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

 描述（由申请人提供）：美国国家癌症研究所估计，2014年将有超过42，000人被诊断患有口腔癌，超过8，000人将死于这种疾病。虽然这些比率与许多其他癌症相比较低，但与大多数其他癌症不同，口腔癌的发病率-特别是人乳头瘤病毒（HPV）阳性癌症-一直在增加。据估计，仅在过去十年中，口腔癌的发病率就增加了五倍。在通过舌切除术（手术切除舌头的一部分，包括癌症）治疗舌癌的情况下，我们在这里关注，通常有显着的治疗后发病率，包括言语和吞咽困难和睡眠呼吸暂停。将肿瘤大小和舌切除术的类型与术后语言中的舌头运动联系起来的研究已经进行了许多年。这些研究，其中大部分涉及声学和语言清晰度结果的措施，开始揭示原则，可以告知临床医生在开发最佳治疗。但是，很少有关于舌运动本身作为结果的信息，并且当报道这一点时，它几乎只报道了来自舌表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组和患者舌肌运动的详细模式。通过同时分析来自电影磁共振图像、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舌切除术造成的肌肉损失。具体而言，我们将：1）优化体内舌肌的扩散MRI成像的采集; 2）使用体内标记的MRI和扩散MRI建立舌肌纤维的作用线中的应变测量; 3）开发言语期间舌中的功能连接的模型;以及4）评估舌切除术后言语中的舌策略。肌纤维产生应变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，过去无法在体内研究这种关系。目前的研究将使同时在体内分析复杂的肌肉几何形状的舌头，肌肉的液压，可能是第一次。通过优化现有方法（成像和图像分析），我们将为舌癌手术的手术结果评估提供新的能力。对舌癌幸存者进行的研究将提供关于舌癌治疗对语言影响的关键信息，以便通过修改手术实践或在手术后进行特定的语言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.