Search Results (733)

The aim of this study was to compare carcass composition, meat quality, digestive tract morphometry, and leg bone dimensions of Pekin and Muscovy ducks. The study involved 40 birds, including 10 males and 10 females from each genotype, reared to market age. Carcass traits, physicochemical properties of breast and leg muscles, texture parameters, internal organ development, intestinal measurements, and selected dimensions of the femur and tibia were evaluated. The results demonstrated a significant effect of duck genotype (p < 0.05) on carcass weight, dressing percentage, and the proportion of neck, wings, and skin with subcutaneous fat. Genotype also affected meat color (L*, a*, b*), intramuscular fat and collagen content, cooking loss, pH, electrical conductivity, and selected texture parameters of breast muscles. Differences were also observed in the mass and proportion of internal organs, most intestinal morphometric traits, and selected bone measurements. Sex had a significant effect on body and carcass weight, selected meat quality traits, intestinal measurements, and leg bone dimensions, with males generally showing greater body size and more developed skeletal structures. Significant interactions between genotype and sex were observed for several analyzed traits. The findings indicate that both genotype and sex substantially affect slaughter traits and meat quality characteristics of ducks. Full article

Objectives: This study aimed to evaluate the utility of MRI-based morphometric and qualitative parameters in identifying patients with suspected normal pressure hydrocephalus (NPH) associated with shunt surgery selection following clinical and lumbar puncture evaluation. Methods: We retrospectively analyzed 134 participants: 84 symptomatic patients evaluated for suspected NPH and 50 age-matched controls with normal brain MRI findings. Symptomatic patients were categorized according to subsequent clinical management following lumbar puncture evaluation into those who underwent shunt surgery (Shunt group) and those who received conservative management (Conservative group). The Evans index, fronto-occipital horn ratio (FOHR), bicaudate index, callosal angle, ventricular measurements, and disproportionately enlarged subarachnoid space hydrocephalus (DESH) components were analyzed. The discriminatory performance of MRI parameters for shunt surgery selection was assessed using ROC analysis; independent predictors of shunt surgery selection were determined using logistic regression. Results: Although conventional ventricular indices and ventricular dimensions were significantly greater in symptomatic patients than in the control group (p < 0.001), baseline continuous MRI measurements did not significantly differ between the Shunt and Conservative groups (p > 0.05). Callosal angle demonstrated no discriminatory value for shunt surgery selection. In univariate analyses, an Evans Index > 0.36, a bicaudate index > 0.23, and a DESH score > 2 were associated with shunt surgery selection. High-convexity tightness and an Evans Index > 0.36 differed significantly between groups and remained independently associated with shunt surgery selection in multivariable analysis. Conclusions: Ventricular width-based indices alone appear insufficient for identifying patients selected for shunt surgery among individuals evaluated for suspected NPH. Both qualitative and quantitative MRI features, particularly high-convexity tightness and an Evans Index > 0.36, were independently associated with shunt surgery selection following routine clinical assessment. Integrating multimodal imaging parameters with clinical evaluation may provide a more reliable approach for identifying patients who are ultimately selected for shunt surgery following lumbar puncture assessment. Full article

Objectives: This study aimed to evaluate the impact of thoracic endovascular aortic repair (TEVAR) on aortic remodeling using CT angiography-based morphometric measurements and to examine associated mid-term clinical outcomes in patients with acute Stanford type B aortic dissection. Methods: This retrospective, single-center observational cohort study included 33 consecutive patients who underwent TEVAR for acute Stanford type B aortic dissection between January 2020 and January 2025. Preoperative and postoperative true lumen (TL), false lumen (FL), and descending aorta (DA) diameters were compared using paired t-tests after Shapiro–Wilk normality testing. Endoleak, reintervention, FL thrombosis, and mortality were analyzed. Univariable analyses identified factors associated with endoleak and reintervention. Spearman’s correlation assessed factors associated with morphometric remodeling response. Results: All 33 patients had acute Stanford type B dissection (mean time to intervention: 2.73 ± 3.86 days). Among 33 patients (81.8% male; mean age 53.6 ± 12.1 years), mean follow-up was 4.08 ± 1.66 years. TEVAR induced a significant aortic remodeling response: TL diameter increased from 9.55 ± 5.91 mm to 28.30 ± 5.49 mm (+18.76 ± 8.83 mm; p < 0.001) and FL diameter decreased from 33.39 ± 6.76 mm to 11.48 ± 8.97 mm (−21.91 ± 9.53 mm; p < 0.001), while DA diameter remained stable (42.94 ± 6.90 vs. 42.03 ± 9.46 mm; p = 0.323). Complete FL thrombosis was achieved in 19 patients (57.6%). Endoleak occurred in nine patients (27.3%); Zone 2 landing was significantly associated with endoleak (54.5% vs. 13.6%, p = 0.033). Secondary intervention was required in 13 patients (39.4%). Overall mortality was 12.1%. Narrower preoperative TL was strongly associated with greater TL expansion (Spearman r = −0.724, p < 0.001); longer stent–graft coverage was associated with greater TL gain (r = +0.522, p = 0.002). Conclusions: TEVAR induced clinically meaningful aortic remodeling in acute Stanford type B dissection without progressive aortic enlargement. A narrower baseline TL and longer stent–graft coverage were associated with greater remodeling benefit. Zone 2 deployment was significantly associated with higher endoleak rates, underscoring the value of careful preprocedural planning and systematic long-term imaging surveillance. Full article

Fish phenotyping plays an important role in growth evaluation, selective breeding, and precision aquaculture. Conventional phenotypic measurement methods are labor-intensive, time-consuming, and susceptible to observer variability. To improve measurement efficiency and reproducibility, this study proposes an automated fish phenotyping framework based on Transformer-enhanced instance segmentation. Specifically, a Mask2Former decoder was integrated into the Mask R-CNN architecture to improve boundary delineation and segmentation quality. Based on segmentation outputs, phenotypic parameters, including body length, body height, and projected area, were automatically extracted using PCA-assisted orientation estimation and geometric measurement. In addition, a standardized anatomical landmark annotation framework consisting of 12 reference points was introduced to support reproducible phenotypic description and future extensible morphometric analysis. Body weight was further estimated using polynomial regression based on extracted morphological traits. Experiments were conducted using images from three crucian carp varieties under controlled imaging conditions. The proposed framework achieved 92.7% mAP and 89.4% Boundary IoU, improving segmentation performance over the baseline model. Automated measurement yielded average relative errors of 2.16% for body length and 3.85% for body height, while weight prediction achieved an R² of 0.9479 and a mean relative error of 7.31%. These results demonstrate that Transformer-enhanced segmentation can support accurate and efficient automated phenotyping under standardized conditions and provide a foundation for future deployment in more complex aquaculture environments. Full article

Background/Objectives: Anthropometric measurements provide essential normative datasets that form the foundation for clinical practice and forensic identification. The human ear is a highly informative structure due to its complex morphology and individual specificity, making it a valuable tool for biometric systems. This study aimed to estimate biological sex based on auricular morphometric measurements, develop a logistic regression model for this purpose, and validate its performance using ROC analysis. Materials and Methods: This cross-sectional study included 120 adult participants (60 males, 60 females). Standardized digital photographs were analyzed in ImageJ to record 22 linear and 6 angular measurements using established anatomical landmarks. LASSO logistic regression was employed for variable selection and model shrinkage. The final model’s discriminative performance was assessed using the area under the receiver operating characteristic (ROC) curve (AUC), the Hosmer–Lemeshow test, and the Brier score. Results: A comparative analysis revealed that most linear and angular measurements showed significant sexual dimorphism. Almost all linear dimensions (A1–A22) were significantly larger in males (p < 0.001). Auricular width (A2) and width at the level of the tragus (A3) emerged as the most robust indicators, demonstrating “very large” effect sizes. Conversely, the angle between the preauricular line and the vertical plane (A28) was significantly greater in females, providing a unique inverse relationship for sex estimation. A parsimonious 5-predictor model (incorporating A2, A3, A5, A10, and A28) achieved exceptional discriminative performance with an AUC of 0.980. Conclusions: Auricular morphometry is a highly effective tool for sex estimation. The findings confirm significant sexual dimorphism in the external ear, particularly in linear dimensions. The developed model may serve as a preliminary morphometric reference for future automated biometric recognition studies, although no artificial intelligence-based classification model was developed in the present study. Full article

Although extensively studied in humans, data on the middle cranial fossa foramina remain limited in dogs, despite their different skull morphology and high relevance to veterinary neurology, surgery and oncology. In this retrospective anatomic study, we aimed to fill this gap by presenting the morphometric data of these foramina in domestic dogs of different breeds, ages, body weights, and skull sizes. The study used CBCT images of 40 dogs. Dogs were divided into three groups (small, medium, and large), regardless of sex, body weight, and breed, using neurocranium length. Then, morphological and morphometric analyses of the foramina were performed. The neurocranium length of each group differed significantly from the others (p < 0.001). In each group, the orbital fissure and round and oval foramina were bilaterally located rostrally to caudally and were of similar size (p > 0.05). While the orbital fissure was a canal in 80% of dogs, in dogs with medium and large skull sizes (17.5%), the spinous foramen showed variation, becoming both a foramen and a canal. The opening sizes increased along with the skull size (p < 0.001); the widest opening was the orbital fissure, and the narrowest opening (except for the spinous foramen) was the oval foramen. The findings may guide skull base surgeries, regional anesthesia, and the diagnosis of cranial nerve dysfunctions. Furthermore, a classification based on neurocranial length is anticipated to provide more objective craniometric measurements in animals with diverse head types and body weights. Full article

The development of digital photogrammetry techniques has revolutionized the study of marine ecosystems, enabling the generation of high-precision three-dimensional models from conventional imagery. Structure from Motion (SfM) algorithms have become effective tools for mapping and monitoring underwater habitats, offering a non-invasive and cost-effective alternative to traditional methods. This study presents a pilot methodological validation of SfM-based underwater photogrammetry for the non-invasive morphometric monitoring of vulnerable benthic species, using Pinna rudis. The research focused on refining photogrammetric methodologies for marine conservation, addressing technical challenges such as variations in light conditions, water turbidity, and image acquisition complexity. The study area, the Cabrera Archipelago Maritime-Terrestrial National Park, is a pristine marine environment in the western Mediterranean, hosting diverse benthic communities, including an abundant Pinna rudis population. Data acquisition comprises sampling by scuba diving techniques at depths ranging from 26 to 31 m, performed during the July 2022 field campaign within a permanent demographic plot established in 2013 and the methodology applied involved generating three-dimensional models using SfM, allowing for direct measurements of the seabed and extraction of morphometric parameters of sessile species. The characterization of the Pinna rudis aggregation was based on specimen density and size structure, determined using maximum shell width. The 3D model of the pilot plot covers 86.1 m², hosting 31 individuals. Morphometric measurements derived from SfM-based 3D models were validated against in situ diver measurements of maximum shell width. The results showed that the average maximum width obtained from 3D models (15.19 ± 3.23 cm) was consistent with in situ measurements (15.35 ± 3.48 cm). The mean difference between methods was −0.16 ± 0.82 cm, indicating a negligible systematic bias. The mean absolute error was 0.65 cm, corresponding to an average relative error of 4.34%, and a strong linear relationship was observed between both methods (r = 0.97). These results confirm that underwater photogrammetry is a reliable and non-invasive tool for monitoring vulnerable benthic species, providing high-resolution spatial and morphometric data to support conservation strategies in marine protected areas and allowing the collection of additional data compared to in situ surveys. Full article

Background/Objectives: Maggot debridement therapy (MDT) is an established biodebridement modality in chronic wound management; however, quantitative evidence regarding its effects on wound-healing dynamics remains limited. This study aimed to evaluate morphometric healing changes in chronic wounds treated with MDT using quantitative image-based analysis. Methods: This retrospective observational study analyzed archival records of patients who underwent MDT between 1 January 2024, and 1 January 2025. Wound images acquired according to a standardized clinical photography protocol were analyzed in ImageJ software (version 1.53k) after scale calibration. Lesion areas were measured in a blinded manner by two independent anatomy specialists. Morphometric data were analyzed using R, and healing trajectories were evaluated using the Kaplan–Meier method. Results: A total of 95 chronic wound cases were included. The mean age was 65 ± 11 years, and 73% of patients were male. Most lesions were localized to the foot (91%), and 40% were classified as stage 3 wounds. A total of 294 MDT sessions were performed. The mean wound-area reduction per session was 9.7% (median 6.6%). Wound-area reduction differed significantly across treatment sessions (H = 14; p = 0.008), with the greatest improvement during the first three sessions; pairwise analysis showed a significant difference between sessions 1 and 3 (p = 0.029). Approximately 18% of cases achieved ≥50% wound-area reduction, with a median of eight sessions required to reach this threshold. Age and sex were not significantly associated with healing outcomes. Conclusions: MDT facilitates measurable reductions in wound area and contributes to the healing process in chronic wounds. The findings suggest that the therapeutic effect of MDT may be more pronounced during the early treatment sessions and may help optimize treatment planning in chronic wound management. Full article

The following narrative review discusses the use of deep learning and 3D modeling in facial reconstruction from skeletal remains, focusing on accuracy, algorithmic bias, and evidential reliability. Forensic facial reconstruction (FFR) is a multidisciplinary field combining anthropology, medicine, and visual sciences to approximate the facial appearance of unidentified individuals from skeletal remains. Traditional manual methods, based on anatomical knowledge and facial soft tissue thickness (FSTT) measurements, are limited by subjectivity, labor intensity, and inter-expert variability. This narrative review summarizes contemporary AI-assisted approaches, with emphasis on convolutional neural networks (CNNs), generative adversarial networks (GANs), variational autoencoders (VAEs), and diffusion models, which enable probabilistic prediction of facial morphology while accounting for demographic variables such as sex, age, and population ancestry. Key challenges affecting reconstruction accuracy—including dataset limitations, population-specific variability, and algorithmic bias—are discussed, alongside quantitative validation methods and concerns regarding model transparency. Legal and ethical considerations, such as privacy, biometric data protection, and the need for explainable AI (XAI) frameworks, are highlighted. Future perspectives include hybrid expert–AI workflows, the development of globally representative datasets, and the integration of multimodal data sources, including DNA phenotyping, 3D morphometrics, and biomechanical modeling. These advances aim to create standardized, interpretable, and biologically informed frameworks that enable AI to support expert judgment and enhance the reliability of forensic facial reconstructions. Full article

Accurate body-weight measurement is important for precision pig farming, but conventional weighing methods are labor-intensive and may disturb normal animal activity. Although three-dimensional sensing systems can provide reliable geometric information, their deployment cost limits large-scale application in commercial farms. This study proposes a non-contact pig weight estimation framework based on standard RGB images. The framework combines SAM 2 foreground extraction with a transformer-based dorsal segmentation network to obtain stable body contours under complex farm conditions. Cross-covariance attention and local patch interaction modules are introduced to preserve both global body structure and local boundary details during segmentation. A hybrid loss function combining focal loss and label-distribution-aware margin loss is further adopted to address foreground-background imbalance. After segmentation, 17 morphometric features are extracted from the dorsal region and used for weight prediction with XGBoost regression. Experiments were conducted on the public PIGRGB-Weight dataset containing 12,476 RGB images from 124 pigs. The proposed method achieved a mean absolute error of 2.983 kg and an $R^2$ value of 0.9891. Compared with a DeepLabV3+-based baseline under the same regression protocol, the proposed framework reduced the prediction error by 24.1%. The results indicate that improving dorsal segmentation quality can substantially enhance the stability of morphometric feature extraction from low-cost RGB images. Full article

Schwann cells (SCs) are critical effectors of peripheral nerve regeneration, and their interaction with biomaterial scaffolds is a key parameter in neural tissue engineering. This pilot study described and evaluated protocols for a morphological, quantitative, and morphometric analysis of SCs seeded on electrospun polyhydroxybutyrate (PHB) scaffolds using variable-pressure scanning electron microscopy (VP-SEM) under a low vacuum, without a metal coating. Six protocols were compared, varying the number of seeded cells (50,000 or 100,000) and the method used to label the seeded face of the scaffold: no marking, graphite pencil, or permanent ink (Sharpie). Confocal microscopy confirmed SC viability and adhesion. The VP-SEM analysis revealed that seeding 100,000 cells significantly increased the number of detectable cells on the scaffold surface. Graphite labeling was associated with higher cell counts and a more stellate morphology, consistent with the biocompatibility of carbon-based materials reported in the literature. Conversely, ink labeling appeared to inhibit SC adhesion. A refined protocol for measuring SC extensions using ImageJ’s ROI Manager and segmented line tools was also established. These findings provide practical methodological insights to improve the reliability and reproducibility of SC morphological analyses on ultra-thin polymeric scaffolds, with implications for peripheral nerve regeneration research. Full article

Background/Objectives: This study evaluated the reproducibility of brain morphometric measurements obtained with different head coils and acceleration factors on a PET/MR scanner, with the aim of supporting reliability in longitudinal neuroimaging studies following major scanner hardware upgrades and introduction of higher-channel-density coils for improved image quality and shorter acquisition times. Methods: Fifteen healthy subjects underwent MPRAGE imaging on a 3T PET/MR scanner using a 16 channel head/neck coil with acceleration factor 2 and a 32 channel PET-transparent head coil with acceleration factors 2 and 4. Cortical thickness and subcortical volumes were measured with FreeSurfer. We performed correlation analyses to test the association between the values of cortical thickness and subcortical volumes derived from MPRAGE images acquired with either the 16- or the 32 channel coil. Test–retest variability and intraclass correlation coefficient were calculated to assess the reproducibility of the measurements for each brain region generated by each sequence and coil. Results: Cortical thickness and subcortical volume measurements from images acquired with different coils and acceleration factors showed high correlation (R = 0.96–1.00, p < 0.001) between protocols, with median test–retest variability below 4% for cortical thickness and a structure-dependent pattern for subcortical volumes, with higher variability in smaller structures such as the accumbens, reaching approximately 7.9% in cross-coil comparisons. Conclusions: Overall, brain morphometry measurements were reproducible across acquisition conditions. Coils with a higher number of channels were associated with improved signal-to-noise ratio, shorter acquisition times, and maintained quantitative consistency. Full article

Beach nourishment, as one of the most widely and effectively used coastal management measures recently, inevitably changes the coastal environment. This study aims to assess how the coastal profile is transformed during repeated beach nourishments with coarser-than-native sand in the Palanga recreational zone, Lithuania, Baltic Sea, using field survey data from the last three decades. When the granulometric composition of the sand is artificially changed during nourishment, the beach adapts to environmental changes by adjusting its morphometric parameters. These changes can be perceived as an intensification of coastal erosion, and, at the same time, a failure of the project. However, the results of this study show that these changes are associated with the transformation of the beach towards a morphologically adjusted state under the new sediment characteristics. In the Palanga case, the coarser-than-native sand used for nourishment led to narrower and steeper beaches compared to the pre-nourishment beaches composed of finer sand, and these characteristics persisted five years after nourishment. Therefore, the wide and low-slope beaches created during beach nourishment could not maintain the formed morphometric features with the coarser sand. For this reason, when implementing a replenishment project, it is important to predict the cross-shore profile that will develop for a given grain-size composition and quantity of the nourishment sand. Full article

Background/Objectives: The median nerve exhibits clinically relevant anatomical variability, with critical implications for surgical exposure, regional anesthesia, peripheral nerve repair, and diagnostic imaging. Despite extensive descriptive reports, quantitative morphometric analyses incorporating biological sex and donor record population classification remain limited, particularly among Hispanic cadaveric cohorts. Methods: This multi-institutional cadaveric study evaluated median nerve formation and segmental morphometry in 82 anatomical donors, each contributing paired bilateral upper limbs (164 upper limbs total), classified in institutional records as Puerto Rican, Caucasian, or African American. Standardized dissections were performed from the brachial plexus to the distal forearm, and linear measurements were obtained between predefined anatomical landmarks using digital calipers. Results: Mixed-effects modeling was used to evaluate morphometric differences associated with biological sex, donor record population classification, and anatomical location. Male specimens demonstrated localized differences in proximal median nerve formation, including a longer medial cord contribution on the left side. Population group comparisons identified greater measured morphometric distances in the Puerto Rican cohort compared with Caucasian and African American cohorts. Normalized LEH/MEH ratios did not differ between sexes, suggesting that some absolute differences may reflect limb-size scaling rather than proportional shifts in nerve position. Conclusions: These findings provide standardized landmark-based morphometric data and support the value of population-sensitive anatomical reference data for surgical planning and imaging-based interpretations of median nerve morphology. Full article

Accurate anatomical landmark detection is important for orthodontic analysis, surgical planning, and morphometric measurement, but fully supervised methods usually require large expert-annotated datasets. This work studies a one-shot setting, where only a single annotated template image is used for training. We propose a foundation-model-based landmark detection framework using a frozen DINO Vision Transformer (ViT) backbone. The proposed framework integrates three complementary components: a Multi-Layer Multi-Facet (MLMF) module that adaptively fuses key and value features from multiple ViT layers through global source-wise reweighting; a Mamba-Based Long-Range Context Aggregation (MLCA) module that injects global anatomical context into fused patch descriptors with linear complexity; and a Topology-Constrained Graph Refinement (TCGR) module that refines the predicted landmark configuration using anatomical graph constraints. Experiments on the Cephalometric dataset and the Hand X-ray dataset demonstrate that the proposed method achieves strong performance. Overall, the results show that jointly exploiting multi-source foundation-model representations, efficient long-range context aggregation, and topology-aware refinement improves annotation-efficient anatomical landmark detection. Full article