• This prospective single-centre study showed discordance for full patient staging of 44% between WB-MRI and a multi-modality reference standard in paediatric and adolescent Hodgkin's lymphoma. • WB-MRI underestimates interim disease response in paediatric and adolescent Hodgkin's lymphoma. • WB-MRI shows promise in paediatric and adolescent Hodgkin's lymphoma but currently cannot replace conventional staging pathways including F-FDG-PET-CT.
HighlightsMinimal user interaction is needed for a good segmentation of the placenta.Random forests with high level features improved the segmentation.Higher accuracy than state-of-the-art interactive segmentation methods.Co-segmentation of multiple volumes outperforms single sparse volume based method.
The International Association for the Study of Lung Cancer proposed changes to the 7th edition of the Tumor, Node, and Metastasis (TNM) staging manual of non-small cell lung cancer (NSCLC) to improve the prognostic relevance of its descriptors. These changes include the subdivision of T1 and T2 disease according to size cut points; reassignment of the T and M categories of same-lobe, ipsilateral, and contralateral malignant pulmonary nodules; reassignment of pleural disease to metastatic disease; and introduction of intra- and extrathoracic metastatic disease. Because of movement between T and M descriptors and resultant stage migration, new stage groupings that contain TNM subsets different from those of the previous edition were created. The new staging classification was created on the basis of statistical analysis of a large international database of cases of NSCLC. The new classification has many advantages; however, limitations remain. Problems with routine radiologic staging of NSCLC have not been addressed, the varied survival rates for patients with the different histologic subtypes is not reflected, the new classification is not compatible with the previous system, and application of treatment algorithms on the basis of evidence from the previous edition is less clear.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.