Undulation Index Research Articles

Discriminators of Paraclinoid Aneurysm Rupture Based On Morphological Computer-Assisted Semiautomated Measurement (CASAM) and Hemodynamic Analysis.

Paraclinoid aneurysms, arising from the proximal dural ring and extending to the origin of the posterior communicating artery of the internal carotid artery (ICA), represent asignificant proportion of all intracranial aneurysms (IAs). Accurate prediction of the rupture risk of paraclinoid aneurysms is crucial for optimal management. The objective of this study was to identify risk factors for the rupture of paraclinoid aneurysms on the basis of computer-assisted semiautomated measurement (CASAM) and hemodynamics. The clinical, demographic and radiological data of the 304 paraclinoid aneurysms (285 unruptured and 19 ruptured) included were extracted from the Chinese Intracranial Aneurysm Project (CIAP) database. Morphological parameters were quantified via CASAM, and hemodynamic simulations were performed via computational fluid dynamics (CFD). Univariate and multivariate logistic regression analyses were conducted to identify independent risk factors for aneurysm rupture. The mean age of the patients was 56.91 ± 11.0 years, with afemale predominance (71.7%). Univariate analysis revealed that the undulation index (UI) and nonsphericity index (NSI) were significantly greater in ruptured paraclinoid aneurysms than in unruptured aneurysms. The proportion of ruptured paraclinoid aneurysms located laterally on the ICA was significantly lower than that of those located anteriorly (p = 0.002). Multivariate logistic regression analysis revealed that agreater UI (OR = 1.086, 95% CI 1.012-1.165; p = 0.022) and larger low shear area (LSA) (OR = 1.034, 95% CI 1.004-1.064; p = 0.028) were independent risk factors for rupture. Our findings indicate that agreater UI and alarger LSA are independent risk factors for the rupture of paraclinoid aneurysms. Compared with aneurysms in other orientations, paraclinoid aneurysms located anteriorly to the ICA are more prone to rupture. These findings may be useful in developing more consummate predictive models to enhance the management and surveillance of paraclinoid aneurysms in the future, leading to improved clinical decision-making and better patient outcomes.

Association Between Baseline Macular Morphologic Features on Optical Coherence Tomography and Visual Outcomes in Patients with Vogt-Koyanagi-Harada Disease.

The choroidal thickening and serous retinal detachments that characterize Vogt-Koyanagi-Harada (VKH) disease can be imaged in detail using spectral domain optical coherence tomography (SD-OCT). Whether specific qualitative and quantitative SD-OCT features at presentation were associated with visual outcomes in a randomized controlled trial comparing methotrexate to mycophenolate for steroid-sparing control of uveitis were evaluated. An exploratory subanalysis of data from the FAST trial in which SD-OCT images from VKH participants were analyzed for presence/absence of bacillary detachments, retinal pigment epithelium (RPE) folds, and internal limiting membrane (ILM) fluctuations was performed. A modified RPE undulation index was calculated to provide a quantifiable surrogate marker for choroidal folds. SD-OCT images were available from 158 eyes with VKH. At baseline, bacillary detachments were present in 23.5% of eyes, RPE folds in 22.8% of eyes, and ILM fluctuations in 35.2% of eyes. For each 0.1 unit increase in modified RPE undulation index, there was an associated 0.13 increase in mean logMAR BSCVA at baseline. None of the SD-OCT features were associated with BSCVA at the 6-month primary endpoint. Indeed, mean final BSCVA was similar in those with and without the SD-OCT features of interest at baseline, and was between 0.1 and 0.2 logMAR (Snellen visual acuity 20/25 to 20/30). While eyes with VKH may present with a variety of SD-OCT imaging pathology prior to starting immunosuppression with methotrexate or mycophenolate mofetil, final visual outcome in our study was excellent. With appropriate immunosuppression, good visual outcomes are possible in VKH.ClinicalTrials.gov Identifier NCT01829295Date of Registration: April 11, 2013.

Assessment of intracranial aneurysm neck deformation after contour deployment

Purpose:The contour neurovascular system (CNS) is a novel device to treat intracranial wide-necked bifurcation aneurysms, with few studies assessing its long-term effects. Particularly its impact on aneurysm morphology has not been explored yet. We present a preliminary study to explore this impact for the first time, focusing on the neck curve and ostium of the aneurysm.Methods:We investigated seven aneurysms treated with the CNS to assess ostium deformation after CNS deployment by comparing models extracted from in vivo medical pre-treatment and follow-up scans via morphological analysis. Time between pre- and follow-up scans was ten months on average. Size and shape indices like area, neck diameter, ellipticity index, undulation index, and more were assessed.Results:Ostium size was reduced after treatment. On average, ostium area was reduced at a rate of -\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$-$$\\end{document}0.58 (± 4.88) mm2 per year, from 15.52 (± 3.51) mm2 to 13.30 (± 2.27) mm2, and ostium width from 5.01 (± 0.54) mm to 4.49 (± 0.45) mm, with an average reduction of -\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$-$$\\end{document}0.59 (± 0.87) mm. This shrinking positively correlated with time passing. Shape deformation was low, though notably mean ellipticity index was reduced by 0.06 (± 0.15) on average, indicating ostia were less elongated after treatment.Conclusion:We interpret the shrinking of the ostium as part of the healing process. Shape changes were found to be small enough to conclude no shape deformation of the ostium from CNS deployment, but the analysis of more cases with more parameters and information is necessary.

Hemodynamic and morphological differences in cerebral aneurysms between before and after rupture.

Although it has been proposed that aneurysm morphology is different after rupture, detailed research of the morphological changes using 3D imaging acquired before and after rupture has not been conducted because of the difficulty of data collection. Similarly, hemodynamic changes due to morphological alterations after rupture have not been analyzed. The aim of this study was to investigate the changes in morphology and hemodynamics observed after aneurysm rupture. For 21 cerebral aneurysms (21 patients) that ruptured during observation, 3D geometry of the aneurysms and parent arteries were reconstructed based on the angiographic images before and after their rupture. In addition, using the reconstructed geometry, blood flow was simulated by computational fluid dynamics (CFD) analysis. Morphological and hemodynamic parameters were calculated both before and after rupture, and their changes from before to after were compared. In the morphological parameters, statistically significantly higher values were observed after rupture in height (before: 5.5 ± 2.1 mm, after: 6.1 ± 2.0 mm; p < 0.0001), aspect ratio (p = 0.002), aneurysm volume (p = 0.04), and undulation index (p = 0.005). In terms of hemodynamic changes, the mean normalized wall shear stress (NWSS) decreased significantly (before: 5.4 × 10-1 ± 2.9 × 10-1, after: 4.4 × 10-1 ± 2.8 × 10-1; p < 0.001) as well as the other NWSS parameters, including maximum and minimum NWSS, which were associated with stagnant flow due to the morphological changes after rupture. Aneurysm morphology was found to change after rupture into an elongated and irregular geometry, accompanied by an increase in aneurysm volume. These morphological changes were also associated with statistically significant hemodynamic alterations that produced low wall sheer stress by stagnant flow. The authors' results also provide the opportunity to explore and develop a risk evaluation method for aneurysm rupture based on prerupture morphology and hemodynamics by further exploration in this direction.

Study on the historical landscape evolution of the core reserve of Guangfu Ancient City based on computer simulation

Abstract In the conservation of the historical landscape within the Guangfu Ancient City Core Protection Area, traditional descriptions via drawings and textual narratives often exhibit subjective biases. To address this, a theoretical model for the historical architectural landscape has been developed to objectively measure and characterize the spatial patterns and morphologies of the landscape. This study introduces Exploratory Spatial Data Analysis (ESDA) techniques, utilizing spatial weights and spatial correlation measures as primary analytical tools. Additionally, meta-cellular automata are employed to simulate the spatial and temporal evolution of the historical landscape. Geographical Information Systems (GIS) and Remote Sensing (RS) technologies have been leveraged to establish a spatial database and facilitate the visualization of the historical landscape’s evolutionary processes. This integrated model and technological approach enable a detailed analysis of the architectural landscape characteristics and the spatial structure’s evolution within the study area. The findings reveal distinct spatial distribution characteristics, with an undulation index ranging from 5 to 20 and a predominant index over 7, accounting for 15.67% of the land. Based on these insights, the study proposes strategic interventions to safeguard the historical integrity of Guangfu Ancient City’s core conservation area.

Assessing the risk of intracranial aneurysm rupture using computational fluid dynamics: a pilot study.

This study compared 2 representative cases with ruptured aneurysms to explore the role of hemodynamic and morphological parameters in evaluating the rupture risk of intracranial aneurysms (IAs). CTA and 3-dimensional rotational angiography (3DRA) of 3 IAs in 2 patients were retrospectively analyzed in this study. Hemodynamics and morphological parameters were compared between a ruptured IA and an unruptured IA in case1, and between before and after aneurysm rupture in case 2. In case 1, the ruptured aneurysm had larger morphological parameters including size ratio (SR), aspect ratio (AR), aneurysm vessel angle (θF), Aneurysm inclination angle (θA), Undulation index (UI), Ellipticity index (EI), and Non-sphericity Index (NSI) than the unruptured aneurysm. And oscillatory shear index (OSI) is also larger. Higher rupture resemblance score (RRS) was shown in the ruptured aneurysm. In case 2, the aneurysm had one daughter sac after 2 years. Partial morphological and hemodynamic parameters including SR, AR, θF, θA, UI, EI, NSI, OSI, and relative residence time (RRT) increased, and normalized wall shear stress (NWSS) was significantly reduced. RRS increased during this period. SR and OSI may have predictive values for the risk of intracranial aneurysm rupture. It is possible that WSS Changes before and after IA rupture, yet the influence of high or low WSS on growth and rupture of IA remains unclear. RRS is promising to be used in the clinical assessment of the rupture risk of IAs and to guide the formulation of treatment plans.

Evaluating a 3D deep learning pipeline for cerebral vessel and intracranial aneurysm segmentation from computed tomography angiography-digital subtraction angiography image pairs.

Computed tomography angiography (CTA) is the most widely used imaging modality for intracranial aneurysm (IA) management, yet it remains inferior to digital subtraction angiography (DSA) for IA detection, particularly of small IAs in the cavernous carotid region. The authors evaluated a deep learning pipeline for segmentation of vessels and IAs from CTA using coregistered, segmented DSA images as ground truth. Using 50 paired CTA-DSA images, the authors trained (n = 27), validated (n = 3), and tested (n = 20) a deep learning model (3D DeepMedic) for cerebrovasculature segmentation from CTA. A landmark-based coregistration algorithm was used for registration and upsampling of CTA images to paired DSA images. Segmented vessels from the DSA were used as the ground truth. Accuracy of the model for vessel segmentation was evaluated using conventional metrics (dice similarity coefficient [DSC]) and vessel segmentation-specific metrics, like connectivity-area-length (CAL). On the test cases (20 IAs), 3 expert raters attempted to detect and segment IAs. For each rater, the authors recorded the rate of IA detection, and for detected IAs, raters segmented and calculated important IA morphology parameters to quantify the differences in IA segmentation by raters to segmentations by DeepMedic. The agreement between raters, DeepMedic, and ground truth was assessed using Krippendorf's alpha. In testing, the DeepMedic model yielded a CAL of 0.971 ± 0.007 and a DSC of 0.868 ± 0.008. The model prediction delineated all IAs and resulted in average error rates of < 10% for all IA morphometrics. Conversely, average IA detection accuracy by the raters was 0.653 (undetected IAs were present to a significantly greater degree on the ICA, likely due to those in the cavernous region, and were significantly smaller). Error rates for IA morphometrics in rater-segmented cases were significantly higher than in DeepMedic-segmented cases, particularly for neck (p = 0.003) and surface area (p = 0.04). For IA morphology, agreement between the raters was acceptable for most metrics, except for the undulation index (α = 0.36) and the nonsphericity index (α = 0.69). Agreement between DeepMedic and ground truth was consistently higher compared with that between expert raters and ground truth. This CTA segmentation network (DeepMedic trained on DSA-segmented vessels) provides a high-fidelity solution for CTA vessel segmentation, particularly for vessels and IAs in the carotid cavernous region.

Understanding and Improving Risk Assessment of Abdominal Aortic Aneurysm Growth Using Statistical Shape Modeling of the Infrarenal Aorta

Maximum diameter of the aneurysmal sac remains the primary method for defining surveillance intervals and the timing for surgical intervention. Recent studies have attempted to expand on this one-dimensional metric by incorporating additional descriptors of the aneurysmal sac such as undulation, curvature and tortuosity. However, these metrics are often biased and may overlook certain anatomical abnormalities, limiting predictive potential. This study aimed to identify novel three-dimensional shape features of the aneurysmal flow lumen and outer wall structure (OWS, with or without intraluminal thrombus) to predict aneurysmal growth. A cohort of 192 patients (median age, 72 [range, 62-79]; 99% male) with infrarenal abdominal aortic aneurysms (AAAs) (initial max diameter, 50.3 ± 4.2 mm) and serial computed tomography images obtained during AAA surveillance (median follow-up, 2.0 years [range, 1.0-5.3 years]) were retrospectively considered for this study. Estimated annual AAA growth was the clinical end point and was used to classify patients into slow (first quintile, <2.5 mm/year) and fast (fifth quintile, >5.0 mm/year) cohorts. A previously validated pipeline was implemented to automatically segment computed tomography images. Three-dimensional statistical shape models of the aneurysmal flow lumen and OWS were used to identify three-dimensional patterns involved in AAA growth. Undulation index and radius of curvature of the AAA, previously suggested to be predictive of AAA growth, were also calculated. Model training with derived shape features was performed using iterated 10-fold optimization with shuffling (100 iterations). C-statistics for each feature combination was used to evaluate performance. Integrating the lumen and OWS as unique components within the three-dimensional statistical shape model captured the lumen-thrombus interface. These features proved to be superior to max diameter, undulation index, and radius of curvature in prediction of AAA growth phenotype (P < .001). Corresponding median C-statistics for predicting slow and fast growth are highlighted in the Figure. Integrated models outperformed individual components in prediction of both slow and fast AAA growth (P < .001). Standardized feature extraction from both the aneurysmal flow lumen and the OWS, enabled by a fully automated pipeline, can characterize the evolving lumen-thrombus interface, and improves AAA growth prediction. Future work is focused on validating this statistical shape-based model on larger cohorts that also include smaller AAAs.

Complex Morphologic Analysis of Cerebral Aneurysms Through the Novel Use of Fractal Dimension as a Predictor of Rupture Status: A Proof of Concept Study

Aneurysm morphology has been correlated with rupture. Previous reports identified several morphologic indices that predict rupture status, but they measure only specific qualities of the morphology of an aneurysm in a semiquantitative fashion. Fractal analysis is a geometric technique whereby the overall complexity of a shape is quantified through the calculation of a fractal dimension (FD). By progressively altering the scale of measurement of a shape and determining the number of segments required to incorporate the entire shape, a noninteger value for the dimension of the shape is derived. We present a proof-of-concept study to calculate the FD of an aneurysm for a small cohort of patients with aneurysms in 2 specific locations to determine whether FD is associated with aneurysm rupture status. Twenty-nine aneurysms of the posterior communicating and middle cerebral arteries were segmented from computed tomography angiograms in 29 patients. FD was calculated using a standard box-counting algorithm extended for use with three-dimensional shapes. Nonsphericity index and undulation index (UI) were used to validate the data against previously reported parameters associated with rupture status. Nineteen ruptured and 10 unruptured aneurysms were analyzed. Through logistic regression analysis, lower FD was found to be significantly associated with rupture status (P= 0.035; odds ratio, 0.64; 95% confidence interval, 0.42-0.97 per FD increment of 0.05). In this proof-of-concept study, we present a novel approach to quantify the geometric complexity of intracranial aneurysms through FD. These data suggest an association between FD and patient-specific aneurysm rupture status.

Abstract Number ‐ 15: Morphological Characteristics of Ruptured and Unruptured Intracranial Aneurysms: A Systematic Literature Review and Meta‐Analysis

Introduction It is unclear what morphological features of brain aneurysms are better at predicting risk of rupture.We have performed a meta‐analysis to analyze the best morphological determinants of risk of rupture. Methods The Nested Knowledge platformwas used to search thePubMed database for studiesreporting aneurysmal size, aspect ratio (AR), size ratio (SR), ellipticity index (EI), nonsphericity index (NSI) and undulation index (UI).Effect sizes were computed as logarithmically transformed mean differences (MD) between ruptured and unruptured aneurysm. Finally, effect sizes were pooled using random‐effects and inverse‐variance weighting via restricted effects maximum likelihood estimation. Results We included 63 studies with 13,025 aneurysms: ruptured 6966 and unruptured 6059. Ruptured aneurysms were larger compared to unruptured (µ 6.1 mm, 95% CI 5.7‐6.6 vs 4.9 mm, 95% CI 4.5‐5.3 respectively, p &lt; 0.001). There was no significant difference in size between ruptured and unruptured aneurysms in the anterior cerebral artery (ACA, p = 0.28), anterior communicating artery (ACom, p = 0.31) and basilar artety (BA, p = 0.51). AR was significantly higher in ruptured compared to unruptured aneurysms(µ 1.5,95% CI: 1.4‐1.6 vs.1.1, 95% CI: 1.1‐1.2 respectively,p &lt; 0.001).SR was significantly higher in ruptured compared to unruptured aneurysms (µ 2.3,95% CI: 2.1‐2.5 vs. 1.6, 95% CI: 1.4‐1.8 respectively,p &lt; 0.001).Ruptured aneurysms in the ACA and Acom had the largest mean SRs (2.5, 95% CI: 1.0‐ 6.4 and 2.6,95% CI: 2.2‐ 3.0 respectively).NSI and EI were higher in ruptured compared to unruptured aneurysms (p = 0.049 and p = 0.049, respectively). UI was similar in ruptured and unruptured aneurysms (p = 0.22). Conclusions Small aneurysms in the ACA and ACom can rupture regardless of size. SR is the best predictor of rupture status for aneurysms in these locations.SR and AR are predictors of rupture status independently of size.

Morphological Characteristics of Ruptured Brain Aneurysms: A Systematic Literature Review and Meta‐Analysis

Background It is unclear what morphological features of brain aneurysms are better at predicting risk of rupture. We conducted a meta‐analysis to analyze the best morphological determinants of rupture status. Methods The Nested Knowledge platform was used to perform a search of articles reporting on aneurysm size, aspect ratio (AR), size ratio (SR), ellipticity index, nonsphericity index, and undulation index. The mean differences between ruptured and unruptured aneurysms were used to calculate effect sizes. Results A total of 63 studies with 13 025 aneurysms were included: 6966 ruptured aneurysms and 6059 unruptured aneurysms. Ruptured aneurysms had a larger size ( P &lt;0.001), AR ( P &lt;0.001), SR ( P &lt;0.001), ellipticity index ( P =0.049), and nonsphericity index ( P =0.049) compared with unruptured aneurysms. The mean size of ruptured aneurysms was 6.1 mm (95% CI, 5.6–6.5). The size of ruptured and unruptured aneurysms was similar in the anterior cerebral artery ( P =0.28), anterior communicating artery ( P =0.31), and basilar artery ( P =0.51). The mean AR of ruptured aneurysms was 1.5 (95% CI, 1.4–1.6), and the mean SR was 2.3 (95% CI, 2.1–2.5). For mirror aneurysms, the mean AR was 1.2 (95% CI, 1.2–1.5), and the mean SR was 2.2 (95% CI, 2.1–2.5). Conclusions Size is not significantly different between ruptured and unruptured aneurysms located in the anterior cerebral artery, anterior communicating artery, and basilar artery. SR is significantly different between ruptured and unruptured aneurysms in all locations. A mean AR of 1.5 and SR of 2.3 are the thresholds associated with ruptured aneurysm status.

Abstract 15889: Evaluation of a Novel CTA/DSA-Based Deep-Learning Cerebrovascular Segmentation Method for Cavernous Intracranial Aneurysms

Introduction: CTA is a mainstay diagnostic imaging modality for screening and follow-up of intracranial aneurysms (IAs). One challenge facing neuroradiologists is detection and visualization of IAs on the cavernous internal carotid artery (ICA), which are often obstructed by bony tissue. Such IAs are either missed diagnosed, or must be re-imaged by high-resolution DSA. We sought to evaluate the performance of automated deep learning methods in segmenting cavernous ICA aneurysms from CTA. Methods: In 30 cases, we collected and registered CTA-DSA image pairs to train 2 deep-learning (DL) networks (namely, Brave-Net [BN], and DeepMedic [DM]) for brain vessel segmentation from CTA images of patients with IAs. Segmented DSA was used as the ground truth. Independent testing was performed on a separate cohort of 20 cases to compare network performances. The best-performing network was used for comparison against expert rater assessment in IA detection and segmentation. Quantitative evaluation of expert rater IA segmentation was also performed by comparing IA morphology quantified by parameters, such as size, aspect ratio, neck diameter, and undulation index, against DL predictions. Results: In the independent testing dataset, BN significantly outperformed DM in terms of Dice similarity coefficient DSC (0.875±0.0083 vs. 0.864±0.0075, p=0.004), while DM significantly outperformed BN in terms of precision (0.891±0.016 vs. 0.867±0.017, p&lt;0.001). Qualitative assessment confirmed the superiority of DM in segmenting the IAs located on cavernous ICA. Compared to DM, expert raters missed 7 IAs located on cavernous ICA. Furthermore, DM segmentation provided better measurement of neck diameter (p=0.009), aspect ratio (p=0.029) and shape parameters as compared to the expert rater assessment. Conclusions: A deep learning approach using DM can provide a high-fidelity solution for CTA segmentation of vessels and IAs in the cavernous ICA region.

Investigation of Pedestrian-Level Wind Environment with Skyline Quantitative Factors

This paper presented a Computational Fluid Dynamics (CFD) study on the relationship between skyline quantitative factors and the wind environment. At present, most researches on skyline revealed the changes of skyline quantitative factors on the aesthetic degrees but neglected the influence of the factors on the outdoor wind environment. This paper addresses the gap in using the changing factors for the prediction of outdoor wind speed. It provides a standardized range for aesthetic degrees in the comfortable range of the wind environment and an exact relationship between the factors and the wind environment. To validate the effectiveness of the proposed approach, a case study is undertaken on the existing skyline of Qianjiang New City in Hangzhou and extracts the following three skyline quantitative factors in skyline contour: contour tortuosity, building undulation, and skyline rhythm index. The result shows that the proposed range and relationship are ready to provide a quantitative understanding of the skyline under outdoor wind conditions.

Leaf surface traits related to differential particle adsorption – A case study of two tropical legumes

We aimed to test a set of epidermal traits in two legume species with contrasting chemical, physical, and micromorphological leaf-surface features to assess which ones would determine higher PM retention. For that, we performed a biomonitoring study in southeastern Brazil at the Steel Valley Metropolitan Region, where there is predominance of steel industry and one of the largest vehicle fleets in the country. A reference station was installed at a neighboring park. We evaluated leaf-surface roughness at two hierarchical levels, leaf wettability, epidermal-cell anticlinal-wall undulation, epidermal-cell perimeter, and the micromorphology and chemical composition of epicuticular waxes. Particle retention was significantly higher in Paubrasilia echinata than in Libidibia ferrea var. leiostachya, the former of which has lower roughness given by both the epidermal tissue (macro-roughness; 0.6 vs 2.6 μm) and epicuticular waxes (micro-roughness; 68 vs 220 nm), higher leaf wettability (82° vs 143°), lower epidermal-cell undulation index (1.2 vs 1.8), lower epidermal-cell perimeter (93 vs 146 μm), wax deposition in the form of a smooth layer (as opposed to densely aggregated rosettes of vertical platelets), and more polar wax chemical constitution (68% vs 47% of polar compounds). While all of the assessed traits contributed to particle retention, canonical loadings revealed that macro-roughness was the trait that contributed the most to the retention of PM2.5 (ca = 1.47; r = −0.56), PM10 (ca = 1.08; r = −0.61), PM100 (ca = −4.95; r = −0.39) and TSP (ca = 0.98; r = −0.62), although this trait was shown by factor analysis to be secondary in distinguishing between species (0.92 contribution to the second axis). Our findings shed new light on the criteria that should be considered when selecting species for green infrastructure aiming to reduce urban air pollution, as well as on novel possibilities for PM biomonitoring in the tropics.

North Atlantic Oscillation seesaw effect in leaf morphological records from dwarf birch shrubs in Greenland and Finland

The North Atlantic Oscillation (NAO) determines wind speed and direction, seasonal heat, moisture transport, storm tracks, cloudiness and sea-ice cover through atmospheric mass balance shifts between the Arctic and the subtropical Atlantic. The NAO is characterized by the typical, yet insufficiently understood, seesaw pattern of warmer winter and spring temperatures over Scandinavia and cooler temperatures over Greenland during the positive phase of the NAO, and vice versa during the negative phase. We tested the potential to reconstruct NAO variation beyond the meteorological record through the application of a microphenological proxy. We measured the Undulation Index (UI) in Betula nana epidermal cells from herbarium leaf samples and fossil peat fragments dating back to 1865—exceeding most meteorological records in the Arctic—to estimate imprints of spring thermal properties and NAO in Greenland and Finland. We found negative relations between Greenland UI and late winter, spring and early summer NAO, and mostly positive, but not significant, relations between Finland UI and NAO in years with pronounced NAO expression. The direction of the UI response in this common circumpolar species is, therefore, likely in line with the NAO seesaw effect, with leaf development response to NAO fluctuations in northern Europe opposing the response in Greenland and vice versa. Increased knowledge of the UI response to climate may contribute to understanding ecological properties of key Arctic species, whilst additionally providing a proxy for NAO dynamics.

Definition and extraction of 2D shape indices of intracranial aneurysm necks for rupture risk assessment

PurposeIntracranial aneurysms are local dilations of brain vessels. Their rupture, as well as their treatment, is associated with high risk of morbidity and mortality. In this work, we propose shape indices for aneurysm ostia for the rupture risk assessment of intracranial aneurysms.MethodsWe analyzed 84 middle cerebral artery bifurcation aneurysms (27 ruptured and 57 unruptured) and their ostia, with respect to their size and shape. We extracted 3D models of the aneurysms and vascular trees. A semi-automatic approach was used to separate the aneurysm from its parent vessel and to reconstruct the ostium. We used known indices to quantitatively describe the aneurysms. For the ostium, we present new shape indices: the 2D Undulation Index (UI_mathrm{2D}), the 2D Ellipticity Index (EI_mathrm{2D}) and the 2D Noncircularity Index (NCI_mathrm{2D}). Results were analyzed using the Student t test, the Mann–Whitney U test and a correlation analysis between indices of the aneurysms and their ostia.ResultsOf the indices, none was significantly associated with rupture status. Most aneurysms have an NCI_mathrm{2D} below 0.2. Of the aneurysms that have an NCI_mathrm{2D} above 0.5, only one is ruptured, which indicates that ruptured aneurysms often have a circular-shaped ostium. Furthermore, the ostia of ruptured aneurysms tend to have a smaller area, which is also correlated with the aneurysm’s size. While also other variables were significantly correlated, strong linear correlations can only be seen between the area of the ostium with the aneurysm’s volume and surface.ConclusionThe proposed shape indices open up new possibilities to quantitatively describe and compare ostia, which can be beneficial for rupture risk assessment and subsequent treatment decision. Additionally, this work shows that the ostium area and the size of the aneurysm are correlated. Further longitudinal studies are necessary to analyze whether stable and unstable aneurysms can be distinguished by their ostia.

Effects of experimental warming on Betula nana epidermal cell growth tested over its maximum climatological growth range.

Numerous long-term, free-air plant growth facilities currently explore vegetation responses to the ongoing climate change in northern latitudes. Open top chamber (OTC) experiments as well as the experimental set-ups with active warming focus on many facets of plant growth and performance, but information on morphological alterations of plant cells is still scarce. Here we compare the effects of in-situ warming on leaf epidermal cell expansion in dwarf birch, Betula nana in Finland, Greenland, and Poland. The localities of the three in-situ warming experiments represent contrasting regions of B. nana distribution, with the sites in Finland and Greenland representing the current main distribution in low and high Arctic, respectively, and the continental site in Poland as a B. nana relict Holocene microrefugium. We quantified the epidermal cell lateral expansion by microscopic analysis of B. nana leaf cuticles. The leaves were produced in paired experimental treatment plots with either artificial warming or ambient temperature. At all localities, the leaves were collected in two years at the end of the growing season to facilitate between-site and within-site comparison. The measured parameters included the epidermal cell area and circumference, and using these, the degree of cell wall undulation was calculated as an Undulation Index (UI). We found enhanced leaf epidermal cell expansion under experimental warming, except for the extremely low temperature Greenland site where no significant difference occurred between the treatments. These results demonstrate a strong response of leaf growth at individual cell level to growing season temperature, but also suggest that in harsh conditions other environmental factors may limit this response. Our results provide evidence of the relevance of climate warming for plant leaf maturation and underpin the importance of studies covering large geographical scales.

Prediction of Abdominal Aortic Aneurysm Growth Using Geometric Assessment of Computerized Tomography Images Acquired During the Aneurysm Surveillance Period.

We investigated the utility of geometric features for future AAA growth prediction. Novel methods for growth prediction of AAA are recognized as a research priority. Geometric feature have been used to predict cerebral aneurysm rupture, but not examined as predictor of AAA growth. Computerized tomography (CT) scans from patients with infra-renal AAAs were analyzed. Aortic volumes were segmented using an automated pipeline to extract AAA diameter (APD), undulation index (UI), and radius of curvature (RC). Using a prospectively recruited cohort, we first examined the relation between these geometric measurements to patients' demographic features (n = 102). A separate 192 AAA patients with serial CT scans during AAA surveillance were identified from an ongoing clinical database. Multinomial logistic and multiple linear regression models were trained and optimized to predict future AAA growth in these patients. There was no correlation between the geometric measurements and patients' demographic features. APD (Spearman r = 0.25, P < 0.05), UI (Spearman r = 0.38, P < 0.001) and RC (Spearman r =-0.53, P < 0.001) significantly correlated with annual AAA growth. Using APD, UI, and RC as 3 input variables, the area under receiver operating characteristics curve for predicting slow growth (<2.5 mm/yr) or fast growth (>5 mm/yr) at 12 months are 0.80 and 0.79, respectively. The prediction or growth rate is within 2 mm error in 87% of cases. Geometric features of an AAA can predict its future growth. This method can be applied to routine clinical CT scans acquired from patients during their AAA surveillance pathway.

Performance of Radiomics derived morphological features for prediction of aneurysm rupture status

BackgroundMorphological differences between ruptured and unruptured cerebral aneurysms represent a focus of neuroimaging researchfor understanding the mechanisms of aneurysmal rupture. We evaluated the performance of Radiomics derived morphological features, recently...

Isotopic and morphologic proxies for reconstructing light environment and leaf function of fossil leaves: a modern calibration in the Daintree Rainforest, Australia.

Within closed-canopy forests, vertical gradients of light and atmospheric CO2 drive variations in leaf carbon isotope ratios, leaf mass per area (LMA), and the micromorphology of leaf epidermal cells. Variations in traits observed in preserved or fossilized leaves could enable inferences of past forest canopy closure and leaf function and thereby habitat of individual taxa. However, as yet no calibration study has examined how isotopic, micro- and macromorphological traits, in combination, reflect position within a modern closed-canopy forest or how these could be applied to the fossil record. Leaves were sampled from throughout the vertical profile of the tropical forest canopy using the 48.5 m crane at the Daintree Rainforest Observatory, Queensland, Australia. Carbon isotope ratios, LMA, petiole metric (i.e., petiole-width2 /leaf area, a proposed proxy for LMA that can be measured from fossil leaves), and leaf micromorphology (i.e., undulation index and cell area) were compared within species across a range of canopy positions, as quantified by leaf area index (LAI). Individually, cell area, δ13 C, and petiole metric all correlated with both LAI and LMA, but the use of a combined model provided significantly greater predictive power. Using the observed relationships with leaf carbon isotope ratio and morphology to estimate the range of LAI in fossil floras can provide a measure of canopy closure in ancient forests. Similarly, estimates of LAI and LMA for individual taxa can provide comparative measures of light environment and growth strategy of fossil taxa from within a flora.