Tongue muscle function after cancer surgery using 4D MRI, DTI, and MR tagging

 描述(由申请人提供)：国家癌症研究所估计，2014年将有超过42,000人被诊断为口腔癌，超过8,000人将死于这种疾病。尽管与许多其他癌症相比，这些比率较低，但与大多数其他癌症不同，口腔癌--特别是人类乳头瘤病毒(HPV)阳性癌症--的发病率一直在上升。据估计，仅在过去十年里，口腔癌的发病率就增加了五倍之多。在通过舌癌切除术(包括舌癌在内的部分舌部的手术切除)治疗舌癌的情况下，治疗后的发病率往往很高，包括言语困难、吞咽困难和睡眠呼吸暂停。多年来，将舌癌的大小和类型与手术后舌头的运动联系起来的研究一直在进行中。这些研究大多涉及声学和语音清晰度的结果测量，开始揭示可以为临床医生开发最佳治疗方法提供信息的原则。但关于舌头运动本身作为结果的信息很少，当这一结果被报道时，它几乎只报告了来自舌面运动测量的测量结果，而不是其内部肌肉。随着技术的进步，我们现在有机会研究正常对照和患者的舌肌运动的详细模式。通过同时分析电影磁共振图像、标记磁共振图像和扩散磁共振图像的数据，我们将能够观察整个舌头的激活模式-观察和测量一种新型的功能连接-以便更好地了解患者如何补偿因舌切除而造成的肌肉损失。具体地说，我们将：1)优化体内舌肌扩散MRI成像的获取；2)使用体内标记的MRI和扩散MRI建立舌肌纤维作用线的应变测量；3)建立语音过程中舌头功能连接的模型；以及4)评估舌头切除术后语音中的舌头策略。肌肉纤维产生张力的能力在任何肌肉的功能中都是至关重要的，但由于成像限制，过去还不可能在体内研究这种关系。目前的研究将使舌头复杂的肌肉几何形状的体内同步分析成为可能，这是第一次可能的肌肉水化器。通过优化现有的方法--成像和图像分析--我们将使评估舌癌手术结果的新能力成为可能。这项将在舌癌幸存者中进行的研究将提供有关舌癌治疗对语音影响的关键信息，以便通过改变手术实践或在手术后进行特定的语音治疗来避免显著的发病率。

 DESCRIPTION (provided by applicant): The National Cancer Institute estimates that over 42,000 people will be diagnosed with oral cancer and over 8,000 will die from this disease in 2014. Although these rates are low in comparison to many other cancers, unlike most other cancers the incidence of oral cancers-especially the human papillomavirus (HPV)-positive cancers-has been increasing. By some estimates there is as much as a five-fold increase in oral cancers just over the past decade. In the case of tongue cancer treatment through glossectomy (the surgical removal of part of the tongue including the cancer), which we focus on here, there is often significant post-treatment morbidity including difficulties in speech and swallowing and sleep apnea. Research connecting the tumor size and type of glossectomy surgery with tongue movement in speech after surgery has been ongoing for a number of years. These studies, most of which involve acoustic and speech intelligibility outcome measures, are beginning to reveal principles that can inform clinicians in developing optimal treatments. But very little information has been available relating tongue motion itself as an outcome, and when this is reported it almost exclusively reports measures derived from measurement of motion of the tongue surface, not its internal muscles. With advancements in technology we now have the opportunity to study the detailed patterns of tongue muscle motions in both normal controls and patients. By simultaneously analyzing data from cine magnetic resonance images, tagged magnetic resonance images, and diffusion magnetic resonance images, we will be able to observe patterns of activation throughout the tongue-observing and measuring a new type of functional connectivity-in order to better understand how patients compensate for muscle loss due to glossectomy. Specifically, we will: 1) Optimize acquisition of diffusion MRI imaging of in vivo tongue muscles; 2) Establish strain measures in the line of action of tongue muscle fibers using in vivo tagged MRI and diffusion MRI; 3) Develop models of functional connectivity in the tongue during speech; and 4) Assess tongue strategies in post-glossectomy speech. The ability of muscle fibers to create strain is crucial in the function of any muscle, but it is has not been possible to study this relationship in vivo in the past due to imaging constraints. The present research will enable simultaneous in vivo analysis in the complex muscle geometry of the tongue, a muscular hydrostat, possible for the first time. Through optimization of existing methods-both imaging and image analysis-we will enable a novel capability for the assessment of surgical outcomes in tongue cancer surgery. The study to be carried out on a spectrum of tongue cancer survivors will provide key information about the impact of tongue cancer treatment on speech, in order that significant morbidity might be avoided by modifying surgical practice or by engaging in specific speech therapies after surgery.