A semiautomatic CT-based ensemble segmentation of lung tumors: Comparison with oncologists’ delineations and with the surgical specimen

AbstractPurposeTo assess the clinical relevance of a semiautomatic CT-based ensemble segmentation method, by comparing it to pathology and to CT/PET manual delineations by five independent radiation oncologists in non-small cell lung cancer (NSCLC).Materials and methodsFor 20 NSCLC patients (stages Ib–IIIb) the primary tumor was delineated manually on CT/PET scans by five independent radiation oncologists and segmented using a CT based semi-automatic tool. Tumor volume and overlap fractions between manual and semiautomatic-segmented volumes were compared. All measurements were correlated with the maximal diameter on macroscopic examination of the surgical specimen. Imaging data are available on www.cancerdata.org.ResultsHigh overlap fractions were observed between the semi-automatically segmented volumes and the intersection (92.5±9.0, mean±SD) and union (94.2±6.8) of the manual delineations. No statistically significant differences in tumor volume were observed between the semiautomatic segmentation (71.4±83.2cm3, mean±SD) and manual delineations (81.9±94.1cm3; p=0.57). The maximal tumor diameter of the semiautomatic-segmented tumor correlated strongly with the macroscopic diameter of the primary tumor (r=0.96).ConclusionsSemiautomatic segmentation of the primary tumor on CT demonstrated high agreement with CT/PET manual delineations and strongly correlated with the macroscopic diameter considered as the “gold standard”. This method may be used routinely in clinical practice and could be employed as a starting point for treatment planning, target definition in multi-center clinical trials or for high throughput data mining research. This method is particularly suitable for peripherally located tumors

Shear-wave velocity structure beneath the Dinarides from the inversion of Rayleigh-wave dispersion

Highlights • Rayleigh-wave phase velocity in the wider Dinarides region using the two-station method. • Uppermost mantle shear-wave velocity model of the Dinarides-Adriatic Sea region. • Velocity model reveals a robust high-velocity anomaly present under the whole Dinarides. • High-velocity anomaly reaches depth of 160 km in the northern Dinarides to more than 200 km under southern Dinarides. • New structural model incorporating delamination as one of the processes controlling the continental collision in the Dinarides. The interaction between the Adriatic microplate (Adria) and Eurasia is the main driving factor in the central Mediterranean tectonics. Their interplay has shaped the geodynamics of the whole region and formed several mountain belts including Alps, Dinarides and Apennines. Among these, Dinarides are the least investigated and little is known about the underlying geodynamic processes. There are numerous open questions about the current state of interaction between Adria and Eurasia under the Dinaric domain. One of the most interesting is the nature of lithospheric underthrusting of Adriatic plate, e.g. length of the slab or varying slab disposition along the orogen. Previous investigations have found a low-velocity zone in the uppermost mantle under the northern-central Dinarides which was interpreted as a slab gap. Conversely, several newer studies have indicated the presence of the continuous slab under the Dinarides with no trace of the low velocity zone. Thus, to investigate the Dinaric mantle structure further, we use regional-to-teleseismic surface-wave records from 98 seismic stations in the wider Dinarides region to create a 3D shear-wave velocity model. More precisely, a two-station method is used to extract Rayleigh-wave phase velocity while tomography and 1D inversion of the phase velocity are employed to map the depth dependent shear-wave velocity. Resulting velocity model reveals a robust high-velocity anomaly present under the whole Dinarides, reaching the depths of 160 km in the north to more than 200 km under southern Dinarides. These results do not agree with most of the previous investigations and show continuous underthrusting of the Adriatic lithosphere under Europe along the whole Dinaric region. The geometry of the down-going slab varies from the deeper slab in the north and south to the shallower underthrusting in the center. On-top of both north and south slabs there is a low-velocity wedge indicating lithospheric delamination which could explain the 200 km deep high-velocity body existing under the southern Dinarides

Crustal Thinning From Orogen to Back-Arc Basin: The Structure of the Pannonian Basin Region Revealed by P-to-S Converted Seismic Waves

We present the results of P-to-S receiver function analysis to improve the 3D image of the sedimentary layer, the upper crust, and lower crust in the Pannonian Basin area. The Pannonian Basin hosts deep sedimentary depocentres superimposed on a complex basement structure and it is surrounded by mountain belts. We processed waveforms from 221 three-component broadband seismological stations. As a result of the dense station coverage, we were able to achieve so far unprecedented spatial resolution in determining the velocity structure of the crust. We applied a three-fold quality control process; the first two being applied to the observed waveforms and the third to the calculated radial receiver functions. This work is the first comprehensive receiver function study of the entire region. To prepare the inversions, we performed station-wise H-Vp/Vs grid search, as well as Common Conversion Point migration. Our main focus was then the S-wave velocity structure of the area, which we determined by the Neighborhood Algorithm inversion method at each station, where data were sub-divided into back-azimuthal bundles based on similar Ps delay times. The 1D, nonlinear inversions provided the depth of the discontinuities, shear-wave velocities and Vp/Vs ratios of each layer per bundle, and we calculated uncertainty values for each of these parameters. We then developed a 3D interpolation method based on natural neighbor interpolation to obtain the 3D crustal structure from the local inversion results. We present the sedimentary thickness map, the first Conrad depth map and an improved, detailed Moho map, as well as the first upper and lower crustal thickness maps obtained from receiver function analysis. The velocity jump across the Conrad discontinuity is estimated at less than 0.2 km/s over most of the investigated area. We also compare the new Moho map from our approach to simple grid search results and prior knowledge from other techniques. Our Moho depth map presents local variations in the investigated area: the crust-mantle boundary is at 20–26 km beneath the sedimentary basins, while it is situated deeper below the Apuseni Mountains, Transdanubian and North Hungarian Ranges (28–33 km), and it is the deepest beneath the Eastern Alps and the Southern Carpathians (40–45 km). These values reflect well the Neogene evolution of the region, such as crustal thinning of the Pannonian Basin and orogenic thickening in the neighboring mountain belts

Verfahren zur Identifizierung von Genen eines bestimmten Phänotyps

Preface Abstract i Acknowledgement ii Contents iii List of Figures v List of Tables vi Abbreviations vii 1 Introduction 1 1.1 Knowledge Discovery in Databases 1 1.2 Biological Background 4 1.2.1 Central Dogma of Molecular Biology 4 1.2.2 Gene Expression 7 1.3 Biological Challenge 7 1.3.1 Common Denominator Concept 8 1.3.2 Phenotype Angiogenesis 9 1.4 Outline 10 2 System and Methods 12 2.1 Infrastructure 12 2.2 Data Sources 13 2.2.1 Adaptation to CGAP Expression Data 13 2.2.2 Definition of the IndicatorGeneSet 14 2.2.3 Definition of the AngioTestGroup 14 2.3 Common Denominator Procedure (CDP) 15 2.3.1 Generation of the LibraryProfile 17 2.3.2 Calculation of the GeneScore 20 2.3.3 Control Profiles 22 2.3.4 Definition of AngioProfiles 23 2.3.5 Selection of Candidate Genes 23 2.4 XantoScreen 25 2.4.1 HUVEC Proliferation High Throughput Screening Assay 27 3 Results 29 3.1 Basic CDP 30 3.1.1 Definition of Input Data 30 3.1.2 Determination of the LibraryProfile 32 3.1.3 Determination of the GeneScore 32 3.1.4 Selection of Candidate Genes 33 3.1.5 Procedure Control and Validation 33 3.2 Genetic Algorithm Based CDP 37 3.2.1 Definition of Input Data 37 3.2.2 Determination of the LibraryProfile 39 3.2.3 Determination of the GeneScore 39 3.2.4 Selection of Candidate Genes 39 3.2.5 Procedure Control and Validation 40 3.3 Indicator Genes Based CDP 43 3.3.1 Definition of Input Data 43 3.3.2 Determination of the LibraryProfile 45 3.3.3 Determination of the GeneScore 45 3.3.4 Selection of AngioProfiles 46 3.3.5 Selection of Candidate Genes 46 3.3.6 Procedure Control and Validation 48 3.4 Summary 53 3.4.1 Internal Procedure Control 54 3.4.2 Procedure Validation - Experimental 55 3.4.3 Procedure Validation - Literature 56 4 Discussion 57 4.1 Comparison of the Procedures 58 4.2 Comparison to Established Procedures 60 4.3 Extensibility 61 4.4 Future Perspective 63 Appendix 66 References 66 A Data Sources 75 B Implementation 78 C Anhang gemäß Promotionsordnung 80 C.1 Erklärung 80 C.2 Lebenslauf 81 C.3 Zusammenfassung 82This thesis addresses the gap between the amount of on-hand expression data and the availability of information related to the function of those genes. To this end, a data mining procedure for the identification of genes that are associated with pre-defined phenotypes and/or molecular pathways was established. Based on the observation that pathway/phenotype associated genes are frequently expressed in same or nearby places and at identical or similar time points, an approach termed Common Denominator Procedure (CDP) was devised. One unique feature of this novel approach is that the specificity and probability to identify desired phenotype/pathway-associated factors increases the more diverse the input data are. Three different approaches are discussed and compared: (i) a basic CDP, (ii) a genetic algorithm based CDP and (iii) an indicator genes based CDP. To show the feasibility of these approaches, the CGAP Expression Data combined with a defined set of angiogenic factors was used to identify additional and novel angiogenesis-associated genes. A multitude of these additional genes were known to be associated with angiogenesis according to published data, verifying the approach. Application of a high throughput functional genomics platform (XantoScreen(tm)) provided further experimental evidence for association of candidate genes with angiogenesis.Die vorliegende Arbeit handelt von einem Data Mining Verfahren zur Identifizierung von Genen eines bestimmten Regelkreises bzw. Phänotyps. Das Common Denominator Procedure (CDP) genannte Verfahren basiert auf der Beobachtung, dass Gene, die mit einem bestimmten Pathway/Phänotyp assoziiert sind, häufig zum selben Zeitpunkt am selben Ort exprimiert sind. Eine außergewöhnliche Eigenschaft dieses neuen Verfahrens, im Gegensatz zu bereits bekannten, ist, dass die Spezifität und Wahrscheinlichkeit die gesuchten Pathway/Phänotyp assoziierten Faktoren zu identifizieren mit der Diversität der Eingangsdaten wächst. Es werden drei unterschiedliche Vorgehensweisen diskutiert und miteinander verglichen: (i) elementares CDP, (ii) genetischer Algorithmus basiertes CDP und (iii) Indikatorgen basiertes CDP. CGAP Expressionsdaten wurden zusammen mit einer definierten Testgruppe angiogenetischer Faktoren benutzt, zur Identifizierung neuer mit Angiogenese- assoziierter Gene. Die Anreicherung von Angiogenese-spezifischen Genen in den resultierenden Kandidatenlisten wurden mit Hilfe (a) der Anreicherung von Genen aus der Testgruppe, (b) der Präsenz von zusätzlichen Genen, deren Angiogenesemodulation bereits beschreiben wurde, und (c) der Präsenz von experimentell validierten Genen, deren Assoziation mit Angiogenese bisher unbekannt war, bewertet. Für alle genannten CDPs konnte eine relevante Anreicherung von Angiogenese assoziierten Genen gezeigt werden. Das beschriebene Verfahren kann leicht auf andere Pathways/Phänotypen angewandt werden, indem entsprechende TestGruppen, bzw. Indikatorgene definiert werden. Darüber hinaus ist das Verfahren nicht auf CGAP Expressionsdaten beschränkt. Information über die Präsenz von Genen in bestimmten Gewebeproben, wie sie neben EST und SAGE Daten auch RT-PCR, QPCR, Northern Blot und Mikroarray Analysen liefern, ist ausreichend für das CDP. Auf Grund der hohen Spezifität ist das CDP als primärer Screen zur Identifizierung von Targets geeignet. Außerdem kann es mit genomweiten funktionellen Analysetechniken kombiniert werden, um Targets für die Diagnose und Therapie humaner Krankheiten zu finden

The higher taxonomic nomenclature of Devonian to Cretaceous ammonoids and Jurassic to Cretaceous ammonites including their authorship and publication

For the taxon comprising all Devonian to Cretaceous ammonoids, a variety of conflicting names with different authorship and taxonomic rank are available and have been repeatedly cited. Here, we review the primary literature and suggest the appropriate name, authorship and date of publication; we suggest the rank of a superorder for the ammonoids. The monophylum including all Devonian to Cretaceous ammonoids is here called Ammonoida. For the traditional suborder Ammonitina comprising Jurassic and Cretaceous forms the taxonomic rank of an order named Ammonitida is suggested to match the ranking of Palaeozoic ammonoid groups. Although the International Rules of Zoological Nomenclature only cover categories from subspecies to superfamily levels, similar procedures are applied to the higher taxonomic categories described here in order to avoid further inconsistencies in cephalopod taxonomy. Schlagworte - Ammonitida • Ammonitina • Ammonoidea • Ammonacea • Ammonidae • Ammonitae • Ammonitidae • Ammonoides • Devonian to Cretaceou

Estimating [

Context. Gaia Data Release 3 will contain more than a billion sources with positions, parallaxes, and proper motions. In addition, for hundreds of millions of stars, it will include low-resolution blue photometer (BP) and red photometer (RP) spectra. Obtained by dispersing light with prisms, these spectra have resolutions that are too low to allow us to measure individual spectral lines and bands. However, the combined BP/RP spectra can be used to estimate some stellar properties such as Teff, log g, and [M/H]. Aims. We investigate the feasibility of using the ExtraTrees algorithm to estimate the alpha element to iron abundance ratio [α/Fe] from low-resolution BP/RP spectra. Methods. To infer [α/Fe] from the spectra, we created regression models using the ExtraTrees algorithm trained on two samples: a set of synthetic spectra and a set of observed spectra from stars that have known [α/Fe] since they have also been observed using the High Efficiency and Resolution Multi-Element Spectrograph (HERMES) as part of the Galactic Archaeology with HERMES survey. We applied each model to the other sample and to a larger observed sample to assess the performance of the models. In addition, we used our models to analyse stars from the Gaia-Enceladus structure. Results. We find that the model trained on synthetic data has some ability to reconstruct [α/Fe] from synthetic spectra, but little to none when used on observed spectra. The model trained on observed data reconstructs realistic [α/Fe] from observed spectra, but only for cool stars (⪅5000 K) that have the same correlations as in the training sample between [α/Fe] and other properties such as [Fe/H]. Conclusions. Models using the ExtraTrees algorithm can be used to estimate [α/Fe] from low-resolution BP/RP spectra of cool stars. However, they do this by exploiting correlations between [α/Fe] and other parameters, rather than the causal effect of [α/Fe] on the spectrum. Hence, they are unlikely to be useful in studies that attempt to distinguish stars that only differ in [α/Fe]

Calculated Vogel number for each specimen used in this study.

<p>Vogel number is calculated as the square root of the surface area of the chamber divided by the cube root of the volume of the chamber. Linearizing these values allow direct comparisons between the two while removing scaling effects due to size. It is important to note that the difference between ammonites and <i>S</i>. <i>spirula</i> in early ontogeny exists even when corrected for size. The high values shown by the early chambers of <i>A</i>. <i>scrobiculatus</i> may be an artifact due to resolution and should be interpreted with care.</p

The Evolution and Development of Cephalopod Chambers and Their Shape - Fig 2

<p>A) Comparison between the surface area to volume ratio (SA_C:V_C) of each segmented chamber against chamber number for all specimens. B) SA_C:V_C against shell diameter at each chamber for <i>A</i>. <i>scrobiculatus</i>, <i>S</i>. <i>spirula</i>, <i>Arnsbergites</i> sp., <i>Amauroceras</i> sp., and <i>Kosmoceras</i> sp. SA_C:V_C is a parameter that reflects the capacity of the shell to compensate for potential buoyancy changes due to the water storing, organic lining in each chamber (Kroger, 2002). Chamber volume (C) and chamber surface area (D) comparisons between <i>S</i>. <i>spirula</i> and selected ammonoids. <i>A</i>. <i>scrobiculatus</i> and <i>N</i>. <i>pompilius</i> have an overall larger volume and surface area due to the much larger size of the animal, maximum diameter is an order of magnitude larger than <i>S</i>. <i>spirula</i> or <i>Kosmoceras</i>. Comparison between <i>S</i>. <i>spirula</i> and the ammonoids is a comparison between extreme morphologies as <i>S</i>. <i>spirula</i> has a whorl interspace, conservative shell cross-section through ontogeny and simple sutures while ammonoids have overlapping whorls, more complex septa (complexity changes through ontogeny), and variable conch morphology and ornamentation. Hm is the potential hatching point, Pa is the pathological chamber, TC is the terminal countdown.</p