An extended reference region model for DCE-MRI that accounts for plasma volume

Dynamic 2-deoxy-D-glucose-enhanced multispectral optoacoustic tomography for assessing metabolism and vascular hemodynamics of breast cancer

Clinical tools for measuring tumor vascular hemodynamics, such as dynamic contrast-enhanced MRI, are clinically important to assess tumor properties. Here we explored the use of multispectral optoacoustic tomography (MSOT), which has a high spatial and temporal resolution, to measure the intratumoral pharmacokinetics of a near-infrared-dye-labeled 2-Deoxyglucose, 2-DG-800, in orthotropic 2-LMP breast tumors in mice. As uptake of 2-DG-800 is dependent on both vascular properties, and glucose transporter activity - a widely-used surrogate for metabolism, we evaluate hemodynamics of 2-DG-MP by fitting the dynamic MSOT signal of 2-DG-800 into two-compartment models including the extended Tofts model (ETM) and reference region model (RRM). We showed that dynamic 2-DG-enhanced MSOT (DGE-MSOT) is powerful in acquiring hemodynamic rate constants, including Ktrans and Kep, via systemically injecting a low dose of 2-DG-800 (0.5 µmol/kg b.w.). In our study, both ETM and RRM are efficient in deriving hemodynamic parameters in the tumor. Area-under-curve (AUC) values (which correlate to metabolism), and Ktrans and Kep values, can effectively distinguish tumor from muscle. Hemodynamic parameters also demonstrated correlations to hemoglobin, oxyhemoglobin, and blood oxygen level (SO2) measurements by spectral unmixing of the MSOT data. Together, our study for the first time demonstrated the capability of DGE-MSOT in assessing vascular hemodynamics of tumors.

Fluid Mechanics Approach to Perfusion Quantification: Vasculature Computational Fluid Dynamics Simulation, Quantitative Transport Mapping (QTM) Analysis of Dynamics Contrast Enhanced MRI, and Application in Nonalcoholic Fatty Liver Disease Classification

OBJECTIVE

We quantify liver perfusion using quantitative transport mapping (QTM) method that is free of arterial input function (AIF). QTM method is validated in a vasculature computational fluid dynamics (CFD) simulation and is applied for processing dynamic contrast enhanced (DCE) MRI images in differentiating liver with nonalcoholic fatty liver disease (NAFLD) from healthy controls using pathology reference in a preclinical rabbit model.

METHODS

QTM method was validated on a liver perfusion simulation based on fluid dynamics using a rat liver vasculature model and the mass transport equation. In the NAFLD grading task, DCE MRI images of 7 adult rabbits with methionine choline-deficient diet-induced nonalcoholic steatohepatitis (NASH), 8 adult rabbits with simple steatosis (SS) were acquired and processed using QTM method and dual-input two compartment Kety's method respectively. Statistical analysis was performed on six perfusion parameters: velocity magnitude | u | derived from QTM, liver arterial blood flow LBFa, liver venous blood flow LBFv, permeability Ktrans, blood volume Vp and extravascular space volume Ve averaged in liver ROI.

RESULTS

In the simulation, QTM method successfully reconstructed blood flow, reduced error by 48% compared to Kety's method. In the preclinical study, only QTM |u| showed significant difference between high grade NAFLD group and low grade NAFLD group.

CONCLUSION

QTM postprocesses DCE-MRI automatically through deconvolution in space and time to solve the inverse problem of the transport equation. Comparing with Kety's method, QTM method showed higher accuracy and better differentiation in NAFLD classification task.

SIGNIFICANCE

We propose to apply QTM method in liver DCE MRI perfusion quantification.

Intraprocedural Transcatheter Intraarterial Perfusion (TRIP)-MRI for Evaluation of Irreversible Electroporation Therapy Response in a Rabbit Liver Tumor Model

Purpose

Irreversible electroporation (IRE) is a promising new ablation method for hepatocellular carcinoma (HCC) treatment with few side-effects; however, tissue perfusion and differentiation between treatment zones have not been sufficiently studied. In this project, we analyzed HCC tumor perfusion changes immediately after IRE treatment using transcatheter intraarterial perfusion (TRIP)-MRI to monitor treatment zone margins.

Materials and Methods

All protocols were approved by the institutional animal care and use committee. A total of 34 rabbits were used for this prospective study: tumor liver group (n=17), normal liver group (n=14), and 3 for growing VX2 tumors. All procedures and imaging were performed under anesthesia. VX2 tumors were grown by injection of VX2 cells into rabbit hindlimbs. Liver tumors were induced by percutaneous US-guided injection of VX2 tumor fragments into liver. For digital subtraction angiography (DSA), a 2F catheter was advanced through left hepatic artery via femoral artery access, followed by contrast injection. All rabbits underwent baseline anatomic MRI, then IRE procedure or IRE probe placement only, and lastly post-procedure anatomic and TRIP-MRI. Liver tissues were dissected immediately after imaging for histology. All statistical analyses were performed on GraphPad Prism, with P<0.05 considered significant.

Results

IRE generated central IRE zone and peripheral reversible electroporation (RE) zone on anatomic MRI for both normal liver and liver tumor tissues. The semiquantitative analysis showed that IRE zone had the lowest AUC, PE, WIS, K^trans, v_e , and v_p as well as the highest TTP, followed by RE zone, then untreated tissues. Receiver operating characteristic analysis showed that WIS and AUC₆₀ had the highest AUC_ROC. Histologic analysis showed a positive correlation in viable area fraction between MRI and histologic measurements. IRE zone had the highest %apoptosis and lowest CD31+ staining.

Conclusion

Our results demonstrated that intraprocedural TRIP-MRI can effectively differentiate IRE and RE zones after IRE ablation in normal liver and liver tumor tissues.

Dose-response assessment by quantitative MRI in a phase 1 clinical study of the anti-cancer vascular disrupting agent crolibulin

The vascular disrupting agent crolibulin binds to the colchicine binding site and produces anti-vascular and apoptotic effects. In a multisite phase 1 clinical study of crolibulin (NCT00423410), we measured treatment-induced changes in tumor perfusion and water diffusivity (ADC) using dynamic contrast-enhanced MRI (DCE-MRI) and diffusion-weighted MRI (DW-MRI), and computed correlates of crolibulin pharmacokinetics. 11 subjects with advanced solid tumors were imaged by MRI at baseline and 2–3 days post-crolibulin (13–24 mg/m²). ADC maps were computed from DW-MRI. Pre-contrast T₁ maps were computed, co-registered with the DCE-MRI series, and maps of area-under-the-gadolinium-concentration-curve-at-90 s (AUC_90s) and the Extended Tofts Model parameters k^trans, v_e, and v_p were calculated. There was a strong correlation between higher plasma drug \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${C}^{max}$$\end{document}Cmax and a linear combination of (1) reduction in tumor fraction with \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${AUC}_{90s}>15.8$$\end{document}AUC90s>15.8 mM s, and, (2) increase in tumor fraction with \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${v}_{e}<0.3$$\end{document}ve<0.3. A higher plasma drug AUC was correlated with a linear combination of (1) increase in tumor fraction with \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text{ADC}} < 1.1 \times 10^{ - 3} \;{\text{mm}}^{2} /{\text{s}}$$\end{document}ADC<1.1×10-3mm2/s, and, (2) increase in tumor fraction with \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$v_{e}<0.3$$\end{document}ve<0.3. These findings are suggestive of cell swelling and decreased tumor perfusion 2–3 days post-treatment with crolibulin. The multivariable linear regression models reported here can inform crolibulin dosing in future clinical studies of crolibulin combined with cytotoxic or immune-oncology agents.

Pharmacokinetic modeling of dynamic contrast-enhanced MRI using a reference region and input function tail

PURPOSE

Quantitative analysis of dynamic contrast-enhanced MRI (DCE-MRI) requires an arterial input function (AIF) which is difficult to measure. We propose the reference region and input function tail (RRIFT) approach which uses a reference tissue and the washout portion of the AIF.

METHODS

RRIFT was evaluated in simulations with 100 parameter combinations at various temporal resolutions (5-30 s) and noise levels (σ = 0.01-0.05 mM). RRIFT was compared against the extended Tofts model (ETM) in 8 studies from patients with glioblastoma multiforme. Two versions of RRIFT were evaluated: one using measured patient-specific AIF tails, and another assuming a literature-based AIF tail.

RESULTS

RRIFT estimated the transfer constant K trans and interstitial volume v e with median errors within 20% across all simulations. RRIFT was more accurate and precise than the ETM at temporal resolutions slower than 10 s. The percentage error of K trans had a median and interquartile range of -9 ± 45% with the ETM and -2 ± 17% with RRIFT at a temporal resolution of 30 s under noiseless conditions. RRIFT was in excellent agreement with the ETM in vivo, with concordance correlation coefficients (CCC) of 0.95 for K trans , 0.96 for v e , and 0.73 for the plasma volume v p using a measured AIF tail. With the literature-based AIF tail, the CCC was 0.89 for K trans , 0.93 for v e and 0.78 for v p .

CONCLUSIONS

Quantitative DCE-MRI analysis using the input function tail and a reference tissue yields absolute kinetic parameters with the RRIFT method. This approach was viable in simulation and in vivo for temporal resolutions as low as 30 s.