Imaging Modalities Research Articles

General practitioners (GPs) in the Republic of Ireland have historically faced limited access to diagnostic imaging. A new national initiative allowing GPs to refer patients to private providers for imaging studies may alter referral patterns and improve patient care. This exploratory study aimed to evaluate the perceived impact of expanded GP access to diagnostic imaging on referral patterns and patient care quality in Irish primary care. A cross-sectional analysis was conducted of 620 diagnostic imaging referrals from 45 GP clinics across all Community Health Organization (CHO) regions, spanning June 2021 to August 2022. Data included imaging modalities (X-ray, DEXA, CT, MRI), referral frequencies to emergency departments (EDs), acute medical units (AMUs), outpatient clinics, and GP perceptions of care quality. GPs also provided retrospective assessments of how they would have managed each case prior to the initiative. ED and AMU referrals decreased by 89%, while outpatient clinic referrals declined by 53%. Concurrently, management of cases within GP settings rose substantially. In total, 91% of participating GPs reported improved patient care quality, citing more timely and accessible imaging as a key factor. Despite the study's exploratory design and reliance on retrospective GP assessments, these findings suggest that broadening GP access to diagnostic imaging may reduce hospital-based referrals and enhance patient care. Ongoing monitoring and further research are recommended to confirm the long-term impacts and sustainability of this initiative.

Hepatic artery pseudoaneurysms (HAP) and hepatic haemangiomas (HH) may present with indistinguishable imaging characteristics, particularly when clinical history favors one diagnosis over the other. Primary imaging alone may be insufficient for definitive differentiation. This case highlights the importance of further non-invasive imaging modalities in avoiding unnecessary invasive procedures if clinical condition allows. A 55-year-old patient presented with abdominal trauma after a fall. Computed tomography (CT) revealed a grade III liver laceration with a hyper vascular lesion near the right hepatic artery, initially suspected to be a HAP. Trans-arterial embolization (TAE) was planned, and selective catheterization was performed. However, angiography showed no pseudoaneurysm filling but rather features suggestive of a haemangioma, leading to the abortion of the procedure. Subsequent magnetic resonance imaging (MRI) confirmed a flash-filling HH. The patient remained stable, with no haemorrhagic complications or need for further intervention. In emergencies, recognizing imaging features distinguishing haemangiomas from pseudoaneurysms is crucial to avoid unnecessary invasive procedures, especially in stable patients, using accurate non-invasive tools like CT or MRI.

Approximately 20-50% of patients develop biochemical recurrence (BCR) of prostate cancer within 10 years following radical prostatectomy (RP). The accurate identification of recurrent disease is crucial for guiding salvage treatment decisions. While multiparametric MRI (mpMRI) and prostate-specific membrane antigen positron emission tomography/computed tomography (PSMA PET/CT) are both utilized for detecting local recurrence, their combined diagnostic benefits remain unclear. This study seeks to evaluate the diagnostic performance of both modalities alone and in conjunction for detecting local recurrence following RP in patients with BCR. A retrospective single-institution analysis included 37 post-RP patients with BCR who received mpMRI and PSMA PET/CT. Five board-certified radiologists reviewed images in three phases: mpMRI only, PSMA PET/CT only, and both modalities combined. Multidisciplinary tumor board consensus served as the reference standard. Diagnostic performance, inter-reader agreement, and radiologist confidence with each modality was examined. MpMRI outperformed PSMA PET/CT, yielding a higher sensitivity (73.0% vs. 65.2%) and specificity (77.1% vs. 75.7%). Interpretation of mpMRI and PSMA PET/CT together achieved the highest diagnostic accuracy (77.8%), representing a statistically-significant increase over PSMA PET/CT (p = 0.026) but a non-statistically-significant increase over mpMRI (p = 0.441). Combined imaging also resulted in greater specificity (90.0%) and inter-rater reliability (κ = 0.622). However, in some cases performance decreased with both modalities due to interpretive pitfalls. While mpMRI remains the preferred imaging modality for post-RP local recurrence surveillance, the integration of PSMA PET/CT may lead to improved specificity and inter-rater reliability. However, radiologists must understand each modality's limitations to avoid interpretive pitfalls.

Induction chemotherapy (ICT) followed by concurrent chemoradiotherapy is a standard of care in locoregionally advanced nasopharyngeal carcinoma (LA-NPC). However, there is a lack of consensus on appropriate radiotherapy (RT) target volumes and prescriptions after ICT. We systematically reviewed the literature to inform a planned international consensus guideline development. A scoping review was done to define the areas of significant practice differences, followed by a systematic review. The reviews were conducted by a Steering Committee (SC) and an Evidence Review Committee (ERC) consisting of radiation oncologists with expertise in treating NPC. The scoping review revealed significant practice differences on (1) optimal timing for post-ICT RT, (2) ideal imaging modalities for RT target delineation, (3) RT dose prescription and fractionation, and (4) RT target volume delineation. The systematic review found no specific recommendations on optimal timing for post-ICT RT and optimal imaging modalities. Regarding dose prescription, current guidelines advocate including two or three dose levels. Differences in post-induction target volume delineation were found. The data show that volume reduction may be possible without compromising oncologic outcomes and may improve quality of life. There is a lack of evidence and guidelines on post-ICT RT timing and optimal imaging modalities. Guidelines on post-ICT target volumes and dose levels differ significantly; published evidence from clinical trials is limited. Considering this lack of consensus after ICT in LA-NPC, international consensus guidelines among experts from endemic regions are needed and may help harmonize practices.

Dual-layer spectral detector CT (DLCT) represents an advanced and emerging modality in CT imaging, offering multiparametric images that enhance the quantitative assessment of pancreatic diseases. Non-hypervascular non-functional pancreatic neuroendocrine neoplasms (NF-pNENs) and solid pseudopapillary neoplasms (SPNs) frequently exhibit overlapping clinical and imaging features, complicating their differentiation. This study aimed to investigate the valuable quantitative parameters of DLCT in preoperative differentiation between non-hypervascular NF-pNEN and SPN, as well as to analyze their diagnostic performance. This retrospective study included 52 patients with pathologically confirmed non-hypervascular NF-pNENs and SPNs who underwent DLCT examination before surgery between June 2019 and September 2025. To differentiate between non-hypervascular NF-pNENs and SPNs, independent relevant clinical-radiological features and quantitative parameters were identified using the Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis and multivariate logistic regression analysis. The diagnostic performances of independent variables were assessed through receiver operating characteristic curves. There were 34 patients with non-hypervascular NF-pNENs (46.7 ± 10.2 years, 19 females) and 18 patients with SPNs (32.8 ± 7.9 years, 14 females). Clinical, radiological features and parameters were evaluated with near-perfect agreements among two radiologists. Age and normalised iodine concentration of lesion in the arterial phase (nICa) were the independent factors for differentiating between non-hypervascular NF-pNENs and SPNs in multivariate logistic regression analysis. The areas under the receiver operating characteristic curves (AUCs) for age, nCTa and nICa in tumour differentiation were 0.855 (95% confidence interval [CI], 0.754-0.956; cutoff, 36 years), 0.797 (95% CI, 0.679-0.916; cutoff, 0.285) and 0.891 (95% CI, 0.806-0.975; cutoff, 0.147), respectively. The combined model (age + nICa) demonstrated the highest performance (AUC = 0.980; 95% CI, 0.952-1.000) when comparing to that of age (P = 0.008), nCTa (P = 0.002) and nICa (P = 0.03), with satisfactory accuracy (92.3%), sensitivity (88.2%) and specificity (100%). The DLCT parameter nICa combined with age facilitates non-invasive quantitative differentiation between non-hypervascular NF-pNENs and SPNs with satisfactory diagnostic performance. Not applicable.

The antenatal diagnosis of hypospadias has implications for parental counselling, decision-making and organizing postnatal management. Recent imaging advancements have enabled antenatal detection of hypospadias with significant implications for parental psychology and clinical management. However, there is considerable variability in the application of the diagnostic techniques and their reliability or diagnostic accuracy. To assess the diagnostic accuracy of prenatal imaging modalities in the antenatal detection of hypospadias using a Bayesian statistical framework and to identify key imaging features that enhance prenatal diagnosis. Comprehensive searches across PubMed, Scopus and Google Scholar identified primary research on antenatal hypospadias diagnosis, which was subject to systematic review as per PRISMA guidelines. A Bayesian model employing non-informative priors (Beta (1,1)) was used to calculate pooled sensitivity and specificity, along with corresponding 95% credible intervals, enabling the probabilistic quantification of diagnostic uncertainty. The review included 34 studies published between 1989 and 2023, representing 280 pregnant females with 282 foetuses. Bayesian analysis revealed high sensitivity (0.87; 95% CrI: 0.80-0.92) and moderate specificity (0.46; 95% CrI: 0.34-0.58), translating into reliable detection of cases, though with a higher risk of false positives. While 2D sonography served as the universal screening tool (100%), supplementary techniques included 3D sonography (32.3%), color Doppler (32.3%) and magnetic resonance imaging (8.8%). Diagnosis occurred at a mean gestational age of 26.3 ± 5.5 weeks (range 20-39 weeks). Key imaging features identified were ventral curvature (n = 62), a shortened penile shaft (n = 52), a blunt penile tip (n = 60), Meizner's tulip sign (n = 51) and a bifid scrotum (n = 20). The tulip sign, bifid scrotum and cranially-directed phallus were exclusively associated with proximal variants. While 2D-ultrasonography remains the primary investigative modality, antenatal detection of hypospadias may be improved through the integration of 3D ultrasound, Doppler and MRI, particularly in complex cases. Confirmatory postnatal evaluation is crucial to address the moderate specificity and risk of false-positive results. However, there is a need to address the disparities in access to advanced imaging and technical expertise in prenatal diagnosis.

Breast cancer imaging without gadolinium-based contrast agent: A review of current applications and future trends.

Mass spectrometry imaging (MSI) is a powerful multiplexed biochemical imaging modality. It relies on raster scanning for localized data acquisition, which can be time-consuming, limiting applications of high-resolution tissue mapping and 3D reconstruction. This work presents a computational framework that integrates a raster scanning forward model with a deep learning prior to reconstruct high-resolution ion images from sparsely sampled pixels. The deep learning prior, implemented as a pretrained network-based denoiser, is incorporated into a plug-and-play-based iterative reconstruction algorithm without retraining for different acquisition settings. We show that our method can reconstruct high-fidelity ion images from sparse data acquired with different MSI instruments, acquisition settings, and tissue types without requiring additional training. Notably, our approach generalizes robustly to biologically and structurally distinct tissues, such as from brain to kidney sections, highlighting its potential for broad deployment in various experimental MSI workflows.

To summarize the current evidence on the incidence, risk factors, diagnosis, prevention, and management of incisional hernias following robotic urologic surgery. Emerging evidence has highlighted both surgical and patient-related factors that influence the risk of incisional hernia. Surgical variables associated with higher incidence include midline extraction sites, midline trocar placement, prior abdominal surgery, non-bladed trocar use, and advanced tumor stage. Patient-specific contributors include visceral obesity and rectus diastasis. The financial impact is substantial, with U.S. healthcare expenditures for incisional hernia management estimated at $1.7billion annually, underscoring the need to optimize surgical technique and patient selection to reduce this burden. Incisional hernia (IH) remains a significant postoperative complication, even with the advent of minimally invasive and robotic surgical techniques. Studies report a variable incidence of IH 0.2-6.3% following robotic prostatectomy, with rates as high as 27% in robotic nephrectomy depending on imaging modality and hernia definition. Diagnosis is commonly made with CT imaging, which remains the gold standard for preoperative planning. Although many IHs are asymptomatic, they may progress to incarceration, necessitating emergency repair with significant morbidity and mortality. Risk factors for IH are multifactorial and include patient-related variables such as obesity, smoking, COPD, diabetes, and rectus diastasis, as well as surgical factors including trocar size and type, extraction site location, and fascial closure technique. Notably, midline and bladed trocar placements are associated with higher hernia risk, while Pfannenstiel extraction and use of non-bladed trocars may be protective. Management strategies remain inconsistent, and preventive measures such as prophylactic mesh, proven effective in general surgery, have yet to be evaluated in urologic robotic procedures. This review summarizes the current literature on IH following robotic urologic surgery, with emphasis on incidence, risk factors, diagnostic modalities, preventive techniques, and potential areas for future research. Given the growing use of robotics in urology and the rising economic burden of IH, better understanding of prevention and early intervention is essential to improving outcomes and reducing healthcare costs.

Pediatric deep neck infections (DNIs) pose diagnostic and therapeutic challenges due to their varied presentation across age groups. Current management strategies lack age-specific guidelines despite known anatomical and clinical differences. Our study aims to evaluate age-related variations in clinical presentation, imaging use, treatment approach and outcomes in pediatric DNIs, and to assess potential implications for modifying existing management algorithms. This retrospective study analyzed 268 pediatric patients diagnosed with retropharyngeal or parapharyngeal infections between 2009 and 2020 at a tertiary pediatric center. Patients were stratified into 3 age groups: <1 year, 1-6 years and >6 years. Clinical features, imaging modality, treatment and outcomes were compared across age groups. Multivariate logistic regression was used to identify predictors for surgical drainage and prolonged hospitalization. Retropharyngeal infections were predominant in children under 6, while parapharyngeal infections were more common in those over 6. The clinical presentation varied significantly by age, with infants more likely to present with nonspecific symptoms and older children presenting with localized signs. Computed tomography scan performance was the strongest predictor for surgical drainage (P < 0.001). However, age did not significantly influence the surgical intervention rate or hospitalization length. The overall rate of surgical drainage was low (7.8%). Pediatric DNIs exhibit distinct age-related patterns in presentation and infection site, though outcomes remain consistent across groups. These findings support the need for age-specific clinical algorithms, particularly regarding diagnostic imaging and thresholds for intervention, to optimize care and reduce unnecessary procedures in young children.

Accurate abdominal multi-organ segmentation is essential for disease diagnosis and treatment planning. Although numerous deep-learning models have been proposed, current methods still struggle to balance segmentation accuracy with computational efficiency, particularly for images exhibiting inhomogeneous intensity distributions and complex anatomical structures. To address these challenges, we present a hybrid framework that integrates an Efficient Vision Mamba (EViM) module into a Transformer-based encoder. The EViM module leverages hidden-state mixer-based state-space duality to enable efficient global context modelling and channel-wise interactions. In addition, a weighted combination of cross-entropy and Jaccard loss is employed to improve boundary delineation. Experimental results on the Synapse dataset demonstrate that the proposed model achieves an average Dice score of 82.67% and an HD95 of 16.36 mm, outperforming current state-of-the-art methods. Further validation on the ACDC cardiac MR dataset confirms the generalizability of our approach across imaging modalities. The results indicate that the proposed framework achieves high segmentation accuracy while effectively integrating global and local information, offering a practical and robust solution for clinical abdominal multi-organ segmentation.

Chest computed tomography (CT) surpasses chest radiography (CR) in accurately assessing disease severity and detecting early structural pulmonary changes in patients with cystic fibrosis (CF). Chest CT provides detailed visualisation and quantification of CF-specific lung pathologies and can reveal these changes before they manifest clinically or become detectable on CR. The past decade has witnessed the advent and refinement of radiation-reducing techniques in CT which have enabled substantial dose reductions. Our study prospectively evaluates the efficacy of ultra-low dose CT (ULDCT) chest in identifying pulmonary changes within a paediatric patient cohort. Paediatric patients with CF, who presented for routine clinical outpatient follow-up between 01/07/2022, and 01/07/2023 underwent ULDCT and CR (if not recently performed) and image analysis was performed. Radiation dose, subjective and objective image quality and disease severity were recorded. 45 patients (mean age 10.5 years) underwent clinically indicated ULDCT chest ± CR. The mean effective dose was of ULDCT was 0.07 ± 0.01 mSv, a dose that approximates that of a frontal and lateral chest radiograph. The average ULDCT Brody II severity score across the entire cohort was 5.62, with excellent inter-rater reliability and intra-class correlation coefficient (ICC) of 0.98 (95% CI = 0.96, 0.99). The average Chrispin-Norman score on chest radiograph was 0.93 with moderate inter-rater reliability and ICC of 0.64 (95% CI = 0.19, 0.83). In light of its superior diagnostic capabilities, minimal radiation dose penalty, we advocate for ULDCT to be the preferred modality for surveillance imaging in paediatric patients with CF.

Introduction Neurodegenerative diseases such as Alzheimer's and Parkinson's are characterized by complex, multifactorial progression patterns that challenge early diagnosis and personalized treatment planning. Methods To address this, we propose an integrated AI-radiomics framework that combines symbolic reasoning, deep learning, and multi-modal feature alignment to model disease progression from structural imaging and behavioral data. The core of our method is a biologically informed architecture called NeuroSage, which incorporates radiomic features, clinical priors, and graph-based neural dynamics. We further introduce a symbolic alignment strategy (CAIS) to ensure clinical interpretability and cognitive coherence of the learned representations. Results and discussion Experiments on multiple datasets—including ADNI, PPMI, and ABIDE for imaging, and YouTubePD and PDVD for behavioral signals—demonstrate that our approach consistently outperforms existing baselines, achieving an F1 score of 88.90 on ADNI and 85.43 on PPMI. These results highlight the framework's effectiveness in capturing disease patterns across imaging and non-imaging modalities, supporting its potential for real-world neurodegenerative disease monitoring and diagnosis.

Combing magnetic resonance imaging (MRI) and cancer therapy modalities within one nanoplatform holds great potential for imaging-guided cancer theranostics. However, simultaneously achieving optimal MRI performance and satisfactory anti-cancer effects is still a challenge. Here, by manipulating the position of a Fe3O4 core that has MRI capability within a porous shell, this work synthesizes a series of core-shell structured Fe3O4@carbon/copper oxide nanoparticles (Fe3O4@C/CuOx NPs) in which the Fe3O4 core has different degrees of exposure. This work demonstrates that in an eccentric structure with maximally exposed Fe3O4 core, the NPs exhibits optimal MRI capability. Additionally, using polymer as scaffold blended with carbon-doped copper oxide, the shell of the NPs can integrate chemotherapy, photothermal therapy (PTT) and cuproptosis to exert synergistic anti-cancer effect in a pH/NIR dual responsive manner. The porous shell allows efficient DOX loading for chemotherapy, the copper oxide component serves as photothermal agents for PTT and triggers for cuproptosis. Last, the Fe3O4 core is also a nanozyme that possesses peroxidase (POD)-like properties, which enhances the efficacy of above-mentioned anti-cancer effects via promoting reactive oxygen species (ROS) generation. This work evaluates the MRI-guided anti-cancer efficacy of the NPs both in vitro and in vivo, and demonstrates NPs' superior performance in imaging-guided cancer theranostics.

Ultrasound localization microscopy (ULM) is an emerging imaging modality that resolves microvasculature in deep tissues with high spatial resolution. However, existing preclinical ULM applications are largely constrained to anesthetized animals, introducing confounding vascular effects such as vasodilation and altered hemodynamics. As such, ULM quantifications (e.g., vessel diameter, density, and flow velocity) may be confounded by the use of anesthesia, undermining the usefulness of ULM in practice. Here, we introduce a method to address this limitation and achieve ULM imaging in awake mouse brain. Pupillary monitoring was used to support the presence of the awake state during ULM imaging. Vasodilation induced by isoflurane was observed by ULM. Upon recovery to the awake state, reductions in vessel density and flow velocity were observed across different brain regions. In the cortex, the effects induced by isoflurane are more pronounced on venous flow than on arterial flow. In addition, serial in vivo imaging of the same animal brain at weekly intervals demonstrated the highly robust longitudinal imaging capability of the proposed technique. The consistency was further verified through quantitative analysis on individual vessels, cortical regions of arteries and veins, and subcortical regions. This study demonstrates longitudinal ULM imaging in the awake mouse brain, which is crucial for many ULM brain applications that require awake and behaving animals.

Cardiac arrhythmias, including atrial fibrillation, ventricular tachycardia, and sudden cardiac death, remain a leading cause of morbidity and mortality worldwide. While traditional models of arrhythmogenesis have focused on structural remodeling and ion channel dysfunction, emerging evidence highlights the pivotal role of immune-inflammatory processes in shaping arrhythmic substrates. This review synthesizes current knowledge on the immunobiology of the heart and the mechanisms by which cytokine signaling, inflammasome activation, and immune cell-cardiomyocyte interactions promote electrical instability. Clinical data from myocarditis, autoimmune cardiomyopathies, postmyocardial infarction, and systemic inflammatory diseases provide strong evidence linking inflammation with arrhythmic outcomes. We also evaluate diagnostic strategies-including biomarkers, advanced imaging modalities, electrocardiographic phenotypes, and endomyocardial biopsy-that enable the identification of inflammatory substrates, while discussing the safety challenges of ablation, device therapy, and immunomodulation in this context. Emerging technologies such as artificial intelligence, molecular imaging, and multiomics approaches are advancing risk stratification and paving the way for precision therapies. Despite persistent gaps in specificity, standardization, and trial evidence, integrating immunology with electrophysiology offers a transformative framework for predicting, preventing, and managing inflammation-driven arrhythmias. This convergence may ultimately yield novel therapeutic targets and improve outcomes in high-risk patient populations.

Nephrotic syndrome (NS) is a systemic disorder characterized not only by glomerular dysfunction but also by profound dysregulation of lipid metabolism and microvascular integrity. Adipose tissue, as a central lipid-handling and endocrine organ, undergoes structural and functional remodeling in chronic renal conditions yet remains underexplored in this context. The aim of this manuscript is to integrate adipose tissue imaging into the diagnostic and mechanistic framework of NS. To establish this perspective, we first summarize current knowledge on adipose tissue architecture and imaging in both physiological states and renal disease. We then present a multimodal imaging approach—combining ultrasound (US), histology, and atomic force microscopy (AFM)—applied to human adipose tissue as a potential diagnostic and pathophysiological marker in NS. Original imaging from our laboratory experience is presented as a demonstrative material, complemented by literature synthesis. Given that different modalities of imaging-based characterization of adipose tissue are sparse across the literature, this pictorial review offers a guide to identifying structural biomarkers of adipose remodeling in NS. By bridging imaging modalities with metabolic and vascular perturbations observed in NS, this work aims to guide future research toward the clinical application of adipose tissue imaging in renal disease. This provides insights into cell size heterogeneity, vascular topology, and subcellular features such as membrane wrinkles and nanodomain organization. We propose that such morphometric parameters, accessible via minimally invasive biopsies, could serve as surrogate markers of adipose remodeling in nephrotic syndrome. This sets the stage for integrating adipose tissue imaging into the diagnostic and mechanistic evaluation of systemic features in NS.

Left ventricular hypertrophy (LVH) can be identified through both electrocardiography (ECG) and echocardiography, with echocardiography recognized as the gold standard for the assessment of LVH. This imaging modality determines the presence of LVH by evaluating the left ventricular mass index (LVMI). For diagnostic purposes, LVH is defined in males as a left ventricular mass index greater than 115 g/m² and in females as greater than 95 g/m². Despite the high accuracy of echocardiography in diagnosing LVH, access to this examination is not universal across all healthcare facilities. Consequently, electrocardiography, a widely available, non-invasive, and cost-effective diagnostic tool, serves as an alternative for the diagnosis of LVH. Several criteria exist for the electrocardiographic assessment of LVH, including the Sokolow-Lyon and Cornell voltage criteria. However, the sensitivity of these electrocardiographic methods remains relatively low, with reported sensitivities of 17% for the Sokolow-Lyon criteria and 35% for the Cornell criteria. In left ventricular hypertrophy, the interstitium experiences changes characterized by fibrosis and other deposits. These alterations can reduce the expression of hypertrophic myocardial tension and limit the diagnostic capabilities of surface electrocardiograms. Additionally, several factors influence electrical tension, including variations in chest wall thickness, heart muscle activity, the distance of the electrode from the left ventricle, and lung activity. The presence of these limiting factors can increase the rate of false negatives in diagnosis. In 2017, Peguero and Lo Presti introduced novel criteria for the diagnosis of LVH, defined by evaluating the deepest S wave and summing it with the S wave in lead V4. According to these new criteria, LVH is identified as ≥ 2.8 mV in men and ≥ 2.3 mV in women. The Peguero-Lo Presti criteria demonstrate improved sensitivity when compared to traditional criteria such as Sokolow-Lyon and Cornell, offering enhanced diagnostic accuracy.

Early diagnosis and noninvasive monitoring of neurological disorders require sensitivity to elusive cellular-level alterations that occur much earlier than volumetric changes observable with the millimeter-resolution of medical imaging modalities. Morphological changes in axons, such as axonal varicosities or beadings, are observed in neurological disorders, as well as in development and aging. Here, we reveal the sensitivity of time-dependent diffusion MRI (dMRI) to the structurally disordered axonal morphology at the micrometer scale. Scattering theory uncovers the two parameters that determine the diffusive dynamics of water along axons: the average reciprocal cross-section and the variance of long-range cross-sectional fluctuations. This theoretical development allows us to predict dMRI metrics sensitive to axonal alterations over tens of thousands of axons in seconds rather than months of simulations in a male rat model of traumatic brain injury, and is corroborated with ex vivo dMRI. Our approach bridges the gap between micrometers and millimeters in resolution, offering quantitative and objective biomarkers applicable to a broad spectrum of neurological disorders.

Dystocia, or difficult parturition, is a significant challenge for small ruminant farmers, often leading to maternal and foetal mortality. This case reports the successful non-surgical management of dystocia in a 3-year-old Uda ewe weighing 55 kg, presented with prolonged labour and a hanging placenta. Clinical examination revealed a second, dead foetus with a flexed forelimb. Haematology results indicated leukocytosis and anaemia. Management involved obstetric manoeuvres by correcting the limb flexion through repulsion and manual retraction, followed by uterine lavage with warm saline and Septol® to reduce bacterial load. Vetcotrim® boli and systemic antibiotics were administered. The dead foetus was delivered using obstetrical techniques, and the ewe recovered, with her vital signs and appetite improved within five days. The first lamb from the earlier lambing remained active and suckled milk well. It was concluded that dystocia in sheep could be resolved without resorting to a caesarean section. Obstetrical manoeuvres application along with intrauterine uterine lavage followed by the administration of Vetcorim® effectively prevents septic metritis in sheep. This case management approach is more useful in remote areas with limited surgical facilities and equipment. Compared to a caesarean section, this method is relatively inexpensive. It is recommended to practitioners to reserve caesarean sections as a last resort to save time and reduce expenses for clients. The case management emphasises effectiveness and cost-efficiency (₦10,000) of non-surgical interventions in resource-limited settings. It also recommends timely intervention and the need for access to imaging modalities in dystocia management.