Optics 101

Advancing Breast Tissue Diagnosis: Compact Photoacoustic Sensing Instrument Unveiled

In the biomedical field, imaging techniques are vital for diagnostic purposes. Recently, photoacoustic (PA) techniques have been used in biomedical diagnostics and nondestructive testing and evaluation in various industrial applications.

Advancing Breast Tissue Diagnosis: Compact Photoacoustic Sensing Instrument Unveiled

Image Credit: Andrei_R/ShutterStock 

How is Photoacoustics Used in the Field?

The PA method involves exciting biological samples using a nanosecond pulsed laser. The excitation leads to a temperature excursion, and the resulting non-radiative dissipation produces ultrasound waves.

A probe, usually an ultrasound transducer, detects these acoustic waves, forming the PA signal. This signal, captured in the time domain, reflects the sample's signature based on its optical absorption and tissue density. The acoustic spectra of the signal, revealing these characteristics, can be acquired through Fourier transform. The amplitude of the PA signal corresponds to the optical absorption of the sample, while the time delay is employed to ascertain the distance of the biological sample.

Photoacoustic Technique for Volumetric Vasculature Imaging of Breast Tissue

Volumetric vasculature imaging of breast tissue has emerged as an innovative diagnostic procedure facilitated by three-dimensional PA images using high-acoustic impedance transducers (HATs). A recent article published in Photonics highlights how this technique enables the visualization and assessment of blood vessels within breast tissue, providing valuable insights for detecting and characterizing breast lesions.

A research team conducted human breast imaging based on this principle using a 128-element HAT with a center frequency of 5 MHz. The piezo elements were arranged in a spiral distribution on the probe's hemispherical surface, with a radius of 100 mm.

PA images were acquired from a healthy volunteer by illuminating a 20 mJ pulsed laser at a wavelength of 800 nm. The total data acquisition time was 24 seconds, covering a Field of View (FOV) of 64 × 50 mm2. The resulting images provided visualization of 3D vascular networks up to a depth of 40 mm.

To overcome challenges related to respiratory distortion and improve tumor detection in the breast, a fast PA imaging (PAI) system has been recently developed. This system can capture whole breast images within a single breath-hold, addressing issues associated with lengthy scanning times.

Analysis of PA images from seven breast cancer patients indicated higher blood vessel densities in tumor regions. This is particularly relevant for patients with dense breast tissue, where conventional X-Ray mammography may face limitations. PAI has shown significant potential for diagnosing malignant regions with high sensitivity, offering promise in enhancing breast cancer detection, especially in cases involving dense breast tissue.

Uses of Hand-held PA Systems in Breast Conservation Surgery

Breast-conserving surgery (BCS) is a common approach employed in 60–70 % of breast cancer patients. The objective of BCS is to excise all tumor tissue along with a margin of healthy tissue, aiming to preserve the cosmetic appearance of the breast. Unfortunately, approximately 19 % of breast cancer patients who have undergone BCS require secondary surgery due to incomplete tumor removal.

Imaging techniques play a crucial role in overcoming the limitations of sparse tissue sampling, offering a comprehensive visualization of the disease extent. PAI has demonstrated the potential to distinguish between cancerous and healthy tissue.

In a recent article published in Photoacoustics, a team of researchers explored the feasibility of a compact hand-held PAI probe tailored for breast cancer margin imaging, focusing on lipid content differences. Notably, this probe was designed with enhanced sensitivity to bulk tissue compared to other hand-held PAI probes.

When imaging a breast cancer lumpectomy specimen phantom, strong PA signals were observed in regions containing lipids. Comparative analysis with a full PA system revealed that the images captured with the hand-held PA probe exhibited higher signal-to-noise and less blurring than those obtained with the near full-view PA system.

The prototype hand-held PAI probe successfully identified hypo-intense features, suggesting its potential for detecting residual cancerous tissue. Existing hand-held tools for breast cancer margin assessment often provide binary outputs (yes/no) and limited tissue sampling, lacking depth discrimination. In contrast, the hand-held PAI probe offers a continuous range of image contrast at various depths from the surface.

Latest Compact Diode-Laser PA Sensing Instrument for Breast Tissue Diagnosis

A compact case design for laser diodes has been developed and published in the Journal of Biomedical Optics, along with an in-house pulsed current supply unit to power the laser diodes, generating a 25 ns current pulse at 20 kHz. The casing accommodates up to five current-controlled laser diodes. The optical power of the laser diodes was characterized using a photodiode (PD) system. The PA sensing technique aims to investigate the mechano-biological characteristics of biological tissues, encompassing factors like elasticity and density.

In an in vitro experiment using the PA Spectral Response (PASR) technique, archived formalin-fixed breast tissue samples were investigated. The system examined fibrocystic breast disease tissue (B1) and normal breast parenchyma (B2) samples. Eight samples were collected, including normal and diseased tissues from four different patients.

The average dominant peak (fp) and midband fit (MF) of normal breast tissue were between 0.26 ± 0.005 MHz and 1.45 ± 0.43 MHz. In contrast, the dominant frequency peak and MF of non-tumor fibrosis breast disease tissue were 1.66 ± 0.23 MHz and 2.04 ± 0.44 MHz, respectively.

The sections from B1 exhibited typical features of fibrocystic breast disease, including areas of stromal fibrosis with abundant extracellular collagenous matrix, resulting in increased tissue density. Cystic dilatation of the ducts and acini of terminal ductal lobular units, increased glandular elements in the form of adenosis, and mild epitheliosis of the acini were also observed, contributing to increased cellularity and tissue density.

These findings highlight the potential of the PASR technique in characterizing tissues through parameters such as spectral energy, dominant frequency peaks, and correlation with physical properties. These findings underscore the possible clinical applications of PASR in diagnosing and investigating different pathological conditions. Additional research and developments in PASR, including the incorporation of advanced signal processing techniques and high-frequency transducers, could enhance its capabilities for real-time and in vivo studies, broadening its clinical utility.

How is Machine Learning Used for the Optimization of PA Spectroscopy Techniques?

PA Spectroscopy (PAS) is often used in biomedical diagnostics due to its ease of use, superior sensitivity compared to conventional methods, and ability to provide accurate results.

The design and operational results of a novel chamber-integrated PA probe have been highlighted in ACS Sensors. The technique has been optimized for successfully monitoring breast tumor progression in mice. Breast tumors were induced in nude mice by injecting MCF-7 cells, and PA spectra were recorded at different time points (day 0, 5, 10, 15, and 20) of tumor progression in the same animals. The recorded PA spectra underwent preprocessing, wavelet transformation, and filter-based feature selection using the minimum redundancy maximum relevance (mRMR) algorithm.

The classification models demonstrated 100 % specificity, with sensitivities of 95 %, 100 %, 92.5 %, and 85 % for the time points on days 5, 10, 15, and 20, respectively. These findings indicate the potential of using PA signal-based classification for tracking breast tumor progression in a preclinical model. The PA signal contains valuable information about the biochemical changes linked to disease progression, highlighting its translational strength in early disease diagnosis.

Continuous advancements are being made in the field of PA sensing for biomedical sensing, especially for breast diagnosis. With the implementation of AI algorithms and enhancements in sensing mechanisms, the sensitivity of PA instruments is improving drastically, thereby solidifying its position as the most efficient technique for breast tissue diagnosis.

More from AZoOptics: Photoacoustic Imaging for Life Sciences

References and Further Reading

Optics.org. (2024). Compact photoacoustic sensing instrument characterizes breast tissue. [Online] Optics.org. Available at: https://optics.org/news/15/2/23 [Accessed 25 February 2024].

Lee, H., et al. (2023). A Review on the Roles of Photoacoustic Imaging for Conventional and Novel Clinical Diagnostic Applications. Photonics. doi.org/10.3390/photonics10080904

Rascevska, E., et al. (2023). Investigating the feasibility of a hand-held photoacoustic imaging probe for margin assessment during breast-conserving surgery. Photoacoustics. doi.org/10.1016/j.pacs.2022.100424

Khan, S., et al. (2024). Development of a cost-effective compact diode-laser-based photoacoustic sensing instrument for breast tissue diagnosis. Journal of Biomedical Optics. doi.org/10.1117/1.JBO.29.1.017002

Rodrigues, J., et al. (2024). Machine Learning Enabled Photoacoustic Spectroscopy for Noninvasive Assessment of Breast Tumor Progression In Vivo: A Preclinical Study. ACS sensors. doi.org/10.1021/acssensors.3c01085

Disclaimer: The views expressed here are those of the author expressed in their private capacity and do not necessarily represent the views of AZoM.com Limited T/A AZoNetwork the owner and operator of this website. This disclaimer forms part of the Terms and conditions of use of this website.

Ibtisam Abbasi

Written by

Ibtisam Abbasi

Ibtisam graduated from the Institute of Space Technology, Islamabad with a B.S. in Aerospace Engineering. During his academic career, he has worked on several research projects and has successfully managed several co-curricular events such as the International World Space Week and the International Conference on Aerospace Engineering. Having won an English prose competition during his undergraduate degree, Ibtisam has always been keenly interested in research, writing, and editing. Soon after his graduation, he joined AzoNetwork as a freelancer to sharpen his skills. Ibtisam loves to travel, especially visiting the countryside. He has always been a sports fan and loves to watch tennis, soccer, and cricket. Born in Pakistan, Ibtisam one day hopes to travel all over the world.


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