A PET/CT scanner for guiding treatment of head and neck cancer

摘要/摘要 头颈癌(HNC)是最具挑战性的癌症之一，难以有效治疗(五年 一些HNC的存活率低至25%)；复发率从8%到43%不等。数量 由于目前与HPV相关的HNCs几近流行，新病例正在上升。不幸的是，大多数治疗方法 由于该区域的敏感结构(脊髓、 唾液腺、腮腺、食道、颈动脉和甲状腺)。HNC是通过外科手术治疗的 切除、放射治疗或多种方法的组合。治疗的选择是基于对 肿瘤的位置、大小、与骨骼的接近程度、对周围组织的浸润量和扩散到区域 用先进的成像方法进行的淋巴转移。也许这些方法中最有希望的是 基于代谢的成像，特别是PET，通常使用FDG。非最优空间分辨率和固定值 然而，全身扫描仪的几何形状限制了PET通过抑制能力来实现其在这一角色中的承诺 为了准确检测淋巴结中的小肿块，并在量化原发肿瘤的大小和性质方面 肿瘤。因此，对改进的PET/CT扫描仪技术以加强治疗计划的需求尚未得到满足 HNC的。为了抓住这一机会，我们建议创建和测试一种成本较低、灵活的几何图形， 高分辨率PET/CT系统(接近临床前PET扫描仪的空间分辨率)，称为 HNPET/CT，专门为头部和颈部区域的成像而设计。它将由一对新奇的 大面积、浸没冷却的PET探测器和安装在旋转上的锥束CT(CBCT)扫描仪 其几何形状可以根据患者的大小和解剖进行扫描的机架。利用这一点 HNPET/CT的高分辨率图像，一种同时利用CBCT和PET图像的图像分割方法 将被开发和测试。我们计划探索HNPET/CT在加强治疗方面的潜在应用 计划(手术和放射治疗)。这项评估将首先使用拟人化的幻影和 然后在有限的人体试验中。除了新颖的探测器设计和可调节的几何形状外，HNPET/CT还将 为尚未被终端用户广泛采用的HNC的治疗计划引入新功能 临床上的。它可以增强当前的规划技术(例如，减少治疗边际规模)，使 有效地应用先进的方法(例如，剂量涂抹)，也许会启发 新的、更有效的个性化治疗策略需要高分辨率、多模式成像。这个 该系统的较低成本保证了将尖端的、图像引导的治疗引入到未得到充分服务的人 由小诊所或私人诊所治疗的地区的人口往往负担不起这种技术。这个项目 将由加入放射科的多学科学术产业伙伴关系执行， 西弗吉尼亚大学和Xoran Technologies，LLC的头颈外科和放射肿瘤学。

ABSTRACT/SUMMARY Head and neck carcinomas (HNC) are some of the most challenging cancers to effectively treat (five-year survival rates for some HNCs are as low as 25%); recurrence rates range from 8% to 43%. The number of new cases is rising due to the current, near epidemic of HPV-associated HNCs. Unfortunately, most treatments are associated with significant morbidity due to damage of sensitive structures in the region (spinal cord, salivary glands, parotid gland, esophagus, carotid arteries and thyroid gland). HNCs are treated with surgical excision, radiation therapy, or a combination of methods. Selection of therapy is based upon assessment of tumor location, size, proximity to bone, amount of infiltration into surrounding tissues and spread to regional lymph nodes performed with advanced imaging methods. Perhaps the most promising of these methods is metabolic-based imaging, specifically PET, often utilizing FDG. The non-optimal spatial resolution and fixed geometry of whole body scanners, however, limits PET in fulfilling its promise in this role by inhibiting the ability to accurately detect small tumor masses in lymph nodes, and in quantifying the size and nature of the primary tumor. Thus, there is an unmet need for improved PET/CT scanner technology to enhance treatment planning of HNCs. To address this opportunity, we propose the creation and testing of a lower-cost, flexible geometry, high-resolution PET/CT system (approaching the spatial resolution of pre-clinical PET scanners), called HNPET/CT, designed specifically for the imaging of the head and neck region. It will consist of a novel pair of large area, immersion-cooled, PET detectors and a cone beam CT (CBCT) scanner mounted on a rotating gantry whose geometry can be tailored to patient size and anatomy to be scanned. To capitalize on HNPET/CT’s high-resolution images, an image segmentation method that utilizes both CBCT and PET images will be developed and tested. We plan to explore the potential utility of HNPET/CT for enhancing therapy planning (surgical and radiation). This assessment will first be performed with anthropomorphic phantoms and then in a limited human trial. In addition to the novel detector design and adjustable geometry, HNPET/CT will introduce a new capability to the treatment planning of HNCs not yet broadly employed by end users in the clinical. It could enhance current planning techniques (reduce treatment margin size, for example), enable the effective application of advanced methods (dose painting, for example), and perhaps inspire development of new, more effective personalized treatment strategies that require high resolution, multi-modality imaging. The lower cost of the system promises the introduction of cutting-edge, image-guided treatments to under-served populations in areas treated by small or private clinics that often cannot afford such technology. This project will be performed by a multi-disciplinary academic industrial partnership joining the Departments of Radiology, Head and Neck Surgery and Radiation Oncology at West Virginia University, and Xoran Technologies, LLC.