Big Data analysis may help treatment of breast cancer

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  • Author: Statistics Views
  • Date: 25 February 2016
  • Copyright: Image appears courtesy of Getty Images

Researchers from Case Western Reserve University have reported a new way to analyze magnetic resonance images (MRI) data for women with the most common type of breast cancer, which appears to reliably distinguish between patients who would need only hormonal treatment and those who also need chemotherapy,.

The research, published in the journal Nature Scientific Reports suggests that the analysis may provide women diagnosed with estrogen positive-receptor (ER-positive) breast cancer answers far faster than current tests and, due to its expected low cost, open the door to this kind of testing worldwide.

thumbnail image: Big Data analysis may help treatment of breast cancer

Until about 15 years ago, doctors had no way of telling aggressive cancer from non-aggressive, so the majority of women were prescribed chemotherapy, which can produce very harsh side effects,

Since then, a genomic test for differentiating between aggressive and nonaggressive cancer has been developed. The test, which costs an average $4000 in the US, requires doctors to send a biopsy sample to a company that analyzes it and assigns a risk score that the doctors then use to guide treatment.

The Case Western Reserve team, led by biomedical engineering professor Anant Madabhusji, employ big data to study disease, and thought they might find useful signals to discern aggressive ER-positive from indolent by mining radiologic data from MRIs.

They analyzed images of 96 ER-positive cancer patients scanned at a hospital in Cleveland or Boston. Each woman had undergone what's called a "dynamic contrast enhanced MRI," which produces images of tissues as they take up a contrast agent. Each woman had also undergone the genomic test.

Because intensity values regularly used to analyze tissues vary by scanner, the researchers needed a different way to search for signals distinguishing the two categories of patients.

• They discovered differences in gene expression -- molecular changes that appeared as changes in textural patterns in the images.
• They converted the dynamic texture changes into quantitative measurements and used differences in the measurements to determine which patients needed chemotherapy and which did not.

In 85 percent of the cases, the conclusions matched those of the genomic test.

Madabhushi said.that a computer and program are the only tools required, and using cloud computing and data warehousing technology researchers can analyze images coming in from anywhere in the world. Instead of waiting a week or two for results, the wait would be minutes, reducing the stress on patients and allowing them to quickly start treatment.

The researchers are seeking funding to evaluate the test further, and plan to test scans from more sites to see if the results hold up.

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