Search Results (430)

Background/Objectives: Fat and inflammation confound current magnetic resonance imaging (MRI) methods for assessing fibrosis in liver disease. Sodium or amide proton transfer-weighted MRI methods may be more specific for assessing liver fibrosis. The purpose of this study was to determine the feasibility of sodium and amide proton transfer-weighted MRI in individuals with liver disease and to determine if either method correlated with clinical markers of fibrosis. Methods: T₁ and T₂ relaxation maps, proton density fat fraction maps, liver shear stiffness maps, amide proton transfer-weighted (APTw) images, and sodium images were acquired at 3T. Image data were extracted from regions of interest placed in the liver. ANOVA tests were run with disease status, age, and body mass index as independent factors; significance was set to p < 0.05. Post-hoc t-tests were run when the ANOVA showed significance. Results: A total of 36 participants were enrolled, 34 of whom were included in the final APTw analysis and 24 in the sodium analysis. Estimated liver tissue sodium concentration differentiated participants with liver disease from those without, whereas amide proton transfer-weighted MRI did not. Estimated liver tissue sodium concentration negatively correlated with the Fibrosis-4 score, but amide proton transfer-weighted MRI did not correlate with any clinical marker of disease. Conclusions: Amide proton-weighted imaging was not different between groups. Estimated liver tissue sodium concentrations did differ between groups but did not provide additional information over conventional methods. Full article

Arrhythmogenic cardiomyopathies (ACMs) are a phenotypically and etiologically heterogeneous group of myocardial disorders characterized by fibrotic or fibro-fatty replacement of ventricular myocardium, electrical instability, and an elevated risk of sudden cardiac death. Initially identified as a right ventricular disease, ACMs are now recognized to include biventricular and left-dominant forms. Genetic causes account for a substantial proportion of cases and include desmosomal variants, non-desmosomal variants, and familial gene-elusive forms with no identifiable pathogenic mutation. Nongenetic etiologies, including post-inflammatory, autoimmune, and infiltrative mechanisms, may mimic the phenotype. In many patients, the disease remains idiopathic despite comprehensive evaluation. Cardiac magnetic resonance imaging has emerged as a key tool for identifying non-ischemic scar patterns and for distinguishing arrhythmogenic phenotypes from other cardiomyopathies. Emerging classifications propose the unifying concept of scarring cardiomyopathies based on shared structural substrates, although global consensus is evolving. Risk stratification remains challenging, particularly in patients without overt systolic dysfunction or identifiable genetic markers. Advances in tissue phenotyping, multi-omics, and artificial intelligence hold promise for improved prognostic assessment and individualized therapy. Full article

Background: Congenital anosmia (CA) is a rare condition characterized by a lifelong inability to perceive odors, which significantly affects daily life and may be linked to broader neurodevelopmental alterations. This study aimed to investigate structural brain differences in patients with CA using MRI, focusing on gray matter (GM) and white matter (WM) changes and their implications for neurodevelopment. Methods: This retrospective study included 28 patients with CA and 28 age- and gender-matched healthy controls. Patients with CA were diagnosed at a single medical center between 1 January 2001 and 30 August 2024. Controls were randomly selected from an imaging database and had no history of olfactory dysfunction. Brain Magnetic Resonance Imaging (MRI)was analyzed using volumetric analysis in SPM12.GM and WM volumes were quantified across 11 anatomical brain regions based on theWFU_PickAtlas toolbox, including frontal, temporal, parietal, occipital, limbic, sub-lobar, cerebellum (anterior/posterior), midbrain, the pons, and the frontal–temporal junction. Left–right hemispheric comparisons were also conducted. Results: Patients with CA exhibited significantly smaller GM volumes compared to healthy controls (560.6 ± 114.7 cc vs. 693.7 ± 96.3 cc, p < 0.001) but larger WM volumes (554.2 ± 75.4 cc vs. 491.1 ± 79.7 cc, p = 0.015). Regionally, GM reductions were observed in the frontal (131.9 ± 33.7 cc vs. 173.7 ± 27.0 cc, p < 0.001), temporal (81.1 ± 18.4 cc vs. 96.5 ± 14.1 cc, p = 0.001), parietal (52.4 ± 15.2 cc vs. 77.2 ± 12.4 cc, p < 0.001), sub-lobar (57.8 ± 9.7 cc vs. 68.2 ± 10.2 cc, p = 0.001), occipital (39.1 ± 13.0 cc vs. 57.8 ± 8.9 cc, p < 0.001), and midbrain (2.0 ± 0.5 cc vs. 2.3 ± 0.4 cc, p = 0.006) regions. Meanwhile, WM increases were notable in the frontal(152.0 ± 19.9 cc vs. 139.2 ± 24.0 cc, p = 0.027), temporal (71.5 ± 11.5 cc vs. 60.8 ± 9.5 cc, p = 0.001), parietal (75.8 ± 12.4 cc vs. 61.9 ± 11.5 cc, p < 0.001), and occipital (58.7 ± 10.3 cc vs. 41.9 ± 7.9 cc, p < 0.001) lobes. A separate analysis of the left and right hemispheres revealed similar patterns of reduced GM and increased WM volumes in patients with CA across both sides. An exception was noted in the right cerebellum-posterior, where patients with CA showed significantly greater WM volume (5.625 ± 1.667 cc vs. 4.666 ± 1.583 cc, p = 0.026). Conclusions: This study demonstrates widespread structural brain differences in individuals with CA, including reduced GM and increased WM volumes across multiple cortical and sub-lobar regions. These findings suggest that congenital olfactory deprivation may impact brain maturation beyond primary olfactory pathways, potentially reflecting altered synaptic pruning and increased myelination during early neurodevelopment. The involvement of the cerebellum further implies potential adaptations beyond motor functions. These structural differences may serve as potential neuroimaging markers for monitoring CA-associated cognitive or emotional comorbidities. Full article

Background: Vascular risk factors (VRFs) are known to influence cerebral small vessel disease (cSVD) burden and progression. However, their specific impact on the presence and distribution of each cSVD imaging marker (white matter hyperintensity [WMH], perivascular spaces [PVSs], lacunes, and cerebral microbleeds [CMBs]) and their spatial distribution remains unclear. Methods: We conducted a retrospective analysis of 93 patients with lacunar stroke with a standardized investigational magnetic resonance imaging protocol using a 3T scanner. WMH and PVSs were segmented semi-automatically, and lacunes and CMBs were manually segmented. We assessed the univariable associations of four common VRFs (hypertension, hyperlipidemia, diabetes, and smoking) with the load of each cSVD marker. Then, we assessed the independent associations of these VRFs in multivariable regression models adjusted for age and sex. Spatial lesion patterns were explored with regional volumetric comparisons using Pearson’s coefficient analysis, which was adjusted for multiple comparisons, and by visually examining heatmap lesion distributions. Results: Hypertension was the VRF that exhibited stronger associations with the cSVD markers in the univariable analysis. In the multivariable analysis, only lacunes (p = 0.009) and PVSs in the basal ganglia (p = 0.014) and white matter (p = 0.016) were still associated with hypertension. In the regional analysis, hypertension showed a higher WMH load in deep structures and white matter, particularly in the posterior periventricular regions. In patients with hyperlipidemia, WMH was preferentially found in hippocampal regions. Conclusions: Hypertension was confirmed to be the VRF with the most impact on cSVD load, especially for lacunes and PVSs, while the lesion topography was variable for each VRF. These findings shed light on the complexity of cSVD expression in relation to factors detrimental to vascular health. Full article

Background/Objectives: Digital food-related videos significantly influence cravings, appetite, and weight outcomes; however, the dynamic neural mechanisms underlying appetite fluctuations during naturalistic viewing remain unclear. This study aimed to identify neural activity patterns associated with moment-to-moment appetite changes during naturalistic food-cue video viewing and to examine their relationships with cravings and weight-related outcomes. Methods: Functional magnetic resonance imaging (fMRI) data were collected from 58 healthy female participants as they viewed naturalistic food-cue videos. Participants concurrently provided continuous ratings of their appetite levels throughout video viewing. Hidden Markov Modeling (HMM), combined with machine learning regression techniques, was employed to identify distinct neural states reflecting dynamic appetite fluctuations. Findings were independently validated using a shorter-duration food-cue video viewing task. Results: Distinct neural states characterized by heightened activation in default mode and frontoparietal networks consistently corresponded with increases in appetite ratings. Importantly, the higher expression of these appetite-related neural states correlated positively with participants’ Body Mass Index (BMI) and post-viewing food cravings. Furthermore, these neural states mediated the relationship between BMI and food craving levels. Longitudinal analyses revealed that the expression levels of appetite-related neural states predicted participants’ BMI trajectories over a subsequent six-month period. Participants experiencing BMI increases exhibited a significantly greater expression of these neural states compared to those whose BMI remained stable. Conclusions: Our findings elucidate how digital food cues dynamically modulate neural processes associated with appetite. These neural markers may serve as early indicators of obesity risk, offering valuable insights into the psychological and neurobiological mechanisms linking everyday media exposure to food cravings and weight management. Full article

Background/Objectives: Gut-derived tryptophan (Trp) metabolites play important roles in metabolic and cardiovascular regulation. Although animal studies suggest their protective effects against metabolic dysfunction, data in adolescents, particularly those with obesity, remain limited. The objective of this study was to evaluate associations between circulating gut-derived Trp metabolites and markers of cardiometabolic, vascular, and platelet health in adolescents with obesity. Methods: Data were analyzed from 28 adolescents (ages 13–18; mean BMI = 36 ± 6.4 kg/m²). Fasting blood was collected to assess lipid profiles using a clinical analyzer and insulin resistance using the homeostatic model assessment for insulin resistance (HOMA-IR). Gut-derived Trp metabolites were measured by UPLC–mass spectrometry, peak oxygen uptake (VO_{2 peak}) by gas exchange during an incremental cycle ergometer test, and body composition by dual-energy X-ray absorptiometry. Platelet spare respiratory capacity (SRC), endothelial function, and liver fat were measured using high-resolution respirometry, flow-mediated dilation (FMD) of the brachial artery, and magnetic resonance imaging respectively. Results: Indole-3-propionic acid was inversely associated with diastolic blood pressure (rho = −0.39, p = 0.047), total cholesterol (rho = −0.55, p = 0.002), and LDL-C (rho = −0.57, p = 0.0014), independent of sex and obesity severity. Indoxyl sulfate was positively correlated with fasting glucose (rho = 0.47, p = 0.012), and adolescents with impaired fasting glucose had 1.6-fold higher IS levels. Indole-3-acetaldehyde declined with age (rho = −0.50, p = 0.007), and Indole-3-acetic acid and indole were higher in Hispanics vs. non-Hispanics. No significant associations were observed between Trp metabolites and FMD, VO₂ peak, or SRC. Conclusions: Gut-derived Trp metabolites, particularly indole-3-propionic and indoxyl sulfate, are associated with markers of cardiometabolic risk in adolescents with obesity. These findings support their potential relevance in early-onset cardiovascular disease risk. Full article

Background: Secukinumab is a fully human monoclonal antibody that targets interleukin (IL)-17A and is used to treat axial spondyloarthritis (axSpA) and psoriatic arthritis (PsA). Treating axSpA and PsA can be challenging in patients with comorbidities. In this multicenter retrospective study, we aimed to evaluate the efficacy and safety of secukinumab treatment in patients with axSpA and PsA who had a history of tuberculosis, multiple sclerosis (MS), or congestive heart failure (CHF). Methods: The study included 44 patients with a diagnosis of axSpA and PsA and a history of tuberculosis, MS, or CHF who received secukinumab treatment at 13 centers in our country. Erythrocyte sedimentation rate, C-reactive protein (CRP), Bath Ankylosing Spondylitis Disease Activity Index, Ankylosing Spondylitis Disease Activity Score CRP, visual analog scale, and Disease Activity Score-28 CRP markers at months 0, 3, and 12 of secukinumab treatment were analyzed. Alongside this, tuberculosis, MS, and CHF were evaluated at follow-up using clinical assessments and imaging methods such as chest radiographs, brain magnetic resonance, and echocardiography. Results: A statistically significant improvement in inflammatory markers and disease activity scores was observed in patients treated with secukinumab. There was no reactivation in patients with a history of tuberculosis. In most MS patients, the disease was stable, while clinical and radiological improvement was observed in one patient. No worsening of CHF stage was observed in patients with a history of CHF. Conclusions: With regular clinical monitoring, secukinumab may be an effective and safe treatment option for axSpA and PsA patients with a history of tuberculosis, MS, or CHF. Full article

A young adult patient presented to the gastrointestinal outpatient department with a suspected hepatic tumor. The patient was in a traffic accident ten years ago and underwent splenectomy and distal pancreatectomy at another medical institution. The physical examination was unremarkable. The liver function tests and tumor markers were within normal limits, with the alpha-fetoprotein level at 1.38 ng/mL. Both hepatitis B surface antigen and anti-HCV were negative. Based on the clinical history, intrahepatic splenosis was suspected first. Dynamic computed tomography revealed a 2.3 cm lesion exhibiting suspicious early wash-in and early wash-out enhancement patterns. As previous studies have reported, this finding makes hepatocellular carcinoma and metastatic lesions the major differential diagnoses. For further evaluation, dynamic magnetic resonance imaging was performed, and similar enhancing features were observed, along with restricted diffusion. As hepatocellular carcinoma still could not be confidently ruled out, the patient underwent an ultrasound-guided biopsy. The diagnosis of intrahepatic splenosis was confirmed by the pathologic examination. Intrahepatic splenosis is a rare condition defined as an acquired autoimplantation of splenic tissue within the hepatic parenchyma. Diagnosis can be challenging due to its ability to mimic liver tumors in imaging studies. Therefore, in patients with a history of splenic trauma and/or splenectomy, a high index of suspicion and awareness is crucial for accurate diagnosis and for prevention of unnecessary surgeries or interventions. Full article

Background and Objectives: Non-invasive imaging biomarkers for the early detection of chronic kidney allograft injury are needed to improve long-term transplant outcomes. T1 mapping by magnetic resonance imaging (MRI) has emerged as a promising method to assess renal structure and function. This study aimed to determine the potential of MRI as a diagnostic tool for evaluating graft function and structural changes in kidney grafts 1 year after transplantation. Materials and Methods: Thirty-four kidney transplant recipients were prospectively recruited, with 27 completing the follow-up at one year. Renal MRI at 3T was performed to acquire T1, T2, and apparent diffusion coefficient (ADC) maps. Clinical parameters, including estimated glomerular filtration rate (eGFR), albumin-to-creatinine ratio (ACR), protein-to-creatinine ratio (PCR), and histological IF/TA scores, were collected. MRI parameters were compared across the groups stratified by clinical and histological markers. Diagnostic accuracy was assessed using receiver operating characteristic (ROC) analysis. Results: At 1 year, T1 corticomedullary differentiation (CMD) values were significantly higher in patients with elevated ACR (≥3 mg/mmol), PCR (≥15 mg/mmol), and mild to moderate or severe IF/TA, reflecting a reduction in the corticomedullary gradient. T1 CMD demonstrated moderate-to-good diagnostic performance in detecting ACR (AUC 0.791), PCR (AUC 0.730), and IF/TA (AUC 0.839). No significant differences were observed in T2 or ADC values across these groups. T1 CMD also showed a significant positive correlation with ACR but not with eGFR, suggesting a closer association with structural rather than functional deterioration. Conclusions: T1 mapping, particularly T1 CMD, shows promise as a non-invasive imaging biomarker for detecting chronic allograft injury and monitoring renal function 1 year after kidney transplantation. Full article

Background/Objectives: Early and accurate prediction of stroke severity is crucial for optimizing guided therapeutic decisions and improving outcomes. This study investigates the predictive value of lesion size and functional connectivity for neurological deficits, assessed by the National Institutes of Health Stroke Scale (NIHSS score), in patients with acute or subacute subcortical ischemic stroke. Methods: Forty-four patients (mean age: 68.11 years, 23 male, and admission NIHSS score 4.30 points) underwent high-resolution anatomical and resting-state functional Magnetic Resonance Imaging (rs-fMRI) within seven days of stroke onset. Lesion size was volumetrically quantified, while functional connectivity within the motor, default mode, and frontoparietal networks was analyzed using seed-based correlation methods. Multiple linear regression and cross-validation were applied to develop predictive models for stroke severity. Results: Our results showed that lesion size explained 48% of the variance in NIHSS scores (R² = 0.48, cross-validated R² = 0.49). Functional connectivity metrics alone were less predictive but enhanced model performance when combined with lesion size (achieving an R² = 0.71, cross-validated R² = 0.73). Additionally, left hemisphere connectivity features were particularly informative, as models based on left-hemispheric connectivity outperformed those using right-hemispheric or bilateral predictors. This suggests that the inclusion of contralateral hemisphere data did not enhance, and in some configurations, slightly reduced, model performance—potentially due to lateralized functional organization and lesion distribution in our cohort. Conclusions: The findings highlight lesion size as a reliable early marker of stroke severity and underscore the complementary value of functional connectivity analysis. Integrating rs-fMRI into clinical stroke imaging protocols offers a potential approach for refining prognostic models. Future research efforts should prioritize establishing this approach in larger cohorts and analyzing additional biomarkers to improve predictive models, advancing personalized therapeutic strategies for stroke management. Full article

Nuclear Magnetic Resonance (NMR) and Magnetic Resonance Imaging (MRI) are powerful techniques that have been employed to analyze foodstuffs comprehensively. These techniques offer in-depth information about the chemical composition, structure, and spatial distribution of components in a variety of food products. Quantitative NMR is widely applied for precise quantification of metabolites, authentication of food products, and monitoring of food quality. Low-field ¹H-NMR relaxometry is an important technique for investigating the most abundant components of intact foodstuffs based on relaxation times and amplitude of the NMR signals. In particular, information on water compartments, diffusion, and movement can be obtained by detecting proton signals because of H₂O in foodstuffs. Saffron adulterations with calendula, safflower, turmeric, sandalwood, and tartrazine have been analyzed using benchtop NMR, an alternative to the high-field NMR approach. The fraudulent addition of Robusta to Arabica coffee was investigated by ¹H-NMR Spectroscopy and the marker of Robusta coffee can be detected in the ¹H-NMR spectrum. MRI images can be a reliable tool for appreciating morphological differences in vegetables and fruits. In kiwifruit, the effects of water loss and the states of water were investigated using MRI. It provides informative images regarding the spin density distribution of water molecules and the relationship between water and cellular tissues. ¹H-NMR spectra of aqueous extract of kiwifruits affected by elephantiasis show a higher number of small oligosaccharides than healthy fruits do. One of the frauds that has been detected in the olive oil sector reflects the addition of hazelnut oils to olive oils. However, using the NMR methodology, it is possible to distinguish the two types of oils, since, in hazelnut oils, linolenic fatty chains and squalene are absent, which is also indicated by the ¹H-NMR spectrum. NMR has been applied to detect milk adulterations, such as bovine milk being spiked with known levels of whey, urea, synthetic urine, and synthetic milk. In particular, T2 relaxation time has been found to be significantly affected by adulteration as it increases with adulterant percentage. The ¹H spectrum of honey samples from two botanical species shows the presence of signals due to the specific markers of two botanical species. NMR generates large datasets due to the complexity of food matrices and, to deal with this, chemometrics (multivariate analysis) can be applied to monitor the changes in the constituents of foodstuffs, assess the self-life, and determine the effects of storage conditions. Multivariate analysis could help in managing and interpreting complex NMR data by reducing dimensionality and identifying patterns. NMR spectroscopy followed by multivariate analysis can be channelized for evaluating the nutritional profile of food products by quantifying vitamins, sugars, fatty acids, amino acids, and other nutrients. In this review, we summarize the importance of NMR spectroscopy in chemical profiling and quality assessment of food products employing magnetic resonance technologies and multivariate statistical analysis. Full article

The risk of developing symptomatic knee osteoarthritis (KOA) during a lifetime, i.e., pain, aching, or stiffness in a joint associated with radiographic KOA, was estimated in 2008 to be around 40% in men and 47% in women. The clinical and scientific communities lack an efficient diagnostic method to effectively monitor, evaluate, and predict the evolution of KOA before and during the therapeutic protocol. In this review, we summarize the main methods that are used or seem promising for the diagnosis of osteoarthritis, with a specific focus on non- or low-invasive methods. As standard diagnostic tools, arthroscopy, magnetic resonance imaging (MRI), and X-ray radiography provide spatial and direct visualization of the joint. However, discrepancies between findings and patient feelings often occur, indicating a lack of correlation between current imaging methods and clinical symptoms. Alternative strategies are in development, including the analysis of biochemical markers or acoustic emission recordings. These methods have undergone deep development and propose, with non- or minimally invasive procedures, to obtain data on tissue condition. However, they present some drawbacks, such as possible interference or the lack of direct visualization of the tissue. Other original methods show strong potential in the field of KOA monitoring, such as electrical bioimpedance or near-infrared spectrometry. These methods could permit us to obtain cheap, portable, and non-invasive data on joint tissue health, while they still need strong implementation to be validated. Also, the use of Artificial Intelligence (AI) in the diagnosis seems essential to effectively develop and validate predictive models for KOA evolution, provided that a large and robust database is available. This would offer a powerful tool for researchers and clinicians to improve therapeutic strategies while permitting an anticipated adaptation of the clinical protocols, moving toward reliable and personalized medicine. Full article

Hemolytic uremic syndrome (HUS), a thrombotic microangiopathy primarily affecting the kidneys, can also involve the central nervous system (CNS), often leading to significant morbidity and mortality. Neurologic manifestations are among the most severe extra-renal complications, particularly in children and during outbreaks of Shiga toxin-producing Escherichia coli (STEC)-associated HUS (typical (tHUS)). This review explores the clinical spectrum, pathophysiology, diagnostic workup, and age-specific outcomes of neurologic involvement in both typical (tHUS) and atypical (aHUS). Neurologic complications occur in up to 11% of pediatric and over 40% of adult STEC-HUS cases in outbreak settings. Presentations include seizures, encephalopathy, focal deficits, movement disorders, and posterior reversible encephalopathy syndrome (PRES). Magnetic resonance imaging (MRI) commonly reveals basal ganglia or parieto-occipital lesions, though subtle or delayed findings may occur. Laboratory workup typically confirms microangiopathic hemolytic anemia (MAHA), thrombocytopenia, and kidney damage, with additional markers of inflammation or metabolic dysregulation. Eculizumab is the first-line treatment for aHUS with CNS involvement, while its utility in STEC-HUS remains uncertain. Although many children recover fully, those with early CNS involvement are at greater risk of developing epilepsy, cognitive delays, or fine motor deficits. Adults may experience lingering neurocognitive symptoms despite apparent clinical recovery. Differences in presentation and imaging findings between age groups emphasize the need for tailored diagnostic and therapeutic strategies. Comprehensive neurorehabilitation and long-term follow-up are crucial for identifying residual deficits. Continued research into predictive biomarkers, neuroprotective interventions, and standardized treatment protocols is needed for improving outcomes in HUS patients with neurological complications. Full article

Prognostication of neurodevelopmental outcomes for neonates with hypoxic–ischemic encephalopathy (HIE) is primarily reliant on structural assessment using conventional brain magnetic resonance imaging in the clinical setting. Diffuse optical tomography (DOT) can provide complementary information on brain function at the bedside, further enhancing prognostic accuracy. The predictive accuracy and generalizability of DOT-based neuroimaging markers are unknown. This study aims to test the feasibility of prospectively recruiting and retaining neonates for 12 months in a larger study that investigates the prognostic utility of DOT-based biomarkers of HIE. The study will recruit 25 neonates with HIE over one year and follow them beyond NICU discharge at 6 and 12 months of age. Study subjects will undergo resting-state DOT measurement within 7 days of life for a 30–45-min period without sedation. A customized neonatal cap with 10 sources and eight detectors per side will be used to quantify cortical functional connectivity and to generate brain networks using MATLAB-based software (version 24.2). The Ages and Stages Questionnaires—3rd edition will be used for standardized developmental assessments at follow-up. This feasibility study will help refine the design and sample-size calculation for an adequately powered larger study that determines the clinical utility of DOT-based neuroimaging in perinatal brain injury. Full article

Tricuspid regurgitation (TR) represents a significant, often silently progressing, valvular heart disease with historically suboptimal management due to perceived high surgical risks. Transcatheter tricuspid valve interventions (TTVI) offer a promising, less invasive therapeutic avenue. Central to the success of TTVI is Right Ventricular Reverse Remodelling (RVRR), defined as an improvement in RV structure and function, which strongly correlates with enhanced patient survival. The right ventricle (RV) undergoes complex multi-scale biomechanical maladaptations, progressing from adaptive concentric to maladaptive eccentric hypertrophy, coupled with increased stiffness and fibrosis. Molecular drivers of this pathology include early failure of antioxidant defenses, metabolic shifts towards glycolysis, and dysregulation of microRNAs. Accurate RV function assessment necessitates advanced imaging modalities like 3D echocardiography, Cardiac Magnetic Resonance Imaging (CMR), and Computed Tomography (CT), along with strain analysis. Following TTVI, RVRR typically manifests as a biphasic reduction in RV volume overload, improved myocardial strain, and enhanced RV-pulmonary arterial coupling. Emerging molecular biomarkers alongside advanced imaging-derived biomechanical markers like CT-based 3D-TAPSE and RV longitudinal strain, are proving valuable. Artificial intelligence (AI) and machine learning (ML) are transforming prognostication by integrating diverse clinical, laboratory, and multi-modal imaging data, enabling unprecedented precision in risk stratification and optimizing TTVI strategies. Full article