Saudi Cultural Missions Theses & Dissertations
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Item Restricted In-vivo and ex-vivo detection of colorectal cancer at ultra-low field using fast field-cycling methods(Saudi Digital Library, 2025) Alamri, Amnah Saad; Ramsay, George; Broche, Lionel MColorectal cancer (CRC) remains a major global health burden, with over 1.9 million new cases and approximately 904,000 deaths reported worldwide in 2022. CRC includes cancers of both the colon and rectum, with rectal cancer affecting the last 12-15 cm of the large intestine. Staging this disease relies heavily on CT and MRI of the pelvis. To date, these imaging modalities provide limited information on the microstructural and biological changes associated with tumour progression or treatment response. This thesis aims to investigate the potential of field-cycling magnetic resonance methods, specifically Fast Field-Cycling Nuclear Magnetic Resonance (FFC-NMR) and Field-Cycling Imaging (FCI), as innovative approaches for the detection and characterisation of CRC and LARC. Specifically, the work explores whether intrinsic tissue relaxation properties can differentiate tumours from surrounding tissues and provide early indicators of therapeutic response. To address these questions, two pilot studies were conducted. The ex-vivo study analysed fresh CRC tissues using FFC-NMR relaxometry to assess ¹H relaxation dispersion profiles in tumour, peritumour, and healthy samples. To support interpretation of the signal differences, proteomics analysis was performed on the same samples to explore protein expression contributions to the observed relaxation behaviour. In the in-vivo study, the whole body FCI scanner was used to scan a cohort of LARC patients, acquiring pre- and post-treatment scans to evaluate whether changes in relaxation biomarkers could reflect response to neoadjuvant chemoradiotherapy (nCRT). Findings from the ex-vivo study indicated noticeable differences in the dispersion profiles between tissue types, and proteomic analysis identified different pathways potentially linked to these contrasts, including enrichment in ATP production, protein synthesis, and ribosomal activity in tumour tissues. In the in-vivo study, the FCI imaging protocol was successfully implemented, and preliminary data showed significantly higher R1 values in tumour regions compared to healthy tissue at 2 mT and 0.2 mT (p < 0.0001), with slope and intercept biomarkers also differing significantly (p < 0.005), with changes observed after treatment in patients showing complete or partial response. In conclusion, this thesis provides preliminary evidence supporting the feasibility of FFC-NMR and FCI as non-invasive tools for CRC and LARC assessment. While findings are promising, further research with larger cohorts is essential to validate these findings, improve statistical power and enable patient stratification to better capture tumour heterogeneity and treatment response.5 0Item Restricted Comparative analysis of magnetic resonance imaging- and computed tomography-based finite element approaches in estimating bone strength in children(Saudi Digital Library, 2025) Alasmari, Nayef Mohammed; Li, Xinshan; Offiah, AmakaThis PhD thesis compares magnetic resonance imaging (MRI)- and computed tomography (CT)-based finite element analysis (FEA) in estimating bone strength in children. A systematic review and meta-analysis (Chapter 3) was conducted and confirmed the reliability of MRI and FEA in assessing bone material properties and strength in adults but revealed limited paediatric research, identifying only one study. As segmentation is a critical step in FEA, we then conducted a comparative study (Chapter 4) to assess the accuracy and efficiency of ITK-SNAP, 3D Slicer and Amira™ using paired paediatric CT/MRI scans. ITK-SNAP and Amira™ were the most accurate, while 3D Slicer provided comparable results with greater efficiency and was selected for this thesis. Chapter 5 outlines the methodology used to compare MRI- and CT-based FEA in estimating bone strength in children without (n = 9; Chapter 6) and with (n = 8; Chapter 7) bone disease. In children without bone disease, MRI- and CT-based FEA exhibited strong correlation for tensile (ICC = 0.83) and moderate correlation for compressive (ICC = 0.61) failure loads, with MRI-based FEA consistently underestimating the failure loads. In children with bone disease, the modalities demonstrated moderate correlation for tensile (ICC = 0.60) and fair correlation for compressive (ICC = 0.40) failure loads, with similar underestimation of failure loads by MRI-based FEA. Discrepancies between MRI- and CT-based FEA tensile and compressive estimates did not significantly differ between children without and with bone disease (p = 0.386 and p = 0.441, respectively). Chapter 8 summarises the findings, limitations and future directions. Overall, MRI-based FEA showed similar trends to CT-based FEA in estimating bone strength in children, despite underestimating failure loads, particularly in proximal femurs and under compressive loading. With continued improvements in MRI resolution and FEA modelling, MRI-based FEA holds potential as a radiation-free alternative for paediatric bone strength assessment.55 0Item Restricted Deep Learning based Cancer Classification and Segmentation in Medical Images(Saudi Digital Library, 2025) Alharbi, Afaf; Zhang, QianniCancer has significantly threatened human life and health for many years. In the clinic, medical images analysis is the golden stand for evaluating the prediction of patient prog- nosis and treatment outcome. Generally, manually labelling tumour regions in hundreds of medical images is time- consuming and expensive for pathologists, radiologists and CT scans experts. Recently, the advancements in hardware and computer vision have allowed deep-learning-based methods to become main stream to segment tumours automatically, significantly reducing the workload of healthcare professionals. However, there still remain many challenging tasks towards medical images such as auto- mated cancer categorisation, tumour area segmentation, and relying on large-scale labeled images. Therefore, this research studies theses challenges tasks in medical images proposing novel deep-learning paradigms that can support healthcare professionals in cancer diagnosis and treatment plans. Chapter 3 proposes automated tissue classification framework called Multiple Instance Learning (MIL) in whole slide histology images. To overcome the limitations of weak super- vision in tissue classification, we incorporate the attention mechanism into the MIL frame- work. This integration allows us to effectively address the challenges associated with the inadequate labeling of training data and improve the accuracy and reliability of the tissue classification process. Chapter 4 proposes a novel approach for histopathology image classification with MIL model that combines an adaptive attention mechanism into an end-to-end deep CNN as well as transfer learning pre-trained models (Trans-AMIL). Well-known Transfer Learning architectures of VGGNet [14], DenseNet [15] and ResNet[16] are leverage in our framework implementation. Experiment and deep analysis have been conducted on public histopathol- ogy breast cancer dataset. The results show that our Trans-AMIL proposed approach with VGG pre- trained model demonstrates excellent improvement over the state-of-the-art. Chapter 5 proposes a self-supervised learning for Magnetic resonance imaging (MRI) tu- mour segmentation. A self-supervised cancer segmentation framework is proposed to re- duce label dependency. An innovative Barlow-Twins technique scheme combined with swin transformer is developed to perform this self supervised method in MRI brain medical im- ages. Additionally, data augmentation are applied to improve the discriminability of tumour features. Experimental results show that the proposed method achieves better tumour seg- mentation performance than other popular self- supervised methods. Chapter 6 proposes an innovative Barlow Twins self supervised technique combined with Regularised variational auto-encoder for MRI tumour images as well as CT scans images segmentation task. A self-supervised cancer segmentation framework is proposed to reduce label dependency. An innovative Barlow-Twins technique scheme is developed to represent tumour features based on unlabeled images. Additionally, data augmentation are applied to improve the discriminability of tumour features. Experimental results show that the pro- posed method achieves better tumour segmentation performance than other existing state of the art methods. The thesis presents four approaches for classifying and segmenting cancer images from his- tology images, MRI images and CT scans images: unsupervised, and weakly supervised methods. This research effectively classifies histopathology images tumour regions based on histopathological annotations and well-designed modules. The research additionally comprehensively segments MRI and CT images. Our studies comprehensively demonstrate label-effective automatic on various types of medical image classification and segmentation. Experimental results prove that our works achieve state-of-the-art performances on both classification and segmentation tasks on real world datasets16 0Item Restricted Advancement of the Quantitative Blood Oxygenation Level-Dependent (qBOLD) MRI technique to improve clinical feasibility.(university of Nottingham, 2024) Alzaidi, Ahlam; Blockley, NicholasAbstract Quantitative Blood Oxygenation Level Dependent (qBOLD) MRI offers a noninvasive method for measuring brain oxygenation, with potential applications in various neurological conditions. However, its clinical implementation has been hindered by methodological inconsistencies and challenges in standardisation. This thesis aims to address these obstacles and advance the clinical applicability of qBOLD techniques through three studies. First, a comprehensive scoping review of the qBOLD literature was conducted. The review revealed four main qBOLD acquisition methods: multiparametric (mpqBOLD), asymmetric spin echo (ASE), gradient echo (GRE), and gradient echo sampling of spin echo (GESSE). Notably, mp-qBOLD emerged as the most used technique, likely due to its easier implementation in clinical settings. However, significant variability in the reversible transverse relaxation rate (R2') measurements across different acquisition techniques was observed, highlighting the need for standardisation. To address this variability and enable quality assurance, the second study focused on developing and validating a new qBOLD phantom using glass microspheres. A linear relationship between R2' contrast and glass bubble volume fraction was established, and the phantom demonstrated good reproducibility in construction and MRI measurements. Crucially, R2' measurements were consistent across different qBOLD acquisitions and MRI vendors and the phantom accurately replicated known in vivo R2' values for human brain tissue. However, challenges arose in matching the irreversible transverse relaxation rate (R2) values to the human brain range. The third study explored a combined hyperoxia-BOLD and mp-qBOLD (hmpqBOLD) approach to improve oxygen extraction fraction (OEF) estimation in a clinically translatable manner. This combined method overestimated OEF compared to an established technique, with values exceeding normal physiological ranges. In conclusion, this thesis has made important contributions towards addressing key challenges to the clinical implementation of qBOLD imaging, laying a solid foundation for future advancements in quantitative oxygenation imaging and its translation to clinical practice.26 0Item Restricted SEVERITY GRADING AND EARLY DETECTION OF ALZHEIMER’S DISEASE THROUGH TRANSFER LEARNING(Saudi Digital Library, 2025) Alqahtani, Saeed; Zohdy, MohamedAlzheimer’s disease (AD) is a neurological disorder that predominantly affects individuals aged 65 and older. It is one of the primary causes of dementia, and it contributes significantly and progressively to impairing and destroying brain cells. Recently, efforts to mitigate the impact of AD have focused with particular emphasis on early detection through computer aided diagnosis (CAD) tools. This study aims to develop deep learning models for the early detection and classification of AD cases into four categories: non-demented, moderate-demented, mild-demented, and very mild demented. Using Transfer Learning technique (TL), several models were implemented including AlexNet, ResNet-50, GoogleNet (InceptionV3), and SqueezeNet, by leveraging magnetic resonance images (MRI) and applying image augmentation techniques. A total of 12,800 images across the four classifications that were preprocessed to ensure balance and meet the specific requirements of each model. The dataset was split into 80% for training and 20% for testing. AlexNet achieved an average accuracy of 98.05%, GoogleNet (InceptionV3) reached 97.80%, ResNet-50 attained 91.11%, and SqueezeNet 86.37%. The use of transfer learning method addresses data limitations, allowing effective model training without the need for building from scratch, thereby enhancing the potential for early and accurate diagnosis of Alzheimer’s disease [1].17 0Item Restricted Investigating Glymphatic System and AQP4 Water Channels with Novel Drugs and MRI Techniques(Saudi Digital Library, 2025) Alghanimy, Alaa; Holmes, WilliamThe glymphatic system serves as a vital low resistance pathway for the efficient removal of toxic waste products from the brain and its malfunction is implicated in numerous neuropathological conditions. Aquaporin-4 (AQP4) water channels are membrane-tied and highly expressed at the end-feet of astrocytic cells in the brain. They are thought to be crucial to the glymphatic clearance system, water circulation, and homeostasis of the brain. Pharmacologically targeting AQP4 presents a promising therapeutic strategy for various neurological diseases. In 2009, Huber et al. developed TGN-020, a potent AQP4 inhibitor that significantly reduced cerebral oedema in stroke models. In 2018, they introduced TGN-073, a novel AQP4 facilitator that enhanced fluid turnover and interstitial fluid clearance. This thesis investigates the effects of these AQP4 modulators, with a particular focus on TGN-073, using advanced MRI techniques and immunofluorescence staining in rat models to elucidate their potential therapeutic benefits. The initial objective was to employ an H2 17O tracer to evaluate the effect of the novel AQP4 facilitator TGN-073 on glymphatic transport. Despite extensive optimization efforts, the tracer signal remained low and unreliable, precluding its use in conducting our studies. Consequently, we assessed the impact of TGN-073 on glymphatic transport using dynamic contrast-enhanced MRI. This involved catheterizing the cisterna magna to infuse the MRI contrast agent Gd-DTPA into the cerebrospinal fluid. Our findings indicated that rats treated with TGN-073 exhibited a more extensive distribution and higher parenchymal uptake of Gd DTPA compared to the vehicle group, suggesting TGN-073's potential in enhancing glymphatic function. Following this, I developed and established an immunohistochemistry protocol for AQP4 staining using immunofluorescence, a first in our department. The aim was to optimize this technique to its fullest potential, ensuring precision and reliability for the following experiments. Given the invasive nature of the method used to investigate the impact of TGN 073 on glymphatic transport, which requires cisterna magna cannulation, non invasive alternatives were explored. Therefore, the impact of both AQP4 modulators, TGN-020 and TGN-073, was assessed without the necessity of exogenous contrast agents. These evaluations utilized T2 mapping and stimulated echo diffusion-weighted echo planar imaging (STE-DW-EPI), followed by immunofluorescence labelling of AQP4. No significant changes in the diffusion coefficient were observed across all observation times in any animal group, indicating no substantial alterations in brain microstructure. However, T2 values significantly decreased following the administration of TGN-073, suggesting enhanced water exchange. In contrast, T2 values significantly increased following the administration of TGN-020, while remaining unchanged in the vehicle group. These findings underscore the role of AQP4 in modulating water exchange between tissue compartments. Immunofluorescence staining revealed significantly higher AQP4 expression in the brains treated with TGN-073, contrasting with a significant decrease in AQP4 expression in the brains treated with TGN-020, compared to the vehicle-treated group. To advance our understanding of the positive effects of AQP4 facilitators on glymphatic function, we investigated the impact of TGN-073 in a rat model of vascular cognitive impairment, specifically the bilateral common carotid artery stenosis (BCAS) model. This model, known for inducing chronic cerebral hypoperfusion and vascular dementia, represents a novel application within our institution. To our knowledge, this is the first study to evaluate glymphatic transport in BCAS rat models and to assess the impact of an AQP4 facilitator in this context. We successfully established cerebral hypoperfusion in the BCAS model, as evidenced by a significant reduction in cerebral blood flow (CBF). Our findings demonstrated glymphatic dysfunction and altered AQP4 expression associated with BCAS. Importantly, TGN-073, effectively mitigated these effects by restoring AQP4 expression, enhancing glymphatic function, and alleviating CBF reduction. This study highlights the potential of AQP4 facilitators in ameliorating the adverse effects of cerebral hypoperfusion and associated glymphatic dysfunction. TGN-073 shows promise for preventing the progression of neurodegenerative diseases and improving the quality of life for affected individuals.22 0Item Restricted Cancer target discovery for biomarker development, imaging and radionuclide loaded nanoparticle therapy(Saudi Digital Library, 2023-12-04) Shabbir, Rekaya; Choudhury, Ananya; West, Catharine; Smith, TimBackground and aims: Patients with hypoxic muscle invasive bladder cancer (MIBC) have a poor prognosis and overall survival (OS) rate. There is a need to develop biomarkers for informing on hypoxia-targeting therapy. Gene expression signatures can predict benefit from hypoxia modification to improve outcome. Imaging genomics links medical images with molecular profiling to discover imaging biomarkers that could reflect hypoxia. Molecular radiotherapy (MRT) targets specific receptors expressed by cells. The overexpression of EGFR also associates with poor survival rates, EGFR inhibitors are promising but tumour heterogeneity is problematic. The thesis aims were to: 1) identify genes upregulated by hypoxia in bladder cancer cells; 2) investigate whether the West 24-gene bladder hypoxia signature is sensitive to changes in oxygen levels; 3) use MRI to identify hypoxia in large and small tumours in vivo; 4) identify new hypoxia-associated gene panels from transcriptomic data generated in vitro and in vivo; 5) identify bladder cancer hypoxic biomarkers and surface membrane targets for MRT using proteomics in MIBC; and 6) study the uptake and dose-distributions of EGFR-targeted 177Lu or 90Y radiolabelled-AuNPs. Methods: 1) Six BC cell lines (HT1376, T24, J82, UMUC3, RT4, RT112) were exposed to normoxia (21% O2) and hypoxia (1%, 0.1% and 0.2% O2) for 24h. RNA was extracted, transcriptomic data generated using Clariom S Microarrays and expression of hypoxia upregulated genes identified. 2) The data were used to explore changes in West 24-gene signature scores. 3) Small (300mm3) and large (700mm3) xenografts were established for HT1376 MIBC cells. Hypoxia was identified using pimonidazole (PIMO), OE-MRI and DCE-MRI. Differential gene expression was determined. 4) Gene panels were derived from in vitro and in vivo transcriptomic data and tested (log-rank Mantel Cox test) in a TCGA bladder cancer cohort (n=412). Hypoxia scores were generated using the median expression of the genes in a signature/panel. 5) HT1376, T24 and J82 cells were cultured in normoxia (21% O2) and hypoxia (1% and 0.1% O2) for 24h and 48h. Proteins were extracted and analysed using LC-MS and SWATH-MS, and the data used to identify surface membrane targets. Differential expression of EGFR and hypoxia markers (CAIX, GLUT-1) was measured using transcriptomics, proteomics, western blot and EGFR-ELISA. 6) Anti-EGFR conjugated radiolabelled (177Lu or 90Y) AuNPs were used to study dose distributions in vivo. Results: 1) 77 genes were significantly upregulated (padj≤ 0.001) in hypoxia (0.1% O2) across ≥3 cell lines. Three genes (DPYSL2, SYDE1, SLC2A3) were in both the West 24-gene signature and new 77-gene panel. 2) The expression of the 24-gene West signature increased with decreasing O2 levels. 3) Hypoxic regions were identified in small and large xenografted tumours using a combination of OE-MRI and DCE-MRI approaches. The in vivo transcriptomics analysis identified gene expression differences between PIMO-high(hypoxic) and PIMO-low(normoxic) regions and differences in HSs generated from the 24-gene signature (p<0.0052) and the new 77-gene panel (p<0.0025). 4) Gene signatures/panels were prognostic for overall survival: 24-gene (p<0.000064), 77-gene (p<0.01), 3 common genes (p<0.0013). 5) 26 proteins had consistently higher expression in hypoxia across all three cell lines. A gene panel based on the 26 proteins was prognostic in the TCGA cohort (p<0.00065). Eleven plasma membrane proteins were identified as upregulated under hypoxia. No significant differential expression of EGFR was seen in BC cells by hypoxia. The expression of hypoxia markers (CAIX and GLUT-1) was significantly increased by hypoxia using different measurement approaches in all bladder cells. 6) The coefficient of variation of EGFR-targeted 90Y-radiolabelled-AuNPs was less than EGFR-targeted 177Lu-radiolabelled-AuNPs in xenografted tumours. Conclusions: 1) Hypoxia influences the expression of many common genes across different bladder cancer cell lines. 2) The West 24-gene bladder hypoxia score is sensitive to changes in O2 levels in vitro showing it reflects differences in hypoxia. 3) Gene panels derived from hypoxic cells in vitro inform on hypoxia and prognosis 4) The West 24-gene signature performed best as a biomarker of hypoxia. 5) Proteomic profiling identified cell membrane markers to study for MRT. 6) Anti-EGFR radionuclides labelled AuNPs provided insight about the heterogeneity and dosimetry of MRT.11 0Item Restricted Using multi-modal PET and MRI to predict the site of tumour recurrence in high-grade glioma(The University of Manchester, 2024) Alfaifi, Bandar Q; Hinz, Rainer; Coope, David; Lewis, Daniel; Jackson, AlanBackground: High-grade gliomas (HGG) are highly aggressive and incurable brain tumours that often recur within 2 cm of the original site, even after complete oncological treatments. Advanced MRI and PET techniques hold promise for better tumour delineation and characterisation. This thesis investigates the spatial characterisation of translocator protein (TSPO) and amino acid PET in initially diagnosed HGG and at the point of post-treatment progression, with a view to identifying future sites of disease progression. Methods: HGG patients underwent prospective imaging with [11C](R)PK11195 and [11C]methionine PET alongside MRI including diffusion tensor imaging (DTI). [11C](R)PK11195 binding potential (BPND) and [11C]methionine tumour-to-background ratio were generated. The PET biomarkers were first used to characterise tumour regions defined on MRI as contrast-enhancing (CE) and peritumoral regions and diffusion connectivity map (N=12 initially diagnosed). Secondly, tumour biological volumes were delineated and compared among [11C](R)PK11195 and [11C]methionine PET and CE-MRI using overlap, Dice and Jaccard similarity coefficients (DSC and JSC), and discrepancy measures at baseline (12- initially diagnosed; 8 post-treatment). Disease progression was assessed using follow-up MRI (N=16) and registered with baseline PET biomarkers to explore overlap and similarity. Results: In newly diagnosed HGG, 67±22% of CE-MRI regions showed positive TSPO/methionine, while 36±15% of peritumoral regions showed positive TSPO but negative methionine. TSPO binding in CE-MRI and peritumoral regions was significantly higher than in the contra-lesional reference. [11C](R)PK11195 PET demonstrated a gradual decrease in TSPO binding along the DTI connectivity map compared to [11C]methionine. [11C](R)PK11195 and [11C]methionine biological volumes showed moderate spatial similarity (DSC=0.65±0.15, JSC=0.50±0.16) at initial diagnosis, which decreased for post-treatment HGG (DSC=0.35±0.15, JSC=0.22±0.11). Both PET volumes exhibited moderate overlap with CE-MRI at initial diagnosis, but post-treatment spatial similarity decreased, with substantial discrepancies. TSPO binding and methionine uptake show signals in areas where future disease progression occurred, with average overlaps of 0.51±0.25 and 0.43±0.26, respectively. Conclusions: This work provides the first detailed spatial characterisation of two PET biomarkers in newly diagnosed HGG and at the point of post-treatment progression. Elevated TSPO binding without increased methionine uptake may indicate inflammatory or discrete neoplastic populations not captured by standard imaging techniques. Both PET radiotracers demonstrated increased uptake beyond initial contrast enhancement, and although the exact site lacked specificity, disease progression almost universally occurred within this area. Notably, the discrepancy between TSPO and methionine binding increases post-treatment, with elevated TSPO expression likely reflecting late-stage inflammation contributing to symptomatic worsening in such patients.19 0Item Restricted Development of a Patient-Specific Streamlined Workflow for a Predictive Tool for Coronary Artery Bypass Graft Outcomes(University College London, 2024-12-01) Alsaleh, Abdullah; Torii, RyoCoronary artery disease is one of the leading causes of mortality worldwide and is treatable by only a few procedures, such as coronary artery bypass grafting (CABG). However, predicting the long-term success of CABG, particularly in terms of graft patency and disease progression, remains a challenge. This thesis aims to develop a patient-specific streamlined workflow for a predictive tool that integrates peri-operative Coronary Computed Tomography Angiography (CCTA) with Computational Fluid Dynamics (CFD) simulations to predict post-CABG outcomes. The patient-specific streamlined workflow for a predictive tool for CABG outcomes is designed to simulate hemodynamic conditions within grafts, providing personalized predictions to guide surgical decisions and improve patient outcomes. The methodology includes creating anatomically accurate 3D models, simulating hemodynamic conditions, and validating the results against clinical data. While the patient-specific streamlined workflow for the predictive tool shows promise, significant challenges remain in terms of boundary condition setup, data integration, and discrepancies between simulation results and hospital data. The overestimation of flow rates and high wall shear stress observed in the simulations indicate the need for refinements in model assumptions, including incorporating non-Newtonian blood properties, vessel wall compliance, and pulsatile blood flow. Despite these limitations, this study demonstrates the potential of a patient-specific streamlined workflow for a predictive tool for CABG outcomes and offers a path forward for personalized cardiovascular treatment. Future work will focus on refining the model to enhance its accuracy, and clinical applicability, and commercializing the method.30 0Item Restricted Exploring Muscle Structure, Function, and Gait Patterns in People with Distal Hereditary Motor Neuropathy: Natural History and the Effect of Rehabilitation Interventions(University College London (UCL), 2024-09) Alangary, Aljwhara; Ramdharry, Gita; Morrow, Jasper; Laura, MatildeBackground: Distal Hereditary Motor Neuropathy (DHMN) is a rare heterogenous inherited neuromuscular disorder. It is characterised by distal progressive weakness. Objectives: This thesis provides preliminary longitudinal data to describe the natural history of DHMN in terms of muscle structure, muscle strength, and gait parameters, also to investigate the effect of commonly used rehabilitation interventions. Methods: DHMN adult participants underwent the following measures: MRI scans of the foot, calf, and thigh muscles, isokinetic and isometric strength measures of the lower limb using dynamometer, 3D motion analysis to capture kinetic and kinematic data of walking gait. For direct comparison, matched health controls underwent the same measures. Measures were repeated after 6 and 12 months to explore the natural history of the disease. DHMN participants underwent additional gait analysis wearing bilateral carbon fibre ankle foot orthoses to explore the effect on gait. Eligible DHMN participants were prescribed a home based resistance training program, and the response to training was analysed by the same measures after 6 months of training. Results: The study identified significant progressive muscle atrophy and increased intramuscular fat accumulation at the calf in DHMN participants, with a notable decline in muscle strength over time and altered gait mechanics. The use of ankle-foot orthoses showed improvements in gait stability, while the resistance training program indicated potential benefits in maintaining muscle function, but adherence was a key challenge. Conclusion: The preliminary data from this study provide valuable insights into the natural history of DHMN, highlighting the progressive nature of muscle degeneration and functional decline. These findings offer useful guidance for health practitioners in managing DHMN and emphasize the need for targeted rehabilitation interventions to improve patient outcomes. Future research should focus on longer-term studies with larger cohorts to validate these findings and further explore effective management strategies.17 0