Cancers (Jul 2023)

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

  • Marta Araujo-Castro,
  • Iñigo García Sanz,
  • César Mínguez Ojeda,
  • María Calatayud,
  • Felicia A. Hanzu,
  • Mireia Mora,
  • Almudena Vicente Delgado,
  • Concepción Blanco Carrera,
  • Paz de Miguel Novoa,
  • María del Carmen López García,
  • Laura Manjón-Miguélez,
  • Pablo Rodríguez de Vera Gómez,
  • María del Castillo Tous,
  • Rebeca Barahona San Millán,
  • Mónica Recansens,
  • Mariana Tomé Fernández-Ladreda,
  • Nuria Valdés,
  • Paola Gracia Gimeno,
  • Cristina Robles Lazaro,
  • Theodora Michalopoulou,
  • Victoria Gómez Dos Santos,
  • Cristina Alvarez-Escola,
  • Rogelio García Centeno,
  • Cristina Lamas,
  • Aura Herrera-Martínez

DOI
https://doi.org/10.3390/cancers15143736
Journal volume & issue
Vol. 15, no. 14
p. 3736

Abstract

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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 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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