An Integrated CT and MRI Imaging Model to Differentiate between Adrenal Adenomas and Pheochromocytomas

Purpose: to perform an external validation of our predictive model to rule out pheochromocytoma (PHEO) based on unenhanced CT in a cohort of patients with PHEOs and adenomas who underwent adrenalectomy. Methods: The predictive model was previously developed in a retrospective cohort of 1131 patients...

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Detalles Bibliográficos
Autores: Araujo Castro, Marta, García Sanz, Íñigo, Mínguez Ojeda, César, Calatayud Gutiérrez, María, Hanzu, Felicia Alexandra, Mora, Natalia, Vicente Delgado, Almudena, Vicente Delgado, Concepción, Miguel Novoa, Paz de, López García, María del Carmen, Manjón Miguélez, Laura, Rodríguez de Vera Gómez, Pablo, Castillo Tous, María del, Barahona San Millán, Rebeca, Recasens Sala, Mònica, Tomé Fernández-Ladreda, Mariana, Valdés Gallego, Nuria, Gracia Gimeno, Paola, Robles Lázaro, Cristina, Michalopoulou Alevras, Theodora, Gómez Dos Santos, Victoria, Álvarez Escolá, Cristina, García Centeno, Rogelio, Lamas Oliveira, Cristina, Herrera Martínez, Aura
Tipo de recurso: artículo
Fecha de publicación:2023
País:España
Institución:Universidad de Castilla-La Mancha
Repositorio:RUIdeRA. Repositorio Institucional de la UCLM
OAI Identifier:oai:ruidera.uclm.es:10578/42703
Acceso en línea:https://www.mdpi.com/2072-6694/15/14/3736
https://hdl.handle.net/10578/42703
Access Level:acceso abierto
Palabra clave:Adrenal adenoma
Adrenal tumor
Atypical adrenal adenoma
High lipid content
Pheochromocytoma
Descripción
Sumario:Purpose: to perform an external validation of our predictive model to rule out pheochromocytoma (PHEO) based on unenhanced CT in a cohort of patients with PHEOs and adenomas who underwent adrenalectomy. Methods: The predictive model was previously developed in a retrospective cohort of 1131 patients presenting with adrenal lesions. In the present study, we performed an external validation of the model in another cohort of 214 patients with available histopathological results. Results: For the external validation, 115 patients with PHEOs and 99 with adenomas were included. Our previously described predictive model combining the variables of high lipid content and tumor size in unenhanced CT (AUC-ROC: 0.961) had a lower diagnostic accuracy in our current study population for the prediction of PHEO (AUC: 0.750). However, when we excluded atypical adenomas (with Hounsfield units (HU) > 10, n = 39), the diagnostic accuracy increased to 87.4%. In addition, in the whole cohort (including atypical adenomas), when MRI information was included in the model, the diagnostic accuracy increased to up to 85% when the variables tumor size, high lipid content in an unenhanced CT scan, and hyperintensity in the T2 sequence in MRI were included. The probability of PHEO was <0.3% for adrenal lesions <20 mm with >10 HU and without hyperintensity in T2. Conclusion: Our study confirms that our predictive model combining tumor size and lipid content has high reliability for the prediction of PHEO when atypical adrenal lesions are excluded. However, for atypical adrenal lesions with >10 HU in an unenhanced CT scan, MRI information is necessary for a proper exclusion of the PHEO diagnosis.

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