Significance: The multimodality imaging system has become a powerful tool for in-vivo biomedical research. However, a conventional multimodality system generally employs two independent detectors, which is costly and bulky. Meanwhile, the geometric cocalibration and image registration between the imaging modalities are also complicated.

Aim: To acquire the multimodality images for small animals with only one visible light sensed single-pixel detector.

Approach: The system is built based on a structured detection Fourier single-pixel imaging architecture. A cesium iodide doped with thallium [CsI(Tl)] scintillator plate is placed behind the sample in x-ray imaging, so the x-ray images can be converted to be visible and sensed with the same single-pixel detector as applied in fluorescence imaging.

Results: The spatial resolution of x-ray imaging was measured to be 1.81 mm, the sensitivity and the imaging depth of fluorescence imaging was evaluated to be ∼1.48 nmol / ml and 4 mm, respectively. In vivo multimodality imaging of a C57BL/6 female mouse bearing tumor targeted with mCherry was carried out.

Conclusions: We proposed an x-ray and fluorescence multimodality imaging system for small animals via the structured detection FSI architecture. The system is low cost, with a more compact structure, and free of image registration from different modalities. In vivo multimodality imaging results of a mouse bearing tumor demonstrate its capability for small animal research.

Significance: The method of photobiomodulation (PBM) has been used in medicine for a long time to promote anti-inflammation and pain-resolving processes in different organs and tissues. PBM triggers numerous cellular pathways including stimulation of the mitochondrial respiratory chain, alteration of the cytoskeleton, cell death prevention, increasing proliferative activity, and directing cell differentiation. The most effective wavelengths for PBM are found within the optical window (750 to 1100 nm), in which light can permeate tissues and other water-containing structures to depths of up to a few cm. PBM already finds its applications in the developing fields of tissue engineering and regenerative medicine. However, the diversity of three-dimensional (3D) systems, irradiation sources, and protocols intricate the PBM applications.

Aim: We aim to discuss the PBM and 3D tissue engineered constructs to define the fields of interest for PBM applications in tissue engineering.

Approach: First, we provide a brief overview of PBM and the timeline of its development. Then, we discuss the optical properties of 3D cultivation systems and important points of light dosimetry. Finally, we analyze the cellular pathways induced by PBM and outcomes observed in various 3D tissue-engineered constructs: hydrogels, scaffolds, spheroids, cell sheets, bioprinted structures, and organoids.

Results: Our summarized results demonstrate the great potential of PBM in the stimulation of the cell survival and viability in 3D conditions. The strategies to achieve different cell physiology states with particular PBM parameters are outlined.

Conclusions: PBM has already proved itself as a convenient and effective tool to prevent drastic cellular events in the stress conditions. Because of the poor viability of cells in scaffolds and the convenience of PBM devices, 3D tissue engineering is a perspective field for PBM applications.

Significance: Follicular thyroid carcinoma carries a substantially poor prognosis due to its unique biological behavior and less favorable outcomes. In particular, fine-needle aspiration (FNA) biopsies, which play a key role in screening thyroid nodules, cannot differentiate benign from malignant follicular neoplasm.

Aim: We report on the use of hyperspectral Raman microscopy in combination with chemometric analysis for identifying and classifying single cells obtained from clinical samples of human follicular thyroid neoplasms.

Approach: We used a method intended to simulate the FNA procedure to obtain single cells from thyroid nodules. A total of 392 hyperspectral Raman images of single cells from follicular thyroid neoplasms were collected.

Results: Malignant cells were identified based on their intrinsic Raman spectral signatures with an overall diagnostic accuracy of up to 83.7%.

Conclusions: Our findings indicate that hyperspectral Raman microscopy can potentially be developed into an ancillary test for analyzing single cells from thyroid FNA biopsies to better stratify “indeterminate” nodules and other cytologically challenging cases.

Significance: Fiber-optic extended-wavelength diffuse reflectance spectroscopy (EWDRS) using both visible/near-infrared and shortwave-infrared detectors enables improved detection of spectral absorbances arising from lipids, water, and collagen and has demonstrated promise in a variety of applications, including detection of nerves and neurovascular bundles (NVB). Development of future applications of EWDRS for nerve detection could benefit from the use of model-based analyses including Monte Carlo (MC) simulations and evaluation of agreement between model systems and empirical measurements.

Aim: The aim of this work is to characterize agreement between EWDRS measurements and simulations and inform future applications of model-based studies of nerve-detecting applications.

Approach: A model-based platform consisting of an ex vivo microsurgical nerve dissection model, unique two-layer optical phantoms, and MC model simulations of fiber-optic EWDRS spectroscopic measurements were used to characterize EWDRS and compare agreement across models. In addition, MC simulations of an EWDRS measurement scenario are performed to provide a representative example of future analyses.

Results: EWDRS studies performed in the common chicken thigh femoral nerve microsurgical dissection model indicate similar spectral features for classification of NVB versus adjacent tissues as reported in porcine models and human subjects. A comparison of measurements from unique EWDRS issue mimicking optical phantoms and MC simulations indicates high agreement between the two in homogeneous and two-layer optical phantoms, as well as in dissected tissues. Finally, MC simulations of measurement over a simulated NVB indicate the potential of future applications for measurement of nerve plexus.

Conclusions: Characterization of agreement between fiber-optic EWDRS measurements and MC simulations demonstrates strong agreement across a variety of tissues and optical phantoms, offering promise for further use to guide the continued development of EWDRS for translational applications.

Significance: The diagnosis of prostate cancer (PCa) and focal treatment by brachytherapy are limited by the lack of precise intraoperative information to target tumors during biopsy collection and radiation seed placement. Image-guidance techniques could improve the safety and diagnostic yield of biopsy collection as well as increase the efficacy of radiotherapy.

Aim: To estimate the accuracy of PCa detection using in situ Raman spectroscopy (RS) in a pilot in-human clinical study and assess biochemical differences between in vivo and ex vivo measurements.

Approach: A new miniature RS fiber-optics system equipped with an electromagnetic (EM) tracker was guided by trans-rectal ultrasound-guided imaging, fused with preoperative magnetic resonance imaging to acquire 49 spectra in situ (in vivo) from 18 PCa patients. In addition, 179 spectra were acquired ex vivo in fresh prostate samples from 14 patients who underwent radical prostatectomy. Two machine-learning models were trained to discriminate cancer from normal prostate tissue from both in situ and ex vivo datasets.

Results: A support vector machine (SVM) model was trained on the in situ dataset and its performance was evaluated using leave-one-patient-out cross validation from 28 normal prostate measurements and 21 in-tumor measurements. The model performed at 86% sensitivity and 72% specificity. Similarly, an SVM model was trained with the ex vivo dataset from 152 normal prostate measurements and 27 tumor measurements showing reduced cancer detection performance mostly attributable to spatial registration inaccuracies between probe measurements and histology assessment. A qualitative comparison between in situ and ex vivo measurements demonstrated a one-to-one correspondence and similar ratios between the main Raman bands (e.g., amide I-II bands, phenylalanine).

Conclusions: PCa detection can be achieved using RS and machine learning models for image-guidance applications using in situ measurements during prostate biopsy procedures.

Significance: The diagnosis and treatment of prostate cancer (PCa) are limited by a lack of intraoperative information to accurately target tumors with needles for biopsy and brachytherapy. An innovative image-guidance technique using optical devices could improve the diagnostic yield of biopsy and efficacy of radiotherapy.

Aim: To evaluate the performance of multimodal PCa detection using biomolecular features from in-situ Raman spectroscopy (RS) combined with image-based (radiomics) features from multiparametric magnetic resonance images (mpMRI).

Approach: In a prospective pilot clinical study, 18 patients were recruited and underwent high-dose-rate brachytherapy. Multimodality image fusion (preoperative mpMRI with intraoperative transrectal ultrasound) combined with electromagnetic tracking was used to navigate an RS needle in the prostate prior to brachytherapy. This resulting dataset consisted of Raman spectra and co-located radiomics features from mpMRI. Feature selection was performed with the constraint that no more than 10 features were retained overall from a combination of inelastic scattering spectra and radiomics. These features were used to train support vector machine classifiers for PCa detection based on leave-one-patient-out cross-validation.

Results: RS along with biopsy samples were acquired from 47 sites along the insertion trajectory of the fiber-optics needle: 26 were confirmed as benign or grade group = 1, and 21 as grade group >1, according to histopathological reports. The combination of the fingerprint region of the RS and radiomics showed an accuracy of 83% (sensitivity = 81 % and a specificity = 85 % ), outperforming by more than 9% models trained with either spectroscopic or mpMRI data alone. An optimal number of features was identified between 6 and 8 features, which have good potential for discriminating grade group ≥1 / grade group <1 (accuracy = 87 % ) or grade group >1 / grade group ≤1 (accuracy = 91 % ).

Conclusions: In-situ Raman spectroscopy combined with mpMRI radiomics features can lead to highly accurate PCa detection for improved in-vivo targeting of biopsy sample collection and radiotherapy seed placement.

Significance: Skin malformations in dermatology are mostly evaluated subjectively, based on a doctor’s experience and visual perception; an option for objective quantitative skin assessment is camera-based spectrally selective diagnostics. Multispectral imaging is a technique capable to provide information about concentrations of the absorbing chromophores and their distribution over the malformation in a noncontact way. Conversion of spectral images into distribution maps of chromophores can be performed by means of the modified Beer–Lambert law. However, such distribution maps represent only single specific cases, therefore, some extensive method for data comparison is needed.

Aim: This study aims to develop a more informative approach for identification and characterization of skin malformations using three-dimensional (3D) representation of triple spectral line imaging data.

Approach: The 3D-representation method is experimentally tested on eight different skin pathology types, including both benign and malignant pathologies; an imaging device ensuring uniform three laser line (448, 532, and 659 nm) illumination is used. Three spectral line images are extracted from a single snapshot RGB image data, with subsequent calculation of attenuation coefficients for each working wavelength at every image pixel and represented as 3D graphs. Skin chromophore content variations in malformations are represented in a similar way.

Results: Clinical measurement results for 99 skin pathologies, including basal cell carcinomas, melanoma, dermal nevi, combined nevi, junctional nevi, blue nevi, seborrheic keratosis, and hemangiomas. They are presented as 3D spectral attenuation maps exhibiting specific individual features for each group of pathologies. Along with intensity attenuation maps, 3D maps for content variations of three main skin chromophores (melanin, oxyhemoglobin, and deoxyhemoglobin), calculated in frame of a model based on modified Beer–Lambert law, are also presented. Advantages and disadvantages of the proposed data representation method are discussed.

Conclusions: The described 3D-representation method of triple spectral line imaging data shows promising potential for objective quantitative noncontact diagnosis of skin pathologies.

Significance: Mueller matrix (MM) polarimetry is a promising tool for the detection of skin cancer. Polarimetric in vivo measurements often suffer from misalignment of the polarimetric images due to motion, which can lead to false results.

Aim: We aim to provide an easy-to-implement polarimetric image data registration method to ensure proper image alignment.

Approach: A feature-based image registration is implemented for an MM polarimeter for phantom and in vivo human skin measurements.

Results: We show that the keypoint-based registration of polarimetric images is necessary for in vivo skin polarimetry to ensure reliable results. Further, we deliver an efficient semiautomated method for the registration of polarimetric images.

Conclusions: Image registration for in vivo polarimetry of human skin is required for improved diagnostics and can be efficiently enhanced with a keypoint-based approach.

Significance: Methylene blue (MB) is an exogenous contrast agent that has the potential to assist with visualization and penetration challenges in photoacoustic imaging. However, monitoring the local concentration between MB and endogenous chromophores is critical for avoiding unnecessary MB accumulations that could lead to adverse effects such as hemolysis when exposed to increased dose and photodamage when exposed to high laser energies.

Aim: We developed a modified version of a previously proposed acoustic-based atlas method to estimate concentration levels from a mixture of two photoacoustic-sensitive materials after two laser wavelength emissions.

Approach: Photoacoustic data were acquired from mixtures of 100-μM MB and either human or porcine blood (Hb) injected in a plastisol phantom, using laser wavelengths of 710 and 870 nm. An algorithm to perform linear regression of the acoustic frequency response from an atlas composed of pure concentrations was designed to assess the concentration levels from photoacoustic samples obtained from 11 known MB/Hb volume mixtures. The mean absolute error (MAE), coefficient of determination (i.e., R²), and Spearman’s correlation coefficient (i.e., ρ) between the estimated results and ground-truth labels were calculated to assess the algorithm performance, linearity, and monotonicity, respectively.

Results: The overall MAE, R², and ρ were 12.68%, 0.80, and 0.89, respectively, for the human Hb dataset and 9.92%, 0.86, and 0.93, respectively, for the porcine Hb dataset. In addition, a similarly linear relationship was observed between the acoustic frequency response at 2.3 MHz and 870-nm laser wavelength and the ground-truth concentrations, with R² and | ρ | values of 0.76 and 0.88, respectively.

Conclusions: Contrast agent concentration monitoring is feasible with the proposed approach. The potential for minimal data acquisition times with only two wavelength emissions is advantageous toward real-time implementation in the operating room.

Significance: Real-time histology can close a variety of gaps in tissue diagnostics. Currently, gross pathology analysis of excised tissue is dependent upon visual inspection and palpation to identify regions of interest for histopathological processing. Such analysis is limited by the variable correlation between macroscopic and microscopic findings. The current standard of care is costly, burdensome, and inefficient.

Aim: We are the first to address this gap by introducing optical coherence tomography (OCT) to be integrated in real-time during the pathology grossing process.

Approach: This is achieved by our high-resolution, ultrahigh-speed, large field-of-view OCT device designed for this clinical application.

Results: We demonstrate the feasibility of imaging tissue sections from multiple human organs (breast, prostate, lung, and pancreas) in a clinical gross pathology setting without interrupting standard workflows.

Conclusions: OCT-based real-time histology evaluation holds promise for addressing a gap that has been present for >100 years.

Significance: Optical imaging of responses in fluorescently labeled neurons has progressed significantly in recent years. However, there is still a need to monitor neural activities at divergent spatial scales and at depths beyond the optical diffusion limit.

Aim: To meet these needs, we aim to develop multiscale photoacoustic tomography (PAT) to image neural activities across spatial scales with a genetically encoded calcium indicator GCaMP.

Approach: First, using photoacoustic microscopy, we show that depth-resolved GCaMP signals can be monitored in vivo from a fly brain in response to odor stimulation without depth scanning and even with the cuticle intact. In vivo monitoring of GCaMP signals was also demonstrated in mouse brains. Next, using photoacoustic computed tomography, we imaged neural responses of a mouse brain slice at depths beyond the optical diffusion limit.

Results: We provide the first unambiguous demonstration that multiscale PAT can be used to record neural activities in transgenic flies and mice with select neurons expressing GCaMP.

Conclusions: Our results indicate that the combination of multiscale PAT and fluorescent neural activity indicators provides a methodology for imaging targeted neurons at various scales.

Significance: Physics-based simulations of photoacoustic (PA) signals are used to validate new methods, to characterize PA setups and to generate training datasets for machine learning. However, a thoroughly validated PA simulation toolchain that can simulate realistic images is still lacking.

Aim: A quantitative toolchain was developed to model PA image acquisition in complex tissues, by simulating both the optical fluence and the acoustic wave propagation.

Approach: Sampling techniques were developed to decrease artifacts in acoustic simulations. The performance of the simulations was analyzed by measuring the point spread function (PSF) and using a rotatable three-channel phantom, filled with cholesterol, a human carotid plaque sample, and porcine blood. Ex vivo human plaque samples were simulated to validate the methods in more complex tissues.

Results: The sampling techniques could enhance the quality of the simulated PA images effectively. The resolution and intensity of the PSF in the turbid medium matched the experimental data well. Overall, the appearance, signal-to-noise ratio and speckle of the images could be simulated accurately.

Conclusions: A PA toolchain was developed and validated, and the results indicate a great potential of PA simulations in more complex and heterogeneous media.

Significance: The ability to perform frequent non-invasive monitoring of glucose in the bloodstream is very applicable for diabetic patients.

Aim: We experimentally verified a non-invasive multimode fiber-based technique for sensing glucose concentration in the bloodstream by extracting and analyzing the collected speckle patterns.

Approach: The proposed sensor consists of a laser source, digital camera, computer, multimode fiber, and alternating current (AC) generated magnetic field source. The experiments were performed using a covered (with cladding and jacket) and uncovered (without cladding and jacket) multimode fiber touching the skin under a magnetic field and without it. The subject’s finger was placed on a fiber to detect the glucose concentration. The method tracks variations in the speckle patterns due to light interaction with the bloodstream affected by blood glucose.

Results: The uncovered fiber placed above the finger under the AC magnetic field (150 G) at 140 Hz was found to have a lock-in amplification role, improving the glucose detection precision. The application of the machine learning algorithms in preprocessed speckle pattern data increase glucose measurement accuracy. Classification of the speckle patterns for uncovered fiber under the AC magnetic field allowed for detection of the blood glucose with high accuracy for all tested subjects compared with other tested configurations.

Conclusions: The proposed technique was theoretically analyzed and experimentally validated in this work. The results were verified by the traditional finger-prick method, which was also used for classification as a conventional reference marker of blood glucose levels. The main goal of the proposed technique was to develop a non-invasive, low-cost blood glucose sensor for easy use by humans.