Significance: Near-infrared (NIR) fluorescence imaging using indocyanine green (ICG) has proven to be a feasible application for real-time intraoperative assessment of tissue perfusion, although quantification of NIR fluorescence signals is pivotal for standardized assessment of tissue perfusion.

Aim: Four patients are described with possible compromised bowel perfusion after mesenteric resection. Based on these patients we want to emphasize the difficulties in the quantification of NIR fluorescence imaging for perfusion analysis.

Approach: During image-guided fluorescence assessment, 5 mg of ICG (2.5  mg  /  ml) was intravenously administered by the anesthesiologist. NIR fluorescence imaging was done with the open camera system of Quest Medical Imaging. Fluorescence data taken from the regions of interest (bowel at risk, transition zone of bowel at risk and adjacent normally perfused bowel, and normally perfused reference bowel) were quantitatively analyzed after surgery for fluorescence intensity-and perfusion time-related parameters.

Results: Bowel perfusion, as assessed clinically by independent surgeons based on NIR fluorescence imaging, resulted in different treatment strategies, three with excellent clinical outcome, but one with a perfusion related complication. Post-surgery quantitative analysis of fluorescence dynamics showed different patterns in the affected bowel segment compared to the unaffected reference segments for the four patients.

Conclusions: Similar intraoperative fluorescence results could lead to different surgical treatment strategies, which demonstrated the difficulties in interpretation of uncorrected fluorescence signals. Real-time quantification and standardization of NIR fluorescence perfusion imaging could probably aid surgeons in the nearby future.

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.

Significance: Acoustically detecting the rich optical absorption contrast in biological tissues, photoacoustic tomography (PAT) seamlessly bridges the functional and molecular sensitivity of optical excitation with the deep penetration and high scalability of ultrasound detection. As a result of continuous technological innovations and commercial development, PAT has been playing an increasingly important role in life sciences and patient care, including functional brain imaging, smart drug delivery, early cancer diagnosis, and interventional therapy guidance.

Aim: Built on our 2016 tutorial article that focused on the principles and implementations of PAT, this perspective aims to provide an update on the exciting technical advances in PAT.

Approach: This perspective focuses on the recent PAT innovations in volumetric deep-tissue imaging, high-speed wide-field microscopic imaging, high-sensitivity optical ultrasound detection, and machine-learning enhanced image reconstruction and data processing. Representative applications are introduced to demonstrate these enabling technical breakthroughs in biomedical research.

Conclusions: We conclude the perspective by discussing the future development of PAT technologies.

Guest editors Jessica Ramella-Roman, Amir H. Gandjbakhche, Stephen C. Kanick, Babak Shadgan, and Bruce J. Tromberg introduce and summarize the articles included in the 6-part JBO Special Section on Wearable, Implantable, Mobile, and Remote Biomedical Optics Photonics.

Significance: Diffuse optical imaging (DOI) provides in vivo quantification of tissue chromophores such as oxy- and deoxyhemoglobin (HbO₂ and HHb, respectively). These parameters have been shown to be useful for predicting neoadjuvant treatment response in breast cancer patients. However, most DOI devices designed for the breast are nonportable, making frequent longitudinal monitoring during treatment a challenge. Furthermore, hemodynamics related to the respiratory cycle are currently unexplored in the breast and may have prognostic value.

Aim: To design, fabricate, and validate a high optode-density wearable continuous wave diffuse optical probe for the monitoring of breathing hemodynamics in breast tissue.

Approach: The probe has a rigid-flex design with 16 dual-wavelength sources and 16 detectors. Performance was characterized on tissue-simulating phantoms, and validation was performed through flow phantom and cuff occlusion measurements. The breasts of N  =  4 healthy volunteers were measured while performing a breathing protocol.

Results: The probe has 512 unique source–detector (S-D) pairs that span S-D separations of 10 to 54 mm. It exhibited good performance characteristics: μ_a drift of 0.34%/h, μ_a precision of 0.063%, and mean SNR  ≥  24  dB up to 41 mm S-D separation. Absorption contrast was detected in flow phantoms at depths exceeding 28 mm. A cuff occlusion measurement confirmed the ability of the probe to track expected hemodynamics in vivo. Breast measurements on healthy volunteers during paced breathing revealed median signal-to-motion artifact ratios ranging from 8.1 to 8.7 dB. Median ΔHbO₂ and ΔHHb amplitudes ranged from 0.39 to 0.67  μM and 0.08 to 0.12  μM, respectively. Median oxygen saturations at the respiratory rate ranged from 82% to 87%.

Conclusions: A wearable diffuse optical probe has been designed and fabricated for the measurement of breast tissue hemodynamics. This device is capable of quantifying breathing-related hemodynamics in healthy breast tissue.

Significance: Speckle noise limits the diagnostic capabilities of optical coherence tomography (OCT) images, causing both a reduction in contrast and a less accurate assessment of the microstructural morphology of the tissue.

Aim: We present a speckle-noise reduction method for OCT volumes that exploits the advantages of adaptive-noise wavelet thresholding with a wavelet compounding method applied to several frames acquired from consecutive positions. The method takes advantage of the wavelet representation of the speckle statistics, calculated properly from a homogeneous sample or a region of the noisy volume.

Approach: The proposed method was first compared quantitatively with different state-of-the-art approaches by being applied to three different clinical dermatological OCT volumes with three different OCT settings. The method was also applied to a public retinal spectral-domain OCT dataset to demonstrate its applicability to different imaging modalities.

Results: The results based on four different metrics demonstrate that the proposed method achieved the best performance among the tested techniques in suppressing noise and preserving structural information.

Conclusions: The proposed OCT denoising technique has the potential to adapt to different image OCT settings and noise environments and to improve image quality prior to clinical diagnosis based on visual assessment.

Significance: Morphological collagen signatures are important for tissue function, particularly in the tumor microenvironment. A single algorithmic framework with quantitative, multiscale morphological collagen feature extraction may further the use of collagen signatures in understanding fundamental tumor progression.

Aim: A modification of the 2D wavelet transform modulus maxima (WTMM) anisotropy method was applied to both digitally simulated collagen fibers and second-harmonic-generation imaged collagen fibers of mouse skin to calculate a multiscale anisotropy factor to detect collagen fiber organization.

Approach: The modified 2D WTMM anisotropy method was initially validated on synthetic calibration images to establish the robustness and sensitivity of the multiscale fiber organization tool. Upon validation, the algorithm was applied to collagen fiber organization in normal wild-type skin, melanoma stimulated skin, and integrin α10KO skin.

Results: Normal wild-type skin collagen fibers have an increased anisotropy factor at all sizes scales. Interestingly, the multiscale anisotropy differences highlight important dissimilarities between collagen fiber organization in normal wild-type skin, melanoma stimulated, and integrin α10KO skin. At small scales (∼2 to 3  μm), the integrin α10KO skin was vastly different than normal skin (p-value  ∼  10^−  8), whereas the melanoma stimulated skin was vastly different than normal at large scales (∼30 to 40  μm, p-value  ∼  10^−  15).

Conclusions: This objective computational collagen fiber organization algorithm is sensitive to collagen fiber organization across multiple scales for effective exploration of collagen morphological alterations associated with melanoma and the lack of α10 integrin binding.

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.

Significance: Noninvasive diffuse optical spectroscopy (DOS) is a promising adjunct diagnostic imaging technique for distinguishing benign and malignant breast lesions. Most DOS approaches require normalizing lesion biomarkers to healthy tissue since major tissue constituents exhibit large interpatient variations. However, absolute optical biomarkers are desirable as it avoids reference measurements which may be difficult or impractical to acquire.

Aim: Our goal is to determine whether absolute measurements of minor absorbers such as collagen and methemoglobin (metHb) can successfully distinguish lesions. We hypothesize that metHb would exhibit less interpatient variability and be more suitable as an absolute metric for malignancy. However, we would expect collagen to exhibit more variability, because unlike metHb, collagen is also present in the healthy tissue.

Approach: In this retrospective clinical study, 30 lesions with breast imaging reporting and database system score   (  BIRADS  )    >    =  3 (12 benign and 18 malignant) measured with broadband quantitative DOS were analyzed for their oxyhemoglobin (HbO), deoxyhemoglobin (HHb), water, lipids, collagen, metHb concentrations, and optical scattering characteristics. Wilcoxon rank sum test was used to compare benign and malignant lesions for all variables in both normalized and absolute forms.

Results: Among all absolute DOS parameters considered, only absolute metHb was observed to be significant for lesion discrimination (0.43  ±  0.18  μM for benign versus 0.87  ±  0.32  μM for malignant, p  =  0.0002). Absolute metHb concentration was also determined to be the best predictor of malignancy with an area under the curve of 0.89.

Conclusions: Our findings demonstrate that lesion metHb concentration measured by DOS can improve noninvasive optical diagnosis of breast malignancies. Since metHb concentration found in normal breast tissue is extremely low, metHb may be a more direct indicator of malignancy that does not depend on other biomarkers found in healthy tissue with significant variability. Furthermore, absolute parameters require reduced measurement time and can be utilized in cases where healthy reference tissue is not available.

Significance: Idiopathic pulmonary fibrosis (IPF) patients have a poor prognosis with short lifespan following diagnosis as there are limited effective treatment options. Despite matrix stiffening being the hallmark of the disease there remains a lack of knowledge surrounding the underlying collagen alterations in the disease. Specifically, while increased collagen crosslinking has been implicated, the resulting effects on collagen macro/supramolecular changes have not been explored.

Aim: We sought to determine if second-harmonic generation (SHG) microscopy could characterize differences in the collagen architecture in 3D spheroid models of IPF grown under different crosslinking modulation conditions (promotion and inhibition).

Approach: We used SHG metrics based on the fiber morphology, relative SHG brightness, and macro/supramolecular structure by SHG polarization analyses to compare the structure of the IPF spheroids.

Results: Comparison of the fiber morphology of the spheroids showed that the control group had the longest, straightest, and thickest fibers. The spheroids with crosslink enhancement and inhibition had the highest and lowest SHG conversion efficiencies, respectively, consistent with the resulting harmonophore density. SHG polarization analyses showed that the peptide pitch angle, alignment of collagen molecules, and overall chirality were altered upon crosslink modulation and were also consistent with reduced organization relative to the control group.

Conclusions: While no single SHG signature is associated with crosslinking, we show that the suite of metrics used here is effective in delineating alterations across the collagen architecture sizescales. The results largely mirror those of human tissues and demonstrate that the combination of 3D spheroid models and SHG analysis is a powerful approach for hypothesis testing the roles of operative cellular and molecular factors in IPF.

Significance: Spectral-domain optical coherence tomography (SD-OCT) offers depth-resolved imaging of optical scattering contrast but is limited in sensitivity to optical absorption. Dual-modality imaging combined with the noncontact absorption contrast of photoacoustic remote sensing (PARS) microscopy can augment SD-OCT applications with specific molecular and functional contrasts in an all-optical, fiber-based platform.

Aim: To develop a fiber-based multimodal PARS and SD-OCT imaging system, which efficiently uses a common 1050-nm light source for SD-OCT and PARS interrogation.

Approach: PARS microscopy has predominantly utilized a 1310-nm interrogation light source to date. Hence, a recent dual-modality PARS and 1050-nm SD-OCT imaging system required three distinct wavelengths including a 532-nm PARS excitation, necessitating a free-space optical architecture with discrete subsystems. Here, we validate the first use of a 1050-nm interrogation wavelength for PARS. This enables the transition to fiber-based interferometry as is standard in modern SD-OCT systems, though infeasible with inclusion of an additional 1310-nm wavelength. PARS interrogation functionality is integrated using a broadband optical circulator.

Results: Dual-modality imaging is demonstrated in carbon fiber phantoms and a mouse ear in vivo. SD-OCT provided a 4.5-μm lateral resolution, 8.8-μm axial resolution in air, and >101  dB of sensitivity, and PARS contributed 532-nm optical absorption contrast with a 47-dB SNR, and lateral and axial resolutions of 2.4 and 35  μm, respectively. Total interrogation power was reduced from 90% to 58% of the ANSI limit compared to a previous three-wavelength approach.

Conclusions: Adapting PARS to use the 1050-nm SD-OCT light source for interrogation enabled implementation of a fiber-based dual-modality system configuration, with image quality maintained. This will facilitate development of potential applications demanding handheld, catheter-based, or endoscopic form factors.

Significance: Subretinal injection is an effective way of delivering transplant genes and cells to treat many degenerative retinal diseases. However, the technique requires high-dexterity and microscale precision of experienced surgeons, who have to overcome the physiological hand tremor and limited visualization of the subretinal space.

Aim: To automatically guide the axial motion of microsurgical tools (i.e., a subretinal injector) with microscale precision in real time using a fiber-optic common-path swept-source optical coherence tomography distal sensor.

Approach: We propose, implement, and study real-time retinal boundary tracking of A-scan optical coherence tomography (OCT) images using a convolutional neural network (CNN) for automatic depth targeting of a selected retinal boundary for accurate subretinal injection guidance. A simplified 1D U-net is used for the retinal layer segmentation on A-scan OCT images. A Kalman filter, combining retinal boundary position measurement by CNN and velocity measurement by cross correlation between consecutive A-scan images, is applied to optimally estimate the retinal boundary position. Unwanted axial motions of the surgical tools are compensated by a piezoelectric linear motor based on the retinal boundary tracking.

Results: CNN-based segmentation on A-scan OCT images achieves the mean unsigned error (MUE) of ∼3  pixels (8.1  μm) using an ex vivo bovine retina model. GPU parallel computing allows real-time inference (∼2  ms) and thus real-time retinal boundary tracking. Involuntary tremors, which include low-frequency draft in hundreds of micrometers and physiological tremors in tens of micrometers, are compensated effectively. The standard deviations of photoreceptor (PR) and choroid (CH) boundary positions get as low as 10.8  μm when the depth targeting is activated.

Conclusions: A CNN-based common-path OCT distal sensor successfully tracks retinal boundaries, especially the PR/CH boundary for subretinal injection, and automatically guides the tooltip’s axial position in real time. The microscale depth targeting accuracy of our system shows its promising possibility for clinical application.

The errata correct the errors in citation numbering that appeared in the originally published article.