目的：探讨高清弥散加权成像及MRI动态增强对鼻腔鼻窦横纹肌肉瘤的诊断价值。方法：回顾性分析15例鼻腔鼻窦横纹肌肉瘤患者的临床及影像学资料。对所有患者的MRI平扫、增强图像及表观扩散系数（Apparent diffusion coefficient，ADC）值进行分析；8例患者行动态增强MRI（Dynamic contrast-enhanced MRI，DCE-MRI），对时间-信号强度曲线（Time-intensity curve，TIC）及半定量参数（包括达峰时间（Tpeak）、最大强化率（ERmax）、最大率上升斜率（Slopemax）、流出率（WR））进行分析。结果：15例患者中，12例病变累及单侧鼻腔鼻窦，3例累及双侧鼻腔鼻窦；病变主体位于筛窦10例，上颌窦3例，多个鼻窦2例。肿块边界欠清，不同程度侵犯邻近结构。与脑灰质相比，T1WI呈略低信号10例，呈等信号5例；T2WI呈略高信号15例。15例患者中，7例病变信号尚均匀，增强后均匀强化；8例病变信号混杂，T1WI见条状高信号，T2WI见条状高、低信号，增强后3例呈典型的葡萄状强化、5例呈环形及条片强化。肿瘤实性部分ADC平均值为（0.59±0.08）×10-3 mm2/s。8例行DCE-MRI检查的患者中，TIC为速升缓降型6例，速升速降型2例，Tpeak为（69.1±13.3），WR为（2.2±0.5）%。结论：鼻腔鼻窦横纹肌肉瘤的ADC值为（0.59±0.08）×10-3 mm2/s，动态增强为Ⅱ、Ⅲ型曲线，提示为恶性肿瘤；结合常规MRI对病变的定性和鉴别诊断有一定的参考价值。
Abstract
Objective: To identify MR imaging features of sinonasal RMS, including high resolution diffusion weighted imaging(DWI) and dynamic contrast-enhanced(DCE) MRI. Materials and Methods: MRI and clinical data of 15 patients were analyzed retrospectively． Imaging features of conventional MR(non-enhanced and dynamic contrast-enhanced), the ADC values and DCE-MRI parameters(n=8) were analyzed. The semiquantitative parameters included Tpeak, ERmax, Slopemax and WR. Results: In the 15 cases of RMS, 12 were unilateral while the other 3 were bilateral, including 10 in the ethmoid sinus, 3 in the maxillary sinus, and 2 in the multi-paranasal sinus． The lesions were invasive, destructive or expansive. Compared with gray matter, 10 of the tumors showed hypointensity and 5 showed isointensity on T1WI. And 15 demonstrated hyperintensity on T2WI． There were multiple linear high signals on T1WI and high or low signal on T2WI within the mass in 8 of the 15 tumors. Evaluated with gadolinium-enhanced imaging, 3 patients showed clustered enhancement while 5 patients showed ring or linear enhancement. The mean ADC value was (0.59±0.08)×10-3 mm2/s. The time-intensity curve(TIC) of DCE-MRI showed rapid enhancement and slow wash out in 6 cases, rapid enhancement and rapid wash out in 2 cases. Tpeak was (69.1±13.3), and WR was (2.2±0.5)%. Conclusions: Combined with conventional imaging, high resolution diffusion-weighted imaging and dynamic contrast-enhanced MRI have the potential to improve the diagnostic accuracy of sinonasal RMS.
关键词
鼻肿瘤 /
横纹肌肉瘤 /
磁共振成像
Key words
Nose neoplasms /
Rhabdomyosarcoma /
Magnetic resonance imaging
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
参考文献
[1]薛元领，满凤媛，鲜军舫，等. 鼻腔鼻窦横纹肌肉瘤的CT诊断[J]. 中国医学影像技术，2003，19（4）：412-414.
[2]Yabuuchi H, Fukuya T, Tajima T, et al. Salivary gland tumors: diagnostic value of gadolinium-enhanced dynamic MR imaging with histopathologic correlation[J]. Radiology, 2003, 226(2): 345-354.
[3]汪晓红，耿道颖，顾雅佳，等. 动态增强MRI鉴别乳腺良恶性病变的价值[J]. 放射学实践，2005，20（8）：662-666.
[4]林岚，王纾宜，王坚. 儿童头面部胚胎性横纹肌肉瘤的临床病理特点及预后分析[J]. 中国循证儿科杂志，2008，3（5）：350-355.
[5]宋乐，杨本涛，陈光利，等. 鼻腔鼻窦横纹肌肉瘤的CT和MRI诊断[J]. 中国医学影像技术，2008，24（3）：366-369.
[6]Zhu J, Zhang J, Tang G, et al. Computed tomography and magnetic resonance imaging observations of rhabdomyosarcoma in the head and neck[J]. Oncol Lett, 2014, 8(1): 155-160.
[7]Hagiwara A, Lnoue Y, Nakayama T, et al. The “botryoid sign”: a characteristic feature of rhabdomyosareomas in the head and neck[J]. Neuroradiology, 2001, 43(4): 331-335.
[8]李晶，谢传淼，李卉，等. 儿童头颈部横纹肌肉瘤的影像表现[J]. 放射学实践，2014，29（3）：326-329.
[9]Sumi M, Ichikawa Y, Nakamura T. Diagnostic ability of apparent diffusion coefficients for lymphomas and carcinomas in the pharynx[J]. Eur Radiol, 2007, 17(10): 2631-2637.
[10]Porter DA, Heidemann RM. High resolution diffusion-weighted imaging using readout-segmented echo-planar imaging, parallel imaging and a two-dimensional navigator-based reacquisition[J]. Magn Reson Med, 2009, 62(2): 468-475.
[11]Zhao M, Liu Z, Sha Y, et al. Readout-segmented echo-planar imaging in the evaluation of sinonasal lesions: A comprehensive comparison of image quality in single-shot echo-planar imaging[J]. Magn Reson Imaging, 2016, 34(2): 166-172.
[12]王永哲，杨本涛，鲜军舫，等. MR扩散加权成像表观扩散系数鉴别鼻腔鼻窦实性肿块的价值[J]. 中华放射学杂志，2014，48（3）：207-210.
[13]高维青，陶晓峰，朱凌. 功能性磁共振成像技术及其对腮腺肿瘤的应用价值[J]. 功能与分子医学影像学：电子版，2015，4（2）：686-690.
[14]蒯新平. MR弥散加权成像及动态增强在眼眶肿块诊断中的价值[D]. 第二军医大学，2012.
