Colorectal Cancer: Texture Analysis of Portal Phase Hepatic CT Images as a Potential Marker of Survival

Miles, Kenneth A.; Ganeshan, Balaji; Griffiths, Meryl; Young, Rupert; Chatwin, Christopher R.

doi:10.1148/radiol.2502071879

Cited by 237 publications

(189 citation statements)

References 25 publications

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“…2B-D)-using entropy (a measure of irregularity). Texture values were further normalized (12) to the coarsest scale to give a series of relative texture values (i.e., relative contribution to overall texture made by texture components of different scales), as further described in Supplementary Data.…”

Section: Texture Analysismentioning

confidence: 99%

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Tumor Heterogeneity and Permeability as Measured on the CT Component of PET/CT Predict Survival in Patients with Non–Small Cell Lung Cancer

Win

Miles

Janes

et al. 2013

Clinical Cancer Research

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190

152

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Purpose: We prospectively examined the role of tumor textural heterogeneity on positron emission tomography/computed tomography (PET/CT) in predicting survival compared with other clinical and imaging parameters in patients with non-small cell lung cancer (NSCLC).Experimental Design: The feasibility study consisted of 56 assessed consecutive patients with NSCLC (32 males, 24 females; mean age 67 AE 9.7 years) who underwent combined fluorodeoxyglucose (FDG) PET/ CT. The validation study population consisted of 66 prospectively recruited consecutive consenting patients with NSCLC (37 males, 29 females; mean age, 67.5 AE 7.8 years) who successfully underwent combined FDG PET/CT-dynamic contrast-enhanced (DCE) CT. Images were used to derive tumoral PET/CT textural heterogeneity, DCE CT permeability, and FDG uptake (SUV max ). The mean follow-up periods were 22.6 AE 13.3 months and 28.5AE 13.2 months for the feasibility and validation studies, respectively. Optimum threshold was determined for clinical stage and each of the above biomarkers (where available) from the feasibility study population. Kaplan-Meier analysis was used to assess the ability of the biomarkers to predict survival in the validation study. Cox regression determined survival factor independence.Results: Univariate analysis revealed that tumor CT-derived heterogeneity (P < 0.001), PET-derived heterogeneity (P ¼ 0.003), CT-derived permeability (P ¼ 0.002), and stage (P < 0Á001) were all significant survival predictors. The thresholds used in this study were derived from a previously conducted feasibility study. Tumor SUV max did not predict survival. Using multivariable analysis, tumor CT textural heterogeneity (P ¼ 0.021), stage (P ¼ 0.001), and permeability (P < 0.001) were independent survival predictors. These predictors were independent of patient treatment.Conclusions: Tumor stage and CT-derived textural heterogeneity were the best predictors of survival in NSCLC. The use of CT-derived textural heterogeneity should assist the management of many patients with NSCLC.

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Section: Texture Analysismentioning

confidence: 99%

“…A potentially easier approach is to evaluate tumor heterogeneity using imaging to assess how grainy or coarse a tumor seems to be. PET and CT have both been used to derive tumor textural information, and the appearance of the tumors has been shown to relate to patient outcome in esophageal and colorectal cancer (11)(12)(13).…”

Section: Introductionmentioning

confidence: 99%

Tumor Heterogeneity and Permeability as Measured on the CT Component of PET/CT Predict Survival in Patients with Non–Small Cell Lung Cancer

Win

Miles

Janes

et al. 2013

Clinical Cancer Research

Self Cite

190

152

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“…In [4] the effect of acquisition parameters, such as tube currents and voltages (10 different combinations), on texture was assessed on CT images of a cylindric phantom filled with water. Eight different texture parameters were analyzed.…”

Section: Related Workmentioning

confidence: 99%

Effect of Slice Thickness on Texture-Based Classification of Liver Dynamic CT Scans

Duda

Krȩtowski

Bézy-Wendling

2013

Computer Information Systems and Industrial Management

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Abstract. This paper assesses the impact of slice thickness on texture parameters. Experiments are performed on liver dynamic CT scans, with two slice thicknesses. Three acquisition moments are considered: without contrast, in arterial and in portal phase. In total, 155 texture parameters, extracted with 9 methods, are tested. Classification of normal and cirrhotic liver is performed using a boosting algorithm. Experiments reveal that slice thickness does not considerably influence the stability of the parameters. They also enable to assess the rate of parameter dependency on slice thickness. Finally, they show that applying different slice thicknesses for training and testing the CAD system requires slice thickness-independent parameters.

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“…The ability of 18 F-FDG-PET to detect cancer is based on elevated aerobic glycolysis in the malignant tissue in comparison with the normal tissue-also known as the Warburg 12 effect. Although primarily reporting on tumour cell activity, 18 F-FDG-PET has been shown to also inform on tumour heterogeneity. A retrospective study using 18 F-FDG-PET/CT to monitor response among lesions in patients with bone-dominant metastatic breast cancer treated with systemic therapies reported that lesions showed heterogeneous metabolic response amongst responding and nonresponding bony and non-bony lesions.…”

Section: Various Imaging Modalities and Methods That Can Help To Map mentioning

confidence: 99%

“…Although primarily reporting on tumour cell activity, 18 F-FDG-PET has been shown to also inform on tumour heterogeneity. A retrospective study using 18 F-FDG-PET/CT to monitor response among lesions in patients with bone-dominant metastatic breast cancer treated with systemic therapies reported that lesions showed heterogeneous metabolic response amongst responding and nonresponding bony and non-bony lesions. 13 Novel utilization of 18 F-FDG-PET/CT in recent years, such as texture analysis on CT imaging, has been shown to reflect tumour heterogeneity and associated prognosis.…”

Section: Various Imaging Modalities and Methods That Can Help To Map mentioning

confidence: 99%

The use of molecular imaging combined with genomic techniques to understand the heterogeneity in cancer metastasis

Chowdhury¹,

Ganeshan²,

Irshad³

et al. 2014

BJR|case reports

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Colorectal Cancer: Texture Analysis of Portal Phase Hepatic CT Images as a Potential Marker of Survival

Abstract: http://radiology.rsnajnls.org/cgi/content/full/2502071879/DC1.

Cited by 237 publications

References 25 publications

Tumor Heterogeneity and Permeability as Measured on the CT Component of PET/CT Predict Survival in Patients with Non–Small Cell Lung Cancer

Tumor Heterogeneity and Permeability as Measured on the CT Component of PET/CT Predict Survival in Patients with Non–Small Cell Lung Cancer

Effect of Slice Thickness on Texture-Based Classification of Liver Dynamic CT Scans

The use of molecular imaging combined with genomic techniques to understand the heterogeneity in cancer metastasis

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