Multiparametric assessment of right ventricular function in heart transplant recipients by echocardiography and relations with pulmonary hemodynamics.

OBJECTIVE: Right ventricular (RV) dilatation and dysfunction are usually present in heart transplant (HTx) patients and worsened with residual pulmonary hypertension (PH). We aimed to determine the ability of different echocardiographic modalities to evaluate RV function in comparison with cardiac magnetic resonance (CMR) and their relations with pulmonary hemodynamics in HTx patients. METHODS: A total of 62 data sets [echocardiographic, hemodynamic, and CMR] were acquired from 35 HTx patients. Comprehensive echocardiography, including two-dimensional (2D) transthoracic echocardiography, speckle tracking echocardiography, and three-dimensional (3D) echocardiography, was performed. Mean pulmonary artery pressure (mPAP) was obtained invasively from right heart catheterization. The correlations between all echocardiographic parameters and CMR imaging data and the differences between patients with and without residual PH were evaluated. RESULTS: Diastolic and systolic RV volumes and RV ejection fraction (RVEF) by 3D echocardiography correlated strongly with CMR-derived volumes and RVEF (r = .91, r = .79, r = .64; p < .0001 for each, respectively). Among other parameters, RV fractional area change (r = .439; p < .001) and RV free wall longitudinal strain (RVFW-LS) (r = -.34; p < .05) correlated moderately with CMR-RVEF, whereas tricuspid annulus S' velocity (r = .29; p < .05) and tricuspid annular systolic plane excursion (r = .27; p < .05) correlated weakly with CMR-RVEF. Additionally, 3D-RVEF and RVFW-LS were significantly decreased in studies with mPAP ≥ 20 mm Hg in comparison to those with mPAP < 20 mm Hg (47.7 ± 3.7 vs. 50.9 ± 5.3, p = .04 and -15.5 ± 3.1 vs. -17.5 ± 3, p = .03, respectively). CONCLUSION: The best method for the evaluation of RV function in HTx recipients is 3D echocardiography. Besides, the subclinical impact of residual PH on RV function can be best determined by RVFW-LS and 3D-RVEF in these patients.

Deciphering the "Art" in Modeling and Simulation of the Knee Joint: Assessing Model Calibration Workflows and Outcomes.

Model reproducibility is a point of emphasis for the National Institutes of Health (NIH) and in science, broadly. As the use of computational modeling in biomechanics and orthopedics grows, so does the need to assess the reproducibility of modeling workflows and simulation predictions. The long-term goal of the KneeHub project is to understand the influence of potentially subjective decisions, thus the modeler's "art", on the reproducibility and predictive uncertainty of computational knee joint models. In this paper, we report on the model calibration phase of this project, during which five teams calibrated computational knee joint models of the same specimens from the same specimen-specific joint mechanics dataset. We investigated model calibration approaches and decisions, and compared calibration workflows and model outcomes among the teams. The selection of the calibration targets used in the calibration workflow differed greatly between the teams and was influenced by modeling decisions related to the representation of structures, and considerations for computational cost and implementation of optimization. While calibration improved model performance, differences in the postcalibration ligament properties and predicted kinematics were quantified and discussed in the context of modeling decisions. Even for teams with demonstrated expertise, model calibration is difficult to foresee and plan in detail, and the results of this study underscore the importance of identification and standardization of best practices for data sharing and calibration.

Radiological management and challenges of the twin earthquakes of February 6th.

Two major earthquakes measuring 7.8 and 7.7 on the Richter scale struck Turkey and Northern Syria on February 6, claiming more than 50,000 lives. In such an unprecedented disaster, radiologists were confronted with very critical tasks of stepping out of the routine reporting process, performing radiological triage, managing acute adverse events, and optimizing imaging protocols. In our experience, radiologists can take three different positions in such disasters: (1) in the scene of the disaster, (2) serving in teleradiology, and (3) working in tertiary hospital for transported patients. With this article, we aimed to describe the challenges radiologists face on the three main fronts and how we manage these challenges.

Imaging in crush injury: a spectrum of findings in survivors of the twin earthquakes on February 6, 2023.

On February 6, two major earthquakes with magnitudes of 7.8 and 7.7 on the Richter scale hit Turkey and Northern Syria causing more than 50,000 deaths. In the immediate aftermath of the earthquakes, our major tertiary medical referral center received dozens of cases of crush syndrome, presenting with a variety of imaging findings. Crush syndrome is characterized by hypovolemia, hyperkalemia, and myoglobinuria that can lead to rapid death of victims, despite their survival of staying under wreckage for days. The typical triad of crush syndrome consists of the acute tubular necrosis, paralytic ileus, and third-space edema. In this article, we focus primarily on characteristic imaging findings of earthquake-related crush syndrome and divided them into two distinct subsections: myonecrosis, rapid hypovolemia, excessive third-space edema, acute tubular necrosis, and paralytic ileus, which are directly related to crush syndrome, and typical accompanying findings of earthquake-related crush syndrome. Lower extremity compression in earthquake survivors results in the typical third-space edema. In addition to the lower extremities, other skeletal muscle regions are also affected, especially rotator muscles, trapezius, and pectoral muscles. Although it may be relatively easy to better detect myonecrosis with contrast-enhanced CT scans, changing the windowing of the images may be helpful.

Evaluation of atrial fibrosis in atrial fibrillation patients with three different methods.

BACKGROUND: The presence of atrial fibrosis has already been known as a risk factor for atrial fibrillation (AF) development. We aimed to evaluate atrial fibrosis with previously defined three different methods, which were cardiac magnetic resonance imaging (C-MRI), echocardiographic strain imaging, and biomarkers and show the relationship between these methods in patients with AF scheduled for cryoballoon ablation. METHODS: A total of 30 patients were enrolled. Atrial T1 relaxation durations were measured using C-MRI before the procedure of atrial fibrillation catheter ablation. Fibroblast growth factor-21 (FGF-21) and fibroblast growth factor-23 (FGF-23) levels were measured at serum derived from the femoral artery (Peripheral FGF 21 and 23) and left atrium blood samples (Central FGF 21 and 23) before catheter ablation. Preprocedural transthoracic echocardiography was performed. The median follow-up duration for atrial tachyarrhythmia (ATa) recurrence was 13 (12-18 months) months. RESULTS: The mean ages of the study group were 55.23 ± 12.37 years, and there were 17 (56.7%) female patients in study population. There were negative correlations between post contrast T1 relaxation durations of both posterior and posterosuperior atrium, and central FGF-23 (r: - 0.561; p = 0.003; r:-0.624; p = 0.001; Posterior T1 vs. central FGF-23 levels and Posterosuperior T1 vs central FGF-23 levels, respectively). The positive correlations were observed between postcontrast posterior T1 relaxation durations and left ventricle ejection fraction (r:0.671; p = 0.001); left atrial emptying fraction (r:0.482; p = 0.013); peak atrial longitudinal strain (r:0.605; p = 0.001), and peak atrial contraction strain (r:0.604; p = 0.001). Also negative correlation was observed between postcontrast posterior T1 relaxation durations, and left atrial volume index (r: - 0.467; p = 0.016).

Deciphering the "Art" in Modeling and Simulation of the Knee Joint: Variations in Model Development.

The use of computational modeling to investigate knee joint biomechanics has increased exponentially over the last few decades. Developing computational models is a creative process where decisions have to be made, subject to the modelers' knowledge and previous experiences, resulting in the "art" of modeling. The long-term goal of the KneeHub project is to understand the influence of subjective decisions on the final outcomes and the reproducibility of computational knee joint models. In this paper, we report on the model development phase of this project, investigating model development decisions and deviations from initial modeling plans. Five teams developed computational knee joint models from the same dataset, and we compared each teams' initial uncalibrated models and their model development workflows. Variations in the software tools and modeling approaches were found, resulting in differences such as the representation of the anatomical knee joint structures in the model. The teams consistently defined the boundary conditions and used the same anatomical coordinate system convention. However, deviations in the anatomical landmarks used to define the coordinate systems were present, resulting in a large spread in the kinematic outputs of the uncalibrated models. The reported differences and similarities in model development and simulation presented here illustrate the importance of the "art" of modeling and how subjective decision-making can lead to variation in model outputs. All teams deviated from their initial modeling plans, indicating that model development is a flexible process and difficult to plan in advance, even for experienced teams.

A Method to Compare Heterogeneous Types of Bone and Cartilage Meshes.

Accurately capturing the bone and cartilage morphology and generating a mesh remains a critical step in the workflow of computational knee joint modeling. Currently, there is no standardized method to compare meshes of different element types and nodal densities, making comparisons across research teams a significant challenge. The aim of this paper is to describe a method to quantify differences in knee joint bone and cartilages meshes, independent of bone and cartilage mesh topology. Bone mesh-to-mesh distances, subchondral bone boundaries, and cartilage thicknesses from meshes of any type of mesh are obtained using a series of steps involving registration, resampling, and radial basis function fitting after which the comparisons are performed. Subchondral bone boundaries and cartilage thicknesses are calculated and visualized in a common frame of reference for comparison. The established method is applied to models developed by five modeling teams. Our approach to obtain bone mesh-to-mesh distances decreased the divergence seen in selecting a reference mesh (i.e., comparing mesh A-to-B versus mesh B-to-A). In general, the bone morphology was similar across teams. The cartilage thicknesses for all models were calculated and the mean absolute cartilage thickness difference was presented, the articulating areas had the best agreement across teams. The teams showed disagreement on the subchondral bone boundaries. The method presented in this paper allows for objective comparisons of bone and cartilage geometry that is agnostic to mesh type and nodal density.

Credible practice of modeling and simulation in healthcare: ten rules from a multidisciplinary perspective.

The complexities of modern biomedicine are rapidly increasing. Thus, modeling and simulation have become increasingly important as a strategy to understand and predict the trajectory of pathophysiology, disease genesis, and disease spread in support of clinical and policy decisions. In such cases, inappropriate or ill-placed trust in the model and simulation outcomes may result in negative outcomes, and hence illustrate the need to formalize the execution and communication of modeling and simulation practices. Although verification and validation have been generally accepted as significant components of a model's credibility, they cannot be assumed to equate to a holistic credible practice, which includes activities that can impact comprehension and in-depth examination inherent in the development and reuse of the models. For the past several years, the Committee on Credible Practice of Modeling and Simulation in Healthcare, an interdisciplinary group seeded from a U.S. interagency initiative, has worked to codify best practices. Here, we provide Ten Rules for credible practice of modeling and simulation in healthcare developed from a comparative analysis by the Committee's multidisciplinary membership, followed by a large stakeholder community survey. These rules establish a unified conceptual framework for modeling and simulation design, implementation, evaluation, dissemination and usage across the modeling and simulation life-cycle. While biomedical science and clinical care domains have somewhat different requirements and expectations for credible practice, our study converged on rules that would be useful across a broad swath of model types. In brief, the rules are: (1) Define context clearly. (2) Use contextually appropriate data. (3) Evaluate within context. (4) List limitations explicitly. (5) Use version control. (6) Document appropriately. (7) Disseminate broadly. (8) Get independent reviews. (9) Test competing implementations. (10) Conform to standards. Although some of these are common sense guidelines, we have found that many are often missed or misconstrued, even by seasoned practitioners. Computational models are already widely used in basic science to generate new biomedical knowledge. As they penetrate clinical care and healthcare policy, contributing to personalized and precision medicine, clinical safety will require established guidelines for the credible practice of modeling and simulation in healthcare.

Deciphering the "Art" in Modeling and Simulation of the Knee Joint: Overall Strategy.

Recent explorations of knee biomechanics have benefited from computational modeling, specifically leveraging advancements in finite element analysis and rigid body dynamics of joint and tissue mechanics. A large number of models have emerged with different levels of fidelity in anatomical and mechanical representation. Adapted modeling and simulation processes vary widely, based on justifiable choices in relation to anticipated use of the model. However, there are situations where modelers' decisions seem to be subjective, arbitrary, and difficult to rationalize. Regardless of the basis, these decisions form the "art" of modeling, which impact the conclusions of simulation-based studies on knee function. These decisions may also hinder the reproducibility of models and simulations, impeding their broader use in areas such as clinical decision making and personalized medicine. This document summarizes an ongoing project that aims to capture the modeling and simulation workflow in its entirety-operation procedures, deviations, models, by-products of modeling, simulation results, and comparative evaluations of case studies and applications. The ultimate goal of the project is to delineate the art of a cohort of knee modeling teams through a publicly accessible, transparent approach and begin to unravel the complex array of factors that may lead to a lack of reproducibility. This manuscript outlines our approach along with progress made so far. Potential implications on reproducibility, on science, engineering, and training of modeling and simulation, on modeling standards, and on regulatory affairs are also noted.

Perspectives on Sharing Models and Related Resources in Computational Biomechanics Research.

The role of computational modeling for biomechanics research and related clinical care will be increasingly prominent. The biomechanics community has been developing computational models routinely for exploration of the mechanics and mechanobiology of diverse biological structures. As a result, a large array of models, data, and discipline-specific simulation software has emerged to support endeavors in computational biomechanics. Sharing computational models and related data and simulation software has first become a utilitarian interest, and now, it is a necessity. Exchange of models, in support of knowledge exchange provided by scholarly publishing, has important implications. Specifically, model sharing can facilitate assessment of reproducibility in computational biomechanics and can provide an opportunity for repurposing and reuse, and a venue for medical training. The community's desire to investigate biological and biomechanical phenomena crossing multiple systems, scales, and physical domains, also motivates sharing of modeling resources as blending of models developed by domain experts will be a required step for comprehensive simulation studies as well as the enhancement of their rigor and reproducibility. The goal of this paper is to understand current perspectives in the biomechanics community for the sharing of computational models and related resources. Opinions on opportunities, challenges, and pathways to model sharing, particularly as part of the scholarly publishing workflow, were sought. A group of journal editors and a handful of investigators active in computational biomechanics were approached to collect short opinion pieces as a part of a larger effort of the IEEE EMBS Computational Biology and the Physiome Technical Committee to address model reproducibility through publications. A synthesis of these opinion pieces indicates that the community recognizes the necessity and usefulness of model sharing. There is a strong will to facilitate model sharing, and there are corresponding initiatives by the scientific journals. Outside the publishing enterprise, infrastructure to facilitate model sharing in biomechanics exists, and simulation software developers are interested in accommodating the community's needs for sharing of modeling resources. Encouragement for the use of standardized markups, concerns related to quality assurance, acknowledgement of increased burden, and importance of stewardship of resources are noted. In the short-term, it is advisable that the community builds upon recent strategies and experiments with new pathways for continued demonstration of model sharing, its promotion, and its utility. Nonetheless, the need for a long-term strategy to unify approaches in sharing computational models and related resources is acknowledged. Development of a sustainable platform supported by a culture of open model sharing will likely evolve through continued and inclusive discussions bringing all stakeholders at the table, e.g., by possibly establishing a consortium.

Introducing AEM-RADS: A novel reporting and data system for abdominal emergencies.

PURPOSE: The Reporting and Data System (RADS) has proven successful in various medical settings, but a standardized reporting system for abdominal emergencies is lacking. In this study, the Abdominal Emergency Reporting and Data System (AEM-RADS) for urgent findings on abdominal CT scans is introduced to address the need for consistency in emergency radiology. METHODS: In this prospective observational study, conducted over a six-month period, the urgency of abdominal CT scans was assessed using the proposed AEM-RADS scoring system. The committee developed a scale ranging from AEM-RADS 1 (normal) to AEM-RADS 5 (urgent disease). Interobserver agreement between two observers with different experience was evaluated, and robust AEM-RADS reference values were established by radiologists who were not observers. Statistical analysis used mean, standard deviations and Kendall's tau analysis for interobserver agreement. RESULTS: Among 2656 patients who underwent CT for abdominal emergencies, the AEM-RADS distribution was 17.50% AEM-RADS 1, 28.57% AEM-RADS 2, 7.22% AEM-RADS 3, 35.61% AEM-RADS 4, and 11.06% AEM-RADS 5. Interobserver agreement was high, especially for urgent and emergent cases (p < 0.0001). Notable discrepancies were observed in AEM-RADS categories 2C-D and 3B-C, emphasizing the influence of radiologists' experience on interpretation. However, the interobserver agreement for both AEM-RADS 2C-D and 3B-C were statistically significant (p < 0.001). CONCLUSIONS: AEM-RADS showed promising reliability, particularly in identifying urgent and emergent cases. Despite some inter-observer discrepancies, the system showed potential for standardized emergency workups. AEM-RADS could significantly enhance diagnostic accuracy in abdominal emergencies and provide a structured framework for shared decision-making between clinicians and radiologists.0.

Novel Machine Learning Identifies 5 Asthma Phenotypes Using Cluster Analysis of Real-World Data.

BACKGROUND: Asthma classification into different subphenotypes is important to guide personalized therapy and improve outcomes. OBJECTIVES: To further explore asthma heterogeneity through determination of multiple patient groups by using novel machine learning (ML) approaches and large-scale real-world data. METHODS: We used electronic health records of patients with asthma followed at the Cleveland Clinic between 2010 and 2021. We used k-prototype unsupervised ML to develop a clustering model where predictors were age, sex, race, body mass index, prebronchodilator and postbronchodilator spirometry measurements, and the usage of inhaled/systemic steroids. We applied elbow and silhouette plots to select the optimal number of clusters. These clusters were then evaluated through LightGBM's supervised ML approach on their cross-validated F1 score to support their distinctiveness. RESULTS: Data from 13,498 patients with asthma with available postbronchodilator spirometry measurements were extracted to identify 5 stable clusters. Cluster 1 included a young nonsevere asthma population with normal lung function and higher frequency of acute exacerbation (0.8 /patient-year). Cluster 2 had the highest body mass index (mean ± SD, 44.44 ± 7.83 kg/m2), and the highest proportion of females (77.5%) and Blacks (28.9%). Cluster 3 comprised patients with normal lung function. Cluster 4 included patients with lower percent of predicted FEV1 of 77.03 (12.79) and poor response to bronchodilators. Cluster 5 had the lowest percent of predicted FEV1 of 68.08 (15.02), the highest postbronchodilator reversibility, and the highest proportion of severe asthma (44.9%) and blood eosinophilia (>300 cells/µL) (34.8%). CONCLUSIONS: Using real-world data and unsupervised ML, we classified asthma into 5 clinically important subphenotypes where group-specific asthma treatment and management strategies can be designed and deployed.

Optimization of nonlinear hyperelastic coefficients for foot tissues using a magnetic resonance imaging deformation experiment.

Accurate prediction of plantar shear stress and internal stress in the soft tissue layers of the foot using finite element models would provide valuable insight into the mechanical etiology of neuropathic foot ulcers. Accurate prediction of the internal stress distribution using finite element models requires that realistic descriptions of the material properties of the soft tissues are incorporated into the model. Our investigation focused on the creation of a novel three-dimensional (3D) finite element model of the forefoot with multiple soft tissue layers (skin, fat pad, and muscle) and the development of an inverse finite element procedure that would allow for the optimization of the nonlinear elastic coefficients used to define the material properties of the skin muscle and fat pad tissue layers of the forefoot based on a Ogden hyperelastic constitutive model. Optimization was achieved by comparing deformations predicted by finite element models to those measured during an experiment in which magnetic resonance imaging (MRI) images were acquired while the plantar surface forefoot was compressed. The optimization procedure was performed for both a model incorporating all three soft tissue layers and one in which all soft tissue layers were modeled as a single layer. The results indicated that the inclusion of multiple tissue layers affected the deformation and stresses predicted by the model. Sensitivity analysis performed on the optimized coefficients indicated that small changes in the coefficient values (±10%) can have rather large impacts on the predicted nominal strain (differences up to 14%) in a given tissue layer.

Role of multi-layer tissue composition of musculoskeletal extremities for prediction of in vivo surface indentation response and layer deformations.

Emergent mechanics of musculoskeletal extremities (surface indentation stiffness and tissue deformation characteristics) depend on the underlying composition and mechanics of each soft tissue layer (i.e. skin, fat, and muscle). Limited experimental studies have been performed to explore the layer specific relationships that contribute to the surface indentation response. The goal of this study was to examine through statistical modeling how the soft tissue architecture contributed to the aggregate mechanical surface response across 8 different sites of the upper and lower extremities. A publicly available dataset was used to examine the relationship of soft tissue thickness (fat and muscle) to bulk tissue surface compliance. Models required only initial tissue layer thicknesses, making them usable in the future with only a static ultrasound image. Two physics inspired models (series of linear springs), which allowed reduced statistical representations (combined locations and location specific), were explored to determine the best predictability of surface compliance and later individual layer deformations. When considering the predictability of the experimental surface compliance, the physics inspired combined locations model showed an improvement over the location specific model (percent difference of 25.4 +/- 27.9% and 29.7 +/- 31.8% for the combined locations and location specific models, respectively). While the statistical models presented in this study show that tissue compliance relies on the individual layer thicknesses, it is clear that there are other variables that need to be accounted for to improve the model. In addition, the individual layer deformations of fat and muscle tissues can be predicted reasonably well with the physics inspired models, however additional parameters may improve the robustness of the model outcomes, specifically in regard to capturing subject specificity.

Open Knee(s): A Free and Open Source Library of Specimen-Specific Models and Related Digital Assets for Finite Element Analysis of the Knee Joint.

There is a growing interest in the use of virtual representations of the knee for musculoskeletal research and clinical decision making, and to generate digital evidence for design and regulation of implants. Accessibility to previously developed models and related digital assets can dramatically reduce barriers to entry to conduct simulation-based studies of the knee joint and therefore help accelerate scientific discovery and clinical innovations. Development of models for finite element analysis is a demanding process that is both time consuming and resource intensive. It necessitates expertise to transform raw data to reliable virtual representations. Modeling and simulation workflow has many processes such as image segmentation, surface geometry generation, mesh generation and finally, creation of a finite element representation with relevant loading and boundary conditions. The outcome of the workflow is not only the end-point knee model but also many other digital by-products. When all of these data, derivate assets, and tools are freely and openly accessible, researchers can bypass some or all the steps required to build models and focus on using them to address their research goals. With provenance to specimen-specific anatomical and mechanical data and traceability of digital assets throughout the whole lifecycle of the model, reproducibility and credibility of the modeling practice can be established. The objective of this study is to disseminate Open Knee(s), a cohort of eight knee models (and relevant digital assets) for finite element analysis, that are based on comprehensive specimen-specific imaging data. In addition, the models and by-products of modeling workflows are described along with model development strategies and tools. Passive flexion served as a test simulation case, demonstrating an end-user application. Potential roadmaps for reuse of Open Knee(s) are also discussed.

A Call to Action for Musculoskeletal Research Funding: The Growing Economic and Disease Burden of Musculoskeletal Conditions in the United States Is Not Reflected in Musculoskeletal Research Funding.

ABSTRACT: As a result of an aging population, musculoskeletal disease is a growing source of health and economic burden in the United States. In 2019, musculoskeletal conditions affected approximately 127.4 million people (more than a third of the U.S. population); they were the top driver of health-care spending in 2016, with an estimated direct annual cost of $380.9 billion. While musculoskeletal conditions represent a substantial and growing burden in terms of prevalence, disability, and health-care costs, National Institutes of Health (NIH) research funding has remained disproportionately allocated to other disease conditions. Therefore, our purpose was to provide an assessment of the current burden of musculoskeletal disease in terms of prevalence, disability, and health-care costs, and compare the changing burden of disease to trends in NIH funding.

Pros and cons of rib unfolding software: a reliability and reproducibility study on trauma patients.

BACKGROUND: Examination of all 24 ribs on axial computed tomography (CT) slices might become a leeway and rib fractures (RF) may easily overlook in daily practice. Rib unfolding (RU), a computer-assisted software, that promises rapid assessment of the ribs in a two-dimensional plan, was developed to facilitate rib evaluation. We aimed to evaluate the reliability and reproducibility of RU software for RF detection on CT and to determine the accelerating effect to determine any drawback of RU application. METHODS: Fifty-one patients with thoracic trauma formed the sample to be assessed by the observers. The characterization and distribution of RFs on CT images in this sample were recorded independently by the non-observers. Regarding the presence or ab-sence of RF, CT images were assessed blindedly by two radiologists with 5 years (observer-A) and 18 years (observer-B) of experience in thoracic radiology. Each observer assessed the axial CT and RU images on different days under non-observer supervision. RESULTS: A total of 113 RFs were detected in 22 patients. The mean evaluation time for the axial CT images was 146.64 s for ob-server-A and 119.29 s for observer-B. The mean evaluation time for RU images was 66.44 s for observer-A and 32.66 s for observer-B. A statistically significant decrease was observed between the evaluation periods of observer-A and observer-B with RU software compared to the axial CT image assessment (p<0.001). The inter-observer κ value was 0.638, while the intra-observer results showed moderate (κ: 0.441) and good (κ: 0.752) reproducibility comparing the RU and axial CT assessments. Observer-A detected 47.05% non-displaced fractures, 48.93% minimally displaced (≤2 mm) fractures, and 38.77% displaced fractures on RU images (p=0.009). Ob-server-B detected 23.52% non-displaced fractures, 57.44% minimally displaced (≤2 mm) fractures, and 48.97% displaced fractures on RU images (p=0.045). CONCLUSION: RU software accelerates fracture evaluation, while it has drawbacks including low sensitivity in fracture detection, false negativity, and underestimation of displacement.

Long-term results of liver thermal ablation in patients with hepatocellular carcinoma and colorectal cancer liver metastasis regarding spatial features and tumor-specific variables

PURPOSE: Colorectal cancer liver metastasis (CRLM) and hepatocellular carcinoma (HCC) are widely treated using microwave and radiofrequency ablation. Local tumor progression (LTP) may develop depending on the shortest vascular distance and large lesion diameter. This study aims to explore the effect of these spatial features and to investigate the correlation between tumor-specific variables and LTP. METHODS: This is a retrospective study covering the period between January 2007 and January 2019. One hundred twenty-five patients (CRLM: HCC: 64:61) with 262 lesions (CRLM: HCC: 142:120) were enrolled. The correlation between LTP and the variables was analyzed using the chi-square test, Fischer's exact test, or the Fisher-Freeman-Halton test where applicable. The local progression-free survival (Loc-PFS) was analyzed using the Kaplan-Meier method. Univariable and multivariable Cox regression analyses were performed to identify prognostic factors. RESULTS: Significant correlations were observed for LTP in both CRLM and HCC at a lesion diameter of 30-50 mm (P = 0.019 and P < 0.001, respectively) and SVD of ≤3 mm (P < 0.001 for both). No correlation was found between the ablation type and LTP (CRLM: P = 0.141; HCC: P = 0.771). There was no relationship between residue and the ablation type, but a strong correlation with tumor size was observed (P = 0.127 and P < 0.001, respectively). In CRLM, LTP was associated with mutant K-ras and concomitant lung metastasis (P < 0.001 and P = 0.003, respectively). In HCC, a similar correlation was found for Child-Pugh B, serum alpha-fetoprotein (AFP) level of >10 ng/mL, predisposing factors, and moderate histopathological differentiation (P < 0.001, P = 0.008, P = 0.027, and P <0.001, respectively). In CRLM, SVD of ≤3 mm proved to be the variable with the greatest negative effect on Loc-PFS (P = 0.007), followed by concomitant lung metastasis (P = 0.027). In HCC, a serum AFP level of >10 ng/mL proved to be the variable with the greatest negative effect on Loc-PFS (P = 0.045). CONCLUSION: In addition to the lesions' spatial features, tumor-specific variables may also have an impact on LTP.

Sarcopenia and anthracycline cardiotoxicity in patients with cancer.

BACKGROUND: Several studies have suggested that sarcopenia is associated with an increased treatment toxicity in patients with cancer. The aim of this study is to evaluate the relationship between sarcopenia and anthracycline-related cardiotoxicity. METHODS: Patients who received anthracycline-based chemotherapy between 2014 and 2018 and had baseline abdominal CT and baseline and follow-up echocardiography after anthracycline treatment were included. European Society of Cardiology ejection fraction criteria and American Society of Echocardiography diastolic dysfunction criteria were used for definition of cardiotoxicity. Sarcopenia was defined on the basis of skeletal muscle index (SMI) and psoas muscle index (PMI) calculated on CT images at L3 and L4 vertebra levels. RESULTS: A total of 166 patients (75 men and 91 women) were included. Sarcopenia was determined in 33 patients (19.9%) according to L3-SMI, in 17 patients (10.2%) according to L4-SMI and in 45 patients (27.1%) according to PMI. 27 patients (16.3%) developed cardiotoxicity. PMI and L3-SMI were significantly associated with an increased risk of cardiotoxicity (L3-SMI: HR=3.27, 95% CI 1.32 to 8.11, p=0.01; PMI: HR=3.71, 95% CI 1.58 to 8.73, p=0.003). CONCLUSIONS: This is the first study demonstrating a significant association between CT-diagnosed sarcopenia and anthracycline-related cardiotoxicity. Routine CT scans performed for cancer staging may help clinicians identify high-risk patients in whom closer follow-up or cardioprotective measures should be considered.