Chemical exchange saturation transfer MRI to assess cell death in breast cancer xenografts at 7T

Development and Validation of Four Different Methods to Improve MRI-CEST Tumor pH Mapping in Presence of Fat

CEST-MRI is an emerging imaging technique suitable for various in vivo applications, including the quantification of tumor acidosis. Traditionally, CEST contrast is calculated by asymmetry analysis, but the presence of fat signals leads to wrong contrast quantification and hence to inaccurate pH measurements. In this study, we investigated four post-processing approaches to overcome fat signal influences and enable correct CEST contrast calculations and tumor pH measurements using iopamidol. The proposed methods involve replacing the Z-spectrum region affected by fat peaks by (i) using a linear interpolation of the fat frequencies, (ii) applying water pool Lorentzian fitting, (iii) considering only the positive part of the Z-spectrum, or (iv) calculating a correction factor for the ratiometric value. In vitro and in vivo studies demonstrated the possibility of using these approaches to calculate CEST contrast and then to measure tumor pH, even in the presence of moderate to high fat fraction values. However, only the method based on the water pool Lorentzian fitting produced highly accurate results in terms of pH measurement in tumor-bearing mice with low and high fat contents.

Investigation of breast cancer microstructure and microvasculature from time-dependent DWI and CEST in correlation with histological biomarkers

We investigated the associations of time-dependent DWI, non-Gaussian DWI, and CEST parameters with histological biomarkers in a breast cancer xenograft model. 22 xenograft mice (7 MCF-7 and 15 MDA-MB-231) were scanned at 4 diffusion times [T_d = 2.5/5 ms with 11 b-values (0–600 s/mm²) and T_d = 9/27.6 ms with 17 b-values (0–3000 s/mm²), respectively]. The apparent diffusion coefficient (ADC) was estimated using 2 b-values in different combinations (ADC^0–600 using b = 0 and 600 s/mm² and shifted ADC [sADC^200–1500] using b = 200 and 1500 s/mm²) at each of those diffusion times. Then the change (Δ) in ADC/sADC between diffusion times was evaluated. Non-Gaussian diffusion and intravoxel incoherent motion (IVIM) parameters (ADC₀, the virtual ADC at b = 0; K, Kurtosis from non-Gaussian diffusion; f, the IVIM perfusion fraction) were estimated. CEST images were acquired and the amide proton transfer signal intensity (APT SI) were measured. The ΔsADC_9–27.6 (between \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text{sADC}}_{{9\,{\text{ms}}}}^{200{-}1500}$$\end{document}sADC9ms200-1500 and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text{sADC}}_{{27.6\,{\text{ms}}}}^{200{-}1500}$$\end{document}sADC27.6ms200-1500 and ΔADC_2.5_sADC_27.6 (between \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text{ADC}}_{{2.5\, {\text{ms}}}}^{0{-}600}$$\end{document}ADC2.5ms0-600 and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text{sADC}}_{{27.6\,{\text{ms}}}}^{200{-}1500}$$\end{document}sADC27.6ms200-1500) was significantly larger for MCF-7 groups, and ΔADC_2.5_sADC_27.6 was positively correlated with Ki67_max and APT SI. ADC₀ decreased significantly in MDA-MB-231 group and K increased significantly with T_d in MCF-7 group. APT SI and cellular area had a moderately strong positive correlation in MDA-MB-231 and MCF-7 tumors combined, and there was a positive correlation in MDA-MB-231 tumors. There was a significant negative correlation between APT SI and the Ki-67-positive ratio in MDA-MB-231 tumors and when combined with MCF-7 tumors. The associations of ΔADC_2.5_sADC_27.6 and API SI with Ki-67 parameters indicate that the T_d-dependent DW and CEST parameters are useful to predict the histological markers of breast cancers.

A comparative study of the value of amide proton transfer-weighted imaging and diffusion kurtosis imaging in the diagnosis and evaluation of breast cancer

OBJECTIVES

To compare the value of amide proton transfer-weighted imaging (APTWI) and diffusion kurtosis imaging (DKI) in differentiating benign and malignant breast lesions and analyze the correlations between the derived parameters and prognostic factors of breast cancer.

METHODS

One hundred thirty-five women underwent breast APTWI and DKI. The magnetization transfer ratio asymmetry (MTRasym (3.5 ppm)), apparent kurtosis coefficient (K_app), and non-Gaussian diffusion coefficient (D_app) were calculated according to the histological subtype, grade, and prognostic factors (Ki-67, estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor-2 (HER-2), lymph node metastasis, and maximum lesion diameter). The differences, efficacy, and correlation between the parameters were determined.

RESULTS

The K_app value was higher and the D_app and MTRasym (3.5 ppm) values were lower in the malignant group than in the benign group (all p < 0.001; AUC (K_app) = 0.913, AUC (D_app) = 0.910, and AUC (MTRasym (3.5 ppm)) = 0.796). The differences in the AUC between K_app and MTRasym (3.5 ppm) and between D_app and MTRasym (3.5 ppm) were significant (p = 0.023, 0.046). K_app was moderately correlated with the pathological grade (|r| = 0.724) and mildly correlated with Ki-67 and HER-2 expression (|r| = 0.454, 0.333). D_app was moderately correlated with the pathological grade (|r| = 0.648) and mildly correlated with Ki-67 expression (|r| = 0.400). MTRasym (3.5 ppm) was only mildly correlated with the pathological grade (|r| = 0.468).

CONCLUSION

DKI is superior to APTWI in differentiating between benign and malignant breast lesions. Each parameter is correlated with some prognostic factors to a certain extent.

KEY POINTS

• DKI and APTWI provide valuable information regarding lesion characterization. • K_app, D_app, and MTRasym (3.5 ppm) are valid parameters for the characterization of tissue microstructure. • DKI is superior to APTWI in the study of breast cancer.

Accelerating CEST MRI in the mouse brain at 9.4 T by exploiting sparsity in the Z-spectrum domain

PURPOSE

Chemical exchange saturation transfer (CEST) is an MR contrast modality offering an enhanced sensitivity for the detection of dilute metabolites with exchangeable protons. Quantitative analysis requires the acquisition of a number of images (usually between 20 and 50 RF offsets) per Z-spectrum, leading to long acquisition times of the order of 5-40 min in practice. In this work, we explore the possibility of employing sparsity in the Z-spectrum domain (irradiation offset dimension) to provide an accelerated acquisition scheme without compromising the quality of reconstructed CEST spectra.

METHOD AND THEORY

Ex vivo and in vivo data were acquired on an experimental, small animal 9.4 T system. Three different reconstruction methods were tested: k-Z SPARSE, k-Z SLR and k-Z principal component analysis (PCA) using retrospective undersampling with net acceleration factors R = 2, 3, 5. The quality of the reconstructed data was compared with respect to CEST spectra and full magnetization transfer ratio (MTR) asymmetry maps.

RESULTS

In both phantom and in vivo data, CEST spectra and the resulting MTR asymmetry maps were reconstructed without significant deterioration in data quality. For a low acceleration factor (R = 2, 3) all applied methods resulted in similar data quality, while for high acceleration factor (R = 5) only k-Z PCA and k-Z SLR could be used. Loss in spatial resolution was observed in reconstruction with k-Z PCA for all acceleration factors. An example of prospective undersampling with acceleration factor R = 3 and k-Z PCA reconstruction demonstrates improved CEST maps when compared with fully sampled data acquisition with either three times longer scan duration or threefold prolonged acquisition window per frequency offset.

CONCLUSION

The acquisition time of CEST spectra can be significantly accelerated by exploiting the sparsity of the Z-domain. For prospective and retrospective analysis using k-Z PCA, an acceleration factor of up to R = 3 can be used without significant loss in data quality.

Novel nanomedicine with a chemical-exchange saturation transfer effect for breast cancer treatment in vivo

BACKGROUND

Nanomedicine is a promising new approach to cancer treatment that avoids the disadvantages of traditional chemotherapy and improves therapeutic indices. However, the lack of a real-time visualization imaging technology to monitor drug distribution greatly limits its clinical application. Image-tracked drug delivery is of great clinical interest; it is useful for identifying those patients for whom the therapy is more likely to be beneficial. This paper discusses a novel nanomedicine that displays features of nanoparticles and facilitates functional magnetic resonance imaging but is challenging to prepare.

RESULTS

To achieve this goal, we synthesized an acylamino-containing amphiphilic block copolymer (polyethylene glycol-polyacrylamide-polyacetonitrile, PEG-b-P(AM-co-AN)) by reversible addition-fragmentation chain transfer (RAFT) polymerization. The PEG-b-P(AM-co-AN) has chemical exchange saturation transfer (CEST) effects, which enable the use of CEST imaging for monitoring nanocarrier accumulation and providing molecular information of pathological tissues. Based on PEG-b-P(AM-co-AN), a new nanomedicine PEG-PAM-PAN@DOX was constructed by nano-precipitation. The self-assembling nature of PEG-PAM-PAN@DOX made the synthesis effective, straightforward, and biocompatible. In vitro studies demonstrate decreased cytotoxicity of PEG-PAM-PAN@DOX compared to free doxorubicin (half-maximal inhibitory concentration (IC50), mean ~ 0.62 μg/mL vs. ~ 5 μg/mL), and the nanomedicine more efficiently entered the cytoplasm and nucleus of cancer cells to kill them. Further, in vivo animal experiments showed that the nanomedicine developed was not only effective against breast cancer, but also displayed an excellent sensitive CEST effect for monitoring drug accumulation (at about 0.5 ppm) in tumor areas. The CEST signal of post-injection 2 h was significantly higher than that of pre-injection (2.17 ± 0.88% vs. 0. 09 ± 0.75%, p < 0.01).

CONCLUSIONS

The nanomedicine with CEST imaging reflects the characterization of tumors and therapeutic functions has great potential medical applications.