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Item Restricted CYBERSECURITY OF CRITICAL INFRASTRUCTURE’S MANUFACTURING SYSTEMS A NOVEL FRAMEWORK AND APPROACH FOR PREDICTING CYBERATTACKS BASED ON ATTACKER MOTIVATIONS(Saudi Digital Library, 2025) Alqudhaibi, Adel; Sandeep, JagtapIndustry 4.0 signifies a transformative shift in industrial operations, powered by the integration of automation, connectivity, and digital technologies. This shift enhances diagnostics, autonomous decision-making, automation, and data analysis by machinery and networking equipment, revolutionizing the manufacturing and critical infrastructure sectors. However, the increased reliance on such technologies raises significant cybersecurity concerns. These vulnerabilities are particularly acute in Industrial Control Systems (ICS) , which are commonly used in critical infrastructure (CI) for operational and supervisory control. Industry 4.0 manufacturing systems face increasing cybersecurity threats due to the lack of predictive threat detection, inadequate security frameworks, and growing system complexity. Existing approaches are reactive, failing to incorporate attacker motivations and proactive risk mitigation. As a result, manufacturing systems are exposed to numerous cyber-attacks that can have catastrophic concerns for critical infrastructure sectors such as energy, transportation, and water. Addressing these challenges requires a comprehensive and systematic approach to cybersecurity that is specifically tailored to the nature of these systems. This research introduces a novel cybersecurity approach that predicts potential cyberattacks by considering attacker motivations and the specific characteristics of CI systems. Machine learning (ML) models are employed to predict potential attack methods, offering a proactive solution to prevent cyber threats before they occur. This approach demonstrates a substantial improvement in predictive accuracy, as confirmed by initial evaluation results. Cybersecurity in CI manufacturing systems remains reactive, relying on post-attack mitigation rather than proactive threat prevention. This research addresses the gap by developing a predictive cybersecurity approach Predicting Cyberattacks in Critical Infrastructures (PCCI) which anticipates cyber threats based on attacker motivations and CI system vulnerabilities. Using machine learning (ML) models, this approach enhances attack method prediction, significantly reducing false positives and improving detection accuracy. The proposed framework shifts cybersecurity from a reactive to a proactive stance, contributing to enhanced resilience in Industry 4.0 environments. Initial tests demonstrate notable improvements in prediction accuracy, validating its potential for real-world application. Beyond the implementation of predictive cybersecurity models, this research presents a comprehensive cybersecurity framework that emphasises sustainability within the manufacturing sector. The framework is structured to protect critical resources by ensuring the confidentiality, integrity, and availability of data, while simultaneously enhancing operational resilience. It incorporates proactive strategies for anticipating cyber threats and underscores the importance of comprehensive employee education at all organisational levels. This framework seeks not only to mitigate immediate security risks but also to integrate long-term resilience into cybersecurity strategies, thereby promoting the sustainability of manufacturing operations. A key finding of this research is the significant gap in robust security standards and proactive measures within the manufacturing sector concerning cybersecurity. Despite the growing adoption of Industry 4.0 technologies, many systems remain vulnerable to cyberattacks due to the absence of sufficient security protocols during the early stages of implementation. The absence of standardized guidelines contributes to insufficient employee knowledge and preparedness, leaving them vulnerable to cybersecurity risks. Addressing these gaps is essential for the manufacturing sector to fully capitalize on Industry 4.0 advancements while ensuring the protection of critical systems from emerging cyber threats. The study concludes by recommending a redirection of security resources and procedures to the manufacturing industry. It emphasises the need for increased investment in employee awareness, training programs, and more robust cybersecurity protocols specifically tailored to the needs of industrial systems. By implementing these recommendations, organisations can better mitigate risks, enhance their cybersecurity posture, and ensure the continuity of critical manufacturing and infrastructure operations in the face of progressing cyberattacks.5 0Item Restricted Healthcare Professionals' Understanding of Children's Rights: Development and Psychometric Testing of the Children's Rights Questionnaire(Saudi Digital Library, 2025) Alshammari, Sahar Mazied N; Noble, Helen; Linden, MarkThe United Nations Convention on the Rights of the Child (UNCRC) emphasises the active participation of children in matters related to their well-being. While numerous studies highlight the significance of understanding children’s rights, there is a notable lack of validated and reliable tools to assess healthcare professionals' (HCPs) comprehension of these rights. This gap poses challenges for consistent evaluation and progress tracking in both research and clinical practice. To date, studies have relied on invalid and unreliable measures, limiting their generalisability and underscoring the urgent need for the development of robust assessment tools. HCPs play a crucial role in advocating for and implementing children’s rights; however, their understanding of these rights vary significantly. Addressing this gap is essential for enhancing advocacy efforts among HCPs. Aim: This study aimed to develop and psychometrically test the Children’s Rights for Healthcare Professionals Questionnaire (CRHPQ) to assess HCPs’ understanding of children’s rights. The study pursued four key objectives: (a) to establish and test the CRHPQ for face and content validity, (b) to determine its construct validity and internal consistency, (c) to examine its test-retest reliability, and (d) to utilise the CRHPQ in comparing the understanding of children's rights between HCPs in the Kingdom of Saudi Arabia (KSA) and the United Kingdom (UK). Methods: A systematic review was conducted to critically appraise and synthesise the existing literature on HCPs’ understanding of children’s rights. The questionnaire was developed following a rigorous multi-phase process, including expert validation, pilot testing, and ii psychometric evaluation with a diverse sample of HCPs. The scale development methodology comprised two phases. Phase 1: focused on the development of the CRHPQ, detailing the steps involved in constructing the scale, including item generation, format selection, expert review for content validity, and pilot testing. The role of both the Children’s Project Advisory Group (CPAG) and the Adult Project Advisory Group (APAG) in refining the scale was also highlighted. The research team collaborated with advisory groups to assess the clarity, importance, and relevance of the questionnaire items, ensuring alignment with the World Health Organization’s (WHO) seven standards of children’s rights based on the UNCRC. The CRHPQ was piloted with 26 students to evaluate content validity. Phase 2: addressed the validation of the CRHPQ, involving scale administration and Exploratory Factor Analysis (EFA) to examine its construct validity. Reliability assessment, including internal consistency and test-retest reliability, was conducted to evaluate the scale’s stability and consistency. To test the psychometric properties of the CRHPQ, an exploratory factor analysis and internal consistency tests were performed. A cross-sectional study was conducted with 272 HCPs to assess the construct validity of the CRHPQ. Participants were recruited from three major hospitals using a convenience sampling strategy. Data were analysed using descriptive and inferential statistics, including reliability testing and factor analysis. Test-retest reliability was assessed with postgraduate healthcare students at Queen’s University Belfast. Participants completed the questionnaire twice, with a two-week interval. Recruitment was conducted via module coordinators, and data were collected online. A minimum of 30 paired responses was required, but 40 participants were recruited to ensure sufficient data. iii A cross-sectional online questionnaire study compared HCPs’ understanding of children’s rights in KSA and the UK. Primary data from 40 randomly selected HCPs in KSA were compared with responses from 40 postgraduate healthcare students in the UK. In KSA, participants were drawn from the larger sample of 272 HCPs, while in the UK, postgraduate students were recruited for accessibility and relevant clinical training. Results: The systematic review identified three main themes: (1) barriers to implementing children’s rights in healthcare, (2) factors facilitating implementation, and (3) study instruments used to measure outcomes. Several barriers hindered the implementation of children’s rights, including limited knowledge, misconceptions about legal and ethical principles, time constraints, resource shortages, and workforce pressures. Parental dominance in decision-making and a lack of formal training further exacerbated these challenges. Despite these challenges, certain factors facilitated the implementation of children’s rights. HCPs with specialist training demonstrated a stronger understanding and application of these rights. Effective communication strategies, such as age-appropriate explanations and trust-building, were crucial in encouraging children’s participation in decision-making. Institutional policies and legal frameworks also played a role in promoting consistent rights- based practices. Statistical analyses confirmed the CRHPQ’s validity and reliability, establishing it as a robust tool for measuring HCPs' awareness and comprehension of children’s rights. The EFA revealed a seven-factor solution consisting of 53 items. Internal consistency, assessed using Cronbach’s alpha, demonstrated excellent reliability (α = 0.979). Test-retest reliability analysis, completed by 40 HCPs, indicated moderate reliability, with four out of seven subscales exhibiting poor test-retest reliability. In its first application, iv the CRHPQ was employed to compare HCPs' understanding of children’s rights in the UK and KSA. An independent t-test revealed a statistically significant difference in total scores between the two groups, t(50.529) = 2.034, p = .047 (two-tailed), suggesting that HCPs in the UK had a higher understanding of children’s rights than those in KSA. Conclusions: The CRHPQ is a valid and reliable tool for assessing HCPs’ understanding of children’s rights. This research underscores the importance of equipping HCPs with the knowledge necessary to provide rights-respecting care in line with global frameworks such as the UNCRC. Findings indicate significant variations in understanding across different contexts, highlighting the need for targeted interventions to enhance HCPs’ awareness of children’s rights. The CRHPQ not only identifies understanding gaps but can also be utilised to support the development of educational programmes to improve HCPs’ understanding and application of children’s rights. Integrating rights-based approaches into healthcare is crucial, necessitating training, policy development, and practical application. Ultimately, the CRHPQ has the potential to drive systemic change in healthcare practices globally, ensuring that children’s rights are consistently upheld.3 0Item Restricted Evaluating the Impact of Vision 2030's Legal Reforms on Attracting Foreign Investment to Saudi Arabia(Saudi Digital Library, 2025) Alshehri, Amani; Austin, NwaforOver the years, Saudi Arabia has relied heavily on oil exports, making it one of the world’s largest oil exporters. Oil accounted for over 42% of Saudi Arabia’s GDP, 90% of export revenue, and 87% of budget revenues. However, this dependence on oil creates significant vulnerabilities which impact the economy negatively. This includes the decrease in oil prices, demographic changes, the world’s transition towards renewable energy and concerns about the long-term sustainability of oil-based economies. These challenges led to the transformation plan Vision 2030 Launched in 2016 to diversify the economy. Vision 2030 aims to diversify the economy into non-oil sectors such as tourism, technology, and renewable energy. 5 Some of the indicators include Increase KSA's share of non-oil exports, Raise private sector contribution to 65% of GDP, Increase FDI contribution to GDP to 5.7% among others. To achieve this, different economic, social, and legal reforms were instituted while improving the foreign investment positioning of the country. The legal reforms remain one of the significant initiatives to attract foreign direct investment (FDI) by creating a more transparent, efficient, and business-friendly regulatory environment. Hence, this research aims to analyse critically the Impact of Vision 2030's Legal Reforms on Attracting Foreign Investment to Saudi Arabia.19 0Item Restricted Sustainable Wildlife Tourism in Saudi Arabia(Saudi Digital Library, 2024) Aldughaishem, Abdulrhman; Philip, RylandThis study explores the opportunities and challenges of developing sustainable wildlife tourism in Saudi Arabia, a country known for its rich biodiversity and unique ecosystems. The research underscores the importance of economic benefits such as job creation and revenue generation in enhancing tourist satisfaction, aligning with Saudi Arabia's Vision 2030 objectives of economic diversification. However, the study also highlights significant environmental concerns, including habitat disruption and pollution, which pose challenges to the long-term sustainability of wildlife tourism. The effectiveness of current regulatory frameworks is questioned, suggesting a need for stronger enforcement and policy refinement. Community involvement emerges as a crucial factor, positively influencing both economic and social benefits. The study concludes with recommendations for enhancing environmental regulations, promoting community-based tourism, and fostering public-private partnerships. Additionally, it calls for future research to focus on the long-term impacts of tourism, broader geographic studies, and the effects of climate change on wildlife tourism in Saudi Arabia. These insights aim to guide policymakers, industry stakeholders, and researchers in developing a sustainable wildlife tourism sector that supports economic growth while preserving natural resources and enhancing community well-being.9 0Item Restricted AI Impersonation on social media Analysing Human Characteristics and Ethical Implications(Saudi Digital Library, 2025) Almuammar, Eyad; Fahad, AhmadThis study explores the behavioural, ethical, social, and regulatory implications of AI bots that impersonate humans on social media platforms. As artificial intelligence becomes increasingly integrated into online communication, AI-driven bots are being deployed to mimic human users, influence opinions, and automate engagement. While these technologies offer efficiency, they also raise serious concerns about misinformation, manipulation, transparency, and digital trust. Using a structured online questionnaire distributed via platforms such as Twitter (X), LinkedIn, and WhatsApp, this research gathered responses from 57 participants. The survey examined user perceptions across multiple dimensions, including their confidence in identifying bots, behavioural changes due to bot exposure, ethical concerns, perceived political influence, and expectations for regulation and education. Findings indicate that while many users feel moderately confident in recognizing bots, they also express reduced trust and engagement when bots are suspected. Ethical concerns particularly around privacy and undisclosed AI interaction were prominent, and users widely supported stronger regulation, transparency tools, and public education initiatives. The study concludes that AI bots pose a significant challenge to online authenticity and democratic discourse and highlights the need for multi-stakeholder governance to ensure safe and ethical deployment of such technologies.3 0Item Restricted Stress Detection: Leveraging IoMT Data and Machine Learning for Enhanced Well-being(Saudi Digital Library, 2025) Alsharef, Moudy Sharaf; Alshareef, Moudywe focus on the detection of acute stress, characterized by short-term physiological changes such as changes in heart rate variability (HRV), breathing patterns, and other bodily functions. Often measurable through wearable or contactless sensors. Accurate detection of acute stress is crucial in high-pressure environments, such as clinical settings, to reduce cognitive overload, prevent burnout, and minimize errors. Current research on stress detection faces multiple challenges. First, most proposed methods are not designed to identify stress in unseen subjects, limiting their generalizability and practical applicability. Second, due to the sensitive nature of stress-related physiological data and the risk of data leakage, insufficient attention has been paid to ensuring data privacy while preserving utility. Third, many existing studies rely on synthetically induced stress in controlled environments, overlooking real-world scenarios where stress can have severe consequences. Finally, nearly all research in this domain employs invasive IoMT sensors or wearable devices, which may not be practical or scalable for real-world applications. This thesis presents five key contributions in the field of stress detection using Internet of Medical Things (IoMT) sensors and machine learning. First, it introduces a deep learning model based on self-attention (Transformer), trained and evaluated using the WESAD dataset, a widely used benchmark collected from 15 participants under controlled stress tasks. The model achieved 96% accuracy in detecting stress and was validated using leave-one-subject-out (LOSO) cross-validation to demonstrate generalizability to unseen individuals. Second, to ensure data privacy, a differential privacy framework was integrated into the model. This approach adds noise during training to prevent sensitive data leakage and achieved 93% accuracy, confirming it is both private and effective. Third, the thesis introduces a new dataset called PARFAIT, collected from 30 healthcare workers during real hospital duties (ICU, ER, OR) using non-invasive HRV sensors and the Maslach Burnout Inventory (MBI) to label stress levels. This dataset supports real-world analysis of stress among physicians. Fourth, a cost-sensitive model is developed using XGBoost and the PARFAIT dataset, assigning higher penalties to stress misclassifications that could lead to medical errors. This model achieved 98% accuracy and reduced false negatives, making it suitable for clinical settings. Finally, a contactless radar-based system is presented to detect stress using ultrawideband (UWB) radar, capturing HRV and breathing data. A deep learning model achieved 92.35% accuracy, offering a non-wearable, scalable alternative. Although the radar-based model achieved a slightly lower accuracy (92.35%) compared to the wearable-based model (96%), it provides several important advantages. It works with out any physical contact, helps maintain user privacy, and can be more practical to deploy in clinical settings where wearable sensors may not be suitable. The small drop in accuracy is mainly due to the limitations of radar in measuring HRV precisely. However, by combining radar-based HRV with breathing features, the overall performance remains competitive. 311 0Item Restricted Saudi teachers’ perception on working with learning disabilities pupils and their attitude regarding prospects for inclusive education: A qualitative study in Yanbu mainstream primary schools.(Saudi Digital Library, 2025) Aljohani, Abrar; Christopher, OstrowdunThe need to include students with learning disabilities (LDs) in mainstream classrooms (alongside peers without such disabilities) is manifested in many educational policies, set to address their unique needs. This study set in Yanbu, Saudi Arabia, aimed to explore the inclusion of children with LDs in mainstream primary schools, from teachers’ perspective. Semi-structured interviews with nine teachers (both general and special education teachers) were conducted to collect evidence. Thematic analysis of data helped extract five main themes: (1) inclusion as a challenging but rewarding experience, (2) inclusion practices in general classrooms, (3) students lagging and struggling socially, (4) school-related challenges slowing down progress and (5) holistic approach to improving inclusion. It was found that teachers are committed to inclusion, which they perceive as extremely beneficial. At the same time, they also recognise the need to provide additional support in resource rooms, which shows that there is still room for growth when it comes to meeting inclusion goals stated in Saudi educational policies. More research involving other stakeholders is needed to better understand the challenges of including students with LDs and paths towards their better integration in mainstream classrooms.1 0Item Restricted OPTIMISATION OF POLYMERIC NANOPARTICLES FOR BRAIN TUMOURS: A TRANSITION FROM CONVENTIONAL METHODS TO MICROFLUIDICS(Saudi Digital Library, 2025-03) Alasmari, Tariq Mohammed; McConville, ChristopherGlioblastoma multiforme (GBM) is one of the predominant causes of cancer-related mortality worldwide, affecting individuals across various age groups. The blood-brain barrier (BBB) is a substantial obstacle for chemotherapeutics, as it restricts their ability to penetrate the brain and complicates the management of GBM. Nanoparticles (NPs) offer a customisable, non-invasive approach to improve drug delivery to the brain. This thesis aimed to develop poly(lactide-co-glycolide) (PLGA) NPs with enhanced drug loading (DL) capacity for Irinotecan hydrochloride (IRN) and the scaling up of their production through microfluidics. These NPs can overcome the challenges associated with the BBB and improve therapeutic efficacy. Various IRN-PLGA NPs were produced using the single emulsion evaporation technique to enhance DL while keeping the particle size under 300 nm. The production of NP was scaled up via the microfluidics technique. The processing parameters for microfluidics were optimised using blank PLGA NPs, followed by incorporating IRN into the PLGA NPs. The Box-Behnken Design (BBD) of the experiment was conducted using the optimal microfluidics processing parameters to determine the optimal formulation conditions for achieving the smallest particle size, lowest zeta potential, and high encapsulation efficiency (EE) and DL. The influence of formulation variables, specifically PLGA, IRN, and polyvinyl alcohol (PVA), on the physicochemical properties of the NPs was assessed. The cytotoxicity, cellular uptake, and mechanisms of cell death were evaluated in GBM cells. The permeability of the NPs across the BBB model was assessed through transendothelial electrical resistance (TEER) measurements. The results indicated that the NPs generated by the traditional method (F7 NPs) exhibited an increase in DL to approximately 5% with a particle size of 292 nm. The variation of microfluidic parameters, which include flow rate ratio (FRR) and total flow rate (TFR), impacted the physicochemical properties of the blank PLGA NPs. The findings demonstrated that the optimal processing parameters for microfluidics were an FRR of 1:7 and a TFR of 8 ml. The loading study demonstrated that IRN was efficiently incorporated into the PLGA NPs at concentrations determined based on F7 NPs using optimal microfluidic conditions. The BBD determined the optimum formulation using independent variable values of 128.3 mg of PLGA (X1), 13.9 mg of IRN (X2), and 2.4% PVA (X3). This formulation yielded a particle size of 161.36 nm and a DL of 6% (MF13 NPs). The characterisations of the NPs produced by the conventional technique and microfluidics were comparable, except for particle size and DL. Microfluidics generated NPs with a smaller particle size and enhanced DL compared to those produced by the traditional method. The release of IRN from the PLGA matrix was affected by the pH of the release media, with a higher IRN release observed under acidic conditions. MF13 NPs exhibited enhanced cellular uptake, cytotoxicity, and permeability across the BBB model compared to F7 NPs due to their smaller particle size, which improved their biological interaction. Overall, MF13 NPs exhibit potential effectiveness in the treatment of GBM. Therefore, future in vivo studies are essential to further evaluate the biodistribution and therapeutic efficacy of MF13 NPs.10 0Item Restricted Identification, analysis and formulation of natural bio-organic molecules enhanced by nanoparticles for the potential treatment of amyloid disease(Saudi Digital Library, 2025) Alaziqi, Bakri; Middleton, DavidThe apparent health benefits of a Mediterranean diet have been attributed to the consumption of unprocessed extra virgin olive oil (EVOO), which contains a high content of polyphenols having antioxidant and anti-inflammatory properties. Phenolic compounds from a range of dietary sources have also been found to reduce the rate of protein self-assembly into amyloid fibrils associated with Alzheimer’s disease (AD) and other protein misfolding disorders. Amyloid fibrils are nanoscale fibrous structures formed by the self-assembly of certain proteins into repeating arrays of β-strands stabilized by intermolecular hydrogen bonds. Amyloid is associated with over 30 human diseases and can occur systemically or in localized areas such as around the brain as observed in Alzheimer’s disease. AD is associated with the assembly of amyloid-β (Aβ) peptides into β-sheet rich amyloid fibrils and the aggregation of microtubule-associated protein tau into neurofibrillary tangles in the brain. There is a clinical need to find a cure for the disease, or a treatment option which improves the quality of life for patients with Alzheimer’s disease. The phenolic compounds oleuropein and oleocanthal from extra virgin olive oil (EVOO) have previously been shown to individually reduce the accumulation of amyloid fibrils associated with Alzheimer’s disease (AD), either by inhibiting amyloid formation (oleuropein) or by promoting amyloid clearance (oleocanthal). EVOO contains many other compounds, but as to date, no such evaluation of EVOO phenol mixtures when isolated from the fatty acid component of olive oil has been reported. This thesis aims to examine mixed and individual polyphenols isolated from olive oil and explore their ability to modulate amyloid formation by Aβ and tau. Chapter 1 focuses on the current literature around natural phenolic compounds derived from EVOO. Also, this chapter discusses the literature around amyloid diseases with a particular focus on Alzheimer’s disease including its pathologies and overview of pharmacological and non-pharmacological treatment approaches of AD. Chapter 2 discusses the main techniques used for analysis and characterisation of polyphenols found in natural products. Also, this chapter illustrates techniques used for investigation and analysis of amyloid β (proteins). Chapter 3 shows preparation and implementation of a methodology for the expression, purification and characterisation of labelled (15N) and unlabelled, amyloid proteins. In Chapter 4, different methods of extraction of phenols from EVOO are evaluated to optimise the yield and range of phenols obtained in the extracted mixture. Mixtures are extracted from Greek and Saudi Arabian EVOO and analysed in detail using chromatographic and magnetic resonance methods. Over 30 different compounds are identified, several of which are quantified and shown to be present in different concentrations in the two EVOO extracts. Chapter 5 describes a range of methods that are used to test the effects of the phenolic mixtures in vitro on the aggregation of the 40-amino acid Aβ40 peptide and a repeat-domain fragment of tau. Thioflavin T fluorescence and circular dichroism measurements show that the Greek extract reduces the rate of tau aggregation only at very high phenolic concentrations (> 100 µg/mL). By comparison, Greek and Saudi extracts exert similar effects on Aβ40 aggregation at much lower concentrations (< 20 µg/mL). Transmission electron microscopy (TEM) indicates that the extracts reduce fibril deposition of Aβ40 after the end-point of aggregation is reached. An HPLC procedure combined with TEM, dynamic light scattering, and solid-state NMR reveals that most compounds in the extracts bind to pre-formed Aβ40 fibrils, which generates soluble Aβ oligomers that are mildly toxic to SH-SY5Y cells. Much higher (500 µg/mL) extract concentrations are required to remodel tau filaments into oligomers and no binding of phenolic compounds to the pre-formed filaments is observed. It is concluded that the entire phenolic profiles of different EVOO samples are similarly capable of modulating Aβ40 aggregation and fibril morphology in vitro at relatively low concentrations but are much less efficient at modulating tau aggregation. Chapter 6 describes the synthesis and characterization of solid lipid nanoparticles (SLNs) with the aim of enhancing the in vivo delivery of polyphenol mixtures in the treatment of amyloid diseases and other pathologies. The method was used to successfully prepare SLNs having a homogeneous size distribution and a high efficiency of polyphenol encapsulation from the mixtures prepared in Chapter 4. Animal experiments are being investigated in future work to increase absorption, bioavailability, and circulation times of EVOO polyphenols in vivo. It is estimated that around 3 M tonnes of olive oil are consumed worldwide annually. The results described in this thesis have increased understanding of the potentially neuroprotective benefits of EVOO consumed in the Mediterranean diet and laid the foundations for future in vivo applications of EVOO polyphenol mixtures for disease testing.15 0Item Restricted PHENOTYPING RIGHT VENTRICULAR STRUCTURE AND FUNCTION USING ECHOCARDIOGRAPHY AND CARDIAC MAGNETIC RESONANCE IN ARRHYTHMOGENIC RIGHT VENTRICULAR CARDIOMYOPATHY(Saudi Digital Library, 2025) Aljehani, Areej; Rick, SteedsArrhythmogenic right ventricular cardiomyopathy ARVC) is a rare inherited disease characterised by an increased risk of ventricular arrhythmias and sudden cardiac death often presenting before structural changes are apparent. Early detection and risk stratification for major adverse cardiac events are crucial to improving patient outcomes. However, limited data exist on identifying patients at high risk for MACE. This thesis aimed to comprehensively characterise, over time, a cohort of ARVC patients from a large tertiary university centre, with a focus on advanced cardiovascular imaging findings. It encompassed both retrospective and prospective studies across different disease stages of ARVC. We identified significant differences between definite and early stages of ARVC, with structural progression strongly associated with an increased risk of MACE. Notably, advanced imaging techniques, particularly strain imaging, demonstrated superior performance in detecting structural abnormalities and predicting MACE compared to conventional imaging parameters. Exercise-derived strain imaging showed superior diagnostic value compared to conventional resting measures. These findings highlight the importance of incorporating advanced imaging tools into the routine assessment and risk stratification of ARVC patients to enable early intervention and improve long-term outcomes.36 0