AJNR. American journal of neuroradiology最新文献

Background and purpose: The abnormalities of the long arm of chromosome 18 (18q) constitute a complex spectrum. We aimed to systematically analyze their MR imaging features. We hypothesized that there would be variable but recognizable white matter and structural patterns in this cohort.

Materials and methods: In this retrospective cohort study, we included pediatric patients with a proved abnormality of 18q between 2000-2022. An age- and sex-matched control cohort was also constructed.

Results: Thirty-six cases, median MR imaging age 19.6 months (4.3-59.3), satisfied our inclusion criteria. Most were female (25, 69%, F:M ratio 2.2:1). Fifty MR imaging studies were analyzed, and 35 (70%) had delayed myelination. Two independent readers scored brain myelination with excellent interrater reliability. Three recognizable evolving MR imaging patterns with distinct age distributions and improving myelination scores were identified: Pelizaeus-Merzbacher disease-like (9.9 months, 37), intermediate (22 months, 48), and washed-out pattern (113.6 months, 53). Etiologically, MRIs were analyzed across 3 subgroups: 18q deletion (34, 69%), trisomy 18 (10, 21%), and ring chromosome 18 (5, 10%). Ring chromosome 18 had the highest myelination lag (27, P = .005) and multifocal white matter changes (P = .001). Trisomy 18 had smaller pons and cerebellar dimensions (anteposterior diameter pons, P = .002; corpus callosum vermis, P < .001; and transverse cerebellar diameter, P = .04).

Conclusions: In this cohort of 18q chromosomal abnormalities, MR imaging revealed recognizable patterns correlating with improving brain myelination. Imaging findings appear to be on a continuum with more severe white matter abnormalities in ring chromosome 18 and greater prevalence of structural abnormalities of the pons and cerebellum in trisomy 18.

Background and purpose: Sotos syndrome is a rare autosomal dominant condition caused by pathogenic mutations in the NSD1 gene that presents with craniofacial dysmorphism, overgrowth, seizures, and neurodevelopmental delay. Macrocephaly, ventriculomegaly, and corpus callosal dysmorphism are typical neuroimaging features that have been described in the medical literature. The purpose of this study was to expand on the neuroimaging phenotype by detailed analysis of a large cohort of patients with genetically proved Sotos syndrome.

Materials and methods: This multicenter, multinational, retrospective observational cohort study systematically analyzed the clinical characteristics and neuroimaging features of 77 individuals with genetically diagnosed Sotos syndrome, via central consensus review with 3 pediatric neuroradiologists.

Results: In addition to previously described features, malformations of cortical development were identified in most patients (95.0%), typically dysgyria (92.2%) and polymicrogyria (22.1%), varying in location and distribution. Incomplete rotation of the hippocampus was observed in 50.6% of patients and was associated with other imaging findings, in particular with dysgyria (100% versus 84.2%, P = .012).

Conclusions: Our findings show a link between the genetic-biochemical basis and the neuroimaging features and aid in better understanding the underlying clinical manifestations and possible treatment options. These findings have yet to be described to this extent and correspond with recent studies that show that NSD1 participates in brain development and has interactions with other known relevant genetic pathways.

Background and purpose: Considering recent iodinated contrast shortages and a focus on reducing waste, developing protocols with lower contrast dosing while maintaining image quality through artificial intelligence is needed. This study compared reduced iodinated contrast media and standard dose CTP acquisitions, and the impact of deep learning denoising on CTP image quality in preclinical and clinical studies. The effect of reduced X-ray mAs dose was also investigated in preclinical studies.

Materials and methods: Twelve swine underwent 9 CTP examinations each, performed at combinations of 3 different x-ray (37, 67, and 127 mAs) and iodinated contrast media doses (10, 15, and 20 mL). Clinical CTP acquisitions performed before and during the iodinated contrast media shortage and protocol change (from 40 to 30 mL) were retrospectively included. Eleven patients with reduced iodinated contrast media dosages and 11 propensity-score-matched controls with the standard iodinated contrast media dosages were included. A residual encoder-decoder convolutional neural network (RED-CNN) was trained for CTP denoising using k-space-weighted image average filtered CTP images as the target. The standard, RED-CNN-denoised, and k-space-weighted image average noise-filtered images for animal and human studies were compared for quantitative SNR and qualitative image evaluation.

Results: The SNR of animal CTP images decreased with reductions in iodinated contrast media and milliampere-second doses. Contrast dose reduction had a greater effect on SNR than milliampere-second reduction. Noise-filtering by k-space-weighted image average and RED-CNN denoising progressively improved the SNR of CTP maps, with RED-CNN resulting in the highest SNR. The SNR of clinical CTP images was generally lower with a reduced iodinated contrast media dose, which was improved by the k-space-weighted image average and RED-CNN denoising (P < .05). Qualitative readings consistently rated RED-CNN denoised CTP as the best quality, followed by k-space-weighted image average and then standard CTP images.

Conclusions: Deep learning-denoising can improve image quality for low iodinated contrast media CTP protocols, and could approximate standard iodinated contrast media dose CTP, in addition to potentially improving image quality for low milliampere-second acquisitions.

Background and purpose: Photon-counting detector CT (PCD-CT) is now clinically available and offers ultra-high-resolution (UHR) imaging. Our purpose was to prospectively evaluate the relative image quality and impact on diagnostic confidence of head CTA images acquired by using a PCD-CT compared with an energy-integrating detector CT (EID-CT).

Materials and methods: Adult patients undergoing head CTA on EID-CT also underwent a PCD-CT research examination. For both CT examinations, images were reconstructed at 0.6 mm by using a matched standard resolution (SR) kernel. Additionally, PCD-CT images were reconstructed at the thinnest section thickness of 0.2 mm (UHR) with the sharpest kernel, and denoised with a deep convolutional neural network (CNN) algorithm (PCD-UHR-CNN). Two readers (R1, R2) independently evaluated image quality in randomized, blinded fashion in 2 sessions, PCD-SR versus EID-SR and PCD-UHR-CNN versus EID-SR. The readers rated overall image quality (1 [worst] to 5 [best]) and provided a Likert comparison score (-2 [significantly inferior] to 2 [significantly superior]) for the 2 series when compared side-by-side for several image quality features, including visualization of specific arterial segments. Diagnostic confidence (0-100) was rated for PCD versus EID for specific arterial findings, if present.

Results: Twenty-eight adult patients were enrolled. The volume CT dose index was similar (EID: 37.1 ± 4.7 mGy; PCD: 36.1 ± 4.0 mGy). Overall image quality for PCD-SR and PCD-UHR-CNN was higher than EID-SR (eg, PCD-UHR-CNN versus EID-SR: 4.0 ± 0.0 versus 3.0 ± 0.0 (R1), 4.9 ± 0.3 versus 3.0 ± 0.0 (R2); all P values < .001). For depiction of arterial segments, PCD-SR was preferred over EID-SR (R1: 1.0-1.3; R2: 1.0-1.8), and PCD-UHR-CNN over EID-SR (R1: 0.9-1.4; R2: 1.9-2.0). Diagnostic confidence of arterial findings for PCD-SR and PCD-UHR-CNN was significantly higher than EID-SR: eg, PCD-UHR-CNN versus EID-SR: 93.0 ± 5.8 versus 78.2 ± 9.3 (R1), 88.6 ± 5.9 versus 70.4 ± 5.0 (R2); all P values < .001.

Conclusions: PCD-CT provides improved image quality for head CTA images compared with EID-CT, both when PCD and EID reconstructions are matched, and to an even greater extent when PCD-UHR reconstruction is combined with a CNN denoising algorithm.

Infarcts from cerebral air embolism are rare events with potentially catastrophic clinical consequences. The imaging features of cerebral air embolism are not well-defined in the literature. We report a novel constellation of MR imaging findings of cerebral arterial air emboli-induced infarcts in a series of 6 patients. Awareness of the more distinguishing MR imaging patterns of cerebral air embolism may help establish this diagnosis and facilitate implementation of timely treatment.

Background and purpose: The rise of large language models such as generative pretrained transformers (GPTs) has sparked considerable interest in radiology, especially in interpreting radiologic reports and image findings. While existing research has focused on GPTs estimating diagnoses from radiologic descriptions, exploring alternative diagnostic information sources is also crucial. This study introduces the use of GPTs (GPT-3.5 Turbo and GPT-4) for information retrieval and summarization, searching relevant case reports via PubMed, and investigates their potential to aid diagnosis.

Materials and methods: From October 2021 to December 2023, we selected 115 cases from the "Case of the Week" series on the American Journal of Neuroradiology website. Their Description and Legend sections were presented to the GPTs for the 2 tasks. For the Direct Diagnosis task, the models provided 3 differential diagnoses that were considered correct if they matched the diagnosis in the diagnosis section. For the Case Report Search task, the models generated 2 keywords per case, creating PubMed search queries to extract up to 3 relevant reports. A response was considered correct if reports containing the disease name stated in the diagnosis section were extracted. The McNemar test was used to evaluate whether adding a Case Report Search to Direct Diagnosis improved overall accuracy.

Results: In the Direct Diagnosis task, GPT-3.5 Turbo achieved a correct response rate of 26% (30/115 cases), whereas GPT-4 achieved 41% (47/115). For the Case Report Search task, GPT-3.5 Turbo scored 10% (11/115), and GPT-4 scored 7% (8/115). Correct responses totaled 32% (37/115) with 3 overlapping cases for GPT-3.5 Turbo, whereas GPT-4 had 43% (50/115) of correct responses with 5 overlapping cases. Adding Case Report Search improved GPT-3.5 Turbo's performance (P = .023) but not that of GPT-4 (P = .248).

Conclusions: The effectiveness of adding Case Report Search to GPT-3.5 Turbo was particularly pronounced, suggesting its potential as an alternative diagnostic approach to GPTs, particularly in scenarios where direct diagnoses from GPTs are not obtainable. Nevertheless, the overall performance of GPT models in both direct diagnosis and case report retrieval tasks remains not optimal, and users should be aware of their limitations.

Background and purpose: CSF leaks of the skull base and spine share a common process of CSF volume loss, and yet only the latter has been associated with spontaneous intracranial hypotension (SIH). Despite published claims that only spinal leaks cause SIH, no prior studies have evaluated brain MR imaging in patients with skull base leaks for findings associated with SIH, such as dural enhancement. The purpose of our study was to use a validated brain MR imaging scoring system to evaluate patients with skull base CSF leaks for findings associated with SIH.

Materials and methods: We included patients with confirmed skull base CSF leaks and contrast-enhanced preoperative brain MRI. The preoperative MR images were reviewed for findings associated with SIH by using the Bern score. Patient age, presenting symptoms and their duration, and leak site were also recorded.

Results: Thirty-one patients with skull base CSF leaks were included. Mean Bern score was 0.9 (range 0-4, standard deviation 1.1), and only 1 patient (3%) had dural enhancement. Mean age was 53 years (range 18-76). Mean symptom duration was 1.3 years, with 22 patients presenting within 1 year of symptom onset. Twenty-three patients (74.2%) had intraoperative confirmation of leak from the middle cranial fossa, involving the temporal bone, while 7 (22.6%) had leaks from the anterior skull base. One patient, who had dural enhancement, had an infratentorial CSF leak along the petrous segment of the internal carotid artery.

Conclusions: Our study provides further evidence that skull base and spinal CSF leaks represent distinct pathophysiologies and present with different brain MRI findings.

Background and purpose: DSC-MR imaging can be used to generate fractional tumor burden (FTB) maps via application of relative CBV thresholds to spatially differentiate glioblastoma recurrence from posttreatment radiation effects (PTRE). Image-localized histopathology was previously used to validate FTB maps derived from a reference DSC-MR imaging protocol by using preload, a moderate flip angle (MFA, 60°), and postprocessing leakage correction. Recently, a DSC-MR imaging protocol with a low flip angle (LFA, 30°) with no preload was shown to provide leakage-corrected relative CBV (rCBV) equivalent to the reference protocol. This study aimed to identify the rCBV thresholds for the LFA protocol that generate the most accurate FTB maps, concordant with those obtained from the reference MFA protocol.

Materials and methods: Fifty-two patients with grade-IV glioblastoma who had prior surgical resection and received chemotherapy and radiation therapy were included in the study. Two sets of DSC-MR imaging data were collected sequentially first by using LFA protocol with no preload, which served as the preload for the subsequent MFA protocol. Standardized relative CBV maps (sRCBV) were obtained for each patient and coregistered with the anatomic postcontrast T1-weighted images. The reference MFA-based FTB maps were computed by using previously published sRCBV thresholds (1.0 and 1.56). A receiver operating characteristics (ROC) analysis was conducted to identify the optimal, voxelwise LFA sRCBV thresholds, and the sensitivity, specificity, and accuracy of the LFA-based FTB maps were computed with respect to the MFA-based reference.

Results: The mean sRCBV values of tumors across patients exhibited strong agreement (concordance correlation coefficient = 0.99) between the 2 protocols. Using the ROC analysis, the optimal lower LFA threshold that accurately distinguishes PTRE from tumor recurrence was found to be 1.0 (sensitivity: 87.77%; specificity: 90.22%), equivalent to the ground truth. To identify aggressive tumor regions, the ROC analysis identified an upper LFA threshold of 1.37 (sensitivity: 90.87%; specificity: 91.10%) for the reference MFA threshold of 1.56.

Conclusions: For LFA-based FTB maps, an sRCBV threshold of 1.0 and 1.37 can differentiate PTRE from recurrent tumors. FTB maps aid in surgical planning, guiding pathologic diagnosis and treatment strategies in the recurrent setting. This study further confirms the reliability of single-dose LFA-based DSC-MR imaging.

Background and purpose: The circle of Willis (COW) is a crucial mechanism for cerebral collateral circulation. This proof-of-concept study aims to develop and assess an analysis method to characterize the hemodynamics of the arterial segments in the COW by using arterial spin-labeling (ASL) based non-contrast-enhanced dynamic MR angiography (dMRA).

Materials and methods: The developed analysis method uses a graph model, bootstrap strategy, and ensemble learning methodologies to determine the time curve shift from ASL dMRA to estimate the flow direction within the COW. The performance of the method was assessed on 52 subjects, by using the flow direction, either antegrade or retrograde, derived from 3D phase-contrast MR imaging as the reference.

Results: A total of 340 arterial segments in the COW were evaluated, among which 30 (8.8%) had retrograde flow according to 3D phase-contrast MRI. The ASL dMRA-based flow direction estimation has an accuracy, sensitivity, and specificity of 95.47%, 80%, and 96.34%, respectively.

Conclusions: Using ASL dMRA and the developed image analysis method to estimate the flow direction in COW is feasible. This study provides a new method to assess the hemodynamics of the COW, which could be useful for the diagnosis and study of cerebrovascular diseases.

Background and purpose: Vein of Galen malformation (VOGM) is the most common congenital cerebrovascular malformation, and many patients have high mortality rates and poor cognitive outcomes. Quantitative diagnostic tools are needed to improve clinical outcomes, and the purpose of this study was to characterize intracranial blood flow in VOGM using quantitative 4D flow MRI.

Materials and methods: A prospective study of children with VOGM was conducted by acquiring 4D flow MRI to quantify total blood inflow to the brain, flow in the pathologic falcine sinus, and flow in the superior sagittal sinus. Linear regression was used to test the relationships between these flows and age, clinical status, and the mediolateral diameter of the outflow tract of the lesion through the falcine or straight sinus diameter, which is a known morphologic prognostic metric.

Results: In all 11 subjects (mean age, 22 [SD,17 ] weeks), total blood flow to the brain always exceeded normal levels (mean, 1063 [SD, 403] mL/minute). Significant correlations were observed between falcine sinus flow and the mediolateral diameter of the straight or falcine sinus, the posterior cerebral artery/MCA flow ratio and age at scanning, and superior sagittal sinus flow proximal to malformation inflow and age at scanning.

Conclusions: Using 4D flow MRI, we established the hemodynamic underpinnings of the mediolateral diameter of the straight or falcine sinus and investigated metrics representing parenchymal venous drainage that could be used to monitor the normalization of hemodynamics during embolization therapy.