Department of Radiology, Center for Biomedical Imaging (CBI), Center for Advanced Imaging Innovation and Research (CAI2R), New York University School of Medicine, 660 First Avenue, New York, NY, 10016, USA.
Department of Otolaryngology-Head and Neck Surgery, New York University School of Medicine, New York, NY, USA.
Sci Rep. 2020 Nov 27;10(1):20764. doi: 10.1038/s41598-020-77740-5.
In this study, we investigate the feasibility of using dynamic contrast enhanced magnetic resonance imaging (DCE-MRI), diffusion weighted imaging (DWI), and dynamic positron emission tomography (PET) for detection of metastatic lymph nodes in head and neck squamous cell carcinoma (HNSCC) cases. Twenty HNSCC patients scheduled for lymph node dissection underwent DCE-MRI, dynamic PET, and DWI using a PET-MR scanner within one week prior to their planned surgery. During surgery, resected nodes were labeled to identify their nodal levels and sent for routine clinical pathology evaluation. Quantitative parameters of metastatic and normal nodes were calculated from DCE-MRI (v, v, PS, F, K), DWI (ADC) and PET (K, K, k, k) to assess if an individual or a combination of parameters can classify normal and metastatic lymph nodes accurately. There were 38 normal and 11 metastatic nodes covered by all three imaging methods and confirmed by pathology. 34% of all normal nodes had volumes greater than or equal to the smallest metastatic node while 4 normal nodes had SUV > 4.5. Among the MRI parameters, the median v, F, PS, and K values of the metastatic lymph nodes were significantly lower (p = <0.05) than those of normal nodes. v and ADC did not show any statistical significance. For the dynamic PET parameters, the metastatic nodes had significantly higher k (p value = 8.8 × 10) and K (p value = 5.3 × 10) than normal nodes. K and k did not show any statistically significant difference. K had the best separation with accuracy = 0.96 (sensitivity = 1, specificity = 0.95) using a cutoff of K = 5.3 × 10 mL/cm/min, while k and volume had accuracy of 0.94 (sensitivity = 0.82, specificity = 0.97) and 0.90 (sensitivity = 0.64, specificity = 0.97) respectively. 100% accuracy can be achieved using a multivariate logistic regression model of MRI parameters after thresholding the data with K < 5.3 × 10 mL/cm/min. The results of this preliminary study suggest that quantitative MRI may provide additional value in distinguishing metastatic nodes, particularly among small nodes, when used together with FDG-PET.
在这项研究中，我们研究了使用动态对比增强磁共振成像（DCE-MRI）、扩散加权成像（DWI）和正电子发射断层扫描（PET）检测头颈部鳞状细胞癌（HNSCC）患者转移淋巴结的可行性。20 例 HNSCC 患者在计划手术前一周内使用 PET-MR 扫描仪进行 DCE-MRI、动态 PET 和 DWI 检查。在手术过程中，切除的淋巴结被标记以识别其淋巴结水平，并送常规临床病理评估。从 DCE-MRI（v、v、PS、F、K）、DWI（ADC）和 PET（K、K、k、k）中计算转移和正常淋巴结的定量参数，以评估单个或多个参数是否可以准确分类正常和转移淋巴结。所有三种成像方法均覆盖了 38 个正常淋巴结和 11 个转移性淋巴结，并通过病理证实。所有正常淋巴结中有 34%的体积大于或等于最小的转移性淋巴结，而 4 个正常淋巴结的 SUV 值大于 4.5。在 MRI 参数中，转移性淋巴结的中位 v、F、PS 和 K 值明显低于正常淋巴结（p 值均小于 0.05）。v 和 ADC 没有显示出任何统计学意义。对于动态 PET 参数，转移性淋巴结的 k 值（p 值=8.8×10）和 K 值（p 值=5.3×10）明显高于正常淋巴结。K 和 k 没有显示出任何统计学差异。K 的最佳分离精度为 0.96（灵敏度=1，特异性=0.95），K 的截断值为 K=5.3×10 mL/cm/min，而 k 和体积的精度分别为 0.94（灵敏度=0.82，特异性=0.97）和 0.90（灵敏度=0.64，特异性=0.97）。使用经过 K < 5.3×10 mL/cm/min 数据阈值处理后的 MRI 参数的多元逻辑回归模型，可实现 100%的准确率。这项初步研究的结果表明，当与 FDG-PET 联合使用时，定量 MRI 可能为区分转移性淋巴结，特别是小淋巴结提供额外的价值。
