Computer-aided diagnosis of carotid atherosclerosis based on ultrasound image statistics, laws' texture and neural networks

Quantitative characterisation of carotid atherosclerosis and classification into symptomatic or asymptomatic is crucial in planning optimal treatment of atheromatous plaque. The computer-aided diagnosis (CAD) system described in this paper can analyse ultrasound (US) images of carotid artery and classify them into symptomatic or asymptomatic based on their echogenicity characteristics. The CAD system consists of three modules: a) the feature extraction module, where first-order statistical (FOS) features and Laws' texture energy can be estimated, b) the dimensionality reduction module, where the number of features can be reduced using analysis of variance (ANOVA), and c) the classifier module consisting of a neural network (NN) trained by a novel hybrid method based on genetic algorithms (GAs) along with the back propagation algorithm. The hybrid method is able to select the most robust features, to adjust automatically the NN architecture and to optimise the classification performance. The performance is measured by the accuracy, sensitivity, specificity and the area under the receiver-operating characteristic (ROC) curve. The CAD design and development is based on images from 54 symptomatic and 54 asymptomatic plaques. This study demonstrates the ability of a CAD system based on US image analysis and a hybrid trained NN to identify atheromatous plaques at high risk of stroke.

Ragu: a free tool for the analysis of EEG and MEG event-related scalp field data using global randomization statistics

We present a program (Ragu; Randomization Graphical User interface) for statistical analyses of multichannel event-related EEG and MEG experiments. Based on measures of scalp field differences including all sensors, and using powerful, assumption-free randomization statistics, the program yields robust, physiologically meaningful conclusions based on the entire, untransformed, and unbiased set of measurements. Ragu accommodates up to two within-subject factors and one between-subject factor with multiple levels each. Significance is computed as function of time and can be controlled for type II errors with overall analyses. Results are displayed in an intuitive visual interface that allows further exploration of the findings. A sample analysis of an ERP experiment illustrates the different possibilities offered by Ragu. The aim of Ragu is to maximize statistical power while minimizing the need for a-priori choices of models and parameters (like inverse models or sensors of interest) that interact with and bias statistics.

Omega-3 poly-unsaturated fatty acids for the prevention of severe neutropenic enterocolitis in patients with acute myeloid leukemia

Neutropenic enterocolitis is a potentially fatal complication of myeloablative chemotherapy in patients with acute myeloid leukemia. Omega-3 polyunsaturated fatty acids (PUFA) are precursors of potent anti-inflammatory prostaglandins. Our aim was to explore the safety and effectiveness of omega-3 PUFA added to parenteral nutrition in protecting leukemia patients from severe enterocolitis. Fourteen patients with acute myeloid leukemia who received omega-3 PUFA in a Phase II trial were compared with 66 consecutive control patients not getting this intervention. We performed crude and adjusted comparisons, using inverse probability of treatment weighting for adjusted analysis, and blind outcome assessment to minimize assessor bias. Primary outcome was severe enterocolitis (≥Grade 3). The crude odds ratio of Grade 3 colitis or higher was 1.36 (95% CI 0.37 to 4.96, P = 0.64), and the adjusted odds ratio was 0.79 (95% CI 0.35 to 1.78, P = 0.57). There was little evidence to suggest differences between groups in serious adverse events and overall mortality. Our results provide little evidence that addition of omega-3 PUFA is beneficial in this condition. Routine treatment with omega-3 PUFA is currently not warranted.

Interferons in hematopoiesis and leukemia

Interferons not only exert a fundamental role during inflammation and immune responses but also modulate the activity of hematopoietic stem cells during homeostatic and demand-adapted hematopoiesis. Identical mechanisms regulate the homeostasis and proliferation of leukemic stem cells (LSCs). Understanding these mechanisms may lead to novel therapeutic approaches against leukemia.

Cytotoxic T cells induce proliferation of chronic myeloid leukemia stem cells by secreting interferon-γ

Chronic myeloid leukemia (CML) is a clonal myeloproliferative neoplasia arising from the oncogenic break point cluster region/Abelson murine leukemia viral oncogene homolog 1 translocation in hematopoietic stem cells (HSCs), resulting in a leukemia stem cell (LSC). Curing CML depends on the eradication of LSCs. Unfortunately, LSCs are resistant to current treatment strategies. The host’s immune system is thought to contribute to disease control, and several immunotherapy strategies are under investigation. However, the interaction of the immune system with LSCs is poorly defined. In the present study, we use a murine CML model to show that LSCs express major histocompatibility complex (MHC) and co-stimulatory molecules and are recognized and killed by leukemia-specific CD8+ effector CTLs in vitro. In contrast, therapeutic infusions of effector CTLs into CML mice in vivo failed to eradicate LSCs but, paradoxically, increased LSC numbers. LSC proliferation and differentiation was induced by CTL-secreted IFN-γ. Effector CTLs were only able to eliminate LSCs in a situation with minimal leukemia load where CTL-secreted IFN-γ levels were low. In addition, IFN-γ increased proliferation and colony formation of CD34+ stem/progenitor cells from CML patients in vitro. Our study reveals a novel mechanism by which the immune system contributes to leukemia progression and may be important to improve T cell–based immunotherapy against leukemia.