Multispectral Optoacoustic Tomography (MSOT) of Human Breast Cancer

Photoacoustic imaging in prostate cancer: A new paradigm for diagnosis and management

The global health issue of prostate cancer (PCa) requires better diagnosis and treatment. Photoacoustic imaging (PAI) may change PCa management. This review examines PAI's principles, diagnostic role, and therapeutic guidance. PAI uses optical light excitation and ultrasonic detection for high-resolution functional and molecular imaging. PAI uses endogenous and exogenous contrast agents to distinguish cancerous and benign prostate tissues with greater sensitivity and specificity than PSA testing and TRUS-guided biopsy. In addition to diagnosing, PAI can guide and monitor PCa therapy. Its real-time imaging allows precise biopsies and brachytherapy seed placement. Photoacoustic temperature imaging allows non-invasive monitoring of thermal therapies like cryotherapy, improving treatment precision and success. Transurethral illumination probes, innovative contrast agents, integration with other imaging modalities, and machine learning analysis are being developed to overcome depth and data complexity restrictions. PAI could become an essential tool for PCa diagnosis and therapeutic guidance as the field advances.

Deep learning acceleration of iterative model-based light fluence correction for photoacoustic tomography

Photoacoustic tomography (PAT) is a promising imaging technique that can visualize the distribution of chromophores within biological tissue. However, the accuracy of PAT imaging is compromised by light fluence (LF), which hinders the quantification of light absorbers. Currently, model-based iterative methods are used for LF correction, but they require extensive computational resources due to repeated LF estimation based on differential light transport models. To improve LF correction efficiency, we propose to use Fourier neural operator (FNO), a neural network specially designed for estimating partial differential equations, to learn the forward projection of light transport in PAT. Trained using paired finite-element-based LF simulation data, our FNO model replaces the traditional computational heavy LF estimator during iterative correction, such that the correction procedure is considerably accelerated. Simulation and experimental results demonstrate that our method achieves comparable LF correction quality to traditional iterative methods while reducing the correction time by over 30 times.

Multispectral optoacoustic tomography of benign parotid tumors in vivo: a prospective observational pilot study

Parotid lumps are a heterogeneous group of mainly benign but also malignant tumors. Preoperative imaging does not allow a differentiation between tumor types. Multispectral optoacoustic tomography (MSOT) may improve the preoperative diagnostics. In this first prospective pilot trial the ability of MSOT to discriminate between the two most frequent benign parotid tumors, pleomorphic adenoma (PA) and Warthin tumor (WT) as well as to normal parotid tissue was explored. Six wavelengths (700, 730, 760, 800, 850, 900 nm) and the parameters deoxygenated (HbR), oxygenated (HbO2), total hemoglobin (HbT), and saturation of hemoglobin (sO2) were analyzed. Ten patients with PA and fourteen with WT were included (12/12 female/male; median age: 51 years). For PA, the mean values for all measured wave lengths as well as for the hemoglobin parameters were different for the tumors compared to the healthy parotid (all p < 0.05). The mean MSOT parameters were all significantly higher (all p < 0.05) in the WT compared to healthy parotid gland except for HbT and sO2. Comparing both tumors directly, the mean values of MSOT parameters were not different between PA and WT (all p > 0.05). Differences were seen for the maximal MSOT parameters. The maximal tumor values for 900 nm, HbR, HbT, and sO2 were lower in PA than in WT (all p < 0.05). This preliminary MSOT parotid tumor imaging study showed clear differences for PA or WT compared to healthy parotid tissue. Some MSOT characteristics of PA and WT were different but needed to be explored in larger studies.

Preclinical multi-physiologic monitoring of immediate-early responses to diverse treatment strategies in breast cancer by optoacoustic imaging

Optoacoustic imaging enables the measurement of tissue oxygen saturation (sO2) and blood perfusion while being utilized for detecting tumor microenvironments. Our aim was to employ multispectral optoacoustic tomography (MSOT) to assess immediate-early changes of hemoglobin level and sO2 within breast tumors during diverse treatments. Mouse breast cancer models were allocated into four groups: control, everolimus (EVE), paclitaxel (PTX), and photodynamic therapy (PDT). Hemoglobin was quantified daily, as well as sO2 and blood perfusion were verified by immunohistochemical (IHC) staining. MSOT showed a temporal window of enhanced oxygenation and improved perfusion in EVE and PTX groups, while sO2 consistently remained below baseline in PDT. The same results were obtained for the IHC. Therefore, MSOT can monitor tumor hypoxia and indirectly reflect blood perfusion in a non-invasive and non-labeled way, which has the potential to monitor breast cancer progression early and enable individualized treatment in clinical practice.

Influence of structural moieties in squaraine dyes on optoacoustic signal shape and intensity

Optoacoustic imaging has grown in clinical relevance due to inherent advantages in sensitivity, resolution, and imaging depth, but the development of contrast agents is lacking. This study assesses the influence of structural features of squaraine dyes on optoacoustic activity through computational models, in vitro testing, and in vivo experimentation. The squaraine scaffold was decorated with halogens and side-chain extensions. Extension of side chains and heavy halogenation of squaraines both increased optoacoustic signals individually, although they had a more significant effect in tandem. Density functional theory models suggest that the origin of the increased optoacoustic signal is the increase in transition dipole moment and vibrational entropy, which manifested as increased absorbance in near-infrared region (NIR) wavelengths and decreased fluorescence quantum yield. This study provides insight into the structure-function relationships that will lead guiding principles for optimizing optoacoustic contrast agents. Further developments of squaraines and other agents will further increase the relevance of optoacoustic imaging in a clinical setting.

Current status of optoacoustic breast imaging and future trends in clinical application: is it ready for prime time?

Optoacoustic imaging (OAI) is an emerging field with increasing applications in patients and exploratory clinical trials for breast cancer. Optoacoustic imaging (or photoacoustic imaging) employs non-ionizing, laser light to create thermoelastic expansion in tissues and detect the resulting ultrasonic emission. By combining high optical contrast capabilities with the high spatial resolution and anatomic detail of grayscale ultrasound, OAI offers unique opportunities for visualizing biological function of tissues in vivo. Over the past decade, human breast applications of OAI, including benign/malignant mass differentiation, distinguishing cancer molecular subtype, and predicting metastatic potential, have significantly increased. We discuss the current state of optoacoustic breast imaging, as well as future opportunities and clinical application trends. CLINICAL RELEVANCE STATEMENT: Optoacoustic imaging is a novel breast imaging technique that enables the assessment of breast cancer lesions and tumor biology without the risk of ionizing radiation exposure, intravenous contrast, or radionuclide injection. KEY POINTS: • Optoacoustic imaging (OAI) is a safe, non-invasive imaging technique with thriving research and high potential clinical impact. • OAI has been considered a complementary tool to current standard breast imaging techniques. • OAI combines parametric maps of molecules that absorb light and scatter acoustic waves (like hemoglobin, melanin, lipids, and water) with anatomical images, facilitating scalable and real-time molecular evaluation of tissues.

Signal domain adaptation network for limited-view optoacoustic tomography

Optoacoustic (OA) imaging is based on optical excitation of biological tissues with nanosecond-duration laser pulses and detection of ultrasound (US) waves generated by thermoelastic expansion following light absorption. The image quality and fidelity of OA images critically depend on the extent of tomographic coverage provided by the US detector arrays. However, full tomographic coverage is not always possible due to experimental constraints. One major challenge concerns an efficient integration between OA and pulse-echo US measurements using the same transducer array. A common approach toward the hybridization consists in using standard linear transducer arrays, which readily results in arc-type artifacts and distorted shapes in OA images due to the limited angular coverage. Deep learning methods have been proposed to mitigate limited-view artifacts in OA reconstructions by mapping artifactual to artifact-free (ground truth) images. However, acquisition of ground truth data with full angular coverage is not always possible, particularly when using handheld probes in a clinical setting. Deep learning methods operating in the image domain are then commonly based on networks trained on simulated data. This approach is yet incapable of transferring the learned features between two domains, which results in poor performance on experimental data. Here, we propose a signal domain adaptation network (SDAN) consisting of i) a domain adaptation network to reduce the domain gap between simulated and experimental signals and ii) a sides prediction network to complement the missing signals in limited-view OA datasets acquired from a human forearm by means of a handheld linear transducer array. The proposed method showed improved performance in reducing limited-view artifacts without the need for ground truth signals from full tomographic acquisitions.

Recurrent and convolutional neural networks for sequential multispectral optoacoustic tomography (MSOT) imaging

Multispectral optoacoustic tomography (MSOT) is a beneficial technique for diagnosing and analyzing biological samples since it provides meticulous details in anatomy and physiology. However, acquiring high through-plane resolution volumetric MSOT is time-consuming. Here, we propose a deep learning model based on hybrid recurrent and convolutional neural networks to generate sequential cross-sectional images for an MSOT system. This system provides three modalities (MSOT, ultrasound, and optoacoustic imaging of a specific exogenous contrast agent) in a single scan. This study used ICG-conjugated nanoworms particles (NWs-ICG) as the contrast agent. Instead of acquiring seven images with a step size of 0.1 mm, we can receive two images with a step size of 0.6 mm as input for the proposed deep learning model. The deep learning model can generate five other images with a step size of 0.1 mm between these two input images meaning we can reduce acquisition time by approximately 71%.

Diagnosis of liver fibrosis and liver function reserve through non-invasive multispectral photoacoustic imaging

Liver function reserve (LFR) is the sum of remnant functional hepatic cells after liver injury. In the pathologic process of liver fibrosis (LF), LFR is impaired. LFR assessment can help determine the safe scope of liver resection or drug regimen and predict prognosis of patients with liver disease. Here, we used a photoacoustic imaging (PAI) system to assess LF and LFR in rabbit models. We performed PAI, ultrasound elastography and biopsy for 21 rabbits developing none (n = 6) and LF (n = 15). In vivo indocyanine green (ICG) measurements by PAI showed that LF group presented a significantly attenuated ICG clearance compared to control group, indicating LFR impairment of LF. Another finding was a significantly higher collagen photoacoustic signal intensity value was observed in LF both in vivo and in vitro. Our findings demonstrated that PAI was potentially effective to evaluate LFR and collagen accumulation of LF.

Optical Breast Imaging: A Review of Physical Principles, Technologies, and Clinical Applications

Optical imaging involves the propagation of light through tissue. Current optical breast imaging technologies, including diffuse optical spectroscopy, diffuse optical tomography, and photoacoustic imaging, capitalize on the selective absorption of light in the near-infrared spectrum by deoxygenated and oxygenated hemoglobin. They provide information on the morphological and functional characteristics of different tissues based on their varied interactions with light, including physiologic information on lesion vascular content and anatomic information on tissue vascularity. Fluorescent contrast agents, such as indocyanine green, are used to visualize specific tissues, molecules, or proteins depending on how and where the agent accumulates. In this review, we describe the physical principles, spectrum of technologies, and clinical applications of the most common optical systems currently being used or developed for breast imaging. Most notably, US co-registered photoacoustic imaging and US-guided diffuse optical tomography have demonstrated efficacy in differentiating benign from malignant breast masses, thereby improving the specificity of diagnostic imaging. Diffuse optical tomography and diffuse optical spectroscopy have shown promise in assessing treatment response to preoperative systemic therapy, and photoacoustic imaging and diffuse optical tomography may help predict tumor phenotype. Lastly, fluorescent imaging using indocyanine green dye performs comparably to radioisotope mapping of sentinel lymph nodes and appears to improve the outcomes of autologous tissue flap breast reconstruction.

Efficient Photoacoustic Image Synthesis with Deep Learning

Photoacoustic imaging potentially allows for the real-time visualization of functional human tissue parameters such as oxygenation but is subject to a challenging underlying quantification problem. While in silico studies have revealed the great potential of deep learning (DL) methodology in solving this problem, the inherent lack of an efficient gold standard method for model training and validation remains a grand challenge. This work investigates whether DL can be leveraged to accurately and efficiently simulate photon propagation in biological tissue, enabling photoacoustic image synthesis. Our approach is based on estimating the initial pressure distribution of the photoacoustic waves from the underlying optical properties using a back-propagatable neural network trained on synthetic data. In proof-of-concept studies, we validated the performance of two complementary neural network architectures, namely a conventional U-Net-like model and a Fourier Neural Operator (FNO) network. Our in silico validation on multispectral human forearm images shows that DL methods can speed up image generation by a factor of 100 when compared to Monte Carlo simulations with 5×108 photons. While the FNO is slightly more accurate than the U-Net, when compared to Monte Carlo simulations performed with a reduced number of photons (5×106), both neural network architectures achieve equivalent accuracy. In contrast to Monte Carlo simulations, the proposed DL models can be used as inherently differentiable surrogate models in the photoacoustic image synthesis pipeline, allowing for back-propagation of the synthesis error and gradient-based optimization over the entire pipeline. Due to their efficiency, they have the potential to enable large-scale training data generation that can expedite the clinical application of photoacoustic imaging.

Mitigating Under-Sampling Artifacts in 3D Photoacoustic Imaging Using Res-UNet Based on Digital Breast Phantom

In recent years, photoacoustic (PA) imaging has rapidly grown as a non-invasive screening technique for breast cancer detection using three-dimensional (3D) hemispherical arrays due to their large field of view. However, the development of breast imaging systems is hindered by a lack of patients and ground truth samples, as well as under-sampling problems caused by high costs. Most research related to solving these problems in the PA field were based on 2D transducer arrays or simple regular shape phantoms for 3D transducer arrays or images from other modalities. Therefore, we demonstrate an effective method for removing under-sampling artifacts based on deep neural network (DNN) to reconstruct high-quality PA images using numerical digital breast simulations. We constructed 3D digital breast phantoms based on human anatomical structures and physical properties, which were then subjected to 3D Monte-Carlo and K-wave acoustic simulations to mimic acoustic propagation for hemispherical transducer arrays. Finally, we applied a 3D delay-and-sum reconstruction algorithm and a Res-UNet network to achieve higher resolution on sparsely-sampled data. Our results indicate that when using a 757 nm laser with uniform intensity distribution illuminated on a numerical digital breast, the imaging depth can reach 3 cm with 0.25 mm spatial resolution. In addition, the proposed DNN can significantly enhance image quality by up to 78.4%, as measured by MS-SSIM, and reduce background artifacts by up to 19.0%, as measured by PSNR, even at an under-sampling ratio of 10%. The post-processing time for these improvements is only 0.6 s. This paper suggests a new 3D real time DNN method addressing the sparse sampling problem based on numerical digital breast simulations, this approach can also be applied to clinical data and accelerate the development of 3D photoacoustic hemispherical transducer arrays for early breast cancer diagnosis.

Functional photoacoustic imaging: from nano- and micro- to macro-scale

Functional photoacoustic imaging is a promising biological imaging technique that offers such unique benefits as scalable resolution and imaging depth, as well as the ability to provide functional information. At nanoscale, photoacoustic imaging has provided super-resolution images of the surface light absorption characteristics of materials and of single organelles in cells. At the microscopic and macroscopic scales. photoacoustic imaging techniques have precisely measured and quantified various physiological parameters, such as oxygen saturation, vessel morphology, blood flow, and the metabolic rate of oxygen, in both human and animal subjects. This comprehensive review provides an overview of functional photoacoustic imaging across multiple scales, from nano to macro, and highlights recent advances in technology developments and applications. Finally, the review surveys the future prospects of functional photoacoustic imaging in the biomedical field.

Simultaneous Detection of Multiple Tumor-targeted Gold Nanoparticles in HER2-Positive Breast Tumors Using Optoacoustic Imaging

Purpose To develop optoacoustic, spectrally distinct, actively targeted gold nanoparticle-based near-infrared probes (trastuzumab [TRA], TRA-Aurelia-1, and TRA-Aurelia-2) that can be individually identifiable at multispectral optoacoustic tomography (MSOT) of human epidermal growth factor receptor 2 (HER2)-positive breast tumors. Materials and Methods Gold nanoparticle-based near-infrared probes (Aurelia-1 and 2) that are optoacoustically active and spectrally distinct for simultaneous MSOT imaging were synthesized and conjugated to TRA to produce TRA-Aurelia-1 and 2. Freshly resected human HER2-positive (n = 6) and HER2-negative (n = 6) triple-negative breast cancer tumors were treated with TRA-Aurelia-1 and TRA-Aurelia-2 for 2 hours and imaged with MSOT. HER2-expressing DY36T2Q cells and HER2-negative MDA-MB-231 cells were implanted orthotopically into mice (n = 5). MSOT imaging was performed 6 hours following the injection, and the Friedman test was used for analysis. Results TRA-Aurelia-1 (absorption peak, 780 nm) and TRA-Aurelia-2 (absorption peak, 720 nm) were spectrally distinct. HER2-positive human breast tumors exhibited a significant increase in optoacoustic signal following TRA-Aurelia-1 (28.8-fold) or 2 (29.5-fold) (P = .002) treatment relative to HER2-negative tumors. Treatment with TRA-Aurelia-1 and 2 increased optoacoustic signals in DY36T2Q tumors relative to those in MDA-MB-231 controls (14.8-fold, P < .001; 20.8-fold, P < .001, respectively). Conclusion The study demonstrates that TRA-Aurelia 1 and 2 nanoparticles operate as a spectrally distinct HER2 breast tumor-targeted in vivo optoacoustic agent. Keywords: Molecular Imaging, Nanoparticles, Photoacoustic Imaging, Breast Cancer Supplemental material is available for this article. © RSNA, 2023.

Molecular breast cancer subtype identification using photoacoustic spectral analysis and machine learning at the biomacromolecular level

Breast cancer threatens the health of women worldwide, and its molecular subtypes largely determine the therapy and prognosis of patients. However, an uncomplicated and accurate method to identify subtypes is currently lacking. This study utilized photoacoustic spectral analysis (PASA) based on the partial least squares discriminant algorithm (PLS-DA) to identify molecular breast cancer subtypes at the biomacromolecular level in vivo. The area of power spectrum density (APSD) was extracted to semi-quantify the biomacromolecule content. The feature wavelengths were obtained via the variable importance in projection (VIP) score and the selectivity ratio (Sratio), to identify the biomarkers. The PASA achieved an accuracy of 84%. Most of the feature wavelengths fell into the collagen-dominated absorption waveband, which was consistent with the histopathological results. This paper proposes a successful method for identifying molecular breast cancer subtypes and proves that collagen can be treated as a biomarker for molecular breast cancer subtyping.

Application of photoacoustic computed tomography in biomedical imaging: A literature review

Photoacoustic computed tomography (PACT) is a hybrid imaging modality that combines optical excitation and acoustic detection techniques. It obtains high-resolution deep-tissue images based on the deep penetration of light, the anisotropy of light absorption in objects, and the photoacoustic effect. Hence, PACT shows great potential in biomedical sample imaging. Recently, due to its advantages of high sensitivity to optical absorption and wide scalability of spatial resolution with the desired imaging depth, PACT has received increasing attention in preclinical and clinical practice. To date, there has been a proliferation of PACT systems designed for specific biomedical imaging applications, from small animals to human organs, from ex vivo to in vivo real-time imaging, and from simple structural imaging to functional and molecular imaging with external contrast agents. Therefore, it is of great importance to summarize the previous applications of PACT systems in biomedical imaging and clinical practice. In this review, we searched for studies related to PACT imaging of biomedical tissues and samples over the past two decades; divided the studies into two categories, PACT imaging of preclinical animals and PACT imaging of human organs and body parts; and discussed the significance of the studies. Finally, we pointed out the future directions of PACT in biomedical applications. With the development of exogenous contrast agents and advances of imaging technique, in the future, PACT will enable biomedical imaging from organs to whole bodies, from superficial vasculature to internal organs, from anatomy to functions, and will play an increasingly important role in biomedical research and clinical practice.

High-fidelity deep functional photoacoustic tomography enhanced by virtual point sources

Photoacoustic tomography (PAT), a hybrid imaging modality that acoustically detects the optical absorption contrast, is a promising technology for imaging hemodynamic functions in deep tissues far beyond the traditional optical microscopy. However, the most clinically compatible PAT often suffers from the poor image fidelity, mostly due to the limited detection view of the linear ultrasound transducer array. PAT can be improved by employing highly-absorbing contrast agents such as droplets and nanoparticles, which, however, have low clinical translation potential due to safety concerns and regulatory hurdles imposed by these agents. In this work, we have developed a new methodology that can fundamentally improve PAT's image fidelity without hampering any of its functional capability or clinical translation potential. By using clinically-approved microbubbles as virtual point sources that strongly and isotropically scatter the local pressure waves generated by surrounding hemoglobin, we can overcome the limited-detection-view problem and achieve high-fidelity functional PAT in deep tissues, a technology referred to as virtual-point-source PAT (VPS-PAT). We have thoroughly investigated the working principle of VPS-PAT by numerical simulations and in vitro phantom experiments, clearly showing the signal origin of VPSs and the resultant superior image fidelity over traditional PAT. We have also demonstrated in vivo applications of VPT-PAT for functional small-animal studies with physiological challenges. We expect that VPS-PAT can find broad applications in biomedical research and accelerated translation to clinical impact.

Recent Advances in Contrast-Enhanced Photoacoustic Imaging: Overcoming the Physical and Practical Challenges

For decades now, photoacoustic imaging (PAI) has been investigated to realize its potential as a niche biomedical imaging modality. Despite its highly desirable optical contrast and ultrasonic spatiotemporal resolution, PAI is challenged by such physical limitations as a low signal-to-noise ratio (SNR), diminished image contrast due to strong optical attenuation, and a lower-bound on spatial resolution in deep tissue. In addition, contrast-enhanced PAI has faced practical limitations such as insufficient cell-specific targeting due to low delivery efficiency and difficulties in developing clinically translatable agents. Identifying these limitations is essential to the continuing expansion of the field, and substantial advances in developing contrast-enhancing agents, complemented by high-performance image acquisition systems, have synergistically dealt with the challenges of conventional PAI. This review covers the past four years of research on pushing the physical and practical challenges of PAI in terms of SNR/contrast, spatial resolution, targeted delivery, and clinical application. Promising strategies for dealing with each challenge are reviewed in detail, and future research directions for next generation contrast-enhanced PAI are discussed.

Advances in Imaging of Inflammation, Fibrosis, and Cancer in the Gastrointestinal Tract

Gastrointestinal disease is prevalent and broad, manifesting itself in a variety of ways, including inflammation, fibrosis, infection, and cancer. However, historically, diagnostic technologies have exhibited limitations, especially with regard to diagnostic uncertainty. Despite development of newly emerging technologies such as optoacoustic imaging, many recent advancements have focused on improving upon pre-existing modalities such as ultrasound, computed tomography, magnetic resonance imaging, and endoscopy. These advancements include utilization of machine learning models, biomarkers, new technological applications such as diffusion weighted imaging, and new techniques such as transrectal ultrasound. This review discusses assessment of disease processes using imaging strategies for the detection and monitoring of inflammation, fibrosis, and cancer in the context of gastrointestinal disease. Specifically, we include ulcerative colitis, Crohn's disease, diverticulitis, celiac disease, graft vs. host disease, intestinal fibrosis, colorectal stricture, gastric cancer, and colorectal cancer. We address some of the most recent and promising advancements for improvement of gastrointestinal imaging, including unique discussions of such advancements with regard to imaging of fibrosis and differentiation between similar disease processes.

Investigating the feasibility of a hand-held photoacoustic imaging probe for margin assessment during breast conserving surgery

Approximately 19 % of breast cancer patients undergoing breast conserving surgery (BCS) must return for a secondary surgery due to incomplete tumour removal. Our previous work demonstrated that the lower lipid content, characteristic of tumour tissue, was observed as regions of hypo-intense photoacoustic (PA) contrast. The goal of this work was to evaluate feasibility of a low-frequency, hand-held PA imaging probe for surgical margin assessment based on lipid content differences. Here, we describe (i) the design of a prototype hand-held PA imaging probe, (ii) the effect of limited-bandwidth on image contrast, (iii) accuracy towards hypo-intense contrast detection, (iv) the limited-view characteristics of the single sensor design, and (iv) early imaging results of an ex-vivo breast cancer specimen. The probe incorporates a single polyvinylidene fluoride acoustic sensor, a 1-to-4 optical fibre bundle and a polycarbonate axicon lens for light delivery. Imaging results on phantoms designed to mimic positive margins demonstrated the ability to detect gaps in optical absorption as small as 1 mm in width. Compared to images from a near full-view PAI system, the hand-held PAI probe had higher signal to noise ratio but suffered from negativity image artifacts. Lumpectomy specimen imaging showed that strong signals can be obtained from the fatty tissue. Taken together, the results show this imaging approach with a hand-held probe has potential for detection of residual breast cancer tissue during BCS; however, more work is needed to reduce the size of the probe to fit within the surgical cavity.

Multispectral optoacoustic tomography for the non-invasive identification of patients with severe anemia in vivo

The immediate diagnosis of severe anemia is crucial for patient outcome. However, reliable non-invasive point-of-care diagnostic tools for e.g., ICU monitoring are currently lacking. Using an advanced Multispectral Optoacoustic Tomography (MSOT) research device, we first substantiated a strong positive correlation of MSOT-signal and absolute hemoglobin concentration ex vivo in blood samples. In a clinical exploratory proof-of-concept study, we then evaluated 19 patients with different severities of anemia and controls by non-invasive in vivo measurement of hemoglobin in the radial artery. Our approach proved excellent in identifying patients with severe anemia triggering RBC transfusion based on a strong positive correlation of MSOT-signal intensity and hemoglobin concentration for 700 nm single wavelength and HbR unmixed MSOT-parameter analysis. In conclusion, our study lays the foundation to further develop MSOT-based real-time quantitative perfusion analyses in follow-up preclinical and clinical imaging studies and as a promising diagnostic tool to improve patient care in the future. DRKS00021442.

Progress of photoacoustic imaging combined with targeted photoacoustic contrast agents in tumor molecular imaging

Molecular imaging visualizes, characterizes, and measures biological processes at the molecular and cellular level. In oncology, molecular imaging is an important technology to guide integrated and precise diagnosis and treatment. Photoacoustic imaging is mainly divided into three categories: photoacoustic microscopy, photoacoustic tomography and photoacoustic endoscopy. Different from traditional imaging technology, which uses the physical properties of tissues to detect and identify diseases, photoacoustic imaging uses the photoacoustic effect to obtain the internal information of tissues. During imaging, lasers excite either endogenous or exogenous photoacoustic contrast agents, which then send out ultrasonic waves. Currently, photoacoustic imaging in conjunction with targeted photoacoustic contrast agents is frequently employed in the research of tumor molecular imaging. In this study, we will examine the latest advancements in photoacoustic imaging technology and targeted photoacoustic contrast agents, as well as the developments in tumor molecular imaging research.

Photoacoustic Tomography Appearance of Fat Necrosis: A First-in-Human Demonstration of Biochemical Signatures along with Histological Correlation

A 50-year-old woman with no past medical history presented with a left anterior chest wall mass that was clinically soft, mobile, and non-tender. A targeted ultrasound (US) showed findings suggestive of a lipoma. However, focal “mass-like” nodules seen within the inferior portion suggested malignant transformation of a lipomatous lesion called for cross sectional imaging, such as MRI or invasive biopsy or excision for histological confirmation. A T1-weighted image demonstrated a large lipoma that has a central fat-containing region surrounded by an irregular hypointense rim in the inferior portion, confirming the benignity of the lipoma. An ultrasound-guided photoacoustic imaging (PA) of the excised specimen to derive the biochemical distribution demonstrated the “mass-like” hypoechoic regions on US as fat-containing, suggestive of benignity of lesion, rather than fat-replacing suggestive of malignancy. The case showed the potential of PA as an adjunct to US in improving the diagnostic confidence in lesion characterization.

Photoacoustic imaging for microcirculation

Microcirculation facilitates the blood-tissue exchange of nutrients and regulates blood perfusion. It is, therefore, essential in maintaining tissue health. Aberrations in microcirculation are potentially indicative of underlying cardiovascular and metabolic pathologies. Thus, quantitative information about it is of great clinical relevance. Photoacoustic imaging (PAI) is a capable technique that relies on the generation of imaging contrast via the absorption of light and can image at micron-scale resolution. PAI is especially desirable to map microvasculature as hemoglobin strongly absorbs light and can generate a photoacoustic signal. This paper reviews the current state of the art for imaging microvascular networks using photoacoustic imaging. We further describe how quantitative information about blood dynamics such as the total hemoglobin concentration, oxygen saturation, and blood flow rate is obtained using PAI. We also discuss its importance in understanding key pathophysiological processes in neurovascular, cardiovascular, ophthalmic, and cancer research fields. We then discuss the current challenges and limitations of PAI and the approaches that can help overcome these limitations. Finally, we provide the reader with an overview of future trends in the field of PAI for imaging microcirculation.

Deep learning methods hold promise for light fluence compensation in three-dimensional optoacoustic imaging

SIGNIFICANCE

Quantitative optoacoustic imaging (QOAI) continues to be a challenge due to the influence of nonlinear optical fluence distribution, which distorts the optoacoustic image representation. Nonlinear optical fluence correction in OA imaging is highly ill-posed, leading to the inaccurate recovery of optical absorption maps. This work aims to recover the optical absorption maps using deep learning (DL) approach by correcting for the fluence effect.

AIM

Different DL models were compared and investigated to enable optical absorption coefficient recovery at a particular wavelength in a nonhomogeneous foreground and background medium.

APPROACH

Data-driven models were trained with two-dimensional (2D) Blood vessel and three-dimensional (3D) numerical breast phantom with highly heterogeneous/realistic structures to correct for the nonlinear optical fluence distribution. The trained DL models such as U-Net, Fully Dense (FD) U-Net, Y-Net, FD Y-Net, Deep residual U-Net (Deep ResU-Net), and generative adversarial network (GAN) were tested to evaluate the performance of optical absorption coefficient recovery (or fluence compensation) with in-silico and in-vivo datasets.

RESULTS

The results indicated that FD U-Net-based deconvolution improves by about 10% over reconstructed optoacoustic images in terms of peak-signal-to-noise ratio. Further, it was observed that DL models can indeed highlight deep-seated structures with higher contrast due to fluence compensation. Importantly, the DL models were found to be about 17 times faster than solving diffusion equation for fluence correction.

CONCLUSIONS

The DL methods were able to compensate for nonlinear optical fluence distribution more effectively and improve the optoacoustic image quality.

Biochemical "decoding" of breast ultrasound images with optoacoustic tomography fusion: First-in-human display of lipid and collagen signals on breast ultrasound

To date, studies which utilized ultrasound (US) and optoacoustic tomography (OT) fusion (US-OT) in biochemical differentiation of malignant and benign breast conditions have relied on limited biochemical data such as oxyhaemoglobin (OH) and deoxyhaemoglobin (DH) only. There has been no data of the largest biochemical components of breast fibroglandular tissue: lipid and collagen. Here, the authors believe the ability to image collagen and lipids within the breast tissue could serve as an important milestone in breast US-OT imaging with many potential downstream clinical applications. Hence, we would like to present the first-in-human US-OT demonstration of lipid and collagen differentiation in an excised breast tissue from a 38-year-old female.

Model resolution matrix based deconvolution improves over non-quadratic penalization in frequency-domain photoacoustic tomography

Frequency domain photoacoustic tomography is becoming more attractive due to low-cost and compact light-sources being used; however, frequency-domain implementation suffers from lower signal to noise compared to time-domain implementation. In this work, we have developed a non-quadratic based penalization framework for frequency-domain photoacoustic imaging, and further proposed a two-step model-resolution matrix based deconvolution approach to improve the reconstruction image quality. The model-resolution matrix was developed in the context of different penalty functions like l₂-norm, l₁-norm, Cauchy, and Geman-McClure. These model-resolution matrices were then used to perform the deconvolution operation using split augmented Lagrangian shrinkage thresholding algorithm in both full-view and limited-view configurations. The results indicated that the two-step approach outperformed the different penalty function (prior constraint) based reconstruction, with an improvement of about 20% in terms of peak signal to noise ratio and 30% in terms of structural similarity index measure. The improved image quality provided using these algorithms will have a direct impact on realizing practical frequency-domain implementation in both limited-view and full-view configurations.

An optoacoustic imaging feature set to characterise blood vessels surrounding benign and malignant breast lesions

Combining optoacoustic (OA) imaging with ultrasound (US) enables visualisation of functional blood vasculature in breast lesions by OA to be overlaid with the morphological information of US. Here, we develop a simple OA feature set to differentiate benign and malignant breast lesions. 94 female patients with benign, indeterminate or suspicious lesions were recruited and underwent OA-US. An OA-US imaging feature set was developed using images from the first 38 patients, which contained 14 malignant and 8 benign solid lesions. Two independent radiologists blindly scored the OA-US images of a further 56 patients, which included 31 malignant and 13 benign solid lesions, with a sensitivity of 96.8% and specificity of 84.6%. Our findings indicate that OA-US can reveal vascular patterns of breast lesions that indicate malignancy using a simple feature set based on single wavelength OA data, which is therefore amenable to application in low resource settings for breast cancer management.

Contrast Agents for Photoacoustic Imaging: A Review Focusing on the Wavelength Range

Photoacoustic imaging using endogenous chromophores as a contrast has been widely applied in biomedical studies owing to its functional imaging capability at the molecular level. Various exogenous contrast agents have also been investigated for use in contrast-enhanced imaging and functional analyses. This review focuses on contrast agents, particularly in the wavelength range, for use in photoacoustic imaging. The basic principles of photoacoustic imaging regarding light absorption and acoustic release are introduced, and the optical characteristics of tissues are summarized according to the wavelength region. Various types of contrast agents, including organic dyes, semiconducting polymeric nanoparticles, gold nanoparticles, and other inorganic nanoparticles, are explored in terms of their light absorption range in the near-infrared region. An overview of the contrast-enhancing capacity and other functional characteristics of each agent is provided to help researchers gain insights into the development of contrast agents in photoacoustic imaging.

Spatial quantification of clinical biomarker pharmacokinetics through deep learning-based segmentation and signal-oriented analysis of MSOT data

Although multispectral optoacoustic tomography (MSOT) significantly evolved over the last several years, there is a lack of quantitative methods for analysing this type of image data. Current analytical methods characterise the MSOT signal in manually defined regions of interest outlining selected tissue areas. These methods demand expert knowledge of the sample anatomy, are time consuming, highly subjective and prone to user bias. Here we present our fully automated open-source MSOT cluster analysis toolkit Mcat that was designed to overcome these shortcomings. It employs a deep learning-based approach for initial image segmentation followed by unsupervised machine learning to identify regions of similar signal kinetics. It provides an objective and automated approach to quantify the pharmacokinetics and extract the biodistribution of biomarkers from MSOT data. We exemplify our generally applicable analysis method by quantifying liver function in a preclinical sepsis model whilst highlighting the advantages of our new approach compared to the severe limitations of existing analysis procedures.

Image processing improvements afford second-generation handheld optoacoustic imaging of breast cancer patients

BACKGROUND

Since the initial breast transillumination almost a century ago, breast cancer imaging using light has been considered in different implementations aiming to improve diagnostics, minimize the number of available biopsies, or monitor treatment. However, due to strong photon scattering, conventional optical imaging yields low resolution images, challenging quantification and interpretation. Optoacoustic imaging addresses the scattering limitation and yields high-resolution visualization of optical contrast, offering great potential value for breast cancer imaging. Nevertheless, the image quality of experimental systems remains limited due to a number of factors, including signal attenuation with depth and partial view angle and motion effects, particularly in multi-wavelength measurements.

METHODS

We developed data analytics methods to improve the accuracy of handheld optoacoustic breast cancer imaging, yielding second-generation optoacoustic imaging performance operating in tandem with ultrasonography.

RESULTS

We produced the most advanced images yet with handheld optoacoustic examinations of the human breast and breast cancer, in terms of resolution and contrast. Using these advances, we examined optoacoustic markers of malignancy, including vasculature abnormalities, hypoxia, and inflammation, on images obtained from breast cancer patients.

CONCLUSIONS

We achieved a new level of quality for optoacoustic images from a handheld examination of the human breast, advancing the diagnostic and theranostic potential of the hybrid optoacoustic-ultrasound (OPUS) examination over routine ultrasonography.

Intraoperative imaging in pathology-assisted surgery

The pathological assessment of surgical specimens during surgery can reduce the incidence of positive resection margins, which otherwise can result in additional surgeries or aggressive therapeutic regimens. To improve patient outcomes, intraoperative spectroscopic, fluorescence-based, structural, optoacoustic and radiological imaging techniques are being tested on freshly excised tissue. The specific clinical setting and tumour type largely determine whether endogenous or exogenous contrast is to be detected and whether the tumour specificity of the detected biomarker, image resolution, image-acquisition times or penetration depth are to be prioritized. In this Perspective, we describe current clinical standards for intraoperative tissue analysis and discuss how intraoperative imaging is being implemented. We also discuss potential implementations of intraoperative pathology-assisted surgery for clinical decision-making.

Review on Multispectral Photoacoustic Analysis of Cancer: Thyroid and Breast

In recent decades, photoacoustic imaging has been used widely in biomedical research, providing molecular and functional information from biological tissues in vivo. In addition to being used for research in small animals, photoacoustic imaging has also been utilized for in vivo human studies, achieving a multispectral photoacoustic response in deep tissue. There have been several clinical trials for screening cancer patients by analyzing multispectral responses, which in turn provide metabolomic information about the underlying biological tissues. This review summarizes the methods and results of clinical photoacoustic trials available in the literature to date to classify cancerous tissues, specifically of the thyroid and breast. From the review, we can conclude that a great potential exists for photoacoustic imaging to be used as a complementary modality to improve diagnostic accuracy for suspicious tumors, thus significantly benefitting patients’ healthcare.

The emerging role of photoacoustic imaging in clinical oncology

Clinical oncology can benefit substantially from imaging technologies that reveal physiological characteristics with multiscale observations. Complementing conventional imaging modalities, photoacoustic imaging (PAI) offers rapid imaging (for example, cross-sectional imaging in real time or whole-breast scanning in 10-15 s), scalably high levels of spatial resolution, safe operation and adaptable configurations. Most importantly, this novel imaging modality provides informative optical contrast that reveals details on anatomical, functional, molecular and histological features. In this Review, we describe the current state of development of PAI and the emerging roles of this technology in cancer screening, diagnosis and therapy. We comment on the performance of cutting-edge photoacoustic platforms, and discuss their clinical applications and utility in various clinical studies. Notably, the clinical translation of PAI is accelerating in the areas of macroscopic and mesoscopic imaging for patients with breast or skin cancers, as well as in microscopic imaging for histopathology. We also highlight the potential of future developments in technological capabilities and their clinical implications, which we anticipate will lead to PAI becoming a desirable and widely used imaging modality in oncological research and practice.

The Potential of Photoacoustic Imaging in Radiation Oncology

Radiotherapy is recognized globally as a mainstay of treatment in most solid tumors and is essential in both curative and palliative settings. Ionizing radiation is frequently combined with surgery, either preoperatively or postoperatively, and with systemic chemotherapy. Recent advances in imaging have enabled precise targeting of solid lesions yet substantial intratumoral heterogeneity means that treatment planning and monitoring remains a clinical challenge as therapy response can take weeks to manifest on conventional imaging and early indications of progression can be misleading. Photoacoustic imaging (PAI) is an emerging modality for molecular imaging of cancer, enabling non-invasive assessment of endogenous tissue chromophores with optical contrast at unprecedented spatio-temporal resolution. Preclinical studies in mouse models have shown that PAI could be used to assess response to radiotherapy and chemoradiotherapy based on changes in the tumor vascular architecture and blood oxygen saturation, which are closely linked to tumor hypoxia. Given the strong relationship between hypoxia and radio-resistance, PAI assessment of the tumor microenvironment has the potential to be applied longitudinally during radiotherapy to detect resistance at much earlier time-points than currently achieved by size measurements and tailor treatments based on tumor oxygen availability and vascular heterogeneity. Here, we review the current state-of-the-art in PAI in the context of radiotherapy research. Based on these studies, we identify promising applications of PAI in radiation oncology and discuss the future potential and outstanding challenges in the development of translational PAI biomarkers of early response to radiotherapy.

Hyperspectral Imaging for Clinical Applications

Measuring morphological and biochemical features of tissue is crucial for disease diagnosis and surgical guidance, providing clinically significant information related to pathophysiology. Hyperspectral imaging (HSI) techniques obtain both spatial and spectral features of tissue without labeling molecules such as fluorescent dyes, which provides rich information for improved disease diagnosis and treatment. Recent advances in HSI systems have demonstrated its potential for clinical applications, especially in disease diagnosis and image-guided surgery. This review summarizes the basic principle of HSI and optical systems, deep-learning-based image analysis, and clinical applications of HSI to provide insight into this rapidly growing field of research. In addition, the challenges facing the clinical implementation of HSI techniques are discussed.

Optoacoustic Imaging And Potential Applications Of Raster-Scan Optoacoustic Mesoscopy In Dermatology

Optoacoustic imaging (OAI) is a hybrid imaging modality that integrates the benefits of optical contrast and ultrasound detection. Raster-scan optoacoustic mesoscopy (RSOM) is an emerging OAI method that provides information about several dermatological conditions' structural, functional, and molecular features. We searched PubMed and Google Scholar databases through September 2021 for articles relevant to OAI in the English language. This review contains 32 studies and other relevant literature. Several studies indicate that RSOM is helpful in inflammatory skin conditions such as psoriasis and eczema, especially as it allows more accurate quantification of inflammation-related alterations such as changes to the dermal vasculature. In psoriasis, RSOM can provide objective early diagnosis and monitoring of disease activity and treatment efficacy. Multispectral RSOM, a method in which skin is lightened at more than a single wavelength, is beneficial in diagnosing and monitoring hypoxia-associated conditions, such as systemic sclerosis and chronic wounds. OAI techniques can visualize the pathological vascularization of skin cancers and quantify their oxygenation status which helps differentiate them from normal skin. Also, they can measure the depth of malignant melanoma and detect the metastatic spread of melanoma cells to sentinel lymph nodes. As demonstrated in this article, there is a large spectrum of potential applications of OAI imaging, especially RSOM, in diagnosing, treating, and managing skin diseases.

Second-Generation Dual Scan Mammoscope With Photoacoustic, Ultrasound, and Elastographic Imaging Capabilities

We recently developed the photoacoustic dual-scan mammoscope (DSM), a system that images the patient in standing pose analog to X-ray mammography. The system simultaneously acquires three-dimensional photoacoustic and ultrasound (US) images of the mildly compressed breast. Here, we describe a second-generation DSM (DSM-2) system that offers a larger field of view, better system stability, higher ultrasound imaging quality, and the ability to quantify tissue mechanical properties. In the new system, we doubled the field of view through laterally shifted round-trip scanning. This new design allows coverage of the entire breast tissue. We also adapted precisely machined holders for the transducer-fiber bundle sets. The new holder increased the mechanical stability and facilitated image registration from the top and bottom scanners. The quality of the US image is improved by increasing the firing voltage and the number of firing angles. Finally, we incorporated quasi-static ultrasound elastography to allow comprehensive characterization of breast tissue. The performance of the new system was demonstrated through in vivo human imaging experiments. The experimental results confirmed the capability of the DSM-2 system as a powerful tool for breast imaging.

Broadband surface plasmon resonance sensor for fast spectroscopic photoacoustic microscopy

High-speed optical-resolution photoacoustic microscopy (OR-PAM), integrating the merits of high spatial resolution and fast imaging acquisition, can observe dynamic processes of the optical absorption-based molecular specificities. However, it remains challenging for the evaluation to morphological and physiological parameters that are closely associated with photoacoustic spectrum due to the inadequate ultrasonic frequency response of the routinely-employed piezoelectric transducer. By utilizing the galvanometer for fast optical scanning and our previously-developed surface plasmon resonance sensor as an unfocused broadband ultrasonic detector, high-speed spectroscopic photoacoustic imaging was accessed in the OR-PAM system, achieving an acoustic bandwidth of ∼125 MHz and B-scan rate at ∼200 Hz over a scanning range of ∼0.5 mm. Our system demonstrated the dynamic imaging of the moving phantoms' structures and the simultaneous characterization of their photoacoustic spectra over time. Further, fast volumetric imaging and spectroscopic analysis of microanatomic features of a zebrafish eye ex vivo was obtained label-freely.

An Excitation-Reception Collinear Probe for Ultrasonic, Photoacoustic, and Thermoacoustic Tri-Modal Volumetric Imaging

Imaging systems that integrate multiple modalities can reveal complementary anatomic and functional information as they exploit different contrast mechanisms, which have shown great application potential and advantages in preclinical studies. A portable and easy-to-use imaging probe will be more conducive to transfer to clinical practice. Here, we present a tri-modal ultrasonic (US), photoacoustic (PA), and thermoacoustic (TA) imaging system with an excitation-reception collinear probe. The acoustic field, light field, and electric field of the probe were designed to be coaxial, realizing homogeneous illumination and high-sensitivity detection at the same detection position. US images can provide detailed information about structures, PA images can delineate the morphology of blood vessels in tissues, and TA images can reveal dielectric properties of the tissues. Moreover, phantoms and in vivo human finger experiments were performed by the tri-modal imaging system to demonstrate its performance. The results show that the tri-modal imaging system with the proposed probe has the ability to detect small breast tumors with a radius of only 2.5 mm and visualize the anatomical structure of the finger in three dimensions. Our work confirms that the tri-modal imaging system equipped with a collinear probe can be applied to a variety of different scenarios, which lays a solid foundation for the application of the tri-modality system in clinical trials.

How molecular imaging will enable robotic precision surgery : The role of artificial intelligence, augmented reality, and navigation

Molecular imaging is one of the pillars of precision surgery. Its applications range from early diagnostics to therapy planning, execution, and the accurate assessment of outcomes. In particular, molecular imaging solutions are in high demand in minimally invasive surgical strategies, such as the substantially increasing field of robotic surgery. This review aims at connecting the molecular imaging and nuclear medicine community to the rapidly expanding armory of surgical medical devices. Such devices entail technologies ranging from artificial intelligence and computer-aided visualization technologies (software) to innovative molecular imaging modalities and surgical navigation (hardware). We discuss technologies based on their role at different steps of the surgical workflow, i.e., from surgical decision and planning, over to target localization and excision guidance, all the way to (back table) surgical verification. This provides a glimpse of how innovations from the technology fields can realize an exciting future for the molecular imaging and surgery communities.

An Activatable Probe with Aggregation-Induced Emission for Detecting and Imaging Herbal Medicine Induced Liver Injury with Optoacoustic Imaging and NIR-II Fluorescence Imaging

Whilte herbal medicines are widely used for health promotion and therapy for chronic conditions, inappropriate use of them may cause adverse effects like liver injury, and accurately evaluating their hepatotoxicity is of great significance for public health. Herein, an activatable probe QY-N for diagnosing herbal-medicine-induced liver injury by detecting hepatic NO with NIR-II fluorescence and multispectral optoacoustic tomography (MSOT) imaging is demonstrated. The probe includes a bismethoxyphenyl-amine-containing dihydroxanthene serving as electron donor, a quinolinium as electron acceptor, and a butylamine as recognition group and fluorescence quencher. The hepatic level of NO reacts with butylamine, thereby generating the activated probe QY-NO which exhibits a red-shifted absorption band (700-850 nm) for optoacoustic imaging and generates strong emission (910-1110 nm) for NIR-II fluorescence imaging. QY-NO is aggregation-induced-emission (AIE) active, which ensures strong emission in aggregated state. QY-N is utilized in the triptolide-induced liver injury mouse model, and experimental results demonstrate the QY-N can be activated by hepatic NO and thus be used in detecting herbal-medicine-induced liver injury. The temporal and spatial information provided by three-dimensional MSOT images well delineates the site and size of liver injury. Moreover, QY-N has also been employed to monitor rehabilitation of liver injury during treatment process.

Recent developments in mesoporous polydopamine-derived nanoplatforms for cancer theranostics

Polydopamine (PDA), which is derived from marine mussels, has excellent potential in early diagnosis of diseases and targeted drug delivery owing to its good biocompatibility, biodegradability, and photothermal conversion. However, when used as a solid nanoparticle, the application of traditional PDA is restricted because of the low drug-loading and encapsulation efficiencies of hydrophobic drugs. Nevertheless, the emergence of mesoporous materials broaden our horizon. Mesoporous polydopamine (MPDA) has the characteristics of a porous structure, simple preparation process, low cost, high specific surface area, high light-to-heat conversion efficiency, and excellent biocompatibility, and therefore has gained considerable interest. This review provides an overview of the preparation methods and the latest applications of MPDA-based nanodrug delivery systems (chemotherapy combined with radiotherapy, photothermal therapy combined with chemotherapy, photothermal therapy combined with immunotherapy, photothermal therapy combined with photodynamic/chemodynamic therapy, and cancer theranostics). This review is expected to shed light on the multi-strategy antitumor therapy applications of MPDA-based nanodrug delivery systems.

Analysis of Fluorescence Decay Kinetics of Indocyanine Green Monomers and Aggregates in Brain Tumor Model In Vivo

Spectroscopic approach with fluorescence time resolution allows one to determine the state of a brain tumor and its microenvironment via changes in the fluorescent dye's fluorescence lifetime. Indocyanine green (ICG) is an acknowledged infra-red fluorescent dye that self-assembles into stable aggregate forms (ICG NPs). ICG NPs aggregates have a tendency to accumulate in the tumor with a maximum accumulation at 24 h after systemic administration, enabling extended intraoperative diagnostic. Fluorescence lifetime analysis of ICG and ICG NPs demonstrates different values for ICG monomers and H-aggregates, indicating promising suitability for fluorescent diagnostics of brain tumors due to their affinity to tumor cells and stability in biological tissue.

A Comparative Study of Four Total Variational Regularization Reconstruction Algorithms for Sparse-View Photoacoustic Imaging

Photoacoustic imaging (PAI) is a new nonionizing, noninvasive biomedical imaging technology that has been employed to reconstruct the light absorption characteristics of biological tissues. The latest developments in compressed sensing (CS) technology have shown that it is possible to accurately reconstruct PAI images from sparse data, which can greatly reduce scanning time. This study focuses on the comparative analysis of different CS-based total variation regularization reconstruction algorithms, aimed at finding a method suitable for PAI image reconstruction. The performance of four total variation regularization algorithms is evaluated through the reconstruction experiment of sparse numerical simulation signal and agar phantom signal data. The evaluation parameters include the signal-to-noise ratio and normalized mean absolute error of the PAI image and the CPU time. The comparative results demonstrate that the TVAL3 algorithm can well balance the quality and efficiency of the reconstruction. The results of this study can provide some useful guidance for the development of the PAI sparse reconstruction algorithm.

A scalable open-source MATLAB toolbox for reconstruction and analysis of multispectral optoacoustic tomography data

Multispectral photoacoustic tomography enables the resolution of spectral components of a tissue or sample at high spatiotemporal resolution. With the availability of commercial instruments, the acquisition of data using this modality has become consistent and standardized. However, the analysis of such data is often hampered by opaque processing algorithms, which are challenging to verify and validate from a user perspective. Furthermore, such tools are inflexible, often locking users into a restricted set of processing motifs, which may not be able to accommodate the demands of diverse experiments. To address these needs, we have developed a Reconstruction, Analysis, and Filtering Toolbox to support the analysis of photoacoustic imaging data. The toolbox includes several algorithms to improve the overall quantification of photoacoustic imaging, including non-negative constraints and multispectral filters. We demonstrate various use cases, including dynamic imaging challenges and quantification of drug effect, and describe the ability of the toolbox to be parallelized on a high performance computing cluster.

New contrast agents for photoacoustic imaging and theranostics: Recent 5-year overview on phthalocyanine/naphthalocyanine-based nanoparticles

The phthalocyanine (Pc) and naphthalocyanine (Nc) nanoagents have drawn much attention as contrast agents for photoacoustic (PA) imaging due to their large extinction coefficients and long absorption wavelengths in the near-infrared region. Many investigations have been conducted to enhance Pc/Ncs' photophysical properties and address their poor solubility in an aqueous solution. Many diverse strategies have been adopted, including centric metal chelation, structure modification, and peripheral substitution. This review highlights recent advances on Pc/Nc-based PA agents and their extended use for multiplexed biomedical imaging, multimodal diagnostic imaging, and image-guided phototherapy.

LightSpeed: A Compact, High-Speed Optical-Link-Based 3D Optoacoustic Imager

Wide-scale adoption of optoacoustic imaging in biology and medicine critically depends on availability of affordable scanners combining ease of operation with optimal imaging performance. Here we introduce LightSpeed: a low-cost real-time volumetric handheld optoacoustic imager based on a new compact software-defined ultrasound digital acquisition platform and a pulsed laser diode. It supports the simultaneous signal acquisition from up to 192 ultrasound channels and provides a hig-bandwidth direct optical link (2x 100G Ethernet) to the host-PC for ultra-high frame rate image acquisitions. We demonstrate use of the system for ultrafast (500Hz) 3D human angiography with a rapidly moving handheld probe. LightSpeed attained image quality comparable with a conventional optoacoustic imaging systems employing bulky acquisition electronics and a Q-switched pulsed laser. Our results thus pave the way towards a new generation of compact, affordable and high-performance optoacoustic scanners.