Evaluation of the elastic properties of tissues offers a promising tool for diagnosis, staging, and therapeutic treatments (coupled with continuous monitoring) of several life-threatening diseases, including cancers.^1,2 Mechanical elasticity or stiffness of soft biological tissues is dependent on the microscopic and/or macroscopic structural organization of their constituent molecules,^{2 – 5} whereas changes in the stromal density and molecular texture of biological tissues—which are closely associated with changes in physiological activities resulting from development and progression of the diseases—are correlated with pathophysiological states of tissues.^{6 – 9} In other words, change in mechanical properties (i.e., hardness) of diseased tissues relative to normal background tissue accompanies the development of various lumps and cancerous lesions (many folds⁴ $\sim 50$). Thus, characterization and/or imaging of tissue hardness facilitates a sensitive way (with good contrast) to detect structural changes abnormally deep inside tissue; thus, these changes can be quantified in terms of characteristic (tissue) elastic coefficients, i.e., shear or Young’s modulus, whereas changes in bulk modulus remain insignificant for soft tissues.⁹

A new adaptive weighting method [delay-and-sum-to-delay-standard-deviation factor (DASDSF)] combined with minimum variance (MV) beamforming is introduced in photoacoustic imaging (PAI). Existing MV-based beamformers improve photoacoustic image quality in terms of achieving narrow main lobes and, thus, improving spatial resolution. But, the beamformers give a strong side-lobe signal strength that greatly degrades the reconstructed image contrast. As a feedback weighting factor, DASDSF addresses the persisting side-lobe issue present in MV-beamformed images, i.e., our proposed method is robust against reduction in noises as well as side lobes, and it outperforms MV and MV combined with coherence factor beamformers. Validation studies—being carried out both in numerical simulation and experiments employing a low-cost (16 elements) linear transducer array in a home-built PAI system—demonstrate an excellent performance of the proposed weighting approach in improving SNR, while reducing main-lobe width (i.e., FWHM) and side-lobe signal strength. The study demonstrates that the proposed algorithm holds promise for development of a cost-effective PAI system using a low-cost linear transducer ( ∼ 16 elements against ∼ 128 generally used).

Use of portable and affordable pulse light sources (light emitting diodes (LED) and laser diodes) for tissue illumination offers an opportunity to accelerate the clinical translation of photoacoustic imaging (PAI) technology. However, imaging depth in this case is limited because of low output (optical) power of these light sources. In this work, we developed a noninvasive technique for enhancing strength (amplitude) of photoacoustic (PA) signal. This is a photothermal-based technique in which a continuous wave (CW) optical beam, in addition to short-pulse $\left(~ \mathrm{nsec}\right)$ laser beam, is employed to irradiate and, thus, raise the temperature of sample material selectively over a pre-specified region of interest (we call the process as pre-illumination). The increase in temperature, in turn enhances the PA-signal strength. Experiments were conducted in methylene blue, which is one of the commonly used contrast agents in laboratory research studies, to validate change in temperature and subsequent enhancement of PA-signal strength for the following cases: (1) concentration or optical absorption coefficient of sample, (2) optical power of CW-optical beam, and (3) time duration of pre-illumination. A theoretical hypothesis, being validated by numerical simulation, is presented. To validate the proposed technique for clinical and/or pre-clinical applications (diagnosis and treatments of cancer, pressure ulcers, and minimally invasive procedures including vascular access and fetal surgery), experiments were conducted in tissue-mimicking Agar phantom and ex-vivo animal tissue (chicken breast). Results demonstrate that pre-illumination significantly enhances PA-signal strength (up to $~70\%$ (methylene blue), $~48\%$ (Agar phantom), and $~40\%$ (chicken tissue)). The proposed technique addresses one of the primary challenges in the clinical translation of LED-based PAI systems (more specifically, to obtain a detectable PA-signal from deep-seated tissue targets).

Photoacoustic imaging offers optical contrast images of human tissue at acoustic resolution, making it valuable for diverse clinical applications. However, quantifying tissue composition via optical contrast remains challenging due to the unknown light fluence within the tissue. Here, we propose a method that leverages known chromophores (e.g., arterial blood) to improve the accuracy of quantitative photoacoustic imaging. By using the optical properties of a known chromophore as a fluence marker and integrating it into the optical inversion process, we can estimate the unknown fluence within the tissue. Experimentally, we demonstrate that this approach successfully recovers both the spectral shape and magnitude of the optical absorption coefficient of an unknown chromophore. Additionally, we show that the fluence marker method enhances conventional optical inversion techniques, specifically (i) a straightforward iterative approach and (ii) a gradient-based method. Our results indicate an improvement in accuracy of up to 24.4% when comparing optical absorption recovery with and without the fluence marker. Finally, we present the method’s performance and illustrate its applications in carotid plaque quantification.