The Key Technology Of DCE-MRI Quantitative Analysis And Its Application In The Detection Of Prostate Cancer

Dynamic Contrast-enhanced Magnetic Resonance(DCE-MRI)imaging technology is widely used in the non-invasive detection,characterization and treatment monitoring of many diseases.Although DCE-MRI has important clinical applications,it still has some problems and limitations.In particular,quantitative analysis of DCE-MRI can not fully detecte all cancer tissue in practical applications such as prostate cancer and breast cancer.Therefore,it is of great theoretical significance and clinical application value to study the key issues of quantitative analysis of DCE-MRI and improve the accuracy of detection of lesions.Because of the long acquisition time of DCE-MRI and the influence of human motion such as colonic motility,the signal-to-noise ratio is usually not high.In the actual application of DCE-MRI,it is usually required to make a trade-off between time resolution,spatial resolution,and signal-to-noise ratio.If the effect of low signal-to-noise ratio can be overcome,better time and spatial resolution may be obtained.On the other hand,the DCE-MRI data acquisition protocal and analysis methods used by various research and clinical institutions are not uniform,which makes it difficult to compare the results of some studies with each other,and the reliability and repeatability of the results cannot be guaranteed.To some extent,it limits the development of DCE-MRI research.In this paper,mathematical simulations,animal experiments,and analysis of the clinical test results of prostate cancer patients were used to analyze the accuracy of DCE-MRI contrast agent concentration curves and arterial input function(AIF)using different mathematical models,as well as the effect of noise and tumor inhomogeneity on the analysis results.This article also studied ultrafast DCE-MRI analysis methods and its detection of prostate cancer,as well as the feasibility and effectiveness of low-dose contrast agent DCE-MRI for the detection of prostate cancer.Both high temporal resolution and low dose of contrast agent will reduce the signal quality of DCE-MRI.This article uses a pure mathematical model to overcome this effect,achieved better analysis results and provided more information than traditional DCE-MRI.The work of this article mainly includes the following aspects:The numerical simulations and experiments were used to evaluate and compare eight different pure mathematical models for fit the contrast agent concentration curves as function of time,and the effects of noise on each model were analyzed.The numerical simulation results show that the EMM model has the best fitting effect among the eight models,whether under the condition of without noise or with noise(SNR=10dB,5dB and 1dB).The EMM model also showed the best analysis for animal experiments,which showed that the value of signal amplitude A was 0.23 ± 0.10 and 0.087 ± 0.040 for tumor and normal muscle tissue,respectively,with statistically significant differences.The numerical simulations were used to evaluate which of nine mathematical AIF models with four to seven parameters were most similar to the Parker model,which was considered a gold standard.Our results demonstrated that the Lin+BiExp AIF model was almost equivalent to the Parker AIF,and corresponding generated and extracted Ktrans and ve were in excellent agreements.The effects of the second pass of contrast agent circulation were small on extracted physiological parameters using the Tofts model.Computer simulations and DCE-MRI data from transplanted rodent prostate cancers were used to evaluate the differences in extracted physiological parameters from ’ROI-averaged’analysis versus ’pixel-averaged’ analysis,with use of the Tofts model for analysis of heterogeneous ROIs.The effects of noise on the Ktrans and ve values of pharmacokinetic parameters were also demonstrated theoretically.The study shows:to increase the sensitivity and specificity of cancer diagnosis using DCE-MRI,’pixel-averaged’ analysis may be preferable for extraction of accurate physiological parameters from heterogeneous tumors.The ’ROI-averaged’ analysis should only be used when there is low SNR for DCE-MRI data.The high temporal resolution DCE-MRI finding for different zones of prostate and ts performance in the diagnosis of prostate cancer were evaluated.The results show that using the EMM model quantitative parameters obtained from the fitting ultrafast(2 seconds)DCE-MRI can improve the diagnostic efficacy of prostate cancer.Subtle differences in contrast kinetics,specifically increased signal enhancement rate or uptake rate(a),initial enhancement slope seen in cancer compared to surrounding normal tissue are helpful in detection of prostate cancer.Combining DCE with ADC and T2 can further improve the diagnostic accuracy of PCa detection.The study investigated whether administration of low doses of Gd for dynamic contrast enhanced(DCE)MRI can be as effective as a standard dose in distinguishing prostate cancer(PCa)from benign tissue.The results show:The parameter obtained from EMM model,signal enhancement rate,can provide effective information for the diagnosis of Pca.Quantitative DCE-MRI with a low Gd dose distinguishes PCa from benign prostate tissue more effectively than the standard Gd dose.