Original PaperTumour heterogeneity in oesophageal cancer assessed by CT texture analysis: Preliminary evidence of an association with tumour metabolism, stage, and survival
Introduction
The incidence of oesophageal cancer is notably high in Asia, Iceland, as well as the United Kingdom and United States.1 In 2010, the American Cancer Society estimated, approximately 16,640 new oesophageal cancer cases annually in the United States.2 The incidence is also rising in other western countries.3 Most people diagnosed with oesophageal cancer present with advanced disease. Despite the use of neoadjuvant chemotherapy and radiotherapy, the prognosis for patients with oesophageal cancer remains poor. The 5 year survival for tumours remaining within the oesophageal wall is about 40%; for tumours involving the adventitia of the oesophagus it is only 4%; and for patients without nodal involvement it is about 40%, diminishing to approximately 3% for those with nodal metastases.4 Novel means of stratifying risk for patients with oesophageal cancer could potentially lead to optimization of management strategies with improved outcomes.
Heterogeneity of the tumour microenvironment is a well-recognized feature of malignancy that is associated with adverse tumour biology. In particular, heterogeneity of the tumour blood supply results in the formation of hypoxic voids, which in turn are associated with oxidative stress, promotion of survival factors, and genomic instability.5 Hypoxia-inducible factors (HIFs) are important biochemical mediators in tissue responses to hypoxia. HIFs are transcription factors that up-regulate a range of processes associated with increased tumour aggression and treatment resistance.6 A heterogeneous blood supply will also impact on treatment response due to poor delivery of chemotherapeutic agents to areas of low vascularity.7 Hence, a non-invasive imaging method for assessment of tumour heterogeneity could potentially provide a biomarker for prognosis and treatment response.
Computed tomography (CT) remains the initial imaging method for clinical staging of oesophageal cancer, evaluating local spread into adjacent structures (T4 disease) and the presence of distant metastases (M1). If these features are absent on CT, subsequent endoscopic ultrasonography (EUS) is used to distinguish T1 tumours from higher-stage lesions and detect nodal involvement (N1 disease), whilst 2-[18F]-fluoro-2-deoxy-d-glucose (FDG) positron-emission tomography computed tomography (PET-CT) is most helpful in the detection of previously occult distant metastases.8 A meta-analysis has also shown that the intensity of FDG uptake also can provide a marker of likely survival and treatment response.9 One study has also reported that high FDG uptake is associated with poorly differentiated tumours.10 However, despite potential relevance to tumour biology, patient survival, and treatment response, none of these imaging methods provides objective assessment of tumour heterogeneity.
By assessing the distribution of grey-levels, coarseness, and regularity within a lesion, computed image analysis algorithms have the potential to provide additional morphological information relating to tumour heterogeneity. These texture analyses also have the advantage of quantifying tumour heterogeneity, something that cannot be achieved reliably by simple visual analysis. Recently, texture analysis performed on CT images of lung tumours has identified parameters reflecting tumour heterogeneity that were associated with advanced disease, increased FDG uptake on PET, and poor survival.11, 12, 13 The association between CT texture and FDG uptake likely reflects increased glucose metabolism in response to regional hypoxia as HIFs are known to up-regulate glucose metabolic pathways.6
As a preliminary step to ascertain whether tumour heterogeneity assessed with CT texture analysis (CTTA) has the potential to provide a similar marker of tumour aggression and predict patient survival in oesophageal cancer, the aim of the present pilot study was to correlate CTTA with staging, glucose metabolism, and patient survival.
Section snippets
Methods and materials
This single institution pilot study comprised a retrospective evaluation of image data from patients undergoing PET-CT and EUS for staging oesophageal cancer. The need for formal ethics evaluation for this retrospective evaluation was waived by the Institutional Review Board.
Results
Based on PET, CT, and EUS imaging, the number of patients with stage ≤II and >II were eight and 13, respectively (stage II, n = 8; stage III, n = 8; and stage IV, n = 5). Of the 21 patients with oesophageal cancer 14 had ADC and seven had SCC at histology. The median (range) tumour SUVmean and SUVmax for all the patients was 4.8 (1.9–9.8) and 11.4 (2.5–32.5). Table 1 summarizes patient demographics (clinical stage, histology, and SUV). Twelve of 21 patients died within 24 months of their PET-CT. The
Discussion
Structural heterogeneity is a recognized feature of malignancy and methods for measuring tumour heterogeneity on histological images have been described previously including application to prediction of progression to invasive cancer in patients with Barrett’s oesophagus.16 However, measurement of tumour heterogeneity on diagnostic images has to date, received relatively little attention particularly in CT, with few studies highlighting its importance in magnetic resonance imaging (MRI).17, 18
References (25)
- et al.
Vessel abnormalization: another hallmark of cancer? Molecular mechanisms and therapeutic implications
Curr Opin Gene Devel
(2011) - et al.
Pulmonary nodule characterization: a comparison of conventional with quantitative and visual semi-quantitative analyses using contrast enhancement maps
Eur J Radiol
(2006) - et al.
Hepatic entropy and uniformity: additional parameters that can potentially increase the effectiveness of contrast enhancement during abdominal CT
Clin Radiol
(2007) - et al.
Computerized morphometry as an aid in determining the grade of dysplasia and progression to adenocarcinoma in Barrett’s esophagus
Lab Invest
(2006) - What are the key statistics about cancer of the esophagus? Detailed guide: esophagus cancer. American Cancer Society....
Esophagoscopic monitoring of Barrett’s esophagus — additional life years of good quality or wasting of limited resources?
Duodecim
(2010)Oesophageal cancer
- et al.
Hypoxia and defective apoptosis drive genomic instability and tumorigenesis
Genes Dev
(2004) HIF-1 and tumor progression: pathophysiology and therapeutics
Trends Mol Med
(2002)
Staging esophageal cancer
Cancer Imaging
Prognostic significance of SUV on PET/CT in patients with esophageal cancer; a systematic review and meta-analysis
Eur J Gastroenterol Hepatol
Cited by (276)
A primer on artificial intelligence in pancreatic imaging
2023, Diagnostic and Interventional ImagingHeterogeneity of Lung Density in Patients With Chronic Thromboembolic Pulmonary Hypertension (CTEPH)
2022, Academic RadiologyCitation Excerpt :Heterogeneity in tumor tissue is a well-recognized feature of malignancy (28,29). Histogram parameters can quantify the heterogeneity in the tissue and show the implications for diagnosis, treatment effect, identification of drug targets, and survival (15). However, the findings of histogram analysis have not been elucidated in patients with respiratory diseases, except in patients with lung cancer (30,31).
Novel Advances in Qualitative Diagnostic Imaging for Decision Making in Multidisciplinary Treatment for Advanced Esophageal Cancer
2024, Journal of Clinical MedicinePredicting response to CCRT for esophageal squamous carcinoma by a radiomics-clinical SHAP model
2023, BMC Medical Imaging