Estimation of contrast agent bolus arrival delays for improved reproducibility of liver DCE MRI

Unified Bayesian network for uncertainty quantification of physiological parameters in dynamic contrast enhanced (DCE) MRI of the liver

Objective. Physiological parameter estimation is affected by intrinsic ambiguity in the data such as noise and model inaccuracies. The aim of this work is to provide a deep learning framework for accurate parameter and uncertainty estimates for DCE-MRI in the liver.Approach. Concentration time curves are simulated to train a Bayesian neural network (BNN). Training of the BNN involves minimization of a loss function that jointly minimizes the aleatoric and epistemic uncertainties. Uncertainty estimation is evaluated for different noise levels and for different out of distribution (OD) cases, i.e. where the data during inference differs strongly to the data during training. The accuracy of parameter estimates are compared to a nonlinear least squares (NLLS) fitting in numerical simulations andin vivodata of a patient suffering from hepatic tumor lesions.Main results. BNN achieved lower root-mean-squared-errors (RMSE) than the NLLS for the simulated data. RMSE of BNN was on overage of all noise levels lower by 33% ± 1.9% forktrans, 22% ± 6% forveand 89% ± 5% forvpthan the NLLS. The aleatoric uncertainties of the parameters increased with increasing noise level, whereas the epistemic uncertainty increased when a BNN was evaluated with OD data. For thein vivodata, more robust parameter estimations were obtained by the BNN than the NLLS fit. In addition, the differences between estimated parameters for healthy and tumor regions-of-interest were significant (p< 0.0001).Significance. The proposed framework allowed for accurate parameter estimates for quantitative DCE-MRI. In addition, the BNN provided uncertainty estimates which highlighted cases of high noise and in which the training data did not match the data during inference. This is important for clinical application because it would indicate cases in which the trained model is inadequate and additional training with an adapted training data set is required.

Phase 0 Study of Vandetanib-Eluting Radiopaque Embolics as a Preoperative Embolization Treatment in Patients with Resectable Liver Malignancies

PURPOSE

To assess the safety and tolerability of a vandetanib-eluting radiopaque embolic (BTG-002814) for transarterial chemoembolization (TACE) in patients with resectable liver malignancies.

MATERIALS AND METHODS

The VEROnA clinical trial was a first-in-human, phase 0, single-arm, window-of-opportunity study. Eligible patients were aged ≥18 years and had resectable hepatocellular carcinoma (HCC) (Child-Pugh A) or metastatic colorectal cancer (mCRC). Patients received 1 mL of BTG-002814 transarterially (containing 100 mg of vandetanib) 7-21 days prior to surgery. The primary objectives were to establish the safety and tolerability of BTG-002814 and determine the concentrations of vandetanib and the N-desmethyl vandetanib metabolite in the plasma and resected liver after treatment. Biomarker studies included circulating proangiogenic factors, perfusion computed tomography, and dynamic contrast-enhanced magnetic resonance imaging.

RESULTS

Eight patients were enrolled: 2 with HCC and 6 with mCRC. There was 1 grade 3 adverse event (AE) before surgery and 18 after surgery; 6 AEs were deemed to be related to BTG-002814. Surgical resection was not delayed. Vandetanib was present in the plasma of all patients 12 days after treatment, with a mean maximum concentration of 24.3 ng/mL (standard deviation ± 13.94 ng/mL), and in resected liver tissue up to 32 days after treatment (441-404,000 ng/g). The median percentage of tumor necrosis was 92.5% (range, 5%-100%). There were no significant changes in perfusion imaging parameters after TACE.

CONCLUSIONS

BTG-002814 has an acceptable safety profile in patients before surgery. The presence of vandetanib in the tumor specimens up to 32 days after treatment suggests sustained anticancer activity, while the low vandetanib levels in the plasma suggest minimal release into the systemic circulation. Further evaluation of this TACE combination is warranted in dose-finding and efficacy studies.

Quantitative transport mapping (QTM) for differentiating benign and malignant breast lesion: Comparison with traditional kinetics modeling and semi-quantitative enhancement curve characteristics

PURPOSE

To test the feasibility of using quantitative transport mapping (QTM) method, which is based on the inversion of transport equation using spatial deconvolution without any arterial input function, for automatically postprocessing dynamic contrast enhanced MRI (DCE-MRI) to differentiate malignant and benign breast tumors.

MATERIALS AND METHODS

Breast DCE-MRI data with biopsy confirmed malignant (n = 13) and benign tumors (n = 13) was used to assess QTM velocity (|u|) and diffusion coefficient (D), volume transfer constant (K^trans), volume fraction of extravascular extracellular space (V_e) from kinetics method, and traditional enhancement curve characteristics (ECC: amplitude A, wash-in rate α, wash-out rate β). A Mann-Whitney U test and receiver operating characteristic curve (ROC) analysis were performed to assess the diagnostic performance of these parameters for distinguishing between benign and malignant tumors.

RESULTS

Between malignant and benign tumors, there was a significant difference in |u| and K^trans, (p = 0.0066, 0.0274, respectively), but not in D, V_e, A, α and β (p = 0.1119, 0.2382, 0.4418,0.2592 and 0.9591, respectively). ROC area-under-the-curve was 0.82, 0.75 (95% confidence level 0.60-0.95, 0.51-0.90) for |u| and K^trans, respectively.

CONCLUSION

QTM postprocesses DCE-MRI automatically through deconvolution in space and time to solve the inverse problem of the transport equation. Comparing with traditional kinetics method and ECC, QTM method showed better diagnostic accuracy in differentiating benign from malignant breast tumors in this study.

VEROnA Protocol: A Pilot, Open-Label, Single-Arm, Phase 0, Window-of-Opportunity Study of Vandetanib-Eluting Radiopaque Embolic Beads (BTG-002814) in Patients With Resectable Liver Malignancies

BACKGROUND

Transarterial chemoembolization (TACE) is the current standard of care for patients with intermediate-stage hepatocellular carcinoma (HCC) and is also a treatment option for patients with liver metastases from colorectal cancer. However, TACE is not a curative treatment, and tumor progression occurs in more than half of the patients treated. Despite advances and technical refinements of TACE, including the introduction of drug-eluting beads-TACE, the clinical efficacy of TACE has not been optimized, and improved arterial therapies are required.

OBJECTIVE

The primary objectives of the VEROnA study are to evaluate the safety and tolerability of vandetanib-eluting radiopaque embolic beads (BTG-002814) in patients with resectable liver malignancies and to determine concentrations of vandetanib and the N-desmethyl metabolite in plasma and resected liver following treatment with BTG-002814.

METHODS

The VEROnA study is a first-in-human, open-label, single-arm, phase 0, window-of-opportunity study of BTG-002814 (containing 100 mg vandetanib) delivered transarterially, 7 to 21 days before surgery in patients with resectable liver malignancies. Eligible patients have a diagnosis of colorectal liver metastases, or HCC (Childs Pugh A), diagnosed histologically or radiologically, and are candidates for liver surgery. All patients are followed up for 28 days following surgery. Secondary objectives of this study are to evaluate the anatomical distribution of BTG-002814 on noncontrast-enhanced imaging, to evaluate histopathological features in the surgical specimen, and to assess changes in blood flow on dynamic contrast-enhanced magnetic resonance imaging following treatment with BTG-002814. Exploratory objectives of this study are to study blood biomarkers with the potential to identify patients likely to respond to treatment and to correlate the distribution of BTG-002814 on imaging with pathology by 3-dimensional modeling.

RESULTS

Enrollment for the study was completed in February 2019. Results of a planned interim analysis were reviewed by a safety committee after the first 3 patients completed follow-up. The recommendation of the committee was to continue the study without any changes to the dose or trial design, as there were no significant unexpected toxicities related to BTG-002814.

CONCLUSIONS

The VEROnA study is studying the feasibility of administering BTG-002814 to optimize the use of this novel technology as liver-directed therapy for patients with primary and secondary liver cancer.

TRIAL REGISTRATION

ClinicalTrial.gov NCT03291379; https://clinicaltrials.gov/ct2/show/NCT03291379.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/13696.

Selection of Fitting Model and Arterial Input Function for Repeatability in Dynamic Contrast-Enhanced Prostate MRI

RATIONALE AND OBJECTIVES

Analysis of dynamic contrast-enhanced (DCE) magnetic resonance imaging is notable for the variability of calculated parameters. The purpose of this study was to evaluate the level of measurement variability and error/variability due to modeling in DCE magnetic resonance imaging parameters.

MATERIALS AND METHODS

Two prostate DCE scans were performed on 11 treatment-naïve patients with suspected or confirmed prostate peripheral zone cancer within an interval of less than two weeks. Tumor-suspicious and normal-appearing regions of interest (ROI) in the prostate peripheral zone were segmented. Different Tofts-Kety based models and different arterial input functions, with and without bolus arrival time (BAT) correction, were used to extract pharmacokinetic parameters. The percent repeatability coefficient (%RC) of fitted model parameters K_trans, v_e, and k_ep was calculated. Paired t-tests comparing parameters in tumor-suspicious ROIs and in normal-appearing tissue evaluated each parameter's sensitivity to pathology.

RESULTS

Although goodness-of-fit criteria favored the four-parameter extended Tofts-Kety model with the BAT correction included, the simplest two-parameter Tofts-Kety model overall yielded the best repeatability scores. The best %RC in the tumor-suspicious ROI was 63% for k_ep, 28% for v_e, and 83% for K_trans . The best p values for discrimination between tissues were p <10^-5 for k_ep and K_trans, and p = 0.11 for v_e. Addition of the BAT correction to the models did not improve repeatability.

CONCLUSION

The parameter k_ep, using an arterial input functions directly measured from blood signals, was more repeatable than K_trans. Both K_trans and k_ep values were highly discriminatory between healthy and diseased tissues in all cases. The parameter v_e had high repeatability but could not distinguish the two tissue types.

A compact solution for estimation of physiological parameters from ultrafast prostate dynamic contrast enhanced MRI

The Tofts pharmacokinetic model requires multiple calculations for analysis of dynamic contrast enhanced (DCE) MRI. In addition, the Tofts model may not be appropriate for the prostate. This can result in error propagation that reduces the accuracy of pharmacokinetic measurements. In this study, we present a compact solution allowing estimation of physiological parameters K ^trans and v _e from ultrafast DCE acquisitions, without fitting DCE-MRI data to the standard Tofts pharmacokinetic model. Since the standard Tofts model can be simplified to the Patlak model at early times when contrast efflux from the extravascular extracellular space back to plasma is negligible, K ^trans can be solved explicitly for a specific time. Further, v _e can be estimated directly from the late steady-state signal using the derivative form of Tofts model. Ultrafast DCE-MRI data were acquired from 18 prostate cancer patients on a Philips Achieva 3T-TX scanner. Regions-of-interest (ROIs) for prostate cancer, normal tissue, gluteal muscle, and iliac artery were manually traced. The contrast media concentration as function of time was calculated over each ROI using gradient echo signal equation with pre-contrast tissue T1 values, and using the 'reference tissue' model with a linear approximation. There was strong correlation (r  =  0.88-0.91, p   <  0.0001) between K ^trans extracted from the Tofts model and K ^trans estimated from the compact solution for prostate cancer and normal tissue. Additionally, there was moderate correlation (r  =  0.65-0.73, p   <  0.0001) between extracted versus estimated v _e. Bland-Altman analysis showed moderate to good agreement between physiological parameters extracted from the Tofts model and those estimated from the compact solution with absolute bias less than 0.20 min^-1 and 0.10 for K ^trans and v _e, respectively. The compact solution may decrease systematic errors and error propagation, and could increase the efficiency of clinical workflow. The compact solution requires high temporal resolution DCE-MRI due to the need to adequately sample the early phase of contrast media uptake.

Realistic 4D MRI abdominal phantom for the evaluation and comparison of acquisition and reconstruction techniques

PURPOSE

This work presents a 4D numerical abdominal phantom, which includes T₁ and T₂ relaxation times, proton density fat fraction, perfusion, and diffusion, as well as respiratory motion for the evaluation and comparison of acquisition and reconstruction techniques.

METHODS

The 3D anatomical mesh models were non-rigidly scaled and shifted by respiratory motion derived from an in vivo scan. A time series of voxelized 3D abdominal phantom images were obtained with contrast determined by the tissue properties and pulse sequence parameters. Two example simulations: (1) 3D T₁ mapping under breath-hold and free-breathing acquisition conditions and (2) two different reconstruction techniques for accelerated 3D dynamic contrast-enhanced MRI, are presented. The source codes can be found at https://github.com/SeiberlichLab/Abdominal_MR_Phantom.

RESULTS

The proposed 4D abdominal phantom can successfully simulate images and MRI data with nonrigid respiratory motion and specific contrast settings and data sampling schemes. In example 1, the use of a numerical 4D abdominal phantom was demonstrated to aid in the comparison between different approaches for volumetric T₁ mapping. In example 2, the average arterial fraction over the healthy hepatic parenchyma as calculated with spiral generalized autocalibrating partial parallel acquisition was closer to that from the fully sampled data than the arterial fraction from conjugate gradient sensitivity encoding, although both are elevated compared to the gold-standard reference.

CONCLUSION

This realistic abdominal MR phantom can be used to simulate different pulse sequences and data sampling schemes for the comparison of acquisition and reconstruction methods under controlled conditions that are impossible or prohibitively difficult to perform in vivo.

Vastly accelerated linear least-squares fitting with numerical optimization for dual-input delay-compensated quantitative liver perfusion mapping

PURPOSE

To propose an efficient algorithm to perform dual input compartment modeling for generating perfusion maps in the liver.

METHODS

We implemented whole field-of-view linear least squares (LLS) to fit a delay-compensated dual-input single-compartment model to very high temporal resolution (four frames per second) contrast-enhanced 3D liver data, to calculate kinetic parameter maps. Using simulated data and experimental data in healthy subjects and patients, whole-field LLS was compared with the conventional voxel-wise nonlinear least-squares (NLLS) approach in terms of accuracy, performance, and computation time.

RESULTS

Simulations showed good agreement between LLS and NLLS for a range of kinetic parameters. The whole-field LLS method allowed generating liver perfusion maps approximately 160-fold faster than voxel-wise NLLS, while obtaining similar perfusion parameters.

CONCLUSIONS

Delay-compensated dual-input liver perfusion analysis using whole-field LLS allows generating perfusion maps with a considerable speedup compared with conventional voxel-wise NLLS fitting. Magn Reson Med 79:2415-2421, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Improved hepatic arterial fraction estimation using cardiac output correction of arterial input functions for liver DCE MRI

Liver dynamic contrast enhanced (DCE) MRI pharmacokinetic modelling could be useful in the assessment of diffuse liver disease and focal liver lesions, but is compromised by errors in arterial input function (AIF) sampling. In this study, we apply cardiac output correction to arterial input functions (AIFs) for liver DCE MRI and investigate the effect on dual-input single compartment hepatic perfusion parameter estimation and reproducibility.

Thirteen healthy volunteers (28.7  ±  1.94 years, seven males) underwent liver DCE MRI and cardiac output measurement using aortic root phase contrast MRI (PCMRI), with reproducibility (n  =  9) measured at 7 d. Cardiac output AIF correction was undertaken by constraining the first pass AIF enhancement curve using the indicator-dilution principle. Hepatic perfusion parameters with and without cardiac output AIF correction were compared and 7 d reproducibility assessed.

Differences between cardiac output corrected and uncorrected liver DCE MRI portal venous (PV) perfusion (p  =  0.066), total liver blood flow (TLBF) (p  =  0.101), hepatic arterial (HA) fraction (p  =  0.895), mean transit time (MTT) (p  =  0.646), distribution volume (DV) (p  =  0.890) were not significantly different. Seven day corrected HA fraction reproducibility was improved (mean difference 0.3%, Bland–Altman 95% limits-of-agreement (BA95%LoA)  ±27.9%, coefficient of variation (CoV) 61.4% versus 9.3%, ±35.5%, 81.7% respectively without correction). Seven day uncorrected PV perfusion was also improved (mean difference 9.3 ml min⁻¹/100 g, BA95%LoA  ±506.1 ml min⁻¹/100 g, CoV 64.1% versus 0.9 ml min⁻¹/100 g, ±562.8 ml min⁻¹/100 g, 65.1% respectively with correction) as was uncorrected TLBF (mean difference 43.8 ml min⁻¹/100 g, BA95%LoA  ±586.7 ml min⁻¹/ 100 g, CoV 58.3% versus 13.3 ml min⁻¹/100 g, ±661.5 ml min⁻¹/100 g, 60.9% respectively with correction). Reproducibility of uncorrected MTT was similar (uncorrected mean difference 2.4 s, BA95%LoA  ±26.7 s, CoV 60.8% uncorrected versus 3.7 s, ±27.8 s, 62.0% respectively with correction), as was and DV (uncorrected mean difference 14.1%, BA95%LoA  ±48.2%, CoV 24.7% versus 10.3%, ±46.0%, 23.9% respectively with correction).

Cardiac output AIF correction does not significantly affect the estimation of hepatic perfusion parameters but demonstrates improvements in normal volunteer 7 d HA fraction reproducibility, but deterioration in PV perfusion and TLBF reproducibility. Improved HA fraction reproducibility maybe important as arterialisation of liver perfusion is increased in chronic liver disease and within malignant liver lesions.