Qu Jiangming, Su Tong, Pan Boju, Zhang Tao, Chen Xingming, Zhu Xiaoli, Chen Yu, Zhang Zhuhua, Jin Zhengyu
Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, No.1 Shuai Fu Yuan, Dong Cheng District, Beijing 100730, China.
Department of Pathology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, No.1 Shuai Fu Yuan, Dong Cheng District, Beijing 100730, China.
Cancers (Basel). 2023 Oct 15;15(20):4992. doi: 10.3390/cancers15204992.
(1) Background: This study aims to evaluate the image quality of abnormal cervical lymph nodes in head and neck cancer and the diagnostic performance of detecting extranodal extension (ENE) using free-breathing StarVIBE. (2) Methods: In this retrospective analysis, 80 consecutive head and neck cancer patients underwent StarVIBE before neck dissection at an academic center. Image quality was compared with conventional VIBE available for 28 of these patients. A total of 73 suspicious metastatic lymph nodes from 40 patients were found based on morphology and enhancement pattern on StarVIBE. Sensitivity (SN), specificity (SP), and odds ratios were calculated for each MR feature from StarVIBE to predict pathologic ENE. (3) Results: StarVIBE showed significantly superior image quality, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) for enlarged lymph nodes compared to VIBE. The MR findings of "invading adjacent planes" (SN, 0.54; SP, 1.00) and "matted nodes" (SN, 0.72; SP, 0.89) emerged as notable observations. The highest diagnostic performance was attained by combining these two features (SN, 0.93; SP, 0.89). (4) Conclusions: This study confirms that StarVIBE offers superior image quality for abnormal lymph nodes compared to VIBE, and it can accurately diagnose ENE by utilizing a composite MR criterion in head and neck cancer.
(1) 背景:本研究旨在评估头颈癌中异常颈部淋巴结的图像质量,以及使用自由呼吸StarVIBE序列检测结外侵犯(ENE)的诊断性能。(2) 方法:在这项回顾性分析中,80例连续的头颈癌患者在一家学术中心进行颈部清扫术前接受了StarVIBE序列检查。将图像质量与其中28例患者可用的传统VIBE序列进行比较。根据StarVIBE序列上的形态和强化模式,共发现40例患者的73个可疑转移性淋巴结。计算StarVIBE序列中每个MR特征预测病理ENE的敏感性(SN)、特异性(SP)和比值比。(3) 结果:与VIBE序列相比,StarVIBE序列在显示肿大淋巴结方面图像质量、信噪比(SNR)和对比噪声比(CNR)均显著更优。“侵犯相邻层面”(SN,0.54;SP,1.00)和“融合结节”(SN,0.72;SP,0.89)的MR表现成为显著观察结果。联合这两个特征可获得最高诊断性能(SN,0.93;SP,0.89)。(4) 结论:本研究证实,与VIBE序列相比,StarVIBE序列在显示异常淋巴结方面图像质量更优,并且它可以通过利用复合MR标准对头颈癌中的ENE进行准确诊断。