Neck CT Angiography Research Articles

NeuroMix with MRA: A Fast MR Protocol to Reduce Head and Neck CTA for Patients with Acute Neurologic Presentations.

Overuse of CT-based cerebrovascular imaging in the emergency department and inpatient settings, notably CTA of the head and neck for minor and nonfocal neurologic presentations, stresses imaging services and exposes patients to radiation and contrast. Furthermore, such CT-based imaging is often insufficient for definitive diagnosis, necessitating additional MR imaging. Recent advances in fast MRI may allow timely assessment and a reduced need for head and neck CTA in select populations. We identified inpatients or patients in the emergency department who underwent CTAHN (including noncontrast and postcontrast head CT, with or without CTP imaging) followed within 24 hours by a 3T MRI study that included a 2.5-minute unenhanced multicontrast sequence (NeuroMix) and a 5-minute intracranial time of flight MRA) during a 9-month period (April to December 2022). Cases were classified by 4 radiologists in consensus as to whether NeuroMix and NeuroMix + MRA detected equivalent findings, detected unique findings, or missed findings relative to CTAHN. One hundred seventy-four cases (mean age, 67 [SD, 16] years; 56% female) met the inclusion criteria. NeuroMix alone and NeuroMix + MRA protocols were determined to be equivalent or better compared with CTAHN in 71% and 95% of patients, respectively. NeuroMix always provided equivalent or better assessment of the brain parenchyma, with unique findings on NeuroMix and NeuroMix + MRA in 35% and 36% of cases, respectively, most commonly acute infarction or multiple microhemorrhages. In 8/174 cases (5%), CTAHN identified vascular abnormalities not seen on the NeuroMix + MRA protocol due to the wider coverage of the cervical arteries by CTAHN. A fast MR imaging protocol consisting of NeuroMix + MRA provided equivalent or better information compared with CTAHN in 95% of cases in our population of patients with an acute neurologic presentation. The findings provide a deeper understanding of the benefits and challenges of a fast unenhanced MR-first approach with NeuroMix + MRA, which could be used to design prospective trials in select patient groups, with the potential to reduce radiation dose, mitigate adverse contrast-related patient and environmental effects, and lessen the burden on radiologists and health care systems.

Knowledge-Augmented Deep Learning for Segmenting and Detecting Cerebral Aneurysms With CT Angiography: A Multicenter Study.

Background Deep learning (DL) could improve the labor-intensive, challenging processes of diagnosing cerebral aneurysms but requires large multicenter data sets. Purpose To construct a DL model using a multicenter data set for accurate cerebral aneurysm segmentation and detection on CT angiography (CTA) images and to compare its performance with radiology reports. Materials and Methods Consecutive head or head and neck CTA images of suspected unruptured cerebral aneurysms were gathered retrospectively from eight hospitals between February 2018 and October 2021 for model development. An external test set with reference standard digital subtraction angiography (DSA) scans was obtained retrospectively from one of the eight hospitals between February 2022 and February 2023. Radiologists (reference standard) assessed aneurysm segmentation, while model performance was evaluated using the Dice similarity coefficient (DSC). The model's aneurysm detection performance was assessed by sensitivity and comparing areas under the receiver operating characteristic curves (AUCs) between the model and radiology reports in the DSA data set with use of the DeLong test. Results Images from 6060 patients (mean age, 56 years ± 12 [SD]; 3375 [55.7%] female) were included for model development (training: 4342; validation: 1086; and internal test set: 632). Another 118 patients (mean age, 59 years ± 14; 79 [66.9%] female) were included in an external test set to evaluate performance based on DSA. The model achieved a DSC of 0.87 for aneurysm segmentation performance in the internal test set. Using DSA, the model achieved 85.7% (108 of 126 aneurysms [95% CI: 78.1, 90.1]) sensitivity in detecting aneurysms on per-vessel analysis, with no evidence of a difference versus radiology reports (AUC, 0.93 [95% CI: 0.90, 0.95] vs 0.91 [95% CI: 0.87, 0.94]; P = .67). Model processing time from reconstruction to detection was 1.76 minutes ± 0.32 per scan. Conclusion The proposed DL model could accurately segment and detect cerebral aneurysms at CTA with no evidence of a significant difference in diagnostic performance compared with radiology reports. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Payabvash in this issue.

Relationship between carotid web morphology on CT angiography and stroke: A pooled multicenter analysis.

The Carotid web (CaW) is a cause of stroke, particularly in younger individuals. However, the frequency and the radiological features of the web's morphology associated with stroke risk are uncertain. We determined the CaW radiological features on computed tomography (CT) angiography associated with ipsilateral stroke. Data from six studies of patients with acute ischemic stroke were pooled. Identification and measurement of CaWs were performed by experienced readers using baseline neck CT angiography. We assessed six 2D CaW radiological features on sagittal oblique images, namely, main axis length, thickness, height, base width, distance to wall, and angle between the web main axis and carotid wall, and CaW volume on 3D images. CaWs were divided into symptomatic if acute ischemic stroke was in the ipsilateral internal carotid artery territory and its etiology was undetermined and asymptomatic if one condition was unmet. Univariable and multivariable analyses were conducted to assess the association between each radiological CaW feature and symptomatic CaW. Of the 3442 patients in the pooled data with assessable CTAs, 60 (1.7%) had CaW. In patients with CaW, median age was 59 (interquartile range [IQR]: 50-68) years, 60% were women, and 3 patients had bilateral CaWs. There were 39 (62%) symptomatic and 24 (38%) asymptomatic CaWs. Patients with symptomatic CaW were younger (55 (IQR: 49-61) years versus 69 (IQR: 52-75) years), had lower rates of hypertension (9 (25.0%) versus 12 (57.1%)) and more intracranial large vessel occlusions compared to patients with asymptomatic CaWs. After adjusting for age, hypertension, and occlusion location, CaW length (adjusted odds ratio (aOR) 1.84 (95% confidence interval [CI]: 1.03-3.28)), thickness (aOR: 2.31 (95% CI 1.08-4.97)), volume (aOR: 1.07 per 1 mm3 increment (95% CI: 1.01-1.12)), and angle relative to the carotid wall (aOR: 0.95 (95% CI: 0.91-0.99)) were associated with symptomatic CaW. Radiological assessment of CaW morphology may determine its potential causal role in ischemic stroke etiology. Symptomatic CaWs tend to be longer, larger, and oriented at more acute angles relative to the carotid wall as compared to asymptomatic CaWs.

Anatomical variations of the extracranial internal carotid artery: prevalence, risk factors, and imaging insights from CT-angiography.

To determine the prevalence of different extracranial internal carotid artery (EICA) variations in CT angiography (CTA) of the neck and its predisposing factors. In this retrospective study from 2021 to 2023 conducted in the radiology department of Shafa Hospital, Kerman, Iran, all patients who had undergone neck CTA were included. Expert radiologists blindly examined each CTA image for the following: EICA variations-coiling, kinking, straight morphology, and tortuosity-and the distance between the internal carotid artery and the apex of the epiglottis and the C2 lower margin. Of the 106 patients, the mean age was 55.9 ± 16.9 years. 64.2% were men, and 35.8% were women. Considering each patient's bilateral anatomy, the reported 70.28% (149/212) frequency of EICA variations of all arteries. Tortuosity, kinking, and coiling variation were found in 61.8%, 4.2%, and 4.2% of arteries, respectively. Also, 54.72%, 1.89%, and 0.94% of the participants had bilateral tortuosity, kinking, and coiling, respectively. There was a significant relationship between the prevalence of EICA variations and female sex, age, and hypertension. The frequency of EICA variations in arteries and patients was 70.28% and 73.58%, respectively. Tortuosity was the most common variation. Female sex, old age, and hypertension were significant risk factors for EICA variations.

Upfront vascular imaging in acute stroke: Impact on thrombectomy transfer time at a primary stroke center

ObjectivesEarly cerebral arterial imaging is currently only recommended in the subgroup of acute ischemic stroke (AIS) patients suspected of having large vessel occlusion (LVO). There is limited data on the impact of early cerebrovascular imaging in all suspected AIS patients presenting within 24 h of symptom onset and the impact on door in-door out (DIDO) time. Materials and methodsIn January 2020, our Primary Stroke Center implemented a protocol to perform upfront head and neck CT angiography (CTA) with initial non-contrast CT head for all suspected ischemic stroke patients screening positive for BE-FAST stroke symptoms within 24 h from last known normal time. We retrospectively reviewed IV alteplase and thrombectomy-eligible patients before (January 1-December 31, 2019) and after protocol implementation (January 1, 2020-June 30, 2022). ResultsOf 86 patients meeting study criteria, up-front CTA was associated with significant reductions in door-to-CTA start (median 37 vs 15 min, p = 0.003), door-to-CTA result (median 83 vs 52 min, p = 0.023) and DIDO times (median 150 vs 106 min, p = 0.023). There was no significant difference in door-to-needle time before and after protocol implementation (median 48 vs 43 min, p = 0.450). ConclusionUp-front cerebrovascular imaging with CTA in suspected AIS patients presenting within 24 h resulted in shorter DIDO times without delaying door-to-needle times. Primary Stroke Centers should consider this approach to detect LVO early and expedite patient transport to thrombectomy capable centers.

A Comparative Study of AI-Based Automated and Manual Postprocessing of Head and Neck CT Angiography: An Independent External Validation with Multi-Vendor and Multi-Center Data.

To externally validate the performance of automated postprocessing (AP) on head and neck CT Angiography (CTA) and compare it with manual postprocessing (MP). This retrospective study included head and neck CTA-exams of patients from three tertiary hospitals acquired on CT scanners from five manufacturers. AP was performed by CerebralDoc. The image quality was assessed using Likert scales, and the qualitative and quantitative diagnostic performance of arterial stenosis and aneurysm, postprocessing time, and scanning radiation dose were also evaluated. A total of 250 patients were included. Among these, 55 patients exhibited significant stenosis (≥ 50%), and 33 patients had aneurysms, diagnosed using original CTA datasets and corresponding multiplanar reconstructions as the reference. While the scores of the V4 segment and the edge of the M1 segment on volume rendering (VR), as well as the C4 segment on maximum intensity projection (MIP), were significantly lower with AP compared to MP across vendors (all P < 0.05), most scores in AP demonstrated image quality that was either superior to or comparable with that of MP. Furthermore, the diagnostic performance of AP was either superior to or comparable with that of MP. Moreover, AP also exhibited advantages in terms of postprocessing time and radiation dose when compared to MP (P < 0.001). The AP of CerebralDoc presents clear advantages over MP and holds significant clinical value. However, further optimization is required in the image quality of the V4 and M1 segments on VR as well as the C4 segment on MIP.

Adult vasovagal syncope with abdominal pain diagnosed by head-up tilt combined with transcranial doppler: a preliminary study

BackgroundSyncope is a common condition that increases the risk of injury and reduces the quality of life. Abdominal pain as a precursor to vasovagal syncope (VVS) in adults is rarely reported and is often misdiagnosed.​.MethodsWe present three adult patients with VVS and presyncopal abdominal pain diagnosed by synchronous multimodal detection (transcranial Doppler [TCD] with head-up tilt [HUT]) and discuss the relevant literature.ResultsCase 1: A 52-year-old man presented with recurrent decreased consciousness preceded by six months of abdominal pain. Physical examinations were unremarkable. Dynamic electrocardiography, echocardiography, head and neck computed tomography angiography, magnetic resonance imaging (MRI), and video electroencephalogram showed no abnormalities. Case 2: A 57-year-old woman presented with recurrent syncope for 30 + years, accompanied by abdominal pain. Physical examination, electroencephalography, and MRI showed no abnormalities. Echocardiography showed large right-to-left shunts. Case 3: A 30-year-old woman presented with recurrent syncope for 10 + years, with abdominal pain as a precursor. Physical examination, laboratory analysis, head computed tomography, electrocardiography, and echocardiography showed no abnormalities. Syncope secondary to abdominal pain was reproduced during HUT. Further, HUT revealed vasovagal syncope, and synchronous TCD showed decreased cerebral blood flow; the final diagnosis was VVS in all cases.ConclusionsAbdominal pain may be a precursor of VVS in adults, and our findings enrich the clinical phenotypic spectrum of VVS. Prompt recognition of syncopal precursors is important to prevent incidents and assist in treatment decision-making. Abdominal pain in VVS may be a sign of sympathetic overdrive. Synchronous multimodal detection can help in diagnosing VVS and understanding hemodynamic mechanisms.

Risk factors of internal carotid artery stenosis in patients with proliferative diabetic retinopathy: an analysis using optical coherence tomography and optical coherence tomography angiography

BackgroundThis research investigates the correlation between the severity of internal carotid artery (ICA) stenosis and retinal parameters in patients with proliferative diabetic retinopathy (PDR), aiming to uncover potential risk factors.MethodsA retrospective analysis of 68 patients (136 eyes) diagnosed with bilateral PDR from January 1, 2017, to December 31, 2021, was conducted. Carotid artery stenosis (CAS) was assessed using neck computed tomography angiography (CTA) and carotid duplex ultrasound (CDUS), with stenosis classified into two groups: normal (group 1) and mild or above (group 2), based on the North American Symptomatic Carotid Endarterectomy Trial (NASCET) criteria. Optical coherence tomography (OCT) and OCT angiography (OCTA) measured several retinal parameters, including sub foveal choroidal thickness (SFCT), retinal nerve fiber layer (RNFL) thickness, ganglion cell-inner plexiform layer (GCIPL) thickness, vessel density (VD), and foveal avascular zone (FAZ) area. Statistical analyses determined correlations between ICA degrees and retinal parameters.ResultsThis study showed significant differences between groups in total VD, FAZ area, total RNFL thickness, and temporal RNFL thickness, indicating that patients with more severe ICA stenosis had noticeable retinal changes. Other parameters such as hyperlipidemia, total cholesterol levels, and intraocular pressure (IOP) also differed significantly, while no notable differences were observed in SFCT, central VD, average GCIPL, and superior, nasal, and inferior RNFL thickness.ConclusionThe study findings highlight retinal changes, such as an increased FAZ area, decreased total VD, and a total and thinner temporal RNFL, which suggest the need for carotid artery evaluation in patients. These findings have important clinical implications for the need for carotid work up in patients with PDR.

The application value of a vendor-specific deep learning image reconstruction algorithm in "triple low" head and neck computed tomography angiography.

Head and neck computed tomography angiography (CTA) technology has become the noninvasive imaging method of choice for the diagnosis and long-term follow-up of vascular lesions of the head and neck. However, issues of radiation safety and contrast nephropathy associated with CTA examinations remain concerns. In recent years, deep learning image reconstruction (DLIR) algorithms have been increasingly used in clinical studies, demonstrating their potential for dose optimization. This study aimed to investigate the value of using a DLIR algorithm to reduce radiation and contrast doses in head and neck CTA. A total of 100 patients were prospectively enrolled and randomly divided into two groups. Group A (50 patients) consisted of those who underwent 70-kVp CTA with a low contrast volume and injection rate and who were classified according to the reconstruction algorithm into subgroups A1 [DLIR at high weighting (DLIR-H)], A2 [DLIR at low weighting (DLIR-L)], and A3 [volume-based adaptive statistical iterative reconstruction with 50% weighting (ASIR-V50%)]. Meanwhile, group B (50 patients) consisted of those who underwent standard radiation and contrast doses at 100 kVp with ASIR-V50% reconstruction. The computed tomography (CT) attenuation, background noise, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and subjective image quality score (SIQS) were statistically compared for several vessels among the four groups. Group A showed significant reductions in contrast dosage, injection rate, and radiation dose of 36.09%, 20.88%, and 47.80%, respectively, compared to group B (all P<0.001). The four groups differed significantly in terms of background noise (all P<0.05) with group A1 having the lowest value. Group A1 also had significantly higher SNR and CNR values compared to group B in all vessels (all P<0.05) except the M1 of the middle cerebral artery for the SNR. Group A1 also had the highest SIQS, followed by the A2, B, and A3 groups. The SIQS showed good agreement between the two reviewers in all groups, with κ values between 0.88 and 1. Compared to the standard-dose protocol using 100 kVp and ASIR-V50%, a protocol of 70 kVp combined with DLIR-H significantly reduces the radiation dose, contrast dose, and injection rate in head and neck CTA while still significantly improving image quality for patients with a standard body size.

A deep-learning model for intracranial aneurysm detection on CT angiography images in China: a stepwise, multicentre, early-stage clinical validation study

Artificial intelligence (AI) models in real-world implementation are scarce. Our study aimed to develop a CT angiography (CTA)-based AI model for intracranial aneurysm detection, assess how it helps clinicians improve diagnostic performance, and validate its application in real-world clinical implementation. We developed a deep-learning model using 16 546 head and neck CTA examination images from 14 517 patients at eight Chinese hospitals. Using an adapted, stepwise implementation and evaluation, 120 certified clinicians from 15 geographically different hospitals were recruited. Initially, the AI model was externally validated with images of 900 digital subtraction angiography-verified CTA cases (examinations) and compared with the performance of 24 clinicians who each viewed 300 of these cases (stage 1). Next, as a further external validation a multi-reader multi-case study enrolled 48 clinicians to individually review 298 digital subtraction angiography-verified CTA cases (stage 2). The clinicians reviewed each CTA examination twice (ie, with and without the AI model), separated by a 4-week washout period. Then, a randomised open-label comparison study enrolled 48 clinicians to assess the acceptance and performance of this AI model (stage 3). Finally, the model was prospectively deployed and validated in 1562 real-world clinical CTA cases. The AI model in the internal dataset achieved a patient-level diagnostic sensitivity of 0·957 (95% CI 0·939-0·971) and a higher patient-level diagnostic sensitivity than clinicians (0·943 [0·921-0·961] vs 0·658 [0·644-0·672]; p<0·0001) in the external dataset. In the multi-reader multi-case study, the AI-assisted strategy improved clinicians' diagnostic performance both on a per-patient basis (the area under the receiver operating characteristic curves [AUCs]; 0·795 [0·761-0·830] without AI vs 0·878 [0·850-0·906] with AI; p<0·0001) and a per-aneurysm basis (the area under the weighted alternative free-response receiver operating characteristic curves; 0·765 [0·732-0·799] vs 0·865 [0·839-0·891]; p<0·0001). Reading time decreased with the aid of the AI model (87·5 s vs 82·7 s, p<0·0001). In the randomised open-label comparison study, clinicians in the AI-assisted group had a high acceptance of the AI model (92·6% adoption rate), and a higher AUC when compared with the control group (0·858 [95% CI 0·850-0·866] vs 0·789 [0·780-0·799]; p<0·0001). In the prospective study, the AI model had a 0·51% (8/1570) error rate due to poor-quality CTA images and recognition failure. The model had a high negative predictive value of 0·998 (0·994-1·000) and significantly improved the diagnostic performance of clinicians; AUC improved from 0·787 (95% CI 0·766-0·808) to 0·909 (0·894-0·923; p<0·0001) and patient-level sensitivity improved from 0·590 (0·511-0·666) to 0·825 (0·759-0·880; p<0·0001). This AI model demonstrated strong clinical potential for intracranial aneurysm detection with improved clinician diagnostic performance, high acceptance, and practical implementation in real-world clinical cases. National Natural Science Foundation of China. For the Chinese translation of the abstract see Supplementary Materials section.

Age and duration of hypertension are associated with carotid artery tortuosity.

Tortuosity of the carotid artery is a common angiographic finding that may impact blood flow and neuronal function. However, information on its prevalence and risk factors remains limited. In this study, we determined to explore the factors affecting carotid artery tortuosity. The head and neck computed tomography angiography (CTA) imaging and cerebral angiography data performed at the Second Affiliated Hospital of Wenzhou Medical University between January 2019 and September 2021 were collected, and a total of 356 cases were enrolled in the study after screening. Carotid artery tortuosity refers to the angle between the two adjacent segments of the carotid artery, from the opening of the aortic arch on either side to the external orifice of the carotid canal, being less than 150°. A retrospective analysis was performed to compare the general information, laboratory indicators, personal history, and medical history between the two groups. The χ2 test, t-test, and Mann-Whitney U-test were performed to compare the parameters between the two groups. If there were significant differences between the groups, multivariate logistic regression was performed to analyze the factors affecting carotid artery tortuosity. A total of 222 of the 356 cases were determined to have carotid artery tortuosity, accounting for 63.6%. There were statistically significant differences in age, body mass index (BMI), duration of diabetes and hypertension, levels of low-density lipoprotein cholesterol (LDL-C), diastolic blood pressure, history of ischemic and hemorrhagic stroke, and the usage of antihypertensive drugs between the two groups. Multivariate logistic regression analysis of the above factors showed that age (OR = 5.063, 95% CI 2.963-10.26, p < 0.001) and duration of hypertension (OR = 2.356, 95% CI 1.353-8.625, p = 0.021) were associated with a higher incidence of carotid artery tortuosity. Compared to patients who did not consume antihypertensive drugs, the incidence of carotid artery tortuosity was significantly less (OR = 0.094, 95% CI 0.002-0.713, p = 0.019) in those consuming antihypertensive drugs. Carotid artery tortuosity is a relatively common carotid artery disease. The incidence of carotid artery tortuosity may increase with age and the duration of hypertension. The consumption of antihypertensive drugs may reduce the incidence of carotid artery tortuosity.

High yield clinical applications for photon counting CT in neurovascular imaging.

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.

A novel predictive model based on pericarotid adipose tissue and lumen stenosis for stroke risk in patients with asymptomatic carotid stenosis.

The study aimed to investigate the predictive value of clinical characteristics, major computed tomography angiography (CTA) indexes of carotid AS (carotid lumen stenosis and plaque burden), and inflammatory pericarotid adipose tissue for acute stroke risk in patients with a moderate or higher degree of carotid stenosis. In all, 119 patients with unilateral carotid stenosis who underwent head and neck computed tomography angiography were included and assigned to the stroke group or non-stroke group according to magnetic resonance imaging. Pericarotid adipose tissue attenuation value, net enhancement value in the base phase and the enhancement phase, and atherosclerotic features (plaque burden and lumen stenosis) were recorded. Multivariate logistic regression analysis and the operating characteristic curve (ROC) were performed to establish a predictive model for the presence of acute ischemic stroke. ROC analysis showed that pericarotid adipose tissue attenuation value and lumen stenosis were predictive factors for stroke. The AUC of pericarotid adipose tissue attenuation (PCAT) attenuation, lumen stenosis, the novel prediction model independently constructed based on PCAT attenuation, and lumen stenosis resulted in 0.838 (95% CI 0.759-0.899), 0.700 (95% CI 0.826-0.944), and 0.942 (95% CI 0.884-0.977), respectively. The model had a sensitivity and specificity of 0.909 and 0.893, respectively, when the cutoff value was 0.388. We found that the risk model combining pericarotid adipose tissue attenuation value and lumen stenosis has significant predictive values for the presence of symptomatic stroke among patients with a moderate or higher degree of carotid stenosis.

Is low carotid bifurcation determined by vertebral level always convenient for surgical approach?

Although high-level carotid bifurcation (HCB) could lead to notable surgical difficulty, the definitive reference point for HCB is unclear. HCB is typically characterized as carotid bifurcation (CB) located higher than the level of the third cervical vertebra (C), however, a major obstacle regarding carotid artery surgical exposure is angle of the mandible (AM). The objective of this study was to investigate CB level, define HCB in relation to AM and vertebral levels, and measure the vertical distance from HCB to ipsilateral AM. Moreover, the percentage of surgically challenged CBs, misclassified as low CBs (LCB) based on vertebral level, was investigated. Patients who underwent neck computed tomography angiography were retrospectively studied. HCBs were classified into two categories: CBs above the C3 and either at or above the ipsilateral AM. Of 172 CBs (86 patients; 57 men, 29 women), CB was mostly found at C3 (44.19%), whereas AM was commonly located at C2 (51.16%). Based on vertebral level and AM, HCBs were detected in 10.47% and 20.35% of CBs, respectively. The association of HCBs determined by either C3 or AM between both sides in each individual was nonsignificant (p>0.05), but HCBs determined by C3 level were predominant in women (OR = 3.58, 95%CI = 1.31-9.80). Considering both C3 and AM, there was 8.72% of HCBs. The remaining 91.28% was classified as LCBs, including 11.63% of CBs located at both C3 and AM which were actually classified as HCBs if determined by AM. In cases of CBs above AM level, the mean vertical distance was as high as 6.56 ±2.41mm.

Image quality of photon-counting detector CT virtual monoenergetic and polyenergetic reconstructions for head and neck CT angiography

We compared image quality of head and neck CT angiography (CTA) obtained with a photon-counting detector CT (PCD-CT), including virtual monoenergetic images and polyenergetic reconstructions, and conventional energy-integrating detectors CT (EID-CT) in three patients. PCD-CT monoenergetic reconstructions at 70 keV and lower provided excellent image quality, with improved signal-to-noise and contrast-to-noise compared to EID-CT and PCD-CT polyenergetic reconstructions. PCD-CT may enable radiation dose and iodinated contrast dose reduction for cerebrovascular imaging.

Impact of craniocervical junction abnormality on vertebral artery hemodynamics: based on computational fluid dynamics analysis.

A three-dimensional reconstruction and data analysis of the vertebral artery (VA) with craniocervical junction abnormality (CJA) was performed by computational fluid dynamics (CFD) based on images to assess the impact of CJA on vertebral artery hemodynamics. Retrospective analysis of combined head and neck computed tomography angiography (CTA) images of 60 patients with CJA and 60 normal patients admitted to our department from January 2018 to June 2022. The VA was reconstructed in three dimensions using CFD-related software, and the results were visualized to derive vertebral artery lumen diameter (D), peak systolic velocity (PSV), mean blood flow velocity (MV), wall pressure (P), wall shear stress (WSS), normalized WSS (NWSS), etc. Statistical analysis was used to analyze whether the data related to hemodynamics in the CJA group and the control group were statistically significant. The lumen diameter of the vertebral artery in the CJA group were less than the control group, and the difference was statistically significant (3.354 ± 0.562 vs. 3.744 ± 0.520, p < 0.05); the PSV, MV, P, WSS, and NWSS of the CJA group were increased compared with the control group, and the difference was statistically significant (1.235 ± 0.182 vs. 1.104 ± 0.145, 0.339 ± 0.063 vs. 0.307 ± 0.042, 24576.980 ± 7095.836 vs. 20824.281 ± 6718.438, 34.863 ± 6.816 vs. 31.080 ± 5.438, 0.272 ± 0.075 vs. 0.237 ± 0.067, p < 0.05). In the complex CJA, the possibility of hemodynamic variation in the VAs is higher than in the normal population. The hemodynamic aspects of the vertebral artery in patients with CJA, such as diameter, flow velocity, flow, wall pressure and shear force, differ from those in the normal population and may lead to the occurrence of clinical symptoms, such as dizziness, so preoperative examinations such as combined head and neck CTA should be performed to clarify the vascular abnormalities.

AASeg: Artery-aware Global-to-Local Framework for Aneurysm Segmentation in Head and Neck CTA Images.

Aneurysm segmentation in computed tomography angiography (CTA) images is essential for medical intervention aimed at preventing subarachnoid hemorrhages. However, most existing studies tend to overlook the topological characteristics of arteries related to aneurysms, often resulting in suboptimal performance in aneurysm segmentation. To address this challenge, we propose an arteryaware global-to-local framework for aneurysm segmentation (AASeg) using CTA images of head and neck. This framework consists of two key components: 1) a centerline graph network (CG-Net) for aneurysm global localization, and 2) a point cloud network (PC-Net) for local aneurysm segmentation. The centerline graph is generated by extracting artery centerline structures from vessel masks obtained through a pre-trained model for head and neck vessel segmentation. This representation serves as a high-level representation of the artery structure, allowing for analysis of aneurysms along the entire arteries. It facilitates aneurysm localization via aneurysm-segment graph classification along the arteries. Then, local region of aneurysm segment can be sampled from the vessel mask according to the aneurysm-segment graph. Subsequently, aneurysm segmentation is performed on the point cloud constructed from the aneurysm segment through the PC-Net. Extensive experiments show that the proposed framework achieves state-of-the-art performance in aneurysm localization on a main dataset and an external testing dataset, with Recall of 84.1% and 80.7%, false positives per case of 1.72 and 1.69, and segmentation DSC of 66.1% and 60.2%, respectively.

Blunt Cerebrovascular Injury: Our Experience and Review of Current Practice

Abstract Background: Blunt cerebrovascular injury (BCVI) is an injury to the carotid or vertebral artery that is nonpenetrating and results from stretching or impingement of the vessel walls due to sudden head movement. Recent studies showed that the incidence of BCVI is around 1%–9%, with stroke being the most dreaded complication. Methodology: This retrospective study was conducted after approval by the medical research ethics committee at our tertiary care center, including all consecutive neck computed tomography angiography scans for blunt trauma patients from January 2017 to December 2020. The patient demographics, symptoms, and signs at presentation and imaging were reviewed through the electronic patient records for the presence of BCVI using the modified Denver scoring and Biffl criteria. Patients younger than 18 years, those with penetrating trauma, and patients with no head-and-neck scans were excluded from the study. The treatment and outcome of the positive cases were studied. Results: There were 871 patients with blunt trauma during the study. Of this number, 16 patients were identified with BCVI (1.83%). Most of the patients were male (75%), and the mean age of the cohort was 31 years (18–45 years). Among those with BCVI, five had carotid artery injuries (31%), and 11 had vertebral artery injuries (68.8%). BCVI Grades 2 and 4 were the most prevalent injuries. Ischemic infarction was seen in three patients (18%). Five patients (31.3%) with BCVI received antiplatelet therapy. None of the patients underwent endovascular or surgical treatment. Moreover, there was no BCVI-related mortality. There was a statistically significant between the Biffl grading, type of artery injury, and the presence of neurological deficit at the time of initial presentation, which both turned to be significant with a P = 0.017 and P = 0.049, respectively. Conclusion: BCVI is a serious injury with the potential for neurological complications. The artery involved and Biffl grading influence the presentation. Initiation of therapy with antithrombotic medications for stroke prevention is essential in all patients. The patients with positive findings need follow-up imaging, and an internationally recognized guideline is essential to manage this cohort.

Clinical Application of Dark-blood Imaging in Head and Neck CT Angiography: Effect on Image Quality and Plaque Visibility

The aim of this study was to explore the potential of a newly developed dark-blood imaging technique to improve image quality and plaque visibility in head and neck computed tomography (CT) angiography. Patients who underwent triphasic head and neck CT angiography scans from August 2021 to March 2023 were retrospectively enrolled (mean age 67.23±10.81 [SD] years, range 43-85 years, 64.7% male). The CT protocol consists of pre-contrast, arterial and delayed phases. Dark-blood images were postprocessed with the contrast-enhancement boost (CE-boost) technique. The quantitative assessment involved evaluating the CT value, image noise, contrast-to-noise ratio (CNR), and signal-to-noise ratio (SNR) of calcified plaque and non-calcified plaque. The plaque CNR relative to the vessel lumen (CNRplaque-lumen), vessel wall (CNRplaque-wall), and adjacent muscle (CNRplaque-muscle) was respectively calculated. Two experienced radiologists independently evaluated the CT images (5, best; 1, worst) by four characteristics including calcified plaque visibility, non-calcified plaque visibility, diagnostic confidence, and overall image quality. Inter-rater variability was also evaluated. The artery stenosis rate and plaque burden on dark-blood images were measured and compared with arterial phases. The intraclass correlation coefficient (ICC) was used for consistency analysis. The diagnostic accuracy of dark-blood images for the stenosis rate was evaluated by the area under the curve (AUC). A total of 43 patients with 54 calcified plaques and 34 non-calcified plaques were assessed in this study. When compared with pre-contrast and delayed phase, dark-blood images yielded significantly higher CNRplaque-lumen and CNRplaque-muscle of calcified (219.79±159.20 and 181.23±112.12, respectively) and non-calcified (30.30±29.11 and 6.28±4.75, respectively) plaques (all p<0.001). Calcified plaque SNR of dark-blood showed equal or slightly lower than other phases (p>0.05 or p=0.02). A major increase was observed in the non-calcified plaque SNR of dark-blood compared to the arterial phase (5.56±3.71 vs. 4.23±3.56, p=0.02), although there were no apparent differences compared to pre-contrast and delayed phases (p>0.05). In subjective analyzes, the calcified plaque visibility (4.99±0.07), non-calcified plaque visibility (4.62±0.48), overall image quality (4.81±0.34), and diagnostic confidence (4.74±0.36) in dark-blood images dominated the highest scores (p<0.001). The subjective scores of radiologists exhibited good consistency (all kappa value>0.7). The dark-blood image and the arterial phase image exhibited good consistency in identifying the stenosis rate (p<0.001). In the evaluation of plaque burden, the interobserver agreement for dark-blood images was higher compared to arterial phase images (ICC = 0.870 vs. 0.729). Compared to conventional triphasic head and neck CT angiography, the CE-boost derived dark-blood imaging demonstrated a significant improvement in image quality and visibility for both calcified and non-calcified plaque assessment.

Education Research: Neuroradiology Curriculum and Competencies Among Canadian Adult Neurology Residency Programs: A Cross-Sectional Study.

While benefitting from neuroradiologists' reports, neurologists use their own image interpretation to guide clinical decisions, especially in acute care settings. This calls for robust neuroradiology training in neurology residency, informed by current educational gaps and practices. This study aims to (1) characterize the formal neuroradiology curriculum among Canadian neurology residency programs; (2) assess neurology residents' neuroimaging interpretation competencies; and (3) define neurology residents' and program directors' (PDs) attitudes toward the current curriculum and future directions. Anonymous surveys were sent to Canadian neurology residents and PDs, querying neuroradiology learning activities, imaging modalities covered, assessment modalities, perceived residents' competencies to interpret different modalities, and attitudes regarding neuroradiology training. Residents were asked to interpret 15 neuroimaging cases. Descriptive and inferential analyses were performed. Potential differences in residents' interpretation success rates by seniority, self-perceived proficiency, and perception of curriculum sufficiency were examined using 2-tailed Welch tests with a 95% CI and Holm-Bonferroni comparison adjustment. Statistics were computed using Excel. Seventy-eight (32.6%) residents and 11 (68.8%) PDs participated. Ten of 11 PDs reported including a mandatory neuroradiology rotation, and 9/11 offered a formal neuroradiology curriculum covering head CT, head and neck CT angiography (CTA), spine MRI, and head MRI. Programs predominantly offered additional didactic lectures (9/11), teaching cases (8/11), and imaging websites (8/11). Most of the residents agreed with a minimum 1-month long rotation and desired regular didactics from neuroradiologists. Residents favored learning about head MRI (88.5%), head and neck CTA (76.9%), and spine MRI (69.2%). Senior residents' self-perceived competencies were highest for head CT, head MRI, and head and neck CTA, but lower than PDs' perception. Senior residents had greater interpretation scores than juniors (84.5% ± 13.2% vs 69.1% ± 19.9%; p < 0.0001). Most PDs (7/11, 63.6%) expressed satisfaction with current curricula vs 32.1% of residents. PDs identified time and educator shortages as main barriers to increased training. Neuroradiology training varies among programs. Residents expressed strong interest in commonly taught modalities, for which they also expressed high self-perceived competencies. However, PDs expressed greater satisfaction than residents with the current training. Leveraging interactions with neuroradiologists and online case-based learning while emphasizing trainees' interests can enhance postgraduate neuroradiology training for this useful skill.