Novel Reconstruction Paradigm for Multiphasic CT Imaging of Kidney Cancer

肾癌多相 CT 成像的新型重建范例

• 批准号: 9387307
• 负责人: Frederic Noo
• 金额: $ 21.55万
• 依托单位: UNIVERSITY OF UTAH
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-01 至 2019-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9387307
• 关键词: Abdomen; Algorithms; Anatomy; Appearance; Breathing; Cancer Patient; Clinical; Computer software; Computing Methodologies; Data; Data Analyses; Detection; Development; Diagnosis; Disease; Disease Progression; Dose; Evaluation; Goals; Gold; Health; Hematuria; Human; Image; Individual; Intercellular Fluid; Investigation; Joint repair; Joints; Kidney; Least-Squares Analysis; Lesion; Link; Low Dose Radiation; Medical Imaging; Methodology; Methods; Modeling; Monitor; Noise; Nuclear; Organ; Outcome; Pathology; Patients; Pattern; Pelvis; Performance; Phase; Positioning Attribute; ROC Curve; Radiation; Radiation exposure; Receiver Operating Characteristics; Renal carcinoma; Research; Research Personnel; Research Proposals; Risk; Scanning; Source; Staging; Task Performances; Time; X-Ray Computed Tomography; abdominal CT; base; cancer imaging; clinical application; clinical practice; clinically relevant; computerized data processing; contrast enhanced; design; image reconstruction; image registration; improved; innovation; novel; prototype; quantitative imaging; reconstruction; response; standard of care; success; time interval

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.

多相 CT 扫描采集以短时间间隔间隔的多个 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补充信息 诊断和疾病分期。多相 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 采集才能区分所有肾脏病变 亚型。多期 CT 的优势是显而易见的。然而，四相 CT 扫描平均有 4 个 单次 CT 扫描辐射剂量的倍。此外，这些检查通常定期进行，以 监测疾病进展，这引起了与辐射剂量相关风险的严重担忧 传授给患者。多相扫描中的 CT 图像在对比度方面各不相同 增强模式，并且由于患者呼吸而导致的器官位置也略有变化。尽管如此， 这些 CT 图像之间存在高度的空间和强度相关性。目前临床 重建方法独立重建多相 CT 检查的每个相，丢弃 相关性。所有 CT 阶段的相关图像内容是目前尚未开发的信息来源 将显着提高图像质量和剂量利用率。在此应用中，我们的目标是开发 一种新颖的图像重建范例，可在多相扫描中联合重建所有图像。在这个 范式中，每个单独阶段的图像都将受益于多阶段采集中的所有采集数据。 改进的图像质量可用于减少患者的辐射剂量，或者更有信心地 也许更频繁地跟踪病变对治疗的反应，包括标准护理和 调查性的。所提出的算法建立在基于迭代重建的最先进模型之上 方法;它利用单个图像内和多个相关图像之间的自相似性 多相扫描。客观、基于任务的图像质量 (IQ) 评估对于此项目的成功至关重要 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，并仔细评估提议的和竞争的之间的图像质量增益 开发18个月后所实现的方法。 IQ 评估包括两个部分： 噪声 减少与剂量减少和解剖准确性直接相关。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特定于任务的指标 使用模型和人类观察者的特征方法。该提案的预期结果是 适用于真实患者数据的软件原型，具有改善图像的初步临床相关证据 质量，可以换取较低的辐射剂量。剂量的目标减少是一个接近于 相数。该提案将使多相数据处理和分析发生范式转变 肾癌患者的 CT 扫描。