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 pharmacokinetics.

MRI methods for the evaluation of high intensity focused ultrasound tumor treatment: Current status and future needs.

Thermal ablation with high intensity focused ultrasound (HIFU) is an emerging noninvasive technique for the treatment of solid tumors. HIFU treatment of malignant tumors requires accurate treatment planning, monitoring and evaluation, which can be facilitated by performing the procedure in an MR-guided HIFU system. The MR-based evaluation of HIFU treatment is most often restricted to contrast-enhanced T1 -weighted imaging, while it has been shown that the non-perfused volume may not reflect the extent of nonviable tumor tissue after HIFU treatment. There are multiple studies in which more advanced MRI methods were assessed for their suitability for the evaluation of HIFU treatment. While several of these methods seem promising regarding their sensitivity to HIFU-induced tissue changes, there is still ample room for improvement of MRI protocols for HIFU treatment evaluation. In this review article, we describe the major acute and delayed effects of HIFU treatment. For each effect, the MRI methods that have been-or could be-used to detect the associated tissue changes are described. In addition, the potential value of multiparametric MRI for the evaluation of HIFU treatment is discussed. The review ends with a discussion on future directions for the MRI-based evaluation of HIFU treatment.

T1 ρ mapping for the evaluation of high intensity focused ultrasound tumor treatment.

PURPOSE: This study was aimed to assess the effects of High Intensity Focused Ultrasound (HIFU) thermal ablation on tumor T1ρ . METHODS: In vivo T1ρ measurements of murine tumors at various spin-lock amplitudes (B1 = 0-2000 Hz) were performed before (n = 13), directly after (n = 13) and 3 days (n = 7) after HIFU treatment. T2 maps were obtained from the measurements at B1 = 0 Hz. RESULTS: Average tumor T1ρ distributions at the different experimental time points showed a shift toward lower T1ρ values after HIFU for all spin-lock amplitudes, which became larger with increasing spin-lock amplitude at 3 days after treatment. Statistical analysis confirmed a significant effect of spin-lock amplitude on the average change in T1ρ (ΔT1ρ ) as compared to baseline at 3 days after HIFU. At 3 days after treatment, ΔT1ρ values at B1 above 100 Hz were significantly lower (more negative) than at B1 = 0 Hz (T2 ). CONCLUSION: Significant changes in tumor T1ρ were observed after HIFU treatment. These T1ρ changes were distinctly more pronounced than HIFU-induced changes in T2 . The results indicate that T1ρ imaging is sensitive to HIFU-induced tissue changes and may thus be a suitable MR method for the evaluation of HIFU treatment. Magn Reson Med 73:1593-1601, 2015. © 2014 Wiley Periodicals, Inc.

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

PURPOSE: To evaluate spin-lock MR for detecting superparamagnetic iron oxides and compare the detection sensitivity of quantitative T1ρ with T2 imaging. METHODS: 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. RESULTS: 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. CONCLUSION: 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 agents.

Cluster analysis of DCE-MRI data identifies regional tracer-kinetic changes after tumor treatment with high intensity focused ultrasound.

Evaluation of high intensity focused ultrasound (HIFU) treatment with MRI is generally based on assessment of the non-perfused volume from contrast-enhanced T1-weighted images. However, the vascular status of tissue surrounding the non-perfused volume has not been extensively investigated with MRI. In this study, cluster analysis of the transfer constant K(trans) and extravascular extracellular volume fraction ve , derived from dynamic contrast-enhanced MRI (DCE-MRI) data, was performed in tumor tissue surrounding the non-perfused volume to identify tumor subregions with distinct contrast agent uptake kinetics. DCE-MRI was performed in CT26.WT colon carcinoma-bearing BALB/c mice before (n = 12), directly after (n = 12) and 3 days after (n = 6) partial tumor treatment with HIFU. In addition, a non-treated control group (n = 6) was included. The non-perfused volume was identified based on the level of contrast enhancement. Quantitative comparison between non-perfused tumor fractions and non-viable tumor fractions derived from NADH-diaphorase histology showed a stronger agreement between these fractions 3 days after treatment (R(2) to line of identity = 0.91) compared with directly after treatment (R(2) = 0.74). Next, k-means clustering with four clusters was applied to K(trans) and ve parameter values of all significantly enhanced pixels. The fraction of pixels within two clusters, characterized by a low K(trans) and either a low or high ve , significantly increased after HIFU. Changes in composition of these clusters were considered to be HIFU induced. Qualitative H&E histology showed that HIFU-induced alterations in these clusters may be associated with hemorrhage and structural tissue disruption. Combined microvasculature and hypoxia staining suggested that these tissue changes may affect blood vessel functionality and thereby tumor oxygenation. In conclusion, it was demonstrated that, in addition to assessment of the non-perfused tumor volume, the presented methodology gives further insight into HIFU-induced effects on tumor vascular status. This method may aid in assessment of the consequences of vascular alterations for the fate of the tissue.

Multiparametric MRI analysis for the evaluation of MR-guided high intensity focused ultrasound tumor treatment.

For the clinical application of high intensity focused ultrasound (HIFU) for thermal ablation of malignant tumors, accurate treatment evaluation is of key importance. In this study, we have employed a multiparametric MRI protocol, consisting of quantitative T1, T2, ADC, amide proton transfer (APT), T1ρ and DCE-MRI measurements, to evaluate MR-guided HIFU treatment of subcutaneous tumors in rats. K-means clustering using all different combinations of the endogenous contrast MRI parameters (feature vectors) was performed to segment the multiparametric data into tissue populations with similar MR parameter values. The optimal feature vector for identification of the extent of non-viable tumor tissue after HIFU treatment was determined by quantitative comparison between clustering-derived and histology-derived non-viable tumor fractions. The highest one-to-one correspondence between these clustering-based and histology-based non-viable tumor fractions was observed for the feature vector {ADC, APT-weighted signal} (R(2) to line of identity (R(2)y=x) = 0.92) and the strongest agreement was seen 3 days after HIFU (R(2)y=x = 0.97). To compare the multiparametric MRI analysis results with conventional HIFU monitoring and evaluation methods, the histology-derived non-viable tumor fractions were also quantitatively compared with non-perfused tumor fractions (derived from the level of contrast enhancement in the DCE-MRI measurements) and 240 CEM tumor fractions (i.e. thermal dose > 240 cumulative equivalent minutes at 43 °C). The correlation between histology-derived non-viable tumor fractions directly after HIFU and the 240 CEM fractions was high, but not significant. The non-perfused fractions overestimated the extent of non-viable tumor tissue directly after HIFU, whereas an underestimation was observed 3 days after HIFU. In conclusion, we have shown that a multiparametric MR analysis, especially based on the ADC and the APT-weighted signal, can potentially be used to determine the extent of non-viable tumor tissue 3 days after HIFU treatment. We expect that this method can be incorporated in the current clinical workflow of MR-HIFU ablation therapies.

Automatic segmentation of subcutaneous mouse tumors by multiparametric MR analysis based on endogenous contrast.

OBJECT: Contrast-enhanced T1-weighted imaging is usually included in MRI procedures for automatic tumor segmentation. Use of an MR contrast agent may not be appropriate for some applications, however. We assessed the feasability of automatic tumor segmentation by multiparametric cluster analysis that uses intrinsic MRI contrast only. MATERIALS AND METHODS: Multiparametric MRI consisting of quantitative T1, T2, and apparent diffusion coefficient (ADC) mapping was performed in mice bearing subcutaneous tumors (n = 21). k-means and fuzzy c-means clustering with all possible combinations of MRI parameters, i.e. feature vectors, and 2-7 clusters were performed on the multiparametric data. Clusters associated with tumor tissue were selected on the basis of the relative signal intensity of tumor tissue in T2-weighted images. The optimum segmentation method was determined by quantitative comparison of automatic segmentation with manual segmentation performed by three observers. In addition, the automatically segmented tumor volumes from seven separate tumor data sets were quantitatively compared with histology-derived tumor volumes. RESULTS: The highest similarity index between manual and automatic segmentation (SI manual,automatic = 0.82 ± 0.06) was observed for k-means clustering with feature vector {T2, ADC} and four clusters. A strong linear correlation between automatically and manually segmented tumor volumes (R (2) = 0.99) was observed for this segmentation method. Automatically segmented tumor volumes also correlated strongly with histology-derived tumor volumes (R (2) = 0.96). CONCLUSION: Automatic segmentation of mouse subcutaneous tumors can be achieved on the basis of endogenous MR contrast only.

Amide proton transfer imaging of high intensity focused ultrasound-treated tumor tissue.

PURPOSE: In this study, the suitability of amide proton transfer (APT) imaging as a biomarker for the characterization of high intensity focused ultrasound (HIFU)-treated tumor tissue was assessed. METHODS: APT imaging was performed on tumor-bearing mice before (n = 15), directly after (n = 15) and at 3 days (n = 8) after HIFU treatment. A control group (n = 7) of nontreated animals was scanned at the same time points. Histogram analysis of the tumor APT-weighted signal distributions was performed to assess HIFU-induced changes in the tumor APT contrast. RESULTS: Distinct regions of decreased APT-weighted signal were observed at both time points after HIFU treatment. Analysis of the tumor APT-weighted signal distribution showed a pronounced shift toward lower APT-weighted signal values after HIFU treatment. A significantly increased fraction of pixels with an APT-weighted signal value between -10 and -2% was observed both directly (0.37 ± 0.16) and at 3 days (0.49 ± 0.16) after HIFU treatment as compared to baseline (0.22 ± 0.16). CONCLUSION: The presented results show that APT imaging is sensitive to HIFU-induced changes in tumor tissue and may thus serve as a new biomarker for monitoring the response of tumor tissue to HIFU treatment.

Multiparametric MRI analysis for the identification of high intensity focused ultrasound-treated tumor tissue.

PURPOSE: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Dual-targeting of αvß3 and galectin-1 improves the specificity of paramagnetic/fluorescent liposomes to tumor endothelium in vivo.

Molecular imaging of angiogenesis requires a highly specific and efficient contrast agent for targeting activated endothelium. We have previously demonstrated that paramagnetic and fluorescent liposomes functionalized with two angiogenesis-specific ligands, the galectin-1-specific anginex (Anx) and the α(v)ß(3) integrin-specific RGD, produce synergistic targeting effect in vitro. In the current study, we applied Anx and RGD dual-conjugated liposomes (Anx/RGD-L) for angiogenesis-specific MRI in vivo, focusing on the specificity and efficacy of liposome association with tumor endothelium. The targeting properties, clearance kinetics and biodistribution of Anx/RGD-L were investigated in B16F10 melanoma-bearing mice, and compared to liposomes functionalized with either Anx (Anx-L) or RGD (RGD-L). The contrast enhancement produced by dual- and single-targeted nanoparticles in the tumor was measured using in vivo T(1)-weighted MRI, complemented by ex vivo immunohistochemical evaluation of tumor tissues. Blood clearance kinetics of Anx/RGD-L was three-fold more rapid than for RGD-L, but comparable to Anx-L. Both dual- and single-targeted liposomes produced similar changes in MRI contrast parameters in tumors with high inter-tumor variability (ΔR(1)=0.04±0.03s(-1), 24h post-contrast). Importantly, however, the specificity of Anx/RGD-L association with tumor endothelium of 53±6%, assessed by fluorescence microscopy, was significantly higher compared to 43±9% (P=0.043) and 28±8% (P=0.0001) of Anx-L and RGD-L, respectively. In contrast, long-circulating RGD-L were on average 16% more efficient in targeting tumor endothelium compared to Anx/RGD-L. Significant differences were also found in the biodistribution of investigated contrast agents. In conclusion, synergistic targeting of α(v)ß(3) and galectin-1 improved the specificity of the association of the liposomal contrast agent to tumor endothelium in vivo, providing therefore a more reliable MRI readout of the angiogenic activity.