Evaluation of Liver Cancer With Magnetic Resonance Imaging (MRI)

Not Applicable

Completed

Conditions: HCC
Hepatocellular Carcinoma

Interventions: Device: Magnetic Resonance Imaging

Registration Number: NCT01871545

Lead Sponsor: Icahn School of Medicine at Mount Sinai

Brief Summary: The incidence of hepatocellular carcinoma (HCC) has recently increased in the United States. Although imaging plays a major role in HCC screening and staging, the possibility of predicting HCC tumor grade, aggressiveness, angiogenesis and hypoxia with imaging are unmet needs. In addition, new antiangiogenic drugs now available to treat advanced HCC necessitate the use of new imaging criteria beyond size. The investigators would like to develop and validate non-invasive magnetic resonance imaging (MRI) methods based on advanced diffusion-weighted imaging (DWI), MR Elastography, BOLD (blood oxygen level dependent) MRI and perfusion-weighted imaging (PWI, using gadolinium contrast) to be used as non-invasive markers of major histopathologic features of HCC, and to predict and assess early response of HCC to systemic therapy. The investigators also would like to develop quality control tools to improve the quality and decrease variability of quantitative MRI metrics. These techniques combined could represent non-invasive correlates of histologic findings in HCC, could enable individualized therapy, and provide prognosis in patients with HCC.

Detailed Description: The incidence of hepatocellular carcinoma (HCC) has recently increased in the US mostly due to an increase in chronic hepatitis C infection. Angiogenesis is critical for the growth and metastatic progression of HCC. With the development of new antiangiogenic drugs such as sorafenib, imaging methods to predict and assess therapeutic response beyond changes in size become critical. However, validated imaging methods to predict and assess early HCC response to targeted agents are lacking.

In this study, the investigators would like to develop quantitative MRI methods interrogating different features of HCC tumor biology and pathology, including tumor cellularity, grade, angiogenesis and hypoxia. The investigators propose a multiparametric approach combining advanced DWI (IVIM: intravoxel incoherent motion diffusion measuring perfusion fraction and true diffusion coefficient), DCE-MRI (dynamic contrast-enhanced MRI, which measures arterial and portal flow, mean transit time, blood volume and distribution volume), and BOLD MRI using oxygen or carbogen challenge. This protocol will be performed in patients with HCC undergoing hepatic resection. Routine and advanced histopathologic methods will be performed (tumor grade, CK19 expression, presence of microvascular invasion, VEGF expression, microvessel density, HIF 1-alpha expression). MRI metrics will be correlated with histopathologic metrics.

The first portion of the proposal involves the development of a QC algorithm assessing MR data quality and test-retest. The investigators will propose solutions to improve data acquisition and processing. The last 2 years of the study will be dedicated to a prospective randomized study comparing Yttrium 90 radioembolization to sorafenib, assessing the role of baseline MRI metrics and early changes (at 2 weeks) in these metrics as markers of tumor response and time to progression in patients with unresectable HCC.

Recruitment & Eligibility

Status: COMPLETED

Sex: All

Target Recruitment: 84

Inclusion Criteria

Study group

Patients diagnosed with HCC, who will undergo resection or transplantation within 6 months, as part of routine clinical care and patients diagnosed with unresectable HCC
18 years of age and older
Patient is able to give informed consent for this study

Control group

Healthy volunteers 18 years of age and older
Subject is able to give informed consent for this study

Exclusion Criteria

Age less than 18 years
Unable or unwilling to give informed consent
Contra-indications to MRI:
1. Electrical implants such as cardiac pacemakers or perfusion pumps
2. Ferromagnetic implants such as aneurysm clips, surgical clips, prostheses, artificial hearts, valves with steel parts, metal fragments, shrapnel, tattoos near the eye, or steel implants
3. Ferromagnetic objects such as jewelry or metal clips in clothing
4. Pregnant subjects
5. Pre-existing medical conditions including a likelihood of developing seizures or claustrophobic reactions

Study & Design

Study Type: INTERVENTIONAL

Study Design: SINGLE_GROUP

Arm && Interventions

Group	Intervention	Description
Magnetic Resonance Imaging	Magnetic Resonance Imaging	dynamic contrast-enhanced MRI measuring arterial and portal flow

Primary Outcome Measures

Name	Time	Method
SubStudy 1: Total Tumor Perfusion (Ft)	Day 1	Perfusion/flow measured with dynamic contrast-enhanced imaging using gadolinium contrast
SubStudy 1: Tumor Arterial Perfusion Fraction (ART)	Day 1	Perfusion/flow measured with dynamic contrast-enhanced imaging using gadolinium contrast
SubStudy 1: Tumor Mean Transit Time (MTT)	Day 1	Tumor mean transit time (MTT) of contrast agent. Perfusion/flow measured with dynamic contrast-enhanced imaging using gadolinium contrast
SubStudy 1: Tumor Distribution Volume (DV)	Day 1	Tumor distribution volume (DV) of contrast agent. Perfusion/flow measured with dynamic contrast-enhanced imaging using gadolinium contrast
SubStudy 1: Apparent Diffusion Coefficient (ADC)	Day 1	Tumor diffusion (apparent diffusion coefficient) measured with diffusion-weighted imaging sequence
SubStudy 1: Oxygen Uptake	Day 1	Oxygen uptake measured with T2\* and T1-weighted imaging
SubStudy 2: ADC	baseline and 6 weeks after Y90	Tumor diffusion measured with diffusion-weighted imaging sequence. In diffusion weighted MR imaging (DWI), the signal is proportional to the Brownian motion diffusion of free water protons in tissues. Deposition of collagen in tissue (as in fibrotic disease), or cellularity in tumors act as impediments to free water diffusion. Using different mathematical models, the degree of diffusion can be quantified from the MRI signal, to provide information on diffusion restriction due to disease. From mono exponential fit of diffusion signal, one can obtain the apparent diffusion coefficient (ADC). However, this coefficient reflects free water proton diffusion, as well as transport of water protons in the capillary vessels (capillary perfusion).
SubStudy 1: Percent Change in Oxygen Uptake	Day 1, pre-oxygen administration and 10 min. post-oxygen administration	Oxygen uptake measured with T2\* and T1-weighted imaging. Oxygen uptake (% change pre and post O2 administration) calculated by Liver ΔR2\=100 x (R2\ post O2-R2\* pre O2)/R2\* pre O2. The healthy participants breathed 100% medical O2 through a mask for 10 min., and were imaged before and after O2 administration with the MRI methods that are sensitive to oxygen uptake in tumors.
SubStudy 2: Diffusion Coefficient D	baseline and 6 weeks after Y90	Tumor diffusion measured with diffusion-weighted imaging sequence. To separate the diffusion effect from capillary perfusion, a bi-exponential model is used, which provides 3 coefficients: one is the true diffusion coefficient D, reflecting free water proton diffusion.
SubStudy 2: Pseudodiffusion Coefficient D*	baseline and 6 weeks after Y90	Tumor diffusion measured with diffusion-weighted imaging sequence. To separate the diffusion effect from capillary perfusion, a bi-exponential model is used, which provides 3 coefficients: one is the pseudo-diffusion coefficient D\*, affected by free diffusion and capillary perfusion.
SubStudy 2: Perfusion Fraction (PF)	baseline and 6 weeks after Y90	Tumor diffusion measured with diffusion-weighted imaging sequence. To separate the diffusion effect from capillary perfusion, a bi-exponential model is used, which provides 3 coefficients: one is the perfusion fraction PF, which reflects how much the diffusion-weighted signal is affected by capillary perfusion. PF is a measure of vascularity in the tissue.

Secondary Outcome Measures

Name	Time	Method
SubStudy 2: Extravascular Extracellular Volume ve	baseline and 6 weeks after Y90	Perfusion/flow measured with dynamic contrast-enhanced imaging using gadolinium contrast. Extravascular extracellular volume fraction ve (%) - represents the portion of tissue occupied by the extravascular extracellular volume (interstitial space), in which MRI contrast agent can distribute.
SubStudy 2: Total Tumor Perfusion (Ft)	baseline and 6 weeks after Y90	Perfusion/flow measured with dynamic contrast-enhanced imaging using gadolinium contrast
SubStudy 2: Tumor Arterial Perfusion Fraction (ART)	baseline and 6 weeks after Y90	Perfusion/flow measured with dynamic contrast-enhanced imaging using gadolinium contrast
SubStudy 2: Tumor Mean Transit Time (MTT) of Contrast Agent	baseline and 6 weeks after Y90	Perfusion/flow measured with dynamic contrast-enhanced imaging using gadolinium contrast
Substudy 2: Tumor Stiffness	baseline and 6 weeks after Y90	measured with magnetic resonance elastography
Tumor Response	6 weeks and 6-12 months	Tumor response to treatment is evaluated clinically by radiologists according to RECIST and modified RECIST criteria, by which the diameter of the tumor portion that enhances (lights up on imaging) after administration of gadolinium contrast agent is measured before and after treatment. The response is not reported as diameter or diameter difference in mm, but rather as a qualitative variable: complete response, partial response, stable disease and progressive disease. Complete response means no enhancing tumor regions after treatment (i.e. complete tumor necrosis, no more vascular regions of the tumor that take up contrast), partial response is a decrease in the diameter of the enhancing region, stable disease is unchanged diameter, and progressive disease is an increase in the diameter of the enhancing region after treatment.