Abstract TP265: Reduced Interpretation Time, Improved Detection of High-Grade Stenosis and Occlusions using Lumina3D: A Multi-Reader, Multi-Case Study

Background: Timely detection of vessel occlusion and high-grade stenosis is crucial in stroke care. While CT angiography (CTA) source images are standard, interpretation can be time-consuming. 3D reconstructions improve anatomical clarity, but manual processing may take over 30 minutes. Lumina 3D TM by RapidAI automates this process, producing 3D head and neck reconstructions and curved planar reformats (CPRs) in minutes. This study evaluated Lumina 3D TM ’s impact on diagnostic accuracy and interpretation time. Methods: Five radiologists (3 general, 2 neuro) reviewed 20 head and neck CTA cases using a randomized crossover design. Cases included large vessel occlusions (8), distal medium vessel occlusions (16), and/or high-grade stenoses (12), defined as >75% luminal narrowing. Reference diagnoses were established by consensus of 3 expert neuroradiologists with full clinical access. Each reader reviewed all 20 cases twice—once with and once without Lumina 3D TM —separated by a one-month washout. The review order was randomized. Readers identified vessels with occlusions or stenoses, simulating clinical conditions. Mixed models assessed accuracy (percent agreement with reference), accounting for reader and scan variability. Results: The 20 cases included 24 occlusions and 11 stenoses across various vessels. With Lumina 3D TM , accuracy was 85.6% (95% CI: 73–98.5%) vs. 76.1% (95% CI: 63–89%) without it—an overall 9% improvement (p = 0.0004). Accuracy gains were independent of pathology type but varied by specialty: general radiologists improved 12%, neuroradiologists 6%. Stenosis detection was 7% more accurate than occlusion detection. Interpretation time decreased by 34 seconds per case (from 4.5 to 3.9 minutes; p = 0.027). General radiologists showed the greatest time savings (>1 minute). Conclusion: Automated 3D reconstructions via Lumina 3D TM improved diagnostic accuracy and reduced interpretation time, particularly for general radiologists. These findings suggest Lumina 3D TM may enhance stroke workflows and support faster, more accurate treatment decisions.

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Journal
Stroke
Published
2026-01-29
DOI
https://doi.org/10.1161/str.57.suppl_1.tp265
Primary Topic
Anatomy and Medical Technology
Type
article
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Abstract TP265: Reduced Interpretation Time, Improved Detection of High-Grade Stenosis and Occlusions using Lumina3D: A Multi-Reader, Multi-Case Study

Dhairya A. Lakhani, Karen Copeland, James L Montuori, Christopher Song et al.
Stroke
Anatomy and Medical Technology
article

Abstract TP265: Reduced Interpretation Time, Improved Detection of High-Grade Stenosis and Occlusions using Lumina3D: A Multi-Reader, Multi-Case Study

Dhairya A. Lakhani, Karen Copeland, James L Montuori, Christopher Song, M. A. Khan, Justin Addicks
article en

Abstract

Background: Timely detection of vessel occlusion and high-grade stenosis is crucial in stroke care. While CT angiography (CTA) source images are standard, interpretation can be time-consuming. 3D reconstructions improve anatomical clarity, but manual processing may take over 30 minutes. Lumina 3D TM by RapidAI automates this process, producing 3D head and neck reconstructions and curved planar reformats (CPRs) in minutes. This study evaluated Lumina 3D TM ’s impact on diagnostic accuracy and interpretation time. Methods: Five radiologists (3 general, 2 neuro) reviewed 20 head and neck CTA cases using a randomized crossover design. Cases included large vessel occlusions (8), distal medium vessel occlusions (16), and/or high-grade stenoses (12), defined as >75% luminal narrowing. Reference diagnoses were established by consensus of 3 expert neuroradiologists with full clinical access. Each reader reviewed all 20 cases twice—once with and once without Lumina 3D TM —separated by a one-month washout. The review order was randomized. Readers identified vessels with occlusions or stenoses, simulating clinical conditions. Mixed models assessed accuracy (percent agreement with reference), accounting for reader and scan variability. Results: The 20 cases included 24 occlusions and 11 stenoses across various vessels. With Lumina 3D TM , accuracy was 85.6% (95% CI: 73–98.5%) vs. 76.1% (95% CI: 63–89%) without it—an overall 9% improvement (p = 0.0004). Accuracy gains were independent of pathology type but varied by specialty: general radiologists improved 12%, neuroradiologists 6%. Stenosis detection was 7% more accurate than occlusion detection. Interpretation time decreased by 34 seconds per case (from 4.5 to 3.9 minutes; p = 0.027). General radiologists showed the greatest time savings (>1 minute). Conclusion: Automated 3D reconstructions via Lumina 3D TM improved diagnostic accuracy and reduced interpretation time, particularly for general radiologists. These findings suggest Lumina 3D TM may enhance stroke workflows and support faster, more accurate treatment decisions.

StrokeVol. 57(Suppl_1)
West Virginia University (US), Hackensack University Medical Center (US), UCHealth Yampa Valley Medical Center (US), Capital Health (US)
Openalex Percentile: Top 74%
Anatomy and Medical Technology
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