Estimation of the Number of Compartments Associated With the Apparent Diffusion Coefficient in MRI: The Theoretical and Experimental Investigations

Improving signal-to-noise ratio by maximal convolution of longitudinal and transverse magnetization components in MRI: application to the breast cancer detection

PURPOSE

The extraction of information from images provided by medical imaging systems may be employed to obtain the specific objectives in the various fields. The quantity of signal to noise ratio (SNR) plays a crucial role in displaying the image details. The higher the SNR value, the more the information is available.

METHODS

In this study, a new function has been formulated using the appropriate suggestions on convolutional combination of the longitudinal and transverse magnetization components related to the relaxation times of T1 and T2 in MRI, where by introducing the distinct index on the maximum value of this function, the new maps are constructed toward the best SNR. Proposed functions were analytically simulated using Matlab software and evaluated with respect to various relaxation times. This proposed method can be applied to any medical images. For instance, the T1- and T2-weighted images of the breast indicated in the reference [35] were selected for modelling and construction of the full width at x maximum (FWxM) map at the different values of x-parameter from 0.01 to 0.955 at 0.035 and 0.015 intervals. The range of x-parameter is between zero and one. To determine the maximum value of the derived SNR, these intervals have been first chosen arbitrarily. However, the smaller this interval, the more precise the value of the x-parameter at which the signal to noise is maximum.

RESULTS

The results showed that at an index value of x = 0.325, the new map of FWxM (0.325) will be constructed with a maximum derived SNR of 22.7 compared to the SNR values of T1- and T2-maps by 14.53 and 17.47, respectively.

CONCLUSION

By convolving two orthogonal magnetization vectors, the qualified images with higher new SNR were created, which included the image with the best SNR. In other words, to optimize the adoption of MRI technique and enable the possibility of wider use, an optimal and cost-effective examination has been suggested. Our proposal aims to shorten the MRI examination to further reduce interpretation times while maintaining primary sensitivity.

SIGNIFICANCE

Our findings may help to quantitatively identify the primary sources of each type of solid and sequential cancer.

Sequential PET/diffusion-weighted imaging in the evaluation of myocardial perfusion and viability in coronary artery disease: a preliminary study

OBJECTIVES

To evaluate the utility of sequential F-18 fluorodeoxyglucose PET/diffusion-weighted imaging in assessing myocardial perfusion and viability in coronary artery disease.

METHODS

Fourteen coronary artery disease patients and five non-coronary artery disease subjects underwent sequential cardiac F-18 fluorodeoxyglucose PET/diffusion-weighted imaging using a trimodality PET/computed tomography-MRI system. The perfusion data were acquired by measuring low b-values apparent diffusion coefficient using diffusion-weighted imaging. Regional myocardial viability was determined by perfusion/metabolism patterns. The perfusion/metabolism patterns obtained by low b-values apparent diffusion coefficient/fluorodeoxyglucose uptake were analyzed and compared with the results from the combination of rest methoxyisobutylisonitrile (Tc-MIBI) myocardial perfusion single-photon emission computed tomography with F-18 fluorodeoxyglucose PET/computed tomography.

RESULTS

Ten coronary artery disease patients and five non-coronary artery disease subjects were included in the final analysis. Low b-values apparent diffusion coefficient defects involved with 25 myocardial regions were demonstrated in nine coronary artery disease patients, while Tc-MIBI defects involved with 21 myocardial regions were shown in the same patients. The agreement between low b-values apparent diffusion coefficient and MIBI uptake was good in coronary artery disease patients (κ = 0.627, P < 0.001) and was better still in the whole subjects (κ = 0.733, P < 0.001). Low b-values apparent diffusion coefficient/fluorodeoxyglucose uptake demonstrated mismatch patterns in six coronary artery disease patients and MIBI/fluorodeoxyglucose uptake revealed mismatch patterns in seven coronary artery disease patients. Agreement in the evaluation of regional myocardial viability between low b-values apparent diffusion coefficient/fluorodeoxyglucose uptake and MIBI/fluorodeoxyglucose uptake was high in coronary artery disease patients (κ = 0.627, P < 0.001) and all subjects (κ = 0.728, P < 0.001).

CONCLUSIONS

Low b-values apparent diffusion coefficient/fluorodeoxyglucose uptake is comparable to MIBI/fluorodeoxyglucose uptake in assessing perfusion/metabolism patterns, indicating that microperfusion might dominate the diffusion signal at low b-values and sequential PET/diffusion-weighted imaging might be useful to evaluate myocardial viability in coronary artery disease patients.

A robust deconvolution method to disentangle multiple water pools in diffusion MRI

The diffusion-weighted magnetic resonance imaging (dMRI) signal measured in vivo arises from multiple diffusion domains, including hindered and restricted water pools, free water and blood pseudo-diffusion. Not accounting for the correct number of components can bias metrics obtained from model fitting because of partial volume effects that are present in, for instance, diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI). Approaches that aim to overcome this shortcoming generally make assumptions about the number of considered components, which are not likely to hold for all voxels. The spectral analysis of the dMRI signal has been proposed to relax assumptions on the number of components. However, it currently requires a clinically challenging signal-to-noise ratio (SNR) and accounts only for two diffusion processes defined by hard thresholds. In this work, we developed a method to automatically identify the number of components in the spectral analysis, and enforced its robustness to noise, including outlier rejection and a data-driven regularization term. Furthermore, we showed how this method can be used to take into account partial volume effects in DTI and DKI fitting. The proof of concept and performance of the method were evaluated through numerical simulations and in vivo MRI data acquired at 3 T. With simulations our method reliably decomposed three diffusion components from SNR = 30. Biases in metrics derived from DTI and DKI were considerably reduced when components beyond hindered diffusion were taken into account. With the in vivo data our method determined three macro-compartments, which were consistent with hindered diffusion, free water and pseudo-diffusion. Taking free water and pseudo-diffusion into account in DKI resulted in lower mean diffusivity and higher fractional anisotropy values in both gray and white matter. In conclusion, the proposed method allows one to determine co-existing diffusion compartments without prior assumptions on their number, and to account for undesired signal contaminations within clinically achievable SNR levels.

Estimation of microvascular capillary physical parameters using MRI assuming a pseudo liquid drop as model of fluid exchange on the cellular level

Aim

One of the most important microvasculatures' geometrical variables is number of pores per capillary length that can be evaluated using MRI. The transportation of blood from inner to outer parts of the capillary is studied by the pores and the relationship among capillary wall thickness, size and the number of pores is examined.

Background

Characterization of capillary space may obtain much valuable information on the performance of tissues as well as the angiogenesis.

Methods

To estimate the number of pores, a new pseudo-liquid drop model along with appropriate quantitative physiological purposes has been investigated toward indicating a package of data on the capillary space. This model has utilized the MRI perfusion, diffusion and relaxivity parameters such as cerebral blood volume (CBV), apparent diffusion coefficient (ADC), ΔR ₂ and Δ R 2 * values. To verify the model, a special protocol was designed and tested on various regions of eight male Wistar rats.

Results

The maximum number of pores per capillary length in the various conditions such as recovery, core, normal-recovery, and normal-core were found to be 183 ± 146, 176 ± 160, 275 ± 166, and 283 ± 143, respectively. This ratio in the normal regions was more than that of the damaged ones. The number of pores increased with increasing mean radius of the capillary and decreasing the thickness of the wall in the capillary space.

Conclusion

Determination of the number of capillary pore may most likely help to evaluate angiogenesis in the tissues and treatment planning of abnormal ones.