Journal article
Accuracy of radiomics for differentiating diffuse liver diseases on non-contrast CT
International journal for computer assisted radiology and surgery, Vol.15(10), pp.1727-1736
10/01/2020
DOI: 10.1007/s11548-020-02212-0
PMID: 32592069
Abstract
Radiomics help move cross-sectional imaging into the domain of quantitative imaging to assess the lesions, their stoma as well as in their temporal monitoring. We applied and assessed the accuracy of radiomics for differentiating healthy liver from diffuse liver diseases (cirrhosis, steatosis, amiodarone deposition, and iron overload) on non-contrast abdomen CT images in an institutional-reviewed board-approved, retrospective study.
Our study included 300 adult patients (mean age 63 ± 16 years; 171 men, 129 women) who underwent non-contrast abdomen CT and had either a healthy liver (n = 100 patients) or an evidence of diffuse liver disease (n = 200). The diffuse liver diseases included steatosis (n = 50), cirrhosis (n = 50), hyperdense liver due to amiodarone deposition (n = 50), or iron overload (n = 50). We manually segmented the liver in one section at the level of the porta hepatis (all 300 patients) and then over the entire liver volume (50 patients). Radiomics were estimated for the liver, and statistical comparison was performed with multiple logistic regression and random forest classifier.
With random forest classifier, the AUC for radiomics ranged between 0.72 (iron overload vs. healthy liver) and 0.98 (hepatic steatosis vs. healthy liver) for differentiating diffuse liver disease from the healthy liver. Combined root mean square and gray-level co-occurrence matrix had the highest AUC (AUC:0.99, p < 0.01) for differentiating healthy liver from steatosis. Radiomics were more accurate for differentiating healthy liver from amiodarone (AUC:0.93) than from iron overload (AUC:0.79).
Radiomics enable differentiation of healthy liver from hepatic steatosis, cirrhosis, amiodarone deposition, and iron overload from a single section of non-contrast abdominal CT. The high accuracy of radiomics coupled with rapid segmentation of the region of interest, radiomics estimation, and statistical analyses within the same prototype makes a compelling case for bringing radiomics to clinical use for improving reporting in evaluation of healthy liver and diffuse liver diseases.
Details
- Title: Subtitle
- Accuracy of radiomics for differentiating diffuse liver diseases on non-contrast CT
- Creators
- Fatemeh Homayounieh - Massachusetts General HospitalSanjay Saini - Massachusetts General HospitalLeila Mostafavi - Massachusetts General HospitalRuhani Doda Khera - Harvard Medical SchoolMichael Sühling - Siemens HealthcareBernhard Schmidt - Siemens HealthcareRamandeep Singh - Massachusetts General HospitalThomas Flohr - Siemens HealthcareMannudeep K Kalra - Massachusetts General Hospital
- Resource Type
- Journal article
- Publication Details
- International journal for computer assisted radiology and surgery, Vol.15(10), pp.1727-1736
- DOI
- 10.1007/s11548-020-02212-0
- PMID
- 32592069
- ISSN
- 1861-6410
- eISSN
- 1861-6429
- Language
- English
- Date published
- 10/01/2020
- Academic Unit
- Radiology
- Record Identifier
- 9984697621602771
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