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Updated: Jan 20, 2026

In Vivo Quantitative Assessment of Myocardial Structure, Function, Perfusion and Viability Using Cardiac Micro-computed Tomography
Published on: February 16, 2016
Impact of Knowledge-Based Iterative Model Reconstruction on Image Quality and Hemodynamic Parameters in Dynamic
Yuki Tanabe1, Teruhito Kido1, Akira Kurata1
1From the Departments of Radiology.
Objective:
Knowledge-based iterative model reconstruction (IMR) yields diagnostically acceptable image quality in low-dose static computed tomography (CT). We aimed to evaluate the feasibility of IMR in dynamic myocardial computed tomography perfusion (CTP).
Methods:
We enrolled 24 patients who underwent stress dynamic CTP using a 256-slice CT. Images were reconstructed using filtered back projection (FBP), hybrid IR, and IMR. Image quality and hemodynamic parameters were compared among three algorithms.
Results:
Qualitative image quality and contrast-to-noise ratio were significantly higher by IMR than by FBP or hybrid IR (visual score: 4.1 vs. 3.0 and 3.5; contrast-to-noise ratio: 12.4 vs. 6.6 and 8.4; P < 0.05). No significant difference was observed among algorithms in CTP-derived myocardial blood flow (1.68 vs. 1.73 and 1.70 mL/g/min).
Conclusions:
The use of knowledge-based iterative model reconstruction improves image quality without altering hemodynamic parameters in low-dose dynamic CTP, compared with FBP or hybrid IR.
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