Search

Wolman's disease, a severe form of lysosomal acid lipase deficiency, leads to pathologic lipid accumulation in the liver and gut that, without treatment, is fatal in infancy. Although continued enzyme-replacement therapy (ERT) in combination with dietary fat restriction prolongs life, its therapeutic effect may wane over time. Allogeneic hematopoietic stem-cell transplantation (HSCT) offers a more definitive solution but carries a high risk of death. Here we describe an infant with Wolman's disease who received high-dose ERT, together with dietary fat restriction and rituximab-based B-cell depletion, as a bridge to early HSCT. At 32 months, the infant was independent of ERT and disease-free, with 100% donor chimerism in the peripheral blood., (Copyright © 2024 Massachusetts Medical Society.)

Glioblastoma (GBM) is the most malignant primary brain tumor for which no curative treatment options exist. Non-invasive qualitative (Visually Accessible Rembrandt Images (VASARI)) and quantitative (radiomics) imaging features to predict prognosis and clinically relevant markers for GBM patients are needed to guide clinicians. A retrospective analysis of GBM patients in two neuro-oncology centers was conducted. The multimodal Cox-regression model to predict overall survival (OS) was developed using clinical features with VASARI and radiomics features in isocitrate dehydrogenase ( IDH )-wild type GBM. Predictive models for IDH -mutation, 06-methylguanine-DNA-methyltransferase ( MGMT )-methylation and epidermal growth factor receptor ( EGFR ) amplification using imaging features were developed using machine learning. The performance of the prognostic model improved upon addition of clinical, VASARI and radiomics features, for which the combined model performed best. This could be reproduced after external validation (C-index 0.711 95% CI 0.64-0.78) and used to stratify Kaplan-Meijer curves in two survival groups ( p -value < 0.001). The predictive models performed significantly in the external validation for EGFR amplification (area-under-the-curve (AUC) 0.707, 95% CI 0.582-8.25) and MGMT -methylation (AUC 0.667, 95% CI 0.522-0.82) but not for IDH -mutation (AUC 0.695, 95% CI 0.436-0.927). The integrated clinical and imaging prognostic model was shown to be robust and of potential clinical relevance. The prediction of molecular markers showed promising results in the training set but could not be validated after external validation in a clinically relevant manner. Overall, these results show the potential of combining clinical features with imaging features for prognostic and predictive models in GBM, but further optimization and larger prospective studies are warranted.