Deep learning-reconstructed time-maximum intensity projection versus iterative reconstruction for collateral assessment in acute anterior circulation ischemic stroke.
Authors
Affiliations (4)
Affiliations (4)
- Department of Radiology, The Affiliated Lihuili Hospital of Ningbo University, Ningbo 315041, China.
- Department of Neurosurgery, The Affiliated Lihuili Hospital of Ningbo University, Ningbo 315041, China.
- Shanghai United Imaging Healthcare Co., Ltd., Shanghai 201807, China.
- Department of Radiology, The Affiliated Lihuili Hospital of Ningbo University, Ningbo 315041, China. Electronic address: [email protected].
Abstract
To evaluate the deep learning-reconstructed time-maximum intensity projection (DLR t-MIP) in acute patients with anterior circulation ischemic stroke, and to compare its ability to assess collateral circulation and predict 90-day outcomes with that of single-phase CTA (SP-CTA), multiphase CTA (MP-CTA), and CT perfusion (CTP) volumetrics. This retrospective study analyzed data from 75 AIS patients with unilateral anterior circulation large-vessel occlusion who underwent one-stop CT angiography and CT perfusion (CTA-CTP) scanning. The raw data were reconstructed using iterative reconstruction (IR) algorithms and deep learning algorithms. DLR t-MIPs were generated from dynamic brain scan data; axial MIPs were 24/4 mm. Subjective vessel delineation and noise (5-point scales) and objective attenuation, noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were compared. Collaterals were graded by Menon single-phase (SP-CTA, DLR t-MIP) or multiphase criteria (MP-CTA). Ninety-day mRS defined outcomes (good ≤ 2 vs poor ≥ 3). Prognostic performance was evaluated with a ROC curve and pairwise DeLong tests. Subjective quality scores revealed that the vascular imaging quality was significantly greater in the DLR t-MIP group (p < 0.05), with high interobserver agreement (kappa = 0.716). Objectively, DLR t-MIP demonstrated a significantly lower level of image noise (p < 0.001) and significantly higher vascular CT attenuation values, SNRs, and CNRs (all p < 0.001) than SP-CTA. Collateral scores correlated inversely with the final infarct volume (FIV): DLR t-MIP r = - 0.73 (95 % CI, -0.80 to -0.51), SP-CTA r = - 0.64 (-0.78 to -0.45), and MP-CTA r = - 0.72 (-0.83 to - 0.57); all p < 0.001. The AUCs for 90-day outcomes were as follow: DLR t-MIP 0.84 (95 % CI 0.74-0.92), SP-CTA 0.73 (95 % CI 0.62-0.82), MP-CTA 0.84 (95 % CI 0.71-0.91), ischemic core volume 0.83 (95 % CI 0.73-0.92), and hypoperfusion volume 0.85 (0.75-0.94). DeLong testing showed that DLR t-MIP > SP-CTA (ΔAUC + 0.113; p = 0.012) and ≈ MP-CTA (ΔAUC + 0.002; p = 0.957). DLR t-MIP consolidates temporal information from CTP into a single high-quality angiographic dataset, yielding superior image quality and better prognostic discrimination than SP-CTA, and comparable performance to MP-CTA and CTP volumetrics-without additional acquisition. This approach may streamline acute-stroke triage and collateral-guided decision-making.