Indiana University-Purdue University Indianapolis (IUPUI) / Background: Non-cavitated caries lesions form due to acid diffusion and demineralization of enamel subsurface with an intact surface layer (SL). Caries lesions progress when the outcome of demineralization and remineralization processes over time is net mineral loss. Lesions that continue to demineralize are called active, while those that display no evidence of further demineralization are called inactive. Micro-computed-tomography (µCT) analysis provides objective non-destructive measurements of the thickness of the surface layer (SL) and severity of caries lesions. Aims: 1) To investigate if visual/tactile suspected active non-cavitated early white spot lesions present a thinner surface layer than inactive ones; 2) To investigate if there is an association between the thickness of the surface layer (SLT) and caries activity, as determined by QLF during dehydration (△QD); 3) To determine lesion severity by comparing lesion volume and maximum depth correlation with △Q value at 15 s from QLF during dehydration. Materials and Methods: Thirty extracted human premolars exhibiting non-cavitated approximal white spot early lesions stored in 0.1.-percent thymol/4C and treated with 5.0-percent NaOCl/30 min were included in the study. Fifteen active and 15 inactive lesions were determined by visual/tactile examinations by consensus of two experienced examiners. Roughness measurements (Ra) were acquired using non-contact optical profilometry. Two-dimensional minimum (2D-min), maximum (2D-max), average (2D-avg) SL and three-dimensional (3D) analyses, volume and depth of lesions were determined from µCT image analysis. A series of fluorescence images were acquired at baseline (hydrated), at 1 s, at 5 s, at 10 s and at 15 s by QLF. During image acquisition, surfaces were dehydrated with continuous-compressed-air. △Q and △Q/s (△QD) were calculated. Data were analyzed using two-sample t-tests and Pearson correlation coefficients (p < 0.05). Results: Surface roughness of active and inactive lesions was not significantly different (p > 0.08). Overall lesion volume and depth in dentin were significantly larger in active lesions (p = 0.022, p = 0.009). SL thickness of active and inactive lesions was not significantly different (2D = 0.121, 3D = 0.080, 2D-avg = 0.446, 2D-min = 0.197, 2D-max = 0.122). △QD at 1s was significantly larger for active lesions (p = 0.046). ΔQ at 15 s of dehydration had a moderate positive association with lesion volume (r = 0.56). △QD had a weak negative association with SL thickness (2D-avg) and (2D-min). Conclusions: 1) Active and inactive non-cavitated lesions show no difference in SL thickness; 2) QLF during dehydration (△QD) does not correlate well with SL thickness; 3) ΔQ at 15 s of dehydration correlates moderately well with lesion volume and is consistent with caries activity assessed by visual/tactile examination.

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Accurate measurement brain region volumes are important in studying brain plasticity, which brings insight into the fundamental mechanisms in animal, memory, cognitive, and behavior research. The traditional methods of brain volume measurements are ellipsoid or histology. In this study, micro-computed tomography (micro-CT) method was used to achieve more accurate results. However, manual segmentation of micro-CT images is time consuming, hard to reprodu-ce, and has the risk of human error. Automatic image segmentation is a faster method for obtaining the segmentations and has the potential to provide eciency, reliability, repeatability, and scalability. Different methods are tested and compared in this thesis. In this project, 29 micro-CT scans of lizard heads were used and measurements of the volumes of 6 dierent brain regions was of interest. The lizard heads were semi-manually segmented into 6 regions and three open-source segmentation algorithms were compared, one atlas-based algorithm and two deep-learning-based algorithms. Dierent number of training data were quantitatively compared for deep-learning methods from all three orientations (sagittal, horizontal and coronal). Data augmentation was tested and compared, as well. The comparison shows that the deep-learning algorithms provided more accurate results than the atlas-based algorithm. The results also demonstrated that in the sagittal plane, 5 manually segmented images for training are enough to provide resulting predictions with high accuracy (dice score 0.948). Image augmentation was shown to improve the accuracy of the segmentations but a unique dataset still plays an important role. In conclusion, the results show that the manual segmentation work can be reduced drastically by using deep learning for image segmentation. / Noggrann mätning av hjärnregionsvolymer är viktigt för att studera hjärnans plasticitet, vilket ger insikt i de grundläggande mekanismerna inom djurstudier, minnes-, kognitions- och beteendeforskning. De traditionella metoderna för mätning av hjärnvolym är ellipsoid modellen eller histologi. I den här studien användes mikrodatortomografi (mikro-CT) metoden för att få mer korrekta resultat. Manuell segmentering av mikro-CT-bilder är dock tidskrävande, svår att reproducera och har en risk för mänskliga fel. Automatisk bildsegmentering är en snabb metod för att erhålla segmenteringarna. Den har potentialen att ge eektivitet, tillförlitlighet, repeterbarhet och skalbarhet. Därför testas och jämförs tre metoder för automatisk segmentering i denna studie. I projektet användes 29 mikro-CT-bilder av ödlehuvuden för att få fram volymerna hos 6 olika hjärnregioner. Ödlehuvudena segmenterades halvmanu- ellt i 6 regioner och tre segmenteringsalgoritmer med öppen källkod jämfördes (en atlasbaserad algoritm och två djupinlärningsbaserade algoritmer). Olika antal träningsdata jämfördes kvantitativt för djupinlärningsmetoder i alla tre plan (sagittal, horisontell och frontal). Även datautökning testades och analyserades. Jämförelsen visar att djupinlärningsalgoritmerna gav mer signifikanta resultat än den atlasbaserade algoritmen. Resultaten visade även att i det sagittala planet räcker det med 5 manuellt segmenterade bilder för träning för att ge segmenteringar med hög noggrannhet (dice värde 0,948). Datautökningen har visat sig förbättra segmenteringarnas noggrannhet, men ett unikt dataset spelar fortfarande en viktig roll. Sammanfattningsvis visar resultaten att det manuella segmenteringsarbetet kan minskas drastiskt genom att använda djupinlärning för bildsegmentering.

The present work was carried out within the framework of the priority programme SPP 2045. Technical ultra–fine particle systems (< 10μm) from highly specific separation processes are to be investigated here with regard to multi–dimensional property distributions. Tomographic measurement methods allow a comprehensive 3D description of particle–discrete data sets of statistically relevant size. The focus of the work is on X–ray tomographic analysis by means of micro-computed tomography (micro–CT), which, if necessary, is extended to several size scales by including further measurement methods (nano–CT) and supplemented by suitable elemental analysis (FIB–SEM + EBSD, EDX). Two preparation methods (wax, epoxy resin) for different particle preparations are described methodically, which have already been published in a case study or are the subject of current studies in the outlook of the work. Finally, a networked multiple use of the generated data within an online particle database is shown and its application is explained using three concrete examples.:1 Outline 2 Description of Particle Properties 2.1 Integral or Class–Based Description 2.2 Particle–Discrete Description 2.2.1 2D Description 2.2.2 Full 3D Description 2.3 Multidimensional Characterization on Basis of Particle–Discrete 3D Data 2.3.1 Motivation 2.3.2 Kernel Density Approach 2.3.3 Copula Approach 3 X–ray Tomography 3.1 Historical Context 3.2 X–ray Physics 3.2.1 X–ray Generation 3.2.2 Polychromatic Spectrum 3.2.3 Interaction with Matter 3.3 Tomographic Imaging 3.3.1 Motivation 3.3.2 Basic Idea 3.3.3 X–ray Microscopy Measurement Setup andWorkflow 3.3.4 Tomographic Reconstruction via Filtered Back Projection 3.3.5 Region of Interest Tomography 3.4 Relevant Artefacts Related to Particle Measurement 3.4.1 Temperature Drift 3.4.2 Penumbral Blurring and Shadow 3.4.3 Cone Beam 3.4.4 Out–of–Field 3.4.5 Center Shift 3.4.6 Sample Drift 3.4.7 Beam Hardening 3.4.8 Rings 3.4.9 Noise 3.4.10 Partial Volume 3.4.11 Summary 4 Practical Implementation 4.1 Particle Sample Requirements 4.1.1 Geometry 4.1.2 Dispersity and Homogeneity 4.2 Statistics 4.2.1 Single Particle Properties 4.2.2 Properties of a Limited Number of Particles (10 to several 100) 4.2.3 Particle Populations with Distributed Properties 4.3 2D Validation 4.4 Measurement 4.4.1 X–ray Microscope 4.4.2 Source Filter 4.4.3 Detector Binning 4.4.4 Cone Beam Artefact Compensation 4.4.5 Center Shift Correction 4.4.6 Dynamic Ring Removal 5 Image Analysis 5.1 Image Quality 5.1.1 Grey Value Histogram 5.1.2 Resolution 5.1.3 Signal–to–Noise Ratio 5.1.4 Contrast and Dynamic Range 5.1.5 Sharpness 5.1.6 Summary 5.2 Basic Image Processing Strategies 5.2.1 Threshold–Based Segmentation 5.2.2 Machine Learning Assisted Segmentation 6 Correlative Tomography 6.1 Scouting Approach 6.2 Multiscale Approach 6.3 Multidisciplinary Approach 7 Data Management 7.1 Data Quality 7.2 Data Availability 7.2.1 Tomographic Datasets 7.2.2 Particle Database 8 Outlook on Further Research Activities 9 Publications 9.1 Copyright Declaration 9.2 Overview 9.3 List of Publications Paper A, Preparation techniques for micron–sized particulate samples in X–ray microtomography Paper B, Self–constructed automated syringe for preparation of micron–sized particulate samples in X–ray microtomography Paper C, Preparation strategy for statistically significant micrometer–sized particle systems suitable for correlative 3D imaging workflows on the example of X–ray microtomography Paper D, Multi–scale tomographic analysis for micron–sized particulate samples Paper E, PARROT: A pilot study on the open access provision of particle discrete tomographic datasets 10 Appendix 10.1 Application Example 1: Fracture Analysis 10.2 Application Example 2: 3D Contact Angle Measurement 10.3 Influence of the Source Filter 10.4 Influence of the X–rays on the Sample 10.5 Appropriate Filter Settings 10.6 Log File Parser / Die vorliegende Arbeit ist im Rahmen des Schwerpunktprogramms SPP 2045 entstanden. Technische Feinstpartikelsysteme (< 10μm) aus hochspezifischen Trennprozessen sollen hier hinsichtlich mehrdimensionaler Eigenschaftsverteilungen untersucht werden. Tomographische Messverfahren erlauben dabei eine vollständige 3D Beschreibung partikeldiskreter Datensätze statistisch relevanter Größe. Der Schwerpunkt der Arbeit liegt auf der röntgentomographischen Analyse mittels Mikro–Computertomographie (mikro–CT), die im Bedarfsfall unter Einbeziehung weiterer Messmethoden (nano–CT) auf mehrere Größenskalen erweitert und durch geeignete Elementanalytik (FIB–SEM + EBSD, EDX) ergänzt wird. Methodisch werden zwei Präparationsverfahren (Wachs, Epoxidharz) für unterschiedliche Partikelpräparate beschrieben, welche in einer Fallstudie bereits veröffentlicht bzw. im Ausblick der Arbeit Gegenstand aktueller Studien ist. Schließlich wird eine vernetzte Mehrfachnutzung der erzeugten Daten innerhalb einer online-Partikeldatenbank gezeigt und deren Anwendung an drei konkreten Beispielen erläutert.:1 Outline 2 Description of Particle Properties 2.1 Integral or Class–Based Description 2.2 Particle–Discrete Description 2.2.1 2D Description 2.2.2 Full 3D Description 2.3 Multidimensional Characterization on Basis of Particle–Discrete 3D Data 2.3.1 Motivation 2.3.2 Kernel Density Approach 2.3.3 Copula Approach 3 X–ray Tomography 3.1 Historical Context 3.2 X–ray Physics 3.2.1 X–ray Generation 3.2.2 Polychromatic Spectrum 3.2.3 Interaction with Matter 3.3 Tomographic Imaging 3.3.1 Motivation 3.3.2 Basic Idea 3.3.3 X–ray Microscopy Measurement Setup andWorkflow 3.3.4 Tomographic Reconstruction via Filtered Back Projection 3.3.5 Region of Interest Tomography 3.4 Relevant Artefacts Related to Particle Measurement 3.4.1 Temperature Drift 3.4.2 Penumbral Blurring and Shadow 3.4.3 Cone Beam 3.4.4 Out–of–Field 3.4.5 Center Shift 3.4.6 Sample Drift 3.4.7 Beam Hardening 3.4.8 Rings 3.4.9 Noise 3.4.10 Partial Volume 3.4.11 Summary 4 Practical Implementation 4.1 Particle Sample Requirements 4.1.1 Geometry 4.1.2 Dispersity and Homogeneity 4.2 Statistics 4.2.1 Single Particle Properties 4.2.2 Properties of a Limited Number of Particles (10 to several 100) 4.2.3 Particle Populations with Distributed Properties 4.3 2D Validation 4.4 Measurement 4.4.1 X–ray Microscope 4.4.2 Source Filter 4.4.3 Detector Binning 4.4.4 Cone Beam Artefact Compensation 4.4.5 Center Shift Correction 4.4.6 Dynamic Ring Removal 5 Image Analysis 5.1 Image Quality 5.1.1 Grey Value Histogram 5.1.2 Resolution 5.1.3 Signal–to–Noise Ratio 5.1.4 Contrast and Dynamic Range 5.1.5 Sharpness 5.1.6 Summary 5.2 Basic Image Processing Strategies 5.2.1 Threshold–Based Segmentation 5.2.2 Machine Learning Assisted Segmentation 6 Correlative Tomography 6.1 Scouting Approach 6.2 Multiscale Approach 6.3 Multidisciplinary Approach 7 Data Management 7.1 Data Quality 7.2 Data Availability 7.2.1 Tomographic Datasets 7.2.2 Particle Database 8 Outlook on Further Research Activities 9 Publications 9.1 Copyright Declaration 9.2 Overview 9.3 List of Publications Paper A, Preparation techniques for micron–sized particulate samples in X–ray microtomography Paper B, Self–constructed automated syringe for preparation of micron–sized particulate samples in X–ray microtomography Paper C, Preparation strategy for statistically significant micrometer–sized particle systems suitable for correlative 3D imaging workflows on the example of X–ray microtomography Paper D, Multi–scale tomographic analysis for micron–sized particulate samples Paper E, PARROT: A pilot study on the open access provision of particle discrete tomographic datasets 10 Appendix 10.1 Application Example 1: Fracture Analysis 10.2 Application Example 2: 3D Contact Angle Measurement 10.3 Influence of the Source Filter 10.4 Influence of the X–rays on the Sample 10.5 Appropriate Filter Settings 10.6 Log File Parser

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Indiana University-Purdue University Indianapolis (IUPUI) / Etching of enamel caries lesions has been demonstrated to enhance remineralization. However, this effect reaches a plateau after a period of time. This study aimed at investigating the effectiveness of additional acid etching on remineralization. Forty 1 mm × 2 mm human enamel blocks with chemically induced artificial incipient lesions were used. Ten specimens were randomly selected at the end of demineralization for transverse microradiography (TMR) analysis. The remaining specimens were then divided into three groups (n = 10). Group A was remineralized by a pH cycling system with 1100 ppm sodium fluoride for 20 days. In group B, the specimens were etched with 35-percent phosphoric acid for 30 s and then remineralized. Group C was remineralized by same procedure as group B plus and given an additional acid etch after 10 days of remineralization. Mineral density was measured by x-ray microtomography (µ-CT). The volumetric mineral content [VM (µm3×105)] was determined between 91 and 0-wt%. The µ-CT % mineral recovery (%) was calculated using the formula 100×(remineralize VM - demineralization VM) / (sound VM - demineralization VM). One-hundred-μm sections of demineralized and remineralized specimens were used to assess the mineral loss (IML: vol%×µm) and lesion depth (µm) using TMR. The three groups showed no significant difference in mineral change or mineral content for µ-CT or TMR lesion depth. The TMR IML showed a significant difference between the demineralized specimens and the three remineralized groups. The correlation between TMR IML and TMR lesion depth was 0.66 (p < 0.0001). The µ-CT percent mineral recovery from demineralization was correlated with neither TMR IML nor TMR lesion depth. When evaluated with µ-CT, the twice-acid-etched group presented lower mineral gain values than the group etched only once with acid. Also, the twice-etched group presented lower mineral gain and greater TMR IML compared with the non-acid etch group. TMR images revealed reduction of surface layer in the acid-etched groups, especially in the twice-etched group, in which significant reduction or loss of surface layer occurred. Based on these results, we conclude that additional acid etching with 35-percent phosphoric acid does not enhance remineralization compared with a single application of acid etching. We believe that the viable existence of the surface layer is essential for remineralization of the lesion. Further investigations into the accuracy of µ-CT to detect minute mineral changes in incipient caries lesions are probably needed.

Dissertation Abstract Abdominalaortic aneurysm (AAA) is a serious disease. Its prevalence is in the developed countries about 3%. As an aneurysm is considered a dilatation of all layers of a vessel wall over 3 cm. Majority of AAA are small and asymptomatic, and although the risk of rupture increases with the size of aneurysm sack, even the small aneurysms rupture. The rupture mortaliry ranges about 70 %. Surgical treatment is indicated in the asymptomatic patients in diameter of AAA over 5 cm. The average speed of growth of AAA is 0.3 cm per year, e.g. in the early diagnosed patients there is a several years interval for a pharmacolocical influencing of the progression of this disease. Knowledge of pathogenesis is essential for any targeted pharmacological treatment. Our prospective, non-randomised studies are based on the application of the stereological methods for the histopathological assessment of the AAA samples. The acquired data enable the statistical analysis, including the null hypothesis testing. In our study analyzing the histopathology of AAA aortae of 65 patients (65 walls and 55 thrombi) and 6 normal abdominal aortae from the organ donors we assessed the following parameters: the area fractions of collagen and elastin, and the length density of elastin in intima and media, the area...

The aim of the study was to investigate the effect of X-rays used in micro X-ray computer tomography (µXCT) on the mechanical performance and microstructure of a variety of dental materials. Standardised bending beams (2 × 2 × 25 mm3) were forwarded to irradiation with an industrial tomograph. Using three-dimensional datasets, the porosity of the materials was quantified and flexural strength was investigated prior to and after irradiation. The thermal properties of irradiated and unirradiated materials were analysed and compared by means of differential scanning calorimetry (DSC). Single µXCT measurements led to a significant decrease in flexural strength of polycarbonate with acrylnitril-butadien-styrol (PC-ABS). No significant influence in flexural strength was identified for resin-based composites (RBCs), poly(methyl methacrylate) (PMMA), and zinc phosphate cement (HAR) after a single irradiation by measurement. However, DSC results suggest that changes in the microstructure of PMMA are possible with increasing radiation doses (multiple measurements, longer measurements, higher output power from the X-ray tube). In summary, it must be assumed that X-ray radiation during µXCT measurement at high doses can lead to changes in the structure and properties of certain polymers.

Polymethylmethacrylate (PMMA) removal during septic total joint arthroplasty revision is associated with a high fracture and perforation risk. Ultrasonic cement removal is considered a bone-preserving technique. Currently, there is still a lack of sound data on efficacy as it is difficult to detect smaller residues with reasonable technical effort. However, incomplete removal is associated with the risk of biofilm coverage of the residue. Therefore, the study aimed to investigate the efficiency of ultrasonic-based PMMA removal in a human cadaver model. The femoral components of a total hip and a total knee prosthesis were implanted in two cadaver femoral canals by 3rd generation cement fixation technique. Implants were then removed. Cement mantle extraction was performed with the OSCAR-3-System ultrasonic system (Orthofix®). Quantitative analysis of cement residues was carried out with dual-energy and microcomputer tomography. With a 20 µm resolution, in vitro microcomputer tomography visualized tiniest PMMA residues. For clinical use, dual-energy computer tomography tissue decomposition with 0.75 mm resolution is suitable. With ultrasound, more than 99% of PMMA was removed. Seven hundred thirty-four residues with a mean volume of 0.40 ± 4.95 mm3 were identified with only 4 exceeding 1 cm in length in at least one axis. Ultrasonic cement removal of PMMA was almost complete and can therefore be considered a highly effective technique. For the first time, PMMA residues in the sub-millimetre range were detected by computer tomography. Clinical implications of the small remaining PMMA fraction on the eradication rate of periprosthetic joint infection warrants further investigations.

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