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CSF-venous fistulas (CVFs) are a common cause of spontaneous intracranial hypotension. Despite their relatively frequent occurrence, they can be exceedingly difficult to detect on imaging. Since the initial description of CVFs in 2014, the recognition and diagnosis of this type of CSF leak has continually increased. As a result of multi-institutional efforts, a wide spectrum of imaging modalities and specialized techniques for CVF detection is now available. It is important for radiologists to be familiar with the multitude of available techniques, because each has unique advantages and drawbacks. In this article, we review the spectrum of imaging modalities available for the detection of CVFs, explain the advantages and disadvantages of each, provide typical imaging examples, and discuss provocative maneuvers that may improve the conspicuity of CVFs. Discussed modalities include conventional CT myelography, dynamic myelography, digital subtraction myelography, conebeam CT myelography, decubitus CT myelography by using conventional energy-integrating detector scanners, decubitus photon counting CT myelography, and intrathecal gadolinium MR myelography. Additional topics to be discussed include optimal patient positioning, respiratory techniques, and intrathecal pressure augmentation.
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Soft tissue aneurysmal bone cysts (STABCs) are rare neoplasms histopathologically identical to aneurysmal bone cysts. These benign lesions are characterized by thin, peripheral ossification and no skeletal continuity. STABC may be difficult to distinguish from myositis ossificans (MO) and malignant entities from imaging and fine needle aspiration, due to rarity and overlapping features. We present a case of a STABC occurring in the paraspinal cervical muscles. The imaging, histopathology, molecular analysis, and treatment are discussed. Four other published cases of STABC of the head and neck are reviewed.
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Post-dural puncture headache (PDPH) is an increasingly recognized cause of chronic headache. Outside of clinical history and myelography that requires an additional dural puncture, there is no reliable diagnostic test to evaluate for persistent dural defects. We describe the injection of iodinated contrast into the dorsal epidural space under CT guidance in five patients as a potential tool to visualize persistent dural defects.ABBREVIATIONS: PDPH = post-dural puncture headache; SIH = spontaneous intracranial hypotension; DSM = digital subtraction myelography; CTM = CT myelography.
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BACKGROUND AND PURPOSE: Accurately identifying patients with CSF-venous fistulas (CVF), one cause of spontaneous intracranial hypotension (SIH), is a diagnostic dilemma. This conundrum underscores the need for a CVF biomarker to help select who should undergo an invasive myelogram for further diagnostic workup. Beta trace protein (BTP) is the most abundant CNS derived protein in the CSF and therefore is a potential venous biomarker for CVF detection. The purpose of our study was to measure venous BTP levels as a potential CVF biomarker. MATERIALS AND METHODS: We prospectively enrolled 14 patients with CVF and measured BTP in venous blood samples from the paraspinal veins near the CVF and compared those levels to the peripheral blood. Myelograms used initially to identify the CVF were evaluated for modality, CVF laterality, CVF level, and venous drainage pattern. Patient sex, patient age, and symptom duration were also collected. Brain MR images were reviewed for Bern scores. We also measured the peripheral blood BTP levels in 20 normal controls. RESULTS: In patients with CVF, the mean BTP level near the CVF was 54.5% higher (0.760 [SD 0.673] vs 0.492 [SD 0.095] mg/L; p = 0.069) compared to peripheral blood. Nine (64.3%) patients with CVF had a higher paraspinal BTP level than peripheral BTP level. The 20 control patients had a higher the mean peripheral BTP level 0.720 (SD 0.191) mg/L compared to patients with CVF (p<0.001). CONCLUSIONS: We found that venous blood at the site of CVF had higher BTP values compared to peripheral blood in the majority, but not all patients with CVF. This may reflect the intermittent leaking nature of CVF. Additionally, we found that patients with CVF had a lower peripheral blood BTP level compared to normal controls. BTP requires further evaluation as a potential CVF biomarker. ABBREVIATIONS: SIH = Spontaneous Intracranial Hypotension; CVF = CSF-Venous Fistula; CTM = CT myelogram; DSM = Digital Subtraction Myelography; BTP = Beta Trace Protein.
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Photon-counting detectors (PCDs) represent a major milestone in the evolution of CT imaging. CT scanners using PCD systems have already been shown to generate images with substantially greater spatial resolution, superior iodine contrast-to-noise ratio, and reduced artifact compared with conventional energy-integrating detector-based systems. These benefits can be achieved with considerably decreased radiation dose. Recent studies have focused on the advantages of PCD-CT scanners in numerous anatomic regions, particularly the coronary and cerebral vasculature, pulmonary structures, and musculoskeletal imaging. However, PCD-CT imaging is also anticipated to be a major advantage for head and neck imaging. In this paper, we review current clinical applications of PCD-CT in head and neck imaging, with a focus on the temporal bone, facial bones, and paranasal sinuses; minor arterial vasculature; and the spectral capabilities of PCD systems.
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Fótons , Tomografia Computadorizada por Raios X , Humanos , Tomografia Computadorizada por Raios X/métodos , Tomografia Computadorizada por Raios X/instrumentação , Pescoço/diagnóstico por imagem , Cabeça/diagnóstico por imagem , Cabeça/irrigação sanguínea , PrevisõesRESUMO
We investigated the relationship between optic nerve (ON) size and visual acuity in children with optic nerve hypoplasia (ONH). The medical records of patients <19 years with ONH who underwent brain magnetic resonance imaging (MRI) and visual acuity assessment were reviewed. ON diameter at orbital and cisternal segments was assessed independently by two neuroradiologists and compared with visual acuity. ON diameter <1.7 mm represented a cutoff, below which was significantly associated with visual acuity of 20/200 or worse (P = 0.04) and above which was significantly associated with visual acuity of 20/40 or better (P = 0.004). ON diameter measured with MRI may provide an early prognostic indication of visual potential for children with ONH.
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Imageamento por Ressonância Magnética , Hipoplasia do Nervo Óptico , Nervo Óptico , Acuidade Visual , Humanos , Imageamento por Ressonância Magnética/métodos , Nervo Óptico/diagnóstico por imagem , Nervo Óptico/anormalidades , Nervo Óptico/patologia , Acuidade Visual/fisiologia , Criança , Masculino , Feminino , Hipoplasia do Nervo Óptico/fisiopatologia , Hipoplasia do Nervo Óptico/diagnóstico por imagem , Pré-Escolar , Adolescente , Estudos Retrospectivos , Tamanho do Órgão , LactenteRESUMO
INTRODUCTION: The prevalence of tendon rupture and tendinopathies (TRT) has not been determined in a large population of patients with atherosclerotic cardiovascular disease (ASCVD). We investigated TRT prevalence among patients with ASCVD and in the general population, using data from the Symphony Health Integrated Dataverse, a large US medical and pharmacy claims database. METHODS: This retrospective, observational study included patients aged ≥ 19 years from the claims database during the identification period (January 2019 to December 2020) and 12 months of continuous enrollment. The primary outcome was evidence of TRT in the 12 months following the index date (first ASCVD diagnosis in the ASCVD cohort; first claim in the claims database in the overall population). Diagnostic codes (ICD-10 and/or CPT) were used to define ASCVD and TRT diagnosis. RESULTS: The ASCVD cohort and overall population included 5,589,273 and 61,715,843 patients, respectively. In the ASCVD cohort, use of medications with a potential or known association with TRT was identified in 67.9% (statins), 17.7% (corticosteroids), and 16.7% (fluoroquinolones) of patients. Bempedoic acid use was reported in 1556 (< 0.1%) patients. TRT prevalence during 12-month follow-up was 3.4% (ASCVD cohort) and 1.9% (overall population). Among patients with ASCVD, 83.5% experienced TRT in only one region of the body. Factors most associated with TRT in the ASCVD cohort were increasing age, most notably in those aged 45-|64 years (odds ratio [OR] 2.19; 95% confidence interval [CI] 2.07-2.32), obesity (OR 1.51; 95% CI 1.50-1.53), and rheumatoid arthritis (OR 1.47; 95% CI 1.45-1.79). Use of statins or bempedoic acid was not associated with increased TRT risk. CONCLUSION: Patients with ASCVD may have greater risk of TRT than the general population, which may be driven by an increased prevalence of comorbidities and use of medications with a potential or known association with TRT.
Patients with atherosclerosis, the main cause of heart attacks, strokes, and peripheral vascular disease, typically require several drugs to control the disease. Some of the drugs used to treat atherosclerosis have been linked to a higher occurrence of tendon tears (or ruptures) or swelling/inflammation of the tendons (tendinopathies). However, there may be other factors present in these patients that increase the risk of tendon injuries that are not related to these drugs. This study used the medical records of over 5.5 million patients with atherosclerosis and over 63 million patients reflecting the general population in the United States to determine the prevalence of tendon injury. Additionally, the researchers looked at other factors that might be related to a higher risk of tendon injury in each group. Over a 12-month period, tendon injuries occurred in 3.4% of patients with atherosclerosis and 1.8% of patients in the general population. In patients with atherosclerosis, factors such as being obese, older (4564 years), or having rheumatoid arthritis were also linked to an increased risk of tendon injuries. There was no association seen between statin or bempedoic acid use and tendon injuries. These results may help healthcare providers to determine the underlying risk of tendon injuries and guide treatment of this patient population.
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BACKGROUND: This study aimed to develop and validate a computed tomography angiography based machine learning model that uses plaque composition data and degree of carotid stenosis to detect symptomatic carotid plaques in patients with carotid atherosclerosis. METHODS: The machine learning based model was trained using degree of stenosis and the volumes of 13 computed tomography angiography derived intracarotid plaque subcomponents (eg, lipid, intraplaque hemorrhage, calcium) to identify plaques associated with cerebrovascular events. The model was internally validated through repeated 10-fold cross-validation and tested on a dedicated testing cohort according to discrimination and calibration. RESULTS: This retrospective, single-center study evaluated computed tomography angiography scans of 268 patients with both symptomatic and asymptomatic carotid atherosclerosis (163 for the derivation set and 106 for the testing set) performed between March 2013 and October 2019. The area-under-receiver-operating characteristics curve by machine learning on the testing cohort (0.89) was significantly higher than the areas under the curve of traditional logit analysis based on the degree of stenosis (0.51, P<0.001), presence of intraplaque hemorrhage (0.69, P<0.001), and plaque composition (0.78, P<0.001), respectively. Comparable performance was obtained on internal validation. The identified plaque components and associated cutoff values that were significantly associated with a higher likelihood of symptomatic status after adjustment were the ratio of intraplaque hemorrhage to lipid volume (≥50%, 38.5 [10.1-205.1]; odds ratio, 95% CI) and percentage of intraplaque hemorrhage volume (≥10%, 18.5 [5.7-69.4]; odds ratio, 95% CI). CONCLUSIONS: This study presented an interpretable machine learning model that accurately identifies symptomatic carotid plaques using computed tomography angiography derived plaque composition features, aiding clinical decision-making.
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Doenças das Artérias Carótidas , Angiografia por Tomografia Computadorizada , Aprendizado de Máquina , Placa Aterosclerótica , Humanos , Angiografia por Tomografia Computadorizada/métodos , Masculino , Feminino , Estudos Retrospectivos , Placa Aterosclerótica/diagnóstico por imagem , Idoso , Pessoa de Meia-Idade , Doenças das Artérias Carótidas/diagnóstico por imagem , Doenças das Artérias Carótidas/complicações , Estenose das Carótidas/diagnóstico por imagem , Estenose das Carótidas/complicações , Valor Preditivo dos Testes , Reprodutibilidade dos Testes , Artérias Carótidas/diagnóstico por imagem , Índice de Gravidade de DoençaRESUMO
BACKGROUND AND PURPOSE: Intracranial vessel wall imaging is technically challenging to implement, given the simultaneous requirements of high spatial resolution, excellent blood and CSF signal suppression, and clinically acceptable gradient times. Herein, we present our preliminary findings on the evaluation of a deep learning-optimized sequence using T1-weighted imaging. MATERIALS AND METHODS: Clinical and optimized deep learning-based image reconstruction T1 3D Sampling Perfection with Application optimized Contrast using different flip angle Evolution (SPACE) were evaluated, comparing noncontrast sequences in 10 healthy controls and postcontrast sequences in 5 consecutive patients. Images were reviewed on a Likert-like scale by 4 fellowship-trained neuroradiologists. Scores (range, 1-4) were separately assigned for 11 vessel segments in terms of vessel wall and lumen delineation. Additionally, images were evaluated in terms of overall background noise, image sharpness, and homogeneous CSF signal. Segment-wise scores were compared using paired samples t tests. RESULTS: The scan time for the clinical and deep learning-based image reconstruction sequences were 7:26 minutes and 5:23 minutes respectively. Deep learning-based image reconstruction images showed consistently higher wall signal and lumen visualization scores, with the differences being statistically significant in most vessel segments on both pre- and postcontrast images. Deep learning-based image reconstruction had lower background noise, higher image sharpness, and uniform CSF signal. Depiction of intracranial pathologies was better or similar on the deep learning-based image reconstruction. CONCLUSIONS: Our preliminary findings suggest that deep learning-based image reconstruction-optimized intracranial vessel wall imaging sequences may be helpful in achieving shorter gradient times with improved vessel wall visualization and overall image quality. These improvements may help with wider adoption of intracranial vessel wall imaging in clinical practice and should be further validated on a larger cohort.
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INTRODUCTION: In the current paper, the "carotid artery calcium score" method is presented with the target to offer a metric method to quantify the amount of calcification in the carotid artery. MODEL AND DEFINITION: The Volume of Interest (VOI) should be extracted and those voxels, with a Hounsfield Unit (HU) value ≥130, should be considered. The total weight value is determined by calculating the sum of the HU attenuation values of all voxels with values ≥130 HU. This value should be multiplied by the conversion factor ("or voxel size") and divided by a weighting factor, the attenuation threshold to consider a voxel as calcified (and therefore 130 HU): this equation determines the Carotid Artery Calcium Score (CACS). RESULTS: In order to provide the demonstration of the potential feasibility of the model, the CACS was calculated in 131 subjects (94 males; mean age 72.7 years) for 235 carotid arteries (in 27 subjects, unilateral plaque was present) considered. The CACS value ranged from 0.67 to 11716. A statistically significant correlation was found (rho value = 0.663, p value = .0001) between the CACS in the right and left carotid plaques. Moreover, a statistically significant correlation between the age and the total CACS was present (rho value = 0.244, p value = .005), whereas no statistically significant difference was found in the distribution of CACS by gender (p = .148). The CACS was also tested at baseline and after contrast and no statistically significant difference was found. CONCLUSION: In conclusion, this method is of easy application, and it weights at the same time the volume and the degree of calcification in a unique parameter. This method needs to be tested to verify its potential utility, similar to the coronary artery calcium score, for the risk stratification of the occurrence of cerebrovascular events of the anterior circulation. Further studies using this new diagnostic tool to determine the prognostic value of carotid calcium quantification are needed.
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Carotid atherosclerosis plays a substantial role in cardiovascular morbidity and mortality. Given the multifaceted impact of this disease, there has been increasing interest in harnessing artificial intelligence (AI) and radiomics as complementary tools for the quantitative analysis of medical imaging data. This integrated approach holds promise not only in refining medical imaging data analysis but also in optimizing the utilization of radiologists' expertise. By automating time consuming tasks, AI allows radiologists to focus on more pertinent responsibilities. Simultaneously, the capacity of AI in radiomics to extract nuanced patterns from raw data enhances the exploration of carotid atherosclerosis, advancing efforts in terms of (1) early detection and diagnosis, (2) risk stratification and predictive modeling, (3) improving workflow efficiency, and (4) contributing to advancements in research. This review provides an overview of general concepts related to radiomics and AI, along with their application in the field of carotid vulnerable plaque. It also offers insights into various research studies conducted on this topic across different imaging techniques.
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Inteligência Artificial , Doenças das Artérias Carótidas , Placa Aterosclerótica , Humanos , Placa Aterosclerótica/diagnóstico por imagem , Doenças das Artérias Carótidas/diagnóstico por imagem , Interpretação de Imagem Assistida por Computador/métodos , RadiômicaRESUMO
BACKGROUND AND PURPOSE: Feature variability in radiomics studies due to technical and magnet strength parameters is well-known and may be addressed through various preprocessing methods. However, very few studies have evaluated the downstream impact of variable preprocessing on model classification performance in a multiclass setting. We sought to evaluate the impact of Smallest Univalue Segment Assimilating Nucleus (SUSAN) denoising and Combining Batches harmonization on model classification performance. MATERIALS AND METHODS: A total of 493 cases (410 internal and 83 external data sets) of glioblastoma, intracranial metastatic disease, and primary CNS lymphoma underwent semiautomated 3D-segmentation post-baseline image processing (BIP) consisting of resampling, realignment, coregistration, skull-stripping, and image normalization. Post-BIP, 2 sets were generated, one with and another without SUSAN denoising. Radiomics features were extracted from both data sets and batch-corrected to produce 4 data sets: (a) BIP, (b) BIP with SUSAN denoising, (c) BIP with Combining Batches, and (d) BIP with both SUSAN denoising and Combining Batches harmonization. Performance was then summarized for models using a combination of 6 feature-selection techniques and 6 machine learning models across 4 mask-sequence combinations with features derived from 1 to 3 (multiparametric) MRI sequences. RESULTS: Most top-performing models on the external test set used BIP+SUSAN denoising-derived features. Overall, the use of SUSAN denoising and Combining Batches harmonization led to a slight but generally consistent improvement in model performance on the external test set. CONCLUSIONS: The use of image-preprocessing steps such as SUSAN denoising and Combining Batches harmonization may be more useful in a multi-institutional setting to improve model generalizability. Models derived from only T1 contrast-enhanced images showed comparable performance to models derived from multiparametric MRI.
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Dilated perivascular spaces (PVSs) are common and easily recognized on imaging. However, rarer giant tumefactive PVSs (GTPVSs) can have unusual multilocular cystic configurations, and are often confused for other pathologic entities, including neoplasms, cystic infarctions, and neuroepithelial cysts. Because GTPVSs are scarcely encountered and even more infrequently operated upon, many radiologists are unaware of the imaging and pathologic features of these lesions. Here, a case of a resected GTPVS is presented, highlighting both its radiologic and histologic characteristics, and discussing how such lesions can be differentiated from their closest mimickers on imaging.
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Diseases of the carotid arteries can be classified into different categories based on their origin. Atherosclerotic carotid disease remains the most encountered arterial wall pathology. However, other less-common non-atherosclerotic diseases can have detrimental clinical consequences if not appropriately recognized. The underlying histological features of each disease process may result in imaging findings that possess features that are obvious of the disease. However, some carotid disease processes may have histological characteristics that manifest as non-specific radiologic findings. The purpose of this manuscript is to review various non-atherosclerotic causes of carotid artery disease as well as their histologic-radiologic characteristics to aid in the appropriate recognition of these less-commonly encountered pathologies.
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Noninvasive tumor control of vestibular schwannomas through stereotactic radiosurgery allows high rates of long-term tumor control and has been used primarily for small- and medium-sized vestibular schwannomas. The posttreatment imaging appearance of the tumor, temporal patterns of growth and treatment response, as well as extratumoral complications can often be both subtle or confusing and should be appropriately recognized. Herein, the authors present an imaging-based review of expected changes as well as associated complications related to radiosurgery for vestibular schwannomas.
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Photon-counting CT (PCCT) uses a novel X-ray detection mechanism that confers many advantages over that used in traditional energy integrating CT. As PCCT becomes more available, it is important to thoroughly understand its benefits and highest yield areas for improvements in diagnosis of various diseases. Based on our early experience, we have identified several areas of neurovascular imaging in which PCCT shows promise. Here, we describe the benefits in diagnosing arterial and venous diseases in the head, neck, and spine. Specifically, we focus on applications in head and neck CT angiography (CTA), spinal CT angiography, and CT myelography for detection of CSF-venous fistulas. Each of these applications highlights the technological advantages of PCCT in neurovascular imaging. Further understanding of these applications will not only benefit institutions incorporating PCCT into their practices but will also help guide future directions for implementation of PCCT for diagnosing other pathologies in neuroimaging.
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Angiografia por Tomografia Computadorizada , Fótons , Tomografia Computadorizada por Raios X , Humanos , Angiografia por Tomografia Computadorizada/métodos , Tomografia Computadorizada por Raios X/métodos , Mielografia/métodos , Transtornos Cerebrovasculares/diagnóstico por imagemRESUMO
Photon-counting CT is an increasingly used technology with numerous advantages over conventional energy-integrating detector CT. These include superior spatial resolution, high temporal resolution, and inherent spectral imaging capabilities. Recently, photon-counting CT myelography was described as an effective technique for the detection of CSF-venous fistulas, a common cause of spontaneous intracranial hypotension. It is likely that photon-counting CT myelography will also have advantages for the localization of dural tears, a separate type of spontaneous spinal CSF leak that requires different myelographic techniques for accurate localization. To our knowledge, prior studies on photon-counting CT myelography have been limited to techniques for detecting CSF-venous fistulas. In this technical report, we describe our technique and early experience with photon-counting CT myelography for the localization of dural tears.