Development of a radiomics model to diagnose pheochromocytoma preoperatively: a multicenter study with prospective validation

Jianqiu Kong,Jieying Wu,Junjiong Zheng,Xinxiang Fan,Haide Qin,Lifang Huang,Zhuo Wu,Weibin Xie,Hongpeng Fang,Xiong Chen,Jian Huang,Tianxin Lin,Jinhua Cai,Hao Yu,Yong Li,Xiayao Diao,Shaoxu Wu

doi:10.1186/s12967-022-03233-w

Abstract

BackgroundPreoperative diagnosis of pheochromocytoma (PHEO) accurately impacts preoperative preparation and surgical outcome in PHEO patients. Highly reliable model to diagnose PHEO is lacking. We aimed to develop a magnetic resonance imaging (MRI)-based radiomic-clinical model to distinguish PHEO from adrenal lesions.MethodsIn total, 305 patients with 309 adrenal lesions were included and divided into different sets. The least absolute shrinkage and selection operator (LASSO) regression model was used for data dimension reduction, feature selection, and radiomics signature building. In addition, a nomogram incorporating the obtained radiomics signature and selected clinical predictors was developed by using multivariable logistic regression analysis. The performance of the radiomic-clinical model was assessed with respect to its discrimination, calibration, and clinical usefulness.ResultsSeven radiomics features were selected among the 1301 features obtained as they could differentiate PHEOs from other adrenal lesions in the training (area under the curve [AUC], 0.887), internal validation (AUC, 0.880), and external validation cohorts (AUC, 0.807). Predictors contained in the individualized prediction nomogram included the radiomics signature and symptom number (symptoms include headache, palpitation, and diaphoresis). The training set yielded an AUC of 0.893 for the nomogram, which was confirmed in the internal and external validation sets with AUCs of 0.906 and 0.844, respectively. Decision curve analyses indicated the nomogram was clinically useful. In addition, 25 patients with 25 lesions were recruited for prospective validation, which yielded an AUC of 0.917 for the nomogram.ConclusionWe propose a radiomic-based nomogram incorporating clinically useful signatures as an easy-to-use, predictive and individualized tool for PHEO diagnosis.

Highlights

Pheochromocytoma (PHEO) is a rare neuroendocrine catecholamine-secreting tumor originating from the chromaffin cells, with an annual incidence of approximately 1–2/100,000 person-years [1, 2]
magnetic resonance imaging (MRI) is a morphologic imaging procedure that can differentiate PHEOs from other adrenal tumors such as adenomas and metastases [6, 7] since PHEOs are generally hyperintense on T2-weighted images [8]
239 patients treated in the Sun Yat-sen Memorial Hospital were divided into a training cohort (N = 166 patients with n = 170 lesions diagnosed between September 2010 and October 2013) and an internal validation cohort (N = 73 patients with n = 73 lesions diagnosed between November 2013 and May 2019) in a ratio of 7:3

Summary

Introduction

Pheochromocytoma (PHEO) is a rare neuroendocrine catecholamine-secreting tumor originating from the chromaffin cells, with an annual incidence of approximately 1–2/100,000 person-years [1, 2]. Preoperatively discriminating PHEOs from other adrenal tumors is crucial for appropriate treatment planning. Abdominal/pelvic multiphasic computed tomography (CT) or magnetic resonance imaging (MRI) is commonly used in cancer diagnosis [4] and has been recommended as the most common non-invasive modality to diagnose PHEO [5]. PHEOs may mimic other adrenal masses on the traditional radiological analysis due to the overlap in imaging features and non-specific clinical findings [11,12,13]; encapsulating the notion of “imaging chameleon” [14]. As a result, developing a more accurate preoperative imaging tool to diagnose PHEO is in urgent need. We aimed to develop a magnetic resonance imaging (MRI)-based radiomic-clinical model to distinguish PHEO from adrenal lesions

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Results