A study from Johns Hopkins University, published in Biophotonics Discovery, examined how skin tone affects the accuracy of photoacoustic imaging (PAI), a technology gaining traction in breast cancer diagnostics, especially in situations where traditional mammography is insufficient. The study shows how image reconstruction methods and laser wavelengths influence the visibility of cancerous targets in patients with diverse skin tones and suggests practical solutions to improve equity in diagnostics.
Photoacoustic imaging is a hybrid imaging technique that combines light and sound. Light pulses are transmitted into the body and absorbed by structures like blood vessels, which then undergo thermal expansion and generate sound waves. Ultrasound detectors capture these waves to create detailed images.
“Photoacoustic imaging leverages the unique properties of light absorption and sound propagation,” explained lead study investigator Muyinatu Bell, PhD. “For breast cancer detection, it highlights blood vessels, which tend to form differently around malignant versus benign tissue.”
Approved by the FDA within the last two years, PAI technology complements traditional mammography and ultrasound, especially in cases of indeterminate masses. “The idea is to provide additional certainty for patients with ambiguous imaging results, potentially sparing them years of follow-ups,” said Bell.
The challenge: Skin tone bias
Despite its potential, PAI is not without limitations. Skin tone can significantly affect imaging outcomes because melanin, abundant in darker skin, absorbs light, interfering with the imaging process.
“When you transmit light through the skin, melanin can absorb it, generating a high signal at the skin’s surface and scattering sound waves within the breast tissue,” Bell explained. “This scattering complicates imaging, making it harder to distinguish targets, especially in individuals with darker skin tones.”
To investigate this issue, the researchers tested three image reconstruction methods—fast Fourier transform (FFT), delay-and-sum (DAS) beamforming, and short-lag spatial coherence (SLSC) beamforming—across various skin tones, laser wavelengths (757, 800, and 1064 nm), and target sizes (0.5–3 mm).
The results highlighted significant disparities in imaging performance:
- At shorter wavelengths (757 and 800 nm), darker skin tones caused a notable drop in the signal-to-noise ratio (SNR) and contrast-to-noise ratio (gCNR), making it difficult to detect small cancerous targets.
- FFT and DAS, conventional reconstruction methods, struggled the most under these conditions.
- The longer wavelength (1064 nm) mitigated melanin absorption, producing clearer images across skin tones. However, this wavelength penetrates less deeply, limiting its diagnostic scope.
- SLSC beamforming emerged as a game-changer. By focusing on spatial coherence rather than signal amplitude, it significantly enhanced image quality and reduced bias.
“The SLSC method doesn’t rely on the amplitude of signals, which can be skewed by melanin absorption,” Bell noted. “Instead, it evaluates how spatially correlated these signals are, providing a much clearer picture, especially for smaller targets.” The researchers found that combining the 1064 nm wavelength with SLSC beamforming best enhanced the visibility of targets across all skin tones, providing clearer images with higher SNR and gCNR values.
The study underscores the need for manufacturers and practitioners to consider diverse patient populations when developing and deploying imaging technologies.
“Light-based technologies inherently face challenges with melanin absorption,” Bell emphasized. “It’s crucial for manufacturers to test their systems on diverse groups and for practitioners to ask for this data before integrating such systems into their practice.”
While some manufacturers already use the 1064 nm wavelength to minimize bias, Bell advocates incorporating SLSC beamforming as a software solution. “Our method enhances imaging for all skin tones, not just darker ones. It’s a win-win for patient care,” she said.
Bell hopes her findings will prompt widespread adoption of these improvements, ensuring equitable care. “This isn’t just about advancing technology; it’s about addressing systemic inequities in healthcare,” she concluded.
