To quantitatively evaluate regional brain volume differences between pediatric patients with epilepsy and healthy controls using a fully automated volumetric magnetic resonance imaging (MRI) analysis performed with the Vol2Brain platform. This retrospective study included 150 children (75 with epilepsy and 75 healthy controls) who underwent 1.5 T cranial MRI examinations. High-resolution three-dimensional T1-weighted images were processed using Vol2Brain, a fully automated segmentation tool based on SPM12 and CAT12 frameworks. Absolute and relative volumes of 135 cortical and subcortical structures were computed. Statistical comparisons between groups were performed using the Shapiro-Wilk and Mann-Whitney U tests (p < .05). Patients with epilepsy demonstrated significantly lower volumes in the hippocampus, frontal and temporal gray matter, thalamus, cerebellum, and total brain compared with controls, accompanied by a compensatory increase in cerebrospinal fluid volume. No significant volumetric differences were found in the remaining 128 brain structures, indicating a diffuse morphometric reorganization pattern extending beyond the epileptogenic focus. Fully automated volumetric MRI analysis using vol2Brain can reliably detect widespread structural brain alterations in pediatric epilepsy. These findings support the concept of epilepsy as a diffuse network disorder extending beyond focal lesions. Quantitative morphometry provides an objective approach to characterize subtle structural reorganization and may serve as a basis for future studies investigating clinical and neurocognitive correlations in pediatric epileptology.

Introduction The intervertebral disc herniation (IVDH) is one of the most common causes of spinal injury in dogs. Certain breeds, notably chondrodystrophic dogs, are predisposed to severe thoracolumbar IVDH due to anatomical and genetic factors. Methods This study applied three dimensional (3D) volumetric imaging analysis to compare the spinal canal volume and to investigate the relationship between canal volume and neurological symptoms severity. We retrospectively analyzed 21 dogs (7 Bichon Frisé, 7 Dachshund and 7 French Bulldogs) with imaging confirmed thoracolumbar disc herniation. Computed tomography (CT) scans were segmented using 3D Slicer to quantify the bony spinal canal volume from the cranial to caudal end of the vertebral column. Results and discussions French Bulldogs showed a significantly larger mean spinal canal volume than those of Dachshunds and Bichons ( p &amp;lt; 0.05 for both comparisons). Across all dogs, smaller canal volumes were associated with more severe neurological deficits (Spearman ρ ≈ −0.72, p = 0.0014). Across all breeds, disc herniations were most frequently observed at the thoracolumbar junction (T12–L2; 5 of 21 cases), but substantial overlap existed with neighboring segments. The thoracolumbar junction is especially susceptible to disc herniation because it is a transition zone between the rigid thoracic spine and the mobile lumbar spine, where mechanical stress is concentrated and spinal canal reserve space is limited. The 3D volumetric analysis of the vertebral canal is a feasible adjunct to routine imaging and reveals significant breed specific differences. Narrower canal volume appears to exacerbate the impact of disc herniation on the spinal cord, suggesting that canal size is a contributing risk factor for neurologic severity. A critical volume threshold (~1,700 mm 3 per vertebral segment) was observed, under which dogs were markedly more likely to develop severe deficits.

Current reference standards for measuring gastric emptying and motility are not considered optimal due to the time required, ionizing radiation, invasiveness, and spatial resolution. To assess gastric motility using novel real-time dynamic magnetic resonance imaging in combination with static measurements for gastric emptying and training of an automated deep-learning-based segmentation pipeline. Prospective. The study included 36 healthy volunteers (20 female, mean 24 ± 3 years) and three patients with diagnosed Crohn's disease. Participants ingested water to assess fasting motility and pineapple juice for the postprandial state. 3 T, 3D spoiled gradient echo (GRE) sequence and real-time spoiled GRE. Gastric emptying was measured by using the gastric volume, while motility was analyzed by tracking changes in the antrum's cross-sectional area and applying Fast Fourier Transformation. Segmentations were performed using a trained semantic segmentation model. Linear Mixed Model with continuous dependent variables and fixed effects. Models included a random intercept for participants. Statistical significance was defined as p = 0.05. The method enabled volumetric analysis of gastric content from 3D breath-hold static acquisition and time-resolved quantification of peristaltic parameters from real-time FLASH2 imaging at high temporal resolution (here 6.24 fps). Water emptied rapidly and exponentially (t1/2 = 14.77 ± 10.55 min), while juice showed slower emptying (t1/2 = 64.24 ± 11.87 min). Contraction frequencies (fasted: 2.76 ± 0.43 cpm, fed: 2.89 ± 0.43 cpm) and velocities (fasted: 1.67 ± 0.38 mm/s, fed: 1.72 ± 0.37 mm/s) were within physiological ranges, with fasting conditions characterized by stronger occlusion compared to the fed. Measurements taken from three patients proved that the workflow could be used in a clinical context. Real-time MRI with AI-based analysis enabled quantitative assessment of gastric emptying and motility, revealing physiological peristaltic parameters and state-dependent differences in occlusion. 2. Stage 1.

Low-dose computed tomography (LDCT) employed in lung cancer screening (LCS) programmes is increasing in uptake worldwide. LCS programmes herald a generational opportunity to simultaneously detect cancer and non-cancer-related early-stage lung disease, yet these efforts are hampered by a shortage of radiologists to interpret scans at scale. Here, we present TANGERINE, a computationally frugal, open-source vision foundation model for volumetric LDCT analysis. Designed for broad accessibility and rapid adaptation, TANGERINE can be fine-tuned off the shelf for a wide range of disease-specific tasks with limited computational resources and training data. The model is pretrained using self-supervised learning on more than 98,000 thoracic LDCT scans, including the United Kingdom's largest LCS initiative to date and 27 public datasets. By extending a masked autoencoder framework to three-dimensional imaging, TANGERINE provides a scalable solution for LDCT analysis, combining architectural simplicity, public availability, and modest computational requirements. TANGERINE demonstrates superior computational and data efficiency in a retrospective multi-dataset analysis: it converges rapidly during fine-tuning, requiring significantly fewer graphics processing unit hours than models trained from scratch, and achieves comparable or superior performance using only a fraction of the fine-tuning data. The model achieves strong performance across 14 disease classification tasks, including lung cancer and multiple respiratory diseases, and generalises robustly across diverse clinical centres. TANGERINE's accessible, open-source, lightweight design lays the foundation for rapid integration into next-generation medical imaging tools, enabling lung cancer screening programmes to pivot from a singular focus on lung cancer detection toward comprehensive respiratory disease management in high-risk populations.

Differentiation of venous thrombus consistency in patients with renal cell carcinoma using volumetric analysis of computed tomography first-order radiomic features.

A comparison study to assess U-Net driven volumetric versus single-slice analysis and MRI sequences with different volume coverage to detect renal sinus fat in people with and without diabetes.

Recent advances in the development of antivascular endothelial growth factor (VEGF) therapy for neovascular age-related macular degeneration (nAMD) include the approval of aflibercept 8mg, which delivers four times the previously commercially available dose. A longer durability of aflibercept 8mg compared with 2mg was reported in the clinical trial results. However, there are limited data in patients switching to aflibercept 8mg from other agents in clinical practice. This study reports the initial real-world experience of consecutive patients switched to aflibercept 8mg. Consecutive eyes with previously treated nAMD receiving aflibercept 8mg switched from other agents were retrospectively reviewed. Patients were switched either owing to suboptimal control of disease activity (efficacy group) or to potentially extend treatment intervals (durability group). The main outcome measures included change in optical coherence tomography (OCT)-based anatomical parameters, including central subfield thickness (CST) and presence of subretinal fluid (SRF), intraretinal fluid (IRF), and pigment epithelial detachment (PED) before and after switching. In addition, quantification of OCT biomarkers was performed using the RetinAI Discovery algorithm. A total of 30 eyes from 29 patients were identified. Among the 25 eyes in the efficacy group, 20 eyes remained on aflibercept 8mg through to the last follow-up visit. Median CST showed a significant reduction from 291 (275-301) µm to 279 (269-289) µm (p = 0.02). Volumetric analysis showed a significant reduction in SRF volume, a small nonsignificant increase in IRF volume, and a trend toward reduction in PED volume. The five eyes in the durability group had no SRF, IRF, or hemorrhage at the time of switching and remained stable during the follow-up period. These results provide early experience of aflibercept 8mg in a clinical cohort in hard-to-treat patients. The current analysis demonstrated favorable anatomical outcomes after switching in most patients, with no safety signals.

People with Cystic Fibrosis (CF) experience significant sinonasal airway opacification, leading to chronic airway-related conditions. The triple combination therapy Elexacaftor/Tezacaftor/Ivacaftor (ETI) has emerged as a therapeutic option for CF. This study uses volumetric quantification technique to evaluate changes in CF sinonasal airway patency pre-ETI and post-ETI. Anatomically accurate person-specific three-dimensional sinonasal airspaces were reconstructed from radiographical images of 19 people (12 male, 7 female) with CF, pre-ETI and post-ETI. Sinonasal airspace surface area, volume, and surface-area-to-volume ratio were calculated pre-ETI and post-ETI. Pre-ETI and post-ETI sinonasal airspace changes in these computed parameters were corrected with changes in both Lund-Mackay and SNOT-22 scores. Median (IQR) surface area and volume increased significantly from pre-ETI (Surface Area: 251.97 cm2 (43.71); Volume: 44.86 cm3 (20.72)) to post-ETI (Surface Area: 295.77 cm2 (31.34); Volume: 61.03 cm3 (14.21)), with respective p < 0.01 per computed parameter. Furthermore, median surface-area-to-volume ratio (IQR) was significantly different; pre-ETI: 0.053 cm-1 (0.007); post-ETI: 0.052 cm-1 (0.013); p = 0.04. Pre-ETI to post-ETI improvement changes in surface area and volume significantly correlated with corresponding changes in Lund-Mackay scores (Surface Area: R = -0.78, p < 0.01; Volume: R = -0.68, p < 0.01), but correlated weakly with corresponding changes in patient-reported SNOT-22 scores (Surface Area: R = -0.13, p = 0.62; Volume: R = -0.06, p = 0.82). People with CF treated with ETI exhibited a significant increase in sinonasal airway patency, as evidenced by volumetric quantification analysis of surface area and volume differences. These increases in both parameters showed strong significant correlations with Lund-Mackay scores; however, no such correlations were observed with SNOT-22 scores.

Previous studies have established that parental consumption of a diet high in fat and simple sugar (HF/HSS) leads to long-term effects on offspring brain development. However, most studies have focused on the effects of maternal diets or the combined effects of both parents' diets. As literature suggests that fathers' environmental factors can also impact offspring brain development, we aimed to explore the impact of isolated paternal consumption of an HF/HSS diet on offspring brain structure. C57Bl/6J male mice were acclimated to an HF/HSS diet for eight weeks prior to mating with females who consumed standard chow (control diet, CD). A matching paternal control group was fed the CD during the acclimation period. Throughout gestation and lactation all dams and offspring were fed the CD; all pups were weaned at postnatal day 21 (P21) and stayed on the CD. At P42 offspring brains were prepared for ex vivo magnetic resonance imaging (MRI). Brain MR images were then segmented for volumetric structural analysis. HF/HSS-fed sires gained more weight during acclimation than CD sires (p < 0.001). However, offspring weights at weaning (P21) and at endpoint (P42) were not significantly affected by paternal diet. Offspring brain morphology, as assessed by volume measurements of 185 brain structures, was not significantly affected by sire HF/HSS diet alone. While small structural changes cannot be ruled out, the results suggest that previously observed changes in offspring brain structure attributed to parental consumption of HF/HSS diet (selected to mimic some aspects of the human "Western Diet") require maternal consumption.

Abstract Background Accurate prediction of atrial fibrillation recurrence remains challenging despite rhythm control strategies. Echocardiographic markers such as left atrial (LA) strain components have shown predictive value, but their utility may be affected by technical and clinical factors. Indices reflecting atrioventricular (A-V), ventriculo-atrial (V-A), and right atrial-right ventricular (RA-RV) coupling remain underexplored and may offer additional prognostic insight. Purpose To assess the prognostic significance of established echocardiographic markers and coupling indices for AF recurrence in a homogeneous cohort of patients with paroxysmal AF (PAF). Methods We prospectively studied 73 patients (mean age 59.6±11.6 years; 52% female) with PAF in sinus rhythm at baseline. All underwent comprehensive transthoracic echocardiography including strain and volumetric analysis. AF recurrence was documented over 12 months via ECG, Holter monitoring, or clinical documentation of symptomatic episodes. Variables and coupling indices, including LA volume index (LAVI), LA strain components, E/e’, LA coupling index (LACI), right ventricular fractional area change (RV FAC)/right atrial (RA) volume, tricuspid annular plane systolic excursion (TAPSE)/pulmonary arterial systolic pressure (PASP), were assessed using univariable logistic regression. Significant predictors were entered into multivariable analysis. Results At baseline, recurrence (n=31) and non-recurrence (n=42) groups were similar in age, sex, cardiovascular risk factors, and medication use (all p&amp;gt;0.05), confirming group homogeneity. Most conventional markers, including LAVI, LAEF, E/e’, and LA reservoir or conduit strain, were not associated with recurrence. Coupling indices across the left and right heart also lacked predictive value (all p&amp;gt;0.05). Univariable analysis identified 3 significant predictors: lower RV FAC (OR=0.918 per 1% increase; 95% CI: 0.854–0.987; p=0.020), reduced LA contraction strain (OR=0.886, 95% CI: 0.790–0.994, p=0.039), and a higher LA contraction strain/LAVI ratio (OR=12.238; 95% CI: 1.294–115.775; p=0.029), possibly reflecting mechanical-structural mismatch. In multivariable analysis, RV FAC remained independently predictive (OR=0.921; p=0.034), while the LA contraction strain/LAVI ratio showed a borderline association (OR=14.769, 95% CI: 0.806–84.792, p=0.076) (Table 1). LA contraction strain alone lost significance. Our findings are illustrated in Figure 1, showing measurement of LA contraction strain and RV FAC, two key predictors of AF recurrence in this cohort. Conclusions In this homogeneous PAF cohort, conventional left heart indices and coupling markers were not predictive of recurrence. Instead, impaired RV systolic function and reduced atrial contractile efficiency indexed to atrial size emerged as more relevant predictors. These findings highlight the underrecognized importance of RV function and LA mechanical–structural mismatch in AF risk stratification.

Gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) are heterogeneous tumors with rising incidence, necessitating precise preoperative grading for treatment planning. Existing imaging techniques and endoscopic biopsies often fall short due to insufficient markers and tissue samples. Body composition influences tumor biology, yet traditional 2D assessments are time-consuming and lack objectivity. This study aimed to develop a rapid non-invasive predictive model by integrating automatic segmented abdominal volumetric body composition with machine learning to differentiate between low-grade and high-grade GEP-NENs. This multicenter retrospective cohort study enrolled 633 patients with GEP-NENs from three institutions. Patients were divided into: Training set (n=403) and internal validation (n=174) (7:3 ratio from Hospital 1); test set (n= 56 from 2 other hospitals). An nnUNetv2-based automatic segmentation algorithm for abdominal fat tissue and skeletal muscle on arterial-phase CT was applied. Visceral fat index, subcutaneous fat index, intermuscular fat index and skeletal muscle index were calculated. Features with a P-value < 0.05 were selected using univariate logistic regression and included in the prediction model built using the extreme gradient boosting algorithm. Receiver operating characteristic (ROC) curves and decision curve analysis (DCA) were performed to evaluate the utility of the model. SHapley Additive exPlanations (SHAP) was conducted to enhance model interpretability and visualization. The automatic segmentation achieved a Dice coefficient of 0.98. For pathological grading, the model built using body composition parameters achieved an AUC of 0.863 in the training set, 0.750 in the validation set, and 0.717 in the test set. SHAP analysis revealed that the relative intermuscular adipose tissue (rIMAT) contributed the most among the body composition parameters to the model decision-making, and rIMAT levels were higher in P53-mutant and CK19-positive cases compared to negative cases. Auto-segmented abdominal body composition combined with a machine learning-based model could provide an assisted, non-invasive tool for predicting pathological grade in GEP-NENs.

Objectives To assess the reliability of semi-quantitative and AI-based quantitative brain volume evaluation (Quantib® ND) in predicting clinical diagnosis in patients with suspected neurodegenerative diseases undergoing initial 1.5 T MRI. Additionally, to analyze the frequency of lobar microbleeds (MBs) at diagnosis. Methods Two neuroradiologists (2 vs. 10 years’ experience), blinded to diagnosis, independently evaluated brain atrophy on 3D-T1 images of 133 subjects using Scheltens, Koedam, and Kipps scales. Automated volumetric analysis was performed using Quantib® ND. SWI images were assessed by one neuroradiologist to classify MBs as cortical, juxtacortical, subcortical, or deep. Inter-observer agreement was measured using intraclass correlation coefficients (ICC); correlation with Quantib® ND was analyzed using Spearman's coefficient. Cohen's Kappa assessed agreement with clinical diagnosis. Results Good inter-observer agreement was observed for the MTA scale (ICC 0.86 right, 0.82 left) and Kipps scale (ICC 0.76), with moderate concordance for Koedam (ICC 0.66). Frontal and posterior temporal Kipps subregions had good concordance (ICC 0.77, 0.79), while anterior temporal showed poor agreement (ICC 0.59). Diagnostic accuracy was moderate across observers and Quantib® ND. Observer 1 showed 77% sensitivity, 51% specificity; observer 2 had 79% sensitivity, 62% specificity; Quantib® ND reached 56% sensitivity, 74% specificity. Patients exhibited significantly more lobar MBs than non-dementia patients ( χ 2 p = 0.04). Conclusions Semi-quantitative visual scales proved effective and sensitive for detecting brain atrophy, showing good concordance with automated volumetric data. While AI-based quantification demonstrated higher specificity, visual assessment remained more sensitive. Lobar MBs were more frequent in neurodegenerative cases.

Ultra-low-field (ULF) point-of-care (PoC) Magnetic Resonance Imaging (MRI) offers a promising pathway to improve accessibility in medical imaging due to its portability and lower cost. However, the diagnostic utility of ULF MRI is currently limited by lower image quality, particularly in signal-to-noise ratio, resolution, and contrast. To address this, we introduce SynPoC, a generative diffusion model designed to enhance ULF MRI by synthesizing high-field MRI-like images. SynPoC employs a conditional adversarial diffusion framework that leverages both noise and contrast-specific features to model inter-field representations. We evaluated SynPoC across a multi-site dataset of 180 participants, including both healthy individuals and patients with a variety of brain conditions. The enhanced images exhibited improved anatomical clarity and structural alignment with corresponding high-field MRI, as supported by quantitative and volumetric analyses. Our model demonstrates promise for image quality enhancement and research applications; however, as with other generative approaches, there is a non-zero risk of hallucinated or misleading features, particularly near low-SNR boundaries and fine structures. We therefore provide synchronized slice-by-slice comparison videos (3T, PoC, SynPoC) to aid reader inspection and emphasize that SynPoC is not intended for diagnostic decision-making without additional safeguards and validation. Further validation is warranted before diagnostic use.

Root resorption corresponds to the progressive loss of mineralized dental tissues and may occur in a physiological, pathological, or idiopathic manner. This resorption can affect both the internal and external surfaces of the tooth, presenting different etiological mechanisms, radiographic patterns, and therapeutic implications. Early diagnosis is crucial for the prognosis of the dental element and for defining the most appropriate clinical approach; however, diagnosis often occurs sporadically during routine clinical and radiographic examinations, making a favorable prognosis more difficult. Conventional radiographs, such as periapical and panoramic images, are widely used as initial evaluation methods; nevertheless, because they are two-dimensional examinations, they present important limitations, including structural overlap, distortions, and low sensitivity for early lesions, with computed tomography being the most satisfactory examination for diagnosing this condition. This study is characterized as a narrative literature review, conducted through a systematized survey of scientific literature in the PubMed, Scopus, and Web of Science databases, using the descriptors “Tooth Resorption,” “Root Resorption,” “Radiography,” and “Diagnosis,” combined with Boolean operators; articles published in the last five years, available in full text and directly addressing the use of radiographic methods in the diagnosis of internal and external root resorptions were included, while duplicate studies, isolated case reports, and publications lacking methodological rigor were excluded. The selection process occurred in stages, including the reading of titles and abstracts and the critical analysis of full texts. The results demonstrate that Cone Beam Computed Tomography presents greater sensitivity and specificity compared to conventional radiographs, enabling detailed three-dimensional visualization, better differentiation between types of resorption, and volumetric analysis of root loss, leading to the conclusion that CBCT is a fundamental tool for the diagnosis and monitoring of root resorptions, especially in complex cases involving recovery and orthodontic movement.

Abstract. Light Detection and Ranging (LiDAR) has become a powerful technology for acquiring dense 3D point clouds with high spatial accuracy, enabling volumetric analysis and topographic characterization at multiple scales. Terrestrial Laser Scanner (TLS), here after LiDAR, have expanded their use from natural resource management to the structural health monitoring (SHM) of critical civil infrastructure in dynamic and hazard-prone environments. This study focused on inspecting and documenting infrastructure conditions along the three main rivers of the Monterrey Metropolitan Area: Pesquería, La Silla, and Santa Catarina. The objective was to assess structural integrity and identify elements requiring preventive maintenance or removal. Photographic datasets were compared with Google Street View and Google Earth Pro imagery to geolocate and detect visible changes. Based on this initial analysis, 5 to 6 structures per river were selected for detailed surveys using TLS equipment. TLS data were processed to create detailed plans and 3D models of each structure. Technical files were completed to document structural characteristics, condition assessments, repair proposals, and risk and accessibility analyses. This study demonstrates an effective methodology for SHM of riverine infrastructure. It also emphasizes the need for multidisciplinary expertise—including engineering, geospatial analysis, and urban planning—to support evidence-based public policy. The resulting datasets can inform hydrological and hydraulic modeling, enhance resilience assessments, and guide urban planning, construction strategies, and civil protection efforts in one of Mexico’s most vulnerable metropolitan regions.

To compare the extent of root resorption, assessed via three-dimensional (3D) volumetric CBCT analysis, between tooth-borne and bone-borne rapid maxillary expansion (RME) devices. A systematic search of seven databases (PubMed, Cochrane Library, Embase, etc.) up to December 2024 identified eligible studies (randomised controlled trials, cohort studies, clinical trials) evaluating CBCT-measured root resorption in patients treated with tooth-borne, bone-borne or hybrid RME devices. Data were analysed using STATA 17.0, employing weighted mean differences (WMDs) and random/fixed-effects models. Heterogeneity, subgroup analyses and publication bias were assessed. Sixteen studies (525 patients, 2906 teeth) were included. These studies comprised randomised controlled trials and observational studies, predominantly enrolled adolescent and young adult patients, and directly compared tooth-borne and bone-borne RME devices. Tooth-borne RME resulted in significantly greater root resorption volume compared to bone-borne devices (WMD = -10.4 mm3, 95% CI [-13.9, -6.9], 95% prediction interval [-11.94, -8.92], p < 0.05; I2 = 98.8%). Tooth-borne RME also caused greater root length loss (WMD = -0.14 mm, 95% CI [-0.21, -0.08], 95% prediction interval [-0.20, -0.08], p < 0.05; I2 = 95.6%). Tooth-borne RME resulted in significantly greater root resorption volume (WMD = -20.7 mm3) and length (WMD = -0.40 mm) compared to baseline, indicating increased resorption. Three-dimensional CBCT analysis demonstrated superior sensitivity in detecting resorption morphology and localization compared to linear measurements. Bone-borne RME devices, which are associated with reduced root resorption risks, may be related to improved force distribution to bony structures. Three-dimensional volumetric CBCT assessment provides a more accurate quantification than linear measurements. Clinically, bone-borne expanders are recommended for high-risk patients, while tooth-borne users require close CBCT monitoring. Findings should be interpreted considering limitations of the included evidence, including heterogeneity in RME devices and protocols, risk of bias in some non-randomised studies, and imprecision due to limited sample sizes in subgroup analyses and lack of long-term data. Trial Registration: International Prospective Register of Systematic Reviews (PROSPERO) registration number: CRD420251018535.

Marginal impaction in acetabular posterior wall fractures significantly influences long-term prognosis, yet current assessment methods remain qualitative. This study introduces quantitative volumetric analysis using three-dimensional computed tomography to evaluate the prognostic significance of impaction volume-representing the first volumetric quantification of marginal impaction in the literature. Twenty-two patients with acetabular posterior wall fractures and marginal impaction treated between May 2021 and October 2023 at a tertiary trauma center were retrospectively analyzed. Preoperative computed tomography scans were processed using 3D Slicer-5.8.1 software to measure impacted fragment volumes and impaction volume-to-acetabular volume ratios. Functional outcomes were assessed using Harris Hip Score (HHS) and Modified Merle d'Aubigné-Postel Score (MMAS) at 6 months and 2 years. Statistical analysis included correlation analysis, receiver operating characteristic curves, and multivariate regression to identify prognostic factors. Mean patient age was 45.3 ± 16.8 years (range 23-74) with mean body mass index of 26.4 ± 3.8 kg/m2. Mean impaction volume was 1,847.3 ± 1,124.6 mm3 (range 89-3,842 mm3). Receiver operating characteristic curve analysis identified an exploratory threshold of 2000 mm3 for predicting poor functional outcomes, with area under the curve 0.91 (95% CI: 0.78-1.00, p < 0.001). Patients with impaction volumes > 2000 mm3 (n = 8, 36.4%) demonstrated significantly worse functional outcomes at 2 years compared to those with ≤ 2000 mm3 (HHS: 68.3 ± 10.8 vs 88.5 ± 7.2, p < 0.001; MMAS: 13.4 ± 2.3 vs 17.6 ± 1.2, p < 0.001). Post-traumatic osteoarthritis developed in 9 patients (40.9%), with significantly higher rates in the high-volume group (75.0% vs 21.4%, p = 0.012). Impaction volume showed strong negative correlation with functional scores at 2 years (HHS: r = -0.782, p < 0.001; MMAS: r = -0.758, p < 0.001). The impaction volume-to-acetabular volume ratio averaged 5.12 ± 3.15% and demonstrated similar prognostic value. This study presents the first quantitative volumetric measurement of marginal impaction in acetabular fractures, which may offer improved prognostic discrimination compared to qualitative assessment in this cohort. An exploratory threshold of 2000 mm3, derived from receiver operating characteristic analysis, appears to stratify patients into different risk categories in this cohort for poor functional outcomes. This objective measurement tool may enhance surgical decision-making and patient counseling in acetabular fracture management. Future multicenter studies are needed to validate this threshold and establish standardized volumetric protocols.

Tissue clearing has transformed volumetric imaging by improving optical access to thick tissues, yet most existing protocols remain rigid and fail to accommodate the biochemical diversity of different samples. Here, we introduce a question-oriented modular framework that enables flexible assembly of clearing and imaging pipelines tailored to specific biological objectives. By systematically optimizing each module to preserve endogenous fluorescence, antigenicity, and tissue integrity while achieving high transparency and protein retention, we demonstrate its use across diverse cardiac applications—development, infarction and regeneration, as well as immune and vascular mapping—showing that different questions require distinct module assemblies and parameters. Coupled with light-field microscopy (LFM), the workflow efficiently captures submillimeter sections with 30–100-fold smaller datasets and rapid computational reconstruction, enabling high-throughput quantitative volumetric analysis. Together, this modular framework and imaging integration provide a rational and practical foundation for adaptable and interoperable 3D analyses of regenerative, pathological, and comparative systems across vertebrate models.

Hypertrophic cardiomyopathy (HCM), a genetic heart disease defined by unexplained cardiac wall thickening, is a leading cause of sudden death worldwide. However, the three-dimensional organization of cardiac tissue underlying left ventricular hypertrophy remains poorly understood. We developed CaMVIA-3D, a deep-learning volumetric imaging and analysis pipeline to characterize cardiac microarchitecture. Analysis of tissues from HCM hearts revealed genotype-specific differences in cardiomyocyte volume, morphology, and extracellular volume, with pathogenic variants exhibiting greater concentric cellular hypertrophy and disarray and variant-negative cases showing predominant fibrosis. Longitudinal profiling of a pig HCM model revealed early-onset fibrosis preceding cardiomyocyte hypertrophy. Integrating transcriptomic and morphologic changes, we identified genes associated with cellular and extracellular remodeling. These findings define genotype-specific microstructural differences in HCM, offering insights to improve diagnostics and targeted therapies.

To compare the clinical outcomes of patient-specific customized 3D-printed titanium meshes (PSIs) and stock titanium meshes in orbital floor reconstruction. This retrospective case series included 48 patients undergoing orbital floor repair between June 2024 and March 2025. Patients were divided into Group 1 (n = 22) receiving custom 3D-printed titanium meshes and Group 2 (n = 26) receiving stock titanium meshes. Operative time, orbital volume restoration (via 3D volumetric analysis), resolution of enophthalmos, diplopia, and infraorbital paresthesia were assessed. Volumetric measurements were performed using semi-automatic segmentation based on CT scans. The 3D-printed meshes achieved a better restoration of orbital volume, with a mean reduction in volumetric discrepancy of 89% (SD ± 28%), compared to 51% (SD ± 35%) in the standard mesh group (P = 0.036). No statistically significant differences were observed in operative time or in the resolution of paresthesia. However, a statistically significant difference between the two groups was found in the resolution of both enophthalmos and diplopia (P = 0.025 and P = 0.028). Custom 3D-printed titanium meshes showed improved anatomical accuracy and volumetric outcomes compared to stock meshes. Further prospective studies with long-term follow-up are necessary to confirm these findings and assess cost-effectiveness.