胶质瘤是颅内最常见的原发性恶性肿瘤,其分级对患者治疗方式的选择和预后至关重要。尽管目前组织病理学仍是其最为可靠的分级手段,但需通过有创性手术以获取组织样本,存在一定的风险。相较之下,磁共振成像（MRI）作为一种非侵入性影像诊断工具,在胶质瘤分级中发挥着不可或缺的作用。然而,传统MRI评估受限于医师个体主观性强和可重复性差的问题,一定程度上影响了准确的分级结果。近年来,影像组学技术的崭露头角为解决上述难题开辟了新视角,通过高通量提取影像数据特征捕捉并量化肿瘤的影像学表现,避免因主观因素而导致的不确定性,协助医师更准确地评估肿瘤的恶性程度。本文对近五年来MRI影像组学在胶质瘤术前分级预测方面的相关研究进行了简要综述,旨在为相关领域研究者提供有益的参考和借鉴,以推动MRI影像组学在临床实践中的应用。

Glioma is the most common primary malignant brain tumor,and its grading is crucial for treatment decisions and prognosis．Currently,histopathology remains the gold standard for grading,but it requires invasive procedures and carries inherent risks．In contrast,magnetic resonance imaging（MRI）,a non-invasive diagnostic tool,plays an indispensable role in glioma grading．However,traditional MRI assessment is hampered by interobserver subjectivity and limited repeatability,which compromise grading accuracy．In recent years,radiomics,a burgeoning field,has offered a promising solution to address these challenges．By extracting high-dimensional imaging data features,radiomics enables the quantification of tumor radiological characteristics and elimination of subjectivity-related discrepancies．This technology assists clinicians in more precisely assessing the malignancy of gliomas．This article summarizes relevant studies in the past five years on the application of MRI radiomics in preoperative glioma grading,aiming to provide valuable insights and guidance to researchers in the field and promote the clinician implementation of MRI radiomics．

目的 基于影像组学方法,探讨多层螺旋CT（MSCT）四期增强扫描单一/不同期相及不同容积感兴趣区（VOI）的选择,在术前预测原发性肝细胞癌（HCC）微血管侵犯（MVI）中的价值。方法 回顾性收集88例经手术病理证实为HCC并行术前MSCT四期增强扫描的患者,其中包括47例MVI阳性患者和41例MVI阴性患者。在MSCT增强扫描的动脉早期、动脉晚期、门静脉期及延迟期图像中手动逐层勾画肿瘤ROI,获得瘤体容积感兴趣区VOI（Vt）,然后基于计算机自动膨胀算法将Vt外扩10 mm获得瘤体及瘤周VOI（Vt+Vp）。使用Pyradiomics软件分别从Vt和Vt+Vp中提取影像组学特征,随后采用15种特征选择方法和10种分类器构建150个预测模型,并通过十折交叉检验以验证模型的效能。使用准确度、敏感度、特异度、受试者工作特性曲线下面积（AUC）评估模型的效能,并比较性能最优的前三个预测模型。结果 MSCT四期增强扫描图像中预测HCC MVI状态的影像组学模型在门静脉期的表现优于其它期相及各期相的不同组合,其中最大的AUC值在Vt和Vt+Vp两种ROI中分别为0.768和0.782。此外,基于Vt+Vp的影像组学模型对MVI的预测效能优于基于Vt的影像组学模型,基于Vt+Vp性能最优的预测模型的AUC值、准确度、敏感度和特异度分别0.782、0.728、0.745和0.705。结论 采用影像组学方法术前无创性预测HCC MVI状态首选增强扫描的门静脉期,ROI首选瘤体联合瘤周10 mm区域。

Objective To investigate the value of single or different phases of contrast-enhanced multi-slice spiral CT（MSCT）in different volumetric regions of interest（ROI）to preoperatively predict the state of microvascular invasion in primary hepatocellular carcinoma（HCC）based on radiomics methods．Methods A total of 88 patients with HCC confirmed by surgical pathology who underwent preoperative MSCT quadruple-enhanced scan were retrospectively recruited,including 47 MVI-positive patients and 41 MVI-negative patients．The ROI was manually delineated slice-by-slice in the early arterial phase,late arterial phase,portal venous phase,and equilibrium phase of enhanced MSCT images to obtain the volume of tumor VOI（Vt）,and then Vt was expanded by 10 mm through the computer expansion algorithm automatically to obtain the volume of tumor and peritumor（Vt+Vp）．Pyradiomics software was used to extract radiomic features from Vt and Vt+Vp,followed by 150 discriminant models constructed with 150 feature selection methods and 10 classifiers,and then 10-fold cross-validation was used to evaluate the performance of these models．Using accuracy,sensitivity,specificity,area under the receiver operating characteristic curve（AUC）to assess model performance．The top three predictive models with the best performance were also compared．Results The radiomics model for predicting HCC MVI status in portal venous phase among quadruple-enhanced MSCT images outperformed other phases and different combinations of phases,achieving the highest AUC values of 0.768 and 0.782 in Vt and Vt+Vp respectively．In addition,the prediction performance of the radiomics model based on Vt+Vp was superior to models based on Vt．AUC value,accuracy,sensitivity,and specificity of the model with the best performance based on Vt+Vp were 0.782,0.728,0.745 and 0.705 respectively．Conclusions Radiomics models based on the portal venous phase of contrast-enhanced MSCT and tumor combined with the 10mm peritumoral area were more recommended to be employed to preoperative non-invasively predict the state of HCC MVI．