Analysis of the three-dimensional anatomical variance of the distal radius using 3D shape models

BACKGROUND: Various medical fields rely on detailed anatomical knowledge of the distal radius. Current studies are limited to two-dimensional analysis and biased by varying measurement locations. The aims were to 1) generate 3D shape models of the distal radius and investigate variations in the 3D shape, 2) generate and assess morphometrics in standardized cut planes, and 3) test the model's classification accuracy. METHODS: The local radiographic database was screened for CT-scans of intact radii. 1) The data sets were segmented and 3D surface models generated. Statistical 3D shape models were computed (overall, gender and side separate) and the 3D shape variation assessed by evaluating the number of modes. 2) Anatomical landmarks were assigned and used to define three standardized cross-sectional cut planes perpendicular to the main axis. Cut planes were generated for the mean shape models and each individual radius. For each cut plane, the following morphometric parameters were calculated and compared: maximum width and depth, perimeter and area. 3) The overall shape model was utilized to evaluate the predictive value (leave one out cross validation) for gender and side identification within the study population. RESULTS: Eighty-six radii (45 left, 44% female, 40 +/- 18 years) were included. 1) Overall, side and gender specific statistical 3D models were successfully generated. The first mode explained 37% of the overall variance. Left radii had a higher shape variance (number of modes: 20 female / 23 male) compared to right radii (number of modes: 6 female / 6 male). 2) Standardized cut planes could be defined using anatomical landmarks. All morphometric parameters decreased from distal to proximal. Male radii were larger than female radii with no significant side difference. 3) The overall shape model had a combined median classification probability for side and gender of 80%. CONCLUSIONS: Statistical 3D shape models of the distal radius can be generated using clinical CT-data sets. These models can be used to assess overall bone variance, define and analyze standardized cut-planes, and identify the gender of an unknown sample. These data highlight the potential of shape models to assess the 3D anatomy and anatomical variance of human bones

Disentangling cortical functional connectivity strength and topography reveals divergent roles of genes and environment

The human brain varies across individuals in its morphology, function, and cognitive capacities. Variability is particularly high in phylogenetically modern regions associated with higher order cognitive abilities, but its relationship to the layout and strength of functional networks is poorly understood. In this study we disentangled the variability of two key aspects of functional connectivity: strength and topography. We then compared the genetic and environmental influences on these two features. Genetic contribution is heterogeneously distributed across the cortex and differs for strength and topography. In heteromodal areas genes predominantly affect the topography of networks, while their connectivity strength is shaped primarily by random environmental influence such as learning. We identified peak areas of genetic control of topography overlapping with parts of the processing stream from primary areas to network hubs in the default mode network, suggesting the coordination of spatial configurations across those processing pathways. These findings provide a detailed map of the diverse contribution of heritability and individual experience to the strength and topography of functional brain architecture.Nanyang Technological UniversityPublished versionThis work was supported by the Medical University of Vienna, the Austrian Research Fund (FWF) [grants P 35189, P 34198, and I 3925-B27] in collaboration with the French National Research Agency (ANR), the Vienna Science and Technology Fund (WWTF) [LS20-065], the European Research Council Grant [866533-CORTIGRAD], the National Natural Science Foundation of China [Grant No. 81790652, No.81790650] and the NAM Advanced Biomedical Imaging Program [FY2016] between Nanyang Technological University, Singapore and Medical University of Vienna, Austria

Rule-Based Ventral Cavity Multi-organ Automatic Segmentation in CT Scans

We describe a newmethod for the automatic segmentation of multiple organs of the ventral cavity in CT scans. The methodisbasedonasetofrulesthatdeterminetheorderin which theorgansare isolatedand segmented, from the sim- plestonetothemostdifficultone. First,thebodyisisolated from the background. Second, the trachea and the left and right lungsare segmentedbasedon theirair content.Third, thespleenandthekidneys–theorganswithhighbloodcon- tent–aresegmented. Finally,thekidneyissegmentedbased onthesurroundingorganssegmentation. Eachorganisindi- vidually segmentedwitha four-stepprocedure that consists of: 1) definition of an inclusive region of interest; 2) identi- fication of the largest axial cross-section slice; 3) Semoval of background structuresbymorphologicaloperations,and; 4) 3D region growing segmentation. Ourmethod is unique in that ituses the same generic segmentation approach for all organsand in that it relieson the segmentationdifficultyof organs toguide the segmentationprocess. Experimental re- sultson15CTscansoftheVISCERALAnatomy2Challenge trainingdatasetsyieldaDicevolumeoverlapsimilarityscore of 79.1 for the trachea, 97.4 and 97.6 for the left and right lungs, 89.2 for the spleen, and 92.8 for the left kidney. For the5CT scans testdatasets, theDice scoresare97.9,97.0, 85.6, 93.4 and 90.2, respectively. Our method achieved an overallDICE score of 92.8 andwas ranked first among the fivemethodsthatparticipated inthechallenge. Copyright c © by the paper’s authors. Copying permitted only for private and academic purposes

Learning an atlas of a cognitive process in its functional geometry

Proceedings of the 22nd International Conference, IPMI 2011, Kloster Irsee, Germany, July 3-8, 2011.In this paper we construct an atlas that captures functional characteristics of a cognitive process from a population of individuals. The functional connectivity is encoded in a low-dimensional embedding space derived from a diffusion process on a graph that represents correlations of fMRI time courses. The atlas is represented by a common prior distribution for the embedded fMRI signals of all subjects. The atlas is not directly coupled to the anatomical space, and can represent functional networks that are variable in their spatial distribution. We derive an algorithm for fitting this generative model to the observed data in a population. Our results in a language fMRI study demonstrate that the method identifies coherent and functionally equivalent regions across subjects.National Science Foundation (U.S.) (IIS/CRCNS 0904625)National Science Foundation (U.S.) (CAREER grant 0642971)National Institutes of Health (U.S.) (NCRR NAC P41- RR13218)National Institute of Biomedical Imaging and Bioengineering (U.S.) (U54-EB005149)National Institutes of Health (U.S.) (U41RR019703)National Institutes of Health (U.S.) (P01CA067165)Seventh Framework Programme (European Commission) (n◦257528 (KHRESMOI)

Predicting Activation Across Individuals with Resting-State Functional Connectivity Based Multi-Atlas Label Fusion

The alignment of brain imaging data for functional neuroimaging studies is challenging due to the discrepancy between correspondence of morphology, and equivalence of functional role. In this paper we map functional activation areas across individuals by a multi-atlas label fusion algorithm in a functional space. We learn the manifold of resting-state fMRI signals in each individual, and perform manifold alignment in an embedding space. We then transfer activation predictions from a source population to a target subject via multi-atlas label fusion. The cost function is derived from the aligned manifolds, so that the resulting correspondences are derived based on the similarity of intrinsic connectivity architecture. Experiments show that the resulting label fusion predicts activation evoked by various experiment conditions with higher accuracy than relying on morphological alignment. Interestingly, the distribution of this gain is distributed heterogeneously across the cortex, and across tasks. This offers insights into the relationship between intrinsic connectivity, morphology and task activation. Practically, the mechanism can serve as prior, and provides an avenue to infer task-related activation in individuals for whom only resting data is available. Keywords: Functional Connectivity, Cortical Surface, Task Activation, Target Subject, Intrinsic ConnectivityCongressionally Directed Medical Research Programs (U.S.) (Grant PT100120)Eunice Kennedy Shriver National Institute of Child Health and Human Development (U.S.) (R01HD067312)Neuroimaging Analysis Center (U.S.) (P41EB015902)Oesterreichische Nationalbank (14812)Oesterreichische Nationalbank (15929)Seventh Framework Programme (European Commission) (FP7 2012-PIEF-GA-33003

Branching Fractions for D0 -> K+K- and D0 -> pi+pi-, and a Search for CP Violation in D0 Decays

Using the large hadroproduced charm sample collected in experiment E791 at Fermilab, we have measured ratios of branching fractions for the two-body singly-Cabibbo-suppressed charged decays of the D0: (D0 -> KK)/(D0 -> Kpi) = 0.109 +- 0.003 +- 0.003, (D0 -> pipi)/(D0 -> Kpi) = 0.040 +- 0.002 +- 0.003, and (D0 -> KK)/(D0 -> pipi) = 2.75 +- 0.15 +- 0.16. We have looked for differences in the decay rates of D0 and D0bar to the CP eigenstates K+K- and pi+pi-, and have measured the CP asymmetry parameters A_CP(K+K-) = -0.010 +- 0.049 +- 0.012 and A_CP(pi+pi-) = -0.049 +- 0.078 +- 0.030, both consistent with zero.Comment: 10 Postscript pages, including 2 figures. Submitted to Phys. Lett.

Search for Rare and Forbidden Dilepton Decays of the D+, Ds, and D0 Charmed Mesons

We report the results of a search for flavor-changing neutral current, lepton-flavor violating, and lepton-number violating decays of D+, Ds, and D0 mesons (and their antiparticles) into modes containing muons and electrons. Using data from Fermilab charm hadroproduction experiment E791, we examine the pi,l,l and K,l,l decay modes of D+ and Ds and the l+l- decay modes of D0. No evidence for any of these decays is found. Therefore, we present branching-fraction upper limits at 90% confidence level for the 24 decay modes examined. Eight of these modes have no previously reported limits, and fourteen are reported with significant improvements over previously published results.Comment: 12 pages, 3 figures, LaTeX, elsart.cls, epsf.sty, amsmath.sty Submitted to Physics Letters

Search for CP Violation in Charged D Meson Decays

We report results of a search for CP violation in the singly Cabibbo-suppressed decays D+ -> K- K+ pi+, phi pi+, K*(892)0 K+, and pi- pi+ pi+ based on data from the charm hadroproduction experiment E791 at Fermilab. We search for a difference in the D+ and D- decay rates for each of the final states. No evidence for a difference is seen. The decay rate asymmetry parameters A(CP), defined as the difference in the D+ and D- decay rates divided by the sum of the decay rates, are measured to be: A(CP)(K K pi) = -0.014 +/- 0.029, A(CP)(phi pi) = -0.028 +/- 0.036, A(CP)(K*(892) K) = -0.010 +/- 0.050, and A(CP)(pi pi pi) = -0.017 +/- 0.042.Comment: 13 pages, 5 figures, 1 table; Elsevier LaTe

Measurement of the form-factor ratios for D+ --> K* l nu

The form factor ratios rv=V(0)/A1(0), r2=A2(0)/A1(0) and r3=A3(0)/A1(0) in the decay D+ --> K* l nu, K* -->K-pi+ have been measured using data from charm hadroproduction experiment E791 at Fermilab. From 3034 (595) signal (background) events in the muon channel, we obtain rv=1.84+-0.11+-0.09, r2=0.75+-0.08+-0.09 and, as a first measurement of r3, we find 0.04+-0.33 +-0.29. The values of the form factor ratios rv and r2 measured for the muon channel are combined with the values of rv and r2 that we have measured in the electron channel. The combined E791 results for the muon and electron channels are rv=1.87+-0.08+-0.07 and r2=0.73+-0.06+-0.08.Comment: 9 pages + 3 figures ; submitted to PL