Baxan Nicoleta, Perryman Richard, Chatziathanasiadou Maria V, Syed Nelofer
John Fulcher Neuro-Oncology Laboratory, Department of Brain Sciences, Faculty of Medicine, Imperial College London, London W12 0NN, UK.
Biological Imaging Centre, Hammersmith Campus, Imperial College London, London W12 0NN, UK.
Cancers (Basel). 2025 Apr 8;17(8):1258. doi: 10.3390/cancers17081258.
Glioblastoma (GB) is a particularly malignant brain tumour which carries a poor prognosis and presents limited treatment options. MRI is standard practice for differential diagnosis at initial presentation of GB and can assist in both treatment planning and response assessment. MRI radiomics allows for discerning GB features of clinical importance that are not evident by visual analysis, augmenting the morphological and functional tumour characterisation beyond traditional imaging techniques. Given that radiotherapy is part of the standard of care for GB patients, establishing a platform for phenotyping radiation treatment responses using non-invasive methods is of high relevance.
In this study, we modelled the responses to ionising radiation across four orthotopic mouse models of GB using diffusion and perfusion radiomics. We have identified the optimal set of radiomic features that reflect tumour cellularity, microvascularity, and blood flow changes brought about by radiation treatment in these murine orthotopic models of GB, and directly compared them with endpoint histopathological analysis.
We showed that the selected radiomic features can quantify textural information and pixel interrelationships of tumour response to radiation therapy, revealing subtle image patterns that may reflect intra-tumoural spatial heterogeneity. When compared to GB patients, similarities in selected radiomic features were noted between orthotopic murine tumours and non-enhancing central tumour areas in patients, along with several discrepancies in tumour cellularity and vascularization, denoted by distinct grey level intensities and nonuniformity metrics.
As the field evolves, radiomic profiling of GB may enhance the evaluation of targeted therapeutic strategies, accelerate the development of new therapies, and act as a potential virtual biopsy tool.
胶质母细胞瘤（GB）是一种特别恶性的脑肿瘤，预后较差，治疗选择有限。磁共振成像（MRI）是GB初次就诊时进行鉴别诊断的标准方法，可辅助治疗计划制定和疗效评估。MRI放射组学能够识别具有临床重要性的GB特征，这些特征通过视觉分析并不明显，从而超越传统成像技术增强肿瘤的形态学和功能特征描述。鉴于放射治疗是GB患者标准治疗的一部分，建立一个使用非侵入性方法对放射治疗反应进行表型分析的平台具有高度相关性。
在本研究中，我们使用扩散和灌注放射组学对四种GB原位小鼠模型的电离辐射反应进行建模。我们确定了一组最佳的放射组学特征，这些特征反映了在这些GB小鼠原位模型中放射治疗引起的肿瘤细胞密度、微血管形成和血流变化，并将它们与终点组织病理学分析直接进行比较。
我们表明，所选的放射组学特征可以量化肿瘤对放射治疗反应的纹理信息和像素间关系，揭示可能反映肿瘤内空间异质性的细微图像模式。与GB患者相比，原位小鼠肿瘤与患者非强化中央肿瘤区域在所选放射组学特征上存在相似性，同时在肿瘤细胞密度和血管形成方面存在一些差异，表现为不同的灰度强度和不均匀性指标。
随着该领域的发展，GB的放射组学分析可能会加强对靶向治疗策略的评估，加速新疗法的开发，并作为一种潜在的虚拟活检工具。
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