Fitting Volume Models for Parana Pine With a Nonlinear Regression, Genetic Algorithm and Simulated Annealing

Improving volumetric quantification of Parana pine (Araucaria angustifolia) in Mixed Ombrophilous Forest is a constant need in order to provide accurate and timely information on current and future growing stock to ensure forest management. Thus, the present study aimed to evaluate and compare the volume estimates obtained through Nonlinear Regression (NR), Genetic Algorithm (GA) and Simulated Annealing (SA) in order to generate accurate volume estimates. Volumetric equations were developed including the independent variables diameter at breast height (dbh), total height (h) and crown rate (cr) and from the fit through the NR, GA and SA approaches. The GA and SA approaches evaluated proved to be a reliable optimization strategy for parameter estimation in Parana pine volumetric modelling, however, no significant differences were found in comparison with the NR approach. This study therefore contributes through the generation of robust equations that could be used for accurate estimates of the volume of the Parana pine in southern Brazil, thus supporting the planning and establishment of management and conservation actions.

Automatic Quantification of Atherosclerosis in Contrast-Enhanced MicroCT Scans of Mouse Aortas Ex Vivo

Objective. While microCT evaluation of atherosclerotic lesions in mice has been formally validated, existing image processing methods remain undisclosed. We aimed to develop and validate a reproducible image processing workflow based on phosphotungstic acid-enhanced microCT scans for the volumetric quantification of atherosclerotic lesions in entire mouse aortas. Approach and Results. 42 WT and 42 apolipoprotein E knockout mouse aortas were scanned. The walls, lumen, and plaque objects were segmented using dual-threshold algorithms. Aortic and plaque volumes were computed by voxel counting and lesion surface by triangulation. The results were validated against manual and histological evaluations. Knockout mice had a significant increase in plaque volume compared to wild types with a plaque to aorta volume ratio of 0.3%, 2.8%, and 9.8% at weeks 13, 18, and 26, respectively. Automatic segmentation correlated with manual ( r 2 ≥ 0.89 ; p < .001 ) and histological evaluations ( r 2 > 0.96 ; p < .001 ). Conclusions. The semiautomatic workflow enabled rapid quantification of atherosclerotic plaques in mice with minimal manual work.

Volumetric quantification of wound healing by machine learning and optical coherence tomography in adults with type 2 diabetes: the GC-SHEALD RCT

Type 2 diabetes mellitus is associated with impaired wound healing, which contributes substantially to patient morbidity and mortality. Glucocorticoid (stress hormone) excess is also known to delay wound repair. Optical coherence tomography (OCT) is an emerging tool for monitoring healing by 'virtual biopsy', but largely requires manual analysis, which is labour-intensive and restricts data volume processing. This limits the capability of OCT in clinical research. Using OCT data from the GC-SHEALD trial, we developed a novel machine learning algorithm for automated volumetric quantification of discrete morphological elements of wound healing (by 3mm punch biopsy) in patients with type 2 diabetes. This was able to differentiate between early / late granulation tissue, neo-epidermis and clot structural features and quantify their volumetric transition between day 2 and day 7 wounds. Using OCT, we were able to visualize differences in wound re-epithelialisation and re-modelling otherwise indistinguishable by gross wound morphology between these time points. Automated quantification of maximal early granulation tissue showed a strong correlation with corresponding (manual) GC-SHEALD data. Further, % re-epithelialisation was improved in patients treated with oral AZD4017, an inhibitor of systemic glucocorticoid-activating 11β-hydroxysteroid dehydrogenase type 1 enzyme action, with a similar trend in neo-epidermis volume. Through the combination of machine learning and OCT, we have developed a highly sensitive and reproducible method of automated volumetric quantification of wound healing. This novel approach could be further developed as a future clinical tool for the assessment of wound healing e.g. diabetic foot ulcers and pressure ulcers.

Subcortical brain segmentation in 5-year-old children: validation of FSL-FIRST and FreeSurfer against manual segmentation

Developing accurate subcortical volumetric quantification tools is a crucial issue for neurodevelopmental studies, as they could reduce the need for challenging and time-consuming manual segmentation. In this study the accuracy of two automated segmentation tools, FSL-FIRST (with three different boundary correction settings) and FreeSurfer were compared against manual segmentation of subcortical nuclei, including the hippocampus, amygdala, thalamus, putamen, globus pallidus, caudate and nucleus accumbens, using volumetric and correlation analyses in 80 5-year-olds. Both FSL-FIRST and FreeSurfer overestimated the volume on all structures except the caudate, and the accuracy depended on the structure. Small structures such as the amygdala and nucleus accumbens, which are visually difficult to distinguish, produced considerable overestimations and weaker correlations with all automated methods. Larger and more readily distinguishable structures such as the caudate and putamen produced notably lower overestimations and stronger correlations. Overall, the segmentations performed by FSL-FIRST's Default pipeline were the most accurate, while FreeSurfer's results were weaker across the structures. In line with prior studies, the accuracy of automated segmentation tools was imperfect with respect to manually defined structures. However, apart from amygdala and nucleus accumbens, FSL-FIRST's agreement could be considered satisfactory (Pearson correlation > 0.74, Intraclass correlation coefficient (ICC) > 0.68 and Dice Score coefficient (DSC) > 0.87) with highest values for the striatal structures (putamen, globus pallidus and caudate) (Pearson correlation > 0.77, ICC > 0.87 and DSC > 0.88, respectively). Overall, automated segmentation tools do not always provide satisfactory results, and careful visual inspection of the automated segmentations is strongly advised.

Simulating Expansion of the Intracranial Space to Accommodate Brain Swelling after Decompressive Craniectomy: Volumetric Quantification in a 3D CAD Skull Model with Contour Elevation

Background: Decompressive craniectomy (DC) can be used to augment intracranial space and halt brainstem compromise. However, a widely adopted recommendation for optimal surgical extent of the DC procedure is lacking. In the current study, we utilized three-dimensional (3D) computer-assisted design (CAD) skull models with defect contour elevation for quantitative assessment. Methods: DC was performed for 15 consecutive patients, and 3D CAD models of defective skulls with contour elevations (0–50 mm) were reconstructed using commercial software. Quantitative assessments were conducted in these CAD subjects to analyze the effects of volumetric augmentation when elevating the length of the contour and the skull defect size. The final positive results were mathematically verified using a computerized system for numerical integration with the rectangle method. Results: Defect areas of the skull CAD models ranged from 55.7–168.8 cm2, with a mean of 132.3 ± 29.7 cm2. As the contour was elevated outward for 6 mm or above, statistical significance was detected in the volume and the volume-increasing rate, when compared to the results obtained from the regular CAD model. The volume and the volume-increasing rate increased by 3.665 cm3, 0.285% (p < 0.001) per 1 mm of contour elevation), and 0.034% (p < 0.001) per 1 cm2 of increase of defect area, respectively. Moreover, a 1 mm elevation of the contour in Groups 2 (defect area 125–150 cm2) and 3 (defect area >150 cm2, as a proxy for an extremely large skull defect) was shown to augment the volume and the volume-increasing rate by 1.553 cm3, 0.101% (p < 0.001) and 1.126 cm3, 0.072% (p < 0.001), respectively, when compared to those in Group 1 (defect area <125 cm2). The volumetric augmentation achieved by contour elevation for an extremely large skull defect was smaller than that achieved for a large skull defect. Conclusions: The 3D CAD skull model contour elevation method can be effectively used to simulate the extent of a space-occupying swollen brain and to quantitatively assess the extent of brainstem protection in terms of volume augmentation and volume-increasing rate following DC. As the tangential diameter (representing the degree of DC) exceeded the plateau value, volumetric augmentation was attenuated. However, an increasing volumetric augmentation was detected before the plateau value was reached.

Endolymphatic Hydrops in Patients With Vestibular Migraine and Concurrent Meniere's Disease

Objective: Intravenous contrast agent enhanced, high-resolution magnetic resonance imaging of the inner ear (iMRI) confirmed that patients with Menière's disease (MD) and vestibular migraine (VM) could present with endolymphatic hydrops (EH). The present study aimed to investigate EH characteristics and their interrelation to neurotologic testing in patients with VM, MD, or VM with concurrent MD (VM-MD).Methods: Sixty–two patients (45 females, aged 23–81 years) with definite or probable VM (n = 25, 19 definite), MD (n = 29, 17 definite), or showing characteristics of both diseases (n = 8) were included in this study. Diagnostic workup included neurotologic assessments including video-oculography (VOG) during caloric stimulation and head-impulse test (HIT), ocular and cervical vestibular evoked myogenic potentials (o/cVEMP), pure tone audiometry (PTA), as well as iMRI. EH's degree was assessed visually and via volumetric quantification using a probabilistic atlas-based segmentation of the bony labyrinth and volumetric local thresholding (VOLT).Results: Although a relevant number of VM patients reported varying auditory symptoms (13 of 25, 52.0%), EH in VM was only observed twice. In contrast, EH in VM-MD was prevalent (2/8, 25%) and in MD frequent [23/29, 79.3%; χ2(2) = 29.1, p &lt; 0.001, φ = 0.7]. Location and laterality of EH and neurophysiological testing classifications were highly associated (Fisher exact test, p &lt; 0.005). In MD, visual semi-quantitative grading and volumetric quantification correlated highly to each other (rS = 0.8, p &lt; 0.005, two-sided) and to side differences in VOG during caloric irrigation (vestibular EH ipsilateral: rS = 0.6, p &lt; 0.05, two-sided). In VM, correlations were less pronounced. VM-MD assumed an intermediate position between VM and MD.Conclusion: Cochlear and vestibular hydrops can occur in MD and VM patients with auditory symptoms; this suggests inner ear damage irrespective of the diagnosis of MD or VM. The EH grades often correlated with auditory symptoms such as hearing impairment and tinnitus. Further research is required to uncover whether migraine is one causative factor of EH or whether EH in VM patients with auditory symptoms suggests an additional pathology due to MD.