Economical and compact briefcase spectral-domain optical coherence tomography system for primary care and point-of-care applications

Intraoperative quantitative crystalline lens nuclear opacities analysis based on crystalline lenSx platform

PURPOSE

The main objective is to quantify the lens nuclear opacity using spectral-domain optical coherence tomography (SD-OCT) and to evaluate its association with Lens Opacities Classification System III (LOCS-III) system, lens thickness (LT), and surgical parameters. The secondary objective is to assess the diagnostic model performance for hard nuclear cataract.

METHODS

This study included 70 eyes of 57 adults with cataract, with 49 (70%) and 21 (30%) in training and validation cohort, respectively. Correlations of the average nuclear density (AND) /maximum nuclear density (MND) with LOCS-III scores, LT, and surgical parameters were analyzed. Univariate and multivariate logistic regression analysis, receiver operating characteristic curves and calibration curves were performed for the diagnostic of hard nuclear cataract.

RESULTS

The pre-operative uncorrected distance visual acuity (UDVA), intraocular pressure (IOP), mean axial length (AL), and LT were 1.20 ± 0.47 log MAR, 15.50 ± 2.87 mmHg, 27.34 ± 3.77 mm and 4.32 ± 0.45 mm, respectively. The average nuclear opalescence (NO) and nuclear colour (NC) scores were 3.61 ± 0.94 and 3.50 ± 0.91 (ranging from 1.00 to 6.90), respectively. The average AND and MND were 137.94 ± 17.01 and 230.01 ± 8.91, respectively. NC and NO scores both significantly correlated with the AND (rNC = 0.733, p = 0.000; rNO = 0.755, p = 0.000) and MND (rNC = 0.643, p = 0.000; rNO = 0.634, p = 0.000). In the training cohort, the area under the curve (AUC) of the model was 0.769 (P < 0.001, 95%CI 0.620-0.919), which had a good degree of differentiation (Fig. 2a). The calibration curve showed good agreement between predicted and actual probability.

CONCLUSION

The nuclear density measurement on SD-OCT images can serve as an objective and reliable indicator for quantifying nuclear density.

Optical imaging technologies for in vivo cancer detection in low-resource settings

Cancer continues to affect underserved populations disproportionately. Novel optical imaging technologies, which can provide rapid, non-invasive, and accurate cancer detection at the point of care, have great potential to improve global cancer care. This article reviews the recent technical innovations and clinical translation of low-cost optical imaging technologies, highlighting the advances in both hardware and software, especially the integration of artificial intelligence, to improve in vivo cancer detection in low-resource settings. Additionally, this article provides an overview of existing challenges and future perspectives of adapting optical imaging technologies into clinical practice, which can potentially contribute to novel insights and programs that effectively improve cancer detection in low-resource settings.

Rapid imaging and product screening with low-cost line-field Fourier domain optical coherence tomography

Fourier domain optical coherence tomography (FD-OCT) is a well-established imaging technique that provides high-resolution internal structure images of an object at a fast speed. Modern FD-OCT systems typically operate at speeds of 40,000-100,000 A-scans/s, but are priced at least tens of thousands of pounds. In this study, we demonstrate a line-field FD-OCT (LF-FD-OCT) system that achieves an OCT imaging speed of 100,000 A-scan/s at a hardware cost of thousands of pounds. We demonstrate the potential of LF-FD-OCT for biomedical and industrial imaging applications such as corneas, 3D printed electronics, and printed circuit boards.

SmartOCT: smartphone-integrated optical coherence tomography

Smartphone devices have seen unprecedented technical innovation in computational power and optical imaging capabilities, making them potentially invaluable tools in scientific imaging applications. The smartphone's compact form-factor and broad accessibility has motivated researchers to develop smartphone-integrated imaging systems for a wide array of applications. Optical coherence tomography (OCT) is one such technique that could benefit from smartphone-integration. Here, we demonstrate smartOCT, a smartphone-integrated OCT system that leverages built-in components of a smartphone for detection, processing and display of OCT data. SmartOCT uses a broadband visible-light source and line-field OCT design that enables snapshot 2D cross-sectional imaging. Furthermore, we describe methods for processing smartphone data acquired in a RAW data format for scientific applications that improves the quality of OCT images. The results presented here demonstrate the potential of smartphone-integrated OCT systems for low-resource environments.

Performing tympanometry using smartphones

Background

Tympanometry is used as part of a battery of tests for screening of middle ear function and may help diagnose middle ear disorders, but remains available only on expensive test equipment.

Methods

We report a low-cost smartphone-based tympanometer system that consists of a lightweight and portable attachment to vary air pressure in the ear and measure middle ear function. The smartphone displays a tympanogram and reports peak acoustic admittance in realtime. Our programmable and open-source system operates at 226 Hz and was tested on 50 pediatric patient ears in an audiology clinic in parallel with a commercial tympanometer.

Results

Our study shows an average agreement of 86 ± 2% between the 100 tympanograms produced by the smartphone and commercial device when five pediatric audiologists classified them into five classes based on the Liden and Jerger classification.

Conclusion

Given the accessibility and prevalence of budget smartphones in developing countries, our open-source tool may help provide timely and affordable screening of middle ear disorders.

Tympanometry is a test used to evaluate the health of the middle ear, which is involved in hearing, and helps in diagnosing middle ear disorders. However, the test currently requires expensive equipment and is limited in availability in resource-constrained settings. We present a low-cost smartphone-based tympanometry system. The device is able to change the air pressure of the ear canal and measure ear drum mobility. Our system, for which the software and hardware are openly available, is tested in 50 ears from children attending an audiology clinic. A panel of pediatric audiologists classified tympanometry measurements from our device and a commercial tympanometer with good agreement. Given the increasing availability of smartphones in developing countries, our system has the potential to make screening of middle ear disorders more accessible.

Chan et al. develop an open-source smartphone-based tympanometer to evaluate middle ear function. The authors test their device in a group of paediatric patients at an audiology clinic and report a high level of agreement in audiologists’ classification of tympanograms produced using this device compared with a commercial device.

Enhanced medical diagnosis for dOCTors: a perspective of optical coherence tomography

SIGNIFICANCE

After three decades, more than 75,000 publications, tens of companies being involved in its commercialization, and a global market perspective of about USD 1.5 billion in 2023, optical coherence tomography (OCT) has become one of the fastest successfully translated imaging techniques with substantial clinical and economic impacts and acceptance.

AIM

Our perspective focuses on disruptive forward-looking innovations and key technologies to further boost OCT performance and therefore enable significantly enhanced medical diagnosis.

APPROACH

A comprehensive review of state-of-the-art accomplishments in OCT has been performed.

RESULTS

The most disruptive future OCT innovations include imaging resolution and speed (single-beam raster scanning versus parallelization) improvement, new implementations for dual modality or even multimodality systems, and using endogenous or exogenous contrast in these hybrid OCT systems targeting molecular and metabolic imaging. Aside from OCT angiography, no other functional or contrast enhancing OCT extension has accomplished comparable clinical and commercial impacts. Some more recently developed extensions, e.g., optical coherence elastography, dynamic contrast OCT, optoretinography, and artificial intelligence enhanced OCT are also considered with high potential for the future. In addition, OCT miniaturization for portable, compact, handheld, and/or cost-effective capsule-based OCT applications, home-OCT, and self-OCT systems based on micro-optic assemblies or photonic integrated circuits will revolutionize new applications and availability in the near future. Finally, clinical translation of OCT including medical device regulatory challenges will continue to be absolutely essential.

CONCLUSIONS

With its exquisite non-invasive, micrometer resolution depth sectioning capability, OCT has especially revolutionized ophthalmic diagnosis and hence is the fastest adopted imaging technology in the history of ophthalmology. Nonetheless, OCT has not been completely exploited and has substantial growth potential-in academics as well as in industry. This applies not only to the ophthalmic application field, but also especially to the original motivation of OCT to enable optical biopsy, i.e., the in situ imaging of tissue microstructure with a resolution approaching that of histology but without the need for tissue excision.

A review of low-cost and portable optical coherence tomography

Optical coherence tomography (OCT) is a powerful optical imaging technique capable of visualizing the internal structure of biological tissues at near cellular resolution. For years, OCT has been regarded as the standard of care in ophthalmology, acting as an invaluable tool for the assessment of retinal pathology. However, the costly nature of most current commercial OCT systems has limited its general accessibility, especially in low-resource environments. It is therefore timely to review the development of low-cost OCT systems as a route for applying this technology to population-scale disease screening. Low-cost, portable and easy to use OCT systems will be essential to facilitate widespread use at point of care settings while ensuring that they offer the necessary imaging performances needed for clinical detection of retinal pathology. The development of low-cost OCT also offers the potential to enable application in fields outside ophthalmology by lowering the barrier to entry. In this paper, we review the current development and applications of low-cost, portable and handheld OCT in both translational and research settings. Design and cost-reduction techniques are described for general low-cost OCT systems, including considerations regarding spectrometer-based detection, scanning optics, system control, signal processing, and the role of 3D printing technology. Lastly, a review of clinical applications enabled by low-cost OCT is presented, along with a detailed discussion of current limitations and outlook.

Synthetic polarization-sensitive optical coherence tomography by deep learning

Polarization-sensitive optical coherence tomography (PS-OCT) is a high-resolution label-free optical biomedical imaging modality that is sensitive to the microstructural architecture in tissue that gives rise to form birefringence, such as collagen or muscle fibers. To enable polarization sensitivity in an OCT system, however, requires additional hardware and complexity. We developed a deep-learning method to synthesize PS-OCT images by training a generative adversarial network (GAN) on OCT intensity and PS-OCT images. The synthesis accuracy was first evaluated by the structural similarity index (SSIM) between the synthetic and real PS-OCT images. Furthermore, the effectiveness of the computational PS-OCT images was validated by separately training two image classifiers using the real and synthetic PS-OCT images for cancer/normal classification. The similar classification results of the two trained classifiers demonstrate that the predicted PS-OCT images can be potentially used interchangeably in cancer diagnosis applications. In addition, we applied the trained GAN models on OCT images collected from a separate OCT imaging system, and the synthetic PS-OCT images correlate well with the real PS-OCT image collected from the same sample sites using the PS-OCT imaging system. This computational PS-OCT imaging method has the potential to reduce the cost, complexity, and need for hardware-based PS-OCT imaging systems.

Handheld Briefcase Optical Coherence Tomography with Real-Time Machine Learning Classifier for Middle Ear Infections

A middle ear infection is a prevalent inflammatory disease most common in the pediatric population, and its financial burden remains substantial. Current diagnostic methods are highly subjective, relying on visual cues gathered by an otoscope. To address this shortcoming, optical coherence tomography (OCT) has been integrated into a handheld imaging probe. This system can non-invasively and quantitatively assess middle ear effusions and identify the presence of bacterial biofilms in the middle ear cavity during ear infections. Furthermore, the complete OCT system is housed in a standard briefcase to maximize its portability as a diagnostic device. Nonetheless, interpreting OCT images of the middle ear more often requires expertise in OCT as well as middle ear infections, making it difficult for an untrained user to operate the system as an accurate stand-alone diagnostic tool in clinical settings. Here, we present a briefcase OCT system implemented with a real-time machine learning platform for middle ear infections. A random forest-based classifier can categorize images based on the presence of middle ear effusions and biofilms. This study demonstrates that our briefcase OCT system coupled with machine learning can provide user-invariant classification results of middle ear conditions, which may greatly improve the utility of this technology for the diagnosis and management of middle ear infections.

Panel 1: Biotechnology, biomedical engineering and new models of otitis media

OBJECTIVE

To summarize recently published key articles on the topics of biomedical engineering, biotechnology and new models in relation to otitis media (OM).

DATA SOURCES

Electronic databases: PubMed, Ovid Medline, Cochrane Library and Clinical Evidence (BMJ Publishing).

REVIEW METHODS

Articles on biomedical engineering, biotechnology, material science, mechanical and animal models in OM published between May 2015 and May 2019 were identified and subjected to review. A total of 132 articles were ultimately included.

RESULTS

New imaging technologies for the tympanic membrane (TM) and the middle ear cavity are being developed to assess TM thickness, identify biofilms and differentiate types of middle ear effusions. Artificial intelligence (AI) has been applied to train software programs to diagnose OM with a high degree of certainty. Genetically modified mice models for OM have further investigated what predisposes some individuals to OM and consequent hearing loss. New vaccine candidates protecting against major otopathogens are being explored and developed, especially combined vaccines, targeting more than one pathogen. Transcutaneous vaccination against non-typeable Haemophilus influenzae has been successfully tried in a chinchilla model. In terms of treatment, novel technologies for trans-tympanic drug delivery are entering the clinical domain. Various growth factors and grafting materials aimed at improving healing of TM perforations show promising results in animal models.

CONCLUSION

New technologies and AI applications to improve the diagnosis of OM have shown promise in pre-clinical models and are gradually entering the clinical domain. So are novel vaccines and drug delivery approaches that may allow local treatment of OM.

IMPLICATIONS FOR PRACTICE

New diagnostic methods, potential vaccine candidates and the novel trans-tympanic drug delivery show promising results, but are not yet adapted to clinical use.

Otitis Media Middle Ear Effusion Identification and Characterization Using an Optical Coherence Tomography Otoscope

OBJECTIVE

To determine the feasibility of detecting and differentiating middle ear effusions (MEEs) using an optical coherence tomography (OCT) otoscope.

STUDY DESIGN

Cross-sectional study.

SETTING

US tertiary care children's hospital.

SUBJECTS AND METHODS

Seventy pediatric patients undergoing tympanostomy tube placement were preoperatively imaged using an OCT otoscope. A blinded reader quiz was conducted using 24 readers from 4 groups of tiered medical expertise. The primary outcome assessed was reader ability to detect presence/absence of MEE. A secondary outcome assessed was reader ability to differentiate serous vs nonserous MEE.

RESULTS

OCT image data sets were analyzed from 45 of 70 total subjects. Blinded reader analysis of an OCT data subset for detection of MEE resulted in 90.6% accuracy, 90.9% sensitivity, 90.2% specificity, and intra/interreader agreement of 92.9% and 87.1%, respectively. Differentiating MEE type, reader identification of nonserous MEE had 70.8% accuracy, 53.6% sensitivity, 80.1% specificity, and intra/interreader agreement of 82.9% and 75.1%, respectively. Multivariate analysis revealed that age was the strongest predictor of OCT quality. The mean age of subjects with quality OCT was 5.01 years (n = 45), compared to 2.54 years (n = 25) in the remaining subjects imaged (P = .0028). The ability to capture quality images improved over time, from 50% to 69.4% over the study period.

CONCLUSION

OCT otoscopy shows promise for facilitating accurate MEE detection. The imageability with the prototype device was affected by age, with older children being easier to image, similar to current ear diagnostic technologies.

Two dimensional non-scanning transform-free spatial-domain optical coherence tomography

A novel optical coherence tomography system that can perform scanless two dimensional imaging without Fourier transform is proposed and demonstrated. In the system, a convex cylindrical mirror generates an extended spatial distribution of optical delay in the reference arm and a cylindrical lens is used to form a focused line beam in the sample arm. A charge-coupled device camera captures the two dimensional tomographic image of a sample in a snap-shot manner. Due to its simple configuration and operation, the system is suitable for developing a compact device for tomographic imaging and measurement.

Automated classification platform for the identification of otitis media using optical coherence tomography

The diagnosis and treatment of otitis media (OM), a common childhood infection, is a significant burden on the healthcare system. Diagnosis relies on observer experience via otoscopy, although for non-specialists or inexperienced users, accurate diagnosis can be difficult. In past studies, optical coherence tomography (OCT) has been used to quantitatively characterize disease states of OM, although with the involvement of experts to interpret and correlate image-based indicators of infection with clinical information. In this paper, a flexible and comprehensive framework is presented that automatically extracts features from OCT images, classifies data, and presents clinically relevant results in a user-friendly platform suitable for point-of-care and primary care settings. This framework was used to test the discrimination between OCT images of normal controls, ears with biofilms, and ears with biofilms and middle ear fluid (effusion). Predicted future performance of this classification platform returned promising results (90%+ accuracy) in various initial tests. With integration into patient healthcare workflow, users of all levels of medical experience may be able to collect OCT data and accurately identify the presence of middle ear fluid and/or biofilms.