Proceedings of the MICCAI Challenge on Multimodal Brain Tumor Image Segmentation (BRATS) 2013

International audienceBecause of their unpredictable appearance and shape, segmenting brain tumors from multi-modal imaging data is one of the most challenging tasks in medical image analysis. Although many different segmentation strategies have been proposed in the literature, it is hard to compare existing methods because the validation datasets that are used differ widely in terms of input data (structural MR contrasts; perfusion or diffusion data; ...), the type of lesion (primary or secondary tumors; solid or infiltratively growing), and the state of the disease (pre- or post-treatment). In order to gauge the current state-of-the-art in automated brain tumor segmentation and compare between different methods, we are organizing a Multimodal Brain Tumor Image Segmentation (BRATS) challenge that is held in conjunction with the 16th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2013) on September 22nd, 2013 in Nagoya, Japan

Exploring the impact of trait number and type on functional diversity metrics in real-world ecosystems

The use of trait-based approaches to understand ecological communities has increased in the past two decades because of their promise to preserve more information about community structure than taxonomic methods and their potential to connect community responses to subsequent effects of ecosystem functioning. Though trait-based approaches are a powerful tool for describing ecological communities, many important properties of commonly-used trait metrics remain unexamined. Previous work in studies that simulate communities and trait distributions show consistent sensitivity of functional richness and evenness measures to the number of traits used to calculate them, but these relationships have yet to be studied in actual plant communities with a realistic distribution of trait values, ecologically meaningful covariation of traits, and a realistic number of traits available for analysis. Therefore, we propose to test how the number of traits used and the correlation between traits used in the calculation of functional diversity indices impacts the magnitude of eight functional diversity metrics in real plant communities. We will use trait data from three grassland plant communities in the US to assess the generality of our findings across ecosystems and experiments. We will determine how eight functional diversity metrics (functional richness, functional evenness, functional divergence, functional dispersion, kernel density estimation (KDE) richness, KDE evenness, KDE dispersion, Rao's Q) differ based on the number of traits used in the metric calculation and on the correlation of traits when holding the number of traits constant. Without a firm understanding of how a scientist's choices impact these metric, it will be difficult to compare results among studies with different metric parametrization and thus, limit robust conclusions about functional composition of communities across systems

Health-related quality of life and late morbidity in concurrent chemoradiation and radiotherapy alone in patients with locally advanced cervical carcinoma

Objective: Concurrent chemoradiation has improved survival of patients with cervical carcinoma. However, follow-up of randomized studies is relatively short and data on long term toxicity are scarce, as is information on their health-related quality of life. This study assesses and compares incidences of late side-effects among patients treated with radiotherapy or chemoradiation using two toxicity scoring systems, and investigates impact on health-related quality of life. Methods: Between 1985 and 1993, 114 patients underwent radiotherapy (n=39) or chemoradiation (n=75) for stage IIA-IVB cervical carcinoma. Late side-effects were scored retrospectively by reviewing medical charts using standardised checklists, focusing on bladder- and intestinal side effects. Health-related quality of life was assessed once using the EORTC QLQ-C30. Results: No significant differences in late treatment-related side-effects between radiotherapy and chemoradiation groups were found. Grade >= 2 toxicity was found in 33% (bladder), and in 6% (bowel). Only 1.8% had both grade 3-4 toxicity. Bladder syndrome with high urinary frequency, urine incontinence and small bowel toxicity had a significant impact on health-related quality of life. Conclusion: Grade 2 are relatively frequent late side effects in curatively treated patients, but are not enhanced by the addition of chemotherapy. Their negative impact on health-related quality of life stresses the importance of new radiation techniques, aiming at reduction of these side effects

Multimodal Analysis of Vasogenic Edema in Glioblastoma Patients for Radiotherapy Planning

International audienceGlioblastoma (GBM) is the most common type of primary brain tumor, which is characterized by an infiltrative growth pattern. In current practice, radiotherapy planning is primarily based upon T2 FLAIR MRI despite its known lack of specificity in the detection of tu-mor infiltration. While hyperintensity on T2 FLAIR is widely considered to represent infiltrative tumor, it may also be caused by the presence of vasogenic edema (VE), caused by a leakage of fluid into the brain parenchyma. Distinguishing VE from infiltrative tumor could have im-pact on improving radiotherapy planning. In this paper we study a data set of 17 GBM patients treated with anti-angiogenic therapy for which a fast decrease of T2 FLAIR hypersignal is observed, which indicates the resolution of VE. We investigate if multimodal MRI acquisitions in-cluding diffusion tensor imaging can distinguish between VE and tumor infiltration prior to therapy. Using a random forest classifier, we show that, in this study, morphological information based on the contrast en-hanced T1 image explains up to 75% of the extent of VE. The information from different imaging modalities did not significantly improve the clas-sification. We then show that delineating the VE prior to therapy can have substantial impact on radiotherapy target delineation, leading to smaller treatment volumes and reducing potentially harmful radiation dose to normal brain tissue

Cell-Type-Specific Impact of Glucocorticoid Receptor Activation on the Developing Brain: A Cerebral Organoid Study.

OBJECTIVE: A fine-tuned balance of glucocorticoid receptor (GR) activation is essential for organ formation, with disturbances influencing many health outcomes. In utero, glucocorticoids have been linked to brain-related negative outcomes, with unclear underlying mechanisms, especially regarding cell-type-specific effects. An in vitro model of fetal human brain development, induced human pluripotent stem cell (hiPSC)-derived cerebral organoids, was used to test whether cerebral organoids are suitable for studying the impact of prenatal glucocorticoid exposure on the developing brain. METHODS: The GR was activated with the synthetic glucocorticoid dexamethasone, and the effects were mapped using single-cell transcriptomics across development. RESULTS: The GR was expressed in all cell types, with increasing expression levels through development. Not only did its activation elicit translocation to the nucleus and the expected effects on known GR-regulated pathways, but also neurons and progenitor cells showed targeted regulation of differentiation- and maturation-related transcripts. Uniquely in neurons, differentially expressed transcripts were significantly enriched for genes associated with behavior-related phenotypes and disorders. This human neuronal glucocorticoid response profile was validated across organoids from three independent hiPSC lines reprogrammed from different source tissues from both male and female donors. CONCLUSIONS: These findings suggest that excessive glucocorticoid exposure could interfere with neuronal maturation in utero, leading to increased disease susceptibility through neurodevelopmental processes at the interface of genetic susceptibility and environmental exposure. Cerebral organoids are a valuable translational resource for exploring the effects of glucocorticoids on early human brain development

The RNA-binding protein RBM3 is required for cell proliferation and protects against serum deprivation-induced cell death

Hypoxia and other adverse conditions are commonly encountered by rapidly growing cells. The RNA-binding protein RBM3 (RNA-binding motif protein 3), which is transcriptionally induced by low temperature and hypoxia, has recently been implicated in survival of colon cancer cells by mechanisms involving cyclooxygenase-2 (COX-2) signaling. Immunohistochemically, we found strong RBM3 expression in a variety of malignant and proliferating tissues but low expression in resting and terminally differentiated cells. RBM3 expression in fibroblasts and human embryonal kidney (HEK293) cells subjected to serum deprivation or contact inhibition closely paralleled proliferation rates, assessed by real-time RT-PCR and immunoblotting. siRNA-mediated RBM3 knockdown reduced cell viability and finally led to cell death, which did not involve caspase-3-mediated apoptosis, cell cycle arrest, or COX-2 regulation. In contrast, RBM3 over-expression rescued cells from death under serum starvation. This was associated with increased translation rates, as measured by C serine and H phenylalanine incorporation. Together, RBM3 is a critical factor providing cellular survival advantages in an adverse microenvironment presumably by restoring translation efficacy