Automatic Interpretation of Melanocytic Images in Confocal Laser Scanning Microscopy

The frequency of melanoma doubles every 20 years. The early detection of malignant changes augments the therapy success. Confocal laser scanning microscopy (CLSM) enables the noninvasive examination of skin tissue. To diminish the need for training and to improve diagnostic accuracy, computer-aided diagnostic systems are required. Two approaches are presented: a multiresolution analysis and an approach based on deep layer convolutional neural networks. For the diagnosis of the CLSM views, architectural structures such as micro-anatomic structures and cell nests are used as guidelines by the dermatologists. Features based on the wavelet transform enable an exploration of architectural structures at different spatial scales. The subjective diagnostic criteria are objectively reproduced. A tree-based machine-learning algorithm captures the decision structure explicitly and the decision steps are used as diagnostic rules. Deep layer neural networks require no a priori domain knowledge. They are capable of learning their own discriminatory features through the direct analysis of image data. However, deep layer neural networks require large amounts of processing power to learn. Therefore, modern neural network training is performed using graphics cards, which typically possess many hundreds of small, modestly powerful cores that calculate massively in parallel. Readers will learn how to apply multiresolution analysis and modern deep learning neural network techniques to medical image analysis problems

Virtopsy: forensic traumatology of the subcutaneous fatty tissue; multislice computed tomography (MSCT) and magnetic resonance imaging (MRI) as diagnostic tools

Traumatic lesions of the subcutaneous fatty tissue provide important clues for forensic reconstruction. The interpretation of these patterns requires a precise description and recording of the position and extent of each lesion. During conventional autopsy, this evaluation is performed by dissecting the skin and subcutaneous tissues in successive layers. In this way, depending on the force and type of impact (right angle or tangent), several morphologically distinct stages of fatty tissue damage can be differentiated: perilobular hemorrhage (I), contusion (II), or disintegration (III) of the fat lobuli, and disintegration with development of a subcutaneous cavity (IV). In examples of virtopsy cases showing blunt trauma to the skin and fatty tissue, we analyzed whether these lesions can also be recorded and classified using multislice computed tomography (MSCT) and magnetic resonance imaging (MRI). MSCT has proven to be a valuable screening method to detect the lesions, but MRI is necessary in order to properly differentiate and classify the grade of damage. These noninvasive radiological diagnostic tools can be further developed to play an important role in forensic examinations, in particular when it comes to evaluating living trauma victims

Frequent Down Regulation of the Tumor Suppressor Gene A20 in Multiple Myeloma

<div><p>Multiple myeloma (MM) is a malignant clonal expansion of plasma cells in the bone marrow and belongs to the mature B-cell neoplams. The pathogenesis of MM is associated with constitutive NF-κB activation. However, genetic alterations causing constitutive NF-κB activation are still incompletely understood. Since A20 (<i>TNFAIP3</i>) is a suppressor of the NF-κB pathway and is frequently inactivated in various lymphoid malignancies, we investigated the genetic and epigenetic properties of A20 in MM. In total, of 46 patient specimens analyzed, 3 single base pair exchanges, 2 synonymous mutations and one missense mutation were detected by direct sequencing. Gene copy number analysis revealed a reduced A20 gene copy number in 8 of 45 (17.7%) patients. Furthermore, immunohistochemical staining confirmed that A20 expression correlates with the reduction of A20 gene copy number. These data suggest that A20 contributes to tumor formation in a significant fraction of myeloma patients.</p></div

Genetic aberrations of A20 in multiple myeloma.

<p><b>a: Electropherogram of rs368271377 in exon 7:</b> Arrows indicate the single base pair substitution. <b>b: Electropherogram of rs143002189 in exon 9:</b> The arrow indicates the single base pair substitution. <b>c: Gene copy number analysis of A20 of selected cases:</b> For the gene copy number assays two technical replicates of each samples were used. The blue bar represents the data for exon 4 and the red one for exon 6. Each bar represents the mean values of expression levels ± standard deviation (SD). Cut off for deletion—depicted as red line—was set at 0.7 through the fact that samples exhibited up to 40% non-neoplastic surrounding tissue. <b>d: Representative immunohistochemical A20 staining of multiple myeloma samples.</b> i and ii: multiple myeloma samples with reduced A20 gene copy number. iii and iv: multiple myeloma samples with normal A20 gene copy number.</p

mRNA expression analysis of A20 and 7 NF-κB target genes (BCL2, Cyclin D1, CCR7, CD44, CXCR2, cFlip, IRF4) of MM cases with (n = 6) and without (n = 14) monoallelic A20 deletions and of non-neoplastic bone marrow biopsies (BM; n = 6).

<p>mRNA expression levels were calculated as relative expression in comparison with peripheral mononucleated cells serving as a calibrator. Each bar represents the mean values of expression levels ± standard deviation (SD). The comparison of the expression levels was performed by using the Mann-Whitney U test; all significant associations were corrected for multiple testing by applying a Bonferroni correction.</p