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EPMA Journal

, Volume 9, Issue 4, pp 421–429 | Cite as

Radiomics improves efficiency for differentiating subclinical pheochromocytoma from lipid-poor adenoma: a predictive, preventive and personalized medical approach in adrenal incidentalomas

  • Xiaoping Yi
  • Xiao Guan
  • Youming Zhang
  • Longfei Liu
  • Xueying Long
  • Hongling Yin
  • Zhongjie Wang
  • Xuejun Li
  • Weihua Liao
  • Bihong T. Chen
  • Chishing Zee
Research
  • 31 Downloads

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.

Keywords

Adrenal gland neoplasms Pheochromocytoma Adrenal adenoma Predictive preventive personalized medicine Computed tomography Radiomics 

Abbreviations

AA

Adrenal adenoma

AI

Adrenal incidentaloma

AUC

Area under the receiver operating characteristic curve

CT

Computed tomography

CTpre

Pre-enhanced CT value

CTpost

Enhanced CT value

ICC

Intraclass correlation coefficient

LASSO

Least absolute shrinkage and selection operator

LD

Long diameter

LPA

Lipid-poor adrenal adenoma

MRI

Magnetic resonance imaging

N/C

Necrosis or cystic degeneration

PET

Positron emission tomography

sPHEO

Subclinical pheochromocytoma

ROC

Receiver operating characteristic

SD

Short diameter

Notes

Acknowledgements

We thank Taihao Jin (Ph.D), from the Department of Diagnostic Radiology (City of Hope National Medical Center) for helpful discussion and assistance in preparing the manuscript. Editing assistance was provided by Nancy Linford, PhD.

Funding

This study is partially supported in part by China Postdoctoral Science Foundation funded project (2018M632997) and The Postdoctoral Science Foundation of Central South University (No. 185705).

Compliance with ethical standards

Competing interests

The authors declare that they have no competing interests.

Consent for publication

Not applicable.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. For this type of study, formal consent is not required.

Supplementary material

13167_2018_149_MOESM1_ESM.docx (1.2 mb)
ESM 1 (DOCX 1189 kb)

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Copyright information

© European Association for Predictive, Preventive and Personalised Medicine (EPMA) 2018

Authors and Affiliations

  1. 1.Department of Radiology, Xiangya HospitalCentral South UniversityChangshaPeople’s Republic of China
  2. 2.Postdoctoral Research Workstation of Pathology and Pathophysiology, Basic Medical Sciences, Xiangya HospitalCentral South UniversityChangshaChina
  3. 3.Department of Urology, Xiangya HospitalCentral South UniversityChangshaChina
  4. 4.Department of Pathology, Xiangya HospitalCentral South UniversityChangshaChina
  5. 5.Department of Neurosurgery, Xiangya HospitalCentral South UniversityChangshaChina
  6. 6.Department of Diagnostic RadiologyCity of Hope National Medical CentreDuarteUSA
  7. 7.Department of RadiologyKeck Medical Center of USCLos AngelesUSA

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