Improving utility of brain tumor confocal laser endomicroscopy: objective value assessment and diagnostic frame detection with convolutional neural networks

Confocal laser endomicroscopy (CLE), although capable of obtaining images at cellular resolution during surgery of brain tumors in real time, creates as many non-diagnostic as diagnostic images. Non-useful images are often distorted due to relative motion between probe and brain or blood artifacts. Many images, however, simply lack diagnostic features immediately informative to the physician. Examining all the hundreds or thousands of images from a single case to discriminate diagnostic images from nondiagnostic ones can be tedious. Providing a real-time diagnostic value assessment of images (fast enough to be used during the surgical acquisition process and accurate enough for the pathologist to rely on) to automatically detect diagnostic frames would streamline the analysis of images and filter useful images for the pathologist/surgeon. We sought to automatically classify images as diagnostic or non-diagnostic. AlexNet, a deep-learning architecture, was used in a 4-fold cross validation manner. Our dataset includes 16,795 images (8572 nondiagnostic and 8223 diagnostic) from 74 CLE-aided brain tumor surgery patients. The ground truth for all the images is provided by the pathologist. Average model accuracy on test data was 91% overall (90.79 % accuracy, 90.94 % sensitivity and 90.87 % specificity). To evaluate the model reliability we also performed receiver operating characteristic (ROC) analysis yielding 0.958 average for the area under ROC curve (AUC). These results demonstrate that a deeply trained AlexNet network can achieve a model that reliably and quickly recognizes diagnostic CLE images.Comment: SPIE Medical Imaging: Computer-Aided Diagnosis 201

Accurate state estimation from uncertain data and models: an application of data assimilation to mathematical models of human brain tumors

<p>Abstract</p> <p>Background</p> <p>Data assimilation refers to methods for updating the state vector (initial condition) of a complex spatiotemporal model (such as a numerical weather model) by combining new observations with one or more prior forecasts. We consider the potential feasibility of this approach for making short-term (60-day) forecasts of the growth and spread of a malignant brain cancer (glioblastoma multiforme) in individual patient cases, where the observations are synthetic magnetic resonance images of a hypothetical tumor.</p> <p>Results</p> <p>We apply a modern state estimation algorithm (the Local Ensemble Transform Kalman Filter), previously developed for numerical weather prediction, to two different mathematical models of glioblastoma, taking into account likely errors in model parameters and measurement uncertainties in magnetic resonance imaging. The filter can accurately shadow the growth of a representative synthetic tumor for 360 days (six 60-day forecast/update cycles) in the presence of a moderate degree of systematic model error and measurement noise.</p> <p>Conclusions</p> <p>The mathematical methodology described here may prove useful for other modeling efforts in biology and oncology. An accurate forecast system for glioblastoma may prove useful in clinical settings for treatment planning and patient counseling.</p> <p>Reviewers</p> <p>This article was reviewed by Anthony Almudevar, Tomas Radivoyevitch, and Kristin Swanson (nominated by Georg Luebeck).</p

Sulforhodamine 101 selectively labels human astrocytoma cells in an animal model of glioblastoma

AbstractSulforhodamine 101 (SR101) is a useful tool for immediate staining of astrocytes. We hypothesized that if the selectivity of SR101was maintained in astrocytoma cells, it could prove useful for glioma research. Cultured astrocytoma cells and acute slices from orthotopic human glioma (n=9) and lymphoma (n=6) xenografts were incubated with SR101 and imaged with confocal microscopy. A subset of slices (n=18) were counter-immunostained with glial fibrillary acidic protein and CD20 for stereological assessment of SR101 co-localization. SR101 differentiated astrocytic tumor cells from lymphoma cells. In acute slices, SR101 labeled 86.50% (±1.86; p<0.0001) of astrocytoma cells and 2.19% (±0.47; p<0.0001) of lymphoma cells. SR101-labeled astrocytoma cells had a distinct morphology when compared with in vivo astrocytes. Immediate imaging of human astrocytoma cells in vitro and in ex vivo rodent xenograft tissue labeled with SR101 can identify astrocytic tumor cells and help visualize the tumor margin. These features are useful in studying astrocytoma in the laboratory and may have clinical applications

Pharmacologic and Cell-Based Therapies for Acute Spinal Cord Injury

This article provides a review of current pharmacologic and cell-based modalities used for the management of acute spinal cord injury (SCI). The literature search was focused on clinical trials performed in the United States and Canada. Despite the significant advance in research, there is no definitive treatment option for SCI. Instead, existing pharmacologic and cell-based modalities provide only minimal neurologic recovery benefits. This can be attributed to the complex pathophysiology of SCI and spinal cord regeneration. Further research is imperative to better understand these mechanisms and discover definitive treatment modalities

The definition of necessary axial force for extension of initial borehole for soft soil compaction process design

The article provides an analytical solution of the soil pile and surrounding soil cylinder interaction problem, with the possibility of extension of the pile shaft in its construction. Presents a closed solution for determination of radial and tangential stresses in the process of expansion of the pile shaft, as well as the minimum vertical force sufficient for the crushing of the pile material and move it in radial direction to the specified value. The problem is most actual for compacted soil bases with use of piles-drains of sand and sand-gravel mixture

The definition of necessary axial force for extension of initial borehole for soft soil compaction process design

The article provides an analytical solution of the soil pile and surrounding soil cylinder interaction problem, with the possibility of extension of the pile shaft in its construction. Presents a closed solution for determination of radial and tangential stresses in the process of expansion of the pile shaft, as well as the minimum vertical force sufficient for the crushing of the pile material and move it in radial direction to the specified value. The problem is most actual for compacted soil bases with use of piles-drains of sand and sand-gravel mixture