Discrete Frequency Infrared Spectroscopic Imaging for Breast Histopathology

用于乳腺组织病理学的离散频率红外光谱成像

基本信息

批准号：
9110717
负责人：
Rohit Bhargava
金额：
$ 43.42万
依托单位：
UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN
依托单位国家：
美国
项目类别：
财政年份：
2010
资助国家：
美国
起止时间：
2010-05-01 至 2018-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9110717
关键词：
Address Algorithms Biological Biological Assay Breast Cells Chemicals Clinical Clinical Research Clinical Trials Computational algorithm Computer software Data Data Quality Decision Making Development Diagnosis Diagnostic Disease Drug resistance Dyes Epithelial Epithelial Cells Excision Feedback Frequencies Generations Goals Gold Health Healthcare Histologic Histopathology Human Image Imaging Device Imaging technology Label Laboratories Lasers Lead Malignant Neoplasms Molecular Morphology Noise Operative Surgical Procedures Output Pathologist Pathology Patient Care Patient-Focused Outcomes Patients Pattern Performance Persons Protocols documentation Public Health Recurrence Research Research Personnel Resolution Sampling Signal Transduction Solid Source Speed Staging Staining method Stains Supervision Technology Testing Tissue imaging Tissues Training Translations analytical method anticancer research base cancer care cell transformation clinical practice cost design diagnosis standard diagnostic accuracy foot frontier imaging modality improved innovation instrument instrumentation malignant breast neoplasm molecular pathology neoplastic cell novel novel diagnostics novel strategies outcome forecast practical application prognostic protein expression quantum simulation sound spectroscopic imaging success symposium theories tumor tumor microenvironment

项目摘要

DESCRIPTION: Technologies that can help make accurate, objective and automated decisions to aid the pathologist are sorely needed in clinical practice to improve accuracy and contain costs. The major goal of this project is to provide a practical imaging instrument for clinical and research use that can be operated by any trained person in pathology laboratories. The approach is based, first, on developing novel instrumentation and analytical methods for robust discrete frequency infrared (DF-IR) spectroscopic imaging. The instrument presents a departure from the current state of the art using a design inspired by recent advances in theory, newly-developed sources and advanced control algorithms. The integration of spectral analysis algorithms makes generation of molecular pathology data facile - without any dyes, stains or human supervision. The developed instrument and algorithms is tested in a clinical setting and results that will lead to clinical trials will be obtained. Finally, the approach is geared to bettr predict breast cancer course by utilizing the entire tumor microenvironment. As opposed to current practice, which largely relies only on epithelial cells, the new approach to using the entire tumor microenvironment has the potential to transform decision-making for patients and alter the standard practice of histologic assessment in research.

描述：可以帮助做出准确，客观和自动化的决策来帮助病理学家的技术，以提高准确性并包含成本。该项目的主要目的是为临床和病理实验室中任何受过训练的人都可以操作研究用途。该方法首先是基于开发新的仪器和分析方法的鲁棒频率红外（DF-IR）光谱成像。该仪器使用最新的理论进步，新开发的来源和高级控制算法启发的设计偏离了当前的艺术状态。光谱分析算法的整合使生成分子病理学数据容易 - 没有任何染料，污渍或人类监督。在临床环境中测试了开发的仪器和算法，并将获得将导致临床试验的结果。最后，该方法旨在通过利用整个肿瘤微环境来预测乳腺癌病程。与目前仅依赖上皮细胞的当前实践相反，使用整个肿瘤微环境的新方法有可能改变患者的决策并改变研究中组织学评估的标准实践。