Swanson K R, Harpold H L P, Peacock D L, Rockne R, Pennington C, Kilbride L, Grant R, Wardlaw J M, Alvord E C
Laboratory of Neuropathology, University of Washington, Harborview Medical Center, 325-9th Avenue, Seattle, WA 98104, USA.
Clin Oncol (R Coll Radiol). 2008 May;20(4):301-8. doi: 10.1016/j.clon.2008.01.006. Epub 2008 Mar 4.
The initial aims were to use recently available observations of glioblastomas (as part of a previous study) that had been imaged twice without intervening treatment before receiving radiotherapy in order to obtain quantitative measures of glioma growth and invasion according to a new bio-mathematical model. The results were so interesting as to raise the question whether the degree of radio-sensitivity of each tumour could be estimated by comparing the model-predicted and actual durations of survival and total numbers of glioma cells after radiotherapy.
The gadolinium-enhanced T1-weighted and T2-weighted magnetic resonance imaging volumes were segmented and used to calculate the velocity of radial expansion (v) and the net rates of proliferation (rho) and invasion/dispersal (D) for each patient according to the bio-mathematical model.
The ranges of the values of v, D and rho show that glioblastomas, although clustering at the high end of rates, vary widely one from the other. The effects of X-ray therapy varied from patient to patient. About half survived as predicted without treatment, indicating radio-resistance of these tumours. The other half survived up to about twice as long as predicted without treatment and could have had a corresponding loss of glioma cells, indicating some degree of radio-sensitivity. These results approach the historical estimates that radiotherapy can double survival of the average patient with a glioblastoma.
These cases are among the first for which values of v, D and rho have been calculated for glioblastomas. The results constitute a 'proof of principle' by combining our bio-mathematical model for glioma growth and invasion with pre-treatment imaging observations to provide a new tool showing that individual glioblastomas may be identified as having been radio-resistant or radio-sensitive.
最初的目的是利用最近获得的胶质母细胞瘤观察数据（作为先前一项研究的一部分），这些胶质母细胞瘤在接受放疗前已进行了两次成像且未进行干预治疗，以便根据一种新的生物数学模型获得胶质瘤生长和侵袭的定量测量值。结果非常有趣，引发了一个问题，即是否可以通过比较放疗后模型预测的和实际的生存时间以及胶质瘤细胞总数来估计每个肿瘤的放射敏感性程度。
对钆增强的T1加权和T2加权磁共振成像体积进行分割，并根据生物数学模型计算每位患者的径向扩展速度（v）、增殖净速率（ρ）和侵袭/扩散速率（D）。
v、D和ρ值的范围表明，胶质母细胞瘤虽然聚集在速率的高端，但彼此之间差异很大。X射线治疗的效果因患者而异。大约一半患者未经治疗时存活情况如预测的那样，表明这些肿瘤具有放射抗性。另一半患者存活时间长达未经治疗时预测存活时间的两倍左右，并且胶质瘤细胞可能相应减少，表明有一定程度的放射敏感性。这些结果接近历史估计，即放疗可使胶质母细胞瘤平均患者的生存期翻倍。
这些病例是首批为胶质母细胞瘤计算v、D和ρ值的病例之一。通过将我们用于胶质瘤生长和侵袭的生物数学模型与治疗前成像观察相结合，这些结果构成了一种“原理证明”，提供了一种新工具，表明个体胶质母细胞瘤可被确定为具有放射抗性或放射敏感性。
