Quantitative Assessment of Hyperdense Sign Measured by Hounsfield Units is Associated with Unsuccessful Mechanical Thrombectomy

Automated Intracranial Clot Detection: A Promising Tool for Vascular Occlusion Detection in Non-Enhanced CT

(1) Background: to test the diagnostic performance of a fully convolutional neural network-based software prototype for clot detection in intracranial arteries using non-enhanced computed tomography (NECT) imaging data. (2) Methods: we retrospectively identified 85 patients with stroke imaging and one intracranial vessel occlusion. An automated clot detection prototype computed clot location, clot length, and clot volume in NECT scans. Clot detection rates were compared to the visual assessment of the hyperdense artery sign by two neuroradiologists. CT angiography (CTA) was used as the ground truth. Additionally, NIHSS, ASPECTS, type of therapy, and TOAST were registered to assess the relationship between clinical parameters, image results, and chosen therapy. (3) Results: the overall detection rate of the software was 66%, while the human readers had lower rates of 46% and 24%, respectively. Clot detection rates of the automated software were best in the proximal middle cerebral artery (MCA) and the intracranial carotid artery (ICA) with 88-92% followed by the more distal MCA and basilar artery with 67-69%. There was a high correlation between greater clot length and interventional thrombectomy and between smaller clot length and rather conservative treatment. (4) Conclusions: the automated clot detection prototype has the potential to detect intracranial arterial thromboembolism in NECT images, particularly in the ICA and MCA. Thus, it could support radiologists in emergency settings to speed up the diagnosis of acute ischemic stroke, especially in settings where CTA is not available.

Functional and technical outcomes in acute ischemic stroke patients with hyperdense middle cerebral artery sign treated with endovascular thrombectomy

Background and objective

The hyperdense middle cerebral artery sign (HMCAS) is observed in a proportion of patients with acute ischemic stroke (AIS). This sign reflects the presence of an intravascular thrombus rich in red blood cells. Several studies have demonstrated that HMCAS increases the risk of poor outcomes in AIS patients treated with IV thrombolysis or no reperfusion therapy; however, whether HMCAS predicts a poor outcome in patients treated with endovascular thrombectomy (EVT) is less clear. We aimed to evaluate the functional outcome by the modified Rankin scale (mRS) at 90 days and technical challenges in patients with HMCAS undergoing EVT.

Methods

We studied 143 consecutive AIS patients with middle cerebral artery M1 segment or internal carotid artery + M1 occlusions who underwent EVT.

Results

There were 73 patients (51%) with HMCAS. Patients with HMCAS had a higher frequency of cardioembolic stroke (p = 0.038); otherwise, no other baseline difference was observed. No differences in functional outcomes (mRS) at 90  days (p = 0.698), unfavorable outcomes (mRS > 2) (p = 0.929), frequency of symptomatic intracranial hemorrhage (p = 0.924), and mortality (mRS-6) (p = 0.736) were observed between patients with and without HMCAS. In patients with HMCAS, EVT procedures were 9  min longer, requiring a higher number of passes (p = 0.073); however, optimal recanalization scores (modified thrombolysis in cerebral infarction: 2b-3) were equally achieved by both groups.

Conclusion

Patients with HMCAS treated with EVT do not have a worse outcome at 3  months compared with no-HMCAS patients. Patients with HMCAS required a greater number of thrombus passes and longer procedure times.

Hyperdense Artery Sign in Patients With Acute Ischemic Stroke-Automated Detection With Artificial Intelligence-Driven Software

Background

Hyperdense artery sign (HAS) on non-contrast CT (NCCT) can indicate a large vessel occlusion (LVO) in patients with acute ischemic stroke. HAS detection belongs to routine reporting in patients with acute stroke and can help to identify patients in whom LVO is not initially suspected. We sought to evaluate automated HAS detection by commercial software and compared its performance to that of trained physicians against a reference standard.

Methods

Non-contrast CT scans from 154 patients with and without LVO proven by CT angiography (CTA) were independently rated for HAS by two blinded neuroradiologists and an AI-driven algorithm (Brainomix®). Sensitivity and specificity were analyzed for the clinicians and the software. As a secondary analysis, the clot length was automatically calculated by the software and compared with the length manually outlined on CTA images as the reference standard.

Results

Among 154 patients, 84 (54.5%) had CTA-proven LVO. HAS on the correct side was detected with a sensitivity and specificity of 0.77 (CI:0.66–0.85) and 0.87 (0.77–0.94), 0.8 (0.69–0.88) and 0.97 (0.89–0.99), and 0.93 (0.84–0.97) and 0.71 (0.59–0.81) by the software and readers 1 and 2, respectively. The automated estimation of the thrombus length was in moderate agreement with the CTA-based reference standard [intraclass correlation coefficient (ICC) 0.73].

Conclusion

Automated detection of HAS and estimation of thrombus length on NCCT by the tested software is feasible with a sensitivity and specificity comparable to that of trained neuroradiologists.