Stensjøen Anne Line, Solheim Ole, Kvistad Kjell Arne, Håberg Asta K, Salvesen Øyvind, Berntsen Erik Magnus
Department of Circulation and Medical Imaging, Faculty of Medicine, Norwegian University of Science and Technology, Trondheim, Norway (A.L.S, E.M.B.); Department of Neurosurgery, St. Olavs University Hospital, Trondheim, Norway (O.S.); National Competence Centre for Ultrasound and Image Guided Therapy, St. Olavs University Hospital, Trondheim, Norway (O.S.); Department of Neuroscience, Faculty of Medicine, Norwegian University of Science and Technology, Trondheim, Norway (O.S, A.K.H.); Department of Radiology, St. Olavs University Hospital, Trondheim, Norway (K.A.K, A.K.H., E.M.B.); Department of Cancer Research and Molecular Medicine, Faculty of Medicine, Norwegian University of Science and Technology, Trondheim, Norway (Ø.S.).
Neuro Oncol. 2015 Oct;17(10):1402-11. doi: 10.1093/neuonc/nov029. Epub 2015 Mar 10.
Glioblastomas are primary malignant brain tumors with a dismal prognosis. Knowledge of growth rates and underlying growth dynamics is useful for understanding basic tumor biology, developing realistic tumor models, and planning treatment logistics.
By using repeated pretreatment contrast-enhanced T1-weighted MRI scans from 106 patients (aged 26-83 years), we studied the growth dynamics of untreated glioblastomas in vivo. Growth rates were calculated as specific growth rates and equivalent volume doubling times. The fit of different possible growth models was assessed using maximum likelihood estimations.
There were large variations in growth rates between patients. The median specific growth rate of the tumors was 1.4% per day, and the equivalent volume doubling time was 49.6 days. Exploring 3 different tumor growth models showed similar statistical fit for a Gompertzian growth model and a linear radial growth model and worse fit for an exponential growth model. However, large tumors had significantly lower growth rates than smaller tumors, supporting the assumption that glioblastomas reach a plateau phase and thus exhibit Gompertzian growth.
Based on the fast growth rate of glioblastoma shown in this study, it is evident that poor treatment logistics will influence tumor size before surgery and can cause significant regrowth before adjuvant treatment. Since there is a known association between tumor volume, extent of surgical resection, and response to adjuvant therapy, it is likely that waiting times play a role in patient outcomes.
胶质母细胞瘤是原发性恶性脑肿瘤，预后不佳。了解其生长速率及潜在的生长动力学对于理解肿瘤基本生物学特性、建立逼真的肿瘤模型以及规划治疗方案很有帮助。
我们利用106例患者（年龄26 - 83岁）治疗前重复的对比增强T1加权磁共振成像扫描，研究了未经治疗的胶质母细胞瘤在体内的生长动力学。生长速率以特定生长速率和等效体积倍增时间计算。使用最大似然估计评估不同可能生长模型的拟合情况。
患者之间的生长速率差异很大。肿瘤的中位特定生长速率为每天1.4%，等效体积倍增时间为49.6天。探索三种不同的肿瘤生长模型发现，Gompertzian生长模型和线性径向生长模型的统计拟合相似，指数生长模型的拟合较差。然而，大肿瘤的生长速率明显低于小肿瘤，这支持了胶质母细胞瘤达到平台期并因此呈现Gompertzian生长的假设。
基于本研究中显示的胶质母细胞瘤快速生长速率，显然不良的治疗规划会在手术前影响肿瘤大小，并可能在辅助治疗前导致显著的肿瘤再生长。由于肿瘤体积、手术切除范围与辅助治疗反应之间存在已知关联，等待时间可能对患者预后有影响。
