Automated Image System for Scoring Changes in Quantitative Interstitial Lung Disease

Background

Innovation

Professor Hyun Kim and colleagues from UCLA’s Department of Radiology have developed a new, fully-automated Computer Aided Diagnosis (CAD) scoring system that provides quantitative, repeatable, and retraceable measures of interstitial lung disease (ILD).  The system provides increased sensitivity and consistency over visual scoring and can reliably estimate transitional changes in the levels of fibrotic reticulation, ground glass patterns, and normal, healthy patterns.  The system also includes a de-nosing technique for a reduction in image variation from multi-center trials, which has been a significant improvement over existing quantitative scoring. Overall, this technology combines the de-nosing technique, robust feature selection, model classification and artificial intelligence of a computer-aid diagnosis system to calculate ILD quantitative metric.

Applications

• Assess degree of interstitial lung disease
• Routine monitoring of lung function
• Monitor lung function in clinical trials

Advantages

• Increased accuracy, sensitivity and consistency over visual scoring
• Facilitating drug evaluation process with more rapid assessment, lower cost, and shortened clinical trials
• De-noising technique for multi-center trials

State Of Development

The system is implemented as computer software. This software can be run on individual medical imaging workstation or at the image acquisition device or on a reading workstation. The software could also be run on a centralized server or cluster servers. This software can also be accessed remotely (via the internet).  

Patent Status

Related Materials

• A computer-aided diagnosis system for quantitative scoring of extent of lung fibrosis in scleroderma patients. Clin Exp Rheumatol. (2010)