Method and system for calculating quantitative parameter of magnetic resonance imaging

Abstract

The invention discloses a method and a system for calculating a quantitative parameter of magnetic resonance imaging. The method comprises the following steps of: establishing a dynamic comparison enhancement drug dynamics data analysis model and a magnetic resonance imaging model containing the relationship between the signal intensity and the concentration of a contrast mediummagnetic resonanceimaging model; calculating a residual function according to the dynamic comparison enhancement drug dynamics data analysis model and the acquired quantitative parameter according to the acquired residual function. In the method and the system for calculating the quantitative parameter of magnetic resonance imaging, the quantitative parameter can be also improved.

Description

【Technical Field】 [0001] The invention relates to the field of magnetic resonance imaging data processing, in particular to a method and system for calculating quantitative parameters of magnetic resonance imaging. 【Background technique】 [0002] Tumors, plaques and other new blood vessels grow densely and rapidly. Neovascularization plays an important role in the development and metastasis of tumors and the instability of plaques. Vascular endothelial growth factor (VEGF) is the main factor for angiogenesis. It can promote the proliferation of endothelial cells and improve vascular permeability. Microvascular permeability is closely related to angiogenesis, and it is the main indicator for evaluating tumor malignancy, identifying its recurrence, and evaluating plaque stability. Therefore, measuring the quantitative index of microvascular permeability can quantify the formation of new blood vessels, which can be used to evaluate the malignant degree of tumor and the stability of...

AI Technical Summary

Problems solved by technology

However, the most commonly used calculation of K trans The Tofts data analysis model of the value is obtained by deriving the arterial input function (Arterial Input Function, AIF) used for modeling through sampling and derivation of the normal population, which cannot accurately reflect the AIF of each patient itself, which affects the accuracy and reliability of the results , and its nonlinear fitting method based on the pharmacokinetic data analysis model for result processing assumes AIF as a single exponential step response function, resulting in a decrease in the accuracy of residual function estimation

However, the current research on the AIF of the sampling patient itself selects the ROI of the artery manually, which is easily affected by operator bias and partial volume effects, which affects the accuracy of the results.

Therefore, reducing the quantitative index K trans Robust and reproducible for the assessment of tumors, plaques, etc. with neovascularization

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