Imaging Pearls ❯ 3D and Workflow ❯ Texture Analysis
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- “CT texture analysis (CTTA) is a method of quantifying lesion heterogeneity based on distribution of pixel intensities within a region of interest. This study investigates the ability of CTTA to distinguish different hypervascular liver lesions, and seeks to develop a predictive model utilizing CTTA parameters to distinguish different lesions.”
Classification of hypervascular liver lesions using CT texture analysis:
Generation of a predictive model on the basis of
quantitative spatial frequency measurements
Raman SP, Schroeder J, Huang P, Fishman EK
Radiology (in revision) - “The random forest model successfully distinguished the three lesion types and normal liver, correctly categorizing adenomas in 91.2% of cases, FNHs in 94.4% of cases, and HCCs in 98.6% of cases, with an overall error rate of 4.2%. Logistic regression was utilized to create models distinguishing normal liver from the three lesions, and malignant (HCC) from benign lesions using a small number of the texture parameters.”
Classification of hypervascular liver lesions using CT texture analysis:
Generation of a predictive model on the basis of
quantitative spatial frequency measurements
Raman SP, Schroeder J, Huang P, Fishman EK
Radiology (in revision) - “Texture analysis provides quantitative measures of heterogeneity from the distribution of pixel intensities at different spatial frequencies within a region of interest. While this technique has previously been used to primarily predict tumor prognosis and patient outcomes, CTTA may prove valuable in lesion discrimination and characterization. In this study, incorporating only a patient’s age, gender, and selected texture parameters generated from a single ROI, a random forest model was able to correctly categorize adenomas in 91.2% of cases, FNHs in 94.4% of cases, and HCCs in 98.6% of cases.”
Classification of hypervascular liver lesions using CT texture analysis:
Generation of a predictive model on the basis of
quantitative spatial frequency measurements
Raman SP, Schroeder J, Huang P, Fishman EK
Radiology (in revision) - “ CTTA may prove valuable in lesion discrimination and characterization, and is able to successfully categorize three common hypervascular lesions based on texture parameters.”
Classification of hypervascular liver lesions using CT texture analysis:
Generation of a predictive model on the basis of
quantitative spatial frequency measurements
Raman SP, Schroeder J, Huang P, Fishman EK
Radiology (in revision)
- “ Tumor angiogenesis is essential for cancer growth and provides an attractive target for oncologic therapies. CT perfusion is an emerging imaging tool that provides both qualitative and quantitative information information regarding tumor angiogenesis.”
CT Perfusion in Oncologic Imaging: A Useful Tool-
Garcia-Figueiras R et al
AJR 2013; 200:8-19 - “ Fine texture features are associated with poorer 5 year overall survival rate in patients with primary colorectal cancer.”
Assessment of Primary Colorectal Cancer Heterogeneity by Using Whole Tumor Texture Analysis: Contrast-enhanced CT Texture as a Biomarker of 5 Year Survival
Ng F et al.
Radiology 2013; 266:177-184 - “ The addition of texture analysis to staging contrast-enhanced CT may improve prognostication in patients with primary colorectal cancer.”
Assessment of Primary Colorectal Cancer Heterogeneity by Using Whole Tumor Texture Analysis: Contrast-enhanced CT Texture as a Biomarker of 5 Year Survival
Ng F et al.
Radiology 2013; 266:177-184 - “ Cox regression analysis with stage as a dependent covariate showed texture features were an independent predictor of 5-year overall survival rate.”
Assessment of Primary Colorectal Cancer Heterogeneity by Using Whole Tumor Texture Analysis: Contrast-enhanced CT Texture as a Biomarker of 5 Year Survival
Ng F et al.
Radiology 2013; 266:177-184 - “ In summary in our study, fine texture features (lower entropy, kurtosis, and standard deviation of pixel distribution: higher uniformity and skewness) were associated with a poorer 5-year overall survival rate in patients with colorectal cancer. With the shift from adjuvant to neoadjuvant chemotherapy for colorectal cancer and the ease of introducing such post processing tools into the clinical workflow, texture analysis shows promise as a clinical prognostic tool.”
Assessment of Primary Colorectal Cancer Heterogeneity by Using Whole Tumor Texture Analysis: Contrast-enhanced CT Texture as a Biomarker of 5 Year Survival
Ng F et al.
Radiology 2013; 266:177-184 - “ In summary in our study, fine texture features (lower entropy, kurtosis, and standard deviation of pixel distribution: higher uniformity and skewness) were associated with a poorer 5-year overall survival rate in patients with colorectal cancer.”
Assessment of Primary Colorectal Cancer Heterogeneity by Using Whole Tumor Texture Analysis: Contrast-enhanced CT Texture as a Biomarker of 5 Year Survival
Ng F et al.
Radiology 2013; 266:177-184 - “ With the shify from adjuvant to neoadjuvant chemotherapy for colorectal cancer and the ease of introducing such post processing tools into the clinical workflow, texture analysis shows promise as a clinical prognostic tool.”
Assessment of Primary Colorectal Cancer Heterogeneity by Using Whole Tumor Texture Analysis: Contrast-enhanced CT Texture as a Biomarker of 5 Year Survival
Ng F et al.
Radiology 2013; 266:177-184