New Ultrasound Technique Developed for Diagnosing and Tracking Liver Fibrosis and Tumors

Researchers at Duke University have developed a new ultrasound imaging technique that non-invasively detects tumors and fibrosis in the liver, thus avoiding the pain and complications associated with biopsy. These researchers are also extending the technique to aid in diagnosing other diseases, as well.

NIBIB grantees Kathy Nightingale, Ph.D., the James L. Vincent Associate Professor of Biomedical Engineering at Duke, and Gregg Trahey, PhD, Professor of Biomedical Engineering at Duke and their co-investigators, developed the technique, called Acoustic Radiation Force Impulse imaging (ARFI). The technique has been licensed and adopted for use in new Siemens ultrasound imaging systems in Europe, and clinical studies there and in Asia are showing results consistent with findings from Dr. Nightingale’s lab. While this tool is not yet available in the U.S., Siemens is currently pursuing FDA approval to market it in the U.S.

Background

As with most diseases, the ability to detect liver fibrosis in its early stages has a significant impact on whether or not a patient survives. The current gold standard for diagnosing liver fibrosis is biopsy —a procedure that is painful, expensive, can cause complications, and cannot be performed frequently enough to effectively track the progression of the disease. When the liver has been damaged -- whether by excessive alcohol intake, hepatitis, nonalcoholic fatty liver disease, or from some inherited conditions — healthy liver tissue begins to transform into stiff scars that disrupt the activity of the liver, a condition known as cirrhosis. Chronic liver disease and cirrhosis affect more than 5.5 million people in the United States, causing over 31,000 deaths due to liver failure in 2010¹. In addition, non-alcoholic fatty liver disease (NAFLD), occurs when there is excessive accumulation of fat in the liver, and currently afflicts about 80 million Americans. This condition can progress to cirrhosis and, in its extreme stage to liver cancer.

What’s New

ARFI is an ultrasound technique, and so, does not produce ionizing radiation (unlike X-rays, CT, and PET scans), and is relatively inexpensive compared to other imaging modalities. This means it can be used more frequently to track the progression of fibrosis. In addition, it can image the entire liver, as opposed to biopsy, which can only examine a small sample of the liver. While the quality of an ultrasound image can often be operator-dependent, this test only requires that the operator locate the liver in an image display and then keep the detector in place; this makes it relatively easy to get a clear image of the liver and possible fibrotic tissue in a short amount of time.

Fig 1. ARFI: In Vivo - Liver - Hepatocellular Carcinoma2 Patient with liver cirrhosis, hepatitis C, HIV+ HCC appears softer than surrounding cirrhotic liver tissue Source: Duke Biomedical Engineering   (Click on image to enlarge)

The ARFI technique uses focused, high intensity sound beams to produce “push-pulses” that generate shear waves (secondary waves that extend in a direction perpendicular to the direction of the push pulse) within tissue and then monitors the tissue response with ultrasonic methods. The tissue response is related to the stiffness properties and structure of the liver, and is displayed as high resolution, qualitative elastographic images of the liver (Figure 1). The speed of the shear waves is proportional to the stiffness of tissue; thus ARFI can also produce quantitative stiffness measurements based on the speed of the shear waves. These measurements are used to quantify specific levels of fibrosis that can be used to classify different stages of liver fibrosis (Fig. 2).

Fig 2. ARFI Study: NASH Patient Population Noninvasive Hepatic Fibrosis Staging3 Shear modulus (μ) distinguished low (F0-F2) from high (F3-F4) fibrosis stages using a threshold of 4.2 kPa, with a sensitivity and specificity of 90%, and AUC of 0.9. Source: Duke Biomedical Engineering   (Click on image to enlarge)

For example, a type of liver cancer, called hepatocellular carcinoma (HCC), can appear softer than surrounding cirrhotic liver tissue. The ARFI technique displays an ultrasound image which highlights the softer tissue, so it appears as a mass with a lighter shade of gray than surrounding tissue (Figure 1). On the other hand, another type of liver cancer, called metastatic melanoma, is characterized as a stiffer tissue, and appears as a darker mass than the surrounding non-fibrotic liver tissue (Fig. 3).

Fig 3. ARFI: In Vivo liver (metastatic melanoma)2 Metastatic mass appears stiffer (darker) than surrounding liver tissue Patient with metastatic melanoma in liver, no known fibrosis Source: Duke Biomedical Engineering   (Click on image to enlarge)

An important part of developing this imaging technique was creating an algorithm that allows detection of ARFI data with minimal background noise. Dr. Nightingale’s lab designed an algorithm that creates precise images. Since shear wave speed increases with the severity of the stage of fibrosis, this technique now makes it possible to differentiate late stages of fibrosis from earlier stages. If fibrosis is indicated, a biopsy will still most likely be required to confirm the finding, but this technique can be used as an initial screening device to eliminate unnecessary biopsies.

Existing Technologies

The use of ultrasound and shear waves to detect fibrosis is not entirely new. The FibroscanTM method is an existing technique that also uses ultrasound, plus an external “punch” from a piston pressure source that directs both shear waves and sound pressure waves at the liver. However, it does not produce anatomic or elastographic images, but only numerical data which is used to detect fibrotic tissue. Since this method does not display the precise location of specific regions or structures within the liver that are fibrotic, it can confuse existing blood vessels or other healthy structures with actual liver tissue. In addition, the use of the external “punch” piston in this technique does not work in patients with fluid around the liver (ascites).

Fig 4. Liver MRE Image courtesy of Dr. Richard Ehman, Mayo Clinic    (Click on image to enlarge)

Another method for identifying liver fibrosis, which is already FDA-approved for clinical use, is MR elastography. Like the ARFI method, this technique also uses an external acoustic pressure pulse directed at the abdomen, which produces shear waves within the tissue (i.e., the liver). This method also computes the relative stiffness of tissue components, based on how they respond to the pressure wave, and displays these relative stiffness values in a color-coded image, or MR elastogram (Figure 4). Compared with the ultrasound ARFI technique, MR elastography has the advantages of higher resolution (i.e., more detailed images) and larger area coverage. However, the disadvantages include much higher costs, lack of availability in many clinical settings (e.g. emergency rooms, rural areas, third world countries), and lack of portability, since MRI machines are completely stationary.

What’s Next

In the future, those who are suspected of having fibrosis may first be screened with this exam, and only after a positive indication of stiffness go through the painful and sometimes dangerous biopsy procedure to confirm diagnosis. ARFI could then monitor the progression of the disease on a more regular basis than is currently available. In addition, Drs. Nightingale and Trahey have identified other diseases such as breast, thyroid, and prostate cancer, in addition to cardiovascular diseases that are associated with elevated stiffness and shear wave speed, thus increasing the potential clinical uses of ARFI.

-- Jessica Meade

¹ http://www.cdc.gov/nchs/data/nvsr/nvsr60/nvsr60_04.pdf
² Fahey et al. “In vivo visualization of abdominal malignancies with acoustic radiation force elastography”, Phys. Med. Biol. 53 (2008) 279–293.
³ Palmeri, M., et al, “Evaluating Liver in NAFLD Patients Using Ultrasonic Acoustic Radiation Force-Based Shear Stiffness Quantification”, Journal of Hepatology, 55(3):666-672, 2011.

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