ArticleMedical physics2025
Volumetric soft tissue perfusion assessment on a region basis from x-ray angiography images: Motion compensation.
Article in Medical physics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Intra-operative soft tissue perfusion assessment using X-ray angiography images: ischemic stroke study.Medical physics · 2026Article
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Abstract
backgroundAssessing the soft tissue perfusion quantitatively in interventional suites before, during, and after interventional procedures is desired. The method, if possible, has to assess the perfusion volumetrically and quantitatively, be robust against lesion overlaps and patient motion, require no additional radiation dose, be quick (possibly in real-time), and fit to the clinical workflow well. We have developed a method called IPEN (for Intra-operative PErfusion assessment with No gantry rotation) that has potential to accomplish all of the desired goals except for the patient motion. The innovation with IPEN is not to reconstruct volumetric images, but to estimate enhancement of multiple three-dimensional regions-of-interest directly from x-ray projections acquired at one angle. PURPOSE: To further develop the IPEN method such that it can compensate for patient motion when the patient moves quickly during the angiography scan but stays still otherwise.
methodsThe proposed motion-compensating IPEN (MCI) consists of the following three steps: (Step 1) The time segment is broken into multiple segments, that is, a set of rapid motion segments and a set of stationary segments; (Step 2) the MCI estimates ROI enhancement within each stationary segment; and (Step 3) MCI connects segments. The performance of the proposed MCI and the original IPEN were assessed using the digital perfusion phantom, simulating 13 ischemic stroke "patients." The head moved within 0.6 s each time, and seven times during 16-s scans; motion magnitude parameter a (for ± a mm and ± a degrees) was 0.0 (no motion), 0.5, 2.0, 5.0, and 25.0 for each scan. The accuracy of time-enhancement curves (TECs) and calculated perfusion-like parameter ("max-slope" for the maximum of slope of TEC; similar to Patlak plot analysis) was assessed. In addition, the effect of the motion segments on the accuracy of the estimated TEC has been studied systematically.
resultsHead motion induced very severe inconsistency and artifact in synthesized digital subtraction angiography images. The original IPEN had disjoint TECs, and the correlation coefficients (r) against the true values decreased from 0.475 at a = 0.5 to 0.023 at a = 25.0. The proposed MCI provided smooth and accurate TECs with r = 0.995 at a = 0.5 and r = 0.989 at a = 25.0. The 𝓁
conclusionThe proposed MCI can compensate for the patient motion very effectively and accurately when the motion is not continuous and the ROI enhancement does not change non-linearly and significantly during the motion segment.
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