take place especially when non-subcutaneous inflammations appear at the tumor site, for instance in the lung. The aim of the current study is to evaluate the use of dynamic PET imaging procedure to differentiate in situ and subcutaneous non-small cell lung carcinoma (NSCLC) from inflammation, and estimate the kinetics of inflammations in various locations.
Dynamic FDG-PET was performed on 33 female mice inoculated with tumor and/or inflammation subcutaneously or inside the lung. Standardized Uptake Values (SUVs) from static imaging (SUVmax) as well as values of influx rate constant (Ki) of compartmental modeling from dynamic imaging were obtained. Static and kinetic data from different lesions (tumor and inflammations) or different locations (subcutaneous, in situ and spontaneous group) were compared.
Values of SUVmax showed significant difference in subcutaneous tumor and inflammation (p<0.01), and in inflammations from different locations (p<0.005). However, SUVmax showed no statistical difference between in situ tumor and inflammation (p = 1.0) and among tumors from different locations (subcutaneous and in situ, p = 0.91). Values of Ki calculated from compartmental modeling showed significant difference between tumor and inflammation both subcutaneously (p<0.005) and orthotopically (p<0.01). Ki showed also location specific values for inflammations (subcutaneous, in situ and spontaneous, p<0.015). However, Ki of tumors from different locations (subcutaneous and in situ) showed no significant difference (p = 0.46).
In contrast to static PET based SUVmax, both subcutaneous and in situ inflammations and malignancies can be differentiated via dynamic FDG-PET based Ki. Moreover, Values of influx rate constant Ki from compartmental modeling can offer an assessment for inflammations at different locations of the body, which also implies further validation is necessary before the replacement of in situ inflammation with its subcutaneous counterpart in animal experiments.
[18F]氟代-2-脱氧-D-葡萄糖正电子发射断层扫描(FDG-PET)已广泛应用于肿瘤诊断和分期等肿瘤学程序。然而,假阳性率一直很高,令人难以接受,且主要由炎症性病变引起。特别是当非皮下炎症出现在肿瘤部位,如肺部时,就会出现误诊。本研究的目的是评估动态PET成像程序在区分原位和皮下非小细胞肺癌(NSCLC)与炎症方面的应用,并估计不同部位炎症的动力学。
对33只雌性小鼠进行动态FDG-PET检查,这些小鼠皮下或肺内接种了肿瘤和/或炎症。获取静态成像的标准化摄取值(SUVs)(SUVmax)以及动态成像的房室模型的流入速率常数(Ki)值。比较不同病变(肿瘤和炎症)或不同部位(皮下、原位和自发组)的静态和动力学数据。
SUVmax值在皮下肿瘤和炎症之间(p<0.01)以及不同部位的炎症之间(p<0.005)显示出显著差异。然而,SUVmax在原位肿瘤和炎症之间(p = 1.0)以及不同部位的肿瘤(皮下和原位,p = 0.91)之间没有统计学差异。房室模型计算的Ki值在皮下(p<0.005)和原位(p<0.01)的肿瘤和炎症之间均显示出显著差异。Ki在炎症方面也显示出部位特异性值(皮下、原位和自发,p<0.015)。然而,不同部位(皮下和原位)肿瘤的Ki没有显著差异(p = 0.46)。
与基于静态PET的SUVmax不同,皮下和原位炎症及恶性肿瘤均可通过基于动态FDG-PET的Ki进行区分。此外,房室模型的流入速率常数Ki值可为身体不同部位的炎症提供评估,这也意味着在动物实验中用皮下炎症替代原位炎症之前,还需要进一步验证。