Pleuropulmonary blastoma (PPB) with central nervous system metastasis: case report, imaging findings, and review of literature

Abstract

Pleuropulmonary blastoma (PPB) is a very rare tumor of the chest seen predominantly in young children with great heterogeneity and clinical, biochemical, and biological complexity and recognized, described, and classified as distinct from the pulmonary blastoma typically encountered in adults. Unfortunately, it has a poor and dismal prognosis and is mainly classified as cystic (type 1), mixed type (type 2), and solid (type 3). Herein, we present one case of PPB type 2 presenting clinically with a right pulmonary abscess, a rare clinical presentation of PPB, which was initially treated with surgery, and after approximately 1 year of follow-up, pulmonary rest-recurrence and central nervous system secondary deposits were detected. When a large pleural-based mass is identified in a young child, PPB should also be considered, especially in a patient with a positive oncological family history. Suggestive findings include the absence of chest wall invasion, presence of pleural fluid, right-sided location, and heterogeneous native (NECT) low attenuation with variable postcontrast enhancement. The authors believe that a modern therapeutic approach should consider these results for a better understanding of the genetic nature and complex mechanism and process of PPB disease development (both clinical and preclinical data concerning PPB pathophysiology are still lacking and are not completely understood) so that it would be possible to establish new possible therapeutic options (i.e. nuclear medicine theranostics in PPB treatment, developments and innovation in FLASH radiotherapy and proton therapy) and approaches, and so that, given the severity of the disease, it would be possible to indicate the importance of genetic testing and counseling of close relatives. In line with the previous, the rapid development of artificial intelligence could potentially bring the development of a novel fusion of radio mics and semantic features and MRI-based machine learning in distinguishing PPB from similar pathology.