Novel Reconstruction Paradigm for Multiphasic CT Imaging of Kidney Cancer

多相CT扫描采集由短时间间隔分开的多个CT图像，以便捕获 不同的对比度增强模式。这些不同的模式提供了互补的信息， 诊断和疾病分期。多期CT扫描在腹部和骨盆检查中很常见。在 特别是，不确定的肾脏病变或血尿需要四次CT采集来区分所有肾脏病变 亚型多相CT的受益是明确的。然而，四相CT扫描平均有四个 是单次CT扫描辐射剂量的两倍此外，这些检查通常定期进行， 监测疾病进展，这在与辐射剂量相关的风险方面引起了严重关切 传授给病人。多相扫描中的CT图像在对比度方面彼此不同 增强模式，并且由于患者呼吸，在器官位置方面也略有不同。然而，尽管如此， 在这些CT图像之间存在高度的空间和强度相关性。当前临床 重建方法独立地重建多相CT检查的每个相， 相关性所有CT相位的相关图像内容目前是未开发的信息源， 将能够显著改善图像质量和剂量利用率。在这个应用程序中，我们的目标是开发 一种新颖的图像重建范例，其在多相扫描中联合重建所有图像。在这 在这种范例中，每个单独相位处的图像将受益于多相位采集中的所有采集数据。 然后，改进的图像质量可以用于减少对患者的辐射剂量，或者更自信地确定对患者的辐射剂量。 并且可能更频繁地跟踪病变对治疗的反应，包括标准护理和 调查所提出的算法建立在最先进的基于模型的迭代重建 方法;它利用自相似性在一个单一的图像和多个相关的图像之间， 多相扫描客观的、基于任务的图像质量（IQ）评估是成功的关键。 研究提案。我们将在算法开发过程中使用这种类型的评估来监控进度 和指导，并仔细评估拟议和竞争之间的图像质量增益 经过18个月的发展，IQ评估包括两个组成部分：噪声 与剂量减少直接相关的减少和解剖准确性。我们将设计病变检测 和解剖错误检测任务，并依赖于与接收器操作相关的任务特定度量 特征方法，使用模型和人类观察员。该提案的预期成果是 适用于真实的患者数据的软件原型，具有改善图像的初始临床相关证据 质量，这可以换取较低的辐射剂量。有针对性地减少剂量是一个接近于 阶段数。该提案将实现多相数据处理和分析的范式转变 肾癌患者的CT扫描。

A multiphase CT scan acquires multiple CT images separated by short time intervals in order to capture different contrast enhancement patterns. These different patterns provide complementary information for diagnosis and disease staging. Multiphase CT scans are common in abdominal and pelvis exams. In particular, indeterminate renal lesions or hematuria require four CT acquisitions to distinguish all renal lesion subtypes. The benefit of multiphase CT is unequivocal. However, a four-phase CT scan has on average four times the radiation dose of a single CT scan. Moreover, these exams are often performed periodically to monitor disease progression, which raises serious concerns in terms of risks associated with radiation dose imparted to the patient. The CT images in a multiphase scan differ from each other in terms of contrast enhancement patterns, and also slightly in terms of organ position due to patient breathing. Nevertheless, there is a high level of spatial and intensity correlation between these CT images. Current clinical reconstruction methods reconstruct each phase of a multiphase CT exam independently, discarding the correlation. The correlated image content of all CT phases is currently an untapped source of information that will enable dramatic improvements in image quality and dose utilization. In this application, we aim to develop a novel image reconstruction paradigm that jointly reconstructs all images in a multiphase scan. In this paradigm, the image at each individual phase will benefit from all acquired data in a multiphase acquisition. The improved image quality can then be used to reduce radiation dose to the patient, or to more confidently and perhaps more frequently follow the response of lesions to therapies, both standard of care and investigational. The proposed algorithm builds on state-of-the-art model based iterative reconstruction methods; it utilizes self-similarity both within a single image and among the multiple correlated images in a multiphase scan. Objective, task-based assessment of image quality (IQ) is critical to the success of this research proposal. We will use this type of assessment during algorithm development for progress monitoring and guidance, and also to carefully evaluate image quality gains between the proposed and competing methods as achieved after 18 months of development. The IQ evaluation includes two components: noise reduction which is directly linked to dose reduction, and anatomical accuracy. We will design lesion detection and anatomical error detection tasks, and rely on task-specific metrics associated with receiver operating characteristic methodology, using both model and human observers. The expected outcome of the proposal is a software prototype that is applicable to real patient data with initial clinically-relevant proof of improved image quality, which could be traded for lower radiation dose. The targeted reduction in dose is a factor close to the number of phases. The proposal will enable a paradigm shift in data processing and analysis for multiphase CT scans of kidney cancer patients.