Defining Mild Traumatic Brain Injury: From Research Definition to Clinical Practice.

INTRODUCTION: Approximately 75% of traumatic brain injuries (TBIs) qualify as mild. However, there exists no universally agreed upon definition for mild TBI (mTBI). Consequently, treatment guidelines for this group are lacking. The Center for Disease Control (CDC), American College of Rehabilitation Medicine (ACRM), Veterans Affairs and Department of Defense (VA/DoD), Eastern Association for the Surgery of Trauma (EAST), and the University of Arizona's Brain Injury Guidelines (BIG) have each published differing definitions for mTBI. The aim of this study was to compare the ability of these definitions to correctly classify mTBI patients in the acute care setting. METHODS: A single-center, retrospective cohort study comparing the performance of the varying definitions of mTBI was performed at a Level I trauma center from August 2015 to December 2018. Definitions were compared by sensitivity, specificity, positive predictive value, negative predictive value, as well as overtriage and undertriage rates. Finally, a cost-savings analysis was performed. RESULTS: We identified 596 patients suffering blunt TBI with Glasgow Coma Scale 13-15. The CDC/ACRM definitions demonstrated 100% sensitivity but 0% specificity along with the highest rate of undertriage and TBI-related mortality. BIG 1 included nearly twice as many patients than EAST and VA/DoD while achieving a superior positive predictive value and undertriage rate. CONCLUSIONS: The BIG definition identified a larger number of patients compared to the VA/DoD and EAST definitions while having an acceptable and more accurate overtriage and undertriage rate compared to the CDC and ACRM. By eliminating undertriage and minimizing overtriage rates, the BIG maintains patient safety while enhancing the efficiency of healthcare systems. Using the BIG definition, a cost savings of $395,288.95-$401,263.95 per year could be obtained at our level 1 trauma facility without additional mortality.

Cranial bone thickness and density anomalies quantified from CT images can identify chronic increased intracranial pressure.

PURPOSE: The diagnosis of chronic increased intracranial pressure (IIP)is often based on subjective evaluation or clinical metrics with low predictive value. We aimed to quantify cranial bone changes associated with pediatric IIP using CT images and to identify patients at risk. METHODS: We retrospectively quantified local cranial bone thickness and mineral density from the CT images of children with chronic IIP and compared their statistical differences to normative children without IIP adjusting for age, sex and image resolution. Subsequently, we developed a classifier to identify IIP based on these measurements. Finally, we demonstrated our methods to explore signs of IIP in patients with non-syndromic sagittal craniosynostosis (NSSC). RESULTS: We quantified a significant decrease of bone density in 48 patients with IIP compared to 1,018 normative subjects (P < .001), but no differences in bone thickness (P = .56 and P = .89 for age groups 0-2 and 2-10 years, respectively). Our classifier demonstrated 83.33% (95% CI: 69.24%, 92.03%) sensitivity and 87.13% (95% CI: 84.88%, 89.10%) specificity in identifying patients with IIP. Compared to normative subjects, 242 patients with NSSC presented significantly lower cranial bone density (P < .001), but no differences were found compared to patients with IIP (P = .57). Of patients with NSSC, 36.78% (95% CI: 30.76%, 43.22%) presented signs of IIP. CONCLUSION: Cranial bone changes associated with pediatric IIP can be quantified from CT images to support earlier diagnoses of IIP, and to study the presence of IIP secondary to cranial pathology such as non-syndromic sagittal craniosynostosis.

The Effect of Language on the Decision to Image in the Evaluation of Atraumatic Headache.

BACKGROUND: Patients with limited English proficiency seen in the emergency department (ED) experience lower quality of care and higher diagnostic resource utilization unless they are evaluated in their own language. Despite a low rate of serious pathology identified and the availability of guidelines to direct its use, computed tomography (CT) is commonly used to evaluate atraumatic headache in the ED. OBJECTIVE: Our aim was to determine whether Spanish-speaking patients with atraumatic headache were more likely than their English-speaking counterparts to undergo head CT, and whether evaluation by a clinician who passed a Spanish proficiency test mitigated this difference. METHODS: This retrospective observational study used electronic health record data of adult patients presenting with atraumatic headache to a level I trauma center during a 2-year period. Spanish-language testing of clinicians consisted of a brief, unvalidated, in-person, nonmedical verbal test administered by human resources staff. RESULTS: A total of 3030 patients with atraumatic headache were identified; 1437 were English speaking and 1593 were Spanish speaking. Spanish-speaking patients were older (48.3 vs. 41.9 years), more likely to be women (68.8% vs. 60.5%), and more likely to undergo head CT (31.8% vs. 26.4%). Evaluation by a clinician who passed the Spanish proficiency test had no significant influence on the likelihood of head CT for Spanish-speaking patients after controlling for confounding variables (adjusted odds ratio 0.95; 95% CI 0.75-1.20). CONCLUSIONS: Spanish-speaking patients are more likely to undergo head CT when evaluated for atraumatic headache than English-speaking patients. Evaluation by a clinician who passed a brief Spanish proficiency test did not mitigate this disparity.

Sociodemographic biases in a commercial AI model for intracranial hemorrhage detection.

PURPOSE: To evaluate whether a commercial AI tool for intracranial hemorrhage (ICH) detection on head CT exhibited sociodemographic biases. METHODS: Our retrospective study reviewed 9736 consecutive, adult non-contrast head CT scans performed between November 2021 and February 2022 in a single healthcare system. Each CT scan was evaluated by a commercial ICH AI tool and a board-certified neuroradiologist; ground truth was defined as final radiologist determination of ICH presence/absence. After evaluating the AI tool's aggregate diagnostic performance, sub-analyses based on sociodemographic groups (age, sex, race, ethnicity, insurance status, and Area of Deprivation Index [ADI] scores) assessed for biases. χ2 test or Fisher's exact tests evaluated for statistical significance with p ≤ 0.05. RESULTS: Our patient population was 50% female (mean age 60 ± 19 years). The AI tool had an aggregate accuracy of 93% [9060/9736], sensitivity of 85% [1140/1338], specificity of 94% [7920/ 8398], positive predictive value (PPV) of 71% [1140/1618] and negative predictive value (NPV) of 98% [7920/8118]. Sociodemographic biases were identified, including lower PPV for patients who were females (67.3% [62,441/656] vs. 72.7% [699/962], p = 0.02), Black (66.7% [454/681] vs. 73.2% [686/937], p = 0.005), non-Hispanic/non-Latino (69.7% [1038/1490] vs. 95.4% [417/437]), p = 0.009), and who had Medicaid/Medicare (69.9% [754/1078]) or Private (66.5% [228/343]) primary insurance (p = 0.003). Lower sensitivity was seen for patients in the third quartile of national (78.8% [241/306], p = 0.001) and state ADI scores (79.0% [22/287], p = 0.001). CONCLUSIONS: In our healthcare system, a commercial AI tool had lower performance for ICH detection than previously reported and demonstrated several sociodemographic biases.

Nonaneurysmal perimesencephalic subarachnoid hemorrhage on noncontrast head CT: An accuracy, inter-rater, and intra-rater reliability study.

BACKGROUND AND PURPOSE: To evaluate the reliability and accuracy of nonaneurysmal perimesencephalic subarachnoid hemorrhage (NAPSAH) on Noncontrast Head CT (NCCT) between numerous raters. MATERIALS AND METHODS: 45 NCCT of adult patients with SAH who also had a catheter angiography (CA) were independently evaluated by 48 diverse raters; 45 raters performed a second assessment one month later. For each case, raters were asked: 1) whether they judged the bleeding pattern to be perimesencephalic; 2) whether there was blood anterior to brainstem; 3) complete filling of the anterior interhemispheric fissure (AIF); 4) extension to the lateral part of the sylvian fissure (LSF); 5) frank intraventricular hemorrhage; 6) whether in the hypothetical presence of a negative CT angiogram they would still recommend CA. An automatic NAPSAH diagnosis was also generated by combining responses to questions 2-5. Reliability was estimated using Gwet's AC1 (κG), and the relationship between the NCCT diagnosis of NAPSAH and the recommendation to perform CA using Cramer's V test. Multi-rater accuracy of NCCT in predicting negative CA was explored. RESULTS: Inter-rater reliability for the presence of NAPSAH was moderate (κG = 0.58; 95%CI: 0.47, 0.69), but improved to substantial when automatically generated (κG = 0.70; 95%CI: 0.59, 0.81). The most reliable criteria were the absence of AIF filling (κG = 0.79) and extension to LSF (κG = 0.79). Mean intra-rater reliability was substantial (κG = 0.65). NAPSAH weakly correlated with CA decision (V = 0.50). Mean sensitivity and specificity were 58% (95%CI: 44%, 71%) and 83 % (95%CI: 72 %, 94%), respectively. CONCLUSION: NAPSAH remains a diagnosis of exclusion. The NCCT diagnosis was moderately reliable and its impact on clinical decisions modest.

Comparison of image quality between a novel mobile CT scanner and current generation stationary CT scanners.

PURPOSE: Point-of-care imaging with mobile CT scanners offers several advantages, provided that the image quality is satisfactory. Our aim was to compare image quality of a novel mobile CT to stationary scanners for patients in a neurosurgical intensive care unit (ICU). METHODS: From November 2020 to April 2021, all patients above 18 years of age examined by a mobile CT scanner at a neurosurgical ICU were included if they also had a stationary head CT examination during the same hospitalization. Quantitative image quality parameters included attenuation and noise in six predefined regions of interest, as well as contrast-to-noise ratio between gray and white matter. Subjective image quality was rated on a 4-garde scale, by four radiologists blinded to scanner parameters. RESULTS: Fifty patients were included in the final study population. Radiation dose and image attenuation values were similar for mobCT and stationary CTs. There was a small statistically significant difference in subjective quality rating between mobCT and stationary CT images. Two radiologists favored the stationary CT images, one was neutral, and one favored mobCT images. For overall image quality, 14% of mobCT images were rated grade 1 (poor image quality) compared to 8% for stationary CT images. CONCLUSION: Point-of-care brain CT imaging was successfully performed on clinical neurosurgical ICU patients with small reduction in image quality, predominantly affecting the posterior fossa, compared to high-end stationary CT scanners.

A fast and accurate brain extraction method for CT head images.

BACKGROUND: Brain extraction is an essential prerequisite for the automated diagnosis of intracranial lesions and determines, to a certain extent, the accuracy of subsequent lesion recognition, location, and segmentation. Segmentation using a fully convolutional neural network (FCN) yields high accuracy but a relatively slow extraction speed. METHODS: This paper proposes an integrated algorithm, FABEM, to address the above issues. This method first uses threshold segmentation, closed operation, convolutional neural network (CNN), and image filling to generate a specific mask. Then, it detects the number of connected regions of the mask. If the number of connected regions equals 1, the extraction is done by directly multiplying with the original image. Otherwise, the mask was further segmented using the region growth method for original images with single-region brain distribution. Conversely, for images with multi-region brain distribution, Deeplabv3 + is used to adjust the mask. Finally, the mask is multiplied with the original image to complete the extraction. RESULTS: The algorithm and 5 FCN models were tested on 24 datasets containing different lesions, and the algorithm's performance showed MPA = 0.9968, MIoU = 0.9936, and MBF = 0.9963, comparable to the Deeplabv3+. Still, its extraction speed is much faster than the Deeplabv3+. It can complete the brain extraction of a head CT image in about 0.43 s, about 3.8 times that of the Deeplabv3+. CONCLUSION: Thus, this method can achieve accurate brain extraction from head CT images faster, creating a good basis for subsequent brain volume measurement and feature extraction of intracranial lesions.

Delirium, confusion, or altered mental status as a risk for abnormal head CT in older adults in the emergency department: A systematic review and meta-analysis.

BACKGROUND: Altered mental status (including delirium) is a common presentations among older adults to the emergency department (ED). We aimed to report the association between altered mental status in older ED patients and acute abnormal findings on head computed tomogram (CT). METHODS: A systematic review was conducted using Ovid Medline, Embase, Clinicaltrials.gov, Web of Science, and Cochrane Central from conception to April 8th, 2021. We included citations if they described patients aged 65 years or older who received head imaging at the time of ED assessment, and reported whether patients had delirium, confusion, or altered mental status. Screening, data extraction, and bias assessment were performed in duplicate. We estimated the odds ratios (OR) for abnormal neuroimaging in patients with altered mental status. RESULTS: The search strategy identified 3031 unique citations, of which two studies reporting on 909 patients with delirium, confusion or altered mental status were included. No identified study formally assessed for delirium. The OR for abnormal head CT findings in patients with delirium, confusion or altered mental status was 0.35 (95% CI 0.031 to 3.97) compared to patients without delirium, confusion or altered mental status. CONCLUSION: We did not find a statistically significant association between delirium, confusion or altered mental status and abnormal head CT findings in older ED patients.

Biomarker S100B in plasma a screening tool for mild traumatic brain injury in an emergency department.

INTRODUCTION: A computerized tomography (CT) scan is an effective test for detecting traumatic intracranial findings after mild traumatic brain injury (mTBI). However, a head CT is costly, and can only be performed in a hospital. OBJECTIVE: To determine if the addition of plasma S100B to clinical guidelines could lead to a more selective scanning strategy without compromising safety. METHODS: We conducted a single center prospective cohort study at the emergency department. Patients (≥16 years) who received head CT and had a blood draw were included. The primary outcome was the accuracy of plasma S100B to predict the presence of any traumatic intracranial lesion on head CT. RESULTS: We included 495 patients, out of the 74 patients who had traumatic intracranial lesions, 5 patients had a plasma S100B level below the cutoff value of 0.105 ug/L. For the detection of traumatic intracranial injury, S100B had a sensitivity of 0.932 , a specificity of 0.157, a negative predictive value of 0.930, and a positive predictive value of 0.163. CONCLUSIONS: Among patients undergoing guideline-based CT scan for mTBI, the use of S100B, would results in a further decrease (14.8%) of CT scans but at a cost of missed injury, without clinical consequence, on CT.

Ability of S100B to predict post-concussion syndrome in paediatric patients who present to the emergency department with mild traumatic brain injury.

INTRODUCTION: Among children who sustain mild traumatic brain injury (mTBI), 10-30% develop a cluster of cognitive, physical, and emotional symptoms commonly referred to as post-concussion syndrome (PCS). Symptoms typically resolve within 7-10 days, but a minority of patients report symptoms that persist for months or even years. The aim of our study was to identify a neurobiochemical marker after mTBI that can predict the presence of post-concussion syndrome three months after head injury in paediatric patients. MATERIALS AND METHODS: Children between 7 and 16 years of age who had head trauma and no other complaints were included. Three months after the initial visit, participants or parents/guardians were interviewed in person about the children's PCS symptoms using the Rivermead Post-Concussion Symptoms Questionnaire (RPQ). RESULTS: The mean value of S100B protein in serum in 38 patients without signs of PCS was 0.266 µg L-1, with a 95% confidence interval (CI) of 0.221 - 0.310 µg L-1. Among the 22 patients with signs of PCS, the mean value of S100B protein in serum was 0.845 µg L-1, with a 95% CI of 0.745-0.945 µg L-1. Patients with signs of PCS had higher S100B protein levels than those without signs of PCS (p < 0.0001). CONCLUSIONS: Our prospective study showed that S100B protein is a useful neurobiomarker for detecting paediatric patients at risk for post-concussion syndrome. We found that the biomarker S100B correlated with the severity of traumatic brain injury (number of lesions on CT) and the presence of post-concussion syndrome.

Time ratio disparities among ED patients undergoing head CT.

PURPOSE: To assess if patients who underwent head computed tomography (CT) experienced disparities in the emergency department (ED) and if the indication for head CT affected disparities. METHODS: This study employed a retrospective, IRB-approved cohort design encompassing four hospitals. All ED patients between January 2016 and September 2020 who underwent non-contrast head CTs were included. Furthermore, key time intervals including ED length of stay (LOS), ED assessment time, image acquisition time, and image interpretation time were calculated. Time ratio (TR) was used to compare these time intervals between the groups. RESULTS: A total of 45,177 ED visits comprising 4730 trauma cases, 5475 altered mental status cases, 11,925 cases with head pain, and 23,047 cases with other indications were included. Females had significantly longer ED LOS, ED assessment time, and image acquisition time (TR = 1.012, 1.051, 1.018, respectively, P-value < 0.05). This disparity was more pronounced in female patients with head pain complaints compared to their male counterparts (TR = 1.036, 1.059, and 1.047, respectively, P-value < 0.05). Black patients experienced significantly longer ED LOS, image acquisition time, and image assessment time (TR = 1.226, 1.349, and 1.190, respectively, P-value < 0.05). These disparities persisted regardless of head CT indications. Furthermore, patients with Medicare/Medicaid insurance also faced longer wait times in all the time intervals (TR > 1, P-value < 0.001). CONCLUSIONS: Wait times for ED head CT completion were longer for Black patients and Medicaid/Medicare insurance holders. Additionally, females experienced extended wait times, particularly when presented with head pain complaints. Our findings underscore the importance of exploring and addressing the contributing factors to ensure equitable and timely access to imaging services in the ED.

Artificial Intelligence Model Trained with Sparse Data to Detect Facial and Cranial Bone Fractures from Head CT.

The presence of cranial and facial bone fractures is an important finding on non-enhanced head computed tomography (CT) scans from patients who have sustained head trauma. Some prior studies have proposed automatic cranial fracture detections, but studies on facial fractures are lacking. We propose a deep learning system to automatically detect both cranial and facial bone fractures. Our system incorporated models consisting of YOLOv4 for one-stage fracture detection and improved ResUNet (ResUNet++) for the segmentation of cranial and facial bones. The results from the two models mapped together provided the location of the fracture and the name of the fractured bone as the final output. The training data for the detection model were the soft tissue algorithm images from a total of 1,447 head CT studies (a total of 16,985 images), and the training data for the segmentation model included 1,538 selected head CT images. The trained models were tested on a test dataset consisting of 192 head CT studies (a total of 5,890 images). The overall performance achieved a sensitivity of 88.66%, a precision of 94.51%, and an F1 score of 0.9149. Specifically, the cranial and facial regions were evaluated and resulted in a sensitivity of 84.78% and 80.77%, a precision of 92.86% and 87.50%, and F1 scores of 0.8864 and 0.8400, respectively. The average accuracy for the segmentation labels concerning all predicted fracture bounding boxes was 80.90%. Our deep learning system could accurately detect cranial and facial bone fractures and identify the fractured bone region simultaneously.

Association of hypoxic ischemic brain injury on early CT after out of hospital cardiac arrest with neurologic outcome.

AIM: This study aimed to describe the prevalence of hypoxic-ischemic brain injury (HIBI) on head CT (HCT) obtained within two hours of return of spontaneous circulation (ROSC) care in the Emergency Department following out-of-hospital cardiac arrest (OHCA) and evaluate the association between early HIBI and neurologic outcome. METHODS: Retrospective single center observational study of post-OHCA patients between 2009 and 2017. Two cohorts were analyzed: those who underwent non-contrast HCT within two hours of ROSC and all others who survived to ICU admission. HIBI was defined as the presence of cerebral edema and/or abnormal gray-white matter differentiation in the HCT interpretation by a neuroradiologist. The primary outcomes were the prevalence of HIBI on early HCT and the magnitude of the association between HIBI and survival with good neurologic outcome using multivariable logistic regression. RESULTS: Following OHCA, 333 of 520 patients (64%) underwent HCT within two hours of ROSC and HIBI was present in 96 of 333 patients (29%). Of the early HCT cohort, those with HIBI had a significantly lower hospital survival (2%) and favorable neurologic outcome (1%). In those without HIBI on imaging, 88 of 237 patients (37%) had a favorable outcome. After adjustment for confounding variables, HIBI on early HCT was independently associated with a decreased likelihood of good neurologic outcome (aOR 0.015, 95% CI 0.002-0.12). CONCLUSION: HIBI was present on 29% of HCTs obtained within 2 h of ROSC in the patients selected for early imaging by emergency physicians and was strongly and inversely associated with survival with a good neurologic outcome.

Foundations of Brain Image Segmentation: Pearls and Pitfalls in Segmenting Intracranial Blood on Computed Tomography Images.

Not only the time-dependent varying of signal intensity (i.e. haematoma evolution) characteristics of the intracranial blood in computed tomography images, but also the fluctuating image quality, the distortions introduced after medical interventions, and the brain deformations and intensity profile variations due to underlying pathologies make the segmentation of intracranial blood a challenging task. In addition to describing various challenges with blood segmentation, this chapter also reviews the following: (1) the general concept of segmentation-explaining why a proper segmentation is a critical step when creating machine learning algorithms for image detection purposes, (2) the different segmentation types and how different medical conditions and technical issues can further complicate this task, (3) how to choose a proper software to facilitate the segmentation task, and (4) useful tips that may be applied before launching a similar segmentation project.

Deep learning versus iterative image reconstruction algorithm for head CT in trauma.

PURPOSE: To compare the image quality between a deep learning-based image reconstruction algorithm (DLIR) and an adaptive statistical iterative reconstruction algorithm (ASiR-V) in noncontrast trauma head CT. METHODS: Head CT scans from 94 consecutive trauma patients were included. Images were reconstructed with ASiR-V 50% and the DLIR strengths: low (DLIR-L), medium (DLIR-M), and high (DLIR-H). The image quality was assessed quantitatively and qualitatively and compared between the different reconstruction algorithms. Inter-reader agreement was assessed by weighted kappa. RESULTS: DLIR-M and DLIR-H demonstrated lower image noise (p < 0.001 for all pairwise comparisons), higher SNR of up to 82.9% (p < 0.001), and higher CNR of up to 53.3% (p < 0.001) compared to ASiR-V. DLIR-H outperformed other DLIR strengths (p ranging from < 0.001 to 0.016). DLIR-M outperformed DLIR-L (p < 0.001) and ASiR-V (p < 0.001). The distribution of reader scores for DLIR-M and DLIR-H shifted towards higher scores compared to DLIR-L and ASiR-V. There was a tendency towards higher scores with increasing DLIR strengths. There were fewer non-diagnostic CT series for DLIR-M and DLIR-H compared to ASiR-V and DLIR-L. No images were graded as non-diagnostic for DLIR-H regarding intracranial hemorrhage. The inter-reader agreement was fair-good between the second most and the less experienced reader, poor-moderate between the most and the less experienced reader, and poor-fair between the most and the second most experienced reader. CONCLUSION: The image quality of trauma head CT series reconstructed with DLIR outperformed those reconstructed with ASiR-V. In particular, DLIR-M and DLIR-H demonstrated significantly improved image quality and fewer non-diagnostic images. The improvement in qualitative image quality was greater for the second most and the less experienced readers compared to the most experienced reader.

Radiographic risk factors for intracranial hemorrhage in patients with left ventricular assist devices.

OBJECTIVE: Intracranial hemorrhage (ICH) in patients with left ventricular assist devices (LVAD) is a devastating complication. Demographic risk factors for ICH in LVAD patients are defined, however anatomic predispositions to ICH are unknown. We sought to interrogate intracranial radiographic risk factors for ICH in LVAD patients. METHODS: We reviewed 440 patients who received an LVAD from 2008-2021. We selected patients with CT scans of the head either before or after LVAD placement, but typically within 5 years. 288 patients (21 ICH, 267 Control) with imaging were included. A detailed chart review was performed on demographics, radiographic features, and management. RESULTS: The incidence of ICH in our total cohort was 8.6% (38/440). The presence of pump thrombosis (p=0.001), driveline infection (p=0.034), other hemorrhage (p=0.001), or previous placement of a cardio-defibrillator (p=.003) was associated with increased risk for ICH. An analysis of imaging revealed that the presence of a mass (p=0.006), vascular pathology (p=0.001), and microangiopathy (p=0.04) was significantly associated with ICH in LVAD patients. These radiographic features were validated with a multivariate logistic regression which confirmed presence of a mass (aOR 332.1, 95% CI: 14.7-7485.1, p<0.001), vascular pathology (aOR 69.7, 95% CI: 1.8-2658.8, p=0.022), and microangiopathy (aOR 6.5, 95% CI: 1.1-37.6, p=0.035) were independently associated with ICH. CONCLUSION: Radiographic evidence of microangiopathy, intracranial mass, and vascular pathology are independent risk factors for ICH which are readily identified by imaging. We advocate that CT imaging be used to further stratify patients at highest risk of ICH during treatment with an LVAD.

Pediatric Skull Fractures Contacting Sutures: Relevance in Abusive Head Trauma.

OBJECTIVE. The purpose of this study was to assess the incidence of pediatric skull fractures contacting cranial sutures in abusive versus accidental trauma. MATERIALS AND METHODS. A retrospective review was conducted of head CT studies performed for pediatric head trauma at a free-standing tertiary care children's hospital from 2012 to 2019. Statistical odds ratios were evaluated to assess the significance of skull fracture extension to sutures in abusive versus accidental injury. A two-proportion Z-test was used to determine the statistical significance of suture type contacted by skull fractures in accidental versus abusive injury. RESULTS. The records of 47 children with 57 abusive skull fractures and 47 children with 54 accidental skull fractures were evaluated. The patients were 1-36 months old. Fifty-one abusive skull fractures (89%) terminated in contact with a cranial suture; 35 of the 51 (69%) touched two or more sutures, and 12 touched three or more sutures. Forty-two of the 54 (78%) accidental skull fractures contacted a suture; only 3 of the 42 (7%) touched two sutures, and none touched more than two sutures (odds ratio, 28.4 [95% CI, 7.6-105.9]; p < .001). In the abusive fractures, the suture most commonly contacted by a fracture line was the lambdoid (43%; p < .04), followed by the sagittal (23%), coronal (21%), temporal-squamous (12%), and metopic (1%) sutures. There was no statistical difference in which suture was contacted by fracture lines in accidental cases. CONCLUSION. Skull fracture contacting cranial sutures is common in abusive and accidental pediatric head trauma. However, that a fracture contacts two or more cranial sutures is an imaging finding not previously described that has a significantly higher association with abusive than with accidental head injury.

Utility of Hounsfield unit in the diagnosis of tandem occlusion in acute ischemic stroke.

BACKGROUND: Tandem occlusions can complicate medical and endovascular stroke treatment. To identify these occlusions, computed tomography angiography (CTA) represents the best imaging modality. However, CTA is still not initially performed in some patients not admitted directly to stroke centers. Early identification of an additional occlusion of the proximal extracranial internal carotid artery may improve the best suitable treatment strategy. The purpose of this study was to find a valuable threshold of thrombus attenuation in a non-contrast head CT (NCCT) scan to facilitate a safe diagnosis of tandem occlusions. MATERIALS AND METHODS: Consecutive patients with acute middle cerebral artery (MCA) occlusions who underwent endovascular treatment were identified from our registry of neuroendovascular interventions. Thrombus attenuations of the affected MCA and contralateral vessel were measured by NCCT. To compare individual baseline blood attenuations, the difference between the thrombus attenuation and the contralateral MCA attenuation (referred to as ΔTM) was calculated. RESULTS: Three hundred and twenty-five patients were included. There was a highly significant difference between mean thrombus attenuation with isolated MCA occlusion and additional extracranial internal carotid artery (ICA) occlusion (49.9 ± 8 vs. 56.2 ± 10 Hounsfield units (HU); P < 0.001). The area under the receiver operating characteristic curve of ΔTM was 0.72. The optimal threshold value was 13.5 HU, with a sensitivity of 67.5% and a specificity of 68.6%. CONCLUSION: Despite a significant difference in thrombus attenuation in MCA occlusions with an additional extracranial ICA occlusion compared with isolated MCA occlusions, a relevant threshold of thrombus attenuation was not found.

Sedatives used in children to obtain head CT in the emergency department.

OBJECTIVES: Children in the emergency department who require computerized tomography (CT) of the head often are given sedative medications to facilitate completion of the study with adequate imaging. A prior study found the two most common medications used to obtain head CT in children were pentobarbital and chloral hydrate; however, these medications have become less popular. We hypothesized that there was variability in medication choice amongst providers in the emergency department and there has been a change in the preferred sedatives used in the last decade. METHODS: We conducted a retrospective multicenter cross-sectional study of children 0-18 years old who received a medication with sedative properties and underwent head CT while in the emergency department from 2007 to 2018, using the Pediatric Health Information System (PHIS) database. The primary outcome measure was the frequency of administration of drugs within an individual sedative class. RESULTS: We analyzed 24,418 patient encounters, of whom 53% received an opioid and 41% received a benzodiazepine. There were statistically significant decreases in the use of barbiturates, chloral hydrate, anti-emetic sedatives, and opioids, while increases in barbiturate combination drugs, benzodiazepines and dexmedetomidine were observed over the study period. The majority of medications were administered parenterally. CONCLUSION: There is wide variability in sedatives used in children to obtain head CT and the preferred drugs have shifted over the last decade.

Radiation safety education and diagnostic imaging in pediatric patients with surgically treated hydrocephalus: the patient and family perspective.

PURPOSE: Surgically treated hydrocephalus patients are frequently imaged with head computed tomography (CT), and risk/benefit communication with families is inconsistent and unknown. We aimed to educate patients and caregivers about radiation safety in CT and explore their communication preferences. METHODS: We conducted a pediatric CT radiation safety and diagnostic imaging educational workshop for patients and caregivers at a national conference on hydrocephalus to characterize current practice and desired communication about CT imaging. Our workshop consisted of an interactive educational intervention with pre-/post-session surveys followed by feedback from participants. RESULTS: Our session included 34 participants (100% response rate for surveys) with 28 being parents of individuals with hydrocephalus. A total of 76% (n = 26) participants showed an increase in knowledge after the session (p < 0.01). All participants (N = 34) uniformly desired risk/benefit discussions before CT scans. However, 71% stated that they were not informed of risks/benefits of CT scans by a medical professional. Following the session, the number of participants indicating that informed consent should be obtained before CT scans increased from 30 to 33. Respondents also revealed that 14% of children and young adults had received > 100 CT scans for shunt evaluation with the median being 25 scans (IQR 20). CONCLUSIONS: Caregivers desire and deserve to be empowered through education and social support, and continuously engaged through sharing decisions and co-designing care plans. The neurosurgical community is in an ideal position to collaborate with radiologists, primary care providers, and parents in the development and testing of credible, high-quality online and social media resources.