Assessing the Effect of Middle Ear Effusions on Wideband Acoustic Immittance Using Optical Coherence Tomography.

OBJECTIVES: Wideband acoustic immittance (WAI) noninvasively assesses middle ear function by measuring the sound conduction over a range of audible frequencies. Although several studies have shown the potential of WAI for detecting the presence of middle ear effusions (MEEs), determining the effects of MEE type and amount on WAI in vivo has been challenging due to the anatomical location of middle ear cavity. The purpose of this study is to correlate WAI measurements with physical characteristics of the middle ear and MEEs determined by optical coherence tomography (OCT), a noninvasive optical imaging technique. DESIGN: Sixteen pediatric subjects (average age of 7 ± 4 years) were recruited from the primary care clinic at Carle Foundation Hospital (Urbana, IL). A total of 22 ears (normal: 15 ears, otitis media with effusion: 6 ears, and acute otitis media: 1 ear, based on physician's diagnosis) were examined via standard otoscopy, tympanometry, OCT imaging, and WAI measurements in a busy, community-based clinical setting. Cross-sectional OCT images were analyzed to quantitatively assess the presence, type (relative turbidity based on the amount of scattering), and amount (relative fluid level) of MEEs. These OCT metrics were utilized to categorize subject ears into no MEE (control), biofilm without a MEE, serous-scant, serous-severe, mucoid-scant, and mucoid-severe MEE groups. The absorbance levels in each group were statistically evaluated at α = 0.05. RESULTS: The absorbance of the control group showed a similar trend when compared with a pediatric normative dataset, and the presence of an MEE generally decreased the power absorbance. The mucoid MEE group showed significantly less power absorbance from 2.74 to 4.73 kHz (p < 0.05) when compared with the serous MEE group, possibly due to the greater mass impeding the middle ear system. Similarly, the greater amount of middle ear fluid contributed to the lower power absorbance from 1.92 to 2.37 kHz (p< 0.05), when compared with smaller amounts of fluid. As expected, the MEEs with scant fluid only significantly affected the power absorbance at frequencies greater than 4.85 kHz. A large variance in the power absorbance was observed between 2 and 5 kHz, suggesting the dependence on both the type and amount of MEE. CONCLUSIONS: Physical characteristics of the middle ear and MEEs quantified from noninvasive OCT images can be helpful to understand abnormal WAI measurements. Mucoid MEEs decrease the power absorbance more than serous MEEs, and the greater amounts of MEE decreases the power absorbance, especially at higher (>2 kHz) frequencies. As both the type and amount of MEE can significantly affect WAI measurements, further investigations to correlate acoustic measurements with physical characteristics of middle ear conditions in vivo is needed.

Intraoperative optical coherence tomography for soft tissue sarcoma differentiation and margin identification.

BACKGROUND AND OBJECTIVE: Sarcomas are rare but highly aggressive tumors, and local recurrence after surgical excision can occur in up to 50% cases. Therefore, there is a strong clinical need for accurate tissue differentiation and margin assessment to reduce incomplete resection and local recurrence. The purpose of this study was to investigate the use of optical coherence tomography (OCT) and a novel image texture-based processing algorithm to differentiate sarcoma from muscle and adipose tissue. STUDY DESIGN AND METHODS: In this study, tumor margin delineation in 19 feline and canine veterinary patients was achieved with intraoperative OCT to help validate tumor resection. While differentiation of lower-scattering adipose tissue from higher-scattering muscle and tumor tissue was relatively straightforward, it was more challenging to distinguish between dense highly scattering muscle and tumor tissue types based on scattering intensity and microstructural features alone. To improve tissue-type differentiation in a more objective and automated manner, three descriptive statistical metrics, namely the coefficient of variation (CV), standard deviation (STD), and Range, were implemented in a custom algorithm applied to the OCT images. RESULTS: Over 22,800 OCT images were collected intraoperatively from over 38 sites on 19 ex vivo tissue specimens removed during sarcoma surgeries. Following the generation of an initial set of OCT images correlated with standard hematoxylin and eosin-stained histopathology, over 760 images were subsequently used for automated analysis. Using texture-based image processing metrics, OCT images of sarcoma, muscle, and adipose tissue were all found to be statistically different from one another (P ≤ 0.001). CONCLUSION: These results demonstrate the potential of using intraoperative OCT, along with an automated tissue differentiation algorithm, as a guidance tool for soft tissue sarcoma margin delineation in the operating room. Lasers Surg. Med. 49:240-248, 2017. © 2017 Wiley Periodicals, Inc.

Intraoperative optical coherence tomography for assessing human lymph nodes for metastatic cancer.

BACKGROUND: Evaluation of lymph node (LN) status is an important factor for detecting metastasis and thereby staging breast cancer. Currently utilized clinical techniques involve the surgical disruption and resection of lymphatic structure, whether nodes or axillary contents, for histological examination. While reasonably effective at detection of macrometastasis, the majority of the resected lymph nodes are histologically negative. Improvements need to be made to better detect micrometastasis, minimize or eliminate lymphatic disruption complications, and provide immediate and accurate intraoperative feedback for in vivo cancer staging to better guide surgery. METHODS: We evaluated the use of optical coherence tomography (OCT), a high-resolution, real-time, label-free imaging modality for the intraoperative assessment of human LNs for metastatic disease in patients with breast cancer. We assessed the sensitivity and specificity of double-blinded trained readers who analyzed intraoperative OCT LN images for presence of metastatic disease, using co-registered post-operative histopathology as the gold standard. RESULTS: Our results suggest that intraoperative OCT examination of LNs is an appropriate real-time, label-free, non-destructive alternative to frozen-section analysis, potentially offering faster interpretation and results to empower superior intraoperative decision-making. CONCLUSIONS: Intraoperative OCT has strong potential to supplement current post-operative histopathology with real-time in situ assessment of LNs to preserve both non-cancerous nodes and their lymphatic vessels, and thus reduce the associated risks and complications from surgical disruption of lymphoid structures following biopsy.

Response of Simulated Drinking Water Biofilm Mechanical and Structural Properties to Long-Term Disinfectant Exposure.

Mechanical and structural properties of biofilms influence the accumulation and release of pathogens in drinking water distribution systems (DWDS). Thus, understanding how long-term residual disinfectants exposure affects biofilm mechanical and structural properties is a necessary aspect for pathogen risk assessment and control. In this study, elastic modulus and structure of groundwater biofilms was monitored by atomic force microscopy (AFM) and optical coherence tomography (OCT) during three months of exposure to monochloramine or free chlorine. After the first month of disinfectant exposure, the mean stiffness of monochloramine- or free-chlorine-treated biofilms was 4 to 9 times higher than those before treatment. Meanwhile, the biofilm thickness decreased from 120 ± 8 µm to 93 ± 6-107 ± 11 µm. The increased surface stiffness and decreased biofilm thickness within the first month of disinfectant exposure was presumably due to the consumption of biomass. However, by the second to third month during disinfectant exposure, the biofilm mean stiffness showed a 2- to 4-fold decrease, and the biofilm thickness increased to 110 ± 7-129 ± 8 µm, suggesting that the biofilms adapted to disinfectant exposure. After three months of the disinfectant exposure process, the disinfected biofilms showed 2-5 times higher mean stiffness (as determined by AFM) and 6-13-fold higher ratios of protein over polysaccharide, as determined by differential staining and confocal laser scanning microscopy (CLSM), than the nondisinfected groundwater biofilms. However, the disinfected biofilms and nondisinfected biofilms showed statistically similar thicknesses (t test, p > 0.05), suggesting that long-term disinfection may not significantly remove net biomass. This study showed how biofilm mechanical and structural properties vary in response to a complex DWDS environment, which will contribute to further research on the risk assessment and control of biofilm-associated-pathogens in DWDS.

Role of biofilm roughness and hydrodynamic conditions in Legionella pneumophila adhesion to and detachment from simulated drinking water biofilms.

Biofilms in drinking water distribution systems (DWDS) could exacerbate the persistence and associated risks of pathogenic Legionella pneumophila (L. pneumophila), thus raising human health concerns. However, mechanisms controlling adhesion and subsequent detachment of L. pneumophila associated with biofilms remain unclear. We determined the connection between L. pneumophila adhesion and subsequent detachment with biofilm physical structure characterization using optical coherence tomography (OCT) imaging technique. Analysis of the OCT images of multispecies biofilms grown under low nutrient condition up to 34 weeks revealed the lack of biofilm deformation even when these biofilms were exposed to flow velocity of 0.7 m/s, typical flow for DWDS. L. pneumophila adhesion on these biofilm under low flow velocity (0.007 m/s) positively correlated with biofilm roughness due to enlarged biofilm surface area and local flow conditions created by roughness asperities. The preadhered L. pneumophila on selected rough and smooth biofilms were found to detach when these biofilms were subjected to higher flow velocity. At the flow velocity of 0.1 and 0.3 m/s, the ratio of detached cell from the smooth biofilm surface was from 1.3 to 1.4 times higher than that from the rough biofilm surface, presumably because of the low shear stress zones near roughness asperities. This study determined that physical structure and local hydrodynamics control L. pneumophila adhesion to and detachment from simulated drinking water biofilm, thus it is the first step toward reducing the risk of L. pneumophila exposure and subsequent infections.

Texture-based speciation of otitis media-related bacterial biofilms from optical coherence tomography images using supervised classification.

Otitis media (OM), a highly prevalent inflammatory middle-ear disease in children worldwide, is commonly caused by an infection, and can lead to antibiotic-resistant bacterial biofilms in recurrent/chronic OM cases. A biofilm related to OM typically contains one or multiple bacterial species. OCT has been used clinically to visualize the presence of bacterial biofilms in the middle ear. This study used OCT to compare microstructural image texture features from bacterial biofilms. The proposed method applied supervised machine-learning-based frameworks (SVM, random forest, and XGBoost) to classify multiple species bacterial biofilms from in vitro cultures and clinically-obtained in vivo images from human subjects. Our findings show that optimized SVM-RBF and XGBoost classifiers achieved more than 95% of AUC, detecting each biofilm class. These results demonstrate the potential for differentiating OM-causing bacterial biofilms through texture analysis of OCT images and a machine-learning framework, offering valuable insights for real-time in vivo characterization of ear infections.

Simultaneous label-free autofluorescence multi-harmonic microscopy driven by the supercontinuum generated from a bulk nonlinear crystal.

Nonlinear microscopy encompasses several imaging techniques that leverage laser technology to probe intrinsic molecules of biological specimens. These native molecules produce optical fingerprints that allow nonlinear microscopes to reveal the chemical composition and structure of cells and tissues in a label-free and non-destructive fashion, information that enables a plethora of applications, e.g., real-time digital histopathology or image-guided surgery. Because state-of-the-art lasers exhibit either a limited bandwidth or reduced wavelength tunability, nonlinear microscopes lack the spectral support to probe different biomolecules simultaneously, thus losing analytical potential. Therefore, a conventional nonlinear microscope requires multiple or tunable lasers to individually excite endogenous molecules, increasing both the cost and complexity of the system. A solution to this problem is supercontinuum generation, a nonlinear optical phenomenon that supplies broadband femtosecond radiation, granting a wide spectrum for concurrent molecular excitation. This study introduces a source for nonlinear multiphoton microscopy based on the supercontinuum generation from a yttrium aluminum garnet (YAG) crystal, an approach that allows simultaneous label-free autofluorescence multi-harmonic imaging of biological samples and offers a practical and compact alternative for the clinical translation of nonlinear microscopy. While this supercontinuum covered the visible spectrum (550-900 nm) and the near-infrared region (950-1200 nm), the pulses within 1030-1150 nm produced label-free volumetric chemical images of ex vivo chinchilla kidney, thus validating the supercontinuum from bulk crystals as a powerful source for multimodal nonlinear microscopy.

Texture-based speciation of otitis media-related bacterial biofilms from optical coherence tomography images using supervised classification.

Otitis media (OM) is primarily a bacterial middle-ear infection prevalent among children worldwide. In recurrent and/or chronic OM cases, antibiotic-resistant bacterial biofilms can develop in the middle ear. A biofilm related to OM typically contains one or multiple bacterial strains, the most common include Haemophilus influenzae, Streptococcus pneumoniae, Moraxella catarrhalis, Pseudomonas aeruginosa, and Staphylococcus aureus. Optical coherence tomography (OCT) has been used clinically to visualize the presence of bacterial biofilms in the middle ear. This study used OCT to compare microstructural image texture features from primary bacterial biofilms in vitro and in vivo. The proposed method applied supervised machine-learning-based frameworks (SVM, random forest (RF), and XGBoost) to classify and speciate multiclass bacterial biofilms from the texture features extracted from OCT B-Scan images obtained from in vitro cultures and from clinically-obtained in vivo images from human subjects. Our findings show that optimized SVM-RBF and XGBoost classifiers can help distinguish bacterial biofilms by incorporating clinical knowledge into classification decisions. Furthermore, both classifiers achieved more than 95% of AUC (area under receiver operating curve), detecting each biofilm class. These results demonstrate the potential for differentiating OM-causing bacterial biofilms through texture analysis of OCT images and a machine-learning framework, which could provide additional clinically relevant data during real-time in vivo characterization of ear infections.

Development of polarization-sensitive optical coherence tomography imaging platform and metrics to quantify electrostimulation-induced peripheral nerve injury in vivo in a small animal model.

Significance: Neuromodulation devices are rapidly evolving for the treatment of neurological diseases and conditions. Injury from implantation or long-term use without obvious functional losses is often only detectable through terminal histology. New technologies are needed that assess the peripheral nervous system (PNS) under normal and diseased or injured conditions. Aim: We aim to demonstrate an imaging and stimulation platform that can elucidate the biological mechanisms and impacts of neurostimulation in the PNS and apply it to the sciatic nerve to extract imaging metrics indicating electrical overstimulation. Approach: A sciatic nerve injury model in a 15-rat cohort was observed using a newly developed imaging and stimulation platform that can detect electrical overstimulation effects with polarization-sensitive optical coherence tomography. The sciatic nerve was electrically stimulated using a custom-developed nerve holder with embedded electrodes for 1 h, followed by a 1-h recovery period, delivered at above-threshold Shannon model k -values in experimental groups: sham control (SC, n = 5 , 0.0 mA / 0 Hz ), stimulation level 1 (SL1, n = 5 , 3.4 mA / 50 Hz , and k = 2.57 ), and stimulation level 2 (SL2, n = 5 , 6.8 mA / 100 Hz , and k = 3.17 ). Results: The stimulation and imaging system successfully captured study data across the cohort. When compared to a SC after a 1-week recovery, the fascicle closest to the stimulation lead showed an average change of + 4 % / - 309 % (SL1/SL2) in phase retardation and - 79 % / - 148 % in optical attenuation relative to SC. Analysis of immunohistochemistry (IHC) shows a + 1 % / - 36 % difference in myelin pixel counts and - 13 % / + 29 % difference in axon pixel counts, and an overall increase in cell nuclei pixel count of + 20 % / + 35 % . These metrics were consistent with IHC and hematoxylin/eosin tissue section analysis. Conclusions: The poststimulation changes observed in our study are manifestations of nerve injury and repair, specifically degeneration and angiogenesis. Optical imaging metrics quantify these processes and may help evaluate the safety and efficacy of neuromodulation devices.

In Vivo Optical Characterization of Middle Ear Effusions and Biofilms During Otitis Media.

Otitis media (OM), a common ear infection, is characterized by the presence of an accumulated middle ear effusion (MEE) in a normally air-filled middle ear cavity. While assessing the MEE plays a critical role in the overall management of OM, identifying and examining the MEE is challenging with the current diagnostic tools since the MEE is located behind the semi-opaque eardrum. The objective of this cross-sectional, observational study is to non-invasively visualize and characterize MEEs and bacterial biofilms in the middle ear. A portable, handheld, otoscope-integrated optical coherence tomography (OCT) system combined with novel analytical methods has been developed. In vivo middle ear OCT images were acquired from 53 pediatric subjects (average age of 3.9 years; all awake during OCT imaging) diagnosed with OM and undergoing a surgical procedure (ear tube surgery) to aspirate the MEE and aerate the middle ear. In vivo middle ear OCT acquired prior to the surgery was compared with OCT of the freshly extracted MEEs, clinical diagnosis, and post-operative evaluations. Among the subjects who were identified with the presence of MEEs, 89.6% showed the presence of the TM-adherent biofilm in in vivo OCT. This study provides an atlas of middle ear OCT images exhibiting a range of depth-resolved MEE features, which can only be visualized and assessed non-invasively through OCT. Quantitative metrics of OCT images acquired prior to the surgery were statistically correlated with surgical evaluations of MEEs. Measurements of MEE characteristics will provide new readily available information that can lead to improved diagnosis and management strategies for the highly prevalent OM in children.

Imaging and characterization of transitions in biofilm morphology via anomalous diffusion following environmental perturbation.

Microorganisms form macroscopic structures for the purpose of environmental adaptation. Sudden environmental perturbations induce dynamics that cause bacterial biofilm morphology to transit to another equilibrium state, thought to be related to anomalous diffusion processes. Here, detecting the super-diffusion characteristics would offer a long-sought goal for a rapid detection method of biofilm phenotypes based on their dynamics, such as growth or dispersal. In this paper, phase-sensitive Doppler optical coherence tomography (OCT) and dynamic light scattering (DLS) are combined to demonstrate wide field-of-view and label-free internal dynamic imaging of biofilms. The probability density functions (PDFs) of phase displacement of the backscattered light and the dynamic characteristics of the PDFs are estimated by a simplified mixed Cauchy and Gaussian model. This model can quantify the super-diffusion state and estimate the dynamic characteristics and macroscopic responses in biofilms that may further describe dispersion and growth in biofilm models.

Differentiation of otitis media-causing bacteria and biofilms via Raman spectroscopy and optical coherence tomography.

In the management of otitis media (OM), identification of causative bacterial pathogens and knowledge of their biofilm formation can provide more targeted treatment approaches. Current clinical diagnostic methods rely on the visualization of the tympanic membrane and lack real-time assessment of the causative pathogen(s) and the nature of any biofilm that may reside behind the membrane and within the middle ear cavity. In recent years, optical coherence tomography (OCT) has been demonstrated as an improved in vivo diagnostic tool for visualization and morphological characterization of OM biofilms and middle ear effusions; but lacks specificity about the causative bacterial species. This study proposes the combination of OCT and Raman spectroscopy (RS) to examine differences in the refractive index, optical attenuation, and biochemical composition of Haemophilus influenzae, Streptococcus pneumoniae, Moraxella catarrhalis, and Pseudomonas aeruginosa; four of the leading otopathogens in OM. This combination provides a dual optical approach for identifying and differentiating OM-causing bacterial species under three different in vitro growth environments (i.e., agar-grown colonies, planktonic cells from liquid cultures, and biofilms). This study showed that RS was able to identify key biochemical variations to differentiate all four OM-causing bacteria. Additionally, biochemical spectral changes (RS) and differences in the mean attenuation coefficient (OCT) were able to distinguish the growth environment for each bacterial species.

Multimodal Handheld Probe for Characterizing Otitis Media - Integrating Raman Spectroscopy and Optical Coherence Tomography.

Otitis media (OM) is a common disease of the middle ear, affecting 80% of children before the age of three. The otoscope, a simple illuminated magnifier, is the standard clinical diagnostic tool to observe the middle ear. However, it has limited contrast to detect signs of infection, such as clearly identifying and characterizing middle ear fluid or biofilms that accumulate within the middle ear. Likewise, invasive sampling of every subject is not clinically indicated nor practical. Thus, collecting accurate noninvasive diagnostic factors is vital for clinicians to deliver a precise diagnosis and effective treatment regimen. To address this need, a combined benchtop Raman spectroscopy (RS) and optical coherence tomography (OCT) system was developed. Together, RS-OCT can non-invasively interrogate the structural and biochemical signatures of the middle ear under normal and infected conditions.In this paper, in vivo RS scans from pediatric clinical human subjects presenting with OM were evaluated in parallel with RS-OCT data of physiologically relevant in vitro ear models. Component-level characterization of a healthy tympanic membrane and malleus bone, as well as OM-related middle ear fluid, identified the optimal position within the ear for RS-OCT data collection. To address the design challenges in developing a system specific to clinical use, a prototype non-contact multimodal handheld probe was built and successfully tested in vitro. Design criteria have been developed to successfully address imaging constraints imposed by physiological characteristics of the ear and optical safety limits. Here, we present the pathway for translation of RS-OCT for non-invasive detection of OM.

Automated classification of otitis media with OCT: augmenting pediatric image datasets with gold-standard animal model data.

Otitis media (OM) is an extremely common disease that affects children worldwide. Optical coherence tomography (OCT) has emerged as a noninvasive diagnostic tool for OM, which can detect the presence and quantify the properties of middle ear fluid and biofilms. Here, the use of OCT data from the chinchilla, the gold-standard OM model for the human disease, is used to supplement a human image database to produce diagnostically relevant conclusions in a machine learning model. Statistical analysis shows the datatypes are compatible, with a blended-species model reaching ∼95% accuracy and F1 score, maintaining performance while additional human data is collected.

Efficacy of endotracheal tube suctioning in intubated intensive care unit patients determined by in vivo catheter-based optical coherence tomography-a pilot study.

BACKGROUND: Mechanical ventilation using an endotracheal tube (ETT) is one of the critical interventions given to patients in the intensive care unit (ICU). ETTs are associated with the formation of biofilms, placing patients at increased risk for developing ventilator-associated pneumonia (VAP). ETT suctioning is used to remove secretions, reduce bacterial colonization, and reduce the rate of biofilm formation. However, current standard-of-care suctioning procedures do not adequately eliminate all secretions from the ETT. METHODS: This observational study was conducted in a cohort of 4 subjects admitted to the ICU and intubated with an ETT, irrespective of ethnicity, gender, or race. A total of 23 suctioning procedures were evaluated with in vivo three-dimensional (3D) optical coherence tomography (OCT) imaging, before and after suctioning. A secretion density metric was derived from the OCT data to quantify the amount of secretions present within the ETT, and an attenuation coefficient metric was derived to detect and quantify the presence of biofilms. Analyzed OCT images were correlated with clinical and microscopy data. RESULTS: Data obtained suggests that the current standard-of-care suctioning procedure is inefficient at clearing secretions or preventing the formation of biofilms. The presence of biofilms was corroborated with both post-intubation microscopy of the ETTs, as well as with clinical data. CONCLUSIONS: We conclude that the standard-of-care suctioning method does not eliminate secretions nor reduce the formation of biofilm in ETTs. Our in situ imaging method was sensitive to the presence of secretions, biofilms, and quantitative, and can be used for investigating different suctioning protocols in the future.

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.

Inactivation and sensitization of Pseudomonas aeruginosa by microplasma jet array for treating otitis media.

Otitis media (OM), known as a middle ear infection, is the leading cause of antibiotic prescriptions for children. With wide-spread use of antibiotics in OM, resistance to antibiotics continues to decrease the efficacy of the treatment. Furthermore, as the presence of a middle ear biofilm has contributed to this reduced susceptibility to antimicrobials, effective interventions are necessary. A miniaturized 3D-printed microplasma jet array has been developed to inactivate Pseudomonas aeruginosa, a common bacterial strain associated with OM. The experiments demonstrate the disruption of planktonic and biofilm P. aeruginosa by long-lived molecular species generated by microplasma, as well as the synergy of combining microplasma treatment with antibiotic therapy. In addition, a middle ear phantom model was developed with an excised rat eardrum to investigate the antimicrobial effects of microplasma on bacteria located behind the eardrum, as in a patient-relevant setup. These results suggest the potential for microplasma as a new treatment paradigm for OM.

Evaluating optical coherence tomography for surgical margin assessment of canine mammary tumours.

Optical coherence tomography (OCT) uses near-infrared light waves to generate real-time, high-resolution images on the microscopic scale similar to low power histopathology. Previous studies have demonstrated the use of OCT for real-time surgical margin assessment for human breast cancer. The use of OCT for canine mammary tumours (CMT) could allow intra-operative visualisation of residual tumour at the surgical margins. The purpose of this study was to assess OCT imaging for the detection of incomplete tumour resection following CMT surgery. We hypothesized that the OCT images would have comparable features to histopathological images of tissues at the surgical margins of CMT resections along with a high sensitivity of OCT detection of incomplete surgical excision of CMT. Thirty surgical specimens were obtained from nineteen client-owned dogs undergoing surgical resection of CMT. OCT image appearance and characteristics of adipose tissue, skin, mammary tissue and mammary tumour at the surgical margins were distinct and different. The OCT images of normal and abnormal tissues at the surgical margins were utilized to develop a dataset of OCT images for observer evaluation. The sensitivity and specificity for ex vivo images were 83.3% and 82.0% (observer 1) and 70.0% and 67.9% (observer 2). The sensitivity and specificity for in vivo images were 70.0% and 89.3% (observer 1) and 76.7% and 67.9% (observer 2). These results indicate a potential use of OCT for surgical margin assessment for CMT to optimize surgical intervention and clinical outcomes. Improved training and experience of observers may improve sensitivity and specificity.

In vivo detection of endotracheal tube biofilms in intubated critical care patients using catheter-based optical coherence tomography.

The formation of biofilms in the endotracheal tubes (ETTs) of intubated patients on mechanical ventilation is associated with a greater risk of ventilator-associated pneumonia and death. New technologies are needed to detect and monitor ETTs in vivo for the presence of these biofilms. Longitudinal OCT imaging was performed in mechanically ventilated subjects at 24-hour intervals until extubation to detect the formation and temporal changes of in vivo ETT biofilms. OCT-derived attenuation coefficient images were used to differentiate between mucus and biofilm. Extubated ETTs were examined with optical and electron microscopy, and all imaging results were correlated with standard-of-care clinical test reports. OCT and attenuation coefficient images from four subjects were positive for ETT biofilms and were negative for two subjects. The processed and stained extubated ETTs and clinical reports confirmed the presence/absence of biofilms in all subjects. Our findings confirm that OCT can detect and differentiate between biofilm-positive and biofilm-negative groups (P < 10-5 ). OCT image-based features may serve as biomarkers for direct in vivo detection of ETT biofilms and help drive investigation of new management strategies to reduce the incidence of VAP.

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.