Xiaoping Yi1,2, Xiao Guan3, Youming Zhang1, Longfei Liu3, Xueying Long1, Hongling Yin4, Zhongjie Wang5, Xuejun Li5, Weihua Liao1, Bihong T Chen6, Chishing Zee7. 1. 1Department of Radiology, Xiangya Hospital, Central South University, No. 87 Xiangya Road, Changsha, 410008 People's Republic of China. 2. 2Postdoctoral Research Workstation of Pathology and Pathophysiology, Basic Medical Sciences, Xiangya Hospital, Central South University, Changsha, China. 3. 3Department of Urology, Xiangya Hospital, Central South University, Changsha, China. 4. 4Department of Pathology, Xiangya Hospital, Central South University, Changsha, China. 5. 5Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China. 6. 6Department of Diagnostic Radiology, City of Hope National Medical Centre, Duarte, CA USA. 7. 7Department of Radiology, Keck Medical Center of USC, Los Angeles, CA USA.
Abstract
OBJECTIVES: This study aims to define a radiomic signature for pre-operative differentiation between subclinical pheochromocytoma (sPHEO) and lipid-poor adrenal adenoma (LPA) in adrenal incidentaloma. The goal was to apply a predictive, preventive, and personalized medical approach to the management of adrenal tumors. PATIENTS AND METHODS: This retrospective study consisted of 265 consecutive patients (training cohort, 212 (LPA, 145; sPHEO, 67); validation cohort, 53 (LPA, 36; sPHEO, 17)). Computed tomography (CT) imaging features were evaluated, including long diameter (LD), short diameter (SD), pre-enhanced CT value (CTpre), enhanced CT value (CTpost), shape, homogeneity, necrosis or cystic degeneration (N/C). Radiomic features were extracted and then were used to construct a radiomic signature (Rad-score) and radiomic nomogram. The area under the receiver operating characteristic curve (AUC) was used to evaluate their performance. RESULTS: Sixteen of three hundred forty candidate features were used to build a radiomic signature. The signature was significantly different between the sPHEO and LPA groups (AUC: training, 0.907; validation, 0.902). The radiomic nomogram based on enhanced CT features (M1) consisted of Rad-score, LD, SD, CTpre, shape, homogeneity and N/C (AUC: training, 0.957; validation, 0.967). The pre-enhanced CT features based radiomic nomogram (M2) included Rad-score, LD, SD, CTpre, shape, and homogeneity (AUC: training, 0.955; validation, 0.958). CONCLUSIONS: Our radiomic nomograms based on pre-enhanced and enhanced CT images distinguished sPHEO from LPA. In addition, the promising result using pre-enhanced CT images for predictive diagnostics is important because patients could avoid the additional radiation and risk associated with enhanced CT.
OBJECTIVES: This study aims to define a radiomic signature for pre-operative differentiation between subclinical pheochromocytoma (sPHEO) and lipid-poor adrenal adenoma (LPA) in adrenal incidentaloma. The goal was to apply a predictive, preventive, and personalized medical approach to the management of adrenal tumors. PATIENTS AND METHODS: This retrospective study consisted of 265 consecutive patients (training cohort, 212 (LPA, 145; sPHEO, 67); validation cohort, 53 (LPA, 36; sPHEO, 17)). Computed tomography (CT) imaging features were evaluated, including long diameter (LD), short diameter (SD), pre-enhanced CT value (CTpre), enhanced CT value (CTpost), shape, homogeneity, necrosis or cystic degeneration (N/C). Radiomic features were extracted and then were used to construct a radiomic signature (Rad-score) and radiomic nomogram. The area under the receiver operating characteristic curve (AUC) was used to evaluate their performance. RESULTS: Sixteen of three hundred forty candidate features were used to build a radiomic signature. The signature was significantly different between the sPHEO and LPA groups (AUC: training, 0.907; validation, 0.902). The radiomic nomogram based on enhanced CT features (M1) consisted of Rad-score, LD, SD, CTpre, shape, homogeneity and N/C (AUC: training, 0.957; validation, 0.967). The pre-enhanced CT features based radiomic nomogram (M2) included Rad-score, LD, SD, CTpre, shape, and homogeneity (AUC: training, 0.955; validation, 0.958). CONCLUSIONS: Our radiomic nomograms based on pre-enhanced and enhanced CT images distinguished sPHEO from LPA. In addition, the promising result using pre-enhanced CT images for predictive diagnostics is important because patients could avoid the additional radiation and risk associated with enhanced CT.
Authors: Philippe Lambin; Ralph T H Leijenaar; Timo M Deist; Jurgen Peerlings; Evelyn E C de Jong; Janita van Timmeren; Sebastian Sanduleanu; Ruben T H M Larue; Aniek J G Even; Arthur Jochems; Yvonka van Wijk; Henry Woodruff; Johan van Soest; Tim Lustberg; Erik Roelofs; Wouter van Elmpt; Andre Dekker; Felix M Mottaghy; Joachim E Wildberger; Sean Walsh Journal: Nat Rev Clin Oncol Date: 2017-10-04 Impact factor: 66.675
Authors: Lucinda M Gruber; Veljko Strajina; Irina Bancos; M Hassan Murad; Benzon M Dy; William F Young; David R Farley; Melanie L Lyden; Geoffrey B Thompson; Travis J McKenzie Journal: Gland Surg Date: 2020-04