Department of Oral and Maxillofacial Surgery, Nanjing Stomatological Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, 210000, China; Department of Oral and Maxillofacial Surgery, Affiliated Hospital of Jiangsu University, Zhenjiang, Jiangsu, 210008, China.
Department of Chemistry, Fudan University, Shanghai, 200438, China.
EBioMedicine. 2021 Aug;70:103529. doi: 10.1016/j.ebiom.2021.103529. Epub 2021 Aug 12.
Although there is consensus that the optimal safe margin is ≥ 5mm, obtaining clear margins (≥5 mm) intraoperatively seems to be the major challenge. We applied a molecular diagnostic method at the lipidomic level to determine the safe surgical resection margin of OSCC by desorption electrospray ionisation mass spectrometry imaging (DESI-MSI).
By overlaying mass spectrometry images with hematoxylin-eosin staining (H&E) from 18 recruited OSCC participants, the mass spectra of all pixels across the diagnosed tumour and continuous mucosal margin regions were extracted to serve as the training and validation datasets. A Lasso regression model was used to evaluate the test performance.
By leave-one-out validation, the Lasso model achieved 88.6% accuracy in distinguishing between tumour and normal regions. To determine the safe surgical resection distance and margin status of OSCC, a set of 14 lipid ions that gradually decreased from tumour to normal tissue was assigned higher weight coefficients in the Lasso model. The safe surgical resection distance of OSCC was measured using the developed 14 lipid ion molecular diagnostic model for clinical reference. The overall accuracy of predicting tumours, positive margins, and negative margins was 92.6%.
The spatial segmentation results based on our diagnostic model not only clearly delineated the tumour and normal tissue, but also distinguished the different status of surgical margins. Meanwhile, the safe surgical resection margin of OSCC on frozen sections can also be accurately measured using the developed diagnostic model.
This study was supported by Nanjing Municipal Key Medical Laboratory Constructional Project Funding (since 2016) and the Centre of Nanjing Clinical Medicine Tumour (since 2014).
尽管已经达成共识,最佳安全切缘≥5mm,但在术中获得清晰切缘(≥5mm)似乎是主要挑战。我们应用一种基于脂质组学的分子诊断方法,通过解吸电喷雾电离质谱成像(DESI-MSI)来确定口腔鳞状细胞癌(OSCC)的安全手术切除边界。
通过将质谱图像与 18 名招募的 OSCC 参与者的苏木精-伊红染色(H&E)叠加,从诊断肿瘤和连续黏膜边缘区域的所有像素中提取质谱,作为训练和验证数据集。使用套索回归模型评估测试性能。
通过留一法验证,该套索模型在区分肿瘤和正常区域方面的准确率达到 88.6%。为了确定 OSCC 的安全手术切除距离和边缘状态,我们在套索模型中赋予了一组从肿瘤到正常组织逐渐减少的 14 个脂质离子更高的权重系数。使用开发的 14 个脂质离子分子诊断模型测量 OSCC 的安全手术切除距离,为临床提供参考。预测肿瘤、阳性边缘和阴性边缘的总体准确率为 92.6%。
基于我们的诊断模型的空间分割结果不仅清晰地描绘了肿瘤和正常组织,还区分了手术边缘的不同状态。同时,还可以使用开发的诊断模型准确测量 OSCC 冷冻切片上的安全手术切除边界。
本研究得到南京市重点医学实验室建设项目资助(自 2016 年起)和南京市临床肿瘤医学中心资助(自 2014 年起)。