Can quantitative CT texture analysis be used to differentiate subtypes of renal cell carcinoma?

AIM: To investigate whether computed tomography (CT) texture analysis (TA) can be used to differentiate non-clear-cell renal cell carcinoma (non-ccRCC) from clear-cell RCC (ccRCC) and classify non-ccRCC subtypes. MATERIALS AND METHODS: One hundred ccRCC and 27 non-ccRCC (12 papillary and 15 chromophobe) were analysed. Texture parameters quantified from multiphasic CT images were compared for the objectives. Receiver operating characteristic (ROC) analysis was performed and the area under the ROC curve (AUC) was calculated. The optimal discriminative texture parameters were used to produce support vector machine (SVM) classifiers. Diagnostic accuracy and 10-fold cross-validation was performed. RESULTS: Compared to ccRCC, non-ccRCC had significantly lower mean grey-level intensity (mean), standard deviation (SD), entropy, mean of positive pixels (MPP), and higher kurtosis (p<0.001). A model incorporating SD, entropy, MPP, and kurtosis produced an AUC of 0.94±0.03 with an accuracy of 87% (sensitivity=89%, specificity=92%) to identify non-ccRCC from ccRCC. Compared to chromophobe RCC, papillary RCC had significantly lower mean and MPP (p=0.002). A model incorporating SD, MPP, and skewness resulted in an AUC of 0.96±0.04 with an accuracy of 78% (sensitivity=87%, specificity=92%) to differentiate between papillary and chromophobe RCC. CONCLUSION: CT TA could potentially be used as a less invasive tool to classify histological subtypes of RCC.

Texture analysis of cardiovascular magnetic resonance cine images differentiates aetiologies of left ventricular hypertrophy.

AIM: To investigate whether unenhanced cardiovascular magnetic resonance (CMR) balanced steady state free precession (bSSFP) cine images could be analysed using textural analysis (TA) software to differentiate different aetiologies of disease causing increased myocardial wall thickness (left ventricular hypertrophy [LVH]) and indicate the severity of myocardial tissue abnormality. MATERIALS AND METHODS: A mid short axis unenhanced cine frame of 216 patients comprising 50 cases of hypertrophic cardiomyopathy (HCM; predominantly Left ventricular outflow tract obstruction [LVOTO] subtype), 52 cases of cardiac amyloid (CA; predominantly AL: light chain subtype), 68 cases of aortic stenosis (AS), 15 hypertensive patients with LVH (HTN+LVH), and 31 healthy volunteers (HV) underwent TA of the CMR cine images (CMRTA) using TexRAD (TexRAD Ltd, Cambridge, UK). Among the HV, 16/31 were scanned twice to form a test-retest reproducibility cohort. CMRTA comprised a filtration-histogram technique to extract and quantify features using six parameters. RESULTS: Test-retest analysis in the HV showed a medium filter (3 mm) was the most reproducible (intra-class correlation of 0.9 for kurtosis and skewness and 0.8 for mean and SD). Disease cohorts were statistically different (p<0.001) to HV for all parameters. Pairwise comparisons of CMRTA parameters showed kurtosis and skewness was consistently significant in ranking the degree of difference from HV (greatest to least): CA, HCM, LVH+HTN, AS (p<0.001). Similarly, mean, standard deviation, entropy, and mean positive pixel (MPP) were consistent in ranking degree of difference from HV: HCM, CA, AS and HTN+LVH. CONCLUSION: Radiomic features of bSSFP CMR data sets derived using TA show promise in discriminating between the aetiologies of LVH.

Quantitative assessment of myocardial scar heterogeneity using cardiovascular magnetic resonance texture analysis to risk stratify patients post-myocardial infarction.

AIM: To determine whether heterogeneity of cardiac scar, as assessed by cardiovascular magnetic resonance (CMR) texture analysis, may provide insight into better risk stratification for patients with previous myocardial infarction (MI). MATERIALS AND METHODS: Patients with previous MI (n=76) were followed for a median of 371.5 days after late gadolinium enhancement (LGE) CMR. The primary endpoint was a composite of ventricular tachycardia, ventricular fibrillation, or unexplained syncope. Areas of LGE were identified and manually segmented on a short-axis projection. The characteristics of the scar heterogeneity were evaluated via CMR texture analysis. This is a filtration-histogram technique, where images are filtered using the Laplacian of a Gaussian filter to extract features different sizes (2-6 mm in radius) corresponding to fine, medium, and coarse texture scales followed by a quantification step using histogram analysis (skewness and kurtosis). RESULTS: Patients suffering arrhythmic events during the follow-up period demonstrated significantly higher kurtosis (coarse-scale, p=0.005) and lower skewness (fine-scale, p=0.046) compared to those suffering no arrhythmic events. Furthermore, Kaplan-Meier analysis showed significantly higher coarse kurtosis (p=0.004), and lower fine skewness (p=0.035) were able to predict increased incidence of ventricular arrhythmic events. CONCLUSIONS: In this pilot study, indices of texture analysis reflecting textural heterogeneity were significantly associated with a greater incidence of arrhythmic events. Further work is required to delineate the role of texture analysis techniques in risk stratification post-MI.

CT-based texture analysis potentially provides prognostic information complementary to interim fdg-pet for patients with hodgkin's and aggressive non-hodgkin's lymphomas.

OBJECTIVES: The purpose of this study was to investigate the ability of computed tomography texture analysis (CTTA) to provide additional prognostic information in patients with Hodgkin's lymphoma (HL) and high-grade non-Hodgkin's lymphoma (NHL). METHODS: This retrospective, pilot-study approved by the IRB comprised 45 lymphoma patients undergoing routine 18F-FDG-PET-CT. Progression-free survival (PFS) was determined from clinical follow-up (mean-duration: 40 months; range: 10-62 months). Non-contrast-enhanced low-dose CT images were submitted to CTTA comprising image filtration to highlight features of different sizes followed by histogram-analysis using kurtosis. Prognostic value of CTTA was compared to PET FDG-uptake value, tumour-stage, tumour-bulk, lymphoma-type, treatment-regime, and interim FDG-PET (iPET) status using Kaplan-Meier analysis. Cox regression analysis determined the independence of significantly prognostic imaging and clinical features. RESULTS: A total of 27 patients had aggressive NHL and 18 had HL. Mean PFS was 48.5 months. There was no significant difference in pre-treatment CTTA between the lymphoma sub-types. Kaplan-Meier analysis found pre-treatment CTTA (medium feature scale, p=0.010) and iPET status (p<0.001) to be significant predictors of PFS. Cox analysis revealed that an interaction between pre-treatment CTTA and iPET status was the only independent predictor of PFS (HR: 25.5, 95% CI: 5.4-120, p<0.001). Specifically, pre-treatment CTTA risk stratified patients with negative iPET. CONCLUSION: CTTA can potentially provide prognostic information complementary to iPET for patients with HL and aggressive NHL. KEY POINTS: • CT texture-analysis (CTTA) provides prognostic information complementary to interim FDG-PET in Lymphoma. • Pre-treatment CTTA and interim PET status were significant predictors of progression-free survival. • Patients with negative interim PET could be further stratified by pre-treatment CTTA. • Provide precision surveillance where additional imaging reserved for patients at greatest recurrence-risk. • Assists in risk-adapted treatment strategy based on interim PET and CTTA.

Magnetic resonance based texture parameters as potential imaging biomarkers for predicting long-term survival in locally advanced rectal cancer treated by chemoradiotherapy.

AIM: The study aimed to investigate whether textural features of rectal cancer on MRI can predict long-term survival in patients treated with long-course chemoradiotherapy. METHOD: Textural analysis (TA) using a filtration-histogram technique of T2-weighted pre- and 6-week post-chemoradiotherapy MRI was undertaken using TexRAD, a proprietary software algorithm. Regions of interest enclosing the largest cross-sectional area of the tumour were manually delineated on the axial images and the filtration step extracted features at different anatomical scales (fine, medium and coarse) followed by quantification of statistical features [mean intensity, standard deviation, entropy, skewness, kurtosis and mean of positive pixels (MPP)] using histogram analysis. Cox multiple regression analysis determined which univariate features including textural, radiological and histological independently predicted overall survival (OS), disease-free survival (DFS) and recurrence-free survival (RFS). RESULTS: MPP [fine texture, hazard ratio (HR) 6.9, 95% CI: 2.43-19.55, P < 0.001], mean (medium texture, HR 5.6, 95% CI: 1.4-21.7, P = 0.007) and extramural venous invasion (EMVI) on MRI (HR 2.96, 95% CI: 1.04-8.37, P = 0.041) independently predicted OS while mean (medium texture, HR 4.53, 95% CI: 1.58-12.94, P = 0.003), MPP (fine texture, HR 3.36, 95% CI: 1.36-8.31, P = 0.008) and threatened circumferential resection margin (CRM) on MRI (HR 3.1, 95% CI: 1.01-9.46, P = 0.046) predicted DFS. For OS, EMVI on MRI (HR 4.23, 95% CI: 1.41-12.69, P = 0.01) and for DFS kurtosis (medium texture, HR 3.97, 95% CI: 1.44-10.94, P = 0.007) and CRM involvement on MRI (HR 3.36, 95% CI: 1.21-9.32, P = 0.02) were the independent post-treatment factors. Only TA independently predicted RFS on pre- or post-treatment analyses. CONCLUSION: MR based TA of rectal cancers can predict outcome before undergoing surgery and could potentially select patients for individualized therapy.

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

Tumour heterogeneity has, in recent times, come to play a vital role in how we understand and treat cancers; however, the clinical translation of this has lagged behind advances in research. Although significant advancements in oncological management have been made, personalized care remains an elusive goal. Inter- and intratumour heterogeneity, particularly in the clinical setting, has been difficult to quantify and therefore to treat. The histological quantification of heterogeneity of tumours can be a logistical and clinical challenge. The ability to examine not just the whole tumour but also all the molecular variations of metastatic disease in a patient is obviously difficult with current histological techniques. Advances in imaging techniques and novel applications, alongside our understanding of tumour heterogeneity, have opened up a plethora of non-invasive biomarker potential to examine tumours, their heterogeneity and the clinical translation. This review will focus on how various imaging methods that allow for quantification of metastatic tumour heterogeneity, along with the potential of developing imaging, integrated with other in vitro diagnostic approaches such as genomics and exosome analyses, have the potential role as a non-invasive biomarker for guiding the treatment algorithm.

Gray matter textural heterogeneity as a potential in-vivo biomarker of fine structural abnormalities in Asperger syndrome.

Brain imaging studies contribute to the neurobiological understanding of Autism Spectrum Conditions (ASC). Herein, we tested the prediction that distributed neurodevelopmental abnormalities in brain development impact on the homogeneity of brain tissue measured using texture analysis (TA; a morphological method for surface pattern characterization). TA was applied to structural magnetic resonance brain scans of 54 adult participants (24 with Asperger syndrome (AS) and 30 controls). Measures of mean gray-level intensity, entropy and uniformity were extracted from gray matter images at fine, medium and coarse textures. Comparisons between AS and controls identified higher entropy and lower uniformity across textures in the AS group. Data reduction of texture parameters revealed three orthogonal principal components. These were used as regressors-of-interest in a voxel-based morphometry analysis that explored the relationship between surface texture variations and regional gray matter volume. Across the AS but not control group, measures of entropy and uniformity were related to the volume of the caudate nuclei, whereas mean gray-level was related to the size of the cerebellar vermis. Similar to neuropathological studies, our study provides evidence for distributed abnormalities in the structural integrity of gray matter in adults with ASC, in particular within corticostriatal and corticocerebellar networks. Additionally, this in-vivo technique may be more sensitive to fine microstructural organization than other more traditional magnetic resonance approaches and serves as a future testable biomarker in AS and other neurodevelopmental disorders.

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.

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

AIM: To determine how hepatic entropy and uniformity of computed tomography (CT) images of the liver change after the administration of contrast material and to assess whether these additional parameters are more sensitive to tumour-related changes in the liver than measurements of hepatic attenuation or perfusion. MATERIALS AND METHODS: Hepatic attenuation, entropy, uniformity, and perfusion were measured using multi-phase CT following resection of colorectal cancer. Based on conventional CT and fluorodeoxyglucose positron emission tomography, 12 patients were classified as having no evidence of malignancy, eight with extra-hepatic tumours only, and eight with metastatic liver disease. RESULTS: Hepatic attenuation and entropy increased after CM administration whereas uniformity decreased. Unlike hepatic attenuation, entropy and uniformity changed maximally in the arterial phase. No significant differences in hepatic perfusion or attenuation were found between patient groups, whereas arterial-phase entropy was lower (p=0.034) and arterial-phase uniformity was higher (p=0.034) in apparently disease-free areas of liver in patients with hepatic metastases compared with those with no metastases. CONCLUSION: Temporal changes in hepatic entropy and uniformity differ from those for hepatic attenuation. By reflecting the distribution of hepatic enhancement, these additional parameters are more sensitive to tumour-related changes in the liver than measurements of hepatic attenuation or perfusion.