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Results for “Diffusion Magnetic Resonance Imaging”

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PubMed2024

Sex and APOE ε4 allele differences in longitudinal white matter microstructure in multiple cohorts of aging and Alzheimer's disease.

INTRODUCTION: The effects of sex and apolipoprotein E (APOE)-Alzheimer's disease (AD) risk factors-on white matter microstructure are not well characterized. METHODS: Diffusion magnetic resonance imaging data from nine well-established longitudinal cohorts of aging were free water (FW)-corrected and harmonized. This dataset included 4741 participants (age = 73.06 ± 9.75) with 9671 imaging sessions over time. FW and FW-corrected fractional anisotropy (FAFWcorr) were used to assess differences in white matter microstructure by sex and APOE ε4 carrier status. RESULTS: Sex differences in FAFWcorr in projection tracts and APOE ε4 differences in FW limbic and occipital transcallosal tracts were most pronounced. DISCUSSION: There are prominent differences in white matter microstructure by sex and APOE ε4 carrier status. This work adds to our understanding of disparities in AD. Additional work to understand the etiology of these differences is warranted. HIGHLIGHTS: Sex and apolipoprotein E (APOE) ε4 carrier status relate to white matter microstructural integrity. Females generally have lower free water-corrected fractional anisotropy compared to males. APOE ε4 carriers tended to have higher free water than non-carriers.

Humans↗

PubMed2026

Neurocorrelates of nocturnal enuresis in pre-adolescent children.

INTRODUCTION: Nocturnal enuresis (NE) is a common neurodevelopmental condition, yet its underlying neural mechanisms remain unclear. This study leverages the large-scale Adolescent Brain Cognitive Development (ABCD) dataset to identify structural and functional brain correlates associated with active symptoms and the resolution of bedwetting. METHODS: Using cross-sectional data from 3472 participants aged 9-10 years, children were categorized into three groups: active nocturnal enuresis (ANE, n = 225), history of nocturnal enuresis (HNE, n = 1171), and healthy control groups (CG, n = 2076). Multimodal neuroimaging protocol evaluated macrostructural properties via structural MRI (sMRI), microstructural white matter integrity via diffusion MRI (dMRI), and functional connectivity via resting-state fMRI (fMRI). Group differences were evaluated using linear models within an ANCOVA framework, adjusting for intracranial volume and handedness with False Discovery Rate (FDR) correction. RESULTS: Compared to controls, the ANE group exhibited a significant volume deficit in the right caudate, decreased sulcal depth in the left insula, and lower internal correlation within the Cingulo-Opercular Network (CON). Conversely, the dry HNE group demonstrated significant structural adaptations, including bilaterally larger putamen volumes and increased right caudate volume compared to the ANE group. The HNE group also showed increased microstructural density (decreased mean diffusivity) in the bilateral hippocampus and an increased cortical surface area in the left insula. Both NE groups demonstrated persistently reduced functional coupling within the CON. CONCLUSIONS: Nocturnal enuresis appears to be associated with a potential complex central signaling deficits. Reduced internal correlation within the CON across both active and former bedwetters indicates a potential for impairment in processing internal homeostatic bladder signals during sleep.

Humans↗

PubMed2026

Diffusion MRI radiomics in meningiomas: imaging correlates of tumor grade and intraoperative consistency.

OBJECTIVE: Despite advancements in imaging studies, the preoperative prediction of the biological behavior and intraoperative consistency of intracranial meningiomas remains limited. This study evaluated the association of volumetric diffusion-based and texture-derived radiomic features extracted from routine MRI with histopathological aggressiveness and intraoperative tumor consistency. METHODS: Ninety-seven intracranial meningiomas resected at two tertiary centers were retrospectively analyzed. Volumetric segmentation was performed on contrast-enhanced T1-weighted MRI and coregistered to apparent diffusion coefficient (ADC) maps. Data on first-order diffusion metrics and selected texture features were collected. The associations between World Health Organization (WHO) grade and Ki-67 index were assessed using nonparametric tests and Spearman correlation analysis. Independent factors associated with intraoperative tumor consistency (Zada grades 1-5) were evaluated via multivariate ordinal logistic regression analysis that adjusted for tumor volume, skull base location, calcification status, and WHO grade. Secondary receiver operating characteristic (ROC) curve analyses were performed to differentiate solid (Zada grades 4-5) from soft (Zada grades 1-2) tumors. ROC analyses were performed within the study cohort and were intended as exploratory assessments of discriminative performance. RESULTS: The mean ADC (ADCmean) and the 10th percentile of the ADC decreased significantly with increasing WHO grade (p < 0.001). ADCmean had a moderate inverse correlation with the Ki-67 index (r = -0.42, p < 0.001) and intraoperative tumor consistency (r = -0.45, p < 0.001). In the multivariate analysis, the ADCmean remained independently associated with increasing tumor firmness. Each 0.1 × 10-3 mm2/sec increase corresponded to a 38% reduction in the odds of belonging to a higher consistency category (OR 0.62, 95% CI 0.51-0.74, p < 0.001). The ROC analysis showed good discrimination for solid tumors (area under the curve 0.847, 95% CI 0.742-0.953) and soft tumors (area under the curve 0.824, 95% CI 0.714-0.935). Texture features had weaker associations with intraoperative tumor consistency. CONCLUSIONS: Volumetric diffusion-derived metrics, particularly ADCmean, are associated with both histopathological aggressiveness and intraoperative tumor firmness in meningiomas. Diffusion imaging may reflect a graded microstructural continuum rather than a purely dichotomous property, providing complementary preoperative insights into surgical complexity.

Humans↗

PubMed2026

Fluoropyrimidine Cardiotoxicity: Role of Uridine Triacetate and Pharmacogenomic Insights from a Case of 5-FU-Induced Cardiogenic Shock.

Fluoropyrimidines, including 5-fluorouracil and capecitabine, are widely used antimetabolite agents and remain central to the treatment of several solid tumors, particularly gastrointestinal malignancies. However, they are a well-established cause of chemotherapy-related cardiotoxicity. Although coronary vasospasm is the best recognized manifestation, fluoropyrimidine cardiotoxicity encompasses a broad clinical spectrum, ranging from chest pain and arrhythmias to acute heart failure, and, rarely, fulminant cardiogenic shock. This review discusses severe fluoropyrimidine-associated cardiotoxicity through the illustrative presentation of a young woman without previous cardiovascular disease who developed acute biventricular dysfunction and cardiogenic shock shortly after first exposure to FOLFIRINOX, requiring temporary mechanical circulatory support. Administration of uridine triacetate within the recommended therapeutic window was associated with rapid recovery of ventricular function. Cardiac magnetic resonance imaging demonstrated diffuse myocardial edema without late gadolinium enhancement, consistent with reversible toxic-inflammatory myocardial injury. Expanded genomic analysis identified dihydropyrimidine dehydrogenase and thymidylate synthase variants not detected by standard pretreatment pharmacogenetic screening. In this study we examine the pathophysiological mechanisms of fluoropyrimidine cardiotoxicity, the rationale for uridine triacetate in severe presentations, and the potential role of expanded pharmacogenomic profiling within a precision cardio-oncology framework.

Humans↗

PubMed2026

Genetic Correlation Between Brain Imaging Phenotypes and Externalizing Behavior: A Large-Scale LDSC Analysis of UK Biobank IDPs.

Externalizing has been associated with differences in brain structure and function; however, it remains unclear whether these associations reflect shared common-variant genetic influences. Cross-trait linkage disequilibrium score regression was used to estimate genome-wide genetic correlations between externalizing genome-wide association study (GWAS) results and 3,935 brain imaging-derived phenotypes from the UK Biobank BIG40 resource. The imaging phenotypes covered structural magnetic resonance imaging (MRI), diffusion MRI, susceptibility-weighted imaging, resting-state functional MRI, and task-based functional MRI. Results were included in the primary analysis when the imaging phenotype had positive single-nucleotide polymorphism (SNP) heritability, a heritability Z statistic of at least 1.96, a mean GWAS chi-square statistic of at least 1.02, at least 200,000 regression SNPs, and a complete LDSC result without a fatal error. Technical imaging quality-control phenotypes were excluded from biological inference. Individual results were corrected using the Benjamini-Hochberg false discovery rate procedure. Aggregated Cauchy association tests (ACATs) were used to evaluate evidence across all imaging phenotypes and within predefined imaging categories. Statistical power, simultaneous confidence bounds, and alternative quality-control definitions were examined in sensitivity analyses. Of the 3,935 imaging phenotypes, 3,716 produced estimable genetic correlations, 2,980 met the primary LDSC quality-control criteria, and 2,967 were classified as biological imaging phenotypes. No individual phenotype survived false discovery rate correction. The smallest unadjusted P value was 0.0005, and the minimum adjusted q value was 0.486. The distribution of genetic correlations was centered near zero, with a median genetic correlation of 0.0014 and a median absolute genetic correlation of 0.0338. ACAT provided no evidence of an aggregate association across all biological imaging phenotypes (P = 0.302), and no predefined imaging category survived multiple-testing correction. The median minimum detectable genetic correlation at 80% power was 0.216. Bonferroni-adjusted simultaneous confidence intervals were fully contained within the interval [-0.30, 0.30] for 80.0% of phenotypes in the primary analysis and 88.0% under the stringent heritability quality-control definition. Broad and stringent sensitivity analyses produced the same overall conclusions. In this study, no statistically robust evidence of genome-wide genetic correlations between externalizing and individual UK Biobank brain imaging phenotypes was found. Nevertheless, small, localized, mixed-direction, or developmentally specific genetic effects remain possible.

Journal Article↗

PubMed2025

Diffusion tensor imaging in Chediak Higashi Disease.

AIM: To define the natural history of diffusion tensor imaging (DTI) in Chediak-Higashi Disease (CHD) participants in relation to normative development. METHODS: Twenty-five DTI scans from 15 CHD participants were compared with 100 DTI scans from 100 neurotypical controls (NC). Comparisons were evaluated for DTI metrics including fractional anisotropy (FA), and mean, axial, and radial diffusivity (MD, AD, RD, respectively). Correlational tractography was also performed to identify group differences between CHD and NC. RESULTS: Pediatric CHD participants had DTI metrics similar to NC, however, progressive pathogenic increases in MD, AD, and RD were observed in CHD participants compared to NC in white matter pathways of the whole brain, corpus callosum, and cerebellum. Correlational fiber tractography identified fiber tracts with decreased FA, and increased MD, AD, and RD in CHD compared to NC. INTERPRETATION: Progressive deviations in DTI metrics highlight the progressive neurodegeneration of CHD. Aberrations in cerebellar white matter is reflective of the clinical neurologic phenotype of CHD including cerebellar dysfunction and cognitive decline. The corollary of progressive aberrations in DTI metrics and progressive clinical neurodegeneration suggest DTI may be a suitable neuroimaging marker for CHD. Future studies should evaluate functional magnetic resonance imaging and volumetric studies in this cohort.

Chediak-Higashi Disease↗

PubMed2026

Quality assessment, prognostic factors, and biomarkers for brain tumor analysis: a comprehensive systematic review.

The brain tumors possess different causative factors and properties, making their diagnosis and treatment difficult. Growth of these cancers usually leads to compression of the adjacent nerves and obstruction of the flow of cerebrospinal fluid, thus leading to increase in intracranial pressure. This affects the working of brain in many ways; thus, the difficulty involved in its treatment. With the improvements in technology in neuroimaging, including Diffusion Tensor Imaging (DTI), Positron Emission Tomography (PET), and multiparametric Magnetic Resonance Imaging (mpMRI), the diagnosis process has become easy. The effectiveness of any form of therapy in such patients depends primarily on their prognosis. While it is a common practice that physicians determine the prognosis of the disease by considering the age of the patient, histological grade of the tumor, and resection status, now this method has become more comprehensive by adding molecular signature and genetic analyses to the list of criteria. Next-generation sequencing (NGS) allows a reliable molecular classification. It increases the level of risk stratification, facilitating the application of therapies tailored to individual patients. Thus, molecular oncology has greatly changed our views on brain tumors' pathology and prognosis while neoadjuvant treatments aim at increasing the survival rate. On the other hand, radiogenomics is a field of study that combines non-invasive imaging phenotypes and genomic information in order to find unique molecular signatures of tumors without collecting samples from tumors. Molecular biomarkers are absolutely essential in the diagnosis of cancer, treatment monitoring, and recurrence of cancer. Advances in liquid biopsy technology, particularly the methods for circulating tumor DNA (ctDNA) and Extracellular Vesicle (EV) based analysis, have enabled the possibility of non-invasive monitoring of the progression of the tumors over time. This review highlights key studies and important scientific works about imaging technologies, biomarkers, and prognostic factors of malignant brain tumors.

Humans↗

PubMed2026

Proteomic profiling identifies systemic drivers of blood-brain barrier injury in sickle cell disease.

Sickle cell disease (SCD) causes brain injury and cognitive disability. Systemic inflammation and endothelial injury are central to SCD pathophysiology, yet the relationship between systemic drivers of blood-brain barrier (BBB) disruption and brain injury remains understudied. This cross-sectional study assessed whole-brain and regional BBB permeability (Ktrans) using dynamic contrast-enhanced magnetic resonance imaging for 37 adults with SCD in steady state and 37 adults without SCD. Cerebral oxygen extraction fraction (OEF) and white matter mean diffusivity (MD) measured tissue hypoxia and microstructural injury, respectively. The SCD cohort showed elevated Ktrans compared with controls (3.6 × 10-4·min-1 vs 2.58 × 10-4·min-1; 95% confidence interval [CI] median difference, 0.36 × 10-4·min-1 to 1.30 × 10-4·min-1; P< .001), indicating BBB disruption. In SCD, white matter Ktrans was associated with MD (β, 6.25 [95% CI, 1.72-10.77]; P = .008), independent of OEF (β, 0.22 [95% CI, 0.09-0.35]), and silent cerebral infarcts (β, 0.01 [95% CI, 0.00-0.02]). The interaction (P = .037) between Ktrans and OEF on MD suggested a combined, deleterious effect of BBB disruption and hypoxia on microstructural injury. High-throughput plasma proteomics followed by differential expression analysis, and weighted gene correlation network analysis in a subset of 61 participants revealed that 79 proteins associated with BBB permeability belonged to iron homeostasis, response to hypoxia, immune dysregulation, extracellular matrix degradation, lipoprotein homeostasis, and arginine-proline metabolism pathways. All pathways were independently associated with microstructural injury. BBB permeability was a mediator of brain injury for all pathways except extracellular matrix degradation. Targeting specific systemic pathways to protect the BBB may represent a therapeutic approach to preserve brain health in SCD.

Humans↗

PubMed2025

Predicting telomerase reverse transcriptase promoter mutation status in glioblastoma by whole-tumor multi-sequence magnetic resonance texture analysis.

OBJECTIVE: This study aimed to determine the feasibility of preoperative multi-sequence magnetic resonance texture analysis (MRTA) for predicting TERT promoter mutation status in IDH-wildtype glioblastoma (IDHwt GB). METHODS: The clinical and imaging data of 111 patients with IDHwt GB at our hospital between November 2018 and June 2023 were retrospectively analyzed as the training set, and those of 23 patients with IDHwt GB between July 2023 and November 2023 were interpreted as the validation set. We used molecular sequencing results to classify the training set into TERT promoter mutation and wildtype groups. Textural features of the whole-tumor volume were extracted, including T2-weighted imaging (T2WI), T2-fluid-attenuated inversion recovery, apparent diffusion coefficient (ADC) map, and contrast-enhanced T1-weighted imaging (CE-T1). All textural features were obtained using open-source pyradiomics. After feature selection, logistic regression was used to build prediction models, and a nomogram was generated. Finally, the model was validated using validation cohort. RESULTS: The CE-T1_Model (AUC 0.704) had a better predictive ability than the T2_Model (AUC 0.684) and ADC_Model (AUC 0.624). The MRI_Combined_Model (CE-T1, T2, and ADC texture features) (AUC 0.780) had a better predictive ability than the Clinical_Model (AUC 0.758). The Combined_Model (CE-T1, T2, ADC texture features, and clinical features) had the best predictive performance (AUC 0.871), with a sensitivity, specificity, and accuracy of 82.60 %, 83.30 %, and 80.18 %, respectively. The AUC, sensitivity, specificity, and accuracy in the validation cohort were 0.775, 86.70 %, 75.00 %, and 69.57 %, respectively. CONCLUSIONS: Whole-tumor multi-sequence MRTA can be used as non-invasive quantitative parameters to assist in the preoperative clinical prediction of TERT promoter mutation status in IDHwt GB.

Humans↗

PubMed2026

Enhanced risk stratification in hypertrophic cardiomyopathy through the integration of extracellular volume fraction on cardiovascular magnetic resonance.

AIMS: This study investigated the incremental prognostic value of cardiovascular magnetic resonance (CMR)-derived extracellular volume fraction (ECV), a marker of diffuse interstitial fibrosis, beyond late gadolinium enhancement (LGE) in hypertrophic cardiomyopathy (HCM). METHODS AND RESULTS: We analysed 990 consecutive HCM patients (median age 58 years, male 68.3%) who underwent CMR between 2012 and 2024. LGE and global ECV were quantified, and their associations with the primary endpoint of HCM-related events-a composite of sudden cardiac death (SCD) events, heart failure (HF) events, and HCM-related death-were assessed. During a median follow-up of 3.2 years, 64 (6.5%) patients experienced the primary endpoint. While LGE (median 7.1%, IQR 2.3-16.9%) and ECV (median 29.0%, IQR 26.6-32.0%) were moderately correlated (R = 0.604, P < 0.001), both were significantly associated with increased risk of the primary endpoint and individual outcomes of SCD and HF events, and optimal cutoffs were determined as LGE ≥ 27% and ECV ≥ 35%. Patients with ECV ≥ 35% had more symptoms, a more severe phenotype with greater systolic and diastolic dysfunction, and more pathogenic gene variants. Notably, ECV remained a significant predictor of the primary endpoint (adjusted HR 1.08, 95% CI 1.02-1.15, per 1%) after adjustment for key disease variables, including left ventricular ejection fraction and LGE. Elevated ECV effectively identified high-risk individuals even among lower-risk subgroups, including those with low LGE burden. CONCLUSION: Increased ECV is an independent predictor of HCM-related outcomes. ECV may serve as a novel imaging biomarker to refine risk stratification in HCM patients who do not meet traditional LGE-based high-risk criteria.

Humans↗

PubMed1978

Rate-determining processes in the transport of Pr3+ ions by the ionophore A23187 across phospholipid vesicular membranes. A 1H-MR and theoretical study.

Rate constants and activation parameters have been determined for the transport of Pr3+ ions by the ionophore A23187 across dipalmitoyl phosphatidylcholine vesicular membranes. The novel method described depends on the measurement of changes in chemical shift of the 1H-NMR choline head-group signals as Pr3+ is transported from outside to inside the vesicles. The determined rates are directly proportional to A23187 concentration, suggesting that the rate-determining step involves the species [Pr(A23187)](2+). A theoretical analysis of the initial stages of Pr3+ transport leads to the conclusion that diffusion over the image potential barrier is the rate-determing step. Calculation of the form and height of this barrier for the non-equilibrium state gives results which agree well with the experimental activation energy and also correctly predict a two-fold reduction in rate of transport when 7 mol % decane is present in the bilayer.

Anti-Bacterial Agents↗

PubMed2025

Robot-Assisted Stereotactic Aspiration of a Parietal Brain Abscess With Metagenomic Identification of Fusobacterium nucleatum.

Robot-assisted stereotactic aspiration offers a minimally invasive approach to brain abscesses near the eloquent cortex. We report a rare case of a left parietal abscess caused by Fusobacterium nucleatum in an immunocompetent adult, managed successfully with this approach. The patient, a 52-year-old man, presented with right-sided limb numbness. MRI and contrast-enhanced CT revealed a cystic, ring-enhancing lesion with diffusion restriction in the left parietal lobe. Despite empiric broad-spectrum antibiotics, neurological deterioration occurred due to progressive mass effect. Robot-assisted stereotactic aspiration enabled single-stage, precise drainage of the abscess. Metagenomic next-generation sequencing identified F. nucleatum , prompting adjustment of antibiotics to ceftriaxone plus metronidazole, followed by metronidazole monotherapy. The patient improved clinically, and a 6-month MRI confirmed complete resolution, underscoring the precision of robotic stereotaxy for eloquent-region abscesses and highlighting the diagnostic value of metagenomic sequencing in detecting anaerobic pathogens.

Humans↗

PubMed2025

Radiogenomic MRI biomarkers for noninvasive prediction of GPC3 expression and tumor microenvironment in hepatocellular carcinoma.

BACKGROUND: Glypican-3 (GPC3) is frequently overexpressed in hepatocellular carcinoma (HCC) and plays a key role in immune and metabolic remodeling of the tumor microenvironment. Reliable noninvasive biomarkers for predicting GPC3 status could improve patient stratification and support precision immunotherapy. METHODS: This multicenter retrospective study included 274 patients with pathologically confirmed hepatocellular carcinoma from three institutions, 34 external cases with MRI from The Cancer Imaging Archive, and 363 transcriptomic profiles from The Cancer Genome Atlas. Contrast-enhanced T1-weighted imaging and diffusion-weighted imaging were analyzed. Tumor and peritumoral regions were segmented manually and radiomic features extracted using PyRadiomics. Feature selection was performed with correlation filtering and least absolute shrinkage and selection operator regression. Machine learning classifiers including logistic regression, random forest, support vector machine, k-nearest neighbor, and decision tree were trained with 10-fold cross-validation and tested on independent external cohorts. A radiomics score was calculated for each patient. Radiogenomic analysis correlated radiomics scores with transcriptomic data using weighted gene co-expression network analysis. Hub genes and enriched pathways were identified, and immune infiltration and predicted immunotherapy response were assessed using computational methods. RESULTS: The random forest model using contrast-enhanced T1-weighted imaging achieved an area under the curve of 0.966 in training and 0.935 in internal validation. The integrated contrast-enhanced T1-weighted imaging plus diffusion-weighted imaging model reached an internal validation area under the curve of 0.979. In external testing, the best performance was obtained with a support vector machine model (area under the curve 0.756). Radiomics scores were significantly correlated with GPC3 expression (R = 0.78, p < 0.05). Transcriptomic analysis identified a 10-gene signature enriched in hypoxia and lipid metabolism pathways that stratified patients into prognostic subgroups (concordance index 0.720, hazard ratio 4.07, p < 0.0001). High-risk patients had greater immune infiltration and a lower predicted immune evasion score, suggesting a potential benefit from immunotherapy. CONCLUSIONS: MRI-based radiomics models can noninvasively predict GPC3 expression in hepatocellular carcinoma. Radiomics scores reflect underlying hypoxia and lipid metabolism pathways and stratify patients by prognosis and predicted immunotherapy response. These findings support radiogenomics as a translational approach to imaging-guided precision treatment in hepatocellular carcinoma.

Humans↗

PubMed2026

Phase-resolved functional lung MRI detects single-dose and sustained bronchodilator responses in COPD in a randomized crossover trial.

OBJECTIVES: To evaluate the effects of tiotropium/olodaterol (T/O) on phase-resolved functional lung (PREFUL) MRI parameters in hyperinflated chronic obstructive pulmonary disease (COPD) patients and examine correlations with conventional cardiopulmonary and hyperpolarized 129Xe MRI measures. MATERIALS AND METHODS: Retrospective subanalysis of a prospective, randomized, placebo-controlled, crossover trial with open-label extension. Thirty-two patients with moderate-to-severe COPD (61.5 ± 7.7 years; 17 men); 30 completed the MRI extension at 1.5 T. PREFUL analysis yielded regional ventilation (RVent), flow-volume loop correlation metric (FVL-CM), normalized perfusion (QN), ventilation defect percentage (VDP), perfusion defect percentage (QDP), V/Q match metrics (VQM), and pulmonary pulse wave velocity (PWV; post-hoc parameter). Linear mixed-effects models tested treatment effects; correlations were evaluated with Spearman's rank and bootstrap 95% confidence intervals (95% CIs). RESULTS: PREFUL parameters improved after T/O single dose (SD) versus placebo, including improvements in FVL-CM by 4.1 percentage points (pp; 95% CI: 1.0 to 7.3 pp) and QN by 0.4 pp (95% CI: 0.2 to 0.6 pp) and reductions in VDP and QDP, with parallel gains in VQM(Non-Defect) (p < 0.05). PWV decreased after multiple doses (-0.87 m/s, 95% CI: -1.26 to -0.48 m/s). PREFUL MRI baseline values showed significant correlations with pulmonary function tests, cardiac, dynamic contrast-enhanced and 129Xe MRI. SD treatment-induced absolute changes in VDP(FVL-CM) correlated with reductions in residual volume (ρ = 0.41, 95% CI: 0.02 to 0.64). Further correlations were observed between PREFUL MRI and ¹²⁹Xe-derived VDP, apparent diffusion coefficient, and compartment ratios. CONCLUSION: PREFUL MRI sensitively captured immediate SD T/O-induced improvements in V/Q parameters and dose-dependent PWV responses after sustained bronchodilation. KEY POINTS: Question Can phase-resolved functional lung (PREFUL) MRI sensitively capture immediate single-dose and sustain multi-dose effects of tiotropium/olodaterol on ventilation-perfusion and vascular function in COPD patients? Findings Tiotropium/olodaterol improved PREFUL MRI-derived ventilation, perfusion, and V/Q matching parameters after a single dose, with sustained pulmonary vascular improvements after repeated dosing. Clinical relevance PREFUL MRI detected immediate and sustained functional improvements after tiotropium/olodaterol and showed significant correlations with cardiopulmonary tests and hyperpolarized ¹²⁹Xe MRI, supporting its role as a sensitive, radiation-free tool for monitoring COPD treatment response.

Humans↗

PubMed2026

Glymphatic dysfunction mediates inflammation-driven vascular burden and cognitive decline in cerebral small vessel disease.

BACKGROUND: Cerebral small vessel disease (CSVD) is increasingly recognized as a disorder involving microvascular dysfunction, impaired perivascular clearance, and inflammatory processes. However, how systemic inflammatory burden, neurovascular coupling (NVC), glymphatic MRI markers, vascular lesion burden, and cognition are interrelated remains unclear. MATERIALS AND METHODS: In this prospective study, 155 patients with CSVD and 70 healthy controls (HCs) underwent multimodal MRI. NVC was quantified using the cerebral blood flow/fractional amplitude of low-frequency fluctuations ratio. Glymphatic function was assessed via the diffusion tensor image analysis along the perivascular space (ALPS) index, choroid plexus volume (CPV), and perivascular space (PVS) fractions. Structural equation modeling (SEM) was employed to evaluate the direct and indirect effects of inflammatory markers on vascular burden and cognitive performance. RESULTS: Patients with CSVD exhibited significantly diminished NVC (specifically in the right median cingulate and left frontal gyri) and impaired glymphatic function (lower ALPS-index; higher CPV and PVS fractions) compared to HCs. SEM revealed that inflammatory biomarkers exerted both a direct effect on vascular burden and a substantial indirect effect (accounting for 66.3% of the total effect) mediated through two pathways: a single-mediation path via glymphatic function (42.8%) and a serial-mediation path via NVC and glymphatic function (23.5%). Increased vascular burden was significantly associated with poorer cognitive performance. CONCLUSION: Inflammation drives CSVD progression and cognitive decline primarily through the disruption of NVC and glymphatic clearance mechanisms. These findings highlight glymphatic dysfunction as a critical mediator of inflammation-related structural brain damage.

Humans↗

PubMed2026

Integrating Radiogenomics and CSF-Based Liquid Biopsy Sequencing for Precision Neuro-Oncology.

Glioblastoma and diffuse gliomas pose major therapeutic challenges due to marked intratumoral heterogeneity, limited tissue accessibility, and the blood-brain barrier. Tissue-based next-generation sequencing (NGS) remains essential for WHO CNS5 molecular classification, yet it is invasive and poorly suited to serial monitoring. Two complementary non- or minimally invasive approaches have advanced rapidly: radiogenomics, which correlates multiparametric MRI features with genomic alterations, and cerebrospinal fluid (CSF) liquid biopsy sequencing, which detects circulating tumor DNA with high tissue concordance. This review examines the independent progress and synergistic integration of radiogenomics and CSF-NGS. Imaging signatures can non-invasively predict key drivers (IDH1/2, EGFR, TERT, PTEN, TP53) and molecular subtypes, while CSF-ctDNA sequencing enables real-time assessment of clonal evolution, therapy resistance (including post-temozolomide hypermutation), and residual disease. We discuss technical considerations, performance metrics, multimodal artificial-intelligence fusion, and emerging clinical applications for diagnosis, prognosis, treatment selection, and longitudinal surveillance. Critical challenges, standardization, prospective validation, and workflow integration are highlighted. By combining the spatial phenotypic information of radiogenomics with the temporal genomic resolution of CSF sequencing, this multimodal strategy offers a promising path toward precision neuro-oncology and reduced reliance on repeated invasive sampling.

Humans↗