Rationale And Objectives: Ruptured intracranial aneurysms (IAs) are the leading cause for atraumatic subarachnoid hemorrhage. In case of aneurysm rupture, patients may face life-threatening complications and require aneurysm occlusion. Detection of the aneurysm in computed tomography (CT) imaging is therefore essential for patient outcome. This study provides an evaluation of the diagnostic accuracy of Ultra-High-Resolution Computed Tomography Angiography (UHR-CTA) and Normal-Resolution Computed Tomography Angiography (NR-CTA) concerning IA detection and characterization.

Materials And Methods: Consecutive patients with atraumatic subarachnoid hemorrhage who received Digital Subtraction Angiography (DSA) and either UHR-CTA or NR-CTA were retrospectively included. Three readers evaluated CT-Angiography regarding image quality, diagnostic confidence and presence of IAs. Sensitivity and specificity were calculated on patient-level and segment-level with reference standard DSA-imaging. CTA patient radiation exposure (effective dose) was compared.

Results: One hundred and eight patients were identified (mean age = 57.8 ± 14.1 years, 65 women). UHR-CTA revealed significantly higher image quality and diagnostic confidence (P < 0.001) for all readers and significantly lower effective dose (P < 0.001). Readers correctly classified ≥55/56 patients on UHR-CTA and ≥44/52 patients on NR-CTA. We noted significantly higher patient-level sensitivity for UHR-CTA compared to NR-CTA for all three readers (reader 1: 41/41 [100%] vs. 28/34 [82%], reader 2: 41/41 [100%] vs. 30/34 [88%], reader 3: 41/41 [100%] vs. 30/34 [88%], P ≤ 0.04). Segment-level analysis also revealed significantly higher sensitivity for UHR-CTA compared to NR-CTA for all three readers (reader 1: 47/49 [96%] vs. 34/45 [76%], reader 2: 47/49 [96%] vs. 37/45 [82%], reader 3: 48/49 [98%] vs. 37/45 [82%], P ≤ 0.04). Specificity was comparable for both techniques.

Conclusion: We found Ultra-High-Resolution CT-Angiography to provide higher sensitivity than Normal-Resolution CT-Angiography for the detection of intracranial aneurysms in patients with aneurysmal subarachnoid hemorrhage while improving image quality and reducing patient radiation exposure.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.acra.2023.08.035DOI Listing

Publication Analysis

Top Keywords

subarachnoid hemorrhage
12
computed tomography
12
atraumatic subarachnoid
8
tomography angiography
8
image quality
8
quality diagnostic
8
diagnostic confidence
8
comparison ultra-high-resolution
4
ultra-high-resolution normal-resolution
4
normal-resolution ct-angiography
4

Similar Publications

Background: Granulomatosis with polyangiitis (GPA) is an autoimmune multisystem disorder characterized by small vessel vasculitis with granulomatous inflammation. In this report, we describe a unique case of GPA who presented with complete heart block (CHB) and developed complications due to intracranial large vessel involvement.

Case Summary: A 47-year-old gentleman presented with CHB with a background history of arthralgia and blood-tinged nasal discharge.

View Article and Find Full Text PDF

We present a case detailing the diagnostic challenges of a 23-year-old male presenting with a sudden severe headache, nausea, vomiting, and chest heaviness. Initial evaluation showed elevated blood pressure and respiratory rate. An emergency electrocardiogram (ECG) indicated ST-segment elevation myocardial infarction (STEMI), leading to immediate referral for percutaneous coronary intervention, which revealed normal coronary arteries.

View Article and Find Full Text PDF

Deep learning-based multiclass segmentation in aneurysmal subarachnoid hemorrhage.

Front Neurol

December 2024

CLAIM - Charité Lab for AI in Medicine, Charité Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany.

Introduction: Radiological scores used to assess the extent of subarachnoid hemorrhage are limited by intrarater and interrater variability and do not utilize all available information from the imaging. Image segmentation enables precise identification and delineation of objects or regions of interest and offers the potential for automatization of score assessments using precise volumetric information. Our study aims to develop a deep learning model that enables automated multiclass segmentation of structures and pathologies relevant for aneurysmal subarachnoid hemorrhage outcome prediction.

View Article and Find Full Text PDF

Objective: Hyponatremia after aneurysmal subarachnoid hemorrhage (aSAH) is common, however the incidence, and association with vasospasm, morbidity, and mortality, has yet to be defined. We aimed to identify incidence of hyponatremia after aSAH, and quantify its association with measurable outcomes.

Methods: A PRISMA-compliant systematic review and meta-analysis was conducted (PROSPERO ID CRD42022363472).

View Article and Find Full Text PDF

Background: Aneurysmal subarachnoid hemorrhage (aSAH) carries a high economic cost and clinical morbidity in the United States. Beyond prolonged admissions and poor post-injury functional status, there is an additional cost of chronic shunt-dependent hydrocephalus for many aSAH patients. Adjuvant lumbar drain (LD) placement has been hypothesized to promote clearance of subarachnoid blood from the cisternal space, with an ultimate effect of decreasing shunt placement rates.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!