Journal of Neuroimaging最新文献

Background and Purpose

Differentiation between functioning and nonfunctioning pituitary adenomas/pituitary neuroendocrine tumors (PAs) is clinically relevant. The goal of this study was to determine the feasibility of using time-dependent diffusion MRI (dMRI) for microstructural characterization of PAs.

Methods

The study included 54 participants, 24 with functioning PA and 30 with nonfunctioning PA. Time-dependent dMRI of the pituitary gland was performed using an inner field-of-view echo-planar imaging based on 2-dimensional-selective radiofrequency excitations with oscillating gradient and pulsed gradient preparation (effective diffusion time: 7.1 and 36.3 ms) at b-values of 0 and 1000 seconds/mm². Each tumor had its apparent diffusion coefficients (ADCs) measured at two diffusion times (ADC_7.1 ms and ADC_36.3 ms), its ADC change (cADC), and relative ADC change. The mean values of diffusion parameters were compared between functioning and nonfunctioning PAs. We compared the diffusion parameters of nonfunctioning PAs with those of each type of hormone-producing PAs. The diagnostic performances of the diffusion parameters were assessed.

Results

The cADC was significantly higher in functioning PAs than nonfunctioning PAs (p = .0124). The receiver operating characteristic (ROC) curve analysis revealed that cADC (area under the ROC curve [AUC] = .677, p = .017) is effective in distinguishing between functioning and nonfunctioning PAs. The cADC was significantly higher in growth hormone (GH)-producing PAs compared to nonfunctioning PAs (p = .006). The ROC curve analysis indicated that cADC (AUC = .771, p < .001) effectively distinguishes between GH-producing and nonfunctioning PAs.

Conclusions

The cADC derived from time-dependent dMRI could distinguish between functioning and nonfunctioning PAs, particularly those producing GH.

Multiple sclerosis-related cognitive impairment (MSrCI) affects most patients with multiple sclerosis (MS), significantly contributing to disability and socioeconomic challenges. MSrCI manifests across all disease stages, mainly impacting working memory, information processing, and attention. To date, the underlying mechanisms of MSrCI remain unclear, with its pathogenesis considered multifactorial. While conventional MRI findings correlate with MSrCI, there is no consensus on reliable imaging metrics to detect or diagnose cognitive impairment (CI). Functional MRI (fMRI) has provided unique insights into the brain's neuroplasticity mechanisms, revealing evidence of compensatory mechanisms in response to tissue damage, both beneficial and maladaptive. This review summarizes the current literature on the application of resting-state fMRI (rs-fMRI) and task-based fMRI (tb-fMRI) in understanding neuroplasticity and its relationship with cognitive changes in people with MS (pwMS). Searches of databases, including PubMed/Medline, Embase, Scopus, and the Web of Science, were conducted for the most recent fMRI cognitive studies in pwMS. Key findings ifrom rs-fMRI studies reveal disruptions in brain connectivity and hub integration, leading to CI due to decreased network efficiency. tb-fMRI studies highlight abnormal brain activation patterns in pwMS, with evidence of increased fMRI activity in earlier disease stages as a beneficial compensatory response, followed by reduced activation correlating with increased lesion burden and cognitive decline as the disease progresses. This suggests a gradual exhaustion of compensatory mechanisms over time. These findings support fMRI not only as a diagnostic tool for MSrCI but also as a potential imaging biomarker to improve our understanding of disease progression.

Background and Purpose

Neuromix is a fast, motion robust multi-contrast sequence capable of providing all diagnostic contrasts in ∼3.5 minutes. However, more evaluation is needed across the various contrasts compared to gold standard, optimized sequences routinely used in the clinic. The goal of this study was to prospectively determine how NeuroMix performs in the clinical setting compared to routine clinical MRI.

Methods

NeuroMix and routine clinical MRI sequences were acquired on a 3 Tesla clinical scanner for 39 patients clinically indicated for brain MRI. Three radiologists were asked to assess the diagnostic confidence of NeuroMix compared to the routine MRI using a series of questions. Signal-to-noise and contrast-to-noise ratios (SNR and CNR) were assessed for NeuroMix. Fleiss’ free-marginal multirater kappa was calculated for the qualitative assessment performed by the radiologists.

Results

Radiologists were comfortable substituting or reading some of the NeuroMix sequences in place of the corresponding conventional sequence for some contrasts, including diffusion-weighted imaging, single-shot T₂, and susceptibility-weighted imaging. The image quality, SNR, and CNR allowed the radiologists to visualize anatomy and pathology on NeuroMix images. There was no significant difference between coefficient of variation for the apparent diffusion coefficient maps (p = .084).

Conclusions

Analysis revealed both positives and some pitfalls of NeuroMix. However, these results indicate Neuromix as having the capability to be a backup sequence in case artifacts are present in routine sequences, or potentially a replacement for some contrasts altogether.

Background and Purpose

Neuromyelitis optica spectrum disorder (NMOSD) affects the optic nerves and spinal cord but can also cause focal brain inflammation. Subcortical pathology may contribute to the etiology of cognitive deficits in NMOSD. Using myelin water imaging, we investigated cerebral normal-appearing white matter (NAWM) and thalamic metrics and their association with cognition in NMOSD participants compared to healthy controls (HC).

Methods

Seventeen NMOSD participants and 21 HC were scanned on a 3.0-Tesla MRI scanner using a multicomponent driven-equilibrium single-pulse observation of T₁ and T₂ protocol. Tissue compartment and thalamic volumes (normalized to intracranial volume), T₁ relaxation time, and myelin water fraction (MWF) were reported. Eleven NMOSD participants underwent the Symbol Digit Modalities Test (SDMT) for cognitive evaluation. Group comparisons were performed using Student's t-test. The association between thalamic metrics and SDMT score was assessed using multiple regression analysis with age as a covariate.

Results

Compared to HC, NMOSD participants had reduced white matter volume (−14.2%, p < .0001), increased T₁ relaxation time (+2.29%, p = .022), and lower MWF (−3.64%, p = .024) in NAWM. NMOSD group had a trend for smaller thalamic volumes than HC (−5.52%, p = .082) and no differences in thalamic MWF (p = .258) or T₁ (p = .714). Thalamic T₁ predicted SDMT score (adjusted R² = .51, p = .04) when controlling for age.

Conclusions

NAWM in NMOSD demonstrates diffuse abnormalities with increased water content and demyelination, suggesting a diffuse disease process overlooked by focal inflammation measures. Increased water content, as a biomarker for diffuse thalamic pathology, may partially explain cognitive impairment in NMOSD.

Background and Purpose

Different types of physical training can lead to changes in brain activity and function, and these changes can vary depending on the type of training. However, it remains unclear whether there are commonalities in how different types of training affect brain activity and function. The purpose of this study is to compare the brain activity states of professional athletes with those of ordinary university students and to explore the relationship between training and differences in brain activity states.

Methods

This study primarily utilizes resting-state MRI and the degree centrality metric to investigate spontaneous brain activity in 86 high-level athletes with extensive training and 74 age- and gender-matched nonathletes. Additionally, a correlation analysis between brain activity in relevant regions and years of training was conducted.

Results

The analysis revealed that, compared to nonathletes, high-level athletes exhibited reduced activity in the Calcarine (a visual area) and Middle Temporal Gyrus. Furthermore, changes in the activity of the Calcarine and Middle Temporal Gyrus were significantly correlated with the number of years of professional training.

Conclusions

The study results indicate that long-term physical training is associated with changes in brain activity in athletes, providing insights into the neural mechanisms underlying behavioral performance in professional athletes.

Background and Purpose

The absence of a consensus data quality control (DQC) process inhibits the widespread adoption of MR spectroscopy. Poor DQC can lead to unreliable clinical diagnosis and irreproducible research conclusions. Currently, manual visual assessment or the standard quantitative metrics of signal-to-noise, linewidth, and model fit are used as classifiers, but these measures may not be sufficient. To supplement standard metrics, this paper proposes a novel automated DQC pipeline named Visual Evaluative Control Technology Of Resonance Spectroscopy (VECTORS).

Methods

Manual DQC ratings were conducted on 7180 spectra obtained from 110 young adults using short-echo chemical shift imaging at 3 Tesla. Four reviewers conducted manual ratings on the presence of artifacts and location of metabolites. The ratings were labor intensive, taking over 180 hours. VECTORS was developed to quantify their DQC criteria, detecting artifacts that present as duplicate peaks, vertical shifts, and glutamine + glutamate and myoinositol peak shapes. Run on the same data using a standard laptop, VECTORS only took 2 hours.

Results

The manual ratings were not monotonic to the standard quantitative metrics. VECTORS correctly flagged spectra that the manual ratings missed. VECTORS accurately flagged an additional 126 poor DQ spectra that consensus cutoffs of the standard quantitative metrics deemed good DQ.

Conclusion

Standard quantitative metrics may not account for all DQC artifacts as they are not monotonic to the manual ratings. However, manual ratings are labor intensive, subjective, and irreproducible. VECTORS addresses these issues and should be used in conjunction with standard quantitative metrics.

Background and Purpose

Sonothrombolysis is a potential adjunctive therapy for large vessel occlusion (LVO) stroke. Bedside ultrasound image-guided high-intensity focused ultrasound (HIFU) therapy could deliver higher energy therapeutic ultrasound to the thrombus with higher precision than what was previously accomplished in human trials. The aim is to test the feasibility of diagnostic transcranial contrast-enhanced ultrasound (CEUS) to image the occlusion site and continuously maintain the guidance image on-target for a sufficient exposure time for HIFU to be effective during LVO stroke evaluation and treatment.

Methods

This prospective, single center, observational cohort study included adult patients, presenting within 6 hours of stroke symptom onset, with LVO identified on computed tomography angiography (CTA). A hand-held CEUS imaging study was initiated following CTA and lasted up to 30 minutes. The primary outcome is the proportion of patients where a guidance CEUS image of the occlusion was achieved.

Results

A CEUS image of the occluded artery was obtained in 32/35 of the included patients. The median total imaging time was 23 minutes (interquartile range 15-30). Patients undergoing thrombectomy had a lower total imaging time (17 vs. 29.5 minutes, p = .002). When imaging was successful, on-target image was maintained for only 58% (standard deviation 23.8%) of total imaging time. No complications related to CEUS were observed.

Conclusions

This feasibility study explored the use of diagnostic transcranial CEUS for continuous imaging of occlusion sites in LVO strokes. Challenges in maintaining target image during HIFU were identified, highlighting the need for technical advances for clinical application.

Background and Purpose

Carotid artery stenosis is a major risk factor for ischemic stroke. Despite carotid artery stenting, in-stent restenosis (ISR) remains challenging. Pigs serve as an ideal ISR model. This study aims to establish a novel porcine model of carotid ISR using open-loop and closed-loop stents and to assess ISR with optical coherence tomography (OCT) and histopathology, comparing incidence and vascular response between stent types.

Methods

Twelve adult male Bama miniature pigs underwent carotid stenting with either open-loop or closed-loop stents. The animals received antiplatelet therapy pre- and postimplantation. Postimplantation evaluations at 90 days included carotid digital subtraction angiography (DSA), OCT, histopathological examination, and electron microscopy.

Results

Both stent types showed ISR as detected by OCT and DSA. OCT revealed comparable neointimal proliferation within stent struts for both types, with no significant differences in stent, lumen, and neointimal dimensions. Histopathological analysis and electron microscopy provided insights into tissue responses and healing processes following stent implantation. No significant difference in ISR incidence was found between the stent types based on a χ² test (p = .110). OCT and hematoxylin-eosin staining exhibit the highest consistency in evaluating neointimal area.

Conclusions

The novel porcine ISR model demonstrated similar ISR outcomes for open-loop and closed-loop stents. OCT proved to be a highly consistent and valuable tool for evaluating stent and arterial conditions, comparable to histopathological findings. However, due to a small sample size, the validity of these preliminary findings requires further investigation to be confirmed.

Background and Purpose

Paramagnetic rim lesions (PRLs) are an MRI biomarker of chronic inflammation in people with multiple sclerosis (MS). PRLs may aid in the diagnosis and prognosis of MS. However, manual identification of PRLs is time-consuming and prone to poor interrater reliability. To address these challenges, the Automated Paramagnetic Rim Lesion (APRL) algorithm was developed to automate PRL detection. The primary objective of this study is to evaluate the accuracy of APRL for detecting PRLs in a multicenter setting.

Methods

We applied APRL to a multicenter dataset, which included 3-Tesla MRI acquired in 92 participants (43 with MS, 14 with clinically isolated syndrome [CIS]/radiologically isolated syndrome [RIS], 35 without RIS/CIS/MS). Subsequently, we assessed APRL's performance by comparing its results with manual PRL assessments carried out by a team of trained raters.

Results

Among the 92 participants, expert raters identified 5637 white matter lesions and 148 PRLs. The automated segmentation method successfully captured 115 (78%) of the manually identified PRLs. Within these 115 identified lesions, APRL differentiated between manually identified PRLs and non-PRLs with an area under the curve (AUC) of .73 (95% confidence interval [CI]: [.68, .78]). At the subject level, the count of APRL-identified PRLs predicted MS diagnosis with an AUC of .69 (95% CI: [.57, .81]).

Conclusion

Our study demonstrated APRL's capability to differentiate between PRLs and lesions without paramagnetic rims in a multicenter study. Automated identification of PRLs offers greater efficiency over manual identification and could facilitate large-scale assessments of PRLs in clinical trials.

Background and Purpose

Lateral elbow pain is quite common in everyday life. Lateral epicondylitis and radial tunnel syndrome are the most common causes of lateral elbow pain. The aim of this study was to evaluate the sensitivity and specificity of neuromuscular ultrasound examination in the diagnosis of lateral epicondylitis versus radial tunnel syndrome.

Methods

This was a prospective double-blinded pilot study of 68 elbows in 34 patients with lateral elbow pain. Patients underwent clinical examination and standardized neuromuscular ultrasound evaluation in the first 15 days after the initiation of symptoms. Statistical significance was set at p < .001. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated.

Results

Sixty-eight radial nerves were examined in 34 healthy controls (16 males; mean age 48.1 ± 8.2 years). Pain with palpation over the radial tunnel was found in 25 of 48 elbows (52.1%) compared to the pain over the lateral epicondyle found in 10 of 48 elbows (20.8%). Τhe sensitivity of palpation in differentiating radial tunnel syndrome from lateral epicondylitis was 75.7%, while the specificity was 50% (PPV 71.4%, NPV 51.5%). The sensitivity of neuromuscular ultrasound in differentiating radial tunnel syndrome from lateral epicondylitis was 92.6%, while the specificity was 80% (PPV 92.6%, NPV 80.0%). In most of the patients (25/31), fibrous bands anterior to the radio-capitellar joint were responsible for the nerve entrapment.

Conclusions

The present study highlights the importance of the neuromuscular ultrasound's diagnostic role in differentiating radial tunnel syndrome from lateral epicondylitis in the clinical scenario of lateral elbow pain.