Novel research indicated that electromagnetic fields (EMFs) could be used as an effective approach to halting the spread of breast cancers in other body parts.
The research proved that low-intensity EMFs hampered the specific breast cancer cells to move. The EMFs inhibit the formation of thin, long extensions at the periphery of a migrating tumorous cell. The scientists conducted the research in-vitro, which is available in the journal Communications Biology.
While studying on cancer cell migration, the researchers found that cancerous cells were precisely sensing the presence and the direction of EMFs. To analyze the effects thoroughly, the scientists constructed an instrument, known as “Helmholz coil,” which generates a nearly uniform magnetic field. The researchers exposed the breast cancer cells in a uniform EMF and continuously tracked the movement of cells under a microscope.
The researchers discovered that among the different types of breast cancer cells, metastatic triple-negative breast cancer cells were most sensitive to EMFs.
On a similar note, scientists from the University of Southern California have trained an algorithm to differentiate between benign and malignant tumors in breast tissues, simply by assessing the scanned images.
Usually, surgeons follow incision-based method to detect whether the breast tissue comprises benign or malignant tissues. However, if cancer can be accurately diagnosed through image analysis, then it would be a revolutionary discovery in cancer diagnosis.
The researchers used the AI-based approach and trained an algorithm by storing all the information revealed from 12,000 simulated images.
Then, the researchers tested the algorithm, which revealed 100% accurate results for the imitated images. After that, they moved on to authentic images. The trained algorithm assessed 10 scanned images and concluded that in five cases benign lesions were present and in other five, malignant lesions.
The algorithm was not able to review the cancer type precisely.