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Quantitative Computed Tomography Imaging of Interstitial Lung Diseases
- Source :
- Journal of Thoracic Imaging. 28:298-307
- Publication Year :
- 2013
- Publisher :
- Ovid Technologies (Wolters Kluwer Health), 2013.
-
Abstract
- High-resolution chest computed tomography (HRCT) is essential in the characterization of interstitial lung disease. The HRCT features of some diseases can be diagnostic. Longitudinal monitoring with HRCT can assess progression of interstitial lung disease; however, subtle changes in the volume and character of abnormalities can be difficult to assess. Accuracy of diagnosis can be dependent on expertise and experience of the radiologist, pathologist, or clinician. Quantitative analysis of thoracic HRCT has the potential to determine the extent of disease reproducibly, classify the types of abnormalities, and automate the diagnostic process.Novel software that utilizes histogram signatures to characterize pulmonary parenchyma was used to analyze chest HRCT data, including retrospective processing of clinical CT scans and research data from the Lung Tissue Research Consortium. Additional information including physiological, pathologic, and semiquantitative radiologist assessment was available to allow comparison of quantitative results, with visual estimates of the disease, physiological parameters, and measures of disease outcome.Quantitative analysis results were provided in regional volumetric quantities for statistical analysis and a graphical representation. These results suggest that quantitative HRCT analysis can serve as a biomarker with physiological, pathologic, and prognostic significance.It is likely that quantitative analysis of HRCT can be used in clinical practice as a means to aid in identifying a probable diagnosis, stratifying prognosis in early disease, and consistently determining progression of the disease or response to therapy. Further optimization of quantitative techniques and longitudinal analysis of well-characterized subjects would be helpful in validating these methods.
- Subjects :
- musculoskeletal diseases
Pulmonary and Respiratory Medicine
medicine.medical_specialty
Chest ct
Extent of disease
Article
medicine
Humans
Radiology, Nuclear Medicine and imaging
Medical Informatics Applications
Quantitative computed tomography
Lung
medicine.diagnostic_test
business.industry
fungi
Interstitial lung disease
food and beverages
respiratory system
medicine.disease
Computer aided detection
respiratory tract diseases
medicine.anatomical_structure
Tomography x ray computed
Radiographic Image Interpretation, Computer-Assisted
Tomography
Radiology
Lung Diseases, Interstitial
Tomography, X-Ray Computed
business
Subjects
Details
- ISSN :
- 08835993
- Volume :
- 28
- Database :
- OpenAIRE
- Journal :
- Journal of Thoracic Imaging
- Accession number :
- edsair.doi.dedup.....ccacb93ec8055747683b3d6bc2894a74
- Full Text :
- https://doi.org/10.1097/rti.0b013e3182a21969