我们提出了一种基于磁共振酰胺质子转移（APT）模态数据的胶质瘤中异柠檬酸脱氢酶（IDH）基因分型的双感知深度学习框架，以协助无创诊断胶质瘤。我们收集了118例胶质瘤的脑部多模态磁共振成像（MRI）数据，包括68例野生型和50例突变型。在所有病例中完成了脑部胶质瘤的感兴趣区域（ROI）勾画。APT模态成像不需要对比剂，其在肿瘤上的信号强度与肿瘤的恶性程度呈正相关，而野生型IDH的信号强度高于突变型IDH。对于APT模态，肿瘤成像和派生区域形态上有所变化，边缘轮廓特征不如其他模态明显。基于这些特征，我们提出了双感知框架，引入了多感知框架以挖掘多尺度特征，边缘感知模块则用于挖掘边缘特征以进行自动基因型识别。这两种感知机制的引入有效提高了模型对胶质瘤IDH基因型的识别率。每个模态数据的准确度和AUC也得到了提高，其中APT模态表现最佳，预测的准确度达到了83.1%，AUC为0.822，表明其对于胶质瘤IDH基因型识别具有优势和有效性。基于APT模态图像特征构建的所提出的深度学习算法模型对于胶质瘤IDH基因型分型和识别任务是有效的，并且有可能替代常用的T1CE模态，避免对比剂注射，实现无创IDH基因型分型。

To propose a Dual-Aware deep learning framework for genotyping of isocitrate dehydrogenase (IDH) in gliomas based on magnetic resonance amide proton transfer (APT) modality data as a means to assist non-invasive diagnosis of gliomas.We collected multimodal magnetic resonance imaging (MRI) imaging data of the brain from 118 cases of gliomas, including 68 wild-type and 50 mutant type cases. The delineation of the ROI of brain glioma was completed in all the cases. APT modality imaging does not require contrast agents, and its signal intensity on tumors is positively correlated with tumor malignancy, and the signal intensity on wild-type IDH is higher than that on mutant IDH. For APT modalities, tumor imaging and derived areas are morphologically variable and lack prominent edge contour characteristics compared with other modalities. Based on these characteristics, we propose the Dual-Aware framework, which introduces the Multi-Aware framework to mine multi-scale features, and the Edge Aware module mines the edge features for automatic genotype identification.The introduction of two types of Aware mechanisms effectively improved the identification rate of the model for glioma IDH genotyping. The accuracy and AUC for each modality data were enhanced, and the best performance was achieved on the APT modality with a prediction accuracy of 83.1% and an AUC of 0.822, suggesting its advantages and effectiveness for identifying glioma IDH genotypes.The proposed deep learning algorithm model constructed based on the image characteristics of the APT modality is effective for glioma IDH genotyping and identification task and may potentially replace the commonly used T1CE modality to avoid contrast agent injection and achieve non- invasive IDH genotyping.