Algorithmic Raman: Improved breast diagnostics

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  • Published: Jun 1, 2013
  • Author: David Bradley
  • Channels: Raman
thumbnail image: Algorithmic Raman: Improved breast diagnostics

Raman saving lives

A newly developed, single-step algorithm for processing Raman spectra can reveal the presence of microcalcifications in breast tissue that are often associated with breast cancer lesions and so improve the precision of diagnosis of the disease itself at the early stages without multiple biopsies of suspicious growths.

A newly developed, single-step algorithm for processing Raman spectra can reveal the presence of microcalcifications in breast tissue that are often associated with breast cancer lesions and so improve the precision of diagnosis of the disease itself at the early stages without multiple biopsies of suspicious lumps.

According to Ishan Barman, a post-doctoral researcher at Massachusetts Institute of Technology in Cambridge, USA, "Nearly 1.6 million breast biopsies are performed and roughly 250,000 new breast cancers are diagnosed in the Unites States each year." He suggests that, "If 200,000 repeat biopsies were avoided, even by a conservative estimate, the US healthcare system could save $1 billion per year." His research could open the way to significantly reducing the number of repeat biopsies, thus saving women from potentially unnecessary invasive interventions as well as cutting healthcare costs.

Improving breast cancer diagnosis

Currently, X-ray mammography is the only screening method for the detection of breast cancer at the early stages and is accepted routinely. However, it has a major drawback in that it cannot distinguish accurately between microscopic areas of deposited calcium in the breast tissue (microcalcifications) that are associated with benign or malignant breast lesions. This means that a sample of such a growth as identified by mammography must be removed and analysed in the laboratory to demonstrate one way or the other whether the growth is likely to lead to life-threatening cancer.

The biopsy procedure, a core needle biopsy, is used as standard for testing microcalcifications, Unfortunately, this too has drawbacks and can only retrieve microcalcifications in about 15 to 25 percent of patients. This results in non-diagnostic or false-negative biopsies, requiring the patient to undergo a repeat, often more invasive, surgical biopsy. There has recently been research to improve the precision of needle biopsy using magnetic resonance imaging (MRI) and other techniques. However, a technical solution that precludes the need for a repeat biopsy and offers more accurate results would be more desirable.

Radiological feedback

According to Barman and his colleagues, they have now found a solution to this problem in the form of their newly developed algorithm, which can offer positive and negative predictive values of 100 percent and 96 percent, respectively, for the diagnosis of breast cancer with or without microcalcifications. Moreover, the algorithm can classify 82 percent of biopsy samples into normal, benign or malignant lesions without further intervention, a marked improvement on the 15-25 percent rate often seen in the clinic.

The researchers used a portable clinical Raman spectrometer to obtain data from breast tissue biopsy specimens from 33 women. Spectra were obtained from 146 tissue sites within the samples, including 50 normal tissue sites, 77 lesions with microcalcifications and 19 lesions without microcalcifications. The spectra were quick to retrieve, all being recorded within half an hour of sample removal. The team then fitted the spectra to their model to allow them to discern the different types and texture of various components of the breast tissue. This analysis, in turn, was fed to a single-step Raman algorithm that distinguishes normal breast tissue, breast cancer with and without microcalcifications, and other benign breast lesions including fibrocystic change and fibroadenoma.

"There is an unmet clinical need for a tool that could minimize the number of X-rays and biopsy procedures," explains Barman. "This tool could shorten procedure time; reduce patient anxiety, distress and discomfort; and prevent complications such as bleeding into the biopsy site after multiple biopsy passes." Barman adds that, "Our study demonstrates the potential of Raman spectroscopy to simultaneously detect microcalcifications and diagnose associated lesions with a high degree of accuracy, providing real-time feedback to radiologists during the biopsy procedures."

The team reports that in their small-scale study, the majority of breast cancers diagnosed using the one-step Raman algorithm were of the ductal carcinoma type. This is, in fact, the most common lesion associated with microcalcifications and is usually opaque to conventional diagnosis.

The approach will provide real-time feedback to radiologists and reduce the number of non-diagnostic and false-negatives, the team reports.

Related Links

Cancer Res 2013, 73, 3206-3215: "Application of Raman Spectroscopy to Identify Microcalcifications and Underlying Breast Lesions at Stereotactic Core Needle Biopsy"

Article by David Bradley

The views represented in this article are solely those of the author and do not necessarily represent those of John Wiley and Sons, Ltd.

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