DCE-MRI of the liver: reconstruction of the arterial input function using a low dose pre-bolus contrast injection

Stereotactic Body Radiation Therapy (SBRT) for Hepatocellular Carcinoma (HCC) With Single Photon Emission Computed Tomography (SPECT) Functional Treatment Planning in Patients With Advanced Hepatic Cirrhosis

Purpose

We report on the feasibility and outcomes of liver stereotactic body radiation therapy (SBRT) for hepatocellular carcinoma (HCC) with single-photon emission computed tomography (SPECT) functional treatment planning in patients with Child-Pugh (CP) B/C cirrhosis.

Methods and Materials

Liver SPECT with 99mTc-sulfur colloid was coregistered to treatment planning computed tomography (CT) for the guided avoidance of functional hepatic parenchyma during SBRT. Functional liver volumes (FLVs) obtained from SPECT were compared with anatomic liver volumes defined on the planning CT. Radiation dose constraints were adapted exclusively to FLV. Local control, toxicity, and survival were reported with at least 6 months of radiographic follow-up. Pre- and posttransplant outcomes were analyzed in a subset of patients who completed SBRT as a bridge to liver transplant. Model of End-Stage Liver Disease was used to score hepatic function before and after SBRT completion.

Results

With a median follow-up of 32 months, 45 patients (58 lesions) with HCC and CP-B/C cirrhosis received SBRT to a median dose of 45 Gy (3-5 fractions). FLV loss (34%, P < .001) was observed in all patients, and the functional and anatomic liver volumes matched well in a control group of noncirrhotic/non-HCC patients. Despite marked functional parenchyma retraction, the amount of FLV on SPECT exposed to the threshold irradiation was significantly less than the CT liver volumes (P < .001) because of the optimized beam placement during dosimetry planning. Twenty-three patients (51%) successfully completed orthotopic liver transplant, with a median time to transplant of 9.2 months. With 91% in-field local control, the overall 2-year survival was 65% (90% after the orthotopic liver transplant), with no incidence of radiation-induced liver disease observed within 3 to 4 months or accelerated CP class migration from B to C within the first 6 months post-SBRT. Mean Model of End-Stage Liver Disease-Na score was not significantly elevated at 3-month intervals after SBRT completion.

Conclusions

Functional treatment planning with 99mTc sulfur colloid SPECT/CT allows identification and avoidance of functional hepatic parenchyma in patients with CP-B/C cirrhosis, leading to low toxicity and satisfactory transplant outcomes.

Noninvasive diagnosis of portal hypertension using gadoxetate DCE-MRI of the liver and spleen

OBJECTIVES

To assess the performance of gadoxetate dynamic contrast-enhanced (DCE) MRI of the liver and spleen for noninvasive diagnosis of portal hypertension (PH).

METHODS

Thirty-five patients (M/F 22/13, mean age 55 years) with chronic liver disease who underwent hepatic venous pressure gradient (HVPG) measurements were prospectively enrolled in this IRB-approved study. All patients underwent multiparametric MRI including gadoxetate DCE-MRI acquisition. Model-based and model-free DCE-MRI analyses were performed. The correlation between DCE-MRI parameters and HVPG was assessed. ROC analysis was employed to determine the diagnostic performance of DCE-MRI parameters alone and in combination for prediction of PH and clinically significant (CS)PH (HVPG > 5 and ≥ 10 mmHg, respectively).

RESULTS

Mean HVPG was 7.0 ± 5.0 mmHg (range 0-18 mmHg). Twenty-one (60%) patients had PH, of whom 9 had CSPH. Modeled liver uptake fraction f_i and uptake rate k_i and model-free parameters liver upslope and uptake were all significantly negatively correlated with HVPG (r range - 0.490 to - 0.398, p value range 0.003-0.018), while spleen interstitial fraction v_e was significantly positively correlated with HVPG (r = 0.336, p = 0.048). For PH diagnosis, liver k_i showed the best diagnostic performance with an AUC, sensitivity, and specificity of 0.74 (confidence interval (CI) 0.57-0.91), 71.4%, and 78.6%. The combination of liver k_i and spleen v_e was selected as the best classifier for diagnosis of CSPH with an AUC, sensitivity, and specificity of 0.87 (CI 0.75-0.99), 100%, and 73.1%.

CONCLUSIONS

Our results demonstrate the potential utility of hepatocyte uptake parameters and spleen interstitial fraction obtained with gadoxetate DCE-MRI for the diagnosis of PH and CSPH.

KEY POINTS

• Liver uptake and spleen interstitial fraction estimates from gadoxetate DCE-MRI are significantly correlated with portal pressure measurements. • Liver uptake rate shows good diagnostic performance for the diagnosis of portal hypertension. • The combination of liver uptake rate with spleen interstitial fraction exhibits excellent diagnostic performance for the diagnosis of clinically significant portal hypertension.

Comparison of DCE-MRI of murine model cancers with a low dose and high dose of contrast agent

There are increasing concerns regarding intracellular accumulation of gadolinium (Gd) after multiple dynamic contrast enhanced (DCE) MRI scans. We investigated whether a low dose (LD) of Gd-based contrast agent is as effective as a high dose (HD) for quantitative analysis of DCE-MRI data, and evaluated the use of a split dose protocol to obtain new diagnostic parameters. Female C3H mice (n = 6) were injected with mammary carcinoma cells in the hind leg. MRI experiments were performed on 9.4 T scanner. DCE-MRI data were acquired with 1.5 s temporal resolution before and after a LD (0.04 mmol/kg), then again after 30 min followed by a HD (0.2 mmol/kg) bolus injection of Omniscan. The standard Tofts model was used to extract physiological parameters (K^trans and v_e) with the arterial input function derived from muscle reference tissue. In addition, an empirical mathematical model was used to characterize maximum contrast agent uptake (A), contrast agent uptake rate (α) and washout rate (β and γ). There were moderate to strong correlations (r = 0.69-0.97, p < 0001) for parameters K^trans, v_e, A, α and β from LD versus HD data. On average, tumor parameters obtained from LD data were significantly larger (p < 0.05) than those from HD data. The parameter ratios, K^trans, v_e, A and α calculated from the LD data divided by the HD data, were all significantly larger than 1.0 (p < 0.003) for tumor. T₂* changes following contrast agent injection affected parameters calculated from HD data, but this was not the case for LD data. The results suggest that quantitative analysis of LD data may be at least as effective for cancer characterization as quantitative analysis of HD data. In addition, the combination of parameters from two different doses may provide useful diagnostic information.

Correlation-Weighted Sparse Representation for Robust Liver DCE-MRI Decomposition Registration

Conducting an accurate motion correction of liver dynamic contrast-enhanced magnetic resonance (DCE-MR) imaging remains challenging because of intensity variations caused by contrast agents. Such variations lead to the failure of the traditional intensity-based registration method. To address this problem, we propose a correlation-weighted sparse representation framework to separate the contrast agent from original liver DCE-MR images. This framework allows the robust registration of motion components over time without intensity variances. Existing sparse coding techniques recover a 3D image containing only contrast agents (named contrast enhancement component) from a manually labeled dictionary, whose column has the same size with the original 3D volume (3D-t mode). The high dimension of the recovery target (3D volume) and the indistinguishability between the unenhanced and enhanced images make accurate coding difficult. In this paper, we predefine an ideal time-intensity curve containing only contrast agents (named contrast agent curve) and recover it from the transpose dictionary (t-3D mode), whose column has been updated into the original time-intensity curves. The low dimension of the target (1D curve) and the significant intergroup difference between contrast agent curves and non-contrast agent curves can estimate a series of pure contrast agent curves. A "correlation-weighted" constraint is introduced for the selection of a coding subset with more contrast agent curves, leading to an efficient and accurate sparse recovery process. Then, the contrast enhancement component can be estimated by the solved sparse coefficients' map and the ideal curve and subtracted from the original DCE-MRI. Finally, we register the de-enhanced images and apply the obtained deformation fields for the original DCE-MRI to achieve the goal of motion correction. We conduct the experiments on both simulated and real liver DCE-MRI data. Compared with other state-of-the-art DCE-MRI registration methods, the experimental results show that our method achieves a better registration performance with less computational efficiency.

Dynamic contrast-enhanced MRI to assess hepatocellular carcinoma response to Transarterial chemoembolization using LI-RADS criteria: A pilot study

PURPOSE

To identify quantitative dynamic contrast-enhanced (DCE)-MRI perfusion parameters indicating tumor response of hepatocellular carcinoma (HCC) to transarterial chemoembolization (TACE).

MATERIALS AND METHODS

This prospective pilot study was approved by our institutional review board; written and informed consent was obtained for each participant. Patients underwent DCE-MRI examinations before and after TACE. A variable flip-angle unenhanced 3D mDixon sequence was performed for T1 mapping. A dynamic 4D mDixon sequence was performed after contrast injection for assessing dynamic signal enhancement. Nonparametric analysis was conducted on the time-intensity curves. Parametric analysis was performed on the time-concentration curves using a dual-input single-compartment model. Treatment response according to Liver Reporting and Data System (LI-RADS) v2018 was used as the reference standard. The comparisons within groups (before vs. after treatment) and between groups (nonviable vs. equivocal or viable tumor) were performed using nonparametric bootstrap taking into account the clustering effect of lesions in patients.

RESULTS

Twenty-eight patients with 52 HCCs (size: 10-104 mm) were evaluated. For nonviable tumors (n = 27), time to peak increased from 62.5 ± 18.2 s before to 83.3 ± 12.8 s after treatment (P< 0.01). For equivocal or viable tumors (n = 25), time to peak and mean transit time significantly increased (from 54.4 ± 24.1 s to 69.5 ± 18.9 s, P < 0.01 and from 14.2 ± 11.8 s to 33.9 ± 36.8 s, P= 0.01, respectively) and the transfer constant from the extracellular and extravascular space to the central vein significantly decreased from 14.8 ± 14.1 to 8.1 ± 9.1 s^-1 after treatment (P= 0.01).

CONCLUSION

This prospective pilot DCE-MRI study showed that time to peak significantly changed after TACE treatment for both groups (nonviable tumors and equivocal or viable tumors). In our cohort, several perfusion parameters may provide an objective marker for differentiation of treatment response after TACE in HCC patients.

Quantitative imaging biomarkers alliance (QIBA) recommendations for improved precision of DWI and DCE-MRI derived biomarkers in multicenter oncology trials

Physiological properties of tumors can be measured both in vivo and noninvasively by diffusion-weighted imaging and dynamic contrast-enhanced magnetic resonance imaging. Although these techniques have been used for more than two decades to study tumor diffusion, perfusion, and/or permeability, the methods and studies on how to reduce measurement error and bias in the derived imaging metrics is still lacking in the literature. This is of paramount importance because the objective is to translate these quantitative imaging biomarkers (QIBs) into clinical trials, and ultimately in clinical practice. Standardization of the image acquisition using appropriate phantoms is the first step from a technical performance standpoint. The next step is to assess whether the imaging metrics have clinical value and meet the requirements for being a QIB as defined by the Radiological Society of North America's Quantitative Imaging Biomarkers Alliance (QIBA). The goal and mission of QIBA and the National Cancer Institute Quantitative Imaging Network (QIN) initiatives are to provide technical performance standards (QIBA profiles) and QIN tools for producing reliable QIBs for use in the clinical imaging community. Some of QIBA's development of quantitative diffusion-weighted imaging and dynamic contrast-enhanced QIB profiles has been hampered by the lack of literature for repeatability and reproducibility of the derived QIBs. The available research on this topic is scant and is not in sync with improvements or upgrades in MRI technology over the years. This review focuses on the need for QIBs in oncology applications and emphasizes the importance of the assessment of their reproducibility and repeatability. Level of Evidence: 5 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2019;49:e101-e121.

Multiparametric FDG-PET/MRI of Hepatocellular Carcinoma: Initial Experience

Purpose

To compare multiparametric (mp)FDG-PET/MRI metrics between hepatocellular carcinoma (HCC) and liver parenchyma and to assess the correlation between mpMRI and FDG-PET standard uptake values (SUVs) in liver parenchyma and HCC.

Methods

This prospective, institutional review board-approved study enrolled 15 patients (M/F 12/3; mean age 61 y) with HCC. mpMRI including blood-oxygen-level-dependent (BOLD) MRI, intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI), and dynamic contrast-enhanced-(DCE-) MRI was performed simultaneously with ¹⁸F-FDG-PET on a 3T PET/MRI hybrid system. Quantitative BOLD, IVIM and DCE-MRI parameters (Tofts model (TM) and shutter-speed model (SSM)), and PET parameters (SUV_mean and SUV_max) were quantified and compared between HCC lesions and liver parenchyma using Wilcoxon signed-rank tests. SUV ratios between HCCs and liver were also calculated (SUV_mean T/L and SUV_max T/L). Diagnostic performance of (combined) mp-PET/MRI parameters for characterization of HCC was assessed using ROC analysis. Spearman correlations between PET and mpMRI parameters in HCC tumors and liver parenchyma were evaluated.

Results

21 HCC lesions (mean size 4.0 ± 2.4 cm; range 2-13 cm) were analyzed. HCCs exhibited significantly higher arterial fraction (from DCE-MRI) and lower R ₂ ^∗ pre-O₂ and post-O₂ (from BOLD-MRI) versus liver parenchyma (P < 0.032). The highest diagnostic performance for differentiation between HCC and liver parenchyma was achieved for combined ART SSM and R ₂ ^∗ post-O₂ (AUC = 0.91). SUV_max showed reasonable performance for differentiation of HCC versus liver (AUC = 0.75). In HCC, DCE-MRI parameters K ^trans (TM and SSM) and v _e TM exhibited significant negative correlations with SUV_max T/L (r ranges from -0.624 to -0.566; FDR-adjusted P < 0.050).

Conclusions

Despite the observed reasonable diagnostic performance of FDG-PET SUV_max for HCC detection and several significant correlations between FDG-PET SUV and DCE-MRI parameters, FDG-PET did not provide clear additional value for HCC characterization compared to mpMRI in this pilot study.

Does intravoxel incoherent motion reliably stage hepatic fibrosis, steatosis, and inflammation?

OBJECTIVE

To investigate the usefulness of intravoxel incoherent motion (IVIM) in determining the severity of hepatic fibrosis, steatosis, and inflammation in patients with chronic liver disease.

METHODS

Forty-nine patients who had liver MRI with IVIM sequence and liver biopsy within three months of MRI were enrolled. A reviewer, blinded to histology, placed regions of interest of 1-2 cm² in the right liver lobe. In addition, the first twenty patients were assessed with a second reviewer. Perfusion fraction (f), pseudodiffusion coefficient (D _fast), true diffusion coefficient (D _slow), and apparent diffusion coefficient (ADC) were calculated from normalized signal intensities that were fitted into a biexponential model. Errors in the model were minimized with global stochastic optimization using Simulated Annealing. ANOVA with post hoc Tukey-Kramer test and multivariate generalized linear model analysis were performed, using histological findings as the gold standard.

RESULTS

The most common etiologies for liver disease were hepatitis C and alcohol, accounting together for 76% (37/49) of patients. Low-grade fibrosis (F0, F1), hepatic steatosis, and inflammation were seen in 24% (12/49), 31% (15/49), and 29% (14/49) of patients, respectively. The interobserver correlation was poor for D _fast and D _slow (0.105, 0.173) and moderate for f and ADC (0.461, 0.418). ANOVA showed a strong inverse association between D _fast and liver fibrosis grade (p = 0.001). A weak inverse association was seen between ADC and hepatic steatosis (p = 0.059). Multivariate general linear model revealed that the only significant association between IVIM parameters and pathological features was between D _fast and fibrosis. On ROC curve analysis, D _fast < 23.4 × 10^-3 mm²/s had a sensitivity of 82.8% and a specificity of 64.3% in predicting high-grade fibrosis.

CONCLUSION

D _fast has the strongest association with hepatic fibrosis but has weak interobserver correlation. IVIM parameters were not significantly associated with hepatic inflammation or steatosis.

Comparison of arterial input functions measured from ultra-fast dynamic contrast enhanced MRI and dynamic contrast enhanced computed tomography in prostate cancer patients

The purpose of this study was to evaluate the accuracy of arterial input functions (AIFs) measured from dynamic contrast enhanced (DCE) MRI following a low dose of contrast media injection. The AIFs measured from DCE computed tomography (CT) were used as 'gold standard'. A total of twenty patients received CT and MRI scans on the same day. Patients received 120 ml Iohexol in DCE-CT and a low dose of (0.015 mM kg^-1) of gadobenate dimeglumine in DCE-MRI. The AIFs were measured in the iliac artery and normalized to the CT and MRI contrast agent doses. To correct for different temporal resolution and sampling periods of CT and MRI, an empirical mathematical model (EMM) was used to fit the AIFs first. Then numerical AIFs (AIF_CT and AIF_MRI) were calculated based on fitting parameters. The AIF_MRI was convolved with a 'contrast agent injection' function ([Formula: see text]) to correct for the difference between MRI and CT contrast agent injection times (~1.5 s versus 30 s). The results show that the EMMs accurately fitted AIFs measured from CT and MRI. There was no significant difference (p  >  0.05) between the maximum peak amplitude of AIFs from CT (22.1  ±  4.1 mM/dose) and MRI after convolution (22.3  ±  5.2 mM/dose). The shapes of the AIF_CT and [Formula: see text] were very similar. Our results demonstrated that AIFs can be accurately measured by MRI following low dose contrast agent injection.

Assessment of renal function using intravoxel incoherent motion diffusion-weighted imaging and dynamic contrast-enhanced MRI

PURPOSE

To assess the correlation between each of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) metrics in renal parenchyma with renal function, in a cohort of patients with chronic liver disease.

MATERIALS AND METHODS

Thirty patients with liver disease underwent abdominal MRI at 1.5T, including a coronal respiratory-triggered IVIM-DWI sequence and a coronal 3D FLASH DCE-MRI acquisition. Diffusion signals in the renal cortex and medulla were fitted to the IVIM model to estimate the diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (PF). The apparent diffusion coefficient (ADC) was calculated using all b-values. The glomerular filtration rate (GFR), cortical and medullary renal plasma flow (RPF), mean transit times (MTT) of vascular and tubular compartments and the whole kidney, were calculated from DCE-MRI data by fitting to a three-compartment model. The estimated GFR (eGFR) was calculated from serum creatinine measured 30 ± 27 days of MRI.

RESULTS

ADC, PF, and RPF were significantly higher in renal cortex vs. medulla (P < 10(-5) ). DCE-MRI GFR significantly correlated with, but underestimated, eGFR (Spearman's r/P = 0.49/0.01). IVIM-DWI parameters were not significantly correlated with eGFR. DCE-MRI GFR correlated weakly with D (cortex, r/P = 0.3/0.03; medulla r/P = 0.27/0.05) and ADC (cortex r/P = 0.28/0.04; medulla r/P = 0.34/0.01). Weak correlations were observed for pooled cortical and medullar RPF with PF (r/P = 0.32/10(-3) ) and with ADC (r/P = 0.29/0.0025). Significant negative correlations were observed for vascular MTT with cortical D* (r/P = -0.38/0.004) and D*×PF (r/P = -0.34/0.01).

CONCLUSION

The weak correlations between renal IVIM and DCE-MRI perfusion parameters imply that these functional measures could be complementary. J. Magn. Reson. Imaging 2016;44:317-326.

Assessment of repeatability and treatment response in early phase clinical trials using DCE-MRI: comparison of parametric analysis using MR- and CT-derived arterial input functions

OBJECTIVES

Pharmacokinetic (PK) modelling of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data requires a reliable measure of the arterial input function (AIF) to robustly characterise tumour vascular properties. This study compared repeatability and treatment-response effects of DCE-MRI-derived PK parameters using a population-averaged AIF and three patient-specific AIFs derived from pre-bolus MRI, DCE-MRI and dynamic contrast computed tomography (DC-CT) data.

METHODS

The four approaches were compared in 13 patients with abdominal metastases. Baseline repeatability [Bland-Altman statistics; coefficient of variation (CoV)], cohort percentage change and p value (paired t test) and number of patients with significant DCE-MRI parameter change post-treatment (limits of agreement) were assessed.

RESULTS

Individual AIFs were obtained for all 13 patients with pre-bolus MRI and DC-CT-derived AIFs, but only 10/13 patients had AIFs measurable from DCE-MRI data. The best CoV (7.5 %) of the transfer coefficient between blood plasma and extravascular extracellular space (K (trans)) was obtained using a population-averaged AIF. All four AIF methods detected significant treatment changes: the most significant was the DC-CT-derived AIF. The population-based AIF was similar to or better than the pre-bolus and DCE-MRI-derived AIFs.

CONCLUSIONS

A population-based AIF is the recommended approach for measuring cohort and individual effects since it has the best repeatability and none of the PK parameters derived using measured AIFs demonstrated an improvement in treatment sensitivity.

KEY POINTS

• Pharmacokinetic modelling of DCE-MRI data requires a reliable measure of AIF. • Individual MRI-DCE-derived AIFs cannot reliably be extracted from patients. • All four AIF methods detected significant K (trans) changes after treatment. • A population-based AIF can be recommended for measuring cohort treatment responses in trials.