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Winkelmann, Moritz T; Gassenmaier, Sebastian; Walter, Sven S; Artzner, Christoph; Lades, Felix; Faby, Sebastian; Nikolaou, Konstantin; Bongers, Malte N
Diagnostic and interventional radiology (Ankara, Turkey), 05/2022, Letnik: 28, Številka: 3Journal Article
PURPOSE Differentiation of incidental adrenal lesions remains a challenge in diagnostic imaging, especially on single-phase portal venous computed tomography (CT) in the oncological setting. The aim of the study was to explore the ability of dual-energy CT (DECT)-based iodine quantification and virtual non-contrast (VNC) imaging and advanced radiomic analysis of DECT for differentiation of adrenal adenomas from metastases. METHODS A total of 46 patients with 49 adrenal lesions underwent clinically indicated staging DECT and magnetic resonance imaging. Median values of quantitative parameters such as VNC, fat fraction, and iodine density in DECT images were collected and compared between adenomas and metastases using non-parametric tests. Magnetic resonance imaging, washout CT, and clinical follow-up were used as a reference standard. Diagnostic accuracy was assessed by calculating receiver operating characteristics. A DECT tumor analysis prototype software was used for semiautomatic segmentation of adrenal lesions and extraction of radiomic features. A radiomics prototype was used to analyze the data with multiple logistic regression and random forest classification to determine the area under the curve (AUC). RESULTS The study cohort (60.87% women; mean age: 66.91 + or - 12.93 years) consisted of 32 adenomas and 17 metastases. DECT-based VNC imaging (AUC = 0.89) and fat quantification (AUC = 0.86) differentiate between adrenal adenomas and metastases with high diagnostic accuracy (P < .001). Analysis of radiomic features revealed that DECT features such as VNC imaging and fat fraction (AUC = 0.87-0.89; < .001) and radiomic features such as 90th percentile and total energy (AUC = 0.88-0.93; P < .001) differentiate with high diagnostic accuracy between adrenal adenomas and metastases. Random forest classification revealed an AUC of 0.83 for separating adrenal adenomas from metastases. CONCLUSION Virtual non-contrast imaging and fat quantification as well as extraction of radiomic features accurately differentiate between adrenal adenomas and metastases on single-phase oncologic staging DECT.
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JCR | SNIP | JCR | SNIP | JCR | SNIP | JCR | SNIP |
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