LV-GAN: A deep learning approach for limited-view optoacoustic imaging based on hybrid datasets

The optoacoustic imaging (OAI) methods are rapidly evolving for resolving optical contrast in medical imaging applications. In practice, measurement strategies are commonly implemented under limited-view conditions due to oversized image objectives or system design limitations. Data acquired by limited-view detection may impart artifacts and distortions in reconstructed optoacoustic (OA) images. We propose a hybrid data-driven deep learning approach based on generative adversarial network (GAN), termed as LV-GAN, to efficiently recover high quality images from limited-view OA images. Trained on both simulation and experiment data, LV-GAN is found capable of achieving high recovery accuracy even under limited detection angles less than 60^°. The feasibility of LV-GAN for artifact removal in biological applications was validated by ex vivo experiments based on two different OAI systems, suggesting high potential of a ubiquitous use of LV-GAN to optimize image quality or system design for different scanners and application scenarios.     

Interferometric optical fiber sensor for optoacoustic endomicroscopy

Optical fiber sensors can offer robust and miniaturized detection of wideband ultrasound, yielding high sensitivity and immunity to electromagnetic interference. However, the lack of cost-effective manufacturing methods prevents the disseminated use of these sensors in biomedical applications. In this study, we developed and optimized a simple method to create optical cavities with high-quality mirrors for acoustic sensing based on micro-manipulation of UV-curable optical adhesives and electroless chemical silver deposition. This approach enables the manufacturing of ultrasound sensors based on Fabry-Pérot interferometers on optical fiber tips with minimal production costs. Characterization and high-resolution optoacoustic imaging experiments show that the manufacturing process yielded a fiber sensor with a small NEP () over a broad detection bandwidth (25 MHz), generally outperforming conventional piezoelectric based transducers. We discuss how the new manufacturing process leads to a high-performance acoustic detector that, due to low cost, can be used as a disposable sensor.     

Effects of multispectral excitation on the sensitivity of molecular optoacoustic imaging

Molecular optoacoustic (photoacoustic) imaging typically relies on the spectral identification of absorption signatures from molecules of interest. To achieve this, two or more excitation wavelengths are employed to sequentially illuminate tissue. Due to depth‐related spectral dependencies and detection related effects, the multispectral optoacoustic tomography (MSOT) spectral unmixing problem presents a complex non‐linear inversion operation. So far, different studies have showcased the spectral capacity of optoacoustic imaging, without however relating the performance achieved to the number of wavelengths employed. Overall, the dependence of the sensitivity and accuracy of optoacoustic imaging as a function of the number of illumination wavelengths has not been so far comprehensively studied. In this paper we study the impact of the number of excitation wavelengths employed on the sensitivity and accuracy achieved by molecular optoacoustic tomography. We present a quantitative analysis, based on synthetic MSOT datasets and observe a trend of sensitivity increase for up to 20 wavelengths. Importantly we quantify this relation and demonstrate an up to an order of magnitude sensitivity increase of multi‐wavelength illumination vs. single or dual wavelength optoacoustic imaging. Examples from experimental animal studies are finally utilized to support the findings.

In vivo MSOT imaging of a mouse brain bearing a tumor that is expressing a near‐infrared fluorescent protein. ( a ) Monochromatic optoacoustic imaging at the peak excitation wavelength of the fluorescent protein. ( b ) Overlay of the detected bio‐distribution of the protein (red pseudocolor) on the monochromatic optoacoustic image. ( c ) Ex vivo validation by means of cryoslicing fluorescence imaging.     

Optoacoustic monitoring of water content in tissue phantoms and human skin

Skin water content monitoring is important for diagnostics and management of edema, dehydration, and other skin conditions as well as for cosmetic applications. Because optoacoustic (OA) technique has high (optical) contrast and (ultrasound) resolution and significant probing depth, it may be suitable for accurate, noninvasive water content monitoring in the skin. In this work we studied OA response from skin tissue phantoms and human wrist skin in the wavelength range from 1370 nm to 1650 nm using a novel, tunable OPO OA system. We identified optimal wavelengths for OA water content monitoring in different skin layers. The results of our study suggest that the OA technique may become a valuable, quantitative tool for accurate, high-resolution water content monitoring in the skin and other tissues and may find wide applications in dermatology, cosmetology, and tissue trauma management.     

Inside Cover: A novel in vivo Cerenkov luminescence image‐guided surgery on primary and metastatic colorectal cancer (J. Biophotonics 3/2020)

This study presents a novel intraoperative in vivo imaging approach which harnessed Cerenkov luminescence (CL) to detect primary and metastatic colorectal cancer (CRC) using clinically approved radiopharmaceuticals. In the mice and swine experiments, the proposed approach effectively improved the effect of CRC surgery. The approach is believed to be promising for utilizing CL in open surgery. Further details can be found in the article by Zeyu Zhang, Yawei Qu, Yu Cao et al. ( e201960152 )

     

Three‐dimensional multispectral optoacoustic mesoscopy reveals melanin and blood oxygenation in human skin in vivo

Optical imaging plays a major role in disease detection in dermatology. However, current optical methods are limited by lack of three‐dimensional detection of pathophysiological parameters within skin. It was recently shown that single‐wavelength optoacoustic (photoacoustic) mesoscopy resolves skin morphology, i.e. melanin and blood vessels within epidermis and dermis. In this work we employed illumination at multiple wavelengths for enabling three‐dimensional multispectral optoacoustic mesoscopy (MSOM) of natural chromophores in human skin in vivo operating at 15–125 MHz. We employ a per‐pulse tunable laser to inherently co‐register spectral datasets, and reveal previously undisclosed insights of melanin, and blood oxygenation in human skin. We further reveal broadband absorption spectra of specific skin compartments. We discuss the potential of MSOM for label‐free visualization of physiological biomarkers in skin in vivo.

Cross‐sectional optoacoustic image of human skin in vivo. The epidermal layer is characterized by melanin absorption. A vascular network runs through the dermal layer, exhibiting blood oxygenation values of 50–90%. All scale bars: 250 µm     

Iterative Image Reconstruction for Sparse-View CT Using Normal-Dose Image Induced Total Variation Prior

X-ray computed tomography (CT) iterative image reconstruction from sparse-view projection data has been an important research topic for radiation reduction in clinic. In this paper, to relieve the requirement of misalignment reduction operation of the prior image constrained compressed sensing (PICCS) approach introduced by Chen et al, we present an iterative image reconstruction approach for sparse-view CT using a normal-dose image induced total variation (ndiTV) prior. The associative objective function of the present approach is constructed under the penalized weighed least-square (PWLS) criteria, which contains two terms, i.e., the weighted least-square (WLS) fidelity and the ndiTV prior, and is referred to as “PWLS-ndiTV”. Specifically, the WLS fidelity term is built based on an accurate relationship between the variance and mean of projection data in the presence of electronic background noise. The ndiTV prior term is designed to reduce the influence of the misalignment between the desired- and prior- image by using a normal-dose image induced non-local means (ndiNLM) filter. Subsequently, a modified steepest descent algorithm is adopted to minimize the associative objective function. Experimental results on two different digital phantoms and an anthropomorphic torso phantom show that the present PWLS-ndiTV approach for sparse-view CT image reconstruction can achieve noticeable gains over the existing similar approaches in terms of noise reduction, resolution-noise tradeoff, and low-contrast object detection.     

Saving eyesight,one gene at a time

Kai Yao’s group used prime editing to repair a blindness-causing mutation in the Pde6b gene in the mouse retina. This breakthrough was made possible by a Cas9 nickase that is not constrained by a protospacer adjacent motif (PAM) sequence requirement. This innovation brings prime editing technology one step closer to correcting disease-causing mutations at will.     

Nonlinear iterative perturbation scheme with simplified spherical harmonics (SP3) light propagation model for quantitative photoacoustic tomography

When using quantitative photoacoustic tomography (q-PAT) reconstruction to recover the optical absorption coefficients of tissue, the commonly used diffusion equation has several limitations in the case of the objects that have small geometries and high-absorption or low-scattering areas. Furthermore, the conventional perturbation reconstruction strategy is unsatisfactory when the target tissue containing large heterogeneous features. We herein present a modified q-PAT implementation that employs the higher-order photon migration model achieving the tradeoff between mathematical rigidity and computational efficiency. Besides, a nonlinear iterative method is proposed to obtain the perturbations of optical absorption considering the updating of the sensitivity matrix in calculating the fluence perturbations. Consequently, the distribution of tissue optical properties can be recovered in a robust way even if the targets with high absorption are included. The proposed approach has been validated by simulation, phantom and in vivo experiments, exhibiting promising performances in image fidelity and quantitative feasibility for practical applications.     

Estimating the distribution of heterogeneous treatment effects from treatment responses and from a predictive biomarker in a parallel-group RCT: A structural model approach

When the objective is to administer the best of two treatments to an individual, it is necessary to know his or her individual treatment effects (ITEs) and the correlation between the potential responses (PRs) and under treatments 1 and 0. Data that are generated in a parallel-group design RCT does not allow the ITE to be determined because only two samples from the marginal distributions of these PRs are observed and not the corresponding joint distribution. This is due to the “fundamental problem of causal inference.” Here, we present a counterfactual approach for estimating the joint distribution of two normally distributed responses to two treatments. This joint distribution of the PRs and can be estimated by assuming a bivariate normal distribution for the PRs and by using a normally distributed baseline biomarker functionally related to the sum . Such a functional relationship is plausible since a biomarker and the sum encode for the same information in an RCT, namely the variation between subjects. The estimation of the joint trivariate distribution is subjected to some constraints. These constraints can be framed in the context of linear regressions with regard to the proportions of variances in the responses explained and with regard to the residual variation. This presents new insights on the presence of treatment–biomarker interactions. We applied our approach to example data on exercise and heart rate and extended the approach to survival data.     

Conditional inversion to estimate parameters from eddy-flux observations

Aims Data assimilation is a useful tool to extract information from large datasets of the net ecosystem exchange (NEE) of CO₂ obtained by eddy-flux measurements. However, the number of parameters in ecosystem models that can be constrained by eddy-flux data is limited by conventional inverse analysis that estimates parameter values based on one-time inversion. This study aimed to improve data assimilation to increase the number of constrained parameters.Methods In this study, we developed conditional Bayesian inversion to maximize the number of parameters to be constrained by NEE data in several steps. In each step, we conducted a Bayesian inversion to constrain parameters. The maximum likelihood estimates of the constrained parameters were then used as prior to fix parameter values in the next step of inversion. The conditional inversion was repeated until there were no more parameters that could be further constrained. We applied the conditional inversion to hourly NEE data from Harvard Forest with a physiologically based ecosystem model.Important findings Results showed that the conventional inversion method constrained 6 of 16 parameters in the model while the conditional inversion method constrained 13 parameters after six steps. The cost function that indicates mismatch between the modeled and observed data decreased with each step of conditional Bayesian inversion. The Bayesian information criterion also decreased, suggesting reduced information loss with each step of conditional Bayesian inversion. A wavelet analysis reflected that model performance under conditional Bayesian inversion was better than that under conventional inversion at multiple time scales, except for seasonal and half-yearly scales. In addition, our analysis also demonstrated that parameter convergence in a subsequent step of the conditional inversion depended on correlations with the parameters constrained in a previous step. Overall, the conditional Bayesian inversion substantially increased the number of parameters to be constrained by NEE data and can be a powerful tool to be used in data assimilation in ecology.     

X-ray luminescence computed tomography using a hybrid proton propagation model and Lasso-LSQR algorithm

X-ray luminescence computed tomography (XLCT) uses external X-rays for luminescence excitation, which is becoming a promising molecular imaging technique with superb penetration depth and spatial resolution. To achieve the tomographic mapping of luminescence distribution, accurate optical propagation model and suitable reconstruction method are two keys for XLCT, but not satisfied. To overcome the limitation of the single proton propagation model (e.g., DE, SP₃), we adopted a hybrid diffusion equation with third order simplified spherical harmonics (DE-SP₃) model for XLCT. To enable fast iteration and accurate sparse reconstruction, we also integrated in the inversion optimization, with a novel Least Square QR-factorization based on the Lasso (Lasso-LSQR) algorithm. We first simulated the light propagation in various kinds of organs under DE model and SP₃ model, respectively. By comparison with the Monte Carlo, these tissues can be categorized into two types, namely DE-fitted tissues that include muscle and lung, and SP₃-fitted tissues including heart, kidney, liver, and stomach. According to the above classification results, we built a hybrid DE-SP₃ model to more accurately describing light transport. Numerical simulations and in vivo experiments illustrated that hybrid DE-SP₃ model achieves superior reconstruction performance in terms of location accuracy, and spatial resolution than DE, and less computational cost than SP₃. The hybrid DE-SP₃ model materializes a balance between accuracy and efficiency for XLCT.     

Synthetic data framework to estimate the minimum detectable concentration of contrast agents for multispectral optoacoustic imaging of small animals

The concentrations of contrast agents for optoacoustic imaging of small animals must usually be optimized through extensive pilot experiments on a case‐by‐case basis. The present work describes a streamlined approach for determining the minimum detectable concentration (MDC) of a contrast agent given experimental conditions and imaging system parameters. The developed Synthetic Data Framework (SDF) allows estimation of MDCs of various contrast agents under different tissue conditions without extensive animal experiments. The SDF combines simulated optoacoustic signals from exogenously administered contrast agents with in vivo experimental signals from background tissue to generate realistic synthetic multispectral optoacoustic images. In this paper, the SDF is validated with in vivo measurements and demonstrates close agreement between SDF synthetic data and experimental data in terms of both image intensity and MDCs. Use of the SDF to estimate MDCs for fluorescent dyes and nanoparticles at different tissue depths and for imaging lesions of different sizes is illustrated.     

Three-dimensional spatial reconstruction of coronary arteries based on fusion of intravascular optical coherence tomography and coronary angiography

We present a three-dimensional (3D) spatial reconstruction of coronary arteries based on fusion of intravascular optical coherence tomography (IVOCT) and digital subtraction angiography (DSA). Centerline of vessel in DSA images is exacted by multi-scale filtering, adaptive segmentation, morphology thinning and Dijkstra's shortest path algorithm. We apply the cross-correction between lumen shapes of IVOCT and DSA images and match their stenosis positions to realize co-registration. By matching the location and tangent direction of the vessel centerline of DSA images and segmented lumen coordinates of IVOCT along pullback path, 3D spatial models of vessel lumen are reconstructed. Using 1121 distinct positions selected from eight vessels, the correlation coefficient between 3D IVOCT model and DSA image in measuring lumen radius is 0.94% and 97.7% of the positions fall within the limit of agreement by Bland–Altman analysis, which means that the 3D spatial reconstruction IVOCT models and DSA images have high matching level.     

Front cover

Continuous-wave terahertz reflection imaging is a potential tool for biological tissues. Based on our home-made continuouswave terahertz reflection imaging system, the effect of both polarization mode and reflection window on the imaging performance is studied theoretically and experimentally, showing good agreement. By taking obtaining sample information and image contrast into consideration, p-polarized terahertz waves are recommended. Moreover, considering the sample boundary identification and the image contrast, selection criteria for reflection window are proposed. This work will help to improve the performance of continuous-wave terahertz reflection imaging and accelerate the THz imaging in biological application. Further details can be found in the article by Limin Wu, Yuye Wang, Haibin Li, Zelong Wang, Meilan Ge, Degang Xu, and Jianquan Yao ( e202100245 ).

     

Front Cover

The detection of colon cancer by using Poincaré sphere and 2D polarimetric imaging approach. Further details can be found in the article by Deyan Ivanov, Viktor Dremin, Alexander Bykov, Ekaterina Borisova, et al. ( e202000082 ).

     

Antimicrobial activity of amphiphilic nanomicelles loaded with curcumin against Pseudomonas aeruginosa alone and activated by blue laser light

The aim of this work was to assess the antimicrobial efficacy on Pseudomonas aeruginosa of nanomicelles loaded with curcumin (CUR) alone and activated by blue laser light in an antimicrobial photodynamic therapy (APDT) approach. First, free CUR in liquid suspension and loaded in three amphiphilic nanomicelles (CUR-DAPMA, CUR-SPD and CUR-SPM) were tested both on bacteria and keratinocytes. While free CUR exerted limited efficacy showing moderate cytotoxicity, a strong inhibition of bacterial growth was obtained using all three nanosystems without toxicity on eukaryotic cells. CUR-SPM emerged as the most effective, and was therefore employed in APDT experiments. Among the three sublethal blue laser (λ 445 nm) protocols tested, the ones characterized by a fluence of 18 and 30 J/cm² further decreased the antimicrobial concentration to 50 nM. The combination of blue laser APDT with CUR-SPM nanomicelles results in an effective synergistic activity that represents a promising novel therapeutic approach on resistant species.     

Biophotonics methods for functional monitoring of complications of diabetes mellitus

The prevalence of diabetes complications is a significant public health problem with a considerable economic cost. Thus, the timely diagnosis of complications and prevention of their development will contribute to increasing the length and quality of patient life, and reducing the economic costs of their treatment. This article aims to review the current state‐of‐the‐art biophotonics technologies used to identify the complications of diabetes mellitus and assess the quality of their treatment. Additionally, these technologies assess the structural and functional properties of biological tissues, and they include capillaroscopy, laser Doppler flowmetry and hyperspectral imaging, laser speckle contrast imaging, diffuse reflectance spectroscopy and imaging, fluorescence spectroscopy and imaging, optical coherence tomography, optoacoustic imaging and confocal microscopy. Recent advances in the field of optical noninvasive diagnosis suggest a wider introduction of biophotonics technologies into clinical practice and, in particular, in diabetes care units.     

Arena: Rapid and Accurate Reconstruction of Full Atomic RNA Structures From Coarse-grained Models

RNA tertiary structures from experiments or computational predictions often contain missing atoms, which prevent analyses requiring full atomic structures. Current programs for RNA reconstruction can be slow, inaccurate, and/or require specific atoms to be present in the input. We present Arena (Atomic Reconstruction of RNA), which reconstructs a full atomic RNA structure from residues that can have as few as one atom. Arena first fills in missing atoms and then iteratively refines their placement to reduce nonideal geometries. We benchmarked Arena on a dataset of 361 RNA structures, where Arena achieves high accuracy and speed compared to other structure reconstruction programs. For example, Arena was used to reconstruct full atomic structures from a single phosphorus atom per nucleotide to, on average, within 3.63 Å RMSD of the experimental structure, while virtually removing all clashes and running in <3 s, which is 353× and 46× faster than state-of-the-art programs PDBFixer and C2A, respectively. The Arena source code is available at https://github.com/pylelab/Arena and the webserver at https://zhanggroup.org/Arena/.     

Changes over time in means of suicide in Canada: an analysis of mortality data from 1981 to 2018

BACKGROUND:Ongoing surveillance of the means of suicide is necessary for effective prevention. We examined how mortality rates owing to different means of suicide changed in Canada from 1981 to 2018.METHODS:We obtained data from 1981 to 2018 on suicide deaths of individuals aged 10 years and older, from the Canadian Vital Statistics Death Database. We used joinpoint regression analysis to examine changes over time in the suicide mortality rate for the 3 most common means of suicide.RESULTS:The age-standardized suicide mortality rate declined in earlier decades for both sexes, but did not significantly change in recent decades for either sex. The age-standardized rate of suicide by suffocation increased from 1993 for females (2.1% per year) and from 1996 for males (0.4% per year). The age-standardized rate of suicide by poisoning decreased for females (2.2% per year) and males (2.1% per year) from 1981 to 2018. The age-standardized rate of suicide by firearm decreased from 1981 to 2008 (7.4% per year) but did not significantly change there-after for females; for males, it decreased 2.1% per year from 1981 to 1993 and 5.7% per year from 1993 to 2007, but did not significantly change thereafter.INTERPRETATION:For both sexes, the rate of suicide by poisoning is decreasing, the rate of suicide by suffocation is increasing, and the rate of suicide by firearm has not significantly changed in the last decade. Given the high proportion of suicide deaths by suffocation, its increasing rate and the difficulty of restricting the means of suffocation, other approaches to suicide prevention are needed.

The overall suicide mortality rate in Canada is lower than it was a few decades ago, but continued declines have been absent in recent years and the impact of suicide remains high.^1,2 Suicide was the ninth leading cause of death in 2018.³ More than three-quarters of suicide deaths in Canada are a result of suffocation, poisoning and firearms.^4–6 Suffocation is the predominant suicide method in most countries.⁴ However, the prevalence of different means of suicide can vary over time because of changes in the accessibility of certain means.⁷ Evidence suggests that the relative frequency of different means of suicide has changed in Canada, but those studies have not included data from more recent years.^8,9 Ongoing surveillance of the means of suicide and understanding changes over time are essential for designing and implementing prevention programs.¹⁰It is especially important to consider sex and age in suicide surveillance, because of differences across these sociodemographic characteristics. For instance, females are more likely to self-report thoughts of suicide and to be admitted to hospital owing to self-inflicted injuries,^5,11 while suicide mortality rates are about 3 times higher among males than females in Canada.^2,3,6 Higher suicide mortality rates for males have been observed in almost all countries,¹ and have been attributed, in part, to more lethal means of suicide (e.g., firearms).^5,6,12 Suicide-related behaviour also varies across the lifespan, with the suicide mortality rate tending to be high in middle-aged adults and males older than 80 years, but hospital admissions owing to self-inflicted injuries tending to occur during adolescence (particularly among females).^2,3,5,6,13Canadian data from 2000 to 2009 indicated that suicide by suffocation was more prevalent among individuals aged 15–39 years, while suicide by firearm was more prevalent among individuals aged 60 years and older.⁶ Canadian data for 2001 to 2011 suggested that rates of suicide by firearm and poisoning declined for males aged 15 years and older, but were unchanged among females during this period.⁹ Less is known about whether the means used by age and sex groups have fluctuated over longer periods and in more recent years. We sought to document the means of suicide deaths in Canada in 2018 (the most recent data available at the time of writing) and investigate how the use of different means has changed for males and females and across age groups since 1981.