Intravoxel Incoherent Motion Diffusion-Weighted Imaging for Predicting and Monitoring the Response of Anti-Angiogenic Treatment in the Orthotopic Nude Mouse Model of Lung Adenocarcinoma

Histogram analysis of multiple diffusion models for predicting advanced non-small cell lung cancer response to chemoimmunotherapy

BACKGROUND

There is an urgent need to find a reliable and effective imaging method to evaluate the therapeutic efficacy of immunochemotherapy in advanced non-small cell lung cancer (NSCLC). This study aimed to investigate the capability of intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) histogram analysis based on different region of interest (ROI) selection methods for predicting treatment response to chemoimmunotherapy in advanced NSCLC.

METHODS

Seventy-two stage III or IV NSCLC patients who received chemoimmunotherapy were enrolled in this study. IVIM and DKI were performed before treatment. The patients were classified as responders group and non-responders group according to the Response Evaluation Criteria in Solid Tumors 1.1. The histogram parameters of ADC, Dslow, Dfast, f, Dk and K were measured using whole tumor volume ROI and single slice ROI analysis methods. Variables with statistical differences would be included in stepwise logistic regression analysis to determine independent parameters, by which the combined model was also established. And the receiver operating characteristic curve (ROC) were used to evaluate the prediction performance of histogram parameters and the combined model.

RESULTS

ADC, Dslow, Dk histogram metrics were significantly lower in the responders group than in the non-responders group, while the histogram parameters of f were significantly higher in the responders group than in the non-responders group (all P < 0.05). The mean value of each parameter was better than or equivalent to other histogram metrics, where the mean value of f obtained from whole tumor and single slice both had the highest AUC (AUC = 0.886 and 0.812, respectively) compared to other single parameters. The combined model improved the diagnostic efficiency with an AUC of 0.968 (whole tumor) and 0.893 (single slice), respectively.

CONCLUSIONS

Whole tumor volume ROI demonstrated better diagnostic ability than single slice ROI analysis, which indicated whole tumor histogram analysis of IVIM and DKI hold greater potential than single slice ROI analysis to be a promising tool of predicting therapeutic response to chemoimmunotherapy in advanced NSCLC at initial state.

Intravoxel incoherent motion diffusion-weighted imaging of solitary pulmonary lesions: initial study with gradient- and spin-echo sequences

AIM

To evaluate the feasibility and image quality of intravoxel incoherent motion diffusion-weighted imaging (IVIM) using gradient- and spin-echo (GRASE) in solitary pulmonary lesions (SPLs) compared to echo planar imaging (EPI) and turbo spin-echo (TSE) at 3 T.

MATERIALS AND METHODS

Forty-two patients with SPLs underwent lung magnetic resonance imaging (MRI) using TSE-IVIM, GRASE-IVIM, and EPI-IVIM at 3 T. Signal ratio (SR), contrast ratio (CR), and image distortion ratio (DR) of three sequences were compared. The reproducibility and repeatability of the apparent diffusion coefficient (ADC) and IVIM-derived parameters were assessed using the interclass correlation coefficient (ICC) and coefficient of variation (CV). The repeatability of the ADC and IVIM-derived parameters between all sequences was evaluated using the Bland-Altman method.

RESULTS

EPI-IVIM had a higher SR, lower CR, and higher DR (p<0.05); however, there was no significant difference between TSE-IVIM and GRASE-IVIM (p>0.05). Compared to the D and f values of TSE-IVIM (ICC lower limit >0.90), GRASE-IVIM and EPI-IVIM showed poor reproducibility (ICC lower limit<0.90). The repeatability of the ADC and D values obtained by TSE-IVIM (CV, 1.93-2.96% and 2.44-3.18%, respectively) and GRASE-IVIM (CV, 2.56-3.12% and 3.21-3.51%, respectively) were superior to those of EPI-IVIM (CV, 10.03-10.2% and 11.30-11.57%). The repeatability of D∗ and f values for all sequences was poor. Bland-Altman analysis showed wide limits of agreement between the ADC and IVIM-derived parameters for all sequences.

CONCLUSION

GRASE-IVIM reduced the DR, improved the stability of the ADC and D values on repeated scans, and had the shortest scanning time.

Dynamic Contrast-Enhanced Ultrasound Modeling of an Analog to Pseudo-Diffusivity in Intravoxel Incoherent Motion Magnetic Resonance Imaging

Tumor perfusion and vascular properties are important determinants of cancer response to therapy and thus various approaches for imaging perfusion are being explored. In particular, Intravoxel Incoherent Motion (IVIM) MRI has been actively researched as an alternative to Dynamic-Contrast-Enhanced (DCE) CT and DCE-MRI as it offers non-ionizing, non-contrast-based perfusion imaging. However, for repetitive treatment assessment in a short time period, high cost, limited access, and inability to scan at the bedside remain disadvantages of IVIM MRI. We propose an analysis framework that may enable 3D DCE Ultrasound (DCE-US) - low cost, bedside imaging with excellent safety record - as an alternative modality to IVIM MRI for the generation of DCE-US based pseudo-diffusivity maps in acoustically accessible anatomy and tumors. Modelling intravascular contrast propagation as a convective-diffusive process, we reconstruct parametric maps of pseudo-diffusivity by solving a large-scale fully coupled inverse problem without any assumptions regarding local constancy of the reconstructed parameters. In a mouse tumor model, we demonstrate that the 3D DCE-US pseudo-diffusivity is repeatable, sensitive to treatment with an antiangiogenic agent, and moderately correlated to histological measures of perfusion and angiogenesis.

Application of Intravoxel Incoherent Motion Diffusion-Weighted Imaging in Predicting and Monitoring Early Efficacy of Anti-Angiogenic Therapy in the C6 Glioma Rat Model

Objective

To investigate the feasibility of intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) in evaluating early effects of anti-angiogenic therapy in the C6 glioma rat model.

Methods

Twenty-six rats of the C6 glioma model were randomly divided into a treatment group (received bevacizumab) and a control group (physiological saline). IVIM-DWI was performed on days 0, 1, 3, 5, and 7 after anti-angiogenic therapy and tumor growth and IVIM-DWI parameters were dynamically observed. Hematoxylin and eosin, CD34 microvessel density (MVD), proliferation of cell nuclear antigen (PCNA), and Hif-α staining were performed on day 7. One-way ANOVA was used to compare intra-group differences and an independent-samples t-test was used to compare inter-group differences of MRI parameters. Correlations between IVIM-DWI parameters, tumor size, and pathological results were analyzed.

Results

The relative change in tumor volume (ΔVolume) in the two groups differed significantly on days 5 and 7 (p = 0.038 and p < 0.001). The perfusion-related parameters D*- and f-values decreased in the treatment group and demonstrated significant differences compared with the control group on days 3, 5, and 7 (p = 0.033, p < 0.001, and p < 0.001, respectively). The diffusion-related parameters ADC and D-values increased in the treatment group and were found to be significantly differently different from the control group on days 5 and 7 (both p < 0.001). The initial D-value showed a negative correlation with ΔVolume (γ = −0.744, p < 0.001), whereas the initial D*-value and relative change of D-value had a positive correlation with ΔVolume (γ = 0.718, p < 0.001 and γ = 0.800, p < 0.001, respectively). MVD was strongly positively correlated with D*-value (r = 0.886, p = 0.019), PCNA was negatively correlated with ADC- and D-values (r = −0.848, p = 0.033; and r = −0.928 p = 0.008, respectively), and Hif-1α was strongly negatively correlated with D*-value (r = −0.879, p = 0.010).

Conclusion

IVIM-DWI was sensitive and accurate in predicting and monitoring the effects of early anti-angiogenesis therapy in a C6 glioma rat model.