Real-time photoacoustic imaging system for burn diagnosis

In vivo monitoring of hemoglobin derivatives in a rat thermal injury model using spectral diffuse reflectance imaging

INTRODUCTION

To demonstrate the feasibility of our previously proposed Diffuse reflectance spectral imaging (DRSI) method for in vivo monitoring of oxygenated hemoglobin, deoxygenated hemoglobin, methemoglobin, tissue oxygen saturation, and methemoglobin saturation in a rat scald burn wound model and assess whether the method could be used for differentiating the burn depth groups in rats based on the hemoglobin parameters.

METHODOLOGY

Superficial dermal burns (SDBs), deep dermal burns (DDBs), and deep burns (DBs) were induced in rat dorsal skin using a Walker-Mason method. An approach based on multiple regression analysis for spectral diffuse reflectance images aided by Monte Carlo simulations for light transport was used to quantify the hemoglobin parameters. Canonical discriminant analysis (CDA) was performed to discriminate SDB, DDB, and DB.

RESULTS

CDA using the total hemoglobin concentration, tissue oxygen saturation, and methemoglobin saturation as the independent variables showed good performance for discriminating the SDB, DDB, and DB groups immediately after burn injury and the SDB group from the DDB and DB groups 24-72 h after burn injury.

CONCLUSIONS

The DRSI method with multiple regression analysis for quantification of oxygenated hemoglobin, deoxygenated hemoglobin, and methemoglobin proved to be reliable for monitoring these hemoglobin derivatives in the rat experimental burn injury model. The parameters of tissue oxygen saturation, methemoglobin saturation, and total hemoglobin concentration are promising for the differentiating the degree of burn injury using CDA.

Burn depth assessment by dual-wavelength light emitting diodes-excited photoacoustic imaging in rats

Accurate burn depth assessment is crucial to determine treatment plans for burn patients. We have previously proposed a method for performing burn depth assessments based on photoacoustic (PA) imaging, and we have demonstrated the validity of this method, which allows the successful detection of PA signals originating from the blood under the bloodless burned tissue, using rat burn models. Based on these findings, we started a clinical study in which we faced two technical issues: (1) When the burn depth was shallow, PA signals due to skin contamination and/or melanin in the epidermis (surface signals) could not be distinguished from PA signals originating from the blood in the dermis; (2) the size of the system was too large. To solve these issues, we propose a burn depth diagnosis based on dual-wavelength light emitting diodes (LEDs)-excited PA imaging. The use of LEDs rendered the system compact compared to the previous one that used a conventional solid-state laser. We replicated human burned skin by applying a titrated synthetic melanin solution onto the wound surface in albino rat burn models and measured their burn depths by PA excitation at 690 and 850 nm, where melanin and haemoglobin show greatly different absorption coefficients. As a result, the surface signals were eliminated by subtracting the PA signals at 690 nm from those at 850 nm. The resultant estimated burn depths were strongly correlated with the histological assessment results. The validity of the proposed method was also examined using a burn model of rats with real melanin.

Deep neural network classification of in vivo burn injuries with different etiologies using terahertz time-domain spectral imaging

Thermal injuries can occur due to direct exposure to hot objects or liquids, flames, electricity, solar energy and several other sources. If the resulting injury is a deep partial thickness burn, the accuracy of a physician's clinical assessment is as low as 50-76% in determining the healing outcome. In this study, we show that the Terahertz Portable Handheld Spectral Reflection (THz-PHASR) Scanner combined with a deep neural network classification algorithm can accurately differentiate between partial-, deep partial-, and full-thickness burns 1-hour post injury, regardless of the etiology, scanner geometry, or THz spectroscopy sampling method (ROC-AUC = 91%, 88%, and 86%, respectively). The neural network diagnostic method simplifies the classification process by directly using the pre-processed THz spectra and removing the need for any hyperspectral feature extraction. Our results show that deep learning methods based on THz time-domain spectroscopy (THz-TDS) measurements can be used to guide clinical treatment plans based on objective and accurate classification of burn injuries.

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

SIGNIFICANCE

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

AIM

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

APPROACH

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

RESULTS

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

CONCLUSIONS

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

Application of OCT-Derived Attenuation Coefficient in Acute Burn-Damaged Skin

BACKGROUND AND OBJECTIVES

There remains a need to objectively monitor burn wound healing within a clinical setting, and optical coherence tomography (OCT) is proving itself one of the ideal modalities for just such a use. The aim of this study is to utilize the noninvasive and multipurpose capabilities of OCT, along with its cellular-level resolution, to demonstrate the application of optical attenuation coefficient (OAC), as derived from OCT data, to facilitate the automatic digital segmentation of the epidermis from scan images and to work as an objective indicator for burn wound healing assessment.

STUDY DESIGN/MATERIALS AND METHODS

A simple, yet efficient, method was used to estimate OAC from OCT images taken over multiple time points following acute burn injury. This method enhanced dermal-epidermal junction (DEJ) contrast, which facilitated the automatic segmentation of the epidermis for subsequent thickness measurements. In addition, we also measured and compared the average OAC of the dermis within said burns for correlative purposes.

RESULTS

Compared with unaltered OCT maps, enhanced DEJ contrast was shown in OAC maps, both from single A-lines and completed B-frames. En face epidermal thickness and dermal OAC maps both demonstrated significant changes between imaging sessions following burn injury, such as a loss of epidermal texture and decreased OAC. Quantitative analysis also showed that OAC of acute burned skin decreased below that of healthy skin following injury.

CONCLUSIONS

Our study has demonstrated that the OAC estimated from OCT data can be used to enhance imaging contrast to facilitate the automatic segmentation of the epidermal layer, as well as help elucidate our understanding of the pathological changes that occur in human skin when exposed to acute burn injury, which could serve as an objective indicator of skin injury and healing.

Real-time burn depth assessment using artificial networks: a large-scale, multicentre study

INTRODUCTION

Early judgment of the depth of burns is very important for the accurate formulation of treatment plans. In medical imaging the application of Artificial Intelligence has the potential for serving as a very experienced assistant to improve early clinical diagnosis. Due to lack of large volume of a particular feature, there has been almost no progress in burn field.

METHODS

484 early wound images are collected on patients who discharged home after a burn injury in 48 h, from five different levels of hospitals in Hunan Province China. According to actual healing time, all images are manually annotated by five professional burn surgeons and divided into three sets which are shallow(0-10 days), moderate(11-20 days) and deep(more than 21 days or skin graft healing). These ROIs were further divided into 5637 patches sizes 224 × 224 pixels, of which 1733 shallow, 1804 moderate, and 2100 deep. We used transfer learning suing a Pre-trained ResNet50 model and the ratio of all images is 7:1.5:1.5 for training:validation:test.

RESULTS

A novel artificial burn depth recognition model based on convolutional neural network was established and the diagnostic accuracy of the three types of burns is about 80%.

DISCUSSION

The actual healing time can be used to deduce the depth of burn involvement. The artificial burn depth recognition model can accurately infer healing time and burn depth of the patient, which is expected to be used for auxiliary diagnosis improvement.

Performance Characteristics of Photoacoustic Imaging Probes with Varying Frequencies and Light-delivery Schemes

Photoacoustic imaging (PAI) is an emerging biomedical imaging technique that utilizes a combination of light and ultrasound to detect photoabsorbers embedded within tissues. While the clinical utility of PAI has been widely explored for several applications, limitations in light penetration and detector sensitivity have restricted these studies to mostly superficial sites. Given the importance of PA signal generation and detection on light delivery and ultrasound detector frequency, there is an ongoing effort to optimize these parameters to enhance photoabsorber detection at increased depths. With this in mind, in this study we examined performance benchmarks of a commercially available PAI/ultrasound linear array system when using different imaging frequencies and light delivery schemes. A modified light fiber jacket providing focused light delivery (FLD) at the center of the probe was compared with the built-in fiber optics lining the length of the probe. Studies were performed in vitro to compare performance characteristics such as imaging resolution, maximum imaging depth, and sensitivity to varying hematocrit concentration for each frequency and light delivery method. Monte Carlo simulations of each light delivery method revealed increased light penetration with FLD. In tissue-mimicking phantoms, vascular channels used to simulate blood vessels could be visualized at a depth of 2.4 cm when lowering imaging frequency and utilizing FLD. Imaging at lower frequencies with FLD also enabled enhanced detection of varying hematocrit concentration levels at increased depths, although lateral imaging resolution was reduced. Finally, a proof of concept in vivo probe comparison study in a mouse tumor model provided supportive evidence of our in vitro results. Collectively, our findings show that adjusting imaging frequency and applying FLD can be a straightforward approach for improving PAI performance.

In vivo dual-scale photoacoustic surveillance and assessment of burn healing

Accurate diagnoses of superficial and deep dermal burns are difficult to make even by experienced investigators due to slight differences in dermis damage. Many imaging technologies have been developed to improve the burn depth assessment. But these imaging tools have limitations in deep imaging or resolving ability. Photoacoustic imaging is a hybrid modality combining optical and ultrasound imaging that remains high resolution in deep imaging depth. In this work, we used dual-scale photoacoustic imaging to noninvasively diagnose burn injury and monitor the burn healing. Real-time PACT provided cross-sectional and volumetric images of the burn region. High-resolution PAM allowed for imaging of angiogenesis on the hyperemic ring. A long-term surveillance was also performed to assess the difference between the two damage degrees of burn injuries. Our proposed method suggests an effective tool to diagnose and monitor burn injury.

Optoacoustic mesoscopy for biomedicine

Fuelled by innovation, optical microscopy plays a critical role in the life sciences and medicine, from basic discovery to clinical diagnostics. However, optical microscopy is limited by typical penetration depths of a few hundred micrometres for in vivo interrogations in the visible spectrum. Optoacoustic microscopy complements optical microscopy by imaging the absorption of light, but it is similarly limited by penetration depth. In this Review, we summarize progress in the development and applicability of optoacoustic mesoscopy (OPAM); that is, optoacoustic imaging with acoustic resolution and wide-bandwidth ultrasound detection. OPAM extends the capabilities of optical imaging beyond the depths accessible to optical and optoacoustic microscopy, and thus enables new applications. We explain the operational principles of OPAM, its placement as a bridge between optoacoustic microscopy and optoacoustic macroscopy, and its performance in the label-free visualization of tissue pathophysiology, such as inflammation, oxygenation, vascularization and angiogenesis. We also review emerging applications of OPAM in clinical and biological imaging.

Imaging Techniques for Clinical Burn Assessment with a Focus on Multispectral Imaging

Significance: Burn assessments, including extent and severity, are some of the most critical diagnoses in burn care, and many recently developed imaging techniques may have the potential to improve the accuracy of these evaluations. Recent Advances: Optical devices, telemedicine, and high-frequency ultrasound are among the highlights in recent burn imaging advancements. We present another promising technology, multispectral imaging (MSI), which also has the potential to impact current medical practice in burn care, among a variety of other specialties. Critical Issues: At this time, it is still a matter of debate as to why there is no consensus on the use of technology to assist burn assessments in the United States. Fortunately, the availability of techniques does not appear to be a limitation. However, the selection of appropriate imaging technology to augment the provision of burn care can be difficult for clinicians to navigate. There are many technologies available, but a comprehensive review summarizing the tissue characteristics measured by each technology in light of aiding clinicians in selecting the proper device is missing. This would be especially valuable for the nonburn specialists who encounter burn injuries. Future Directions: The questions of when burn assessment devices are useful to the burn team, how the various imaging devices work, and where the various burn imaging technologies fit into the spectrum of burn care will continue to be addressed. Technologies that can image a large surface area quickly, such as thermography or laser speckle imaging, may be suitable for initial burn assessment and triage. In the setting of presurgical planning, ultrasound or optical microscopy techniques, including optical coherence tomography, may prove useful. MSI, which actually has origins in burn care, may ultimately meet a high number of requirements for burn assessment in routine clinical use.

Structural and Functional Analysis of Intact Hair Follicles and Pilosebaceous Units by Volumetric Multispectral Optoacoustic Tomography

Visualizing anatomical and functional features of hair follicle development in their unperturbed environment is key in understanding complex mechanisms of hair pathophysiology and in discovery of novel therapies. Of particular interest is in vivo visualization of the intact pilosebaceous unit, vascularization of the hair bulb, and evaluation of the hair cycle, particularly in humans. Furthermore, noninvasive visualization of the sebaceous glands could offer crucial insight into the pathophysiology of follicle-related diseases and dry or seborrheic skin, in particular by combining in vivo imaging with other phenotyping, genotyping, and microbial analyses. The available imaging techniques are limited in their ability for deep tissue in vivo imaging of hair follicles and lipid-rich sebaceous glands in their entirety without biopsy. We developed a noninvasive, painless, and risk-free volumetric multispectral optoacoustic tomography method for deep tissue three-dimensional visualization of whole hair follicles and surrounding structures with high spatial resolution below 80 μm. Herein we demonstrate on-the-fly assessment of key morphometric parameters of follicles and lipid content as well as functional oxygenation parameters of the associated capillary bed. The ease of handheld operation and versatility of the newly developed approach poise it as an indispensable tool for early diagnosis of disorders of the pilosebaceous unit and surrounding structures, and for monitoring the efficacy of cosmetic and therapeutic interventions.

Burn depth assessments by photoacoustic imaging and laser Doppler imaging

Diagnosis of burn depths is crucial to determine the treatment plan for severe burn patients. However, an objective method for burn depth assessment has yet to be established, although a commercial laser Doppler imaging (LDI) system is used limitedly. We previously proposed burn depth assessment based on photoacoustic imaging (PAI), in which thermoelastic waves originating from blood under the burned tissue are detected, and we showed the validity of the method by experiments using rat models with three different burn depths: superficial dermal burn, deep dermal burn and deep burn. On the basis of those results, we recently developed a real-time PAI system for clinical burn diagnosis. Before starting a clinical trial, however, there is a need to reveal more detailed diagnostic characteristics, such as linearity and error, of the PAI system as well as to compare its characteristics with those of an LDI system. In this study, we prepared rat models with burns induced at six different temperatures from 70 to 98 °C, which showed a linear dependence of injury depth on the temperature. Using these models, we examined correlations of signals obtained by PAI and LDI with histologically determined injury depths and burn induction temperatures at 48 hours postburn. We found that the burn depths indicated by PAI were highly correlative with histologically determined injury depths (depths of viable vessels) as well as with burn induction temperatures. Perfusion values measured by LDI were less correlative with these parameters, especially for burns induced at higher temperatures, being attributable to the limited detectable depth for light involving a Doppler shift in tissue. In addition, the measurement errors in PAI were smaller than those in LDI. On the basis of these results, we will be able to start clinical studies using the present PAI system.