Qin Danlei, Yang Guoqiang, Jing Hui, Tan Yan, Zhao Bin, Zhang Hui
College of Medical Imaging, Shanxi Medical University, Taiyuan 030001, China.
Shanxi Province Key Laboratory of Oral Diseases Prevention and New Materials, Shanxi Medical University School, Hospital of Stomatology, Taiyuan 030001, China.
Cancers (Basel). 2022 Aug 3;14(15):3771. doi: 10.3390/cancers14153771.
As the most common neuro-epithelial tumors of the central nervous system in adults, gliomas are highly malignant and easy to recurrence, with a dismal prognosis. Imaging studies are indispensable for tracking tumor progression (TP) or treatment-related changes (TRCs). During follow-up, distinguishing TRCs from TP in treated patients with gliomas remains challenging as both share similar clinical symptoms and morphological imaging characteristics (with new and/or increasing enhancing mass lesions) and fulfill criteria for progression. Thus, the early identification of TP and TRCs is of great significance for determining the prognosis and treatment. Histopathological biopsy is currently the gold standard for TP and TRC diagnosis. However, the invasive nature of this technique limits its clinical application. Advanced imaging methods (e.g., diffusion magnetic resonance imaging (MRI), perfusion MRI, magnetic resonance spectroscopy (MRS), positron emission tomography (PET), amide proton transfer (APT) and artificial intelligence (AI)) provide a non-invasive and feasible technical means for identifying of TP and TRCs at an early stage, which have recently become research hotspots. This paper reviews the current research on using the abovementioned advanced imaging methods to identify TP and TRCs of gliomas. First, the review focuses on the pathological changes of the two entities to establish a theoretical basis for imaging identification. Then, it elaborates on the application of different imaging techniques and AI in identifying the two entities. Finally, the current challenges and future prospects of these techniques and methods are discussed.
作为成人中枢神经系统最常见的神经上皮性肿瘤，胶质瘤具有高度恶性且易于复发的特点，预后较差。影像学检查对于追踪肿瘤进展（TP）或治疗相关变化（TRC）不可或缺。在随访过程中，对于接受治疗的胶质瘤患者，区分TRC和TP仍然具有挑战性，因为二者具有相似的临床症状和形态学影像特征（出现新的和/或增大的强化肿块病变），且均符合进展标准。因此，早期识别TP和TRC对于判断预后和确定治疗方案具有重要意义。组织病理学活检是目前诊断TP和TRC的金标准。然而，该技术的侵入性限制了其临床应用。先进的影像学方法（如扩散磁共振成像（MRI）、灌注MRI、磁共振波谱（MRS）、正电子发射断层扫描（PET）、酰胺质子转移（APT）和人工智能（AI））为早期识别TP和TRC提供了一种非侵入性且可行的技术手段，这些方法近来已成为研究热点。本文综述了目前利用上述先进影像学方法识别胶质瘤TP和TRC的研究情况。首先，综述聚焦于这两种情况的病理变化，为影像识别建立理论基础。然后，详细阐述不同影像技术及AI在识别这两种情况中的应用。最后，讨论了这些技术和方法当前面临的挑战及未来前景。
