Evaluation of Fluence Correction Algorithms in Multispectral Photoacoustic Imaging

Quantitative Optical Imaging of Oxygen in Brain Vasculature

The intimate relationship between neuronal activity and cerebral oxygenation underpins fundamental brain functions like cognition, sensation, and motor control. Optical imaging offers a noninvasive approach to assess brain oxygenation and often serves as an indirect proxy for neuronal activity. However, deciphering neurovascular coupling─the intricate interplay between neuronal activity, blood flow, and oxygen delivery─necessitates independent, high spatial resolution, and high temporal resolution measurements of both microvasculature oxygenation and neuronal activation. This Perspective examines the established optical techniques employed for brain oxygen imaging, specifically functional near-infrared spectroscopy, photoacoustic imaging, optical coherence tomography, and two-photon phosphorescent lifetime microscopy, highlighting their fundamental principles, strengths, and limitations. Several other emerging optical techniques are also introduced. Finally, we discuss key technological challenges and future directions for quantitative optical oxygen imaging, paving the way for a deeper understanding of oxygen metabolism in the brain.

Challenges and advances in two-dimensional photoacoustic computed tomography: a review

Significance

Photoacoustic computed tomography (PACT), a hybrid imaging modality combining optical excitation with acoustic detection, has rapidly emerged as a prominent biomedical imaging technique.

Aim

We review the challenges and advances of PACT, including (1) limited view, (2) anisotropy resolution, (3) spatial aliasing, (4) acoustic heterogeneity (speed of sound mismatch), and (5) fluence correction of spectral unmixing.

Approach

We performed a comprehensive literature review to summarize the key challenges in PACT toward practical applications and discuss various solutions.

Results

There is a wide range of contributions from both industry and academic spaces. Various approaches, including emerging deep learning methods, are proposed to improve the performance of PACT further.

Conclusions

We outline contemporary technologies aimed at tackling the challenges in PACT applications.

Quantitative photoacoustic tomography: modeling and inverse problems

Significance

Quantitative photoacoustic tomography (QPAT) exploits the photoacoustic effect with the aim of estimating images of clinically relevant quantities related to the tissue's optical absorption. The technique has two aspects: an acoustic part, where the initial acoustic pressure distribution is estimated from measured photoacoustic time-series, and an optical part, where the distributions of the optical parameters are estimated from the initial pressure.

Aim

Our study is focused on the optical part. In particular, computational modeling of light propagation (forward problem) and numerical solution methodologies of the image reconstruction (inverse problem) are discussed.

Approach

The commonly used mathematical models of how light and sound propagate in biological tissue are reviewed. A short overview of how the acoustic inverse problem is usually treated is given. The optical inverse problem and methods for its solution are reviewed. In addition, some limitations of real-life measurements and their effect on the inverse problems are discussed.

Results

An overview of QPAT with a focus on the optical part was given. Computational modeling and inverse problems of QPAT were addressed, and some key challenges were discussed. Furthermore, the developments for tackling these problems were reviewed. Although modeling of light transport is well-understood and there is a well-developed framework of inverse mathematics for approaching the inverse problem of QPAT, there are still challenges in taking these methodologies to practice.

Conclusions

Modeling and inverse problems of QPAT together were discussed. The scope was limited to the optical part, and the acoustic aspects were discussed only to the extent that they relate to the optical aspect.

Review of Deep Learning Approaches for Interleaved Photoacoustic and Ultrasound (PAUS) Imaging

Photoacoustic (PA) imaging provides optical contrast at relatively large depths within the human body, compared to other optical methods, at ultrasound (US) spatial resolution. By integrating real-time PA and US (PAUS) modalities, PAUS imaging has the potential to become a routine clinical modality bringing the molecular sensitivity of optics to medical US imaging. For applications where the full capabilities of clinical US scanners must be maintained in PAUS, conventional limited view and bandwidth transducers must be used. This approach, however, cannot provide high-quality maps of PA sources, especially vascular structures. Deep learning (DL) using data-driven modeling with minimal human design has been very effective in medical imaging, medical data analysis, and disease diagnosis, and has the potential to overcome many of the technical limitations of current PAUS imaging systems. The primary purpose of this article is to summarize the background and current status of DL applications in PAUS imaging. It also looks beyond current approaches to identify remaining challenges and opportunities for robust translation of PAUS technologies to the clinic.

Ultrasound-guided Photoacoustic image Annotation Toolkit in MATLAB (PHANTOM) for preclinical applications

Depth-dependent fluence-compensation in photoacoustic (PA) imaging is paramount for accurate quantification of chromophores from deep tissues. Here we present a user-friendly toolkit named PHANTOM (PHotoacoustic ANnotation TOolkit for MATLAB) that includes a graphical interface and assists in the segmentation of ultrasound-guided PA images. We modelled the light source configuration with Monte Carlo eXtreme and utilized 3D segmented tissues from ultrasound to generate fluence maps to depth compensate PA images. The methodology was used to analyze PA images of phantoms with varying blood oxygenation and results were validated with oxygen electrode measurements. Two preclinical models, a subcutaneous tumor and a calcified placenta, were imaged and fluence-compensated using the PHANTOM toolkit and the results were verified with immunohistochemistry. The PHANTOM toolkit provides scripts and auxiliary functions to enable biomedical researchers not specialized in optical imaging to apply fluence correction to PA images, enhancing accessibility of quantitative PAI for researchers in various fields.

Phantoms for evaluating the impact of skin pigmentation on photoacoustic imaging and oximetry performance

Recent reports have raised concerns of potential racial disparities in performance of optical oximetry technologies. To investigate how variable epidermal melanin content affects performance of photoacoustic imaging (PAI) devices, we developed plastisol phantoms combining swappable skin-mimicking layers with a breast phantom containing either India ink or blood adjusted to 50-100% SO2 using sodium dithionite. Increasing skin pigmentation decreased maximum imaging depth by up to 25%, enhanced image clutter, and increased root-mean-square error in SO2 from 8.0 to 17.6% due to signal attenuation and spectral coloring effects. This phantom tool can aid in evaluating PAI device robustness to ensure high performance in all patients.

A review of a strategic roadmapping exercise to advance clinical translation of photoacoustic imaging: From current barriers to future adoption

Photoacoustic imaging (PAI), also referred to as optoacoustic imaging, has shown promise in early-stage clinical trials in a range of applications from inflammatory diseases to cancer. While the first PAI systems have recently received regulatory approvals, successful adoption of PAI technology into healthcare systems for clinical decision making must still overcome a range of barriers, from education and training to data acquisition and interpretation. The International Photoacoustic Standardisation Consortium (IPASC) undertook an community exercise in 2022 to identify and understand these barriers, then develop a roadmap of strategic plans to address them. Here, we outline the nature and scope of the barriers that were identified, along with short-, medium- and long-term community efforts required to overcome them, both within and beyond the IPASC group.

Azimuth mapping of fibrous tissue in linear dichroism-sensitive photoacoustic microscopy

Photoacoustic imaging (PAI) has emerged as a molecular-selective imaging technology based on optical absorption contrast. Dichroism-sensitive photoacoustic (DS-PA) imaging has been reported, where the absorption coefficient has a vector characteristic, featuring dimensions of contrast in polarization and wavelength. Herein, we present a DS-PA microscopy (DS-PAM) system that implements optical anisotropy contrast and molecular selectivity. Moreover, we propose mathematical solutions to fully derive dichroic properties. A wavelength for the PAI of collagenous tissue was used, and the proposed algorithms were validated using linear dichroic materials. We successfully mapped dichroic information in fibrous tissue imaging based on the degree of anisotropy and axis orientation, and also deduced mechanical assessment from the tissue arrangement. The proposed DS-PAM system and algorithms have great potential in various diagnostic fields using polarimetry, such as musculoskeletal and cardiovascular systems.

Evaluation of Cholesterol Thickness of Blood Vessels Using Photoacoustic Technology

One of the primary indicators of plaque vulnerability is the lipid composition of atherosclerotic plaques. Therefore, the medical industry requires a method to evaluate necrotic nuclei in atherosclerosis imaging with sensitivity. In this regard, photoacoustic imaging is a plaque detection method that provides chemical information on lipids and cholesterol thickness in the arterial walls of the patient. This aspect aims to increase the low-frequency axial resolution by developing a new photoacoustic-based system. A photoacoustic system has been developed to detect the cholesterol thickness of the blood vessels to observe the progression of plaque in the heart's blood vessels. The application of the coherent photoacoustic discontinuous correlation tomography technique, which is based on a novel signal processing, significantly increased the cholesterol oleate's sensitivity to plaque necrosis. By enhancing the quality of thickness detection, the system for measuring the thickness of cholesterol in blood vessels has been reduced to approximately 23 microns. The results show that the phase spectrum peaked at 100 Hz at 58.66 degrees, and at 400 Hz, the phase spectrum was 46.37 degrees. The minimum amplitude is 1.95 at 100 Hz and 17.67 at 400 Hz. In conclusion, it can be stated that photoacoustic imaging as a method based on new technologies is of great importance in medical research, which is based on the use of nonionizing radiation to perform diagnostic processes and measure different types of body tissues.

Photoacoustic imaging to monitor outcomes during hyperbaric oxygen therapy: validation in a small cohort and case study in a bilateral chronic ischemic wound

Hyperbaric oxygen therapy (HBO2) is a common therapeutic modality that drives oxygen into hypoxic tissue to promote healing. Here, ten patients undergoing HBO2 underwent PA oximetry of the left radial artery and forearm pre- and post-HBO2; this cohort validated the use of PA imaging in HBO2. There was a significant increase in radial artery oxygenation after HBO2 (p = 0.002) in the validation cohort. We also include a case study: a non-diabetic male in his 50s (HB 010) presenting with bilateral ischemic and gangrenous wounds. HB 010 showed higher perfusion and oxygen saturation on the right foot than the left after HBO2 which correlated with independent surgical observations. Imaging assisted with limb salvage treatment. Hence, this work shows that PA imaging can measure changes in arterial oxygen saturation due to HBO2; it can also produce 3D maps of tissue oxygenation and evaluate response to therapy during HBO2.

The IPASC data format: A consensus data format for photoacoustic imaging

Photoacoustic imaging (PAI) is an emerging modality that has shown promise for improving patient management in a range of applications. Unfortunately, the current lack of uniformity in PAI data formats compromises inter-user data exchange and comparison, which impedes: technological progress; effective research collaboration; and efforts to deliver multi-centre clinical trials. To overcome this challenge, the International Photoacoustic Standardisation Consortium (IPASC) has established a data format with a defined consensus metadata structure and developed an open-source software application programming interface (API) to enable conversion from proprietary file formats into the IPASC format. The format is based on Hierarchical Data Format 5 (HDF5) and designed to store photoacoustic raw time series data. Internal quality control mechanisms are included to ensure completeness and consistency of the converted data. By unifying the variety of proprietary data and metadata definitions into a consensus format, IPASC hopes to facilitate the exchange and comparison of PAI data.

Suite of 3D test objects for performance assessment of hybrid photoacoustic-ultrasound breast imaging systems

SIGNIFICANCE

During the development and early testing phases of new photoacoustic (PA) breast imaging systems, several choices need to be made in aspects of system design and measurement sequences. Decision-making can be complex for state-of-the-art systems such as 3D hybrid photoacoustic-ultrasound (PA-US) breast imagers intended for multispectral quantitative imaging. These systems have a large set of design choices and system settings that affect imaging performance in different ways and often require trade-offs. Decisions have to be made carefully as they can strongly influence the imaging performance.

AIM

A systematic approach to assess the influence of various choices on the imaging performance in carefully controlled laboratory situations is crucial before starting with human studies. Test objects and phantoms are used for first imaging studies, but most reported structures have a 2D geometry and are not suitable to assess all the image quality characteristics (IQCs) of 3D hybrid PA-US systems.

APPROACH

Our work introduces a suite of five test objects designed for hybrid PA-US systems with a 3D detection aperture. We present the test object designs and production protocols and explain how they can be used to study various performance measures. To demonstrate the utility of the developed objects, measurements are made with an existing tomographic PA system.

RESULTS

Two test objects were developed for measurements of the US detectors' impulse responses and light distribution on the breast surface. Three others were developed to assess image quality and quantitative accuracy of the PA and US modes. Three of the five objects were imaged to demonstrate their use.

CONCLUSIONS

The developed test objects allow one to study influences of various choices in design and system settings. With this, IQCs can be assessed as a function of measurement sequence settings for the PA and US modes in a controlled way. Systematic studies and measurements using these objects will help to optimize various system settings and measurement protocols in laboratory situations before embarking on human studies.

Review of consensus test methods in medical imaging and current practices in photoacoustic image quality assessment

SIGNIFICANCE

Photoacoustic imaging (PAI) is a powerful emerging technology with broad clinical applications, but consensus test methods are needed to standardize performance evaluation and accelerate translation.

AIM

To review consensus image quality test methods for mature imaging modalities [ultrasound, magnetic resonance imaging (MRI), x-ray CT, and x-ray mammography], identify best practices in phantom design and testing procedures, and compare against current practices in PAI phantom testing.

APPROACH

We reviewed scientific papers, international standards, clinical accreditation guidelines, and professional society recommendations describing medical image quality test methods. Observations are organized by image quality characteristics (IQCs), including spatial resolution, geometric accuracy, imaging depth, uniformity, sensitivity, low-contrast detectability, and artifacts.

RESULTS

Consensus documents typically prescribed phantom geometry and material property requirements, as well as specific data acquisition and analysis protocols to optimize test consistency and reproducibility. While these documents considered a wide array of IQCs, reported PAI phantom testing focused heavily on in-plane resolution, depth of visualization, and sensitivity. Understudied IQCs that merit further consideration include out-of-plane resolution, geometric accuracy, uniformity, low-contrast detectability, and co-registration accuracy.

CONCLUSIONS

Available medical image quality standards provide a blueprint for establishing consensus best practices for photoacoustic image quality assessment and thus hastening PAI technology advancement, translation, and clinical adoption.

Polyacrylamide hydrogel phantoms for performance evaluation of multispectral photoacoustic imaging systems

As photoacoustic imaging (PAI) begins to mature and undergo clinical translation, there is a need for well-validated, standardized performance test methods to support device development, quality control, and regulatory evaluation. Despite recent progress, current PAI phantoms may not adequately replicate tissue light and sound transport over the full range of optical wavelengths and acoustic frequencies employed by reported PAI devices. Here we introduce polyacrylamide (PAA) hydrogel as a candidate material for fabricating stable phantoms with well-characterized optical and acoustic properties that are biologically relevant over a broad range of system design parameters. We evaluated suitability of PAA phantoms for conducting image quality assessment of three PAI systems with substantially different operating parameters including two commercial systems and a custom system. Imaging results indicated that appropriately tuned PAA phantoms are useful tools for assessing and comparing PAI system image quality. These phantoms may also facilitate future standardization of performance test methodology.

Deep learning in photoacoustic imaging: a review

SIGNIFICANCE

Photoacoustic (PA) imaging can provide structural, functional, and molecular information for preclinical and clinical studies. For PA imaging (PAI), non-ideal signal detection deteriorates image quality, and quantitative PAI (QPAI) remains challenging due to the unknown light fluence spectra in deep tissue. In recent years, deep learning (DL) has shown outstanding performance when implemented in PAI, with applications in image reconstruction, quantification, and understanding.

AIM

We provide (i) a comprehensive overview of the DL techniques that have been applied in PAI, (ii) references for designing DL models for various PAI tasks, and (iii) a summary of the future challenges and opportunities.

APPROACH

Papers published before November 2020 in the area of applying DL in PAI were reviewed. We categorized them into three types: image understanding, reconstruction of the initial pressure distribution, and QPAI.

RESULTS

When applied in PAI, DL can effectively process images, improve reconstruction quality, fuse information, and assist quantitative analysis.

CONCLUSION

DL has become a powerful tool in PAI. With the development of DL theory and technology, it will continue to boost the performance and facilitate the clinical translation of PAI.

Technical considerations in the Verasonics research ultrasound platform for developing a photoacoustic imaging system

Photoacoustic imaging (PAI) is an emerging functional and molecular imaging technology that has attracted much attention in the past decade. Recently, many researchers have used the vantage system from Verasonics for simultaneous ultrasound (US) and photoacoustic (PA) imaging. This was the motivation to write on the details of US/PA imaging system implementation and characterization using Verasonics platform. We have discussed the experimental considerations for linear array based PAI due to its popularity, simple setup, and high potential for clinical translatability. Specifically, we describe the strategies of US/PA imaging system setup, signal generation, amplification, data processing and study the system performance.

Correction of wavelength-dependent laser fluence in swept-beam spectroscopic photoacoustic imaging with a hand-held probe

Recently, we demonstrated an integrated photoacoustic (PA) and ultrasound (PAUS) system using a kHz-rate wavelength-tunable laser and a swept-beam delivery approach. It irradiates a medium using a narrow laser beam swept at high repetition rate (∼1 kHz) over the desired imaging area, in contrast to the conventional PA approach using broad-beam illumination at a low repetition rate (10-50 Hz). Here, we present a method to correct the wavelength-dependent fluence distribution and demonstrate its performance in phantom studies using a conventional limited view/bandwidth hand-held US probe. We adopted analytic fluence models, extending diffusion theory for the case of a pencil beam obliquely incident on an optically homogenous turbid medium, and developed a robust method to estimate fluence attenuation in the medium using PA measurements acquired from multiple fiber-irradiation positions swept at a kHz rate. We conducted comprehensive simulation tests and phantom studies using well-known contrast-agents to validate the reliability of the fluence model and its spectral corrections.