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

R² values of ISODATA-derived versus histology-derived non-viable tumor fractions to the line of identity for all assessed feature vectors.

<p>R² values of ISODATA-derived versus histology-derived non-viable tumor fractions to the line of identity for all assessed feature vectors.</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

MRI parameter maps before and longitudinally after HIFU treatment.

<p>Representative example of multiparametric MRI of the hind limb region of a HIFU-treated tumor-bearing mouse before and 1 h and 72 h after HIFU treatment. T₂-weighted images of an axial slice of the tumor-bearing paw are shown in the left panel. The hyper-intense tumor tissue is surrounded by hypo-intense muscle tissue. In the other panels the same T₂-weighted images are displayed except that the tumor pixels are overlaid with MRI parameter maps. The parameter maps were scaled according to the color scale bar shown at the right-hand side of the figure. The corresponding parameter range for this scale bar is indicated above each panel. The approximate direction of the HIFU treatment is shown by the white arrow on the T₂-weighted image, which was collected 1 h after HIFU treatment.</p

Visual correspondence between ISODATA-derived and histology-derived non-viable tumor areas.

<p><b>A</b>) Representative T₂-weighted images of the hind limb region of two HIFU-treated mice before, 1 h after and 72 h after HIFU. The results of ISODATA segmentation with feature vector {T₁, T₂, ADC} are overlaid on the tumor pixels. NADH-diaphorase stained sections of tumors dissected at 72 h after HIFU were made at approximately the same location within the tumor and are shown at the bottom of each column. ROIs around the entire (black line) and non-viable (red line) tumor tissue were drawn manually. Data in the left column are from the animal presented in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0099936#pone-0099936-g001" target="_blank">Figure 1</a>. <b>B</b>) Similar data of a non-treated control mouse that was subjected to serial MRI measurements at the same time points (Day 0, Day 1 and Day 4) as the HIFU-treated animals. Scale bar = 1 mm.</p

One-to-one correspondence between histology-derived and ISODATA-derived non-viable tumor fractions.

<p>Scatter plots of the 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. The symbols ○, □ and ▴ indicate groups ‘1 h after HIFU’, ‘72 h after HIFU’ and ‘Control’, respectively. The line of identity is shown as visual reference. The R² values of the data to the line of identity are shown in the top left corner of each plot.</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

Rapid stromal remodeling by short-term VEGFR2 inhibition increases chemotherapy delivery in esophagogastric adenocarcinoma

Anti-angiogenic agents combined with chemotherapy is an important strategy for the treatment of solid tumors. However, survival benefit is limited, urging the improvement of combination therapies. We aimed to clarify the effects of vascular endothelial growth factor receptor 2 (VEGFR2) targeting on hemodynamic function and penetration of drugs in esophagogastric adenocarcinoma (EAC). Patient-derived xenograft (PDX) models of EAC were subjected to long-term and short-term treatment with anti-VEGFR2 therapy followed by chemotherapy injection or multi-agent dynamic contrast-enhanced (DCE-) MRI and vascular casting. Long-term anti-VEGFR2-treated tumors showed a relatively lower flow and vessel density resulting in reduced chemotherapy uptake. On the contrary, short-term VEGFR2 targeting resulted in relatively higher flow, rapid vasodilation, and improved chemotherapy delivery. Assessment of the extracellular matrix (ECM) revealed that short-term anti-angiogenic treatment drastically remodels the tumor stroma by inducing nitric oxide synthesis and hyaluronan degradation, thereby dilating the vasculature and improving intratumoral chemotherapy delivery. These previously unrecognized beneficial effects could not be maintained by long-term VEGFR2 inhibition. As the identified mechanisms are targetable, they offer direct options to enhance the treatment efficacy of anti-angiogenic therapy combined with chemotherapy in EAC patients