Perfusion Imaging and Single Material Reconstruction in Polychromatic Photon Counting CT

2026-02-02

AI Summary

This work addresses the high radiation dose associated with perfusion CT by proposing VI-PRISM, a novel method that directly reconstructs the dynamic iodine contrast concentration under the assumption of known static background tissue. VI-PRISM introduces, for the first time, a reconstruction framework based on monotone variational inequalities (VI) into perfusion CT, integrating a multi-energy photon-counting model to effectively handle extremely low-dose scenarios (10²–10⁵ photons per detector) and sparse angular sampling (8–984 projection views). Experimental results demonstrate that even at 10–100× lower radiation doses, VI-PRISM consistently achieves iodine concentration reconstruction errors below 0.4 mg/ml, with lower RMSE, reduced noise, and higher SNR compared to conventional filtered back-projection, thereby overcoming the latter’s performance limitations under low-photon conditions.

Technology Category

• Computer Vision: Low Level & Physics-based Vision
• Machine Learning: Multi-instance/Multi-view Learning
• Constraint Satisfaction and Optimization: Other Foundations of Constraint Satisfaction

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Security and Privacy: Data transparency and provenance
• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems

Abstract

Background: Perfusion computed tomography (CT) images the dynamics of a contrast agent through the body over time, and is one of the highest X-ray dose scans in medical imaging. Recently, a theoretically justified reconstruction algorithm based on a monotone variational inequality (VI) was proposed for single material polychromatic photon-counting CT, and showed promising early results at low-dose imaging. Purpose: We adapt this reconstruction algorithm for perfusion CT, to reconstruct the concentration map of the contrast agent while the static background tissue is assumed known; we call our method VI-PRISM (VI-based PeRfusion Imaging and Single Material reconstruction). We evaluate its potential for dose-reduced perfusion CT, using a digital phantom with water and iodine of varying concentration. Methods: Simulated iodine concentrations range from 0.05 to 2.5 mg/ml. The simulated X-ray source emits photons up to 100 keV, with average intensity ranging from $10^5$ down to $10^2$ photons per detector element. The number of tomographic projections was varied from 984 down to 8 to characterize the tradeoff in photon allocation between views and intensity. Results: We compare VI-PRISM against filtered back-projection (FBP), and find that VI-PRISM recovers iodine concentration with error below 0.4 mg/ml at all source intensity levels tested. Even with a dose reduction between 10x and 100x compared to FBP, VI-PRISM exhibits reconstruction quality on par with FBP. Conclusion: Across all photon budgets and angular sampling densities tested, VI-PRISM achieved consistently lower RMSE, reduced noise, and higher SNR compared to filtered back-projection. Even in extremely photon-limited and sparsely sampled regimes, VI-PRISM recovered iodine concentrations with errors below 0.4 mg/ml, showing that VI-PRISM can support accurate and dose-efficient perfusion imaging in photon-counting CT.

Problem

• Perfusion CT
• Photon-counting CT
• Low-dose imaging
• Contrast agent concentration
• Polychromatic reconstruction

Innovation

• photon-counting CT
• perfusion imaging
• variational inequality
• low-dose reconstruction
• single material decomposition