Connie Yip

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

BackgroundTumor spatial heterogeneity is an important prognostic factor, which may be reflected in medical imagesMethodsImage 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.ResultsEarly 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.ConclusionThis 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.

Are Pretreatment 18F-FDG PET Tumor Textural Features in Non–Small Cell Lung Cancer Associated with Response and Survival After Chemoradiotherapy?

There is evidence in some solid tumors that textural features of tumoral uptake in 18F-FDG PET images are associated with response to chemoradiotherapy and survival. We have investigated whether a similar relationship exists in non–small cell lung cancer (NSCLC). Methods: Fifty-three patients (mean age, 65.8 y; 31 men, 22 women) with NSCLC treated with chemoradiotherapy underwent pretreatment 18F-FDG PET/CT scans. Response was assessed by CT Response Evaluation Criteria in Solid Tumors (RECIST) at 12 wk. Overall survival (OS), progression-free survival (PFS), and local PFS (LPFS) were recorded. Primary tumor texture was measured by the parameters coarseness, contrast, busyness, and complexity. The following parameters were also derived from the PET data: primary tumor standardized uptake values (SUVs) (mean SUV, maximum SUV, and peak SUV), metabolic tumor volume, and total lesion glycolysis. Results: Compared with nonresponders, RECIST responders showed lower coarseness (mean, 0.012 vs. 0.027; P = 0.004) and higher contrast (mean, 0.11 vs. 0.044; P = 0.002) and busyness (mean, 0.76 vs. 0.37; P = 0.027). Neither complexity nor any of the SUV parameters predicted RECIST response. By Kaplan–Meier analysis, OS, PFS, and LPFS were lower in patients with high primary tumor coarseness (median, 21.1 mo vs. not reached, P = 0.003; 12.6 vs. 25.8 mo, P = 0.002; and 12.9 vs. 20.5 mo, P = 0.016, respectively). Tumor coarseness was an independent predictor of OS on multivariable analysis. Contrast and busyness did not show significant associations with OS (P = 0.075 and 0.059, respectively), but PFS and LPFS were longer in patients with high levels of each (for contrast: median of 20.5 vs. 12.6 mo, P = 0.015, and median not reached vs. 24 mo, P = 0.02; and for busyness: median of 20.5 vs. 12.6 mo, P = 0.01, and median not reached vs. 24 mo, P = 0.006). Neither complexity nor any of the SUV parameters showed significant associations with the survival parameters. Conclusion: In NSCLC, baseline 18F-FDG PET scan uptake showing abnormal texture as measured by coarseness, contrast, and busyness is associated with nonresponse to chemoradiotherapy by RECIST and with poorer prognosis. Measurement of tumor metabolic heterogeneity with these parameters may provide indices that can be used to stratify patients in clinical trials for lung cancer chemoradiotherapy.

Primary Esophageal Cancer: Heterogeneity as Potential Prognostic Biomarker in Patients Treated with Definitive Chemotherapy and Radiation Therapy

PURPOSE To determine the association between tumor heterogeneity, morphologic tumor response, and overall survival in primary esophageal cancer treated with chemotherapy and radiation therapy (CRT). MATERIALS AND METHODS After an institutional review board waiver was obtained, contrast material-enhanced computed tomographic (CT) studies in 36 patients with stage T2 or greater esophageal tumors who underwent contrast-enhanced CT before and after CRT between 2005 and 2008 were analyzed in terms of whole-tumor texture, with quantification of entropy, uniformity, mean gray-level intensity, kurtosis, standard deviation of the histogram, and skewness for fine to coarse textures (filters 1.0-2.5, respectively). The association between texture parameters and survival time was assessed by using Kaplan-Meier analysis and a Cox proportional hazards model. Survival models involving texture parameters and combinations of texture and morphologic response assessment were compared with morphologic assessment alone by means of receiver operating characteristic (ROC) analysis. RESULTS Posttreatment medium entropy of less than 7.356 (median overall survival, 33.2 vs 11.7 months; P = .0002), coarse entropy of less than 7.116 (median overall survival, 33.2 vs 11.7 months; P = .0002), and medium uniformity of 0.007 or greater (median overall survival, 33.2 vs 11.7 months; P = .0002) were associated with improved survival time. These remained significant prognostic factors after adjustment for stage and age: entropy (filter 2.0: hazard ratio [HR] = 5.038, P = .0004; filter 2.5: HR = 5.038, P = .0004) and uniformity (HR = 0.199, P = .0004). Survival models that included a combination of pretreatment entropy and uniformity with maximal wall thickness assessment, respectively, performed better than morphologic assessment alone (area under the ROC curve, 0.767 vs 0.487 [P = .00005] and 0.802 vs 0.487 [P = .0003]). CONCLUSION Posttreatment texture parameters are associated with survival time, and the combination of pretreatment texture parameters and maximal wall thickness performed better in survival models than morphologic tumor response alone.

Primary Esophageal Cancer Heterogeneity as a Potential Prognostic Biomarker in Patients Treated with Definitive Chemoradiation

PURPOSE To determine the association between tumor heterogeneity, morphologic tumor response, and overall survival in primary esophageal cancer treated with chemotherapy and radiation therapy (CRT). MATERIALS AND METHODS After an institutional review board waiver was obtained, contrast material-enhanced computed tomographic (CT) studies in 36 patients with stage T2 or greater esophageal tumors who underwent contrast-enhanced CT before and after CRT between 2005 and 2008 were analyzed in terms of whole-tumor texture, with quantification of entropy, uniformity, mean gray-level intensity, kurtosis, standard deviation of the histogram, and skewness for fine to coarse textures (filters 1.0-2.5, respectively). The association between texture parameters and survival time was assessed by using Kaplan-Meier analysis and a Cox proportional hazards model. Survival models involving texture parameters and combinations of texture and morphologic response assessment were compared with morphologic assessment alone by means of receiver operating characteristic (ROC) analysis. RESULTS Posttreatment medium entropy of less than 7.356 (median overall survival, 33.2 vs 11.7 months; P = .0002), coarse entropy of less than 7.116 (median overall survival, 33.2 vs 11.7 months; P = .0002), and medium uniformity of 0.007 or greater (median overall survival, 33.2 vs 11.7 months; P = .0002) were associated with improved survival time. These remained significant prognostic factors after adjustment for stage and age: entropy (filter 2.0: hazard ratio [HR] = 5.038, P = .0004; filter 2.5: HR = 5.038, P = .0004) and uniformity (HR = 0.199, P = .0004). Survival models that included a combination of pretreatment entropy and uniformity with maximal wall thickness assessment, respectively, performed better than morphologic assessment alone (area under the ROC curve, 0.767 vs 0.487 [P = .00005] and 0.802 vs 0.487 [P = .0003]). CONCLUSION Posttreatment texture parameters are associated with survival time, and the combination of pretreatment texture parameters and maximal wall thickness performed better in survival models than morphologic tumor response alone.

Radiomics in PET: principles and applications

Radiomics is an evolving field in which the extraction of large amounts of features from diagnostic medical images may be used to predict underlying molecular and genetic characteristics, thereby improving treatment response prediction and prognostication and potentially allowing personalisation of cancer treatment. There is increasing interest in extracting additional data from PET images, particularly novel features that describe the heterogeneity of voxel intensities, but a number of potential limitations need to be recognised and overcome. Nevertheless, some early data suggest that extraction of additional quantitative data may offer further predictive and prognostic information in individual patients.

Assessment of changes in tumor heterogeneity following neoadjuvant chemotherapy in primary esophageal cancer

To assess the changes in computed tomography (CT) tumor heterogeneity following neoadjuvant chemotherapy in esophageal cancer. Thirty-one consecutive patients who received neoadjuvant chemotherapy for esophageal cancer were identified. Analysis of primary tumor heterogeneity (texture) was performed on staging and post-chemotherapy CT scans. Image texture parameters (mean grey-level intensity, entropy, uniformity, kurtosis, skewness, standard deviation of histogram) were derived for different levels of image filtration (0-2.5). Proportional changes in each parameter following treatment were obtained. Comparison between pathological tumor response and texture parameters was analyzed using Mann-Whitney U-test. The relationship between CT texture and overall survival) was estimated using the Kaplan-Meier method. Tumor texture became more homogeneous after treatment with a significant decrease in entropy and increase in uniformity (filter 1.0 and 2.5). Pretreatment (filter 1.5, P = 0.006) and posttreatment standard deviation of histogram (filter 1.0, P = 0.009) showed a borderline association with pathological tumor response. A proportional change in skewness <0.39 (filter 1.0) was associated with improved survival (median overall survival 36.1 vs. 11.1 months; P < 0.001). CT tumor heterogeneity decreased following neoadjuvant chemotherapy and has the potential to provide additional information in primary esophageal cancer.

Molecular imaging of hypoxia in non-small cell lung cancer

Non-small-cell lung cancer (NSCLC) is the commonest cancer worldwide but survival remains poor with a high risk of relapse, particularly after nonsurgical treatment. Hypoxia is present in a variety of solid tumours, including NSCLC. It is associated with treatment resistance and a poor prognosis, although when recognised may be amenable to different treatment strategies. Thus, noninvasive assessment of intratumoral hypoxia could be used to stratify patients for modification of subsequent treatment to improve tumour control. Molecular imaging approaches targeting hypoxic cells have shown some early success in the clinical setting. This review evaluates the evidence for hypoxia imaging using PET in NSCLC and explores its potential clinical utility.

The role of new PET tracers for lung cancer

18F-fluorodeoxyglucose (18F-FDG) positron emission tomography-computed tomography (PET/CT) is established for characterising indeterminate pulmonary nodules and staging lung cancer where there is curative intent. Whilst a sensitive technique, specificity for characterising lung cancer is limited. There is recognition that evaluation of other aspects of abnormal cancer biology in addition to glucose metabolism may be more helpful in characterising tumours and predicting response to novel targeted cancer therapeutics. Therefore, efforts have been made to develop and evaluate new radiopharmaceuticals in order to improve the sensitivity and specificity of PET imaging in lung cancer with regards to characterisation, treatment stratification and therapeutic monitoring. 18F-fluorothymidine (18F-FLT) is a marker of cellular proliferation. It shows a lower accumulation in tumours than 18F-FDG as it only accumulates in the cells that are in the S phase of growth and demonstrates a low sensitivity for nodal staging. Its main role is in evaluating treatment response. Methionine is an essential amino acid. 11C-methionine is more specific and sensitive than 18F-FDG in differentiating benign and malignant thoracic nodules. 18Ffluoromisonidazole (18F-FMISO) is used for imaging tumour hypoxia. Tumour response to treatment is significantly related to the level of tumour oxygenation. Angiogenesis is the process by which new blood vessels are formed in tumours and is involved in tumour growth and metastatic tumour spread and is a therapeutic target. Most clinical studies have focused on targeted integrin PET imaging of which αvβ3 integrin is the most extensively investigated. It is upregulated on activated endothelial cells in association with tumour angiogenesis. Neuroendocrine tumour tracers, particularly 68Ga-DOTA-peptides, have an established role in imaging of carcinoid tumours. Whilst most of these tracers have predominantly been used in the research environment, they offer exciting opportunities for improving staging, characterisation, stratification and response assessment in an era of increased personalised therapy in lung cancer.

Building motion models of lung tumours from cone-beam CT for radiotherapy applications

A method is presented to build a surrogate-driven motion model of a lung tumour from a cone-beam CT scan, which does not require markers. By monitoring an external surrogate in real time, it is envisaged that the motion model be used to drive gated or tracked treatments. The motion model would be built immediately before each fraction of treatment and can account for inter-fraction variation. The method could also provide a better assessment of tumour shape and motion prior to delivery of each fraction of stereotactic ablative radiotherapy. The two-step method involves enhancing the tumour region in the projections, and then fitting the surrogate-driven motion model. On simulated data, the mean absolute error was reduced to 1 mm. For patient data, errors were determined by comparing estimated and clinically identified tumour positions in the projections, scaled to mm at the isocentre. Averaged over all used scans, the mean absolute error was under 2.5 mm in superior-inferior and transverse directions.

Co-registration of cone beam CT and planning CT in head and neck IMRT dose estimation: a feasible adaptive radiotherapy strategy

OBJECTIVE To investigate if cone beam CT (CBCT) can be used to estimate the delivered dose in head and neck intensity-modulated radiotherapy (IMRT). METHODS 15 patients (10 without replan and 5 with replan) were identified retrospectively. Weekly CBCT was co-registered with original planning CT. Original high-dose clinical target volume (CTV1), low-dose CTV (CTV2), brainstem, spinal cord, parotids and external body contours were copied to each CBCT and modified to account for anatomical changes. Corresponding planning target volumes (PTVs) and planning organ-at-risk volumes were created. The original plan was applied and calculated using modified per-treatment volumes on the original CT. Percentage volumetric, cumulative (planned dose delivered prior to CBCT + adaptive dose delivered after CBCT) and actual delivered (summation of weekly adaptive doses) dosimetric differences between each per-treatment and original plan were calculated. RESULTS There was greater volumetric change in the parotids with an average weekly difference of between -4.1% and -27.0% compared with the CTVs/PTVs (-1.8% to -5.0%). The average weekly cumulative dosimetric differences were as follows: CTV/PTV (range, -3.0% to 2.2%), ipsilateral parotid volume receiving ≥26 Gy (V26) (range, 0.5-3.2%) and contralateral V26 (range, 1.9-6.3%). In patients who required replan, the average volumetric reductions were greater: CTV1 (-2.5%), CTV2 (-6.9%), PTV1 (-4.7%), PTV2 (-11.5%), ipsilateral (-10.4%) and contralateral parotids (-12.1%), but did not result in significant dosimetric changes. CONCLUSION The dosimetric changes during head and neck simultaneous integrated boost IMRT do not necessitate adaptive radiotherapy in most patients. ADVANCES IN KNOWLEDGE Our study shows that CBCT could be used for dose estimation during head and neck IMRT.