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New Method to Test Breast Lesions Could Save Money
A newly developed, single-step Raman spectroscopy algorithm has the potential to simultaneously detect microcalcifications and enable diagnosis of the associated breast lesions with high precision, according to data published in Cancer Research, a journal of the American Association for Cancer Research (AACR).
“Nearly 1.6 million breast biopsies are performed, and roughly 250,000 new breast cancers are diagnosed in the Unites States each year,” said lead author Ishan Barman, PhD. “If 200,000 repeat biopsies were avoided, even by a conservative estimate, the U.S. health care system could save $1 billion per year.”
X-ray mammography is currently the only accepted routine screening method for early detection of breast cancer, but it cannot accurately distinguish whether microcalcifications (microscopic areas of calcium accumulation) are associated with benign or malignant breast lesions, according to Barman. Most patients, therefore, undergo core needle biopsy to determine whether the microcalcifications are associated with malignancy, but the technique fails to retrieve microcalcifications in about 15% to 25% of patients. This results in nondiagnostic or false-negative biopsies, requiring the patient to undergo repeat, often surgical biopsy.
According to the researchers, the newly developed algorithm showed positive and negative predictive values of 100% and 96%, respectively, for the diagnosis of breast cancer with or without microcalcifications. The algorithm also showed an overall accuracy of 82% for classification of the samples into normal, benign, or malignant lesions.
“There is an unmet clinical need for a tool that could minimize the number of X-rays and biopsy procedures. 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 said.
The researchers used a portable clinical Raman spectroscopy system to obtain Raman spectra from breast-tissue biopsy specimens obtained from 33 women. They then fitted the spectra into a model that identifies the different types and textures of the various components of breast tissue. A single-step Raman algorithm was used to distinguish normal breast tissue, breast cancer with and without microcalcifications, and other benign breast lesions, including fibrocystic changes and fibroadenoma.
Source: AACR; May 31, 2013.