Scientific Reports · 2019 · 56 citations · 25 references
MedicineOncologySurgeryDiagnostic ImagingDiagnostic RadiologyTumor HeterogeneityCancer Survival AnalysisComputed TomographyPancreatic CancerPancreatic PathologyTumor CharacterizationTumor ImagingBiological PrognosisComputed Tomography PrognosisPancreatic Cancer ImagingPancreatic Cancer ResectionPreoperative Cancer ImagingPreoperative Tumor CharacterizationRecurrence-free SurvivalTomography
Pancreatic cancer is a lethal disease, and resistance to chemotherapy is a critical factor influencing the postoperative prognosis. Tumour heterogeneity is an important indicator of chemoresistance. Therefore, we analysed tumour heterogeneity in preoperative computed tomography scans by performing texture analysis using the grey-level run-length matrix and analysed the correlation of survival with the value obtained in these analyses. We analysed 116 consecutive patients who underwent curative resection and had preoperative contrast-enhanced computed tomography data available for analysis. A region of interest was drawn on all slices with a visible tumour and normal pancreas on the arterial phase computed tomography scans; the correlation of pathological characteristics with grey-level run-length matrix features was analysed. We then performed Kaplan-Meier survival curve analysis among pancreatic cancer patients. The grey-level non-uniformity values in grey-level run-length matrix features for tumours were higher than those for normal pancreas. High grey-level non-uniformity values represent a non-uniform texture, i.e., heterogeneity. Grey-level run-length matrix features showed that recurrence-free survival was shorter in the group with high grey-level non-uniformity 135 values (p = 0.025). Our analyses of the correlation between pathological outcomes and grey-level run-length matrix features in pancreatic cancer patients showed that grey-level non-uniformity values were powerful prognostic indicators.
25
Rebecca L. Siegel, Elizabeth Ward, Otis W. Brawley et al. · CA A Cancer Journal for Clinicians · 2011 · 4.1K citations · Full text
Assessment of tumor heterogeneity: an emerging imaging tool for clinical practice?
F. Davnall, Connie Yip, Gunnar Ljungqvist et al. · Insights into Imaging · 2012 · 878 citations · Full text
Robust Radiomics Feature Quantification Using Semiautomatic Volumetric Segmentation
Chintan Parmar, Emmanuel Rios Velazquez, Ralph T. H. Leijenaar et al. · PLoS ONE · 2014 · 603 citations · Full text
Non–Small Cell Lung Cancer: Histopathologic Correlates for Texture Parameters at CT
Balaji Ganeshan, Vicky Goh, Henry Mandeville et al. · Radiology · 2012 · 453 citations