Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Dana-Farber Cancer Institute, Boston, MA, USA.
J R Soc Interface. 2022 Mar;19(188):20210922. doi: 10.1098/rsif.2021.0922. Epub 2022 Mar 23.
Increased intracranial pressure is the source of most critical symptoms in patients with glioma, and often the main cause of death. Clinical interventions could benefit from non-invasive estimates of the pressure distribution in the patient's parenchyma provided by computational models. However, existing glioma models do not simulate the pressure distribution and they rely on a large number of model parameters, which complicates their calibration from available patient data. Here we present a novel model for glioma growth, pressure distribution and corresponding brain deformation. The distinct feature of our approach is that the pressure is directly derived from tumour dynamics and patient-specific anatomy, providing non-invasive insights into the patient's state. The model predictions allow estimation of critical conditions such as intracranial hypertension, brain midline shift or neurological and cognitive impairments. A diffuse-domain formalism is employed to allow for efficient numerical implementation of the model in the patient-specific brain anatomy. The model is tested on synthetic and clinical cases. To facilitate clinical deployment, a high-performance computing implementation of the model has been publicly released.
颅内压升高是脑胶质瘤患者大多数危急症状的根源，也是导致患者死亡的主要原因。临床干预措施可以受益于通过计算模型提供的对患者脑实质内压力分布的无创估计。然而，现有的脑胶质瘤模型无法模拟压力分布，而且它们依赖于大量的模型参数，这使得从现有患者数据对其进行校准变得复杂。在这里，我们提出了一种新的脑胶质瘤生长、压力分布和相应脑变形的模型。我们方法的显著特点是压力是直接从肿瘤动力学和患者特定解剖结构中得出的，为患者的状态提供了无创的见解。该模型的预测可以估计颅内高血压、脑中线移位或神经和认知障碍等危急情况。采用弥散域形式主义来允许在患者特定的脑解剖结构中有效地实现模型的数值化。该模型在合成和临床病例中进行了测试。为了便于临床应用，该模型的高性能计算实现已经公开发布。
