The imminent performance of multimodal and heterogeneous modalities to forecast the advance of Alzheimer's disease (AD) precisely is one of the key problems. Current models are usually not interpretable, time-consistent, and multimodal, making them less useful in clinical forecasting.
Objective
The objective of the study is to develop a hybrid generative approach to simulate the individualized AD progression process, which can generate future anatomical and clinical states, model latent over-time dynamics, and measure the uncertainty.
Methods
The proposed study suggests using a multimodal paradigm that enables a combination of Conditional Latent Diffusion Models (cLDM) and Neural Ordinary Differential Equations (ODEs). The model permits the generation of plausible future MRI, cognitive scoring, and biomarker trajectories for a patient at baseline. The ADNI dataset was evaluated with structural similarity (SSIM), clinical prediction error, and classification accuracy.
Key Findings
The model provided an SSIM equal to 0.86 on synthesizing future MRI, and the MAE of MMSE prediction was equal to 1.5. It exceeded baselines in all the imaging, cognitive, and biomarker settings. The conversion of AD resulted in an accuracy of the classification of 88% with stable multimodal generalization at calibrated output of probability.
Conclusion
The proposed model offers a feasible and explainable approach to the forecast of an AD trajectory, allowing realistic simulations of a digital twin and projecting its progress within a multi-year perspective. It also supports early detection, custom intervention, and uncertainty-conscious clinical decision-making.
{"title":"cLDM-ODE: A Multimodal Generative Framework for Uncertainty-Aware Forecasting of Alzheimer's Disease Progression","authors":"Rishabh Sharma , Vinay Kukreja , Shanmugasundaram Hariharan , Shih-Yu Chen","doi":"10.1016/j.irbm.2025.100926","DOIUrl":"10.1016/j.irbm.2025.100926","url":null,"abstract":"<div><h3>Context</h3><div>The imminent performance of multimodal and heterogeneous modalities to forecast the advance of Alzheimer's disease (AD) precisely is one of the key problems. Current models are usually not interpretable, time-consistent, and multimodal, making them less useful in clinical forecasting.</div></div><div><h3>Objective</h3><div>The objective of the study is to develop a hybrid generative approach to simulate the individualized AD progression process, which can generate future anatomical and clinical states, model latent over-time dynamics, and measure the uncertainty.</div></div><div><h3>Methods</h3><div>The proposed study suggests using a multimodal paradigm that enables a combination of Conditional Latent Diffusion Models (cLDM) and Neural Ordinary Differential Equations (ODEs). The model permits the generation of plausible future MRI, cognitive scoring, and biomarker trajectories for a patient at baseline. The ADNI dataset was evaluated with structural similarity (SSIM), clinical prediction error, and classification accuracy.</div></div><div><h3>Key Findings</h3><div>The model provided an SSIM equal to 0.86 on synthesizing future MRI, and the MAE of MMSE prediction was equal to 1.5. It exceeded baselines in all the imaging, cognitive, and biomarker settings. The conversion of AD resulted in an accuracy of the classification of 88% with stable multimodal generalization at calibrated output of probability.</div></div><div><h3>Conclusion</h3><div>The proposed model offers a feasible and explainable approach to the forecast of an AD trajectory, allowing realistic simulations of a digital twin and projecting its progress within a multi-year perspective. It also supports early detection, custom intervention, and uncertainty-conscious clinical decision-making.</div></div>","PeriodicalId":14605,"journal":{"name":"Irbm","volume":"47 1","pages":"Article 100926"},"PeriodicalIF":4.2,"publicationDate":"2025-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145748791","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-13DOI: 10.1016/j.irbm.2025.100922
Eng-Keat Kwa , Soon-Keng Cheong , Poh-Foong Lee
Introduction
Visual impairment can significantly affect psychological and physiological well-being, potentially due to autonomic imbalance, and while deep breathing has been shown to improve autonomic modulation as measured by heart rate variability (HRV), its impact on individuals with visual impairment remains underexplored, prompting this study to investigate its immediate and long-term effects on HRV in this population compared to normally sighted individuals.
Materials and methods
A total of 98 participants with visually impaired (VI) individuals (n = 49) and normally sighted (NS) individuals (n = 49) were recruited. The HRV, including standard deviation of the normal-to-normal intervals (SDNN), root mean square of successive differences, normalized low frequency (nLF), normalized high frequency (nHF), and low frequency to high-frequency ratio (LF/HF), was measured at baseline (BL), immediate post intervention (IPI) and post-intervention (POST) after 2 weeks daily audio-guided deep breathing.
Results
Kruskal-Wallis tests revealed significant phase effects for nLF (p = 0.002), nHF (p = 0.002), and LF/HF (p = 0.024) in the VI group, with post hoc analyses indicating significantly higher nLF (p = 0.004), LF/HF (p = 0.007), and lower nHF (p = 0.004) at IPI compared to BL. While the NS group showed no significant changes across phases. Between-group comparisons revealed significantly higher nLF (p = 0.034), LF/HF (p = 0.007), and lower nHF (p = 0.034) at IPI in the VI group compared to the NS group.
Conclusion
Deep breathing led to immediate increases in nLF and LF/HF, and a decrease in nHF, in individuals with visual impairment compared to sighted individuals, suggesting baroreflex resonance at 0.1 Hz. However, the absence of significant SDNN changes limits conclusions about parasympathetic modulation. Further research is needed to assess the potential long-term benefits.
{"title":"Exploring Autonomic Modulation Through Deep Breathing: Immediate and Long-Term Effects on Heart Rate Variability in Visually Impaired Individuals","authors":"Eng-Keat Kwa , Soon-Keng Cheong , Poh-Foong Lee","doi":"10.1016/j.irbm.2025.100922","DOIUrl":"10.1016/j.irbm.2025.100922","url":null,"abstract":"<div><h3>Introduction</h3><div>Visual impairment can significantly affect psychological and physiological well-being, potentially due to autonomic imbalance, and while deep breathing has been shown to improve autonomic modulation as measured by heart rate variability (HRV), its impact on individuals with visual impairment remains underexplored, prompting this study to investigate its immediate and long-term effects on HRV in this population compared to normally sighted individuals.</div></div><div><h3>Materials and methods</h3><div>A total of 98 participants with visually impaired (VI) individuals (n = 49) and normally sighted (NS) individuals (n = 49) were recruited. The HRV, including standard deviation of the normal-to-normal intervals (SDNN), root mean square of successive differences, normalized low frequency (nLF), normalized high frequency (nHF), and low frequency to high-frequency ratio (LF/HF), was measured at baseline (BL), immediate post intervention (IPI) and post-intervention (POST) after 2 weeks daily audio-guided deep breathing.</div></div><div><h3>Results</h3><div>Kruskal-Wallis tests revealed significant phase effects for nLF (p = 0.002), nHF (p = 0.002), and LF/HF (p = 0.024) in the VI group, with post hoc analyses indicating significantly higher nLF (p = 0.004), LF/HF (p = 0.007), and lower nHF (p = 0.004) at IPI compared to BL. While the NS group showed no significant changes across phases. Between-group comparisons revealed significantly higher nLF (p = 0.034), LF/HF (p = 0.007), and lower nHF (p = 0.034) at IPI in the VI group compared to the NS group.</div></div><div><h3>Conclusion</h3><div>Deep breathing led to immediate increases in nLF and LF/HF, and a decrease in nHF, in individuals with visual impairment compared to sighted individuals, suggesting baroreflex resonance at 0.1 Hz. However, the absence of significant SDNN changes limits conclusions about parasympathetic modulation. Further research is needed to assess the potential long-term benefits.</div></div>","PeriodicalId":14605,"journal":{"name":"Irbm","volume":"47 1","pages":"Article 100922"},"PeriodicalIF":4.2,"publicationDate":"2025-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145584574","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-07DOI: 10.1016/j.irbm.2025.100921
Veli Avci , Mehmet Tahir Huyut , Andrei Velichko , Maksim Belyaev
Introduction
Acute appendicitis is the commonest cause of surgical abdominal pain, yet diagnosis in children remains challenging; delays increase the risk of perforation, peritonitis and sepsis. We sought to develop a rapid, inexpensive and interpretable clinical-decision support system (CDSS) that leverages routine blood tests (RBT) to assist early paediatric triage.
Materials and Methods
In this retrospective single-centre study (January 2020–December 2024) we analysed 275 emergency-department encounters for abdominal pain (75 histology-confirmed appendicitis, 200 controls). The six-stage pipeline comprised (1) cohort selection; (2) exploratory logistic-regression screening of RBT variables; (3) training of Random Forest, Gradient Boosting and LightGBM ensembles (with/without SMOTE) under 10 × 10 stratified cross-validation; (4) SHAP-based feature interpretation; (5) exhaustive generation of every two- and three-parameter arithmetic biomarker from seven RBT features; and (6) derivation of probability-threshold curves and a three-zone rule tree for the top biomarker. Performance was reported with accuracy (ACC), Matthews correlation coefficient (MCC), AUC-ROC, sensitivity, specificity, F1-Score PPV and NPV.
Results
Logistic regression and SHAP confirmed CRP, WBC and neutrophil count as strong positive predictors, whereas MPV and PDW were protective; PLT remained non-informative. All three ensemble classifiers surpassed 97% accuracy, 98% AUC-ROC and 0.93 MCC, with no gain from SMOTE. An extensive formula search, the best two-parameter marker was Neutrophil ÷ PDW (MCC = 0.73, specificity 95%). Its ensemble curve crosses P = 0.5 five times; practical cut-offs of < 0.633 (strongly indicate healthy) and > 0.794 (strongly indicate appendicitis) retain high NPV (∼91%) and PPV (∼86%). Among triple formulas that do not rely on PLT, the leading biomarker was CRP+WBC+Neutrophil (MCC = 0.85, PPV 92%, NPV 95%). The ensemble curve intersects at P = 0.5 at three points; values >27 strongly predict appendicitis, <23 indicates a healthy state, and values 23–27 leave a small uncertain band. A rule-based CDSS built on these two biomarkers correctly classified all controls (specificity 100%), sensitivity 95%, achieved 91% overall accuracy, and offers interpretable, electronic health records (EHRs)-ready cut-offs for paediatric appendicitis triage.
Conclusion
Routine haematology-biochemistry data, interpreted through ensemble learning and engineered biomarkers, can deliver fast, transparent and highly accurate support for paediatric appendicitis triage. Given its zero false-positive rate, the proposed CDSS is best suited to in-hospital monitoring, where minimising false negatives is critical. Prospective multi-centre validation is warranted.
{"title":"A Novel Biomarker-Based Decision Support System for Pediatric Appendicitis Diagnosis: A Comparative Study of Ensemble Models Algorithms","authors":"Veli Avci , Mehmet Tahir Huyut , Andrei Velichko , Maksim Belyaev","doi":"10.1016/j.irbm.2025.100921","DOIUrl":"10.1016/j.irbm.2025.100921","url":null,"abstract":"<div><h3>Introduction</h3><div>Acute appendicitis is the commonest cause of surgical abdominal pain, yet diagnosis in children remains challenging; delays increase the risk of perforation, peritonitis and sepsis. We sought to develop a rapid, inexpensive and interpretable clinical-decision support system (CDSS) that leverages routine blood tests (RBT) to assist early paediatric triage.</div></div><div><h3>Materials and Methods</h3><div>In this retrospective single-centre study (January 2020–December 2024) we analysed 275 emergency-department encounters for abdominal pain (75 histology-confirmed appendicitis, 200 controls). The six-stage pipeline comprised (1) cohort selection; (2) exploratory logistic-regression screening of RBT variables; (3) training of Random Forest, Gradient Boosting and LightGBM ensembles (with/without SMOTE) under 10 × 10 stratified cross-validation; (4) SHAP-based feature interpretation; (5) exhaustive generation of every two- and three-parameter arithmetic biomarker from seven RBT features; and (6) derivation of probability-threshold curves and a three-zone rule tree for the top biomarker. Performance was reported with accuracy (ACC), Matthews correlation coefficient (MCC), AUC-ROC, sensitivity, specificity, F1-Score PPV and NPV.</div></div><div><h3>Results</h3><div>Logistic regression and SHAP confirmed CRP, WBC and neutrophil count as strong positive predictors, whereas MPV and PDW were protective; PLT remained non-informative. All three ensemble classifiers surpassed 97% accuracy, 98% AUC-ROC and 0.93 MCC, with no gain from SMOTE. An extensive formula search, the best two-parameter marker was Neutrophil ÷ PDW (MCC = 0.73, specificity 95%). Its ensemble curve crosses P = 0.5 five times; practical cut-offs of < 0.633 (strongly indicate healthy) and > 0.794 (strongly indicate appendicitis) retain high NPV (∼91%) and PPV (∼86%). Among triple formulas that do not rely on PLT, the leading biomarker was CRP+WBC+Neutrophil (MCC = 0.85, PPV 92%, NPV 95%). The ensemble curve intersects at P = 0.5 at three points; values >27 strongly predict appendicitis, <23 indicates a healthy state, and values 23–27 leave a small uncertain band. A rule-based CDSS built on these two biomarkers correctly classified all controls (specificity 100%), sensitivity 95%, achieved 91% overall accuracy, and offers interpretable, electronic health records (EHRs)-ready cut-offs for paediatric appendicitis triage.</div></div><div><h3>Conclusion</h3><div>Routine haematology-biochemistry data, interpreted through ensemble learning and engineered biomarkers, can deliver fast, transparent and highly accurate support for paediatric appendicitis triage. Given its zero false-positive rate, the proposed CDSS is best suited to in-hospital monitoring, where minimising false negatives is critical. Prospective multi-centre validation is warranted.</div></div>","PeriodicalId":14605,"journal":{"name":"Irbm","volume":"47 1","pages":"Article 100921"},"PeriodicalIF":4.2,"publicationDate":"2025-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145622682","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-06DOI: 10.1016/j.irbm.2025.100919
Alireza Y. Bavil , Emmanuel Eghan-Acquah , Rod Barrett , Laura E. Diamond , Liam Johnson , Stefanie Feih , David J. Saxby , Christopher P. Carty
Background
Proximal femoral osteotomy (PFO) is a surgical correction of proximal femoral deformity. Surgical choices, notably the postoperative neck-shaft angle (NSA), can affect postoperative stability and healing. While NSA's role in femoral mechanics is recognized, its impact on bone healing remains unclear.
Objective
To determine the influence of postoperative NSA on bone healing; to investigate the interaction of healing-related parameters and mechanical safety.
Methods
Medical imaging, gait data, and surgical information from nine patients (10 femurs) were used to build personalized finite element models of PFO-implanted femurs. Three postoperative neck-shaft angles (128°, 135°, 143°) were tested. During simulated walking, interfragmentary movement, deviatoric strain, mechanical stimulus, bone-implant micromotion, and peak von Mises stress (PVMS) were evaluated. Healing mode (primary vs. secondary) was classified based on interfragmentary movement thresholds.
Results
Mono-modal healing (primary in four and secondary in three) was observed in seven femurs, independent of postoperative NSA. In three femurs, a transition from primary to secondary healing occurred with increased NSAs. The PVMS for the implant and the bone exceeded critical values across all NSAs for two femurs, and micromotion was deemed critical only at 128° in two femurs.
Conclusion
This study highlights the value of integrating patient-specific modelling into preoperative planning. Bone healing modes were sensitive to postoperative NSA in 30% of cases, while 70% exhibited a single healing mode across the tested angles. Overall, findings suggest the need to simultaneously consider the complex interaction between NSA and subject-specific factors on mechanical safety and healing outcomes following PFO.
{"title":"Selected Postoperative Neck-Shaft Angle in Proximal Femoral Osteotomy Can Affect the Bone Healing: A Finite Element Study","authors":"Alireza Y. Bavil , Emmanuel Eghan-Acquah , Rod Barrett , Laura E. Diamond , Liam Johnson , Stefanie Feih , David J. Saxby , Christopher P. Carty","doi":"10.1016/j.irbm.2025.100919","DOIUrl":"10.1016/j.irbm.2025.100919","url":null,"abstract":"<div><h3>Background</h3><div>Proximal femoral osteotomy (PFO) is a surgical correction of proximal femoral deformity. Surgical choices, notably the postoperative neck-shaft angle (NSA), can affect postoperative stability and healing. While NSA's role in femoral mechanics is recognized, its impact on bone healing remains unclear.</div></div><div><h3>Objective</h3><div>To determine the influence of postoperative NSA on bone healing; to investigate the interaction of healing-related parameters and mechanical safety.</div></div><div><h3>Methods</h3><div>Medical imaging, gait data, and surgical information from nine patients (10 femurs) were used to build personalized finite element models of PFO-implanted femurs. Three postoperative neck-shaft angles (128°, 135°, 143°) were tested. During simulated walking, interfragmentary movement, deviatoric strain, mechanical stimulus, bone-implant micromotion, and peak von Mises stress (PVMS) were evaluated. Healing mode (primary vs. secondary) was classified based on interfragmentary movement thresholds.</div></div><div><h3>Results</h3><div>Mono-modal healing (primary in four and secondary in three) was observed in seven femurs, independent of postoperative NSA. In three femurs, a transition from primary to secondary healing occurred with increased NSAs. The PVMS for the implant and the bone exceeded critical values across all NSAs for two femurs, and micromotion was deemed critical only at 128° in two femurs.</div></div><div><h3>Conclusion</h3><div>This study highlights the value of integrating patient-specific modelling into preoperative planning. Bone healing modes were sensitive to postoperative NSA in 30% of cases, while 70% exhibited a single healing mode across the tested angles. Overall, findings suggest the need to simultaneously consider the complex interaction between NSA and subject-specific factors on mechanical safety and healing outcomes following PFO.</div></div>","PeriodicalId":14605,"journal":{"name":"Irbm","volume":"47 1","pages":"Article 100919"},"PeriodicalIF":4.2,"publicationDate":"2025-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145622683","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-31DOI: 10.1016/j.irbm.2025.100920
Pierre Rumeau , Marc Dupui
User Centered Design (UCD) is widely used in computer science and service provision, not so in public health administration. As a regulatory body (e.santé Occitanie) we applied UCD to design, deploy and assess a new medical service (ambulatory ECG at the local medical practice) at the request of a local general practitioner (GP). Method. We used semi-directed interviews starting with the GP to define the user groups profiles, as-is scenario and personae. We organized a focus group with the local stakeholders and representatives of Social Security, Regional Health Agency and e.santé Occitanie to refine the expression of needs. We used a SWOT to categorize the internal and external factors impacting the service. We designed a first specification prototype and a preliminary assessment of additional costs from the point of view of the Social Security. When the service started we arranged an 8-week prospective survey to verify the medical indications adhered to best practices. We ran an observational costs analysis on the first full year of operation. Results. As the study started in 2018 we had to cope with COVID 19 induced delays and changes. End of 2021 we could observe the start of the operation of the optimized version of the service with 4 steps instead of 9 in the as-is version. The 8-week medical indication survey showed full compliance with best practices. In 2022, first full year of operation, 39 patients had an AECG, less than expected, probably due to a waiting list effect. The additional costs analysis gave a benefit for Social Security of 12,397.05 € at 95% of expectations. After absorption of investment costs, expected benefit is 16,479.45 € at 98%. Conclusion. As a regulatory body, we successfully implemented the full UCD cycle on a bottom-up medical service improvement proposal. The service is still operating and has been spontaneously adopted elsewhere. UCD applied to selected local proposals could unveil a wealth of quality of care improvement solutions while keeping the costs down.
{"title":"User Centered Design May Apply to Public Health Issues: A Case Study on Arrhythmia Detection Service in Rural General Practice","authors":"Pierre Rumeau , Marc Dupui","doi":"10.1016/j.irbm.2025.100920","DOIUrl":"10.1016/j.irbm.2025.100920","url":null,"abstract":"<div><div>User Centered Design (UCD) is widely used in computer science and service provision, not so in public health administration. As a regulatory body (e.santé Occitanie) we applied UCD to design, deploy and assess a new medical service (ambulatory ECG at the local medical practice) at the request of a local general practitioner (<em>GP</em>). Method. We used semi-directed interviews starting with the GP to define the user groups profiles, as-is scenario and personae. We organized a focus group with the local stakeholders and representatives of Social Security, Regional Health Agency and e.santé Occitanie to refine the expression of needs. We used a SWOT to categorize the internal and external factors impacting the service. We designed a first specification prototype and a preliminary assessment of additional costs from the point of view of the Social Security. When the service started we arranged an 8-week prospective survey to verify the medical indications adhered to best practices. We ran an observational costs analysis on the first full year of operation. Results. As the study started in 2018 we had to cope with COVID 19 induced delays and changes. End of 2021 we could observe the start of the operation of the optimized version of the service with 4 steps instead of 9 in the as-is version. The 8-week medical indication survey showed full compliance with best practices. In 2022, first full year of operation, 39 patients had an AECG, less than expected, probably due to a waiting list effect. The additional costs analysis gave a benefit for Social Security of 12,397.05 € at 95% of expectations. After absorption of investment costs, expected benefit is 16,479.45 € at 98%. Conclusion. As a regulatory body, we successfully implemented the full UCD cycle on a bottom-up medical service improvement proposal. The service is still operating and has been spontaneously adopted elsewhere. UCD applied to selected local proposals could unveil a wealth of quality of care improvement solutions while keeping the costs down.</div></div>","PeriodicalId":14605,"journal":{"name":"Irbm","volume":"46 6","pages":"Article 100920"},"PeriodicalIF":4.2,"publicationDate":"2025-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145462854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-29DOI: 10.1016/j.irbm.2025.100918
Kalthoum Belghith, Ali Aghaei, Wael Maktouf, Mustapha Zidi
This study aims to evaluate stress distributions in the medial gastrocnemius muscle (GM) of patients with spastic myopathy after stroke. Shear wave elastography was employed to measure the shear modulus in three specific regions (upper, middle, and lower) of the muscle in six participants (three healthy and three post-stroke). Shear modulus measurements served as inputs for a finite element model to estimate stress distributions during uniform muscle stretching. The skeletal muscle was modeled as a hyperelastic, incompressible, and inhomogeneous material. The results showed that the stress distribution tends to increase in the post-stroke group, particularly in the middle (+60%) and lower regions (+13%). These results demonstrate the feasibility of estimating stress distributions using SWE data in post-stroke conditions, highlighting potential for further optimization of both experimental protocols and numerical models. These advancements could ultimately provide valuable insights into the clinical challenges associated with understanding spastic myopathy pathologies.
{"title":"Assessment of Stress Distributions in a Skeletal Muscle Affected by Post-Stroke Spastic Myopathy","authors":"Kalthoum Belghith, Ali Aghaei, Wael Maktouf, Mustapha Zidi","doi":"10.1016/j.irbm.2025.100918","DOIUrl":"10.1016/j.irbm.2025.100918","url":null,"abstract":"<div><div>This study aims to evaluate stress distributions in the medial gastrocnemius muscle (GM) of patients with spastic myopathy after stroke. Shear wave elastography was employed to measure the shear modulus in three specific regions (upper, middle, and lower) of the muscle in six participants (three healthy and three post-stroke). Shear modulus measurements served as inputs for a finite element model to estimate stress distributions during uniform muscle stretching. The skeletal muscle was modeled as a hyperelastic, incompressible, and inhomogeneous material. The results showed that the stress distribution tends to increase in the post-stroke group, particularly in the middle (+60%) and lower regions (+13%). These results demonstrate the feasibility of estimating stress distributions using SWE data in post-stroke conditions, highlighting potential for further optimization of both experimental protocols and numerical models. These advancements could ultimately provide valuable insights into the clinical challenges associated with understanding spastic myopathy pathologies.</div></div>","PeriodicalId":14605,"journal":{"name":"Irbm","volume":"46 6","pages":"Article 100918"},"PeriodicalIF":4.2,"publicationDate":"2025-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145462855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-03DOI: 10.1016/j.irbm.2025.100915
Esma Nur Kolbasi, Lotte Janssens, Joke Spildooren, Pieter Meyns
Background & Aim: As falls are common during gait in older adults, investigating the factors contributing to stable gait has gained growing interest. In this context, the contribution of visual, somatosensory, and vestibular systems (i.e., sensory integration) to gait has been studied for years, albeit primarily as individual systems. Although an earlier attempt was made to develop a test to comprehensively assess the sensory integration during gait, this effort encountered certain limitations that impacted its overall effectiveness. Thus, this study aims to develop a new test to evaluate sensory integration during gait, called the “Sensory Integration in Walking (SensIWalk) Test” and assess its validity and reliability in both young and older adults.
Methods: This study is planned as an observational study. Younger (n=24, 18-35 years old) and older adults (n=24, ≥65 years old) will be invited to participate, and all measurements will be performed at the Computer Assisted Rehabilitation Environment (CAREN, Motek Medical BV, Amsterdam, The Netherlands). SensIWalk, adapted from the framework of the Clinical Test of Sensory Interaction and Balance (CTSIB) with the same six conditions, will be modified to accommodate locomotion. The conditions of SensIWalk will be as follows: 1) Walking at preferred speed on a firm surface (i.e., on the treadmill) with eyes open, 2) Walking at preferred speed on a firm surface in the dark (1.3 lux), 3) Walking at preferred speed on a firm surface with sways of the virtual reality (VR) environment (i.e., visual conflict), 4) Walking at preferred speed with foam insoles (2 cm thick) with eyes open, 5) Walking at preferred speed with foam insoles in the dark, 6) Walking at preferred speed with foam insoles with sways of the VR environment.
Discussion: This study will allow delving into the underlying sensory mechanisms explaining suboptimal balance during walking by assessing the effects of sensory strategies on movement patterns. This may provide a deeper insight into the underlying mechanisms of falls in older adults, which could foster novel training or rehabilitation paradigms to decrease the risk of falls in older adults.
背景和目的：由于跌倒在老年人步态中很常见，研究影响步态稳定的因素已经引起了越来越多的兴趣。在这种背景下，视觉、体感和前庭系统（即感觉整合）对步态的贡献已经研究了多年，尽管主要是作为单个系统进行研究。虽然早期曾尝试开发一种测试来全面评估步态过程中的感觉整合，但这种努力遇到了某些限制，影响了其整体有效性。因此，本研究旨在开发一种新的测试来评估步态过程中的感觉整合，称为“行走中的感觉整合（SensIWalk）测试”，并评估其在年轻人和老年人中的效度和信度。方法：本研究计划为观察性研究。将邀请年轻人（n=24岁，18-35岁）和老年人（n=24岁，≥65岁）参加，所有测量将在计算机辅助康复环境（CAREN, Motek Medical BV，阿姆斯特丹，荷兰）进行。SensIWalk是根据感觉相互作用和平衡临床测试（CTSIB）的框架改编的，具有相同的六个条件，将进行修改以适应运动。SensIWalk的条件如下：1)睁着眼睛在坚固表面（即跑步机上）以首选速度行走，2)在黑暗中以首选速度行走（1.3 lux）， 3)在虚拟现实（VR）环境中以首选速度行走（即视觉冲突），4)睁着眼睛用泡沫鞋垫（2厘米厚）以首选速度行走，5)在黑暗中用泡沫鞋垫以首选速度行走。6)用泡沫鞋垫和VR环境的摇摆，以喜欢的速度行走。讨论：本研究将通过评估感觉策略对运动模式的影响，深入研究行走过程中解释次优平衡的潜在感觉机制。这可能为老年人跌倒的潜在机制提供更深入的见解，从而可以促进新的训练或康复范例，以降低老年人跌倒的风险。
{"title":"Development of a Sensory Integration Test for Locomotion: A Study Protocol","authors":"Esma Nur Kolbasi, Lotte Janssens, Joke Spildooren, Pieter Meyns","doi":"10.1016/j.irbm.2025.100915","DOIUrl":"10.1016/j.irbm.2025.100915","url":null,"abstract":"<div><div><strong>Background & Aim:</strong> As falls are common during gait in older adults, investigating the factors contributing to stable gait has gained growing interest. In this context, the contribution of visual, somatosensory, and vestibular systems (i.e., sensory integration) to gait has been studied for years, albeit primarily as individual systems. Although an earlier attempt was made to develop a test to comprehensively assess the sensory integration during gait, this effort encountered certain limitations that impacted its overall effectiveness. Thus, this study aims to develop a new test to evaluate sensory integration during gait, called the “Sensory Integration in Walking (SensIWalk) Test” and assess its validity and reliability in both young and older adults.</div><div><strong>Methods:</strong> This study is planned as an observational study. Younger (n=24, 18-35 years old) and older adults (n=24, ≥65 years old) will be invited to participate, and all measurements will be performed at the Computer Assisted Rehabilitation Environment (CAREN, Motek Medical BV, Amsterdam, The Netherlands). SensIWalk, adapted from the framework of the Clinical Test of Sensory Interaction and Balance (CTSIB) with the same six conditions, will be modified to accommodate locomotion. The conditions of SensIWalk will be as follows: 1) Walking at preferred speed on a firm surface (i.e., on the treadmill) with eyes open, 2) Walking at preferred speed on a firm surface in the dark (1.3 lux), 3) Walking at preferred speed on a firm surface with sways of the virtual reality (VR) environment (i.e., visual conflict), 4) Walking at preferred speed with foam insoles (2 cm thick) with eyes open, 5) Walking at preferred speed with foam insoles in the dark, 6) Walking at preferred speed with foam insoles with sways of the VR environment.</div><div><strong>Discussion:</strong> This study will allow delving into the underlying sensory mechanisms explaining suboptimal balance during walking by assessing the effects of sensory strategies on movement patterns. This may provide a deeper insight into the underlying mechanisms of falls in older adults, which could foster novel training or rehabilitation paradigms to decrease the risk of falls in older adults.</div></div>","PeriodicalId":14605,"journal":{"name":"Irbm","volume":"46 6","pages":"Article 100915"},"PeriodicalIF":4.2,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145269774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Currently, the response to chemotherapeutic treatment for most solid tumors is assessed using the surgical specimen obtained after the tumor is surgically removed, following a whole chemotherapy cycle (e.g. 8 weeks). Therefore, early detection of tumor response is of paramount importance. Parameters derived from the backscatter coefficient (BSC) and envelope statistics provide information on tissue microstructure and may therefore be of interest for monitoring therapies that induce morphological changes in the tumor. In this study, our objective was to detect ex vivo early response to chemotherapy in ex vivo murine osteosarcoma model.
Material an Methods
BSC-derived parameters using Lizzi-Feleppa approach and the Gaussian model and envelop statistics parameters using Nakagami and Homodyned-K distributions were extracted on control and treated tumors. Tumors received either 2, 4, or 5 doses of chemotherapy. To investigate the underlying causes of changes in ultrasound parameters, histological and molecular analyses (RNA sequencing) were conducted.
Results
Although the tumor models show resistance to chemotherapy as evidenced by continued tumor growth at the therapeutic dose used, significant differences between treated and control tumors were observed in several BSC-derived and envelope statistics parameters depending on the number of treatments received.
Conclusion
These differences might reflect early molecular changes occurring before the establishment of chemoresistance mechanisms. They might be attributed to morphological changes linked to the underexpression of genes involved in chromatin condensation and/or collagen within the extracellular matrix. These initial findings require further investigation in a larger cohort.
{"title":"Evaluation of Chemotherapy Response in Osteosarcoma Using Quantitative Ultrasound: A Pilot Study Relating Ultrasound Parameters to Molecular Response","authors":"Cyril Malinet , Celia Mansilla , Iveta Fajnorova , Coline Ducrot , Adrien Rohfritsch , David Melodelima , Aurélie Dutour , Pauline Muleki-Seya","doi":"10.1016/j.irbm.2025.100914","DOIUrl":"10.1016/j.irbm.2025.100914","url":null,"abstract":"<div><h3>Objectives</h3><div>Currently, the response to chemotherapeutic treatment for most solid tumors is assessed using the surgical specimen obtained after the tumor is surgically removed, following a whole chemotherapy cycle (<em>e.g.</em> 8 weeks). Therefore, early detection of tumor response is of paramount importance. Parameters derived from the backscatter coefficient (BSC) and envelope statistics provide information on tissue microstructure and may therefore be of interest for monitoring therapies that induce morphological changes in the tumor. In this study, our objective was to detect ex vivo early response to chemotherapy in ex vivo murine osteosarcoma model.</div></div><div><h3>Material an Methods</h3><div>BSC-derived parameters using Lizzi-Feleppa approach and the Gaussian model and envelop statistics parameters using Nakagami and Homodyned-K distributions were extracted on control and treated tumors. Tumors received either 2, 4, or 5 doses of chemotherapy. To investigate the underlying causes of changes in ultrasound parameters, histological and molecular analyses (RNA sequencing) were conducted.</div></div><div><h3>Results</h3><div>Although the tumor models show resistance to chemotherapy as evidenced by continued tumor growth at the therapeutic dose used, significant differences between treated and control tumors were observed in several BSC-derived and envelope statistics parameters depending on the number of treatments received.</div></div><div><h3>Conclusion</h3><div>These differences might reflect early molecular changes occurring before the establishment of chemoresistance mechanisms. They might be attributed to morphological changes linked to the underexpression of genes involved in chromatin condensation and/or collagen within the extracellular matrix. These initial findings require further investigation in a larger cohort.</div></div>","PeriodicalId":14605,"journal":{"name":"Irbm","volume":"46 6","pages":"Article 100914"},"PeriodicalIF":4.2,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145269775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-15DOI: 10.1016/j.irbm.2025.100913
Chenxi Zhao , Jianqiang Li , Qing Zhao , Jing Bai , Susana Boluda , Benoit Delatour , Lev Stimmer , Daniel Racoceanu , Gabriel Jimenez , Guanghui Fu
Alzheimer's Disease (AD) is a neurodegenerative disorder characterized by amyloid-β plaques and tau neurofibrillary tangles, which serve as key histopathological features. The identification and segmentation of these lesions are crucial for understanding AD progression but remain challenging due to the lack of large-scale annotated datasets and the impact of staining variations on automated image analysis. Deep learning has emerged as a powerful tool for pathology image segmentation; however, model performance is significantly influenced by variations in staining characteristics, necessitating effective stain normalization and enhancement techniques. In this study, we address these challenges by introducing an open-source dataset (ADNP-15) of neuritic plaques (i.e., amyloid deposits combined with a crown of dystrophic tau-positive neurites) in human brain whole slide images. We establish a comprehensive benchmark by evaluating five widely adopted deep learning models across four stain normalization techniques, providing deeper insights into their influence on neuritic plaque segmentation. Additionally, we propose a novel image enhancement method that improves segmentation accuracy, particularly in complex tissue structures, by enhancing structural details and mitigating staining inconsistencies. Our experimental results demonstrate that this enhancement strategy significantly boosts model generalization and segmentation accuracy. All datasets and code are open-source, ensuring transparency and reproducibility while enabling further advancements in the field.
{"title":"ADNP-15: An Open-Source Histopathological Dataset for Neuritic Plaque Segmentation in Human Brain Whole Slide Images with Frequency Domain Image Enhancement for Stain Normalization","authors":"Chenxi Zhao , Jianqiang Li , Qing Zhao , Jing Bai , Susana Boluda , Benoit Delatour , Lev Stimmer , Daniel Racoceanu , Gabriel Jimenez , Guanghui Fu","doi":"10.1016/j.irbm.2025.100913","DOIUrl":"10.1016/j.irbm.2025.100913","url":null,"abstract":"<div><div>Alzheimer's Disease (AD) is a neurodegenerative disorder characterized by amyloid-<em>β</em> plaques and tau neurofibrillary tangles, which serve as key histopathological features. The identification and segmentation of these lesions are crucial for understanding AD progression but remain challenging due to the lack of large-scale annotated datasets and the impact of staining variations on automated image analysis. Deep learning has emerged as a powerful tool for pathology image segmentation; however, model performance is significantly influenced by variations in staining characteristics, necessitating effective stain normalization and enhancement techniques. In this study, we address these challenges by introducing an open-source dataset (ADNP-15) of neuritic plaques (i.e., amyloid deposits combined with a crown of dystrophic tau-positive neurites) in human brain whole slide images. We establish a comprehensive benchmark by evaluating five widely adopted deep learning models across four stain normalization techniques, providing deeper insights into their influence on neuritic plaque segmentation. Additionally, we propose a novel image enhancement method that improves segmentation accuracy, particularly in complex tissue structures, by enhancing structural details and mitigating staining inconsistencies. Our experimental results demonstrate that this enhancement strategy significantly boosts model generalization and segmentation accuracy. All datasets and code are open-source, ensuring transparency and reproducibility while enabling further advancements in the field.</div></div>","PeriodicalId":14605,"journal":{"name":"Irbm","volume":"46 6","pages":"Article 100913"},"PeriodicalIF":4.2,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145108655","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-08DOI: 10.1016/j.irbm.2025.100911
Joana F. Almeida , João C. André , Cristina P. Santos
Background: Lower limb exoskeletons are in the focus of the scientific community due to their potential to enhance human quality of life across diverse scenarios. However, their widespread adoption remains limited by the lack of comprehensive frameworks to understand their biomechanical and human-robot interaction (HRI) impacts, which are essential for developing adaptive and personalized control strategies. To address this, understanding the exoskeleton's effects on kinematic, kinetic, and electromyographic signals, as well as HRI dynamics, is paramount to achieve improved usability of wearable robots. Objectives: This study aims to provide a systematic methodology to evaluate the impact of an ankle exoskeleton on human movement during walking and load-carrying (10 kg front pack) tasks, focusing on joint kinematics, muscle activity, and HRI torque signals. The methodology is designed to account for individual and device-specific factors, ensuring adaptability across users and exoskeletons. Materials and Methods: The study employed an inertial data acquisition system (Xsens MVN), electromyography (Delsys), and a unilateral ankle exoskeleton. Three complementary experiments were performed. The first examined basic dorsiflexion and plantarflexion movements. The second analysed the gait of two subjects without and with the device under passive and active assistance modes. The third investigated load-carrying tasks under the same assistance modes. Results and Conclusions: The first experiment confirmed that the HRI sensor captured both voluntary and involuntary torques, providing directional torque insights. The second experiment showed that the device slightly restricted ankle range of motion (RoM) but supported normal gait patterns across all assistance modes. The exoskeleton reduced muscle activity, particularly in active mode. HRI torque varied according to gait phases and highlighted reduced synchronisation, suggesting a need for improved support. The third experiment revealed that load-carrying increased GM and TA muscle activity, but the device partially mitigated user effort by reducing muscle activity compared to unassisted walking. HRI increased during load-carrying, providing insights into user-device dynamics. These results demonstrate the importance of tailoring exoskeleton evaluation methods to specific devices and users, while offering a framework for future studies on exoskeleton biomechanics and HRI.
{"title":"Ankle Exoskeletons in Walking and Load-Carrying Tasks: Insights into Biomechanics and Human-Robot Interaction","authors":"Joana F. Almeida , João C. André , Cristina P. Santos","doi":"10.1016/j.irbm.2025.100911","DOIUrl":"10.1016/j.irbm.2025.100911","url":null,"abstract":"<div><div>Background: Lower limb exoskeletons are in the focus of the scientific community due to their potential to enhance human quality of life across diverse scenarios. However, their widespread adoption remains limited by the lack of comprehensive frameworks to understand their biomechanical and human-robot interaction (HRI) impacts, which are essential for developing adaptive and personalized control strategies. To address this, understanding the exoskeleton's effects on kinematic, kinetic, and electromyographic signals, as well as HRI dynamics, is paramount to achieve improved usability of wearable robots. Objectives: This study aims to provide a systematic methodology to evaluate the impact of an ankle exoskeleton on human movement during walking and load-carrying (10 kg front pack) tasks, focusing on joint kinematics, muscle activity, and HRI torque signals. The methodology is designed to account for individual and device-specific factors, ensuring adaptability across users and exoskeletons. Materials and Methods: The study employed an inertial data acquisition system (Xsens MVN), electromyography (Delsys), and a unilateral ankle exoskeleton. Three complementary experiments were performed. The first examined basic dorsiflexion and plantarflexion movements. The second analysed the gait of two subjects without and with the device under passive and active assistance modes. The third investigated load-carrying tasks under the same assistance modes. Results and Conclusions: The first experiment confirmed that the HRI sensor captured both voluntary and involuntary torques, providing directional torque insights. The second experiment showed that the device slightly restricted ankle range of motion (RoM) but supported normal gait patterns across all assistance modes. The exoskeleton reduced muscle activity, particularly in active mode. HRI torque varied according to gait phases and highlighted reduced synchronisation, suggesting a need for improved support. The third experiment revealed that load-carrying increased GM and TA muscle activity, but the device partially mitigated user effort by reducing muscle activity compared to unassisted walking. HRI increased during load-carrying, providing insights into user-device dynamics. These results demonstrate the importance of tailoring exoskeleton evaluation methods to specific devices and users, while offering a framework for future studies on exoskeleton biomechanics and HRI.</div></div>","PeriodicalId":14605,"journal":{"name":"Irbm","volume":"46 5","pages":"Article 100911"},"PeriodicalIF":4.2,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145104285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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