A fuzzy feature fusion method for auto-segmentation of gliomas with multi-modality diffusion and perfusion magnetic resonance images in radiotherapy

The difusion and perfusion magnetic resonance (MR) images can provide functional information about tumour and enable more sensitive detection of the tumour extent. We aimed to develop a fuzzy feature fusion method for auto-segmentation of gliomas in radiotherapy planning using multi-parametric functional MR images including apparent difusion coefcient (ADC), fractional anisotropy (FA) and relative cerebral blood volume (rCBV). For each functional modality, one histogram-based fuzzy model was created to transform image volume into a fuzzy feature space. Based on the fuzzy fusion result of the three fuzzy feature spaces, regions with high possibility belonging to tumour were generated automatically. The auto-segmentations of tumour in structural MR images were added in fnal autosegmented gross tumour volume (GTV). For evaluation, one radiation oncologist delineated GTVs for nine patients with all modalities. Comparisons between manually delineated and auto-segmented GTVs showed that, the mean volume diference was 8.69% (±5.62%); the mean Dice’s similarity coefcient (DSC) was 0.88 (±0.02); the mean sensitivity and specifcity of auto-segmentation was 0.87 (±0.04) and 0.98 (±0.01) respectively. High accuracy and efciency can be achieved with the new method, which shows potential of utilizing functional multi-parametric MR images for target defnition in precision radiation treatment planning for patients with gliomas

Water relations of evergreen and drought-deciduous trees along a seasonally dry tropical forest chronosequence

Seasonally dry tropical forests (SDTF) are characterized by pronounced seasonality in rainfall, and as a result trees in these forests must endure seasonal variation in soil water availability. Furthermore, SDTF on the northern Yucatan Peninsula, Mexico, have a legacy of disturbances, thereby creating a patchy mosaic of different seral stages undergoing secondary succession. We examined the water status of six canopy tree species, representing contrasting leaf phenology (evergreen vs. drought-deciduous) at three seral stages along a fire chronosequence in order to better understand strategies that trees use to overcome seasonal water limitations. The early-seral forest was characterized by high soil water evaporation and low soil moisture, and consequently early-seral trees exhibited lower midday bulk leaf water potentials (ΨL) relative to late-seral trees (−1.01 ± 0.14 and −0.54 ± 0.07 MPa, respectively). Although ΨL did not differ between evergreen and drought-deciduous trees, results from stable isotope analyses indicated different strategies to overcome seasonal water limitations. Differences were especially pronounced in the early-seral stage where evergreen trees had significantly lower xylem water δ18O values relative to drought-deciduous trees (−2.6 ± 0.5 and 0.3 ± 0.6‰, respectively), indicating evergreen species used deeper sources of water. In contrast, drought-deciduous trees showed greater enrichment of foliar 18O (∆18Ol) and 13C, suggesting lower stomatal conductance and greater water-use efficiency. Thus, the rapid development of deep roots appears to be an important strategy enabling evergreen species to overcome seasonal water limitation, whereas, in addition to losing a portion of their leaves, drought-deciduous trees minimize water loss from remaining leaves during the dry season

Analyzing the Impacts of Dams on Riparian Ecosystems: A Review of Research Strategies and Their Relevance to the Snake River Through Hells Canyon

River damming provides a dominant human impact on river environments worldwide, and while local impacts of reservoir flooding are immediate, subsequent ecological impacts downstream can be extensive. In this article, we assess seven research strategies for analyzing the impacts of dams and river flow regulation on riparian ecosystems. These include spatial comparisons of (1) upstream versus downstream reaches, (2) progressive downstream patterns, or (3) the dammed river versus an adjacent free-flowing or differently regulated river(s). Temporal comparisons consider (4) pre- versus post-dam, or (5) sequential post-dam conditions. However, spatial comparisons are complicated by the fact that dams are not randomly located, and temporal comparisons are commonly limited by sparse historic information. As a result, comparative approaches are often correlative and vulnerable to confounding factors. To complement these analyses, (6) flow or sediment modifications can be implemented to test causal associations. Finally, (7) process-based modeling represents a predictive approach incorporating hydrogeomorphic processes and their biological consequences. In a case study of Hells Canyon, the upstream versus downstream comparison is confounded by a dramatic geomorphic transition. Comparison of the multiple reaches below the dams should be useful, and the comparison of Snake River with the adjacent free-flowing Salmon River may provide the strongest spatial comparison. A pre- versus post-dam comparison would provide the most direct study approach, but pre-dam information is limited to historic reports and archival photographs. We conclude that multiple study approaches are essential to provide confident interpretations of ecological impacts downstream from dams, and propose a comprehensive study for Hells Canyon that integrates multiple research strategies

Diffusion and perfusion weighted magnetic resonance imaging for tumor volume definition in radiotherapy of brain tumors

Abstract Accurate target volume delineation is crucial for the radiotherapy of tumors. Diffusion and perfusion magnetic resonance imaging (MRI) can provide functional information about brain tumors, and they are able to detect tumor volume and physiological changes beyond the lesions shown on conventional MRI. This review examines recent studies that utilized diffusion and perfusion MRI for tumor volume definition in radiotherapy of brain tumors, and it presents the opportunities and challenges in the integration of multimodal functional MRI into clinical practice. The results indicate that specialized and robust post-processing algorithms and tools are needed for the precise alignment of targets on the images, and comprehensive validations with more clinical data are important for the improvement of the correlation between histopathologic results and MRI parameter images