Application of the specular and diffuse reflection analysis for in vitro diagnostics of dental erosion: correlation with enamel softening, roughness, and calcium release

We present assembly and application of an optical reflectometer for the analysis of dental erosion. The erosive procedure involved acid-induced softening and initial substance loss phases, which are considered to be difficult for visual diagnosis in a clinic. Change of the specular reflection signal showed the highest sensitivity for the detection of the early softening phase of erosion among tested methods. The exponential decrease of the specular reflection intensity with erosive duration was compared to the increase of enamel roughness. Surface roughness was measured by optical analysis, and the observed tendency was correlated with scanning electron microscopy images of eroded enamel. A high correlation between specular reflection intensity and measurement of enamel softening (r(2) ? -0.86) as well as calcium release (r(2) ? -0.86) was found during erosion progression. Measurement of diffuse reflection revealed higher tooth-to-tooth deviation in contrast to the analysis of specular reflection intensity and lower correlation with other applied methods (r(2) = 0.42-0.48). The proposed optical method allows simple and fast surface analysis and could be used for further optimization and construction of the first noncontact and cost-effective diagnostic tool for early erosion assessment in vivo.

Fully Automatic Segmentation of Brain Tumor Images using Support Vector Machine Classiffication in Combination with Hierarchical Conditional Random Field Regularization

Delineating brain tumor boundaries from magnetic resonance images is an essential task for the analysis of brain cancer. We propose a fully automatic method for brain tissue segmentation, which combines Support Vector Machine classification using multispectral intensities and textures with subsequent hierarchical regularization based on Conditional Random Fields. The CRF regularization introduces spatial constraints to the powerful SVM classification, which assumes voxels to be independent from their neighbors. The approach first separates healthy and tumor tissue before both regions are subclassified into cerebrospinal fluid, white matter, gray matter and necrotic, active, edema region respectively in a novel hierarchical way. The hierarchical approach adds robustness and speed by allowing to apply different levels of regularization at different stages. The method is fast and tailored to standard clinical acquisition protocols. It was assessed on 10 multispectral patient datasets with results outperforming previous methods in terms of segmentation detail and computation times.

Mastitis diagnostics: quantitative PCR for Staphylococcus aureus genotype B in bulk tank milk

A novel real-time quantitative PCR assay for detecting the pathogenic and contagious Staphylococcus aureus genotype B (GTB) in bulk tank milk was developed and evaluated. The detection of this pathogen in bulk tank milk would greatly facilitate its control, as it is responsible for great economic loss in Swiss dairy herds. The assay is based on the simultaneous detection of 3 GTB-typical target sequences, including 2 enterotoxin genes and a polymorphism within the leucotoxin E gene. A variety of mastitis-associated bacteria was used to validate the assays, resulting in an analytical specificity of 100% and high repeatability. The analytical sensitivity in milk was 40 cfu/mL. An exponential association between simulated cow prevalence and quantitative PCR result was observed. An initial field study revealed 1 GTB-positive herd among the 33 studied herds. This novel assay for bulk tank milk analysis is suitable for routine purposes and is expected to be an effective tool for minimizing Staph. aureus GTB in Swiss dairy herds.

Tumor classification of six common cancer types based on proteomic profiling by MALDI imaging

In clinical diagnostics, it is of outmost importance to correctly identify the source of a metastatic tumor, especially if no apparent primary tumor is present. Tissue-based proteomics might allow correct tumor classification. As a result, we performed MALDI imaging to generate proteomic signatures for different tumors. These signatures were used to classify common cancer types. At first, a cohort comprised of tissue samples from six adenocarcinoma entities located at different organ sites (esophagus, breast, colon, liver, stomach, thyroid gland, n = 171) was classified using two algorithms for a training and test set. For the test set, Support Vector Machine and Random Forest yielded overall accuracies of 82.74 and 81.18%, respectively. Then, colon cancer liver metastasis samples (n = 19) were introduced into the classification. The liver metastasis samples could be discriminated with high accuracy from primary tumors of colon cancer and hepatocellular carcinoma. Additionally, colon cancer liver metastasis samples could be successfully classified by using colon cancer primary tumor samples for the training of the classifier. These findings demonstrate that MALDI imaging-derived proteomic classifiers can discriminate between different tumor types at different organ sites and in the same site.

[Aortic aneurysms and aortic dissection : Epidemiology, pathophysiology and diagnostics.]

Aortic aneurysms and aortic dissection represent a significant health risk due to the demographic developments and current life styles. The mortality of ruptured aortic aneurysms is up to 80 % and the prevalence of aneurysms varies depending on the localization (thoracic or abdominal). Most commonly affected is the infrarenal abdominal aorta; however, there is evidence that the prevalence is diminishing but in contrast the incidence of thoracic aortic aneurysms is increasing. Aortic dissection is often fatal and is the most common acute aortic disease but the incidence is presumed to be underestimated. The pathogenesis of aortic aneurysms is manifold and is based on an interplay between degenerative, proteolytic and inflammatory processes. An aortic dissection arises from a tear in the intima which results in a separation of the aortic wall layers with infiltration of bleeding and the danger of aortic rupture. Various genetic disorders of connective tissue promote degeneration of the aortic media, most notably Marfan syndrome. Risk factors for aortic aneurysms and aortic dissection are nicotine abuse, arterial hypertension, age and male gender. Aortic aneurysms initially have an uneventful course and as a consequence are mostly discovered incidentally. The clinical course and symptoms of aortic dissection are very much dependent on the section of the aorta affected and the manifestations are manifold. Acute aortic dissection is in 80 % of cases first manifested as sudden extremely severe pain. The diagnostics and subsequent course control can be achieved by a variety of imaging procedures but the modality of choice is computed tomography.

[SPECT/CT diagnostics for skeletal infections]

CLINICAL/METHODICAL ISSUE: Skeletal infections are often a diagnostic and clinical challenge. STANDARD RADIOLOGICAL METHODS: Nuclear imaging modalities used in the diagnostic workup of acute and chronic skeletal infections include three-phase bone scintigraphy and scintigraphy with labelled leucocytes. METHODICAL INNOVATIONS: The introduction of hybrid technologies, such as single photon emission computed tomography/computed tomography (SPECT/CT) has dramatically changed nuclear medical imaging of infections. PERFORMANCE: In general SPECT/CT leads to a considerably more accurate diagnosis than planar or SPECT imaging. ACHIEVEMENTS: Given the integrated acquisition of metabolic, functional and morphological information, SPECT/CT has increased in particular the specificity of three-phase skeletal scanning and scintigraphy with labeled leucocytes.

Generalized eMC implementation for Monte Carlo dose calculation of electron beams from different machine types

The electron Monte Carlo (eMC) dose calculation algorithm available in the Eclipse treatment planning system (Varian Medical Systems) is based on the macro MC method and uses a beam model applicable to Varian linear accelerators. This leads to limitations in accuracy if eMC is applied to non-Varian machines. In this work eMC is generalized to also allow accurate dose calculations for electron beams from Elekta and Siemens accelerators. First, changes made in the previous study to use eMC for low electron beam energies of Varian accelerators are applied. Then, a generalized beam model is developed using a main electron source and a main photon source representing electrons and photons from the scattering foil, respectively, an edge source of electrons, a transmission source of photons and a line source of electrons and photons representing the particles from the scrapers or inserts and head scatter radiation. Regarding the macro MC dose calculation algorithm, the transport code of the secondary particles is improved. The macro MC dose calculations are validated with corresponding dose calculations using EGSnrc in homogeneous and inhomogeneous phantoms. The validation of the generalized eMC is carried out by comparing calculated and measured dose distributions in water for Varian, Elekta and Siemens machines for a variety of beam energies, applicator sizes and SSDs. The comparisons are performed in units of cGy per MU. Overall, a general agreement between calculated and measured dose distributions for all machine types and all combinations of parameters investigated is found to be within 2% or 2 mm. The results of the dose comparisons suggest that the generalized eMC is now suitable to calculate dose distributions for Varian, Elekta and Siemens linear accelerators with sufficient accuracy in the range of the investigated combinations of beam energies, applicator sizes and SSDs.