Evaluation of Liver Cancer With Magnetic Resonance Imaging (MRI)

Evaluation of HCC Response to Systemic Therapy With Quantitative MRI

Status

Completed

Phases

Study type

Interventional

Source

ClinicalTrials.gov

Registry ID

NCT01871545

Enrollment

Registered

2013-06-06

Start date

2013-06-30

Completion date

2018-02-02

Last updated

2020-07-09

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

HCC, Hepatocellular Carcinoma

Keywords

hepatocellular carcinoma, HCC, liver cancer, liver disease, magnetic resonance imaging, MRI

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.

Interventions

DEVICEMagnetic Resonance Imaging

Magnetic Resonance Imaging is a radiation free non invasive technique using magnetic radiofrequency waves to image the body. In this study, the research team would like to investigate the possibility of providing functional information on aggressiveness, vascularity and oxygen uptake in liver cancer tumors.

Study design

Allocation

NON_RANDOMIZED

Intervention model

SINGLE_GROUP

Primary purpose

DIAGNOSTIC

Masking

NONE

Eligibility

Sex/Gender

ALL

Age

18 Years to No maximum

Healthy volunteers

Yes

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

Design outcomes

Primary

Measure	Time frame	Description
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.
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: Oxygen Uptake	Day 1	Oxygen uptake measured with T2\* and T1-weighted imaging
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: 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 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 1: Apparent Diffusion Coefficient (ADC)	Day 1	Tumor diffusion (apparent diffusion coefficient) measured with diffusion-weighted imaging sequence
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

Secondary

Measure	Time frame	Description
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: 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: 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.
SubStudy 2: Total Tumor Perfusion (Ft)	baseline and 6 weeks after Y90	Perfusion/flow measured with dynamic contrast-enhanced imaging using gadolinium contrast

Countries

United States

Participant flow

Recruitment details

Enrollment from June 2013 through February 2018

Participants by arm

Arm	Count
Hepatocellular Carcinoma (HCC) Participants with hepatocellular carcinoma (HCC)	56
Healthy Participant Healthy control participants	8
Total	64

Withdrawals & dropouts

Period	Reason	FG000	FG001
Overall Study	Death	2	0
Overall Study	Lack of Efficacy	11	2
Overall Study	Physician Decision	4	0
Overall Study	Withdrawal by Subject	0	1

Baseline characteristics

Characteristic	Healthy Participant	Total	Hepatocellular Carcinoma (HCC)
Age, Continuous	36 years	62 years	65 years
Ethnicity (NIH/OMB) Hispanic or Latino	1 Participants	18 Participants	17 Participants
Ethnicity (NIH/OMB) Not Hispanic or Latino	7 Participants	43 Participants	36 Participants
Ethnicity (NIH/OMB) Unknown or Not Reported	0 Participants	3 Participants	3 Participants
Race (NIH/OMB) American Indian or Alaska Native	0 Participants	0 Participants	0 Participants
Race (NIH/OMB) Asian	3 Participants	7 Participants	4 Participants
Race (NIH/OMB) Black or African American	1 Participants	19 Participants	18 Participants
Race (NIH/OMB) More than one race	0 Participants	0 Participants	0 Participants
Race (NIH/OMB) Native Hawaiian or Other Pacific Islander	0 Participants	0 Participants	0 Participants
Race (NIH/OMB) Unknown or Not Reported	0 Participants	3 Participants	3 Participants
Race (NIH/OMB) White	4 Participants	35 Participants	31 Participants
Sex: Female, Male Female	7 Participants	19 Participants	12 Participants
Sex: Female, Male Male	1 Participants	45 Participants	44 Participants
SubStudy 1: Age	36 years	59 years	59 years
SubStudy 1: Ethnicity Hispanic or Latino	1 Participants	8 Participants	7 Participants
SubStudy 1: Ethnicity Not Hispanic or Latino	7 Participants	31 Participants	24 Participants
SubStudy 1: Ethnicity Unknown or Not Reported	0 Participants	1 Participants	1 Participants
SubStudy 1: Race American Indian or Alaska Native	0 Participants	0 Participants	0 Participants
SubStudy 1: Race Asian	3 Participants	6 Participants	3 Participants
SubStudy 1: Race Black or African American	1 Participants	13 Participants	12 Participants
SubStudy 1: Race More than one race	0 Participants	0 Participants	0 Participants
SubStudy 1: Race Native Hawaiian or Other Pacific Islander	0 Participants	0 Participants	0 Participants
SubStudy 1: Race Unknown or Not Reported	0 Participants	1 Participants	1 Participants
SubStudy 1: Race White	4 Participants	20 Participants	16 Participants
SubStudy 1: Sex Female	7 Participants	13 Participants	6 Participants
SubStudy 1: Sex Male	1 Participants	27 Participants	26 Participants
SubStudy 2: Age	—	68 years	68 years
SubStudy 2: Ethnicity Hispanic or Latino	—	10 Participants	10 Participants
SubStudy 2: Ethnicity Not Hispanic or Latino	—	12 Participants	12 Participants
SubStudy 2: Ethnicity Unknown or Not Reported	—	2 Participants	2 Participants
SubStudy 2: Race American Indian or Alaska Native	—	0 Participants	0 Participants
SubStudy 2: Race Asian	—	1 Participants	1 Participants
SubStudy 2: Race Black or African American	—	6 Participants	6 Participants
SubStudy 2: Race More than one race	—	0 Participants	0 Participants
SubStudy 2: Race Native Hawaiian or Other Pacific Islander	—	0 Participants	0 Participants
SubStudy 2: Race Unknown or Not Reported	—	2 Participants	2 Participants
SubStudy 2: Race White	—	15 Participants	15 Participants
SubStudy 2: Sex Female	—	6 Participants	6 Participants
SubStudy 2: Sex Male	—	18 Participants	18 Participants

Adverse events

Event type	EG000 affected / at risk	EG001 affected / at risk	EG002 affected / at risk
deaths Total, all-cause mortality	0 / 8	2 / 32	6 / 24
other Total, other adverse events	1 / 8	3 / 32	0 / 24
serious Total, serious adverse events	0 / 8	0 / 32	0 / 24

Outcome results

Primary

SubStudy 1: Apparent Diffusion Coefficient (ADC)

Tumor diffusion (apparent diffusion coefficient) measured with diffusion-weighted imaging sequence

Time frame: Day 1

Population: Data analysis only for a subset of patients with HCC undergoing hepatic resection

Arm	Measure	Value (MEAN)	Dispersion
Hepatocellular Carcinoma (HCC)	SubStudy 1: Apparent Diffusion Coefficient (ADC)	1.43 1x10^-3 mm^2/s	Standard Deviation 0.68

Primary

SubStudy 1: Oxygen Uptake

Oxygen uptake measured with T2\* and T1-weighted imaging

Time frame: Day 1

Population: Data analysis only for a subset of patients with HCC undergoing hepatic resection compared to healthy controls. Oxygen uptake for HCCs is reported in patients, and oxygen uptake for the liver is reported in volunteers. R1 measurements method in the volunteers proved unreliable - therefore no data available for T1/R1 in the healthy participant arm.

Arm	Measure	Group	Value (MEAN)	Dispersion
Hepatocellular Carcinoma (HCC)	SubStudy 1: Oxygen Uptake	ΔR1=R1 post O2-R1 pre O2	0.23 s-1	Standard Deviation 1.1
Hepatocellular Carcinoma (HCC)	SubStudy 1: Oxygen Uptake	R1 post O2	1.90 s-1	Standard Deviation 1.79
Hepatocellular Carcinoma (HCC)	SubStudy 1: Oxygen Uptake	R2(=1/T2) pre oxygen (O2) administration	34.6 s-1	Standard Deviation 24.7
Hepatocellular Carcinoma (HCC)	SubStudy 1: Oxygen Uptake	R2* post O2	33.7 s-1	Standard Deviation 14.5
Hepatocellular Carcinoma (HCC)	SubStudy 1: Oxygen Uptake	ΔR2=R2 post O2-R2* pre O2	-0.78 s-1	Standard Deviation 8.7
Hepatocellular Carcinoma (HCC)	SubStudy 1: Oxygen Uptake	R1(=1/T1) pre oxygen (O2) administration	1.67 s-1	Standard Deviation 0.94
Healthy Participant	SubStudy 1: Oxygen Uptake	R2(=1/T2) pre oxygen (O2) administration	33.2 s-1	Standard Deviation 5.8
Healthy Participant	SubStudy 1: Oxygen Uptake	R2* post O2	30.7 s-1	Standard Deviation 5.2

Primary

SubStudy 1: Percent Change in Oxygen Uptake

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.

Time frame: Day 1, pre-oxygen administration and 10 min. post-oxygen administration

Population: Healthy Participants only

Arm	Measure	Value (MEAN)	Dispersion
Healthy Participant	SubStudy 1: Percent Change in Oxygen Uptake	7.2 percent of oxygen uptake	Standard Deviation 7.9

Primary

SubStudy 1: Total Tumor Perfusion (Ft)

Perfusion/flow measured with dynamic contrast-enhanced imaging using gadolinium contrast

Time frame: Day 1

Population: Data analysis only for a subset of patients with HCC undergoing hepatic resection

Arm	Measure	Value (MEAN)	Dispersion
Hepatocellular Carcinoma (HCC)	SubStudy 1: Total Tumor Perfusion (Ft)	358 ml/min/100g	Standard Deviation 337

Primary

SubStudy 1: Tumor Arterial Perfusion Fraction (ART)

Perfusion/flow measured with dynamic contrast-enhanced imaging using gadolinium contrast

Time frame: Day 1

Population: Data analysis only for a subset of patients with HCC undergoing hepatic resection

Arm	Measure	Value (MEAN)	Dispersion
Hepatocellular Carcinoma (HCC)	SubStudy 1: Tumor Arterial Perfusion Fraction (ART)	78.9 percent of perfusion	Standard Deviation 21.5

Primary

SubStudy 1: Tumor Distribution Volume (DV)

Tumor distribution volume (DV) of contrast agent. Perfusion/flow measured with dynamic contrast-enhanced imaging using gadolinium contrast

Time frame: Day 1

Population: Data analysis only for a subset of patients with HCC undergoing hepatic resection

Arm	Measure	Value (MEAN)	Dispersion
Hepatocellular Carcinoma (HCC)	SubStudy 1: Tumor Distribution Volume (DV)	34.6 percent	Standard Deviation 24.7

Primary

SubStudy 1: Tumor Mean Transit Time (MTT)

Tumor mean transit time (MTT) of contrast agent. Perfusion/flow measured with dynamic contrast-enhanced imaging using gadolinium contrast

Time frame: Day 1

Population: Data analysis only for a subset of patients with HCC undergoing hepatic resection

Arm	Measure	Value (MEAN)	Dispersion
Hepatocellular Carcinoma (HCC)	SubStudy 1: Tumor Mean Transit Time (MTT)	21.2 sec	Standard Deviation 15.8

Primary

SubStudy 2: ADC

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).