Neuroradiology最新文献

Purpose: The aim of our study was to assess the diagnostic performance of commercially available AI software for intracranial aneurysm detection and to determine if the AI system enhances the radiologist's accuracy in identifying aneurysms and reduces image analysis time.

Methods: TOF-MRA clinical brain examinations were analyzed using commercially available software and by an consultant neuroradiologist for the presence of intracranial aneurysms. The results were compared with the reference standard, to measure the sensitivity and specificity of the software and the consultant neuroradiologist. Furthermore, we examined the time required for the neuroradiologist to analyze the TOF-MRA image set, both with and without use of the AI software.

Results: In 500 TOF-MRI brain studies, 106 aneurysms were detected in 85 examinations by combining AI software with neuroradiologist readings. The neuroradiologist identified 98 aneurysms (92.5% sensitivity), while AI detected 77 aneurysms (72.6% sensitivity). Specificity and sensitivity were calculated from the combined effort as reference. Combining AI and neuroradiologist readings significantly improves detection reliability. Additionally, AI integration reduced TOF-MRA analysis time by 19 s (23% reduction).

Conclusions: Our findings indicate that the AI-based software can support neuroradiologists in interpreting brain TOF-MRA. A combined reading of the AI-based software and the neuroradiologist demonstrated higher reliability in identifying intracranial aneurysms as compared to reading by either neuroradiologist or software, thus improving diagnostic accuracy of the neuroradiologist. Simultaneously, reading time for the neuroradiologist was reduced by approximately one quarter.

Purpose: Normative ADC values of the pineal gland in young children are currently lacking, however, these are potentially useful in the differential diagnosis of pineal involvement in trilateral retinoblastoma, which is challenging when the size of the tumor is less than 10-15 mm. The main objective of this study was to establish ADC reference values of the normal pineal gland in a large cohort of children between 0 and 4 years.

Methods: This retrospective study was conducted in a tertiary pediatric hospital. We collected 64 patients with normal MRI examination (between 2017 and 2024) and clinical indication unrelated to the pineal gland, and divided them into 5 age groups (0 to 4 years). Gland size and mean ADC values were calculated, using the ellipsoid formula and ROI/histogram analysis, respectively. The established values were tested in three cases of trilateral retinoblastoma (10 to 20 months).

Results: Mean ADC values were always above 1000 × 10^- 6 mm²/s, while in patients with trilateral retinoblastoma they were around 800 × 10^- 6 mm²/s. Pineal ADC values were identical in both genders. The volume of the pineal gland showed a tendency to increase with age.

Conclusions: We present ADC reference data for the pineal gland in children under 4 years of age. The distribution of mean ADC values of trilateral retinoblastoma was significantly different from the normative values, hence, the use DWI/ADC may help to identify small trilateral retinoblastoma in children with ocular pathology.

The Response Assessment in Pediatric Neuro-Oncology (RAPNO) Working Group is an international, collaborative network of experts dedicated to pediatric central nervous system (CNS) tumors that was created in 2011. Since then, six RAPNO articles with imaging guidelines for response assessment in diverse pediatric tumor subgroups have been published, namely: 1) medulloblastomas and leptomeningeal seeding tumors (2018), 2) pediatric high-grade gliomas (2020), 3) pediatric low-grade gliomas (2020), 4) diffuse intrinsic pontine gliomas (2020), 5) pediatric intracranial ependymomas (2022) and 6) pediatric craniopharyngiomas (2023). The purpose of this article is to review all current available RAPNO criteria using a systematized and comparative approach centered on the role of neuroradiologists and supported by neuroimaging examples. Special emphasis will be placed on clarification of core concepts as well as practical adoption aspects of the RAPNO guidelines, namely how and when to image the brain and/or the spine; how to interpret the imaging findings; which other clinical, therapeutic and laboratory variables to consider; and finally how to apply the information to attribute the final appropriate response assessment classification.

Purpose: For nearly half of patients who undergo Endovascular Thrombectomy following ischemic stroke, successful recanalisation does not guarantee a good outcome. Understanding the underlying tissue changes in the infarct tissue with the help of biomarkers specific to ischemic stroke could offer valuable insights for better treatment and patient management decisions. Using quantitative susceptibility mapping (QSM) MRI to measure cerebral iron concentration, this study aims to track the progression of iron within the infarct lesion after successful reperfusion.

Methods: In a prospective study of 87 ischemic stroke patients, successfully reperfused patients underwent MRI scans at 24-to-72 h and 3 months after reperfusion. QSM maps were generated from gradient-echo MRI images. QSM values, measured in parts per billion (ppb), were extracted from ROIs defining the infarct and mirror homolog in the contralateral hemisphere and were compared cross-sectionally and longitudinally.

Results: QSM values in the infarct ROIs matched those of the contralateral ROIs at 24-to-72 h, expressed as median (interquartile range) ppb [0.71(-7.67-10.09) vs. 2.20(-10.50-14.05) ppb, p = 0.55], but were higher at 3 months [10.68(-2.30-21.10) vs. -1.27(-12.98-9.82) ppb, p < 0.001]. The infarct QSM values at 3 months were significantly higher than those at 24-to-72 h [10.41(-2.50-18.27) ppb vs. 1.68(-10.36-12.25) ppb, p < 0.001]. Infarct QSM at 24-to-72 h and patient outcome measured at three months did not demonstrate a significant association.

Conclusion: Following successful endovascular reperfusion, iron concentration in infarct tissue, as measured by QSM increases over time compared to that in healthy tissue. However, its significance warrants further investigation.

Introduction: Prognoses for pediatric brain tumors are suboptimal, as even in low-grade tumors, management techniques can lead to damage in the developing brain. Therefore, advanced neuroimaging methods are critical for developing optimal management plans and improving patient care. Magnetic resonance elastography (MRE) has allowed for the characterization of adult gliomas by their mechanical properties, which are uniquely sensitive to the complex interplay of cellularity, vasculature, and interstitium. However, pediatric tumors differ in behavior and cytoarchitecture, and their mechanical properties have never been assessed.

Methods: Here, we conduct the first study of pediatric brain tumor mechanical properties by using MRE to measure tissue stiffness and damping ratio in low grade gliomas (LGGs). We additionally measure the mechanical properties of non-neoplastic focal abnormal signal intensities (FASIs) in children with neurofibromatosis type 1 (NF1).

Results: 23 patients age 4-17 years who had MR imaging results consistent with a primary LGG or with NF1 were included in this study. We found that pediatric gliomas are on an average 10.9% softer (p = 0.010) with a 17.3% lower (p = 0.009) viscosity than reference tissue. Softness of tumors appeared consistent across tumor subtypes and unrelated to tumor size or contrast-enhancement. In NF1 we found that, unlike gliomas, FASIs are stiffer, though not significantly, than reference tissue by an average of 10.4% and have a 16.7% lower damping ratio.

Conclusions: Measuring tumor mechanical properties patterning and heterogeneity has potential to aid in prediction of biological behavior and inform management strategies for pediatric patients.

Background: It is difficult to distinguish between tumor progression (TP) and treatment-related abnormalities (TRA) in treated glioblastoma patients via conventional MRI, but this distinction is crucial for treatment decision making. Glioblastoma is known to exhibit an invasive growth pattern along white matter architecture and vasculature. This study quantified lesion development patterns in treated glioblastoma lesions and their relation to white matter microstructure to distinguish TP from TRA.

Materials and methods: Glioblastoma patients with confirmed TP or TRA with T1-weighted contrast-enhanced and DTI MR scans from two posttreatment follow-up timepoints were reviewed. The contrast-enhancing regions were segmented, and the regions were coregistered to the DTI data. Lesion increase vectors were categorized into two groups: parallel (0-20 degrees) and perpendicular (70-90 degrees) to white matter. FA-values were also extracted. To test for a statistically significant difference between the TP and TRA groups, a Mann‒Whitney U test was performed.

Results: Of 73 glioblastoma patients, fifteen were diagnosed with TRA, whereas 58 patients suffered TP. TP had a 25.8% (95% CI 24.1%-27.6%) increase in parallel lesions, and TRA had a 25.4% (95% CI 20.9%-29.9%) increase in parallel lesions. The perpendicular increase was 14.7% for TP (95% CI 13.0%-16.4%) and 18.0% (95% CI 13.5%-22.5%) for TRA. These results were not significantly different (p = 0.978). FA value for TP showed to be 0.248 (SD = 0.054) and for TRA it was 0.231 (SD = 0.075), showing no statistically significant difference (p = 0.121).

Conclusions: Based on our results, quantifying posttreatment contrast-enhancing lesion development directionality with DTI in glioblastoma patients does not appear to effectively distinguish between TP and TRA.

Background and objectives: Studies measuring the role of magnetic resonance imaging (MRI) in therapeutic decision-making are rare in people with multiple sclerosis (pwMS). This study aimed to measure the association between MRI utilization and disease-modifying therapy (DMT) switches in pwMS.

Methods: This retrospective cohort study identified pwMS in 2018 from a de-identified national claims database. PwMS who received MRI in 2018 were compared to pwMS not receiving MRI in 2018. PwMS were observed for six months to assess the incidence of DMT switches.

Results: The study sample consisted of 11,972 pwMS. 3,931 (32.8%) pwMS received at least one MRI in 2018. Overall, MRI utilization increased the odds of switching DMT (OR = 1.49, 1.79, and 3.01 for 1, 2, and ≥ 3 CNS locations imaged). For those on injectable or platform DMT, any MRI utilization increased the odds of switching DMT (OR = 1.54, 2.00, and 3.48 for 1, 2, and ≥ 3 locations imaged). For those on oral DMT, only receiving MRI of 2 or ≥ 3 locations increased the odds of a DMT switch (OR = 1.36, 1.89, and 2.40 for 1, 2, and ≥ 3 locations). Finally, for pwMS on infusible therapies, there was little evidence that MRI changed the odds of a DMT switch.

Discussion: Among pwMS on injectable or oral DMT, imaging more CNS locations increased the odds of switching DMT after adjusting for age and relapse incidence. For pwMS on high-efficacy infusible DMTs, MRI did not change the odds of switching DMT but remains essential for safety monitoring.

Purpose: Subdural hematoma (SDH) is quickly becoming the most common neurosurgical pathology due to the aging population. Middle meningeal artery embolization (MMAE) has recently emerged as an effective adjunct to surgical SDH evacuation by decreasing recurrence risk. MMAE has also shown promise as a standalone SDH intervention, but clinical and radiographic predictors of successful MMAE remain ill-defined.

Methods: Retrospective chart review from 2020 to 2023 at a single center identified all MMAE cases performed as primary SDH treatment. Cases were classified by hematoma internal architecture as homogeneous, separated, laminar, or trabecular. SDH maximal thickness was assessed on all follow-up imaging and any recurrences or expansions requiring surgery were denoted as treatment failures.

Results: 164 standalone MMAE cases were reviewed. Most cases were in male patients (75.0%) with a mean age of 73.2 years. The overall MMAE treatment failure rate was 6.7% with a 4.9% periprocedural complication rate. The cases with trabecular and laminar collections were slightly larger than those with homogeneous and separated collections (16.2 mm vs. 14.2 mm, p = 0.008*), but other baseline characteristics were similar. The MMAE failure rate was significantly lower in the laminar and trabecular subgroup (1.2%) compared to the homogeneous and separated subgroup (12.4%) (p = 0.005*). Homogeneous and separated internal hematoma architecture was the only predictor of MMAE failure in multivariate analysis (OR 10.5, p = 0.027*) and was also associated with delayed SDH resorption (ANOVA: F = 4.8, p = 0.0025*).

Conclusions: Standalone MMAE is an effective, safe, and durable treatment for non-acute SDHs, and is especially effective for SDHs with more membranous internal architecture.

Purpose: Low-field (LF) MRI scanners are common in many Low- and middle-Income countries, but they provide images with worse spatial resolution and contrast than high-field (HF) scanners. Image Quality Transfer (IQT) is a machine learning framework to enhance images based on high-quality references that has recently adapted to LF MRI. In this study we aim to assess if it can improve lesion visualisation compared to LF MRI scans in children with epilepsy.

Methods: T1-weighted, T2-weighted and FLAIR were acquired from 12 patients (5 to 18 years old, 7 males) with clinical diagnosis of intractable epilepsy on a 0.36T (LF) and a 1.5T scanner (HF). LF images were enhanced with IQT. Seven radiologists blindly evaluated the differentiation between normal grey matter (GM) and white matter (WM) and the extension and definition of epileptogenic lesions in LF, HF and IQT-enhanced images.

Results: When images were evaluated independently, GM-WM differentiation scores of IQT outputs were 26% higher, 17% higher and 12% lower than LF for T1, T2 and FLAIR. Lesion definition scores were 8-34% lower than LF, but became 3% higher than LF for FLAIR and T1 when images were seen side by side. Radiologists with expertise at HF scored IQT images higher than those with expertise at LF.

Conclusion: IQT generally improved the image quality assessments. Evaluation of pathology on IQT-enhanced images was affected by familiarity with HF/IQT image appearance. These preliminary results show that IQT could have an important impact on neuroradiology practice where HF MRI is not available.