Lisa M Ho1, Ehsan Samei1,2,3,4,5, Maciej A Mazurowski1,4,5,6, Yuese Zheng5, Brian C Allen1, Rendon C Nelson1, Daniele Marin1. 1. 1 Department of Radiology, Duke University Medical Center, 2301 Erwin Rd, Box 3808, Durham, NC 22710. 2. 2 Department of Biomedical Engineering, Duke University, Durham, NC. 3. 3 Department of Physics, Duke University, Durham, NC. 4. 4 Department of Electrical and Computer Engineering, Duke University, Durham, NC. 5. 5 Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University Medical Center, Durham, NC. 6. 6 Department of Biostatistics and Bioinformatics, Duke University, Durham, NC.
Abstract
OBJECTIVE: The purpose of this study is to determine whether second-order texture analysis can be used to distinguish lipid-poor adenomas from malignant adrenal nodules on unenhanced CT, contrast-enhanced CT (CECT), and chemical-shift MRI. MATERIALS AND METHODS: In this retrospective study, 23 adrenal nodules (15 lipid-poor adenomas and eight adrenal malignancies) in 20 patients (nine female patients and 11 male patients; mean age, 59 years [range, 15-80 years]) were assessed. All patients underwent unenhanced CT, CECT, and chemical-shift MRI. Twenty-one second-order texture features from the gray-level cooccurrence matrix and gray-level run-length matrix were calculated in 3D. The mean values for 21 texture features and four imaging features (lesion size, unenhanced CT attenuation, CECT attenuation, and signal intensity index) were compared using a t test. The diagnostic performance of texture analysis versus imaging features was also compared using AUC values. Multivariate logistic regression models to predict malignancy were constructed for texture analysis and imaging features. RESULTS: Lesion size, unenhanced CT attenuation, and the signal intensity index showed significant differences between benign and malignant adrenal nodules. No significant difference was seen for CECT attenuation. Eighteen of 21 CECT texture features and nine of 21 unenhanced CT texture features revealed significant differences between benign and malignant adrenal nodules. CECT texture features (mean AUC value, 0.80) performed better than CECT attenuation (mean AUC value, 0.60). Multivariate logistic regression models showed that CECT texture features, chemical-shift MRI texture features, and imaging features were predictive of malignancy. CONCLUSION: Texture analysis has a potential role in distinguishing benign from malignant adrenal nodules on CECT and may decrease the need for additional imaging studies in the workup of incidentally discovered adrenal nodules.
OBJECTIVE: The purpose of this study is to determine whether second-order texture analysis can be used to distinguish lipid-poor adenomas from malignant adrenal nodules on unenhanced CT, contrast-enhanced CT (CECT), and chemical-shift MRI. MATERIALS AND METHODS: In this retrospective study, 23 adrenal nodules (15 lipid-poor adenomas and eight adrenal malignancies) in 20 patients (nine female patients and 11 male patients; mean age, 59 years [range, 15-80 years]) were assessed. All patients underwent unenhanced CT, CECT, and chemical-shift MRI. Twenty-one second-order texture features from the gray-level cooccurrence matrix and gray-level run-length matrix were calculated in 3D. The mean values for 21 texture features and four imaging features (lesion size, unenhanced CT attenuation, CECT attenuation, and signal intensity index) were compared using a t test. The diagnostic performance of texture analysis versus imaging features was also compared using AUC values. Multivariate logistic regression models to predict malignancy were constructed for texture analysis and imaging features. RESULTS: Lesion size, unenhanced CT attenuation, and the signal intensity index showed significant differences between benign and malignant adrenal nodules. No significant difference was seen for CECT attenuation. Eighteen of 21 CECT texture features and nine of 21 unenhanced CT texture features revealed significant differences between benign and malignant adrenal nodules. CECT texture features (mean AUC value, 0.80) performed better than CECT attenuation (mean AUC value, 0.60). Multivariate logistic regression models showed that CECT texture features, chemical-shift MRI texture features, and imaging features were predictive of malignancy. CONCLUSION: Texture analysis has a potential role in distinguishing benign from malignant adrenal nodules on CECT and may decrease the need for additional imaging studies in the workup of incidentally discovered adrenal nodules.
Authors: Mark Sherlock; Andrew Scarsbrook; Afroze Abbas; Sheila Fraser; Padiporn Limumpornpetch; Rosemary Dineen; Paul M Stewart Journal: Endocr Rev Date: 2020-12-01 Impact factor: 19.871
Authors: F Torresan; F Crimì; F Ceccato; F Zavan; M Barbot; C Lacognata; R Motta; C Armellin; C Scaroni; E Quaia; C Campi; M Iacobone Journal: BJS Open Date: 2021-01-08