SignificancePhotoacoustic imaging (PAI) is an emerging technology that holds high promise in a wide range of clinical applications, but standardized methods for system testing are lacking, impeding objective device performance evaluation, calibration, and inter-device comparisons. To address this shortfall, this tutorial offers readers structured guidance in developing tissue-mimicking phantoms for photoacoustic applications with potential extensions to certain acoustic and optical imaging applications.AimThe tutorial review aims to summarize recommendations on phantom development for PAI applications to harmonize efforts in standardization and system calibration in the field.ApproachThe International Photoacoustic Standardization Consortium has conducted a consensus exercise to define recommendations for the development of tissue-mimicking phantoms in PAI.ResultsRecommendations on phantom development are summarized in seven defined steps, expanding from (1) general understanding of the imaging modality, definition of (2) relevant terminology and parameters and (3) phantom purposes, recommendation of (4) basic material properties, (5) material characterization methods, and (6) phantom design to (7) reproducibility efforts.ConclusionsThe tutorial offers a comprehensive framework for the development of tissue-mimicking phantoms in PAI to streamline efforts in system testing and push forward the advancement and translation of the technology.
SignificanceThe estimation of tissue optical properties using diffuse optics has found a range of applications in disease detection, therapy monitoring, and general health care. Biomarkers derived from the estimated optical absorption and scattering coefficients can reflect the underlying progression of many biological processes in tissues.AimComplex light–tissue interactions make it challenging to disentangle the absorption and scattering coefficients, so dedicated measurement systems are required. We aim to help readers understand the measurement principles and practical considerations needed when choosing between different estimation methods based on diffuse optics.ApproachThe estimation methods can be categorized as: steady state, time domain, time frequency domain (FD), spatial domain, and spatial FD. The experimental measurements are coupled with models of light–tissue interactions, which enable inverse solutions for the absorption and scattering coefficients from the measured tissue reflectance and/or transmittance.ResultsThe estimation of tissue optical properties has been applied to characterize a variety of ex vivo and in vivo tissues, as well as tissue-mimicking phantoms. Choosing a specific estimation method for a certain application has to trade-off its advantages and limitations.ConclusionOptical absorption and scattering property estimation is an increasingly important and accessible approach for medical diagnosis and health monitoring.
SignificancePhotoacoustic imaging (PAI) promises to measure spatially resolved blood oxygen saturation but suffers from a lack of accurate and robust spectral unmixing methods to deliver on this promise. Accurate blood oxygenation estimation could have important clinical applications from cancer detection to quantifying inflammation.AimWe address the inflexibility of existing data-driven methods for estimating blood oxygenation in PAI by introducing a recurrent neural network architecture.ApproachWe created 25 simulated training dataset variations to assess neural network performance. We used a long short-term memory network to implement a wavelength-flexible network architecture and proposed the Jensen–Shannon divergence to predict the most suitable training dataset.ResultsThe network architecture can flexibly handle the input wavelengths and outperforms linear unmixing and the previously proposed learned spectral decoloring method. Small changes in the training data significantly affect the accuracy of our method, but we find that the Jensen–Shannon divergence correlates with the estimation error and is thus suitable for predicting the most appropriate training datasets for any given application.ConclusionsA flexible data-driven network architecture combined with the Jensen–Shannon divergence to predict the best training data set provides a promising direction that might enable robust data-driven photoacoustic oximetry for clinical use cases.
Longitudinal characterisation of the tumour vascular response to radiotherapy is essential for understanding the role of oxygenation and microvascular disruption in response to therapy. Using multi-scale in vivo photoacoustic imaging (PAI), we assessed early response to two hypofractionated radiotherapy schemes in two human breast cancer models. Mesoscopic and multispectral tomographic photoacoustic imaging was performed 24h pre-, post-radiotherapy, and at endpoint. PAI biomarkers were validated ex vivo with multiplex immunofluorescence using a 20-plex panel developed specifically for vascular response assessment at sub-cellular resolution. PAI captured radiotherapy response, revealing the differential effect between radiotherapy schemes and models with different hypoxia phenotypes.
Photoacoustic imaging holds promise in clinical applications, but lacks standardized testing methods. To overcome this, the International Photoacoustic Standardization Consortium (IPASC) assessed the fabrication reproducibility of a stable tissue-mimicking phantom material in an international multicenter study (n>15 centers). The material consists of mineral oil, polymer, ink, and titanium dioxide. Participating centers followed a recipe set up by the main site (Cambridge, UK) and returned samples for characterization. The results demonstrate promising reproducibility for acoustic, photoacoustic and optical properties. By performing this study, IPASC hopes to broaden the uptake of a stable phantom material, supporting system validation and testing.
The International Photoacoustic Standardisation Consortium (IPASC) hereby reports the results of a consensus-finding exercise undertaken to agree recommendations for properties of tissue-mimicking phantom materials and their characterization. Guidelines on material properties are given under defined environmental conditions and include, for example, recommendations on optical and acoustic properties, stability, and structural composition. Multi-center studies involving independent fabrication of phantom material batches are encouraged for reproducibility and verification of properties within acceptable ranges. The recommendations aim to support researchers and manufacturers to develop phantoms that facilitate system performance assessment, inter-device comparisons, and system optimization, ultimately advancing photoacoustic technology.
Longitudinal mesoscopic photoacoustic imaging of vascular networks requires accurate image co-registration to assess local changes in growing tumours, but remains challenging due to sparsity of data and scan-to-scan variability. Here, we compared a set of 5 curated co-registration methods applied to 49 pairs of vascular images of mouse ears and breast cancer xenografts. Images were segmented using a generative adversarial network and pairs of images and/or segmentations were fed into the 5 tested algorithms. We show the feasibility of co-registering vascular networks accurately using a range of quality metrics, taking a step towards longitudinal characterization of those complex structures.
International efforts to standardize emerging biomedical imaging approaches, such as photoacoustic imaging (PAI), require stable physical phantoms to enable routine quality control and robust performance evaluation across devices. Addressing this necessity, the International Photoacoustic Standardization Consortium (IPASC) has undertaken a consensus-finding exercise to establish recommendations for the properties of tissue-mimicking phantom materials and their characterization in the field of PAI. The manufacturing reproducibility of a stable copolymer-in-oil tissue-mimicking material fulfilling these recommendations was tested in an international multi-center study involving n=18 different partner sites. Here, the progress made toward these standardization efforts is outlined, highlighting prospects, challenges, and future trajectories.
SignificancePhotoacoustic imaging (PAI) provides contrast based on the concentration of optical absorbers in tissue, enabling the assessment of functional physiological parameters such as blood oxygen saturation (sO2). Recent evidence suggests that variation in melanin levels in the epidermis leads to measurement biases in optical technologies, which could potentially limit the application of these biomarkers in diverse populations.AimTo examine the effects of skin melanin pigmentation on PAI and oximetry.ApproachWe evaluated the effects of skin tone in PAI using a computational skin model, two-layer melanin-containing tissue-mimicking phantoms, and mice of a consistent genetic background with varying pigmentations. The computational skin model was validated by simulating the diffuse reflectance spectrum using the adding-doubling method, allowing us to assign our simulation parameters to approximate Fitzpatrick skin types. Monte Carlo simulations and acoustic simulations were run to obtain idealized photoacoustic images of our skin model. Photoacoustic images of the phantoms and mice were acquired using a commercial instrument. Reconstructed images were processed with linear spectral unmixing to estimate blood oxygenation. Linear unmixing results were compared with a learned unmixing approach based on gradient-boosted regression.ResultsOur computational skin model was consistent with representative literature for in vivo skin reflectance measurements. We observed consistent spectral coloring effects across all model systems, with an overestimation of sO2 and more image artifacts observed with increasing melanin concentration. The learned unmixing approach reduced the measurement bias, but predictions made at lower blood sO2 still suffered from a skin tone-dependent effect.ConclusionPAI demonstrates measurement bias, including an overestimation of blood sO2, in higher Fitzpatrick skin types. Future research should aim to characterize this effect in humans to ensure equitable application of the technology.
Standard-of-care endoscopy and laparoscopy require multiple cameras to enable molecular imaging, which leads to challenges of 3D image registration and overlay. To address this, we are developing a targeted multispectral imaging (MSI) camera using custom multispectral filter arrays integrated onto image sensors. The design augments RGB-Bayer filters with sub-pixel narrowband filters, thereby maintaining white-light imaging through pixel binning while adding MSI contrast enhancement. Prototypes were tested by imaging tissue-mimicking phantoms containing blood of varied oxygenation, ICG dye and color charts. Future work will examine the translation potential for chip-on-tip endoscopy.
KEYWORDS: Standards development, Photoacoustic spectroscopy, Photoacoustic imaging, Data acquisition, Outreach programs, Image acquisition, Data modeling, Data analysis, Animal model studies
IPASC organized a roadmapping exercise in 2022 encompassing over 50 participants, which identified eight barriers to clinical translation of PAI: 1) scientific and technological limitations; 2) gaps between technological push and clinical pull; 3) lack of interface with existing standards; 4) poor uptake of phantoms; 5) limited community outreach; 6) poor complementarity of animal models with clinical testing; 7) translation of data-driven methods; and 8) quantitative photoacoustics. Participants defined the scope of each barrier and compared the current state against envisioned goals and outcomes. The resulting roadmaps that define IPASC deliverables in standards development and community engagement will be presented.
Here, we assess the capabilities of photoacoustic imaging (PAI) biomarkers to shed light into perfusion-limited hypoxia, a key driver of tumor malignancy. Using two breast cancer xenograft models, we found that photoacoustic tomography could detect higher fluctuations in oxygen saturation (sO2MSOT) in models with higher disease aggressiveness, supported by an overall lower sO2MSOT and greater spatial heterogeneity in sO2MSOT. Photoacoustic mesoscopy revealed differences in vascular architecture and perfusion dynamics between the models. The results were validated using immunohistochemistry and RNA sequencing, highlighting the potential of PAI to provide non-invasive insight on dynamic phenomena associated with perfusion-limited hypoxia in vivo.
Machine learning-based approaches have shown promise for quantitative photoacoustic oximetry, however, the impact of learned methods is hampered by challenges of usability and generalisability, caused by the strong dependence of learned methods on the training data sets. To address these issues we developed a deep learning-based approach with higher flexibility. The method is trained on a suite of training data sets representing a range of general assumptions. The performance is systematically compared to linear unmixing methods and is validated on in silico, in vitro, and in vivo data representing different use cases.
KEYWORDS: Photoacoustic spectroscopy, Standards development, Data conversion, Photoacoustic imaging, Interfaces, Imaging systems, Data storage, Data analysis, Data acquisition, Computer programming
IPASC has recently published a data format through a consensus-based process which includes a defined metadata structure that describes: (1) PAI system design parameters such as the illumination and detection geometry; (2) container format metadata; and (3) data acquisition including the optical wavelengths, sampling frequency, or timestamps. The container format is designed to store time-series data and internal quality control mechanisms are included to ensure completeness and consistency. Furthermore, a Python-based open-source software application programming interface (API) was developed to facilitate using the IPASC data format and we aim to partner with prospective users to make improvements.
IPASC has initiated the creation of an open-source library for image reconstruction algorithms that are compatible with the IPASC data format. The goals of the project are to: (1) create a testing framework for evaluation of newly developed image reconstruction algorithms to identify their context-dependent strengths and weaknesses; (2) enable insight into algorithm behavior under different conditions; (3) develop an open-access dataset comprising both simulated and experimental data; (4) facilitate collaboration among all stakeholders associated with photoacoustic imaging; and (5) accelerate developments in the field by making the project deliverables available open-source, lowering the barrier of entry for new researchers.
We developed an open-source python toolkit for photoacoustic image (PAI) reconstruction and processing. The toolkit implements GPU-accelerated processing algorithms including preprocessing, image reconstruction (backprojection and model-based) and multispectral analysis (linear spectral unmixing and learned spectral decolouring). We implemented methods for the advanced analysis of longitudinal PA data, including standardised analysis of oxygen-enhanced and dynamic contrast enhanced MSOT data. The toolkit currently works with pre-clinical, clinical and simulated PA systems, integrating with the IPASC open data format, simulated datasets from the SIMPA toolkit and iThera Medical MSOT devices. It can easily be extended to support other algorithms and systems.
SignificanceThe capillaries are the smallest blood vessels in the body, typically imaged using video capillaroscopy to aid diagnosis of connective tissue diseases, such as systemic sclerosis. Video capillaroscopy allows visualization of morphological changes in the nailfold capillaries but does not provide any physiological information about the blood contained within the capillary network. Extracting parameters such as hemoglobin oxygenation could increase sensitivity for diagnosis and measurement of microvascular disease progression.AimTo design, construct, and test a low-cost multispectral imaging (MSI) system using light-emitting diode (LED) illumination to assess relative hemoglobin oxygenation in the nailfold capillaries.ApproachAn LED ring light was first designed and modeled. The ring light was fabricated using four commercially available LED colors and a custom-designed printed circuit board. The experimental system was characterized and results compared with the illumination model. A blood phantom with variable oxygenation was used to determine the feasibility of using the illumination-based MSI system for oximetry. Nailfold capillaries were then imaged in a healthy subject.ResultsThe illumination modeling results were in close agreement with the constructed system. Imaging of the blood phantom demonstrated sensitivity to changing hemoglobin oxygenation, which was in line with the spectral modeling of reflection. The morphological properties of the volunteer capillaries were comparable to those measured in current gold standard systems.ConclusionsLED-based illumination could be used as a low-cost approach to enable MSI of the nailfold capillaries to provide insight into the oxygenation of the blood contained within the capillary network.
Nailfold capillaroscopy is a technique for imaging the capillary bed in the finger nailfold, that is used in the diagnosis of scleroderma. Knowledge of the capillary oxygenation profile would be a substantial advantage in disease evaluation. A compact, low-cost LED-illuminated capillaroscopy system was conceived based on inexpensive parts and optical hardware. The system uses a compact Raspberry Pi to control a custom-designed LED ring light, with white-light LEDs interleaved with three narrowband LEDs, and a Raspberry Pi camera. Capillary visualisation and distinction of haemoglobin contrast is demonstrated, suggesting future promise for application of multispectral nailfold capillaroscopy in low-resource settings.
We developed refined methods for time-domain measurements of the optical properties of solid homogeneous turbid phantoms. Employing a reliable time-domain reference setup with a stable, narrow, and clean instrument response function and GPU-based Monte-Carlo fitting, 1% accuracy for optical properties seems realistic. An alternative space-enhanced time-domain method that combines spatially resolved amplitude with a time-domain measurement effectively reduced the crosstalk between absorption and scattering. Besides physical phantoms, we explored and characterized a digital phantom that mimics arbitrary time-of-flight distributions via time-dependent attenuation employing a spatial light modulator and a dedicated multi-fiber delay unit. We discuss potential applications in performance tests.
The current lack of uniformity in photoacoustic imaging (PAI) data formats hampers inter-device data exchange and comparison. Based on the proposed standardized metadata format of the International Photoacoustic Standardization Consortium (IPASC), IPASC’s Data Acquisition and Management theme has now developed a prototype python software to transform photoacoustic time series data from proprietary data formats into a standardised HDF5 format. The tool provides a centralised application programming interface for vendor-specific conversion module implementation and is available open-source under a commercially friendly licence (BSD-3). By providing this tool, the IPASC hopes to facilitate PAI data management, thereby supporting future developments of the technology.
KEYWORDS: Photoacoustic imaging, Monte Carlo methods, Skin, Tissues, Tissue optics, Blood, Systems modeling, In vivo imaging, In vitro testing, Chromophores
Spectral colouring severely affects quantification in photoacoustic imaging, impacting the biological interpretation of the output imaging biomarkers. Melanin is a particularly strong optical absorber in the near infrared wavelength range that exhibits substantial variation in concentration according to skin tone. Here, Monte-Carlo simulations of light transport in a computational skin phantom were carried out to establish the effects of quantifying blood oxygenation at different melanin concentrations. These results were validated with a tissue-mimicking phantom. The results demonstrated that raised melanin concentration in the epidermis significantly affects quantification of haemoglobin concentration and oxygenation with photoacoustic imaging.
Significance: Photoacoustic imaging (PAI) enables the detection of blood hemoglobin (HB) concentration and oxygenation (sO2) with high contrast and resolution. Despite the heavy use of photoacoustically determined total hemoglobin (THb) and oxygenation (sO2) biomarkers in PAI research, their relationship with underlying biochemical blood parameters and the impact of intra- and interspecies genetic variability have yet to be established.
Aim: To explore the relationship between THb and sO2 photoacoustic biomarkers and the underlying biochemical blood parameters in a species-specific manner.
Approach: Experiments were performed on blood in vitro using tissue-mimicking agar phantoms. Blood was extracted from mouse, rat, human, and naked mole-rat (Heterocephalus glaber), anticoagulated in ethylenediaminetetraacetic acid, and measured within 48 h. THb and sO2 were measured using a commercial photoacoustic tomography system (InVision 128, iThera Medical GmBH). Biochemical blood parameters such as HB concentration (g/dL), hematocrit (HCT, %), and red blood cell (RBC) count (μL − 1) were assessed using a hematology analyzer (Mythic 18 Vet, Woodley Equipment).
Results: A significant correlation was observed between THb and biochemical HB, HCT, and RBC in mouse and rat blood. Moreover, PAI accurately recapitulated interspecies variations in HB and HCT between mouse and rat blood and resolved differences in the oxygen dissociation curves measured using sO2 between human, mouse, and rat. With these validation data in hand, we applied PAI to studies of blood obtained from naked mole-rats and could confirm the high oxygen affinity of this species in comparison to other rodents of similar size.
Conclusions: Our results demonstrate the high sensitivity of photoacoustically determined hemoglobin biomarkers toward species-specific variations in vitro.
To accelerate the clinical translation of photoacoustic (PA) imaging, IPASC aims to provide open and publicly available reference datasets for testing of data reconstruction and spectral processing algorithms in a widely accepted data format. The International Photoacoustic Standardisation Consortium (IPASC) has identified and agreed on a list of essential metadata parameters to describe raw time series PA data and used it to develop an initial prototype of a standardized PA data format. We aim to apply the proposed format in an open database that provides reference datasets for testing of processing algorithms, thereby facilitating and advancing PA research and translation.
The International Photoacoustic Standardisation Consortium (IPASC) emerged from SPIE 2018, established to drive consensus on photoacoustic system testing. As photoacoustic imaging (PAI) matures from research laboratories into clinical trials, it is essential to establish best-practice guidelines for photoacoustic image acquisition, analysis and reporting, and a standardised approach for technical system validation. The primary goal of the IPASC is to create widely accepted phantoms for testing preclinical and clinical PAI systems. To achieve this, the IPASC has formed five working groups (WGs). The first and second WGs have defined optical and acoustic properties, suitable materials, and configurations of photoacoustic image quality phantoms. These phantoms consist of a bulk material embedded with targets to enable quantitative assessment of image quality characteristics including resolution and sensitivity across depth. The third WG has recorded details such as illumination and detection configurations of PAI instruments available within the consortium, leading to proposals for system-specific phantom geometries. This PAI system inventory was also used by WG4 in identifying approaches to data collection and sharing. Finally, WG5 investigated means for phantom fabrication, material characterisation and PAI of phantoms. Following a pilot multi-centre phantom imaging study within the consortium, the IPASC settled on an internationally agreed set of standardised recommendations and imaging procedures. This leads to advances in: (1) quantitative comparison of PAI data acquired with different data acquisition and analysis methods; (2) provision of a publicly available reference data set for testing new algorithms; and (3) technical validation of new and existing PAI devices across multiple centres.
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