Biostatistics, Data Analysis and Computation (BDAC Core)

生物统计学、数据分析和计算（BDAC 核心）

• 批准号: 8310104
• 负责人: Eugene Demidenko
• 金额: $ 7.7万
• 依托单位: DARTMOUTH COLLEGE
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/8310104
• 关键词: Algorithms; Animal Experiments; Animals; Biometry; CCNE1 gene; Cancer Center; Cells; Clinic; Color; Computer Simulation; Data; Data Analyses; Environment; Evaluation; Fever; Funding; Gray unit of radiation dose; Heating; Image; Image Analysis; Induced Hyperthermia; Injection of therapeutic agent; Magnetism; Measurement; Methods; Modeling; Nanotechnology; Outcome Assessment; Particle Size; Play; Process; Production; Property; Role; Services; Survival Analysis; Techniques; Temperature; Testing; Time; Tissues; Toxic effect; Translations; Treatment outcome; Tumor Volume; Uncertainty; absorption; base; chemotherapy; design; hyperthermia treatment; in vivo; magnetic field; models and simulation; nanoparticle; nanoscale; nanotherapy; performance tests; pre-clinical; research study; response; statistics; treatment effect; tumor

The Biostatistics, Data Analysis, and Computation (BDAC) Core will provide the following services to the projects of the Dartmouth CCNE: (1) technological and preclinical data analysis of magnetic NanoPartide (mNP) characterization measurements, such as size, heating evaluation, biodistribufion, etc., using traditional numeric values data as well as innovafive statistical image analyses, (2) statistical analysis of mNP-induced hyperthermia treatment outcomes including toxicity, tumor volume, and survival analysis, (S) modeling and computer simulafion of mNP interacfion with fissue and cells in vivo under an alternating magnefic field (AMF) and predicfion ofthe induced temperature rise in tumors. Model-based stafisfical techniques will be used for mNP characterization and evaluation. Unlike method driven algorithms, the model-based approach allows the assessment ofthe uncertainty of methods (e.g. through the standard error) and therefore enables statistical significance testing (Projects 1, 3, Nanoparticle Core). The majority of the mNP characterizafion data, to be derived in the DCCNE will come in the form of images. Methods of Mulfivariate ANalysis Of VAriance (MANOVA) will be used for modeling and statisfical comparison of gray scale and color images. To comply with the normal/Gaussian assumption and to eliminate the differences in images illuminafion and contrast, the logit transformafion will be used (log of the image level intensity with respect to the background). Projects 1, 2, 3, NDPC & TPB cores. The BDAC Core will evaluate the efficacy ofthe mNP treatment of tumors in the DCCNE Projects through the stafistical analysis of tumor regrowth data and survival analysis. A particular emphasis will be given to the statistical significance assessment of the synergy of the treatments, such as mNP hyperthermia and chemotherapy (Projects 1, 2 & 4). Modeling and computer simulation of scattering and absorption fields from mNPs will play an important role in choosing the biologically justified conditions for animal experiments, such as the strength of the AMF, injection concentration, magnetic field exposure time, particle size, etc. The numerical assessment of the mNP-induced hyperthermia will precede animal experiments through estimation ofthe specific absorption rate (SAR) inside the tumor and by solving of the bioheat equafion on the nanometer scale (Projects 1, 3, and Nanoparticle Core).

生物统计、数据分析和计算(BDAC)核心将为达特茅斯CCNE的项目提供下列服务：(1)利用传统的数值数据和创新的五种统计图像分析方法，对磁性纳米粒子(MNP)的表征测量，如大小、加热评估、生物分布等进行技术和临床前数据分析，(2)对磁性纳米粒子与肿瘤的毒性、肿瘤体积和存活分析等治疗结果进行统计分析，(S)对交变磁场下磁性纳米粒子与肿瘤组织和体内细胞的相互作用进行建模和计算机模拟，并预测肿瘤诱导的温度升高。 将使用基于模型的统计技术来描述和评价mNP。与方法驱动的算法不同，基于模型的方法允许评估方法的不确定度(例如，通过标准误差)，因此能够进行统计意义测试(项目1、3，纳米颗粒核心)。 将在DCCNE中得出的大多数mNP特征数据将以图像的形式出现。 将使用多变量方差分析(MANOVA)方法进行建模和统计 灰度图像和彩色图像的比较。遵守正态/高斯假设，并 消除图像照度和对比度的差异，将使用Logit变换(图像级别强度相对于背景的对数)。项目1、2、3、NDPC和TPB核心。 BDAC核心将通过对肿瘤再生数据的统计学分析和生存分析来评估DCCNE项目中mNP治疗肿瘤的疗效。将特别强调对mNP热疗和化疗等治疗协同作用的统计意义评估(项目1、2和4)。 对mNPs的散射场和吸收场的建模和计算机模拟将在为动物实验选择生物学上合理的条件方面发挥重要作用，如AMF的强度、注入浓度、磁场暴露时间、颗粒大小等。mNP诱导的热疗的数值评估将先于动物实验，通过估计肿瘤内的比吸收率(SAR)和求解纳米尺度的生物热方程(项目1、3和纳米颗粒核心)。