Mammograms can find breast microcalcifications but can’t tell whether they are likely benign or malignant.
At SciX 2026 in Sparks, Nevada, Spectroscopy spoke with Sara Miller, a vibrational spectroscopist at Flinders University in Australia.1 She and her co-authors Mitchell C. Chalmers, Teemu Tomberg, and Keith Gordon won the inaugural Peter Griffiths Award for the best paper in Applied Spectroscopy Practica. Their study used deep low-frequency Raman spectroscopy to tell apart model breast microcalcifications immersed in wax and placed under varying depths of it, with wax standing in for tissue as a proof of principle.1
Below is a transcript of our conversation with Miller, which highlights one way that Raman spectroscopy is being used in clinical workflows.
It is a great honor for our research team. It’s nice to have recognition for the work that our research group and international collaboration have carried out.
We're trying to address finding a different way of detecting the breast microcalcifications. A mammogram's really good at detecting the microcalcifications, but it can't distinguish whether it is likely to be benign or malignant. Additional biopsies and tests are required to figure that out. Therefore, we really want to use low-wavenumber Raman to see if we can get a fingerprint of the composition of those microcalcifications and if that could be used as a diagnostic tool.
The ultimate goal is to be able to detect microcalcifications in breast tissue, and so that means we need to be able to detect these microcalcifications below some kind of tissue-like medium. We were really trying to find a proof of principle for this particular study, so we were using wax as our tissue phantom.
The micro-spatially offset setup is where we are taking our Raman measurement, and we’re defocusing from there. That means that you’re starting to capture photons that have undergone Raman scattering across a larger volume and deeper into that substrate. We think that this particular alignment works the best because we’re still capturing a large volume of the photons that were scattered.
In the other alignments that we studied, which were using a lateral offset, we’re moving further away from the illumination laser point, and that means that the photons have to scatter further to be detected, and we’re only looking at a subset of those scattered photons. Therefore, we’re going to end up with more noise and less signal in that particular type of arrangement.
There are a few steps that have to occur before we get to that clinical setting. I think the first thing we need to do is look at a much more representative tissue phantom, whether that is some pork meat and skin, or whether we can utilize varying levels of pigment and hydrogels to try and mimic different skin colors and see how the photons can penetrate under those different conditions. We also need to create a probe that utilizes that type of setup that can be in a more portable system before we then take it to a clinic to even start to build the data to build the robust models.
I think the findings are a good starting point and show promise. I think based on what we’ve found so far, it’s worth pursuing it further for any application where we think mineral-type subsurface signatures might be useful. While we’re targeting the
