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Radiomics analysis with three-dimensional and two-dimensional segmentation to predict survival outcomes in pancreatic cancer

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World Journal of Radiology 2023年第11期15卷 304-314页

作者： Mohammed Saleh Mayur Virarkar Hagar S Mahmoud Vincenzo K Wong Carlos Ignacio Gonzalez Baerga miti parikh Sherif B Elsherif Priya R Bhosale Department of Diagnostic Radiology The University of Texas MD Anderson Cancer CenterHoustonTX 77030United States Department of Diagnostic Radiology The University of Florida College of MedicineJacksonvilleFL 32209United States Keck School of Medicine University of South CaliforniaLos AngelesCA 90033United States

BACKGROUND Radiomics can assess prognostic factors in several types of tumors,but considering its prognostic ability in pancreatic cancer has been *** To evaluate the performance of two different radiomics software in assessing survival outcomes in pancreatic cancer *** We retrospectively reviewed pretreatment contrast-enhanced dual-energy computed tomography images from 48 patients with biopsy-confirmed pancreatic ductal adenocarcinoma who later underwent neoadjuvant chemoradiation and *** were segmented using TexRad software for 2-dimensional(2D)analysis and MIM software for 3D analysis,followed by radiomic feature *** proportional hazard modeling correlated texture features with overall survival(OS)and progression-free survival(PFS).Cox regression was used to detect differences in OS related to pretreatment tumor size and residual tumor following *** Wilcoxon test was used to show the relationship between tumor volume and the percent of residual ***-Meier analysis was used to compare survival in patients with different tumor densities in Hounsfield units for both 2D and 3D *** 3D analysis showed that higher mean tumor density[hazard ratio(HR)=0.971,P=0.041)]and higher median tumor density(HR=0.970,P=0.037)correlated with better OS.2D analysis showed that higher mean tumor density(HR=0.963,P=0.014)and higher mean positive pixels(HR=0.962,P=0.014)correlated with better OS;higher skewness(HR=3.067,P=0.008)and higher kurtosis(HR=1.176,P=0.029)correlated with worse *** entropy correlated with better PFS(HR=0.056,P=0.036).Models determined that patients with increased tumor size greater than 1.35 cm were likely to have a higher percentage of residual tumors of over 10%.CONCLUSION Several radiomics features can be used as prognostic tools for pancreatic ***,results vary between 2D and 3D *** tumor density was the only variable that could reliably predict OS,irrespective

关键词： Radiomics Pancreas Cancer Segmentation

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