A multi-center study: Intra-scan and inter-scan variability of diffusion spectrum imaging

The objective of this study was to investigate whether it is possible to pool together diffusion spectrum imaging data from four different scanners, located at three different sites. Two of the scanners had identical configuration whereas two did not. To measure the variability, we extracted three scalar maps (ADC, FA and GFA) from the DSI and utilized a region and a tract-based analysis. Additionally, a phantom study was performed to rule out some potential factors arising from the scanner performance in case some systematic bias occurred in the subject study. This work was split into three experiments: intra-scanner reproducibility, reproducibility with twin-scanner settings and reproducibility with other configurations. Overall for the intra-scanner and twin-scanner experiments, the region-based analysis coefficient of variation (CV) was in a range of 1%-4.2% and below 3% for almost every bundle for the tract-based analysis. The uncinate fasciculus showed the worst reproducibility, especially for FA and GFA values (CV 3.7-6%). For the GFA and FA maps, an ICC value of 0.7 and above is observed in almost all the regions/tracts. Looking at the last experiment, it was found that there is a very high similarity of the outcomes from the two scanners with identical setting. However, this was not the case for the two other imagers. Given the fact that the overall variation in our study is low for the imagers with identical settings, our findings support the feasibility of cross-site pooling of DSI data from identical scanners.

Late Weichselian local ice dome configuration and chronology in Northwestern Svalbard: early thinning, late retreat

The chronology and configuration of the Svalbard Barents Sea Ice Sheet (SBSIS) during the Late Weichselian (LW) are based on few and geographically scattered data. Thus, the timing and configuration of the SBSIS has been a subject of extensive debate. We present provenance data of erratic boulders and cosmogenic 10Be ages of bedrock and boulders from Northwest Spitsbergen (NWS), Svalbard to determine the thickness, configuration and chronology during the LW. We sampled bedrock and boulders of mountain summits and summit slopes, along with erratic boulders from coastal locations around NWS. We suggest that a local ice dome over central NWS during LW drained radially in all directions. Provenance data from erratic boulders from northern coastal lowland Reinsdyrflya suggest northeastward ice flow through Liefdefjorden. 10Be ages of high-elevation erratic boulders in central NWS (687–836 m above sea level) ranging from 18.3 ± 1.3 ka to 21.7 ± 1.4 ka, indicate that the centre of a local ice dome was at least 300 m thicker than at present. 10Be ages of all high-elevation erratics (>400 m above sea level, central and coastal locations) indicate the onset of ice dome thinning at 25–20 ka. 10Be ages from erratic boulders on Reinsdyrflya ranging from 11.1 ± 0.8 ka to 21.4 ± 1.7 ka, indicate an ice cover over the entire Reinsdyrflya during LW and a complete deglaciation prior to the Holocene, but apparently later than the thinning in the mountains. Lack of moraine deposits, but the preservation of beach terraces, suggest that the ice covering this peninsula possibly was cold-based and that Reinsdyrflya was part of an inter ice-stream area covered by slow-flowing ice, as opposed to the adjacent fjord, which possibly was filled by a fast-flowing ice stream. Despite the early thinning of the ice sheet (25–20 ka) we find a later timing of deglaciation of the fjords and the distal lowlands. Several bedrock samples (10Be) from vertical transects in the central mountains of NWS pre-date the LW, and suggest either ice free or pervasive cold-based ice conditions. Our reconstruction is aligned with the previously suggested hypothesis that a complex multi-dome ice-sheet-configuration occupied Svalbard and the Barents Sea during LW, with numerous drainage basins feeding fast ice streams, separated by slow flowing, possibly cold-based, inter ice-stream areas.

Automatic multi-resolution shape modeling of multi-organ structures.

Point Distribution Models (PDM) are among the most popular shape description techniques and their usefulness has been demonstrated in a wide variety of medical imaging applications. However, to adequately characterize the underlying modeled population it is essential to have a representative number of training samples, which is not always possible. This problem is especially relevant as the complexity of the modeled structure increases, being the modeling of ensembles of multiple 3D organs one of the most challenging cases. In this paper, we introduce a new GEneralized Multi-resolution PDM (GEM-PDM) in the context of multi-organ analysis able to efficiently characterize the different inter-object relations, as well as the particular locality of each object separately. Importantly, unlike previous approaches, the configuration of the algorithm is automated thanks to a new agglomerative landmark clustering method proposed here, which equally allows us to identify smaller anatomically significant regions within organs. The significant advantage of the GEM-PDM method over two previous approaches (PDM and hierarchical PDM) in terms of shape modeling accuracy and robustness to noise, has been successfully verified for two different databases of sets of multiple organs: six subcortical brain structures, and seven abdominal organs. Finally, we propose the integration of the new shape modeling framework into an active shape-model-based segmentation algorithm. The resulting algorithm, named GEMA, provides a better overall performance than the two classical approaches tested, ASM, and hierarchical ASM, when applied to the segmentation of 3D brain MRI.