Abstract
Background
Quantitative angiography (QA) can extract hemodynamic information during neurointerventional procedures by leveraging contrast flow biomarkers. However, clinical adoption of two-dimensional (2D) QA remains limited compared with three-dimensional (3D) methods such as CT perfusion due to view-dependent biases when projecting 3D flow onto 2D images. Variations in tube potential (kVp) further modulate iodine attenuation, introducing intensity inconsistencies that confound QA measurements. This study evaluates a path-length correction (PLC) method designed to reduce orientation- and acquisition-related biases in 2D digital subtraction angiography (DSA).
Materials and methods
Three cerebrovascular cases containing rotational and 2D DSAs were retrospectively analyzed. 3D volumes were reconstructed using cone-beam algorithms, and synthesized projections were spatially aligned with 2D DSA images using affine and non-linear transformations. Frame intensities were normalized for kVp using an iodine mass attenuation lookup. Path-length maps derived from aligned 3D volumes were then used to normalize DSA intensities, generating PLC images. QA parameters—peak height and area under the curve—were computed from pixel-wise time-density curves (TDCs) at matched regions of interest within aneurysm and parent vessels. PLC performance was evaluated by comparing root mean squared errors (RMSEs) between frontal and lateral TDCs and discrepancies in QA parameters before and after correction.
Results
Across three cases, PLC improved cross-view consistency by reducing TDC RMSE from 0.23 ± 0.04 to 0.14 ± 0.04, peak height RMSE from of 0.42 ± 0.16 to 0.15 ± 0.11, and area under the curve RMSE from 0.43 ± 0.13 to 0.14 ± 0.13.
Conclusions
The PLC method reduces foreshortening bias in 2D DSA and improves consistency of QA metrics, enhancing reliability in cerebrovascular assessment and treatment evaluation using clinical DSA.
Keywords
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