Multiparametric MRI Analysis for the Identification of High Intensity Focused Ultrasound-Treated Tumor Tissue

<div><p>Purpose</p><p>In this study endogenous magnetic resonance imaging (MRI) biomarkers for accurate segmentation of High Intensity Focused Ultrasound (HIFU)-treated tumor tissue and residual or recurring non-treated tumor tissue were identified.</p><p>Methods</p><p>Multiparametric MRI, consisting of quantitative T₁, T₂, Apparent Diffusion Coefficient (ADC) and Magnetization Transfer Ratio (MTR) mapping, was performed in tumor-bearing mice before (n = 14), 1 h after (n = 14) and 72 h (n = 7) after HIFU treatment. A non-treated control group was included (n = 7). Cluster analysis using the Iterative Self Organizing Data Analysis (ISODATA) technique was performed on subsets of MRI parameters (feature vectors). The clusters resulting from the ISODATA segmentation were divided into a viable and non-viable class based on the fraction of pixels assigned to the clusters at the different experimental time points. ISODATA-derived non-viable tumor fractions were quantitatively compared to histology-derived non-viable tumor volume fractions.</p><p>Results</p><p>The highest agreement between the ISODATA-derived and histology-derived non-viable tumor fractions was observed for feature vector {T₁, T₂, ADC}. R₁ (1/T₁), R₂ (1/T₂), ADC and MTR each were significantly increased in the ISODATA-defined non-viable tumor tissue at 1 h after HIFU treatment compared to viable, non-treated tumor tissue. R₁, ADC and MTR were also significantly increased at 72 h after HIFU.</p><p>Conclusions</p><p>This study demonstrates that non-viable, HIFU-treated tumor tissue can be distinguished from viable, non-treated tumor tissue using multiparametric MRI analysis. Clinical application of the presented methodology may allow for automated, accurate and objective evaluation of HIFU treatment.</p></div

Correlation between histology-derived and ISODATA-derived non-viable tumor fractions.

<p>Correlation plots of ISODATA-derived non-viable tumor fractions following segmentation with feature vectors {ADC}, {T₂, ADC} and {T₁, T₂, ADC} as a function of the histology-derived non-viable tumor fractions for two different groups of animals: ‘1 h after HIFU + Control’ (<b>A</b>) and ‘72 h after HIFU + Control’ (<b>B</b>). The symbols ○, □ and ▴indicate groups ‘1 h after HIFU’, ‘72 h after HIFU’ and ‘Control’, respectively. Correlation values between the ISODATA-derived and the histology-derived tumor fractions are listed in the top left corner of each plot.</p

Mean MRI parameter values in ISODATA-defined viable and non-viable tumor tissue.

<p>MRI parameter values (mean±SD) in viable tumor tissue (tumor tissue assigned as viable tumor tissue at all time points (n = 14)), non-viable tumor tissue at 1 h after HIFU (n = 14) and non-viable tumor tissue at 72 h after HIFU (n = 7) of the HIFU-treated animals following ISODATA segmentation with feature vector {T₁, T₂, ADC}. * and ** denote a significant difference between viable and non-viable tumor tissue with p<0.05 and p<0.001, respectively (paired Student's t-test).</p

Spin-lock MR enhances the detection sensitivity of superparamagnetic iron oxide particles

To evaluate spin-lock MR for detecting superparamagnetic iron oxides and compare the detection sensitivity of quantitative T1ρ with T2 imaging. In vitro experiments were performed to investigate the influence of iron oxide particle size and composition on T1ρ . These comprise T1ρ and T2 measurements (B0 = 1.41T) of agar (2%) with concentration ranges of three different iron oxide nanoparticles (IONs) (Sinerem, Resovist, and ION-Micelle) and microparticles of iron oxide (MPIO). T1ρ dispersion was measured for a range of spin-lock amplitudes (γB1 = 6.5-91 kHz). Under relevant in vivo conditions (B0 = 9.4T; γB1 = 100-1500 Hz), T1ρ and T2 mapping of the liver was performed in seven mice pre- and 24 h postinjection of Sinerem. Addition of iron oxide nanoparticles decreased T1ρ as well as the native T1ρ dispersion of agar, leading to increased contrast at high spin-lock amplitudes. Changes of T1ρ were highly linear with iron concentration and much larger than T2 changes. MPIO did not show this effect. In vivo, a decrease of T1ρ was observed with no clear influence on T1ρ dispersion. By suppression of T1ρ dispersion, iron oxide nanoparticles cause enhanced T1ρ contrast compared to T2 . The underlying mechanism appears to be loss of lock. Spin-lock MR is therefore a promising technique for sensitive detection of iron oxide contrast agent

Investigating the Cellular Specificity in Tumors of a Surface-Converting Nanoparticle by Multimodal Imaging

Active targeting of nanoparticles through surface functionalization is a common strategy to enhance tumor delivery specificity. However, active targeting strategies tend to work against long polyethylene glycol's shielding effectiveness and associated favorable pharmacokinetics. To overcome these limitations, we developed a matrix metalloproteinase-2 sensitive surface-converting polyethylene glycol coating. This coating prevents nanoparticle-cell interaction in the bloodstream, but, once exposed to matrix metalloproteinase-2, i.e., when the nanoparticles accumulate within the tumor interstitium, the converting polyethylene glycol coating is cleaved, and targeting ligands become available for binding to tumor cells. In this study, we applied a comprehensive multimodal imaging strategy involving optical, nuclear, and magnetic resonance imaging methods to evaluate this coating approach in a breast tumor mouse model. The data obtained revealed that this surface-converting coating enhances the nanoparticle's blood half-life and tumor accumulation and ultimately results in improved tumor-cell targeting. Our results show that this enzyme-specific surface-converting coating ensures a high cell-targeting specificity without compromising favorable nanoparticle pharmacokinetic