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Understanding Uncertainties in Radiomics Studies

了解放射组学研究中的不确定性

基本信息

批准号：
9442742
负责人：
Laurence E Court
金额：
$ 13.92万
依托单位：
UNIVERSITY OF TX MD ANDERSON CAN CTR
依托单位国家：
美国
项目类别：
财政年份：
2017
资助国家：
美国
起止时间：
2017-03-01 至 2020-02-29
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9442742
关键词：
Affect Age Bayesian Modeling Cancer Patient Chest Clinic Clinical Clinical Trials Data Data Set Dose Future Goals Guidelines Heterogeneity Image Immunotherapy Individual Institution Knowledge Manufacturer Name Measurement Measures Modality Modeling Non-Small-Cell Lung Carcinoma Operative Surgical Procedures Outcome Patient risk Patients Positron-Emission Tomography Prognostic Factor Prospective Studies Protocols documentation Public Health Radiation Radiation therapy Radiology Specialty Research Research Personnel Risk Risk stratification Scanning Source Standardization Survival Rate Texture Tumor Volume Uncertainty Validation Variant Work X-Ray Computed Tomography alternative treatment base cancer imaging chemoradiation chemotherapy clinical practice cost high risk improved individual patient outcome prediction patient response patient stratification predictive modeling prospective quantitative imaging radiomics routine imaging tool treatment response tumor

项目摘要

Project Summary Radiomics is the use of tumor texture, as seen in pre-treatment computed tomography, positron emission tomography or other images, to understand important information about individual tumors, such as response to treatment. We have demonstrated that it is possible to use pre-treatment images to categorize patients as low-risk (good survival) and high-risk (poor survival). Additionally, we have some very exciting data that shows that radiomics approaches can predict whether increasing the radiotherapy dose will improve or reduce the individual patient's overall survival. However, before these radiomics model scan be implemented clinically, validation in independent patient datasets is essential. One big hurdle to this is the fact that patients are not all imaged on a single CT scanner (or PET scanner, etc.), but on a wide range of different scanners (different manufacturers, models, etc.), and the calculated value of tumor texture can be affected by which scanner is used to image patient. This means that before we can properly validate radiomics models, and apply them to real-world situations (meaning outside of the well-controlled, single-institution trial setting), it is important to understand the magnitude of these variabilities, and the impact they have on radiomics models. This knowledge will help direct future research to minimize their impact on the creation, independent validation, and future use of radiomics models. This work is relevant to many different treatment types, including chemo- radiotherapy, immunotherapy, etc.

项目摘要放射组学是利用肿瘤纹理，如治疗前计算机断层扫描，正电子发射断层扫描或其他图像，以了解有关个体肿瘤的重要信息，例如对治疗反应。我们已经证明，可以使用治疗前的图像进行分类患者分为低风险（良好的生存）和高风险（生存不良）。此外，我们有一些非常令人兴奋的数据表明，放射组学方法可以预测是否增加放射治疗剂量，将改善或降低个体患者的总体生存率。然而，在这些放射组学为了在临床上实现模型扫描，在独立的患者数据集中进行验证是必要的。一个大这方面的障碍是患者并非都在单个CT扫描仪（或PET扫描仪等）上成像，但是在大范围的不同扫描仪（不同的制造商、型号等）上，和所计算的肿瘤纹理的值可受用于对患者进行成像的扫描仪的影响。这意味着在我们能够正确验证放射组学模型并将其应用于现实世界的情况之前（即在控制良好的单机构试验环境之外），重要的是要了解以及它们对放射组学模型的影响。这些知识将有助于指导未来的研究，以尽量减少其对创建，独立验证和未来使用的影响，放射组学模型这项工作与许多不同的治疗类型有关，包括化疗，放射治疗、免疫治疗等。

项目成果

期刊论文数量（5）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Effect of tube current on computed tomography radiomic features.

DOI：
10.1038/s41598-018-20713-6
发表时间：
2018-02-05
期刊：
Scientific reports
影响因子：
4.6
作者：
Mackin D;Ger R;Dodge C;Fave X;Chi PC;Zhang L;Yang J;Bache S;Dodge C;Jones AK;Court L
通讯作者：
Court L

Comprehensive Investigation on Controlling for CT Imaging Variabilities in Radiomics Studies.

DOI：
10.1038/s41598-018-31509-z
发表时间：
2018-08-29
期刊：
Scientific reports
影响因子：
4.6
作者：
Ger RB;Zhou S;Chi PM;Lee HJ;Layman RR;Jones AK;Goff DL;Fuller CD;Howell RM;Li H;Stafford RJ;Court LE;Mackin DS
通讯作者：
Mackin DS

Practical guidelines for handling head and neck computed tomography artifacts for quantitative image analysis.

DOI：
10.1016/j.compmedimag.2018.09.002
发表时间：
2018-11
期刊：
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
影响因子：
0
作者：
Ger RB;Craft DF;Mackin DS;Zhou S;Layman RR;Jones AK;Elhalawani H;Fuller CD;Howell RM;Li H;Stafford RJ;Court LE
通讯作者：
Court LE