Search Results (380)

Background: Acute focal neurological deficits require rapid differentiation between ischemic stroke and stroke mimics to avoid treatment delays and inappropriate therapy. Seizures, including ictal deficits, status epilepticus, and post-ictal/Todd’s phenomena, are among the most challenging mimics. This review summarizes the role of multimodal neuroimaging in distinguishing acute ischemic stroke from seizure-related deficits. Methods: We performed a focused narrative review of neuroimaging findings in acute stroke mimics, emphasizing non-contrast computed tomography (CT), CT angiography, CT perfusion, magnetic resonance imaging (MRI), including diffusion weighted imaging (DWI), apparent diffusion coefficient (ADC), fluid attenuated inversion recovery (FLAIR), and arterial spin labeling (ASL) sequences. Imaging patterns, diagnostic pitfalls, and practical clues for hyperacute stroke pathways were synthesized. Results: Acute ischemic stroke is typically suggested by vascular-territorial abnormalities, including arterial occlusion or stenosis, territorial hypoperfusion, and congruent DWI/ADC restriction. Seizure-related deficits more often show non-territorial cortical perfusion changes, ictal or status-related hyperperfusion, reversible MRI abnormalities, and absence of arterial occlusion. However, post-ictal hypoperfusion, peri-ictal diffusion restriction, and reperfusion-related hyperperfusion may overlap with ischemic patterns. Conclusions: A multimodal approach integrating vascular imaging, perfusion distribution, DWI/ADC, ASL, clinical timing, and EEG findings can improve diagnostic accuracy in the stroke–seizure differential without delaying treatment in true acute ischemic stroke. Full article

Background/Objectives: Diagnosing hemangioblastomas using magnetic resonance imaging (MRI) is challenging, especially when the tumors appear as solid posterior fossa masses. This study aimed to evaluate the diagnostic performance of perfusion MRI and identify the most useful quantitative features for differentiating hemangioblastomas from other posterior fossa tumors. Methods: Forty-five posterior fossa tumors were analyzed, including 18 hemangioblastomas (HB group) and 27 non-hemangioblastoma tumors (NHB group; 8 metastatic brain tumors, 6 pilocytic astrocytomas, 5 malignant lymphomas, 4 glioblastomas, 2 medulloblastomas, and 2 other tumors). All patients underwent 3.0-T MRI. Arterial spin labeling (ASL) was used to calculate the relative tumor blood flow normalized to the contralateral gray matter. Dynamic susceptibility contrast (DSC) imaging was used to obtain regional cerebral blood flow, regional and corrected cerebral blood volume (CBV), and permeability index (K2) values. Regions of interest (ROIs) were placed within the contrast-enhancing areas. Results: The relative ASL values and corrected CBV were significantly higher in hemangioblastomas than in other tumors (p < 0.001). Relative ASL showed the highest diagnostic performance (sensitivity, 100%; specificity, 93.3%). Conclusions: Non-contrast ASL showed strong diagnostic performance for identifying posterior fossa hemangioblastomas and may serve as a practical alternative to contrast-enhanced DSC, although ROI placement can be challenging in very small mural nodules. Full article

Background and Objectives: Head and neck cancers are heterogeneous malignancies with variable biological behavior and treatment response, contributing to high morbidity and mortality. Conventional imaging techniques are limited in their ability to capture tumor biology, highlighting the need for advanced functional imaging. This review aims to evaluate the role of multiparametric magnetic resonance imaging (MRI) in characterizing the tumor microenvironment. Materials and Methods: A narrative review was conducted based on a targeted literature search of databases, including PubMed and Google Scholar. Studies addressing advanced MRI techniques for assessing tumor cellularity, vascularity, molecular features, and oxygenation were selected and analyzed. Results: Perfusion techniques, such as dynamic contrast-enhanced MRI (DCE-MRI) and arterial spin labeling (ASL), provide a quantitative assessment of tumor vascularity and show value in predicting treatment response. Diffusion-based methods, including diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI), enable evaluation of tissue cellularity and heterogeneity. Molecular approaches, such as chemical exchange saturation transfer (CEST) and amide proton transfer (APT), offer insights into protein content and proliferation. Oxygenation-sensitive techniques, such as blood oxygenation level dependent MRI (BOLD MRI) and oxygen-enhanced MRI (OE-MRI), allow non-invasive assessment of tumor hypoxia. Conclusions: Multiparametric MRI provides a comprehensive and biologically relevant evaluation of the tumor microenvironment in head and neck cancer, with potential to improve treatment prediction and support personalized therapeutic strategies. Full article

Background/Objectives: Quantitative MRI may support non-invasive characterization of myelin-related tissue properties, but the relative association of synthetic MRI (SyMRI) metrics and IVIM-DWI parameters with myelin-related measures remains unclear. This study investigated associations between SyMRI-derived quantitative measures, IVIM-derived parameters, and myelin-related indices in healthy adult brain tissue. Methods: Twenty-six healthy adults underwent IVIM-DWI and SyMRI. ROI-based quantitative parameters were extracted, including ADC, D, D*, perfusion fraction (f), T₁, T₂, and proton density (PD). SyMRI-derived myelin-correlated parenchymal fraction (MyCPF) and myelin-correlated volume (MyC) were obtained. ROI-averaged WM–GM differences were assessed using the Wilcoxon signed-rank test, and associations were evaluated using Spearman correlation with false discovery rate correction. Results: IVIM-derived parameters were significantly higher in WM, whereas T₁ and PD were significantly higher in GM (all p < 0.001); T₂ did not differ significantly (p = 0.901). In WM, PD showed a strong inverse association with MyCPF (ρ = −0.736, p < 0.001, q < 0.001), whereas its association with MyC did not remain significant after correction. In GM, PD showed a moderate inverse association with MyCPF (ρ = −0.532, p = 0.005), but this was not significant after correction (q = 0.073). No IVIM-derived parameter showed significant associations with myelin-related metrics after correction. Conclusions: PD showed the strongest association with MyCPF, particularly in WM, supporting its potential as a non-invasive marker of myelin-related tissue composition. IVIM-derived parameters showed limited relevance for myelin assessment in this healthy cohort. Full article

Background: Magnetic particle imaging (MPI) is an emerging, tracer-based modality that directly detects superparamagnetic iron oxide nanoparticles (SPIONs) with exceptional sensitivity, quantitative signal behavior, and full immunity to air–tissue susceptibility artifacts. These features make MPI particularly well-suited for pulmonary imaging, where traditional techniques such as computed tomography (CT), magnetic resonance imaging (MRI), and nuclear medicine-based ventilation/perfusion (V/Q) imaging are limited by radiation exposure, low contrast, and motion-related signal degradation. Objective: This review synthesizes the current state of MPI for lung imaging, with emphasis on its physical principles, tracer development, preclinical applications, and its potential role in assessing pulmonary perfusion, vascular integrity, inflammation, and therapeutic responses. Methods: A systematic evaluation of preclinical studies was performed across three major application domains: pulmonary perfusion mapping, cell tracking and therapeutic monitoring, and vascular injury and permeability assessment. Study designs, SPION formulations, MPI acquisition strategies, and validation methods, including histopathology, biodistribution, broncho-alveolar lavage fluid (BALF) analysis, and Evans Blue assays, were examined to characterize methodological consistency and imaging performance. Results: MPI consistently demonstrated high-contrast, quantitative visualization of pulmonary blood flow, endothelial barrier disruption, inflammatory signaling, and transplanted or inhaled cell populations. Tracer engineering played a critical role: macroaggregated albumin superparamagnetic iron oxide nanoparticles (MAA-SPIONs) enabled capillary-level perfusion mapping, LS-008 improved temporal resolution and vascular delineation, Synomag/Synomag-D allowed quantification of vascular leakage in acute and chronic lung injury, and vascular cell adhesion molecule-1 (VCAM-1)-targeted probes provided molecular-level assessment of inflammation. Hybrid MPI-CT and MPI-MRI approaches further enhanced anatomic localization and enabled accurate pulmonary blood volume (PBV) estimation. Across studies, MPI measurements showed strong agreement with established biological assays and remained free of the artifacts that limit CT and MRI in the lung. Conclusions: Preclinical evidence demonstrates that MPI is a robust, radiation-free, and quantitatively precise modality for functional and molecular lung imaging. Its ability to map perfusion, track therapeutic agents, and noninvasively quantify vascular permeability positions MPI as a promising future alternative or complement to CT, MRI, and nuclear medicine for pulmonary assessment. Continued tracer optimization, system scaling, and clinical validation are key steps toward translating MPI into routine clinical use. Full article

Background: Chemotherapy-induced peripheral neuropathy (CIPN) is a common, disabling toxicity with no validated biomarkers. MRI-based functional neuroimaging could offer insight into central pain processing and may reveal reproducible brain signatures of CIPN. Methods: Following PRISMA 2020 (PROSPERO: CRD420251132102), we systematically reviewed whole-brain MRI studies in adult cancer patients with CIPN. Eligible MRI techniques included task-based fMRI, resting-state fMRI, perfusion MRI, and structural MRI. Data were synthesized through voxelwise activation likelihood estimation (ALE), systems-level region-of-interest (ROI) mapping, and proportion meta-analysis of regional involvement. Results: Of 2488 screened records, five observational studies were included. The voxelwise ALE analysis did not identify clusters surviving correction, but dispersed foci appeared within the default mode network (DMN), prefrontal executive cortex, and primary sensorimotor regions, suggesting the engagement of these pain-processing networks. ROI synthesis confirmed consistent alterations in the DMN and executive prefrontal and sensorimotor cortices in CIPN patients compared with controls, while the brainstem/periaqueductal gray and cerebellum were rarely implicated. Proportion meta-analysis further quantified these differences: CIPN patients showed altered involvement in 30% (95% CI 0.16–0.48) of contrasts, with the highest frequencies in the DMN (50%), sensorimotor (33%), and executive prefrontal regions (33%). By contrast, control-higher contrasts were less frequent (10%, 95% CI 0.03–0.27), highlighting CIPN-related increases particularly in self-referential and somatosensory networks. Conclusions: Across analytic approaches, CIPN is characterized by reproducible alterations in the DMN and executive prefrontal and sensorimotor networks. These central pain signatures represent promising MRI-based biomarkers for identifying and monitoring CIPN in oncology. Full article

Background/Objectives: Contrast enhancement (CE) on T1-weighted MRI is routinely used to guide therapy in the management of glioblastoma, although adjacent non-contrast-enhancing (non-CE) T2/FLAIR abnormalities can also harbor viable tumor tissue. The differences between these radiographic compartments remain incompletely characterized beyond conventional structural imaging. We therefore compared CE and non-CE compartments in untreated IDH-wildtype glioblastoma using dynamic susceptibility contrast (DSC) and diffusion-weighted MRI derived indices. Methods: Adults with untreated glioblastoma imaged preoperatively between January 2021 and September 2024 on multi-vendor 1.5 T and 3 T scanners were retrospectively included. Regions of interest were placed in CE tumor, adjacent non-CE T2/FLAIR hyperintense tissue, and contralateral normal-appearing white matter (NAWM). Mean apparent diffusion coefficient (rADC), cerebral blood volume (rCBV), capillary transit time heterogeneity (rCTH), oxygen extraction fraction (rOEF), and a cerebral metabolic rate of oxygen index (rCMRO₂) were extracted and harmonized for scanner effects and normalized to NAWM. Paired CE–non-CE differences were tested using Wilcoxon signed-rank tests and summarized by Hodges–Lehmann differences with bootstrap 95% confidence intervals. Spearman correlations were used to assess coupling within contrast-enhancing tumor regions. Results: Seventy-two participants were analyzed (median age 67 years; 34 women); 66 had paired CE and non-CE data. rCMRO₂ and rCBV were higher in CE than non-CE (both p < 0.001), while rADC was lower (p = 0.003). rOEF (p = 0.12) and rCTH (p = 0.52) did not differ significantly between compartments. Conclusions: CE in untreated IDH-wildtype glioblastoma predominantly reflects higher perfusion capacity (rCBV) along with a higher model-derived rCMRO₂ index, while capillary-function indices (rCTH and rOEF) are not consistently compartment-restricted. These findings may refine the physiological interpretation of CE in glioblastoma and support further validation of DSC-derived indices. Full article

Genicular artery embolization (GAE) has emerged as a minimally invasive interventional radiology technique for the management of symptomatic knee osteoarthritis (OA), a highly prevalent condition associated with substantial functional impairment and socioeconomic burden. The rationale of GAE is based on superselective embolization of pathological periarticular neovascularization, aiming to modulate synovial inflammation, angiogenesis, and nociceptive signaling while preserving physiological joint perfusion. This narrative review provides an interventional radiology–oriented framework integrating pathophysiological mechanisms, imaging-based patient selection, and procedural strategy. Particular emphasis is placed on the vascular–inflammatory phenotype of OA, MRI-derived biomarkers of synovitis and hypervascularity, and technical aspects of embolization, including embolic agent selection and angiographic endpoints. A structured literature search was performed to identify relevant studies, including prospective trials and randomized controlled studies. Available evidence is critically discussed, with attention to clinical outcomes, safety profile, and current limitations. In addition, practical technical considerations and procedural pitfalls are summarized to provide a clinically applicable perspective. GAE represents a promising therapeutic option for selected patients with knee OA refractory to conservative management. However, further high-quality studies are required to define long-term durability, optimal patient selection, and standardized procedural strategies. Full article

Background and Purpose: Neurological injury remains a major complication of pediatric cardiac surgery and is closely related to alterations in cerebral blood flow during extracorporeal circulation (ECC). However, the real-time assessment of cerebral perfusion under these conditions has been limited by the lack of magnetic resonance (MR)-compatible perfusion systems. The aim of this pilot feasibility study was to establish a porcine model enabling simultaneous cardiopulmonary bypass (CPB) and real-time MR-based assessment of cerebral blood flow during simulated pediatric cardiac surgery. Methods: We conducted a pilot study on 11 Duroc pigs (14.6 ± 1.4 kg BW), designed in iterative cycles. The experimental setup included an MR-conditional heart-lung machine and a surgical protocol closely mimicking pediatric cardiac surgery. After the initiation of CPB and hemodynamic stabilization, animals were cooled to target temperatures (20 °C or 28 °C) depending on the perfusion strategy. Structural and functional MRI, including phase-contrast imaging, arterial spin labeling, diffusion-weighted imaging, and MR spectroscopy, were performed during cooling and rewarming. Procedural feasibility, technical challenges, and optimization strategies were systematically documented. Results: The study successfully established a reproducible porcine model enabling MR imaging during extracorporeal circulation. Key technical challenges, including vascular access, cannulation of the ascending aorta, and blood volume management, were identified and addressed through the iterative refinement of the surgical and perfusion protocols. The use of the Seldinger technique significantly improved cannulation safety and reduced blood loss. Stable CPB conditions and target hypothermic temperatures were achieved in successfully cannulated animals. MRI acquisition during CPB was feasible, providing simultaneous structural and functional assessment of cerebral perfusion. Representative imaging data demonstrate the capability of the model to capture cerebral hemodynamics in real time. Conclusions: This pilot study establishes a novel MR-compatible porcine model for the real-time assessment of cerebral blood flow during extracorporeal circulation. The platform provides a robust foundation for future quantitative investigations of cerebral perfusion, mechanisms of brain injury, and neuroprotective strategies in pediatric cardiac surgery. Full article

Background/Objectives: Early neurological deterioration (END) is a frequent and clinically relevant complication in patients with a single small subcortical infarction (SSI), including lacunar infarction and branch atheromatous disease (BAD). Despite initially mild symptoms, END occurs in approximately 20–25% of cases and is strongly associated with poor functional outcomes. However, definitions, mechanisms, predictors, and therapeutic strategies remain heterogeneous. This review aims to synthesize current evidence regarding the incidence, pathophysiology, predictors, and management of END in SSI. Methods: We performed a narrative review of published studies addressing END in patients with lacunar stroke or SSI. We analyzed data on END definitions and incidence, imaging and clinical predictors, proposed pathophysiological mechanisms, and preventive and rescue therapeutic strategies. Results: END definitions vary across studies, most commonly defined as a ≥2-point increase in the National Institutes of Health Stroke Scale within 48–72 h. Hemodynamic compromise due to proximal perforator pathology, particularly in BAD, appears central to END development. Advanced imaging studies demonstrate perfusion abnormalities beyond the infarct core, supporting the concept of a “lacunar penumbra.” Lesion topology, proximal infarct patterns, parent artery plaques, larger infarct size, and vertical extension are consistent imaging predictors. Clinical factors such as diabetes mellitus, higher baseline severity, systemic inflammation, and increased arterial stiffness further modulate risk. Preventive strategies, including early dual antiplatelet therapy and intensified antithrombotic regimens, show promising signals, while induced hypertension may benefit selected patients as a rescue therapy. However, evidence remains largely observational or derived from subgroup analyses. Conclusions: END in SSI is a multifactorial and potentially modifiable process driven by interactions between proximal vascular pathology, hemodynamic failure, and tissue vulnerability. Standardized definitions, MRI-based phenotyping, and mechanism-driven trials are needed to optimize risk stratification and develop targeted preventive and rescue strategies. Full article

Background/Objectives: Magnetic nanoparticles have emerged as powerful tools for biomedical imaging, targeted drug delivery, and hyperthermia therapy. Magnetic particle imaging (MPI) is among the most promising technologies built around its properties: a radiation-free, quantitative tomographic modality that detects superparamagnetic iron oxide nanoparticles (SPIONs) directly against a biologically silent background. This review synthesizes MPI’s physical principles, nanoparticle design strategies, and preclinical applications within the broader landscape of magnetic material engineering for biomedical use. Methods: A systematic review was conducted covering MPI signal generation and image reconstruction, nanoparticle core synthesis and surface coating approaches, and preclinical applications, spanning cell tracking, oncological imaging, vascular perfusion, neuroimaging, and MPI-guided theranostics. Studies were selected to provide quantitative benchmarks and direct comparisons with competing modalities where available. Results: MPI delivers signal-to-background ratios above 1000:1, iron-mass linearity at R² ≥ 0.99, regardless of tissue depth, and acquisition rates up to 46 volumes per second. Tracer architecture—encompassing single-core particles, multicore nanoflowers, and stimuli-responsive cluster designs—is the primary determinant of sensitivity, environmental robustness, and theranostic capability. Preclinical results include detection of cell populations in the low thousands, earlier ischaemia identification than diffusion-weighted MRI, real-time drug release quantification, and spatially confined tumour hyperthermia. Three translational bottlenecks are identified: the absence of a clinically approved tracer with optimal relaxation dynamics, hardware performance losses when scaling to human-bore systems, and overestimation of passive tumour accumulation in murine models. Conclusions: MPI illustrates how progress in magnetic material design directly expands clinical imaging and theranostic possibilities. Successful translation will require indication-driven, interdisciplinary development that integrates materials science, scanner engineering, and regulatory strategy in parallel. Full article

Chronic kidney disease (CKD) represents a growing medical, diagnostic and social challenge, and it is estimated to effect 8.5–9.8% of the global population and requires expensive modes of treatment, such as hemodialysis or renal transplants. Currently, a diagnosis of CKD is set based on the level of creatinine in the blood, which is the gold standard of renal function diagnostics. Unfortunately, decrease in GFR is secondary to damage of the kidney parenchyma and indicates that the best time to start more aggressive treatment has already passed. Therefore, several non-invasive methods have been proposed for predicting increased risk of CKD progression; however, in most of the cases kidney biopsy is essential. Currently, the greatest hopes for a method that can confirm CKD are associated with the development of MRI, the most tissue-specific imaging method, and it is already proven to be capable to detect inflammatory and edematous changes, fibrosis, as well as perfusion and oxygenation disturbances. Therefore, in our manuscript we decided to present up-to-date knowledge about kidney MRI from a clinical point of view. Full article

Background: Artificial intelligence (AI) and deep learning (DL) are rapidly changing the field of diagnostics and imaging in cardiology, offering tools for automatic segmentation, quantification of changes, and risk stratification. These technologies have the potential to increase diagnostic accuracy, work efficiency, and individualization of patient care. Methods: This structured narrative review critically evaluates clinically validated applications of artificial intelligence (AI) and deep learning (DL) in cardiovascular medicine, focusing on imaging (echocardiography, coronary CT angiography, cardiac MRI, and ECG), risk stratification, and biomarker integration. A systematic literature search was conducted in PubMed for studies published between January 2015 and December 2026, supplemented by references from key articles. Original English-language studies reporting quantitative clinical outcomes were included, with 78 studies ultimately analyzed. Results: AI and DL models, including convolutional neural networks and transformers, achieved performance comparable to experts in cardiac imaging, myocardial perfusion assessment, valve defect detection, and coronary event prediction. Multimodal approaches improved diagnostic accuracy and reproducibility, while explainable AI enhanced transparency and clinical confidence. Deep learning also enabled faster image acquisition and processing without compromising precision. Conclusions: AI and DL have transformative potential in cardiology, offering fast, accurate, and scalable diagnostic tools. The integration of multimodal data, the validation of algorithms in prospective studies, and ensuring the transparency of models are key. Future research should focus on prospective, multicenter validations and the ethical and safe implementation of AI in everyday clinical practice. Full article

Median overall survival remains a central endpoint in oncology, but it can obscure a clinically meaningful long tail of patients with advanced solid tumors who survive well beyond the median. One biological context in which this pattern may be relevant is tumor microenvironment (TME) acidosis. Driven by aerobic glycolysis, hypoxia, impaired perfusion, and proton-export programs, acidic TME is increasingly implicated in invasion, therapeutic resistance, and immune suppression. This narrative review examines TME acidosis as the primary biological framework and considers long-tail survival as a clinical lens through which its implications may be interpreted. We summarize the biological basis and heterogeneity of acidic TME, review current approaches to clinical and translational assessment of tumor acidity, including acidoCEST magnetic resonance imaging (MRI) and positron emission tomography (PET)-based approaches, and discuss the potential and limitations of alkalization-oriented interventions such as buffering and diet-based strategies. Particular attention is given to the distinction between direct measurements of tumor acidity and clinically feasible but indirect markers such as urinary pH, which should not be interpreted as a direct surrogate for local tumor extracellular pH. From a science-based medicine perspective, long-tail survival is treated here as a hypothesis-generating clinical signal rather than proof of causality. Overall, alkalization-oriented interventions appear biologically plausible and clinically testable, but current clinical evidence remains limited and context-dependent. Future progress will require mechanistically informed biomarkers, careful safety evaluation, and trial designs capable of detecting delayed separation of survival curves and tail-oriented patterns of benefit. Full article

Background: Extracranial metastasis (EM) from glioblastoma (GB), IDH-wildtype (WHO CNS 2021 grade 4) is rare and often under-recognized, yet it has immediate implications for staging and management. We report a case series integrating advanced neuroimaging, whole-body imaging, and pathology/biomarkers to characterize imaging–pathology correlates of EM and highlight practical clinical triggers that should prompt systemic evaluation. Case presentation: We report three patients with adult-type, IDH-wildtype GB who developed EM confirmed by cytology/histology and/or concordant multimodality imaging. Brain MRI (1.5T/3T) demonstrated aggressive primary tumors with qualitative elevation of DSC-perfusion and frequent tumor–surface contact (dural, ependymal/leptomeningeal contact). Intratumoral susceptibility signal reached grade 3 where assessed. All patients underwent surgical resection followed by temozolomide-based chemoradiation; two received fotemustine and bevacizumab, and one underwent re-irradiation. EM presented with clinical triggers including severe axial/back pain, palpable cervical masses, and/or cytopenias. Initial EM sites were bone marrow/vertebrae (n = 1) and cervical lymph nodes (n = 2); staging revealed additional osseous disease in both nodal cases and a small pulmonary nodule in one. Nodal and osseous lesions were FDG-avid on 18F-FDG PET/CT. OLIG2-positive cytology confirmed cervical nodal metastases, and bone marrow aspiration with GFAP/OLIG2 positivity confirmed medullary infiltration. All tumors shared a molecular profile of TERT-promoter mutation, ATRX wild-type, TP53 mutation, and MGMT-promoter methylation. Despite attempts at second- and third-line therapies, disease progression was rapid, and all patients succumbed within 8–16 months of diagnosis. Discussion: This series underscores that EM can occur despite MGMT-promoter methylation and supports the concept of heterogeneous metastatic phenotypes in GB. Our cases reinforce that new axial/back pain or hematologic abnormalities may signal osseous or marrow involvement, and necrotic cervical lymphadenopathy in GB patients warrants dedicated imaging and tissue confirmation with glial markers. Integrating brain MRI features (high perfusion, surface contact, susceptibility burden) with FDG-PET/CT and targeted cytology/pathology can expedite diagnosis and inform multidisciplinary care. Conclusions: EM can arise despite MGMT-promoter methylation in IDH-wildtype GBM. Imaging red flags (high perfusion, surface contact, necrotic/FDG-avid cervical nodes) and clinical cues (axial pain, cytopenias, neck masses) should prompt early systemic staging (CT/PET-CT) and targeted tissue confirmation to advance management. Full article