Dynamic contrast-enhanced MRI of neuroendocrine hepatic metastases: A feasibility study using a dual-input two-compartment model

Perfusion MR Imaging of Liver: Principles and Clinical Applications

Perfusion imaging techniques provide quantitative characterization of tissue microvasculature. Perfusion MR of liver is particularly challenging because of dual afferent flow, need for large organ high-resolution coverage, and significant movement with respiration. The most common MR technique used for quantifying liver perfusion is dynamic contrast-enhanced MR imaging. Here, the authors describe the various perfusion MR models of the liver, the basic concepts behind implementing a perfusion acquisition, and clinical results that have been obtained using these models.

A model selection framework to quantify microvascular liver function in gadoxetate-enhanced MRI: Application to healthy liver, diseased tissue, and hepatocellular carcinoma

PURPOSE

We introduce a novel, generalized tracer kinetic model selection framework to quantify microvascular characteristics of liver and tumor tissue in gadoxetate-enhanced dynamic contrast-enhanced MRI (DCE-MRI).

METHODS

Our framework includes a hierarchy of nested models, from which physiological parameters are derived in 2 regimes, corresponding to the active transport and free diffusion of gadoxetate. We use simulations to show the sensitivity of model selection and parameter estimation to temporal resolution, time-series duration, and noise. We apply the framework in 8 healthy volunteers (time-series duration up to 24 minutes) and 10 patients with hepatocellular carcinoma (6 minutes).

RESULTS

The active transport regime is preferred in 98.6% of voxels in volunteers, 82.1% of patients' non-tumorous liver, and 32.2% of tumor voxels. Interpatient variations correspond to known co-morbidities. Simulations suggest both datasets have sufficient temporal resolution and signal-to-noise ratio, while patient data would be improved by using a time-series duration of at least 12 minutes.

CONCLUSIONS

In patient data, gadoxetate exhibits different kinetics: (a) between liver and tumor regions and (b) within regions due to liver disease and/or tumor heterogeneity. Our generalized framework selects a physiological interpretation at each voxel, without preselecting a model for each region or duplicating time-consuming optimizations for models with identical functional forms.

An automatic framework for evaluating the vascular permeability of bone metastases from prostate cancer

Objectives.Vascular permeability can reflect tumorigenesis and metastasis. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can assess microvascular permeability by pharmacokinetic parameter estimation. Most estimation methods require manually selected arterial input function (AIF) or reference regions. However, the result will be unstable due to the annotation, which relies on personal experience. In this study, we propose an automatic framework for evaluating vascular permeability of bone metastases from prostate cancer without selecting AIF.Materials and methods.This retrospective study comprised of 15 prostate cancer patients with bone metastases. Based on clinical consensus for three typical DCE-MRI curve patterns, three characteristic curves as regularization constraints were introduced to the extended Tofts model (ETM) using clustering strategy, and the clustering-based blind identification of multichannel (CBM) framework was then proposed for pharmacokinetic parameter estimation. With automatic segmentation of the whole bone area, we obtained the estimation of the pharmacokinetic parameters in the bone area and quantified for bone metastases. Two experienced radiologists compared the CBM estimations with the diagnostic results and we compared the estimations with those of the ETM in bone metastasis regions to evaluate the feasibility of the CBM framework.Results.The higher signal regions ofK^transandK_epindicated the metastasis of prostate cancer, which is consistent with the cancer area marked by the radiologists. In addition, theK^transandK_epin bone metastasis regions were significantly higher than in normal bone regions (P < 0.001,P < 0.001). The consistency of estimation by using the CBM framework and conventional ETM method was confirmed by Bland-Altman analysis.Conclusion.The proposed CBM framework can provide a fully automatic and reliable quantitative estimation of vascular permeability for bone metastases in prostate cancer patients.

Quantitative magnetic resonance imaging for focal liver lesions: bridging the gap between research and clinical practice

Magnetic resonance imaging (MRI) is highly important for the detection, characterization, and follow-up of focal liver lesions. Several quantitative MRI-based methods have been proposed in addition to qualitative imaging interpretation to improve the diagnostic work-up and prognostics in patients with focal liver lesions. This includes DWI with apparent diffusion coefficient measurements, intravoxel incoherent motion, perfusion imaging, MR elastography, and radiomics. Multiple research studies have reported promising results with quantitative MRI methods in various clinical settings. Nevertheless, applications in everyday clinical practice are limited. This review describes the basic principles of quantitative MRI-based techniques and discusses the main current applications and limitations for the assessment of focal liver lesions.

Correlation of radiomic features on dynamic contrast-enhanced magnetic resonance with microvessel density in hepatocellular carcinoma based on different models

Objective

To explore the correlations of radiomic features of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) with microvessel density (MVD) in patients with hepatocellular carcinoma (HCC), based on single-input and dual-input two-compartment extended Tofts (SITET and DITET) models.

Methods

We compared the quantitative parameters of SITET and DITET models for DCE-MRI in 30 patients with HCC using paired sample t-tests. The correlations of SITET and DITET model parameters with CD31-MVD and CD34-MVD were analyzed using Pearson’s correlation analysis. A diagnostic model of CD34-MVD was established and the diagnostic abilities of models for MVD were analyzed using receiver operating characteristic curve (ROC) analysis.

Results

There were significant differences between the quantitative parameters in the two kinds of models. Compared with SITET, DITET parameters showed better correlations with CD31-MVD and CD34-MVD. The K^trans and Ve radiomics features of the DITET model showed high efficiency for predicting the level of CD34-MVD according to ROC analysis, with areas under curves of 0.83 and 0.94, respectively.

Conclusion

Compared with SITET, the DITET model provides a better indication of the microcirculation of HCC and is thus more suitable for examining patients with HCC.

Liver function quantification of patients with portal vein embolization using dynamic contrast-enhanced MRI for assessment of hepatocyte uptake and elimination

PURPOSE

We evaluated pharmacokinetic models which quantify liver function including biliary elimination based on a dynamic Gd-EOB-DTPA-enhanced magnetic resonance imaging (MRI) technique with sparse data collection feasible in clinical routine.

METHODS

Twelve patients with embolized liver segments following interventional treatment of primary liver cancer or hepatic metastasis underwent MRI. During Gd-EOB-DTPA bolus administration, a 3D dynamic gradient-echo (GRE) MRI examination was performed over approx. 28 min. Interrupted data sampling was started approx. 5 min after contrast agent administration. Different implementations of dual-inlet models were tested, namely the Euler method (DE) and convolution with residue functions (C). A simple uptake model (U) and an uptake- elimination model (UE) extended by incorporating the biliary contrast agent elimination rate (K_e) were evaluated.

RESULTS

The uptake-elimination model, calculated via the simple Euler method (UE- DE) and by convolution (UE-C), yielded similar overall estimates in terms of fitting quality and agreement with published values. The Euler method was approx. 50 times faster and yielded a mean elimination rate of K_e=1.8±1.2mL/(min·100 mL) in nonembolized liver tissue, which was significantly higher (p=8.8·10^-4) than in embolized tissue K_e=0.4±0.4 mL/(min·100 mL). Fractional hepatocyte volume v_h was not significantly higher in nonembolized tissue (52.4 ± 13.4 mL/100 mL) compared to embolized tissue (44.4 ± 26.1 mL/100 mL).

CONCLUSIONS

Interrupted late enhancement MRI data sampling in conjunction with the uptake-elimination model, deconvolved by integration of the differential rate equation and combined with the simple uptake model implemented with the Euler method (U-DE), turned out to be a stable and practical method for reliable noninvasive assessment of liver function.

Topics on quantitative liver magnetic resonance imaging

Liver magnetic resonance imaging (MRI) is subject to continuous technical innovations through advances in hardware, sequence and novel contrast agent development. In order to utilize the abilities of liver MR to its full extent and perform high-quality efficient exams, it is mandatory to use the best imaging protocol, to minimize artifacts and to select the most adequate type of contrast agent. In this article, we review the routine clinical MR techniques applied currently and some latest developments of liver imaging techniques to help radiologists and technologists to better understand how to choose and optimize liver MRI protocols that can be used in clinical practice. This article covers topics on (I) fat signal suppression; (II) diffusion weighted imaging (DWI) and intravoxel incoherent motion (IVIM) analysis; (III) dynamic contrast-enhanced (DCE) MR imaging; (IV) liver fat quantification; (V) liver iron quantification; and (VI) scan speed acceleration.

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.

Free-Breathing 3D Liver Perfusion Quantification Using a Dual-Input Two-Compartment Model

The purpose of this study is to test the feasibility of applying a dual-input two-compartment liver perfusion model to patients with different pathologies. A total of 7 healthy subjects and 11 patients with focal liver lesions, including 6 patients with metastatic adenocarcinoma and 5 with hepatocellular carcinoma (HCC), were examined. Liver perfusion values were measured from both focal liver lesions and cirrhotic tissues (from the 5 HCC patients). Compared to results from volunteer livers, significantly higher arterial fraction, fractional volume of the interstitial space, and lower permeability-surface area product were observed for metastatic lesions, and significantly higher arterial fraction and lower vascular transit time were observed for HCCs (P < 0.05). Significantly lower arterial fraction and higher vascular transit time, fractional volume of the vascular space, and fractional volume of the interstitial space were observed for metastases in comparison to HCCs (P < 0.05). For cirrhotic livers, a significantly lower total perfusion, lower fractional volume of the vascular space, higher fractional volume of the interstitial space, and lower permeability-surface area product were noted in comparison to volunteer livers (P < 0.05). Our findings support the possibility of using this model with 3D free-breathing acquisitions for lesion and diffuse liver disease characterization.

Evaluation of Magnetic Resonance (MR) Biomarkers for Assessment of Response With Response Evaluation Criteria in Solid Tumors: Comparison of the Measurements of Neuroendocrine Tumor Liver Metastases (NETLM) With Various MR Sequences and at Multiple Phases of Contrast Administration

PURPOSE

Our aim was to compare the interobserver and intraobserver variability for the measurement of the size of liver metastases in patients with carcinoid tumors with various magnetic resonance (MR) series.

MATERIALS AND METHODS

In this retrospective institutional review board-approved study, 30 patients with liver metastases from a carcinoid primary had a complete MR examination of the abdomen at 1.5 T with gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid (Gd-EOB-DTPA). The complete MR examination included T1 (in-phase [IP]/out-of-phase [OOP], T2, diffusion-weighted imaging, pre-Gd-EOB-DTPA and post-Gd-EOB-DTPA 3D gradient echo (4 phases plus 20-minute hepatobiliary phase [HBP] Gd]). Four readers reviewed each series independently. The measurement for each lesion was compared to HBP-Gd images. The sensitivity for detection of each lesion was compared to HBP-Gd. Variance component analysis was used to estimate variance due to patient, lesion within patient, and reader by sequence. Linear mixed model was used to compare lesion size between sequences.

RESULTS

The HBP-Gd had the smallest interreader variability. There was no significant difference between series with respect to interreader variability. Lesion sizes measured in diffusion-weighted imaging was significantly higher. T2-weighted imaging was the closest to HBP-Gd. Lesion sizes measured with the other sequences were significantly smaller. There was significant difference in sensitivity of lesion detection of some series when compared to HBP-Gd.

CONCLUSION

The HBP-Gd series had the smallest interreader variability and is the recommended series to measure lesion size for evaluation of response to treatment.

Flow versus permeability weighting in estimating the forward volumetric transfer constant (Ktrans) obtained by DCE-MRI with contrast agents of differing molecular sizes

PURPOSE

To quantify the differential plasma flow- (F_p-) and permeability surface area product per unit mass of tissue- (PS-) weighting in forward volumetric transfer constant (K^trans) estimates by using a low molecular (Gd-DTPA) versus high molecular (Gadomer) weight contrast agent in dynamic contrast enhanced (DCE) MRI.

MATERIALS AND METHODS

DCE MRI was performed using a 7T animal scanner in 14 C57BL/6J mice syngeneic for TRAMP tumors, by administering Gd-DTPA (0.9kD) in eight mice and Gadomer (35kD) in the remainder. The acquisition time was 10min with a sampling rate of one image every 2s. Pharmacokinetic modeling was performed to obtain K^trans by using Extended Tofts model (ETM). In addition, the adiabatic approximation to the tissue homogeneity (AATH) model was employed to obtain the relative contributions of F_p and PS.

RESULTS

The K^trans values derived from DCE-MRI with Gd-DTPA showed significant correlations with both PS (r²=0.64, p=0.009) and F_p (r²=0.57, p=0.016), whereas those with Gadomer were found only significantly correlated with PS (r²=0.96, p=0.0003) but not with F_p (r²=0.34, p=0.111). A voxel-based analysis showed that K^trans approximated PS (<30% difference) in 78.3% of perfused tumor volume for Gadomer, but only 37.3% for Gd-DTPA.

CONCLUSIONS

The differential contributions of F_p and PS in estimating K^trans values vary with the molecular weight of the contrast agent used. The macromolecular contrast agent resulted in K^trans values that were much less dependent on flow. These findings support the use of macromolecular contrast agents for estimating tumor vessel permeability with DCE-MRI.

Free-breathing liver perfusion imaging using 3-dimensional through-time spiral generalized autocalibrating partially parallel acquisition acceleration

OBJECTIVES

The goal of this study was to develop free-breathing high-spatiotemporal resolution dynamic contrast-enhanced liver magnetic resonance imaging using non-Cartesian parallel imaging acceleration, and quantitative liver perfusion mapping.

MATERIALS AND METHODS

This study was approved by the local institutional review board and written informed consent was obtained from all participants. Ten healthy subjects and 5 patients were scanned on a Siemens 3-T Skyra scanner. A stack-of-spirals trajectory was undersampled in-plane with a reduction factor of 6 and reconstructed using 3-dimensional (3D) through-time non-Cartesian generalized autocalibrating partially parallel acquisition. High-resolution 3D images were acquired with a true temporal resolution of 1.6 to 1.9 seconds while the subjects were breathing freely. A dual-input single-compartment model was used to retrieve liver perfusion parameters from dynamic contrast-enhanced magnetic resonance imaging data, which were coregistered using an algorithm designed to reduce the effects of dynamic contrast changes on registration. Image quality evaluation was performed on spiral images and conventional images from 5 healthy subjects.

RESULTS

Images with a spatial resolution of 1.9 × 1.9 × 3 mm3 were obtained with whole-liver coverage. With an imaging speed of better than 2 s/vol, free-breathing scans were achieved and dynamic changes in enhancement were captured. The overall image quality of free-breathing spiral images was slightly lower than that of conventional long breath-hold Cartesian images, but it provided clinically acceptable or better image quality. The free-breathing 3D images were registered with almost no residual motion in liver tissue. After the registration, quantitative whole-liver 3D perfusion maps were obtained and the perfusion parameters are all in good agreement with the literature.

CONCLUSIONS

This high-spatiotemporal resolution free-breathing 3D liver imaging technique allows voxelwise quantification of liver perfusion.

Dynamic Contrast-Enhanced MRI Kinetic Parameters as Prognostic Biomarkers for Prediction of Survival of Patient with Advanced Hepatocellular Carcinoma: A Pilot Comparative Study

RATIONALE AND OBJECTIVES

Tracer kinetic model selection for dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data analysis influences its use as a prognostic biomarker. Our aim was to find DCE-MRI parameters that predict 1-year survival (1YS) and overall survival (OS) among patients with advanced hepatocellular carcinoma (HCC) treated with antiangiogenic monotherapy by conducting a proof-of-concept comparative study of five different kinetic models.

MATERIALS AND METHODS

Twenty patients with advanced HCC underwent DCE-MRI and subsequently received sunitinib. Pretreatment DCE-MRI data were analyzed retrospectively by using the Tofts-Kety (TK), extended TK, two compartment exchange, adiabatic approximation to the tissue homogeneity (AATH), and distributed parameter (DP) models. Arterial flow fraction (γ), arterial blood flow (BFA), permeability-surface area product (PS), fractional interstitial volume (vI), and other five parameters were calculated for each model. Individual parameters were evaluated for 1YS prediction using cross-validated Kaplan-Meier analysis, and for association with OS using univariate Cox regression analysis, with additional permutation testing.

RESULTS

For 1YS prediction, the TK model-derived γ (P = .007) and vI (P = .029) and the AATH model-derived PS (P = .005) were significant; all these parameters were lower in the high-risk group. Increase in the AATH model-derived PS and the DP model-derived BFA was associated with significant increase in OS with hazard ratios of 0.766 (P = .023) and 0.809 (P = .025), respectively.

CONCLUSIONS

The AATH model-derived PS was an effective prognostic biomarker for both 1YS and OS.

Models and methods for analyzing DCE-MRI: a review

PURPOSE

To present a review of most commonly used techniques to analyze dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), discusses their strengths and weaknesses, and outlines recent clinical applications of findings from these approaches.

METHODS

DCE-MRI allows for noninvasive quantitative analysis of contrast agent (CA) transient in soft tissues. Thus, it is an important and well-established tool to reveal microvasculature and perfusion in various clinical applications. In the last three decades, a host of nonparametric and parametric models and methods have been developed in order to quantify the CA's perfusion into tissue and estimate perfusion-related parameters (indexes) from signal- or concentration-time curves. These indexes are widely used in various clinical applications for the detection, characterization, and therapy monitoring of different diseases.

RESULTS

Promising theoretical findings and experimental results for the reviewed models and techniques in a variety of clinical applications suggest that DCE-MRI is a clinically relevant imaging modality, which can be used for early diagnosis of different diseases, such as breast and prostate cancer, renal rejection, and liver tumors.

CONCLUSIONS

Both nonparametric and parametric approaches for DCE-MRI analysis possess the ability to quantify tissue perfusion.

Water-Exchange-Modified Kinetic Parameters from Dynamic Contrast-Enhanced MRI as Prognostic Biomarkers of Survival in Advanced Hepatocellular Carcinoma Treated with Antiangiogenic Monotherapy

BACKGROUND

To find prognostic biomarkers in pretreatment dynamic contrast-enhanced MRI (DCE-MRI) water-exchange-modified (WX) kinetic parameters for advanced hepatocellular carcinoma (HCC) treated with antiangiogenic monotherapy.

METHODS

Twenty patients with advanced HCC underwent DCE-MRI and were subsequently treated with sunitinib. Pretreatment DCE-MRI data on advanced HCC were analyzed using five different WX kinetic models: the Tofts-Kety (WX-TK), extended TK (WX-ETK), two compartment exchange, adiabatic approximation to tissue homogeneity (WX-AATH), and distributed parameter (WX-DP) models. The total hepatic blood flow, arterial flow fraction (γ), arterial blood flow (BFA), portal blood flow, blood volume, mean transit time, permeability-surface area product, fractional interstitial volume (vI), extraction fraction, mean intracellular water molecule lifetime (τC), and fractional intracellular volume (vC) were calculated. After receiver operating characteristic analysis with leave-one-out cross-validation, individual parameters for each model were assessed in terms of 1-year-survival (1YS) discrimination using Kaplan-Meier analysis, and association with overall survival (OS) using univariate Cox regression analysis with permutation testing.

RESULTS

The WX-TK-model-derived γ (P = 0.022) and vI (P = 0.010), and WX-ETK-model-derived τC (P = 0.023) and vC (P = 0.042) were statistically significant prognostic biomarkers for 1YS. Increase in the WX-DP-model-derived BFA (P = 0.025) and decrease in the WX-TK, WX-ETK, WX-AATH, and WX-DP-model-derived vC (P = 0.034, P = 0.038, P = 0.028, P = 0.041, respectively) were significantly associated with an increase in OS.

CONCLUSIONS

The WX-ETK-model-derived vC was an effective prognostic biomarker for advanced HCC treated with sunitinib.

Prognostication and response assessment in liver and pancreatic tumors: The new imaging

Diffusion-weighted imaging (DWI), dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and perfusion computed tomography (CT) are technical improvements of morphologic imaging that can evaluate functional properties of hepato-bilio-pancreatic tumors during conventional MRI or CT examinations. Nevertheless, the term “functional imaging” is commonly used to describe molecular imaging techniques, as positron emission tomography (PET) CT/MRI, which still represent the most widely used methods for the evaluation of functional properties of solid neoplasms; unlike PET or single photon emission computed tomography, functional imaging techniques applied to conventional MRI/CT examinations do not require the administration of radiolabeled drugs or specific equipments. Moreover, DWI and DCE-MRI can be performed during the same session, thus providing a comprehensive “one-step” morphological and functional evaluation of hepato-bilio-pancreatic tumors. Literature data reveal that functional imaging techniques could be proposed for the evaluation of these tumors before treatment, given that they may improve staging and predict prognosis or clinical outcome. Microscopic changes within neoplastic tissues induced by treatments can be detected and quantified with functional imaging, therefore these techniques could be used also for post-treatment assessment, even at an early stage. The aim of this editorial is to describe possible applications of new functional imaging techniques apart from molecular imaging to hepatic and pancreatic tumors through a review of up-to-date literature data, with a particular emphasis on pathological correlations, prognostic stratification and post-treatment monitoring.

Perfusion imaging in liver MRI

Liver perfusion magnetic resonance (MR) imaging is currently being actively investigated as a functional imaging technique that provides physiologic information on the microcirculation and microenvironment of liver tumors and the underlying liver. It has gained importance in light of antiangiogenic therapy for hepatocellular carcinoma and colorectal liver metastases. This article explains the various model-free and model-based approaches for liver perfusion MR imaging and their relative clinical utility. Relevant published works are summarized for each approach so that the reader can understand their relative strengths and weaknesses, to make an informed choice when performing liver perfusion MR imaging studies.

MRI kinetics with volumetric analysis in correlation with hormonal receptor subtypes and histologic grade of invasive breast cancers

OBJECTIVE. The aim of this study was to assess whether computer-assisted detection-processed MRI kinetics data can provide further information on the biologic aggressiveness of breast tumors. MATERIALS AND METHODS. We identified 194 newly diagnosed invasive breast cancers presenting as masses on contrast-enhanced MRI by a HIPAA-compliant pathology database search. Computer-assisted detection-derived data for the mean and median peak signal intensity percentage increase, most suspicious kinetic curve patterns, and volumetric analysis of the different kinetic patterns by mean percentage tumor volume were compared against the different hormonal receptor (estrogen-receptor [ER], progesterone-receptor [PR], ERRB2 (HER2/neu), and triple-receptor expressivity) and histologic grade subgroups, which were used as indicators of tumor aggressiveness. RESULTS. The means and medians of the peak signal intensity percentage increase were higher in ER-negative, PR-negative, and triple-negative (all p ≤ 0.001), and grade 3 tumors (p = 0.011). Volumetric analysis showed higher mean percentage volume of rapid initial enhancement in biologically more aggressive ER-negative, PR-negative, and triple-negative tumors compared with ER-positive (64% vs 53.6%, p = 0.013), PR-positive (65.4% vs 52.5%, p = 0.001), and nontriple-negative tumors (65.3% vs 54.6%, p = 0.028), respectively. A higher mean percentage volume of rapid washout component was seen in ERRB2-positive tumors compared with ERRB2-negative tumors (27.5% vs 17.9%, p = 0.020). CONCLUSION. Peak signal intensity percentage increase and volume analysis of the different kinetic patterns of breast tumors showed correlation with hormonal receptor and histologic grade indicators of cancer aggressiveness. Computer-assisted detection-derived MRI kinetics data have the potential to further characterize the aggressiveness of an invasive cancer.

MR imaging of primary hepatic neuroendocrine neoplasm and metastatic hepatic neuroendocrine neoplasm: a comparative study

PURPOSE

To investigate MR characteristics in differentiating primary hepatic neuroendocrine neoplasm (PHNEN) from metastatic hepatic neuroendocrine neoplasm (MHNEN).

MATERIALS AND METHODS

Thirty-nine patients with histopathologically proven liver neuroendocrine neoplasm were retrospectively analyzed. The morphological and MR signal features on T1, T2-weighted, dynamic-enhanced, and diffusion-weighted imaging were evaluated and compared between the PHNEN group (n = 12) and the MHNEN group (n = 27).

RESULTS

The tumor size (P = 0.0084), number (P = 0.017), distribution (P = 0.000), contour (P = 0.041), the presence of capsule-like enhancement (P = 0.034), tumor homogeneity (P = 0.018) and the apparent diffusion coefficient (ADC) values (P = 0.024) were different between PHNENs and MHNENs. Large, solitary or massive-growing nodules with lobulated or irregular contour, capsule-like enhancement, heterogeneous signals or lower ADC values supported the diagnosis of PHNEN compared with MHNEN. ROC analysis demonstrated an area under the curve of 0.746, when the optimal cutoff value of 1.049 × 10(-3) mm(2)/s was used, a sensitivity of 63.0 % (95 % CI, 44.2-79.4 %), a specitivity of 80.0 % (95 % CI, 50.1-96.4 %), a positive predictive value of 89.5 % (95 % CI, 70.9-98.2 %), and a negative predictive value of 44.4 % (95 % CI, 23.4-67.0 %) can be achieved.

CONCLUSIONS

MRI may provide valuable information for the diagnosis and differential diagnosis of PHNENs and MHNENs.

Feasibility of Single-Input Tracer Kinetic Modeling with Continuous-Time Formalism in Liver 4-Phase Dynamic Contrast-Enhanced CT

The modeling of tracer kinetics with use of low-temporal-resolution data is of central importance for patient dose reduction in dynamic contrast-enhanced CT (DCE-CT) study. Tracer kinetic models of the liver vary according to the physiologic assumptions imposed on the model, and they can substantially differ in the ways how the input for blood supply and tissue compartments are modeled. In this study, single-input flow-limited (FL), Tofts-Kety (TK), extended TK (ETK), Hayton-Brady (HB), two compartment exchange (2CX), and adiabatic approximation to the tissue homogeneity (AATH) models were applied to the analysis of liver 4-phase DCE-CT data with fully continuous-time parameter formulation, including the bolus arrival time. The bolus arrival time for the 2CX and AATH models was described by modifying the vascular transport operator theory. Initial results indicate that single-input tracer kinetic modeling is feasible for distinguishing between hepatocellular carcinoma and normal liver parenchyma.

Evaluation of neuroendocrine liver metastases: a comparison of dynamic contrast-enhanced magnetic resonance imaging and positron emission tomography/computed tomography

OBJECTIVES

The objective of this study was to evaluate the correlation between dynamic gadoxetic acid-enhanced magnetic resonance imaging parameters and specific uptake values (SUVs) derived from ¹⁸fluorodeoxyglucose (¹⁸F-FDG) and ⁶⁸Ga-DOTA-Tyr(3)-octreotate (⁶⁸Ga-DOTATATE) positron emission tomography/computed tomography (PET/CT) in patients with liver metastases of neuroendocrine neoplasms.

METHODS

A total of 42 patients with hepatic metastases of neuroendocrine neoplasms were prospectively enrolled and underwent both dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and PET/CT, using either ¹⁸F-FDG or ⁶⁸Ga-DOTATATE as tracer. The DCE-MRI was performed at 3 T with gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid acquiring 48 slices every 2.2 seconds for 5 minutes. Three regions of interest (ROIs) representing the liver background and up to 3 ROIs representing metastatic liver tissue were coregistered in the PET/CT and in the DCE-MRI data sets. For each patient, a dedicated dual-inlet, 2-compartment uptake model was fitted to the enhancement curves of DCE-MRI ROIs and perfusion parameters were calculated. Lesion-to-background ratios of SUVs were correlated with corresponding lesion-to-background ratios of the perfusion parameters arterial plasma flow, venous plasma flow, total plasma flow, extracellular mean transit time, extracellular volume, arterial flow fraction, intracellular uptake rate, and hepatic uptake fraction using the Spearman coefficient.

RESULTS

Whereas the lesion-to-background ratios of arterial plasma flow and arterial flow fraction of liver metastases correlated negatively with the lesion-to-background ratios of SUV(mean) derived from ⁶⁸Ga-DOTATATE PET/CT (r = -0.54, P < 0.001; r = -0.39, P < 0.001, respectively), they correlated positively with the lesion-to-background ratios of SUV(mean) derived from ¹⁸F-FDG-PET/CT (r = 0.51, P < 0.05; r = 0.68, P < 0.01, respectively). The lesion-to-background ratios of the DCE-MRI parameters extracellular mean transit time and extracellular volume correlated very weakly with the lesion-to-background ratios of SUV(mean) from ⁶⁸Ga-DOTATATE PET/CT, whereas venous plasma flow, total plasma flow, hepatic uptake fraction, and intracellular uptake rate showed no correlation between DCE-MRI and PET/CT.

CONCLUSIONS

Both ⁶⁸Ga-DOTATATE and ¹⁸fluorodeoxyglucose PET/CT partially correlate with MRI perfusion parameters from the dual-inlet, 2-compartment uptake model. The results indicate that the paired imaging methods deliver complementary functional information.

Semi-quantitative parameter analysis of DCE-MRI revisited: monte-carlo simulation, clinical comparisons, and clinical validation of measurement errors in patients with type 2 neurofibromatosis

PURPOSE

To compare semi-quantitative (SQ) and pharmacokinetic (PK) parameters for analysis of dynamic contrast enhanced MR data (DCE-MRI) and investigate error-propagation in SQ parameters.

METHODS

Clinical data was collected from five patients with type 2-neurofibromatosis (NF2) receiving anti-angiogenic therapy for rapidly growing vestibular schwannoma (VS). There were 7 VS and 5 meningiomas. Patients were scanned prior to therapy and at days 3 and 90 of treatment. Data was collected using a dual injection technique to permit direct comparison of SQ and PK parameters. Monte Carlo modeling was performed to assess potential measurement errors in SQ parameters in persistent, washout, and weakly enhancing tissues. The simulation predictions for five semi-quantitative parameters were tested using the clinical DCE-MRI data.

RESULTS

In VS, SQ parameters and Ktrans showed close correlation and demonstrated similar therapy induced reductions. In meningioma, only the denoised Signal Enhancement Ratio (Rse1/se2(DN)) showed a significant therapy induced reduction (p<0.05). Simulation demonstrated: 1) Precision of SQ metrics normalized to the pre-contrast-baseline values (MSErel and ∑MSErel) is improved by use of an averaged value from multiple baseline scans; 2) signal enhancement ratio Rmse1/mse2 shows considerable susceptibility to noise; 3) removal of outlier values to produce a new parameter, Rmse1/mse2(DN), improves precision and sensitivity to therapy induced changes. Direct comparison of in-vivo analysis with Monte Carlo simulation supported the simulation predicted error distributions of semi-quantitative metrics.

CONCLUSION

PK and SQ parameters showed similar sensitivity to anti-angiogenic therapy induced changes in VS. Modeling studies confirmed the benefits of averaging baseline signal from multiple images for normalized SQ metrics and demonstrated poor noise tolerance in the widely used signal enhancement ratio, which is corrected by removal of outlier values.

Classic models for dynamic contrast-enhanced MRI

Dynamic contrast-enhanced MRI (DCE-MRI) is a functional MRI method where T1 -weighted MR images are acquired dynamically after bolus injection of a contrast agent. The data can be interpreted in terms of physiological tissue characteristics by applying the principles of tracer-kinetic modelling. In the brain, DCE-MRI enables measurement of cerebral blood flow (CBF), cerebral blood volume (CBV), blood-brain barrier (BBB) permeability-surface area product (PS) and the volume of the interstitium (ve ). These parameters can be combined to form others such as the volume-transfer constant K(trans) , the extraction fraction E and the contrast-agent mean transit times through the intra- and extravascular spaces. A first generation of tracer-kinetic models for DCE-MRI was developed in the early 1990s and has become a standard in many applications. Subsequent improvements in DCE-MRI data quality have driven the development of a second generation of more complex models. They are increasingly used, but it is not always clear how they relate to the models of the first generation or to the model-free deconvolution methods for tissues with intact BBB. This lack of understanding is leading to increasing confusion on when to use which model and how to interpret the parameters. The purpose of this review is to clarify the relation between models of the first and second generations and between model-based and model-free methods. All quantities are defined using a generic terminology to ensure the widest possible scope and to reveal the link between applications in the brain and in other organs.

Modeling DCE-MRI at low temporal resolution: a case study on rheumatoid arthritis

PURPOSE

To identify the optimal tracer-kinetic modeling strategy for dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data acquired at low temporal resolution.

MATERIALS AND METHODS

DCE-MRI was performed on 13 patients with rheumatoid arthritis of the hand before and after anti-tumor necrosis factor alpha (TNFα) therapy, using a 3D sequence with a temporal resolution of 13 seconds, imaging for 4 minutes postcontrast injection. Concentration-time curves were extracted from regions of interest (ROIs) in enhancing synovium and fitted to the 3-parameter modified Tofts model (MT) and the 4-parameter two-compartment exchange model (2CXM). To assist the interpretation of the data, the same analysis was applied to simulated data with similar characteristics.

RESULTS

Both models fitted the data closely, and showed similar therapy effects. The MT plasma volume was significantly lower than with 2CXM, but the differences in permeability and interstitial volume were not significant. 2CXM was less precise than MT, with larger standard deviations relative to the mean in most parameters. The additional perfusion parameter determined with 2CXM did not provide a statistically significant trend due to low precision.

CONCLUSION

The standard MT model is the optimal modeling strategy at low temporal resolution. Advanced models improve the accuracy and generate an additional parameter, but these benefits are offset by low precision.

Tracer-kinetic modeling of dynamic contrast-enhanced MRI and CT: a primer

Dynamic contrast-enhanced computed tomography (DCE-CT) and magnetic resonance imaging (DCE-MRI) are functional imaging techniques. They aim to characterise the microcirculation by applying the principles of tracer-kinetic analysis to concentration-time curves measured in individual image pixels. In this paper, we review the basic principles of DCE-MRI and DCE-CT, with a specific emphasis on the use of tracer-kinetic modeling. The aim is to provide an introduction to the field for a broader audience of pharmacokinetic modelers. In a first part, we first review the key aspects of data acquisition in DCE-CT and DCE-MRI, including a review of basic measurement strategies, a discussion on the relation between signal and concentration, and the problem of measuring reference data in arterial blood. In a second part, we define the four main parameters that can be measured with these techniques and review the most common tracer-kinetic models that are used in this field. We first discuss the models for the capillary bed and then define the most general four-parameter models used today: the two-compartment exchange model, the tissue-homogeneity model, the "adiabatic approximation to the tissue-homogeneity model" and the distributed-parameter model. In simpler tissue types or when the data quality is inadequate to resolve all the features of the more complex models, it is often necessary to resort to simpler models, which are special cases of the general models and hence have less parameters. We discuss the most common of these special cases, i.e. the uptake models, the extended Tofts model, and the one-compartment model. Models for two specific tissue types, liver and kidney, are discussed separately. We conclude with a review of practical aspects of DCE-CT and DCE-MRI data analysis, including the problem of identifying a suitable model for any given data set, and a brief discussion of the application of tracer-kinetic modeling in the context of drug development. Here, an important application of DCE techniques is the derivation of quantitative imaging biomarkers for the assessment of effects of targeted therapeutics on tumors.

Primary colorectal cancer: use of kinetic modeling of dynamic contrast-enhanced CT data to predict clinical outcome

PURPOSE

To compare four different tracer kinetic models for the analysis of dynamic contrast material-enhanced computed tomographic (CT) data with respect to the prediction of 5-year overall survival in primary colorectal cancer.

MATERIALS AND METHODS

This study was approved by the ethical review board. Archival dynamic contrast-enhanced CT data from 46 patients with colorectal cancer, obtained as part of a research study, were analyzed retrospectively by using the distributed parameter, conventional compartmental, adiabatic tissue homogeneity, and generalized kinetic models. Blood flow, blood volume, mean transit time (MTT), permeability-surface area product, extraction fraction, extravascular extracellular volume (v(e)), and volume transfer constant (K(trans)) were compared by using the Friedman test, with statistical significance at 5%. Following receiver operating characteristic analysis, parameters of the different kinetic models and tumor stage were compared with respect to overall survival discrimination, with use of Kaplan Meier analysis and a univariate Cox proportional hazard model, with additional cross-validation and permutation testing.

RESULTS

Blood flow was lower with the distributed parameter model than with the conventional compartmental and adiabatic tissue homogeneity models (P < .0001), and blood flow values determined with the conventional compartmental and adiabatic tissue homogeneity models were similar. Conversely, MTT was longer with the distributed parameter model than with the conventional compartmental and adiabatic tissue homogeneity models (P < .0001). Blood volume, permeability-surface area product, and v(e) were higher with the conventional compartmental model than with the adiabatic tissue homogeneity, distributed parameter, or generalized kinetic models (P < .0001). The extraction fraction was higher with the distributed parameter model than with the adiabatic tissue homogeneity model. With respect to 5-year overall survival, only the distributed parameter model-derived v(e) was predictive of 5-year overall survival with a threshold value of 15.48 mL/100 mL after cross-validation and permutation testing.

CONCLUSION

Parameter values differ significantly between models. Of the models investigated, the distributed parameter model was the best predictor of 5-year overall survival.

SUPPLEMENTAL MATERIAL

http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.12120186/-/DC1.

Combined quantification of liver perfusion and function with dynamic gadoxetic acid-enhanced MR imaging

PURPOSE

To evaluate the feasibility of quantifying hepatic perfusion and function by using dynamic contrast material-enhanced (DCE) magnetic resonance (MR) imaging with the hepatobiliary contrast agent gadoxetic acid and a dual-inlet two-compartment uptake model.

MATERIALS AND METHODS

The study was approved by the local institutional review board, and written informed consent was obtained from all patients. Data were acquired between October 2008 and November 2009 in 24 patients with hepatic metastases from neuroendocrine tumors (13 men, 11 women; mean age, 59.8 years). DCE MR imaging was performed at 3.0 T with a standard dose of gadoxetic acid and a three-dimensional sequence, with 48 sections of data acquired every 2.2 seconds for 5 minutes. For each patient, a plasma flow map was calculated by means of deconvolution and the model was fitted to six region-of-interest curves. Results were evaluated with goodness-of-fit analysis and, in normal-appearing liver tissue, by comparing perfusion parameters with those reported in the literature. Interobserver effects in the selection of arterial and venous input functions were assessed.

RESULTS

With an arterial delay parameter, the model provided a good fit to all data. Values for arterial and venous plasma flow and extracellular volume in normal-appearing liver tissue were comparable to those in the literature. The mean intracellular uptake rate is 3.4/100/min with a standard deviation of 1.9/100/min The model also provided a good fit in all tumor data, producing high arterial flow fraction (87%) and lower uptake (1.7/100/min) . Bias due to observer-dependent differences in the selection of the input functions was negligible.

CONCLUSION

The analysis of dynamic gadoxetic acid-enhanced MR images with the dual-inlet two-compartment uptake model presents a new and practical approach for measuring arterial and venous perfusion and hepatic function in a single acquisition.

High temporal resolution dynamic contrast-enhanced MRI at 7 Tesla: a feasibility study with mouse liver model

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has been widely applied to evaluate microcirculatory parameters in clinical settings. However, pre-clinical studies involving DCE-MRI of small animals remain challenging with the requirement for high spatial and temporal resolution for quantitative tracer kinetic analysis. This study illustrates the feasibility of applying a high temporal resolution (2 s) protocol for liver imaging in mice by analyzing the DCE-MRI datasets of mice liver with a dual-input two-compartment tracer kinetic model. Phantom studies were performed to validate the T(1) estimates derived by the proposed protocol before applying it in mice studies. The DCE-MRI datasets of mice liver were amendable to tracer kinetic analysis using a dual-input two-compartment model. Estimated micro-circulatory parameters were consistent with liver physiology, indicating viability of applying the technique for pre-clinical drug developments.

Tracer kinetic modelling in MRI: estimating perfusion and capillary permeability

The tracer-kinetic models developed in the early 1990s for dynamic contrast-enhanced MRI (DCE-MRI) have since become a standard in numerous applications. At the same time, the development of MRI hardware has led to increases in image quality and temporal resolution that reveal the limitations of the early models. This in turn has stimulated an interest in the development and application of a second generation of modelling approaches. They are designed to overcome these limitations and produce additional and more accurate information on tissue status. In particular, models of the second generation enable separate estimates of perfusion and capillary permeability rather than a single parameter K(trans) that represents a combination of the two. A variety of such models has been proposed in the literature, and development in the field has been constrained by a lack of transparency regarding terminology, notations and physiological assumptions. In this review, we provide an overview of these models in a manner that is both physically intuitive and mathematically rigourous. All are derived from common first principles, using concepts and notations from general tracer-kinetic theory. Explicit links to their historical origins are included to allow for a transfer of experience obtained in other fields (PET, SPECT, CT). A classification is presented that reveals the links between all models, and with the models of the first generation. Detailed formulae for all solutions are provided to facilitate implementation. Our aim is to encourage the application of these tools to DCE-MRI by offering researchers a clearer understanding of their assumptions and requirements.

Atypical Enhancement Pattern of Hepatocellular Carcinoma with Portal Vein Thrombosis on Multiphasic CT

Introduction: The 2005 American Association for Study of Liver Diseases (AASLD) diagnostic criteria allow non-invasive diagnosis of hepatocellular carcinoma (HCC) based on their enhancement pattern but we have observed a high incidence of atypical enhancement characteristics in HCC associated with portal vein thrombosis. This study seeks to examine the radiological features of this particular subgroup. Materials and Methods: Patients with HCC and portal vein thrombosis who underwent pre-treatment multiphasic CT imaging were drawn from a surgical database. The arterial, portal venous and delayed phase images were assessed qualitatively and quantitatively (with region of interest [ROI] analysis) for lesion hypervascularity and washout. The background enhancement of the left and right lobes of the liver was also quantified by ROI analysis. Results: Twenty-five lesions in 25 patients were selected for analysis. Qualitative analysis showed that 10/25 (40%) lesions demonstrated arterial hypervascularity while 16/25 (64%) lesions showed washout. Ten out of 25 (40%) lesions demonstrated both arterial hypervascularity and washout. Quantitative analysis showed that the average absolute lesion enhancement from precontrast to arterial phases was 49.1 (±17.1) HU for hypervascular lesions compared to 23.8 (±16.6) HU for non-hypervascular lesions (P <0.01). The mean absolute enhancement of the background liver parenchyma in the arterial phase was 13.79 (±7.9) HU for hypervascular lesions compared to 36.6 (±30.6) HU for non-hypervascular lesions (P = 0.03). Conclusion: A large proportion of HCC with portal vein thrombosis lack characteristic arterial hypervascularity, which may be secondary to compensatory increased arterial supply to the background liver. This is a potential pitfall when applying imaging criteria for diagnosis of HCC. Key words: HCC, Hypervascular, Pitfall, Wash-out

Fundamentals of tracer kinetics for dynamic contrast-enhanced MRI

Tracer kinetic methods employed for quantitative analysis of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) share common roots with earlier tracer studies involving arterial-venous sampling and other dynamic imaging modalities. This article reviews the essential foundation concepts and principles in tracer kinetics that are relevant to DCE MRI, including the notions of impulse response and convolution, which are central to the analysis of DCE MRI data. We further examine the formulation and solutions of various compartmental models frequently used in the literature. Topics of recent interest in the processing of DCE MRI data, such as the account of water exchange and the use of reference tissue methods to obviate the measurement of an arterial input, are also discussed. Although the primary focus of this review is on the tracer models and methods for T(1) -weighted DCE MRI, some of these concepts and methods are also applicable for analysis of dynamic susceptibility contrast-enhanced MRI data.