Noncontrast Head Computed Tomography Scan Research Articles

Assessment of image quality and impact of deep learning-based software in non-contrast head CT scans

In this retrospective study, we aimed to assess the objective and subjective image quality of different reconstruction techniques and a deep learning-based software on non-contrast head computed tomography (CT) images. In total, 152 adult head CT scans (77 female, 75 male; mean age 69.4 ± 18.3 years) obtained from three different CT scanners using different protocols between March and April 2021 were included. CT images were reconstructed using filtered-back projection (FBP), iterative reconstruction (IR), and post-processed using a deep learning-based algorithm (PS). Post-processing significantly reduced noise in FBP-reconstructed images (up to 15.4% reduction) depending on the protocol, leading to improvements in signal-to-noise ratio of up to 19.7%. However, when deep learning-based post-processing was applied to FBP images compared to IR alone, the differences were inconsistent and partly non-significant, which appeared to be protocol or site specific. Subjective assessments showed no significant overall improvement in image quality for all reconstructions and post-processing. Inter-rater reliability was low and preferences varied. Deep learning-based denoising software improved objective image quality compared to FBP in routine head CT. A significant difference compared to IR was observed for only one protocol. Subjective assessments did not indicate a significant clinical impact in terms of improved subjective image quality, likely due to the low noise levels in full-dose images.

Estimate and compensate head motion in non-contrast head CT scans using partial angle reconstruction and deep learning.

Patient head motion is a common source of image artifacts in computed tomography (CT) of the head, leading to degraded image quality and potentially incorrect diagnoses. The partial angle reconstruction (PAR) means dividing the CT projection into several consecutive angular segments and reconstructing each segment individually. Although motion estimation and compensation using PAR has been developed and investigated in cardiac CT scans, its potential for reducing motion artifacts in head CT scans remains unexplored. To develop a deep learning (DL) model capable of directly estimating head motion from PAR images of head CT scans and to integrate the estimated motion into an iterative reconstruction process to compensate for the motion. Head motion is considered as a rigid transformation described by six time-variant variables, including the three variables for translation and three variables for rotation. Each motion variable is modeled using a B-spline defined by five control points (CP) along time. We split the full projections from 360° into 25 consecutive PARs and subsequently input them into a convolutional neural network (CNN) that outputs the estimated CPs for each motion variable. The estimated CPs are used to calculate the object motion in each projection, which are incorporated into the forward and backprojection of an iterative reconstruction algorithm to reconstruct the motion-compensated image. The performance of our DL model is evaluated through both simulation and phantom studies. The DL model achieved high accuracy in estimating head motion, as demonstrated in both the simulation study (mean absolute error (MAE) ranging from 0.28 to 0.45mm or degree across different motion variables) and the phantom study (MAE ranging from 0.40 to 0.48mm or degree). The resulting motion-corrected image, , exhibited a significant reduction in motion artifacts when compared to the traditional filtered back-projection reconstructions, which is evidenced both in the simulation study (image MAE drops from 178 33HU to 37 9HU, structural similarity index (SSIM) increases from 0.60 0.06 to 0.98 0.01) and the phantom study (image MAE drops from 117 17HU to 42 19HU, SSIM increases from 0.83 0.04 to 0.98 0.02). We demonstrate that using PAR and our proposed deep learning model enables accurate estimation of patient head motion and effectively reduces motion artifacts in the resulting head CT images.

Uncertainty-aware deep-learning model for prediction of supratentorial hematoma expansion from admission non-contrast head computed tomography scan

Hematoma expansion (HE) is a modifiable risk factor and a potential treatment target in patients with intracerebral hemorrhage (ICH). We aimed to train and validate deep-learning models for high-confidence prediction of supratentorial ICH expansion, based on admission non-contrast head Computed Tomography (CT). Applying Monte Carlo dropout and entropy of deep-learning model predictions, we estimated the model uncertainty and identified patients at high risk of HE with high confidence. Using the receiver operating characteristics area under the curve (AUC), we compared the deep-learning model prediction performance with multivariable models based on visual markers of HE determined by expert reviewers. We randomly split a multicentric dataset of patients (4-to-1) into training/cross-validation (n = 634) versus test (n = 159) cohorts. We trained and tested separate models for prediction of ≥6 mL and ≥3 mL ICH expansion. The deep-learning models achieved an AUC = 0.81 for high-confidence prediction of HE≥6 mL and AUC = 0.80 for prediction of HE≥3 mL, which were higher than visual maker models AUC = 0.69 for HE≥6 mL (p = 0.036) and AUC = 0.68 for HE≥3 mL (p = 0.043). Our results show that fully automated deep-learning models can identify patients at risk of supratentorial ICH expansion based on admission non-contrast head CT, with high confidence, and more accurately than benchmark visual markers.

Decreasing Lens Irradiation on Brain Imaging: A Multi-CT Scanner Quality Improvement Project.

Cataracts, a leading global cause of blindness, are associated with ionising radiation exposure. This audit aimed to enhance lens exclusion during non-contrast head computed tomography (CT) scans at Newham University Hospital (NUH) using two CT scanners. A retrospective audit of non-contrast head CT scans at NUH excluded scans for trauma and imaging of orbital structures. A one-week audit in April 2023 assessed lens exclusion, compared to the Royal College of Radiologists (RCR) standards. A total of 101 consecutive scans were analysed and 63 (62%) scans were included in the final study. Thirty-eight percent of the scans were excluded according to the exclusion criteria of head, neckand facial traumas, orbital infectionsand papilledema. Results were presented, followed by a three-month radiographer re-education period, emphasizing gantry tilt and patient positioning. A reaudit in August 2023 evaluated outcomes. For the reaudit, 183 consecutive scans were analysed, with 131 (72%) scans included in the final studyand 52 (28%) scans excluded according to the same exclusion criteria as the first audit. Lens exclusion in non-contrast head CT scans improved significantly from 0/63 (0%) compliance to 19/131 (14.50%) (p=0005) compliance with the standards. Variability in radiographer practices, 'near misses' and time constraints were identified as challenges. Staff turnover impacted compliance. This audit has shed light on a critical aspect of patient care in the field of radiology. This research underscores the importance of rigorous and standardised protocols in radiological procedures, particularly when it comes to protecting the lens of the eye. By enhancing lens exclusion during non-contrast head CT scans, we have taken a significant step in mitigating the risk associated with ionising radiation exposure. Although substantial improvements were made, achieving the RCR audit standard remained elusive. Ongoing re-education, reauditsand a multidisciplinary approach are necessary to optimise radiographer adherence and reduce ionising radiation exposure to the lens during head CT scans.This quality improvement project proves thatcontinued emphasis on gantry tilt and patient positioning in radiographer education and training can make a significant difference in patient safety.As we move forward, let us remember that even small improvements can make a big difference in safeguarding the health and well-being of patients.

Real world validation of an AI-based CT hemorrhage detection tool.

Intracranial hemorrhage (ICH) is a potentially life-threatening medical event that requires expedited diagnosis with computed tomography (CT). Automated medical imaging triaging tools can rapidly bring scans containing critical abnormalities, such as ICH, to the attention of radiologists and clinicians. Here, we retrospectively investigated the real-world performance of VeriScout™, an artificial intelligence-based CT hemorrhage detection and triage tool. Ground truth for the presence or absence of ICH was iteratively determined by expert consensus in an unselected dataset of 527 consecutively acquired non-contrast head CT scans, which were sub-grouped according to the presence of artefact, post-operative features and referral source. The performance of VeriScout™ was compared with the ground truths for all groups. VeriScout™ detected hemorrhage with a sensitivity of 0.92 (CI 0.84-0.96) and a specificity of 0.96 (CI 0.94-0.98) in the global dataset, exceeding the sensitivity of general radiologists (0.88) with only a minor relative decrement in specificity (0.98). Crucially, the AI tool detected 13/14 cases of subarachnoid hemorrhage, a potentially fatal condition that is often missed in emergency department settings. There was no decrement in the performance of VeriScout™ in scans containing artefact or postoperative change. Using an integrated informatics platform, VeriScout™ was deployed into the existing radiology workflow. Detected hemorrhage cases were flagged in the hospital radiology information system (RIS) and relevant, annotated, preview images made available in the picture archiving and communications system (PACS) within 10 min. AI-based radiology worklist prioritization for critical abnormalities, such as ICH, may enhance patient care without adding to radiologist or clinician burden.

Prevalence of and Risk Factors for Post-traumatic Headache in Civilian Patients After Mild Traumatic Brain Injury: A TRACK-TBI Study

ObjectiveTo ascertain the prevalence of and risk factors for post-traumatic headache (PTH) attributed to mild traumatic brain injury (mTBI). Patients and MethodsA prospective, longitudinal, multicenter cohort study of patients with mTBI and orthopedic trauma controls who were enrolled from February 26, 2014, to August 8, 2018. The baseline assessment was conducted as soon as possible following evaluation at the emergency department. Follow-ups were scheduled at 2 weeks, 3 months, 6 months, and 12 months postinjury. Eligible patients with mTBI included those 18 years of age or older who presented to the emergency department within 24 hours of head injury warranting evaluation by noncontrast head computed tomography scan. Acute PTH was considered present when a patient reported a headache score of greater than or equal to 2 on the Rivermead Post-concussion Questionnaire at 2 weeks postinjury (ie, headache is at least a mild problem compared with pre-injury). Persistent PTH was defined when a patient with acute PTH reported a Rivermead Post-concussion Questionnaire headache score of greater than or equal to 2 at the scheduled follow-up examinations. ResultsAcute PTH was reported by 963 (60.4%) of 1594 patients with mTBI at 2 weeks postinjury. Among those with acute PTH, 439 (52.4%) of 837 patients reported persistent PTH at 3 months postinjury. This figure decreased over time and 278 (37.5%) of 742 patients continued to report persistent PTH at 6 months, whereas 187 (28.9%) of 646 patients did so as well at 12 months postinjury. Risk factors for acute PTH included younger age, female sex, fewer years of formal education, computed tomography–positive scans, alteration of consciousness, psychiatric history, and history of migraine. Risk factors for persistent PTH included female sex, fewer years of formal education, and history of migraine. ConclusionPost-traumatic headache is a prevalent sequela of mTBI that persists for at least 12 months in a considerable proportion of affected individuals. The attributable burden necessitates better patient follow-up, disease characterization, improved awareness of PTH in clinical practice, and identification of effective therapies.

Artificial intelligence for detection of intracranial haemorrhage on head computed tomography scans: diagnostic accuracy in Hong Kong.

The use of artificial intelligence (AI) to identify acute intracranial haemorrhage (ICH) on computed tomography (CT) scans may facilitate initial imaging interpretation in the accident and emergency department. However, AI model construction requires a large amount of annotated data for training, and validation with real-world data has been limited. We developed an algorithm using an open-access dataset of CT slices, then assessed its utility in clinical practice by validating its performance on CT scans from our institution. Using a publicly available international dataset of >750 000 expert-labelled CT slices, we developed an AI model which determines ICH probability for each CT scan and nominates five potential ICH-positive CT slices for review. We validated the model using retrospective data from 1372 non-contrast head CT scans (84 [6.1%] with ICH) collected at our institution. The model achieved an area under the curve of 0.842 (95% confidence interval=0.791-0.894; P<0.001) for scan-based detection of ICH. A pre-specified probability threshold of ≥50% for the presence of ICH yielded 78.6% accuracy, 73% sensitivity, 79% specificity, 18.6% positive predictive value, and 97.8% negative predictive value. There were 62 true-positive scans and 22 false-negative scans, which could be reduced to six false-negative scans by manual review of model-nominated CT slices. Our model exhibited good accuracy in the CT scan-based detection of ICH, considering the low prevalence of ICH in Hong Kong. Model refinement to allow direct localisation of ICH will facilitate the use of AI solutions in clinical practice.

Headache, vision changes and cranial nerve palsy after head trauma.

A 43-year-old female was brought to the hospital after a ground level fall and her Glasgow Coma Scale was 15. Non-contrast head computed tomography (CT) scan showed small bilateral subdural hematomas, left traumatic subarachnoid hemorrhage, left occipital bone and left longitudinal temporal bone fractures. She was managed conservatively. Interval repeat non-contrast head CT scans showed resolution of the hemorrhage. Two and a half months later she presented to the hospital with headaches, intermittent diplopia, blurry vision and a right lateral gaze palsy. Non-contrast head CT scan showed mild hyperattenuation in the cavernous sinus. Subsequently, a CT angiogram of the head was obtained that showed opacification of the bilateral cavernous sinus and distention of the orbital veins (Figure 1A,B). Evaluation with diagnostic cerebral angiogram showed direct bilateral carotid-cavernous fistulas (CCFs) (Figures 2 and 3). She underwent staged embolization of the CCFs. Direct CCF is the abnormal connection between the internal carotid artery and the cavernous sinus.1, 2 CCFs can present with the classic triad of chemosis, pulsatile proptosis and ocular bruit.3, 4 Other symptoms include orbital pain, abducens nerve palsy, deterioration of visual acuity and ophthalmoplegia.4, 5 Causes of CCF formation are traumatic, iatrogenic, connective tissue disorders and spontaneous.2, 6-9 Traumatic CCFs formation occurs in up to 1.25% of patients with traumatic brain injury or facial and skull base fractures.10, 11 Bilateral CCF formation is rare after trauma and symptoms develop in a delayed fashion.10-15 Treatment options include conservative management, open surgery, endovascular procedures and radiosurgery.16-18

Acute subdural hematoma during sexual intercourse due to an aneurysm rupture on posterior communicating artery: a case report

Patients with an acute subdural hematoma (aSDH) usually have a history of head trauma, but some patients may present with spontaneous aSDH due to a ruptured aneurysm. Spontaneous aSDH is a rare manifestation of aneurysmal rupture. However, aneurysmal rupture remains a major cause of spontaneous aSDH. A 42-year-old man was brought to the emergency room because of a sudden loss of consciousness during sexual intercourse. The patient has seizures and weakness on the right side of his body. The patient has no history of trauma and has never taken anticoagulant or antiplatelet drugs, sexual aphrodisiacs, or other drugs. Physical examination revealed the Glasgow Coma Scale of E2V1M3, ptosis on the left eye, left pupil mydriasis, right central facial palsy, and right hemiparesis. Laboratory results showed hypercoagulopathy. Noncontrast head computed tomography scan revealed subdural hematoma with no subarachnoid or intraparenchymal hemorrhage. The patient underwent an emergency craniotomy, and the hematoma was evacuated. Cerebral angiography was performed 1 week later, revealing a saccular aneurysm in the left posterior communicating artery. The patient has successfully undergone endovascular coiling and was discharged from the hospital in good condition, fully conscious, with no weakness in half side of the body, but there is still third nerve palsy. Patients with pure aSDH without a history of trauma should consider the possibility of aneurysm rupture and perform an angiographic examination to rule out vascular malformations so that the patient can receive appropriate treatment.

Prior knowledge-based precise diagnosis of blend sign from head computed tomography.

Automated diagnosis of intracranial hemorrhage on head computed tomography (CT) plays a decisive role in clinical management. This paper presents a prior knowledge-based precise diagnosis of blend sign network from head CT scans. We employ the object detection task as an auxiliary task in addition to the classification task, which could incorporate the hemorrhage location as prior knowledge into the detection framework. The auxiliary task could help the model pay more attention to the regions with hemorrhage, which is beneficial for distinguishing the blend sign. Furthermore, we propose a self-knowledge distillation strategy to deal with inaccuracy annotations. In the experiment, we retrospectively collected 1749 anonymous non-contrast head CT scans from the First Affiliated Hospital of China Medical University. The dataset contains three categories: no intracranial hemorrhage (non-ICH), normal intracranial hemorrhage (normal ICH), and blend sign. The experimental results demonstrate that our method performs better than other methods. Our method has the potential to assist less-experienced head CT interpreters, reduce radiologists' workload, and improve efficiency in natural clinical settings.

Cisternal Score: A Radiographic Score to Predict Ventriculoperitoneal Shunt Requirement in Aneurysmal Subarachnoid Hemorrhage.

Persistent hydrocephalus requiring a ventriculoperitoneal shunt (VPS) can complicate the management of aneurysmal subarachnoid hemorrhage (aSAH). Identification of high-risk patients may guide external ventricular drain management. To identify early radiographic predictors for persistent hydrocephalus requiring VPS placement. In a 2-center retrospective study, we compared radiographic features on admission noncontrast head computed tomography scans of patients with aSAH requiring a VPS to those who did not, at 2 referral academic centers from 2016 through 2021. We quantified blood clot thickness in the basal cisterns including interpeduncular, ambient, crural, prepontine, interhemispheric cisterns, and bilateral Sylvian fissures. We then created the cisternal score (CISCO) using features that were significantly different between groups. We included 229 survivors (mean age 55.6 years [SD 13.1]; 63% female) of whom 50 (22%) required VPS. CISCO was greater in patients who required a VPS than those who did not (median 4, IQR 3-6 vs 2, IQR 1-4; P < .001). Higher CISCO was associated with higher odds of developing persistent hydrocephalus with VPS requirement (odds ratio 1.6 per point increase, 95% CI 1.34-1.9; P < .001), independent of age, Hunt and Hess grades, and modified GRAEB scores. CISCO had higher accuracy in predicting VPS requirement (area under the curve 0.75, 95% CI 0.68-0.82) compared with other predictors present on admission. Cisternal blood clot quantification on admission noncontrast head computed tomography scan is feasible and can be used in predicting persistent hydrocephalus with VPS requirement in patients with aSAH. Future prospective studies are recommended to further validate this tool.

Emergency Medicine Images: Headache After a Lumbar Puncture

A 34-year-old man presented to the emergency department for a persistent, positional headache 3 weeks after a routine lumbar puncture (LP) for the workup of multiple sclerosis. The headache started gradually approximately 1 week after the uneventful LP and consistently improved with lying flat and worsened when upright. At a previous ED visit for this headache, an epidural blood patch was considered for postdural puncture headache (PDPH); however, the anesthesia service did not think a blood patch would be better than conservative treatment, given the usual benign course and the expectation for near-term resolution of symptoms with PDPH. With the patient experiencing persistent symptoms affecting his daily activities despite home analgesics, the ED clinician ordered a noncontrast head computed tomography scan (CT) (Figures 1 and 2). Figure 2Coronal noncontrast head computed tomographyt. There are bilateral convexity subdural hematomas (arrows) and subdural hematoma along the interhemispheric fissure (chevrons). The lateral ventricles partially effaced. View Large Image Figure Viewer Download Hi-res image Brian J. Ahern is a Physician Assistant at the Department of Emergency Medicine, William Beaumont Army Medical Center, Fort Bliss, TX. ORCID identifier: http://orcid.org/0000-0002-5701-3561. Lisa M. Jin is a Physician Assistant at the Department of Emergency Medicine, William Beaumont Army Medical Center, Fort Bliss, TX. Sean M. Sylvia is a Physician Assistant at the Department of Emergency Medicine, William Beaumont Army Medical Center, Fort Bliss, TX.

Association of Noncontrast Computed Tomography and Perfusion Modalities With Outcomes in Patients Undergoing Late-Window Stroke Thrombectomy

There is substantial controversy with regards to the adequacy and use of noncontrast head computed tomography (NCCT) for late-window acute ischemic stroke in selecting candidates for mechanical thrombectomy. To assess clinical outcomes of patients with acute ischemic stroke presenting in the late window who underwent mechanical thrombectomy stratified by NCCT admission in comparison with selection by CT perfusion (CTP) and diffusion-weighted imaging (DWI). In this multicenter retrospective cohort study, prospectively maintained Stroke Thrombectomy and Aneurysm (STAR) database was used by selecting patients within the late window of acute ischemic stroke and emergent large vessel occlusion from 2013 to 2021. Patients were selected by NCCT, CTP, and DWI. Admission Alberta Stroke Program Early CT Score (ASPECTS) as well as confounding variables were adjusted. Follow-up duration was 90 days. Data were analyzed from November 2021 to March 2022. Selection by NCCT, CTP, or DWI. Primary outcome was functional independence (modified Rankin scale 0-2) at 90 days. Among 3356 patients, 733 underwent late-window mechanical thrombectomy. The median (IQR) age was 69 (58-80) years, 392 (53.5%) were female, and 449 (65.1%) were White. A total of 419 were selected with NCCT, 280 with CTP, and 34 with DWI. Mean (IQR) admission ASPECTS were comparable among groups (NCCT, 8 [7-9]; CTP, 8 [7-9]; DWI 8, [7-9]; P = .37). There was no difference in the 90-day rate of functional independence (aOR, 1.00; 95% CI, 0.59-1.71; P = .99) after adjusting for confounders. Symptomatic intracerebral hemorrhage (NCCT, 34 [8.6%]; CTP, 37 [13.5%]; DWI, 3 [9.1%]; P = .12) and mortality (NCCT, 78 [27.4%]; CTP, 38 [21.1%]; DWI, 7 [29.2%]; P = .29) were similar among groups. In this cohort study, comparable outcomes were observed in patients in the late window irrespective of neuroimaging selection criteria. Admission NCCT scan may triage emergent large vessel occlusion in the late window.

Atrial Fibrillation Detected After Acute Ischemic Stroke

Atrial fibrillation (AF) increases 4-5 times incidence of cardiac embolic stroke. In contrast, as many as 70% of AF cases can be detected in stroke within three days of onset, and this can affect the patient's prognosis. This case report describes the causal pathophysiology of AF and acute stroke and identifies the associated risk factors. Case 1 is a 44-year-old woman, acute stroke with acute decrease level of consciousness. The patient came with status epilepticus and a hypertensive emergency. Obtained a history of stroke, uncontrolled hypertension, and myocardial infarction. Initial Score National Institutes of Health Stroke Scale (NIHSS) was 33 and CHA2DS2-VASc was 5. Investigation non-contrast head Computed Tomography (CT) scan showed no bleeding and echocardiography (ECG) showed AF with rapid ventricular response. The patient died after 3 days of treatment. Case 2 is an 83-year-old woman, acute stroke with acute decrease level of consciousness and right motor lateralization. There was a history of hypertension and stroke with left hemiparesis. The initial NIHSS was 28 and CHA2DS2-VASc was 6. Investigations non-contrast head CT scan showed no bleeding and ECG showed AF with normal ventricular response. The patient was discharged from the hospital after being treated for 22 days with NIHSS of 20. Several risk factors for post-stroke AF are elderly, hypertension, subtype of ischemic stroke, prior stroke, and comorbidities such as DM and hypertension. Post-stroke AF can occur because of changes in heart rhythm through autonomic disorders, increased plasma catecholamine levels, and inflammatory reactions. Early Recognition of risk factors, focusing on patients at higher risk of AF detected after stroke becomes important for comprehensive management of stroke with AF.&#x0D; Keywords: acute ischemic stroke, atrial fibrillation, CHA2DS2-VASc score, risk factors.

Performance of Automated RAPID Intracranial Hemorrhage Detection in Real-World Practice: A Single-Institution Experience.

Intracranial hemorrhage (ICH) is a common finding in patients presenting to the emergency department with acute neurological symptoms. Noncontrast head computed tomography (NCCT) is the primary modality for assessment and detection of ICH in the acute setting. RAPID ICH software aims to automatically detect ICH on NCCT and was previously shown to have high accuracy when applied to a curated test data set. Here, we measured the test performance characteristics of RAPID ICH software in detecting ICH on NCCT performed in patients undergoing emergency stroke evaluation at a tertiary academic comprehensive stroke center. This retrospective study assessed consecutive patients over a 6-month period who presented with acute neurological symptoms suspicious for stroke and underwent NCCT with RAPID ICH postprocessing. RAPID ICH detection was compared with the interpretation of a reference standard comprising a board-certified or board-eligible neuroradiologist, or in cases of discrepancy, adjudicated by a consensus panel of 3 neuroradiologists. Accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of RAPID ICH for ICH detection were determined. Three hundred seven NCCT scans were included in the study. RAPID ICH correctly identified 34 of 37 cases with ICH and 228 of 270 without ICH. RAPID ICH had a sensitivity of 91.9% (78.1%-98.3%), specificity of 84.4% (79.6%-88.6%), NPV of 98.7% (96.3%-99.6%), PPV of 44.7% (37.6%-52.1%), and overall accuracy of 85.3% (80.9%-89.1%). In a real-world scenario, RAPID ICH software demonstrated high NPV but low PPV for the presence of ICH when evaluating possible stroke patients.

Recurrent Ischemic Strokes in the Territory of Recurrent Artery of Heubner Presenting in Relation to Facial Swelling and Weakness

Strokes involving the Recurrent Artery of Huebner are quite rare and are often asymptomatic. Here, we describe a rare case of recurrent infarctions involving the right Recurrent Artery of Heubner, likely due to small vessel disease. Our 32-year-old patient presented to the emergency department with sudden onset right-sided facial weakness, numbness, and difficulty with eye closure. A non-contrast head computed tomography scan and magnetic resonance imaging revealed an incidental subacute infarct in the territory of the right Recurrent Artery of Heubner. He was discharged on valacyclovir and prednisone for suspected Bell’s palsy, as well as aspirin, atorvastatin, metformin, and antihypertensives for secondary stroke prevention. Unfortunately, he was noncompliant with medications and lost to follow-up until he presented again more than one year later with a complaint of isolated right facial swelling and ipsilateral weakness. Imaging revealed an incidental new subacute infarct in the territory of the right Recurrent Artery of Heubner. Close follow-up of the patient and guidelines for appropriate management of secondary risk factors are discussed.

Computed tomography patterns of intracranial infarcts in a Ghanaian tertiary facility.

To determine the Computed Tomography (CT) patterns of intracranial infarcts. A retrospective cross-sectional study. The CT scan unit of the Radiology Department, Cape Coast Teaching Hospital (CCTH), from February 2017 to February 2021. One thousand, one hundred and twenty-five patients with non-contrast head CT scan diagnosis of ischaemic strokes, consecutively selected over the study period without any exclusions. Patterns of non-contrast head CT scan of ischaemic strokes. About 50.6% of the study participants were females with an average age of 62.59±13.91 years. Males were affected with ischaemic strokes earlier than females (p<0.001). The risk factors considered were, hyperlipidaemia (59.5%), hypertension (49.0%), Type 2 diabetes mellitus (DM-2) (39.6%) and smoking (3.0%). The three commonest ischaemic stroke CT scan features were wedge-shaped hypodensity extending to the edge of the brain (62.8%), sulcal flattening/effacement (57.6%) and loss of grey-white matter differentiation (51.0%), which were all significantly associated with hypertension. Small deep brain hypodensities, the rarest feature (2.2%), had no significant association with any of the risk factors considered in the study. Apart from the loss of grey-white matter differentiation, there was no significant association between the other CT scan features and sex. Generally, most of the risk factors and the CT scan features were significantly associated with increasing age. None declared.

Maternal Facial Nerve Palsy and a Perinatal Infection.

Maternal Facial Nerve Palsy and a Perinatal Infection.

Intraoperative blood pressure lability carries a higher risk of headache after carotid endarterectomy

ObjectiveCerebral hyperperfusion syndrome (CHS) is a rare but potentially devastating complication after carotid endarterectomies (CEA). Its symptoms range from new-onset unilateral headache (HA) to intracranial hemorrhage (ICH). Risk factors for CHS in the literature to date have not yet yielded a consensus. This study examines intraoperative and postoperative blood pressure variations as potential risk factors for HA. MethodsA single-center retrospective review at a tertiary care center from January 2010 to November 2019 was performed. Inclusion criteria were all patients undergoing CEA for symptomatic or asymptomatic carotid disease. Patients with incomplete charts were excluded. Primary endpoints were new-onset unilateral HA or postoperative ICH. Data on intraoperative and postoperative mean arterial pressure (MAP), systolic blood pressure (SBP), the mode of endarterectomy, shunt placement, and contralateral carotid status were collected. ResultsThere were 735 patients who met the inclusion criteria: 430 patients underwent modified eversion CEA (59%) and 305 patients for patch angioplasty (42%). The incidence of HA was 19% (n = 142) in our total cohort. Of the 19% with HA, 1.5% (n = 11) demonstrated no relief with analgesics and strict blood pressure control; noncontrast head computed tomography scans were performed subsequently. One patient (0.1%) had an ipsilateral ICH. Univariate analysis demonstrated that greater intraoperative MAP peak had the highest risk for HA (odds ratio [OR], 1.014; 95% confidence interval [CI], 1.007-1.022; P = .0002), followed by intraoperative MAP variability (OR, 1.011; 95% CI,1.005-1.018; P ≤ .0008), and peak intraoperative SBP (OR, 1.01; 95% CI, 1.004-1.015; P = .0011). An unpaired Student t test identified change in intraoperative MAP (P < .005), change in the SBP (P < .005), and peak SBP (P < .001) were significantly associated with HA. Interestingly, there was no significant difference between postoperative MAP variability and HA (P = .1). The mode of endarterectomy showed no statistically significant difference in risk for developing HA (OR, 1.165; 95%; 95% CI, 0.801-1.694; P = .42). ConclusionsGreater intraoperative variability in blood pressures are significantly associated with a higher risk of HA. Adhering to stricter intraoperative blood pressure parameters and limiting blood pressure variability may be beneficial at decreasing the incidence of CHS and its complications.

Admission computed tomography radiomic signatures outperform hematoma volume in predicting baseline clinical severity and functional outcome in the ATACH-2 trial intracerebral hemorrhage population.

Radiomics provides a framework for automated extraction of high-dimensional feature sets from medical images. We aimed to determine radiomics signature correlates of admission clinical severity and medium-term outcome from intracerebral hemorrhage (ICH) lesions on baseline head computed tomography (CT). We used the ATACH-2 (Antihypertensive Treatment of Acute Cerebral Hemorrhage II) trial dataset. Patients included in this analysis (n=895) were randomly allocated to discovery (n=448) and independent validation (n=447) cohorts. We extracted 1130 radiomics features from hematoma lesions on baseline noncontrast head CT scans and generated radiomics signatures associated with admission Glasgow Coma Scale (GCS), admission National Institutes of Health Stroke Scale (NIHSS), and 3-month modified Rankin Scale (mRS) scores. Spearman's correlation between radiomics signatures and corresponding target variables was compared with hematoma volume. In the discovery cohort, radiomics signatures, compared to ICH volume, had a significantly stronger association with admission GCS (0.47 vs. 0.44, p=0.008), admission NIHSS (0.69 vs. 0.57, p<0.001), and 3-month mRS scores (0.44 vs. 0.32, p<0.001). Similarly, in independent validation, radiomics signatures, compared to ICH volume, had a significantly stronger association with admission GCS (0.43 vs. 0.41, p=0.02), NIHSS (0.64 vs. 0.56, p<0.001), and 3-month mRS scores (0.43 vs. 0.33, p<0.001). In multiple regression analysis adjusted for known predictors of ICH outcome, the radiomics signature was an independent predictor of 3-month mRS in both cohorts. Limited by the enrollment criteria of the ATACH-2 trial, we showed that radiomics features quantifying hematoma texture, density, and shape on baseline CT can provide imaging correlates for clinical presentation and 3-month outcome. These findings couldtrigger a paradigm shift where imaging biomarkers may improve current modelsfor prognostication, risk-stratification, and treatment triage of ICH patients.