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Evaluation of Liver Fibrosis Using Texture Analysis on Combined-Contrast-Enhanced Magnetic Resonance Images at 3.0T
- Source :
- BioMed Research International, Vol 2015 (2015), Yokoo, T; Wolfson, T; Iwaisako, K; Peterson, MR; Mani, H; Goodman, Z; et al.(2015). Evaluation of Liver Fibrosis Using Texture Analysis on Combined-Contrast-Enhanced Magnetic Resonance Images at 3.0T. BioMed Research International, 2015. doi: 10.1155/2015/387653. UC San Diego: Retrieved from: http://www.escholarship.org/uc/item/3jd716d3, BioMed Research International
- Publication Year :
- 2015
- Publisher :
- Hindawi Publishing Corporation, 2015.
-
Abstract
- Purpose. To noninvasively assess liver fibrosis using combined-contrast-enhanced (CCE) magnetic resonance imaging (MRI) and texture analysis.Materials and Methods. In this IRB-approved, HIPAA-compliant prospective study, 46 adults with newly diagnosed HCV infection and recent liver biopsy underwent CCE liver MRI following intravenous administration of superparamagnetic iron oxides (ferumoxides) and gadolinium DTPA (gadopentetate dimeglumine). The image texture of the liver was quantified in regions-of-interest by calculating 165 texture features. Liver biopsy specimens were stained with Masson trichrome and assessed qualitatively (METAVIR fibrosis score) and quantitatively (% collagen stained area). UsingL1regularization path algorithm, two texture-based multivariate linear models were constructed, one for quantitative and the other for quantitative histology prediction. The prediction performance of each model was assessed using receiver operating characteristics (ROC) and correlation analyses.Results. The texture-based predicted fibrosis score significantly correlated with qualitative (r=0.698,P<0.001) and quantitative (r=0.757,P<0.001) histology. The prediction model for qualitative histology had 0.814–0.976 areas under the curve (AUC), 0.659–1.000 sensitivity, 0.778–0.930 specificity, and 0.674–0.935 accuracy, depending on the binary classification threshold. The prediction model for quantitative histology had 0.742–0.950 AUC, 0.688–1.000 sensitivity, 0.679–0.857 specificity, and 0.696–0.848 accuracy, depending on the binary classification threshold.Conclusion. CCE MRI and texture analysis may permit noninvasive assessment of liver fibrosis.
- Subjects :
- Liver Cirrhosis
Male
METAVIR Fibrosis Score
Technology
medicine.medical_specialty
Article Subject
Image Processing
Liver fibrosis
Chronic Liver Disease and Cirrhosis
Contrast Media
lcsh:Medicine
General Biochemistry, Genetics and Molecular Biology
030218 nuclear medicine & medical imaging
Masson's trichrome stain
03 medical and health sciences
Computer-Assisted
0302 clinical medicine
Image texture
Information and Computing Sciences
Image Processing, Computer-Assisted
Humans
Medicine
General Immunology and Microbiology
medicine.diagnostic_test
Receiver operating characteristic
business.industry
Liver Disease
lcsh:R
Histology
Magnetic resonance imaging
General Medicine
Middle Aged
Biological Sciences
Magnetic Resonance Imaging
Good Health and Well Being
ROC Curve
Liver biopsy
Biomedical Imaging
Female
030211 gastroenterology & hepatology
Radiology
Digestive Diseases
business
Research Article
Subjects
Details
- Language :
- English
- ISSN :
- 23146141
- Volume :
- 2015
- Database :
- OpenAIRE
- Journal :
- BioMed Research International
- Accession number :
- edsair.doi.dedup.....489f192a944750739156e93422c07ed6