Longitudinal, computer assisted analysis in IPF

IPF 的纵向计算机辅助分析

• 批准号: 8117529
• 负责人: KEVIN R FLAHERTY
• 金额: $ 38.44万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-08-01 至 2014-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8117529
• 关键词: Acetylcysteine; Agreement; Ancillary Study; Award; Azathioprine; Cessation of life; Clinical Trials; Computer Assisted; Data; Data Analyses; Data Collection; Databases; Diagnosis; Disease; Enrollment; Etiology; Fibrosis; Future; Glass; Hamman-Rich syndrome; High Resolution Computed Tomography; Honeycomb Pattern; Lung; Manuscripts; Measurable; Measures; Methodology; Methods; Outcome Measure; Parents; Patients; Pattern; Physicians; Physiology; Placebos; Play; Prednisone; Preparation; Protocols documentation; Quality of life; Radiology Specialty; Randomized; Research; Research Personnel; Resources; Respiratory physiology; Risk; Role; Scanning; Structure of parenchyma of lung; Surrogate Endpoint; System; Testing; Texture; Therapeutic Agents; Time; TimeLine; Training; Vital capacity; Work; abstracting; arm; base; computerized; cost; disability; double-blind placebo controlled trial; longitudinal analysis; mortality; novel; novel therapeutics; outcome forecast; prospective; pulmonary function; radiologist; response

DESCRIPTION (provided by applicant): Idiopathic pulmonary fibrosis (IPF), the most common idiopathic interstitial pneumonia, is characterized by progressive fibrosis leading to increased disability and death. There is no cure for IPF. Mortality is the most important and easily definable endpoint for clinical trials of novel therapeutic agents. Unfortunately the size, duration, and cost of mortality-powered trials are prohibitive. This fact has led investigators to actively pursue identification of easily-measurable surrogate endpoints that predict future mortality. We demonstrated that six and 12 month decline in forced vital capacity (FVC) is associated with an increased risk of subsequent mortality. Unfortunately decline in physiology is unable to correctly predict mortality in all patients as many patients die acutely prior to demonstrating a decline in FVC while others can survive for extended periods of time despite large losses of lung function. These data highlight the need for novel surrogate endpoints that can be used to efficiently evaluate therapeutic agents for patients with IPF. High resolution computed tomography (HRCT) plays a pivotal role in the diagnosis of IPF. Baseline qualitative and semi- quantitative scoring of HRCT features consistently predicts long-term prognosis; longitudinal change has been studied less consistently. Difficulties in utilizing semi-quantitative HRCT scoring systems include physician time, inter-rater disagreement, and the rather large changes required to impact semi-quantitative scores. The Adaptive Multiple Feature Method (AMFM) is a computerized texture-based method for characterizing lung HRCT features. The overall hypothesis of this application is that the computer aided AMFM can be trained to recognize 3D features of IPF (honeycomb pattern, ground glass opacity). Furthermore, quantitative scoring by the AMFM will have better correlation with longitudinal change in forced vital capacity (FVC) & mortality compared to semi-quantitative methodology. This study will utilize cases from the Lung Tissue Research Consortium and the IPF network (IPFnet) to obtain a diverse group of patients with IPF for training the AMFM. Longitudinal aims will utilize the IPFnet's multi-center, randomized, double-blind placebo controlled trial of prednisone + azathioprine + N-acetylcysteine or N-acetylcysteine alone versus placebo in IPF patients (PANTHER study). PANTHER will enroll 130 patients, followed for 60 weeks, into each treatment arm beginning March, 2008. This application will provide a mechanism for obtaining longitudinal HRCT scans which are not part of the PANTHER protocol. This application will take advantage of the IPFnet to develop a HRCT database with baseline and longitudinal data. Through this award we will 1) test if computer aided analysis can recognize and quantify HRCT features of IPF 2) compare the agreement of semi- quantitative (radiologist) and quantitative (AMFM) measures of baseline and longitudinal changes in HRCT features 3) evaluate if longitudinal changes in HRCT can function as surrogate endpoints in clinical trials through correlations with changes in pulmonary function, quality of life, and mortality. Statement of Relevance: Idiopathic pulmonary fibrosis is an incurable disease of unknown etiology characterized by progressive fibrosis of the lung parenchyma leading to increased disability and eventual death. The study of novel agents to impact this disease is critical to access for potential impact on quantity and quality of life. Unfortunately the size, duration, and cost of mortality-powered trials are prohibitive. This study will evaluate if computer aided analysis of longitudinal changes in high resolution computed tomography scans correlates with changes in physiology, quality of life, and survival in patients with IPF. If true, changes in high resolution computed tomography could serve as a non-invasive surrogate endpoint in the study of novel agents to treat this devastating disease. (End of Abstract)

描述（由申请人提供）：

项目成果

The INPULSIS enigma: exacerbations in idiopathic pulmonary fibrosis.

INPULSIS之谜：特发性肺纤维化的恶化。

• DOI: 10.1136/thoraxjnl-2014-206598
• 发表时间: 2015
• 期刊: Thorax
• 影响因子: 10
• 作者: Suissa,Samy;Ernst,Pierre
• 通讯作者: Ernst,Pierre