Hepatic entropy and uniformity: additional parameters that can potentially increase the effectiveness of contrast enhancement during abdominal CT

Quantifying tumour heterogeneity with CT

Heterogeneity is a key feature of malignancy associated with adverse tumour biology. Quantifying heterogeneity could provide a useful non-invasive imaging biomarker. Heterogeneity on computed tomography (CT) can be quantified using texture analysis which extracts spatial information from CT images (unenhanced, contrast-enhanced and derived images such as CT perfusion) that may not be perceptible to the naked eye. The main components of texture analysis can be categorized into image transformation and quantification. Image transformation filters the conventional image into its basic components (spatial, frequency, etc.) to produce derived subimages. Texture quantification techniques include structural-, model- (fractal dimensions), statistical- and frequency-based methods. The underlying tumour biology that CT texture analysis may reflect includes (but is not limited to) tumour hypoxia and angiogenesis. 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.

Assessment of tumor heterogeneity: an emerging imaging tool for clinical practice?

Background

Tumor spatial heterogeneity is an important prognostic factor, which may be reflected in medical images

Methods

Image texture analysis is an approach of quantifying heterogeneity that may not be appreciated by the naked eye. Different methods can be applied including statistical-, model-, and transform-based methods.

Results

Early evidence suggests that texture analysis has the potential to augment diagnosis and characterization as well as improve tumor staging and therapy response assessment in oncological practice.

Conclusion

This review provides an overview of the application of texture analysis with different imaging modalities, CT, MRI, and PET, to date and describes the technical challenges that have limited its widespread clinical implementation so far. With further efforts to refine its application, image texture analysis has the potential to develop into a valuable clinical tool for oncologic imaging.

Teaching Points

• Tumor spatial heterogeneity is an important prognostic factor.

• Image texture analysis is an approach of quantifying heterogeneity.

• Different methods can be applied, including statistical-, model-, and transform-based methods.

• Texture analysis could improve the diagnosis, tumor staging, and therapy response assessment.

Multiparametric PET/CT in oncology

The standardized uptake value (SUV) and other measurements of tumour uptake of fluorodeoxyglucose (FDG) on positron emission tomography (PET) can potentially be supplemented by additional imaging parameters derived either from the PET images or from the computed tomography (CT) component of integrated PET/CT examinations including tumour size, CT attenuation, texture (reflecting tumour heterogeneity) and blood flow. This article illustrates the emerging benefits of such a multiparametric approach. Example benefits include greater diagnostic accuracy in characterization of adrenal masses achieved by using both the SUV and measured CT attenuation. Tumour size combined with the SUV can potentially improve the prognostic information available from PET/CT in oesophageal and lung cancer. However, greater improvements may be realized through using CT measurements of texture instead of size. Studies in breast and lung cancer suggest that combined PET/CT measurements of glucose metabolism and blood flow provide correlates for tumour proliferation and angiogenesis, respectively. These combined measurements can be utilized to determine vascular-metabolic phenotypes, which vary with tumour type. Uncoupling of blood flow and metabolism suggests a poor prognosis for larger more advanced tumours, high-grade lesions and tumours responding poorly to treatment. Vascular-metabolic imaging also has the potential to subclassify tumour response to treatment. The additional biomarkers described can be readily incorporated in existing FDG-PET examinations thereby improving the ability of PET/CT to depict tumour biology, characterize potentially malignant lesions, and assess prognosis and therapeutic response.

Tumour heterogeneity in non-small cell lung carcinoma assessed by CT texture analysis: a potential marker of survival

PURPOSE

To establish the potential for tumour heterogeneity in non-small cell lung cancer (NSCLC) as assessed by CT texture analysis (CTTA) to provide an independent marker of survival for patients with NSCLC.

MATERIALS AND METHODS

Tumour heterogeneity was assessed by CTTA of unenhanced images of primary pulmonary lesions from 54 patients undergoing (18)F-fluorodeoxyglucose (FDG) PET-CT for staging of NSCLC. CTTA comprised image filtration to extract fine, medium and coarse features with quantification of the distribution of pixel values (uniformity) within the filtered images. Receiver operating characteristics identified thresholds for PET and CTTA parameters that were related to patient survival using Kaplan-Meier analysis.

RESULTS

The median (range) survival was 29.5 (1-38) months. 24, 10, 14 and 6 patients had tumour stages I, II, III and IV respectively. PET stage and tumour heterogeneity assessed by CTTA were significant independent predictors of survival (PET stage: Odds ratio 3.85, 95% confidence limits 0.9-8.09, P = 0.002; CTTA: Odds ratio 56.4, 95% confidence limits 4.79-666, p = 0.001). SUV was not a significantly associated with survival.

CONCLUSION

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.

KEY POINTS

Computed tomography is a routine staging procedure in non-small cell lung cancer. CT texture analysis (CTTA) can quantify heterogeneity within these lung tumours. CTTA seems to offer a novel independent predictor of survival for NSCLC. CTTA could contribute to disease risk-stratification for patients with NSCLC.

Tumour heterogeneity in oesophageal cancer assessed by CT texture analysis: preliminary evidence of an association with tumour metabolism, stage, and survival

AIM

To undertake a pilot study assessing whether tumour heterogeneity evaluated using computed tomography texture analysis (CTTA) has the potential to provide a marker of tumour aggression and prognosis in oesophageal cancer.

MATERIALS AND METHODS

In 21 patients, unenhanced CT images of the primary oesophageal lesion obtained using positron-emission tomography (PET)-CT examinations underwent CTTA. CTTA was carried out using a software algorithm that selectively filters and extracts textures at different anatomical scales between filter values 1.0 (fine detail) and 2.5 (coarse features) with quantification as entropy and uniformity (measures image heterogeneity). Texture parameters were correlated with average tumour 2-[(18)F]-fluoro-2-deoxy-d-glucose (FDG) uptake [standardized uptake values (SUV(mean) and SUV(max))] and clinical staging as determined by endoscopic ultrasound (nodal involvement) and PET-CT (distant metastases). The relationship between tumour stage, FDG uptake, and texture with survival was assessed using Kaplan-Meier analysis.

RESULTS

Tumour heterogeneity correlated with SUV(max) and SUV(mean). The closest correlations were found for SUV(mean) measured as uniformity and entropy with coarse filtration (r=-0.754, p<0.0001; and r=0.748, p=0.0001 respectively). Heterogeneity was also significantly greater in patients with clinical stage III or IV for filter values between 1.0 and 2.0 (maximum difference at filter value 1.5: entropy: p=0.027; uniformity p=0.032). The median (range) survival was 21 (4-34) months. Tumour heterogeneity assessed by CTTA (coarse uniformity) was an independent predictor of survival [odds ratio (OR)=4.45 (95% CI: 1.08, 18.37); p=0.039].

CONCLUSION

CTTA assessment of tumour heterogeneity has the potential to identify oesophageal cancers with adverse biological features and provide a prognostic indicator of survival.

Dynamic contrast-enhanced texture analysis of the liver: initial assessment in colorectal cancer

PURPOSE

To undertake an initial assessment of the potential utility of dynamic contrast-enhanced texture analysis (DCE-TA) of the liver in patients with colorectal cancer.

MATERIALS AND METHODS

TA comprised measurement of mean gray-level intensity, entropy, and uniformity with and without selective-scale filtration using a band-pass filter to highlight different spatial frequencies reflecting fine, medium, and coarse textures. An initial phantom study assessed the sensitivity of each texture qualifier to computed tomography (CT) acquisition parameters. Texture was analyzed in DCE-CT series from 27 colorectal cancer patients having apparently normal hepatic morphology (node-negative: n = 8, node-positive: n = 19). Averaged changes in hepatic texture induced by contrast material were assessed qualitatively and quantitatively by using kinetic modeling to calculate hepatic perfusion indices following fine, medium, and coarse image filtration.

RESULTS

All texture qualifiers were less sensitive to changes in CT acquisition parameters than measurement of CT attenuation. Temporal changes in hepatic texture were qualitatively different from changes in enhancement. Statistically significant differences between node-negative and node-positive patients were observed for at least 1 time period for measurements of hepatic enhancement and for all texture parameters. The differences were most statistically significant and occurred over the greatest number of time periods for fine texture quantified as mean gray-level intensity (5 time periods, minimum P value: 0.006) followed by fine texture quantified as entropy (4 time points, minimum P value: 0.006). There was no difference in hepatic perfusion indices for the 2 groups.

CONCLUSIONS

DCE-TA is a potentially useful adjunct to DCE-CT warranting further investigation.

Colorectal cancer: texture analysis of portal phase hepatic CT images as a potential marker of survival

PURPOSE

To assess the utility of texture analysis of liver computed tomographic (CT) images by determining the effect of acquisition parameters on texture and by comparing the abilities of texture analysis and hepatic perfusion CT to help predict survival for patients with colorectal cancer.

MATERIALS AND METHODS

The study comprised a phantom test and a clinical evaluation of 48 patients with colorectal cancer who had consented to retrospective analysis of hepatic perfusion CT data acquired during a research study approved by the institutional review board. Both components involved texture analysis to quantify the relative contribution of CT features between 2 and 12 pixels wide to overall image brightness and uniformity. The effect of acquisition factors on texture was assessed on CT images of a cylindric phantom filled with water obtained by using tube currents between 100 and 250 mAs and voltages between 80 and 140 kVp. Texture on apparently normal portal phase CT images of the liver and hepatic perfusion parameters were related to patient survival by using Kaplan-Meier survival analysis.

RESULTS

A texture parameter that compared the uniformity of distribution of CT image features 10 and 12 pixels wide exhibited the least variability with CT acquisition parameters (maximum coefficient of variation, 2.6%) and was the best predictor of patient survival (P < .005). There was no significant association between survival and hepatic perfusion parameters.

CONCLUSION

The study provides preliminary evidence that analysis of liver texture on portal phase CT images is potentially a superior predictor of survival for patients with colorectal cancer than CT perfusion imaging.

SUPPLEMENTAL MATERIAL

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

Texture analysis in non-contrast enhanced CT: impact of malignancy on texture in apparently disease-free areas of the liver

OBJECTIVES

To determine whether texture analysis of non-contrast enhanced computed tomography (CT) images in apparently disease-free areas of the liver is altered by the presence of extra- and intra-hepatic malignancy in colorectal cancer patients.

MATERIALS AND METHODS

Hepatic attenuation and texture were assessed from non-contrast enhanced CT in three groups of colorectal cancer patients: (A) 15 controls with no malignancy; (B) nine patients with extra-hepatic malignancy but no liver involvement; (C) eight patients with hepatic metastases. Regions of interest were manually constructed only over apparently normal areas of liver tissue excluding major blood vessels and areas of intra-hepatic fat, which may otherwise alter CT texture irrespective of the presence of malignancy. Texture was analysed on unfiltered images and following band-pass image filtration to highlight image features at different spatial frequencies (fine: 2 pixels/1.68 mm in width, medium: 6 pixels/5.04 mm and coarse: 12 pixels/10.08 mm). The relative contributions made to the image by features at two different spatial frequencies were expressed as filter ratios (fine/medium, fine/coarse and medium/coarse). Texture was quantified as mean grey-level intensity, entropy and uniformity.

RESULTS

Texture was not altered on unfiltered images whereas relative texture analysis following image filtration identified differences in fine to medium texture ratios in apparently disease-free areas of the liver in patients with hepatic metastases as compared to patients with no tumour (entropy, p=0.0257) and patients with extra-hepatic disease (uniformity, p=0.0143).

CONCLUSIONS

Relative texture analysis of unenhanced hepatic CT can reveal changes in apparently disease-free areas of the liver that have previously required more complex perfusion measurements for detection.

Colorectal cancer: imaging surveillance following resection of primary tumour

Most patients with colorectal cancer undergo treatment with curative intent and subsequently enter a surveillance programme. The primary aim of surveillance is to identify patients with disease relapse at a resectable stage. However, the identification of local recurrence and metachronous carcinoma are also important aspects of follow up. Patients under observation may be referred for imaging either because regular imaging forms part of the surveillance strategy, or because tumour relapse is suggested by the development of new symptoms or a rise in tumour markers. This paper reviews the use of new and existing imaging techniques during surveillance following resection of primary colorectal cancer. The use of imaging for this surveillance is an application of cancer imaging that is supported by evidence-based clinical guidelines. Computed tomography provides the mainstay modality on grounds of good overall diagnostic performance combined with high availability and low cost. Improvements in survival with more aggressive follow up and treatment are likely to demand more accurate imaging techniques in the future.