Non-Contrast-Enhanced Multiparametric MRI of the Hypoxic Tumor Microenvironment Allows Molecular Subtyping of Breast Cancer: A Pilot Study.

Tumor neoangiogenesis is an important hallmark of cancer progression, triggered by alternating selective pressures from the hypoxic tumor microenvironment. Non-invasive, non-contrast-enhanced multiparametric MRI combining blood-oxygen-level-dependent (BOLD) MRI, which depicts blood oxygen saturation, and intravoxel-incoherent-motion (IVIM) MRI, which captures intravascular and extravascular diffusion, can provide insights into tumor oxygenation and neovascularization simultaneously. Our objective was to identify imaging markers that can predict hypoxia-induced angiogenesis and to validate our findings using multiplexed immunohistochemical analyses. We present an in vivo study involving 36 female athymic nude mice inoculated with luminal A, Her2+, and triple-negative breast cancer cells. We used a high-field 9.4-tesla MRI system for imaging and subsequently analyzed the tumors using multiplex immunohistochemistry for CD-31, PDGFR-ß, and Hif1-α. We found that the hyperoxic-BOLD-MRI-derived parameter ΔR2* discriminated luminal A from Her2+ and triple-negative breast cancers, while the IVIM-derived parameter fIVIM discriminated luminal A and Her2+ from triple-negative breast cancers. A comprehensive analysis using principal-component analysis of both multiparametric MRI- and mpIHC-derived data highlighted the differences between triple-negative and luminal A breast cancers. We conclude that multiparametric MRI combining hyperoxic BOLD MRI and IVIM MRI, without the need for contrast agents, offers promising non-invasive markers for evaluating hypoxia-induced angiogenesis.

A Multi-Variate framework to assess reliability and discrimination power of Bayesian estimation of Intravoxel Incoherent Motion parameters.

PURPOSE: To propose a multivariate multi-step framework for a systematic assessment of the estimation reliability and discriminability of Intravoxel Incoherent Motion (IVIM) model parameters. METHODS: Monte-Carlo simulations were generated on a range of SNRs and in different IVIM combinations considering: i) a dense discretization with 24 b-values; ii) a discretization with 9 b-values. A state-of-the-art Bayesian fitting method was adopted. The framework assessed: i) the best model between mono- and bi-exponential, through the BIC index; ii) the fitting accuracy; iii) the power in discriminating two different IVIM parameters distributions of estimated coefficients, using a multivariate test. Exemplificative oncologic cases were also presented. RESULTS: The bi-exponential fitting was reliable for perfusion fraction higher than 5%, with high accuracy in D estimation, acceptable error for f, but high uncertainty in D*. The discrimination of two distributions is generally feasible if differences in D values (at least 0.3 x10-3 mm2/s) are present; in the case of similar D values, a minimal difference of 5% in f can be discriminated just in case of balanced sample size and dense b-values discretization, whereas the impact of D* is quite negligible. These results were also supported by clinical examples. CONCLUSIONS: IVIM model is generally accurate in estimating diffusion, but uncertainties related to perfusion estimation are not negligible and compromise the discrimination power when different populations should be differentiated. The proposed framework should be adopted as interpretative guidelines to better understand when IVIM model applied on real data can provide reliable findings.

Optimal Model Mapping for Intravoxel Incoherent Motion MRI.

In general, only one diffusion model would be applied to whole field-of-view voxels in the intravoxel incoherent motion-magnetic resonance imaging (IVIM-MRI) study. However, the choice of the applied diffusion model can significantly influence the estimated diffusion parameters. The quality of the diffusion analysis can influence the reliability of the perfusion analysis. This study proposed an optimal model mapping method to improve the reliability of the perfusion parameter estimation in the IVIM study. Six healthy volunteers (five males and one female; average age of 38.3 ± 7.5 years). Volunteers were examined using a 3.0 Tesla scanner. IVIM-MRI of the brain was applied at 17 b-values ranging from 0 to 2,500 s/mm2. The Gaussian model, the Kurtosis model, and the Gamma model were found to be optimal for the CSF, white matter (WM), and gray matter (GM), respectively. In the mean perfusion fraction (fp) analysis, the GM/WM ratios were 1.16 (Gaussian model), 1.80 (Kurtosis model), 1.94 (Gamma model), and 1.54 (Optimal model mapping); in the mean pseudo diffusion coefficient (D*) analysis, the GM/WM ratios were 1.18 (Gaussian model), 1.19 (Kurtosis model), 1.56 (Gamma model), and 1.24 (Optimal model mapping). With the optimal model mapping method, the estimated fp and D* were reliable compared with the conventional methods. In addition, the optimal model maps, the associated products of this method, may provide additional information for clinical diagnosis.

Discrimination of Malignant and Benign Breast Lesions Using Quantitative Multiparametric MRI: A Preliminary Study.

We aimed to compare diagnostic performance in discriminating malignant and benign breast lesions between two intravoxel incoherent motion (IVIM) analysis methods for diffusion-weighted magnetic resonance imaging (DW-MRI) data and between DW- and dynamic contrast-enhanced (DCE)-MRI, and to determine if combining DW- and DCE-MRI further improves diagnostic accuracy. DW-MRI with 12 b-values and DCE-MRI were performed on 26 patients with 28 suspicious breast lesions before biopsies. The traditional biexponential fitting and a 3-b-value method were used for independent IVIM analysis of the DW-MRI data. Simulations were performed to evaluate errors in IVIM parameter estimations by the two methods across a range of signal-to-noise ratio (SNR). Pharmacokinetic modeling of DCE-MRI data was performed. Conventional radiological MRI reading yielded 86% sensitivity and 21% specificity in breast cancer diagnosis. At the same sensitivity, specificity of individual DCE- and DW-MRI markers improved to 36%-57% and that of combined DCE- or combined DW-MRI markers to 57%-71%, with DCE-MRI markers showing better diagnostic performance. The combination of DCE- and DW-MRI markers further improved specificity to 86%-93% and the improvements in diagnostic accuracy were statistically significant (P < .05) when compared with standard clinical MRI reading and most individual markers. At low breast DW-MRI SNR values (<50), like those typically seen in clinical studies, the 3-b-value approach for IVIM analysis generates markers with smaller errors and with comparable or better diagnostic performances compared with biexponential fitting. This suggests that the 3-b-value method could be an optimal IVIM-MRI method to be combined with DCE-MRI for improved diagnostic accuracy.

Intravoxel incoherent motion magnetic resonance imaging for predicting the long-term efficacy of immune checkpoint inhibitors in patients with non-small-cell lung cancer.

OBJECTIVES: Conventional evaluation of anti-tumor activity on the basis of tumor size is inadequate for immune checkpoint inhibitors (ICIs). We therefore aimed to assess the usefulness of intravoxel incoherent motion magnetic resonance imaging (IVIM-MRI) for evaluation of the therapeutic efficacy of ICIs. MATERIALS AND METHODS: A chest IVIM-MRI was performed before and 2, 4, and 8 weeks after administration of ICIs in patients with advanced non-small-cell lung cancer. Apparent diffusion coefficient (ADC), skewness of ADC (ADCskew), kurtosis of ADC (ADCkurt), true diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f) were evaluated at each evaluation point and changes from the baseline (Δ). RESULTS: Twenty patients were enrolled in this study. An increased ADC 8 weeks and decreased ADCkurt and ΔADCkurt 4 weeks after ICIs was associated with objective responses and longer progression-free survival (PFS). A decreased ΔADCskew at 4 weeks was associated with objective responses, disease control, and longer PFS and overall survival. There was no correlation between the efficacy of ICIs and D, D* and f. All of three patients who had pseudoprogression had decreased ΔADCskew at 4 weeks and two of them had decreased ΔADCkurt at 4 weeks. Inversely, all five patients who had progressive disease (PD) did not have increased ΔADCskew at 4 weeks and only one of them had decreased ΔADCkurt at 4 weeks. CONCLUSIONS: Changes in histograms of ADC may be useful for predicting long-term efficacy and distinguishing between pseudoprogression and actual PD after ICIs.

On the identification of the blood vessel confounding effect in intravoxel incoherent motion (IVIM) Diffusion-Weighted (DW)-MRI in liver: An efficient sparsity based algorithm.

IntraVoxel Incoherent Motion (IVIM) Diffusion-Weighted Magnetic Resonance Imaging (DW-MRI) is of great interest for evaluating tissue diffusion and perfusion and producing parametric maps in clinical applications for liver pathologies. However, the presence of macroscopic blood vessels (not capillaries) in a given Region of Interest (ROI) results in a confounding effect that bias the quantification of tissue perfusion. Therefore, it is necessary to identify those voxels affected by blood vessels. In this paper, an efficient algorithm for an automatic identification of blood vessels in a given ROI is proposed. It relies on the sparsity of the spatial distribution of blood vessels. This sparsity prior can be easily incorporated using the all-voxel IVIM-MRI model introduced in this paper. In addition to the identification of blood vessels, the proposed algorithm provides a quantification of blood vessels, tissue diffusion and tissue perfusion of all voxels in a given ROI, in one single step. Besides, two strategies are proposed in this paper to deal with the nonnegativity of the model parameters. The efficiency of the proposed algorithm compared to the Non-Negative Least Square (NNLS)-based method, recently introduced to deal with the confounding blood vessel effect in the IVIM-MRI model, is confirmed using both realistic and real DW-MR images.

Intravoxel incoherent motion MR imaging for differentiating malignant lesions in spine: A pilot study.

PURPOSE: To determine the diagnostic potential of Intravoxel Incoherent Motion (IVIM) MRI for differentiating malignant spinal tumours from acute vertebral compression fractures and tuberculous spondylitis, and to compare IVIM with diffusion-weighted imaging (DWI) and chemical shift imaging (CSI). METHODS: The Institutional Review Board approved this prospective study, and informed consent was obtained. IVIM MRI, DWI, and CSI at 1.5 T were performed in 25 patients with 12 acute compression fractures, 14 tuberculous spondylitis, and 18 malignant spinal tumours. The parameters of these techniques were assessed using the Kruskal-Wallis test. The diagnostic performance of the parameters was evaluated using receiver operating characteristic (ROC) analysis. RESULTS: ADC, SIR, Dslow, Dfast, and f values of malignant tumours were significantly different from those of acute compression fracture (for all, p < 0.05). The mean Dslow and Dfast values of malignant spinal tumours had significant differences compared with those of tuberculous spondylitis (for all, p < 0.05). However, no significant differences were observed in any quantitative parameters between the acute compression fracture and the tuberculous spondylitis (p > 0.05). Dslow•f showed the highest AUC value of 0.980 (95%CI: 0.942-1.000) in differentiating acute compression fracture and malignant spinal tumours. Dslow showed the highest AUC value of 0.877 (95%CI: 0.713-0.966) in differentiating tuberculous spondylitis and malignant spinal tumours. CONCLUSIONS: IVIM MR imaging may be helpful for differentiating malignant spinal tumours from acute vertebral compression fractures and tuberculous spondylitis.

MR imaging biomarkers evaluating vascular normalization window after anti-vessel treatment.

The beginning and the end of the vascular normalization window are not clear in response to anti-angiogenic therapies. We used dynamic contrast-enhanced MRI (DCE-MRI) and intravoxel incoherent motion MRI (IVIM-MRI) to noninvasively evaluate the vascular normalization window. MRI was performed five times: before treatment and on the second, fourth, sixth and eighth days of treatment. Quantitative perfusion parameters were calculated at each time point, including the volume transfer coefficient (Ktrans), reverse transfer constant (Kep), pseudodiffusion coefficient (D*) and perfusion fraction (f). Tumors were evaluated for changes by immunohistochemistry. An increase in Ktrans and Kep was observed after bevacizumab treatment on days 2 and 4. Similar trends were observed for D* and f on days 2 and 4. However, the parameters of Ktrans, Kep, D* and f were decreased on days 6 and 8. A significant increase of the vessel maturity index between the treatment and control groups was measured on days 2 and 4, but this increase abated by days 6 and 8. IVIM and DCE-MRI are helpful when quantifying the tumor perfusion and evaluating the vascular normalization window after anti-vessel therapy. IVIM and DCE-MRI can outline the important period after anti-vessel treatment.