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Am J Surg Pathol ; 48(3): 309-316, 2024 Mar 01.
Artículo en Inglés | MEDLINE | ID: mdl-38155550

RESUMEN

Pediatric adrenocortical neoplasms (ACNs) are extremely rare tumors in contrast to their adult counterparts. Distinguishing benign from malignant is challenging based on pure morphologic grounds. Previously, 2 scoring systems were proposed in pediatric ACN, including the Wieneke criteria (WC) and its modified version (modified WC [mWC]). In adults, the reticulin algorithm (RA) has proven inexpensive, reliable, predictive, and reproducible; however, it has been validated only recently in children in a limited number of cases. This study aims to assess the RA utility compared with other scoring systems in a series of 92 pediatric ACNs. All cases were individually scored, and mitotic rate cutoffs were recorded. Reticulin alterations were classified as quantitative and qualitative. Outcome data were available in 59/92. The median age was 5 years (0.1 to 18 y) with an M:F of 0.6. Clinical presentation included virilization (39%), Cushing syndrome (21%), other symptoms (4%), and asymptomatic (36%). The reticulin framework was intact in 27% and altered in 73% of cases, showing qualitative (22%), quantitative (73%), and both (5%) alterations. In patients with favorable outcomes, 59% showed either intact reticulin or qualitative alteration compared with the unfavorable outcome group, where 90% showed quantitative alterations. All scoring systems WC ( P < 0.0001), mWC ( P = 0.0003), and the adult/pediatric RA ( P < 0.0001) had predictive value. The RA is comparable to WC and mWC, easier to apply, and is the most sensitive histopathological approach to identifying aggressive behavior in pediatric ACN. Its integration into the WC might be helpful in ACN of uncertain malignant potential and deserves further investigation.


Asunto(s)
Neoplasias de la Corteza Suprarrenal , Reticulina , Adulto , Niño , Humanos , Preescolar , Neoplasias de la Corteza Suprarrenal/diagnóstico , Neoplasias de la Corteza Suprarrenal/patología , Algoritmos , Síndrome
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