Skip to main content
eScholarship
Open Access Publications from the University of California
Cover page of Assessing the Outcomes of Focused Heating of the Skin by a Long-Pulsed 1064 nm Laser with an Integrated Scanner, Infrared Thermal Guidance, and Optical Coherence Tomography.

Assessing the Outcomes of Focused Heating of the Skin by a Long-Pulsed 1064 nm Laser with an Integrated Scanner, Infrared Thermal Guidance, and Optical Coherence Tomography.

(2021)

BACKGROUND AND OBJECTIVE: Long-term benefits can be predicted by the incorporation of more intelligent systems in lasers and other devices. Such systems can produce more reliable zones of thermal injury when used in association with non-invasive monitoring and precise laser energy delivery. The more classical endpoint of tumor destruction with radiofrequency or long-pulsed (LP) 1064 nm laser is the non-specific appearance of tissue graying and tissue contraction. Herein we discuss combining non-invasive LP 1064 nm Nd:YAG treatment with the assistance of optical coherence tomography (OCT) and the forward-looking infrared (FLIR) thermal camera while testing literature-based formulae for thermal destruction.

Study design/materials and methods

The skin on the forearm and back of two consenting volunteers was marked and anesthetized with lidocaine with epinephrine. The parameters of a scanner-equipped LP 1064 nm Nd:YAG laser were adjusted to achieve an epidermal/superficial dermal heating of between 50°C and 60°C over a specified time course. Experimental single treatments examined various adjusted parameters including, fluence, pulse overlap, pulse duration, scan size, and pulse rate. A FLIR camera was used to record skin temperature. Outcome measures included skin temperature, post-treatment appearance, and OCT assessment of skin and vascular damage. The clinical response of each treatment was followed daily for 4 weeks.

Results

Optimal protocols initially raised the skin temperature to between 55°C and 60°C, which was carefully maintained using subsequent laser passes over a 60-second time course. Immediately post laser, clinical responses included erythema, edema, and blistering. Immediate OCT revealed increased vascularity with intact, dilated blood vessels. Prolonged exposure above 60°C resulted in sub-epidermal blistering and an absence of blood flow in the treatment area with prolonged healing.

Conclusion

The LP 1064 nm laser can be used to achieve heat-related tissue injury, though the narrow parameters necessary for the desired endpoint require the assistance of IR thermal regulation to avoid unacceptable outcomes. The use of the laser scanner ensures precise energy delivery over a defined treatment area. Future studies might explore this as a selective hyperthermic method for the treatment of non-melanoma skin cancer. Lasers Surg. Med. © 2021 Wiley Periodicals LLC.

Cover page of Phasor-based hyperspectral snapshot microscopy allows fast imaging of live, three-dimensional tissues for biomedical applications.

Phasor-based hyperspectral snapshot microscopy allows fast imaging of live, three-dimensional tissues for biomedical applications.

(2021)

Hyperspectral imaging is highly sought after in many fields including mineralogy and geology, environment and agriculture, astronomy and, importantly, biomedical imaging and biological fluorescence. We developed ultrafast phasor-based hyperspectral snapshot microscopy based on sine/cosine interference filters for biomedical imaging not feasible with conventional hyperspectral detection methods. Current approaches rely on slow spatial or spectral scanning limiting their application in living biological tissues, while faster snapshot methods such as image mapping spectrometry and multispectral interferometry are limited in spatial and/or spectral resolution, are computationally demanding, and imaging devices are very expensive to manufacture. Leveraging light sheet microscopy, phasor-based hyperspectral snapshot microscopy improved imaging speed 10-100 fold which, combined with minimal light exposure and high detection efficiency, enabled hyperspectral metabolic imaging of live, three-dimensional mouse tissues not feasible with other methods. As a fit-free method that does not require any a priori information often unavailable in complex and evolving biological systems, the rule of linear combinations of the phasor could spectrally resolve subtle differences between cell types in the developing zebrafish retina and spectrally separate and track multiple organelles in 3D cultured cells over time. The sine/cosine snapshot method is adaptable to any microscope or imaging device thus making hyperspectral imaging and fit-free analysis based on linear combinations broadly available to researchers and the public.

Cover page of Protocol for rapid ammonia detection via surface-enhanced Raman spectroscopy.

Protocol for rapid ammonia detection via surface-enhanced Raman spectroscopy.

(2021)

As a key industrial nitrogenous product and a critical environmental pollutant, ammonia broadly affects our daily lives. Rapid and sensitive detection of ammonia is essential to both environmental monitoring and process control for industrial manufacturing. Here, we present a protocol for rapid detection of low amounts of ammonia in the aqueous phase, via surface-enhanced Raman spectroscopy. We believe the mechanism and speed of the approach demonstrate its potential toward applications in operando electrochemical catalysis and in situ ammonia detection. For complete details on the use and execution of this protocol, please refer to Liu et al. (2020).

Cover page of Coherent Raman scattering microscopy: capable solution in search of a larger audience.

Coherent Raman scattering microscopy: capable solution in search of a larger audience.

(2021)

Significance

Coherent Raman scattering (CRS) microscopy is an optical imaging technique with capabilities that could benefit a broad range of biomedical research studies.

Aim

We reflect on the birth, rapid rise, and inescapable growing pains of the technique and look back on nearly four decades of developments to examine where the CRS imaging approach might be headed in the next decade to come.

Approach

We provide a brief historical account of CRS microscopy, followed by a discussion of the challenges to disseminate the technique to a larger audience. We then highlight recent progress in expanding the capabilities of the CRS microscope and assess its current appeal as a practical imaging tool.

Results

New developments in Raman tagging have improved the specificity and sensitivity of the CRS technique. In addition, technical advances have led to CRS microscopes that can capture hyperspectral data cubes at practical acquisition times. These improvements have broadened the application space of the technique.

Conclusion

The technical performance of the CRS microscope has improved dramatically since its inception, but these advances have not yet translated into a substantial user base beyond a strong core of enthusiasts. Nonetheless, new developments are poised to move the unique capabilities of the technique into the hands of more users.

Cover page of Mobile-based oral cancer classification for point-of-care screening.

Mobile-based oral cancer classification for point-of-care screening.

(2021)

Significance

Oral cancer is among the most common cancers globally, especially in low- and middle-income countries. Early detection is the most effective way to reduce the mortality rate. Deep learning-based cancer image classification models usually need to be hosted on a computing server. However, internet connection is unreliable for screening in low-resource settings.

Aim

To develop a mobile-based dual-mode image classification method and customized Android application for point-of-care oral cancer detection.

Approach

The dataset used in our study was captured among 5025 patients with our customized dual-modality mobile oral screening devices. We trained an efficient network MobileNet with focal loss and converted the model into TensorFlow Lite format. The finalized lite format model is ∼16.3  MB and ideal for smartphone platform operation. We have developed an Android smartphone application in an easy-to-use format that implements the mobile-based dual-modality image classification approach to distinguish oral potentially malignant and malignant images from normal/benign images.

Results

We investigated the accuracy and running speed on a cost-effective smartphone computing platform. It takes ∼300  ms to process one image pair with the Moto G5 Android smartphone. We tested the proposed method on a standalone dataset and achieved 81% accuracy for distinguishing normal/benign lesions from clinically suspicious lesions, using a gold standard of clinical impression based on the review of images by oral specialists.

Conclusions

Our study demonstrates the effectiveness of a mobile-based approach for oral cancer screening in low-resource settings.

Cover page of Spectroscopic and deep learning-based approaches to identify and quantify cerebral microhemorrhages.

Spectroscopic and deep learning-based approaches to identify and quantify cerebral microhemorrhages.

(2021)

Cerebral microhemorrhages (CMHs) are associated with cerebrovascular disease, cognitive impairment, and normal aging. One method to study CMHs is to analyze histological sections (5-40 μm) stained with Prussian blue. Currently, users manually and subjectively identify and quantify Prussian blue-stained regions of interest, which is prone to inter-individual variability and can lead to significant delays in data analysis. To improve this labor-intensive process, we developed and compared three digital pathology approaches to identify and quantify CMHs from Prussian blue-stained brain sections: (1) ratiometric analysis of RGB pixel values, (2) phasor analysis of RGB images, and (3) deep learning using a mask region-based convolutional neural network. We applied these approaches to a preclinical mouse model of inflammation-induced CMHs. One-hundred CMHs were imaged using a 20 × objective and RGB color camera. To determine the ground truth, four users independently annotated Prussian blue-labeled CMHs. The deep learning and ratiometric approaches performed better than the phasor analysis approach compared to the ground truth. The deep learning approach had the most precision of the three methods. The ratiometric approach has the most versatility and maintained accuracy, albeit with less precision. Our data suggest that implementing these methods to analyze CMH images can drastically increase the processing speed while maintaining precision and accuracy.

Cover page of 1.7-micron Optical Coherence Tomography Angiography for Characterization of Skin Lesions - A Feasibility Study.

1.7-micron Optical Coherence Tomography Angiography for Characterization of Skin Lesions - A Feasibility Study.

(2021)

Optical coherence tomography (OCT) is a non-invasive diagnostic method that offers real-time visualization of the layered architecture of the skin in vivo. The 1.7-micron OCT system has been applied in cardiology, gynecology and dermatology, demonstrating an improved penetration depth in contrast to conventional 1.3-micron OCT. To further extend the capability, we developed a 1.7-micron OCT/OCT angiography (OCTA) system that allows for a visualization of both morphology and microvasculature in the deeper layers of the skin. Using this imaging system, we imaged human skin with different benign lesions and described the corresponding features of both structure and vasculature. The significantly improved imaging depth and additional functional information suggest that the 1.7-micron OCTA system has great potential to advance both dermatological clinical and research settings for characterization of benign and cancerous skin lesions.

Cover page of Integrated pulse scope for tunable generation and intrinsic characterization of structured femtosecond laser.

Integrated pulse scope for tunable generation and intrinsic characterization of structured femtosecond laser.

(2021)

Numerous techniques have been demonstrated for effective generation of orbital angular momentum-carrying radiation, but intracavity generation of continuously tunable pulses in the femtosecond regime remains challenging. Even if such a creation was realized, the generated pulses-like all pulses in reality-are complex and transitory objects that can only be comprehensively characterized via multidimensional spaces. An integrated lasing system that generates pulses while simultaneously quantifies them can achieve adaptive pulse tailoring. Here, we report a femtosecond pulse scope that unifies vector vortex mode-locked lasing and vectorial quantification. With intracavity-controlled Pancharatnam-Berry phase modulation, continuous and ergodic generation of spirally polarized states along a broadband higher-order Poincaré sphere was realized. By intrinsically coupling a two-dimensional polarization-sensitive time-scanning interferometer to the laser, multidimensional spatiotemporal features of the pulse were further visualized. The proposed methodology paves the way for design optimization of ultrafast optics by integrating complex femtosecond pulse generation and structural customization, facilitating its applications in optical physics research and laser-based manufacturing.

Cover page of The contribution of artificial intelligence to reducing the diagnostic delay in oral cancer.

The contribution of artificial intelligence to reducing the diagnostic delay in oral cancer.

(2021)

Oral cancer (OC) is the sixth most commonly reported malignant disease globally, with high rates of disease-related morbidity and mortality due to advanced loco-regional stage at diagnosis. Early detection and prompt treatment offer the best outcomes to patients, yet the majority of OC lesions are detected at late stages with 45% survival rate for 2 years. The primary cause of poor OC outcomes is unavailable or ineffective screening and surveillance at the local point-of-care level, leading to delays in specialist referral and subsequent treatment. Lack of adequate awareness of OC among the public and professionals, and barriers to accessing health care services in a timely manner also contribute to delayed diagnosis. As image analysis and diagnostic technologies are evolving, various artificial intelligence (AI) approaches, specific algorithms and predictive models are beginning to have a considerable impact in improving diagnostic accuracy for OC. AI based technologies combined with intraoral photographic images or optical imaging methods are under investigation for automated detection and classification of OC. These new methods and technologies have great potential to improve outcomes, especially in low-resource settings. Such approaches can be used to predict oral cancer risk as an adjunct to population screening by providing real-time risk assessment. The objective of this study is to (1) provide an overview of components of delayed OC diagnosis and (2) evaluate novel AI based approaches with respect to their utility and implications for improving oral cancer detection.