Preliminary results of intracranial aneurysm treatment with derivo2heal embolization device.

INTRODUCTION: The Derivo 2 Heal Embolization Device (D2HED) is a novel flow diverter (FD) providing a fibrin-/heparin-based surface coating aiming at lower thrombogenicity. We evaluate periprocedural aspects and preliminary aneurysm occlusion efficacy for intracranial aneurysm treatment. METHODS: Thirty-four D2HEDs deployments (34 aneurysms, 32 patients) between 04/2021 and 10/2023 were analyzed. All patients were under dual antiplatelet therapy (dAPT). Periprocedural details, adverse events, and follow-up (FU) imaging were reviewed by consultant-level neuroradiologists. Complication rates and aneurysm occlusion efficacy are compared with performance data of other FDs based on literature research. RESULTS: Each intervention succeeded in the deployment of one D2HED. Significant and/or increased intraaneurysmal contrast stagnation immediately after D2HED deployment was seen in 73.5% of cases according to O'Kelly-Marotta (OKM) grading scale. Clinically relevant early adverse events occurred in three patients: Among them two cases with fusiform aneurysms in the posterior circulation (ischemic events, early in-stent-thrombosis) and one patient (ischemic event) out of the majority of 31 treated internal carotid artery aneurysms (3,2%). Regarding mid-term FU (> 165 days), one aneurysm did not show progressive occlusion presumably caused by a prominent A1 segment arising from the terminal ICA aneurysm itself. Apart from that, mid-term complete / partial occlusion rates of 80% / 20% could be demonstrated. CONCLUSION: Our case series - although suffering from restricted sample size - suggests a potential effectiveness of D2HED in managing intracranial aneurysms. Further studies with larger samples are warranted to quantify long-term occlusion efficacy and the impact of antithrombogenic surface coating on the necessary (d)APT.

Artificial intelligence assistance improves reporting efficiency of thoracic aortic aneurysm CT follow-up.

OBJECTIVE: Follow-up of aortic aneurysms by computed tomography (CT) is crucial to balance the risks of treatment and rupture. Artificial intelligence (AI)-assisted radiology reporting promises time savings and reduced inter-reader variabilities. METHODS: The influence of AI assistance on the efficiency and accuracy of aortic aneurysm reporting according to the AHA / ESC guidelines was quantified based on 324 AI measurements and 1944 radiological measurements: 18 aortic aneurysm patients, each with two CT scans (arterial contrast phase, electrocardiogram-gated) with an interval of at least six months have been included. One board-certified radiologist and two residents (8/4/2 years of experience in vascular imaging) independently assessed aortic diameters at nine landmark positions. Aneurysm extensions were compared with original CT reports. After three weeks washout period, CTs were re-assessed, based on graphically illustrated AI measurements. RESULTS: Time-consuming guideline-compliant aortic measurements revealed additional affections of the root / arch for 80 % of aneurysms that had initially been reported to be limited to the ascending aorta. AI assistance reduced mean reporting time by 63 % from 13:01 to 04:46 min including manual corrections of AI measurements (performed for 33.6 % of all measurements with predominance at the sinuses of Vasalva). AI assistance reduced total diameter inter-reader variability by 42.5 % (0.42 / 1.16 mm with / without AI assistance, mean of all patients and landmark positions, significant reduction for 6 out of 9 measuring positions). Conventional and AI-assisted quantification aneurysm progress varied to small extent (mean of 0.75 mm over all patients / landmark positions) not significantly exceeding radiologist's inter-reader variabilities. CONCLUSIONS: Guideline-compliant aorta measurement is crucial to report detailed aneurysm extension which might affect the strategy of interventional repair. AI assistance promises improved reporting efficiency and has high potential to reduce radiologist's inter-reader variabilities that can hamper diagnostic follow-up accuracy. KEY POINT: The time-consuming guideline-compliant aorta aneurysm assessment is crucial to report aneurysm extension in detail; AI-assisted measurement reduces reporting time, improves extension evaluation and reduces inter-reader variability.

Spatial resolution characterization of a X-ray microCT system.

We report on an experimental characterization of the spatial resolution of a commercial X-ray micro-computed tomography scanner. We have measured the full modulation transfer function (MTF) to assess the spatial resolution. The MTF and those spatial frequencies corresponding to a contrast loss of 50% were determined as a function of different applied X-ray tube parameters and magnification-dependent pixel sizes. A significant influence of the focal spot enlargement on the achievable spatial resolution could be shown. Our results allow for the designation of optimal X-ray tube parameters for a specific application requirement.