Journal ArticleDOI
Assessment of tumor heterogeneity by CT texture analysis : Can the largest cross-sectional area be used as an alternative to whole tumor analysis?
TLDR
Whole tumor analysis appears more representative of tumor heterogeneity, and Kaplan-Meier analysis demonstrated better of E and U for whole tumor analysis for 5-year overall survival.About:
This article is published in European Journal of Radiology.The article was published on 2013-02-01. It has received 298 citations till now. The article focuses on the topics: Primary tumor.read more
Citations
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Journal ArticleDOI
Applications and limitations of radiomics
TL;DR: This technical review will review radiomic application areas and technical issues, as well as proper practices for the designs of radiomic studies.
Journal ArticleDOI
CT Texture Analysis: Definitions, Applications, Biologic Correlates, and Challenges.
TL;DR: Although CTTA CT texture analysis seems to be a promising imaging biomarker, there is marked variability in methods, parameters reported, and strength of associations with biologic correlates.
Journal ArticleDOI
Measuring Computed Tomography Scanner Variability of Radiomics Features.
Dennis Stephen Mackin,X Fave,Lifei Zhang,David Fried,Jinzhong Yang,Brian E. Taylor,Edgardo Rodriguez-Rivera,Cristina Dodge,Aaron Kyle Jones,Laurence E. Court +9 more
TL;DR: The variability in the values of radiomics features calculated on CT images from different CT scanners can be comparable to the variability in these features found in CT images of NSCLC tumors.
Journal ArticleDOI
Reproducibility of radiomics for deciphering tumor phenotype with imaging.
TL;DR: Assessment of the reproducibility of a comprehensive, commonly-used set of radiomic features using a unique, same-day repeat computed tomography data set from lung cancer patients suggests that radiomic Features are reproducible over a wide range of imaging settings.
Journal ArticleDOI
Quantifying tumour heterogeneity with CT.
Balaji Ganeshan,Kenneth A. Miles +1 more
TL;DR: Emerging studies show that CT texture analysis has the potential to be a useful adjunct in clinical oncologic imaging, providing important information about tumour characterization, prognosis and treatment prediction and response.
References
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Journal ArticleDOI
Metastasis: recent discoveries and novel treatment strategies
Suzanne A. Eccles,Danny R. Welch +1 more
TL;DR: This work focuses on recent findings regarding intrinsic and extrinsic molecular mechanisms controlling metastasis that determine how, when, and where cancers metastasise, and their implications for patient management in the 21st century.
Journal ArticleDOI
Tumour heterogeneity in non-small cell lung carcinoma assessed by CT texture analysis: a potential marker of survival.
TL;DR: Assessment of tumour heterogeneity by CTTA of non-contrast enhanced images has the potential for to provide a novel, independent predictor of survival for patients with NSCLC.
Journal ArticleDOI
Assessment of primary colorectal cancer heterogeneity by using whole-tumor texture analysis: contrast-enhanced CT texture as a biomarker of 5-year survival.
TL;DR: In this paper, fine-texture features (lower entropy, kurtosis, and standard deviation; higher uniformity and skewness) were associated with a poorer 5-year overall survival rate in patients with colorectal cancer.
Journal ArticleDOI
Assessment of Response to Tyrosine Kinase Inhibitors in Metastatic Renal Cell Cancer: CT Texture as a Predictive Biomarker
TL;DR: CT texture analysis reflecting tumor heterogeneity is an independent factor associated with time to progression and has potential as a predictive imaging biomarker of response of metastatic renal cancer to targeted therapy.
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