A novel in vivo Cerenkov luminescence image‐guided surgery on primary and metastatic colorectal cancer

Intraoperative Cerenkov luminescence imaging (CLI) can effectively improve the performance of tumor surgery. Nevertheless, the existing approaches are still unsatisfying to the clinical demands of open surgery. This study develops a novel intraoperative in vivo CLI approach to investigate the potential and value of Cerenkov luminescence (CL) image‐guided surgery. A system characterized with high sensitivity (19.61 kBq mL^{?1 18}F‐FDG) and desirable spatial resolution (88.34 μm) is developed. CL image‐guided surgery is performed on colorectal cancer (CRC) models of mice and swine. Tumor surgery is guided by the static CL images, and the resection quality is evaluated quantitatively and contrasted with other imaging modalities exemplified by bioluminescence imaging (BLI). The in vivo results demonstrated the effectiveness of the proposed intraoperative CLI approach for removing primary and metastatic CRC. Safety of performing in vivo CL image‐guided surgery is verified as well through radiation measurements of related staffs. Overall, the developed intraoperative in vivo CLI approach can efficiently improve the cancer treatment.     

Fast and sensitive delineation of brain tumor with clinically compatible moxifloxacin labeling and confocal microscopy

Delineation of brain tumor margins during surgery is critical to maximize tumor removal while preserving normal brain tissue to obtain optimal clinical outcomes. Although various imaging methods have been developed, they have limitations to be used in clinical practice. We developed a high‐speed cellular imaging method by using clinically compatible moxifloxacin and confocal microscopy for sensitive brain tumor detection and delineation. Moxifloxacin is a Food and Drug Administration (FDA) approved antibiotic and was used as a cell labeling agent through topical administration. Its strong fluorescence at short visible excitation wavelengths allowed video‐rate cellular imaging. Moxifloxacin‐based confocal microscopy (MBCM) was characterized in normal mouse brain specimens and visualized their cytoarchitecture clearly. Then, MBCM was applied to both brain tumor murine models and two malignant human brain tumors of glioblastoma and metastatic cancer. MBCM detected tumors in all the specimens by visualizing dense and irregular cell distributions, and tumor margins were easily delineated based on the cytoarchitecture. An image analysis method was developed for automated detection and delineation. MBCM demonstrated sensitive delineation of brain tumors through cytoarchitecture visualization and would have potentials for human applications, such as a surgery‐guiding method for tumor removal.      

Deep learning protocol for improved photoacoustic brain imaging

One of the key limitations for the clinical translation of photoacoustic imaging is penetration depth that is linked to the tissue maximum permissible exposures (MPE) recommended by the American National Standards Institute (ANSI). Here, we propose a method based on deep learning to virtually increase the MPE in order to enhance the signal‐to‐noise ratio of deep structures in the brain tissue. The proposed method is evaluated in an in vivo sheep brain imaging experiment. We believe this method can facilitate clinical translation of photoacoustic technique in brain imaging, especially in transfontanelle brain imaging in neonates.     

A new deep learning method for image deblurring in optical microscopic systems

Deconvolution is the most commonly used image processing method in optical imaging systems to remove the blur caused by the point‐spread function (PSF). While this method has been successful in deblurring, it suffers from several disadvantages, such as slow processing time due to multiple iterations required to deblur and suboptimal in cases where the experimental operator chosen to represent PSF is not optimal. In this paper, we present a deep‐learning‐based deblurring method that is fast and applicable to optical microscopic imaging systems. We tested the robustness of proposed deblurring method on the publicly available data, simulated data and experimental data (including 2D optical microscopic data and 3D photoacoustic microscopic data), which all showed much improved deblurred results compared to deconvolution. We compared our results against several existing deconvolution methods. Our results are better than conventional techniques and do not require multiple iterations or pre‐determined experimental operator. Our method has several advantages including simple operation, short time to compute, good deblur results and wide application in all types of optical microscopic imaging systems. The deep learning approach opens up a new path for deblurring and can be applied in various biomedical imaging fields.     

Biophotonic technologies for assessment of breast tumor surgical margins—A review

Breast conserving surgery (BCS) offering similar surgical outcomes as mastectomy while retaining breast cosmesis is becoming increasingly popular for the management of early stage breast cancers. However, its association with reoperation rates of 20% to 40% following incomplete tumor removal warrants the need for a fast and accurate intraoperative surgical margin assessment tool that offers cellular, structural and molecular information of the whole specimen surface to a clinically relevant depth. Biophotonic technologies are evolving to qualify as such an intraoperative tool for clinical assessment of breast cancer surgical margins at the microscopic and macroscopic scale. Herein, we review the current research in the application of biophotonic technologies such as photoacoustic imaging, Raman spectroscopy, multimodal multiphoton imaging, diffuse optical imaging and fluorescence imaging using medically approved dyes for breast cancer detection and/or tumor subtype differentiation toward intraoperative assessment of surgical margins in BCS specimens, and possible challenges in their route to clinical translation.     

Inside Front Cover: Neurosurgical brain tumor detection based on intraoperative optical intrinsic signal imaging technique: A case report of glioblastoma (J. Biophotonics 1/2020)

Intraoperative neurosurgical diagnosis of brain tumor determines the success rate of patients' prognoses. We firstly proposed a novel approach based on an optical method to distinguish the site of the tumor functionally. The promoted technique is non‐invasive, non‐radioactive, dye‐free, and potential of real‐time monitoring, which is still not available nowadays by using other techniques. The method could be applied to neuroimage guiding system for precision surgery of brain. Further details can be found in the article by Xin‐Rui Liu, Tien‐Yu Hsiao, Yun‐Qian, et al. ( e201900200 ).

     

Inside Front Cover: Fast and sensitive delineation of brain tumor with clinically compatible moxifloxacin labeling and confocal microscopy (J. Biophotonics 1/2020)

A new high‐speed cellular imaging method using clinically applicable moxifloxacin labeling, called as moxifloxacin based confocal microscopy (MBCM), was developed for fast and sensitive tumor detection and delineation. The MBCM demarcated malignant brain tumor from normal brain by visualizing dense and irregular cell distribution in the tumor. An image processing algorithm was developed for automated brain tumor detection. Further details can be found in the article by Seunghun Lee, Won Yeong Park, Hoonchul Chang, et al. ( e201900197 ).

     

Real‐time augmented reality for delineation of surgical margins during neurosurgery using autofluorescence lifetime contrast

Current clinical brain imaging techniques used for surgical planning of tumor resection lack intraoperative and real‐time feedback; hence surgeons ultimately rely on subjective evaluation to identify tumor areas and margins. We report a fluorescence lifetime imaging (FLIm) instrument (excitation: 355 nm; emission spectral bands: 390/40 nm, 470/28 nm, 542/50 nm and 629/53 nm) that integrates with surgical microscopes to provide real‐time intraoperative augmentation of the surgical field of view with fluorescent derived parameters encoding diagnostic information. We show the functionality and safety features of this instrument during neurosurgical procedures in patients undergoing craniotomy for the resection of brain tumors and/or tissue with radiation damage. We demonstrate in three case studies the ability of this instrument to resolve distinct tissue types and pathology including cortex, white matter, tumor and radiation‐induced necrosis. In particular, two patients with effects of radiation‐induced necrosis exhibited longer fluorescence lifetimes and increased optical redox ratio on the necrotic tissue with respect to non‐affected cortex, and an oligodendroglioma resected from a third patient reported shorter fluorescence lifetime and a decrease in optical redox ratio than the surrounding white matter. These results encourage the use of FLIm as a label‐free and non‐invasive intraoperative tool for neurosurgical guidance.     

Mesoscopic fluorescence lifetime imaging: Fundamental principles,clinical applications and future directions

Fluorescence lifetime imaging (FLIm) is an optical spectroscopic imaging technique capable of real-time assessments of tissue properties in clinical settings. Label-free FLIm is sensitive to changes in tissue structure and biochemistry resulting from pathological conditions, thus providing optical contrast to identify and monitor the progression of disease. Technical and methodological advances over the last two decades have enabled the development of FLIm instrumentation for real-time, in situ, mesoscopic imaging compatible with standard clinical workflows. Herein, we review the fundamental working principles of mesoscopic FLIm, discuss the technical characteristics of current clinical FLIm instrumentation, highlight the most commonly used analytical methods to interpret fluorescence lifetime data and discuss the recent applications of FLIm in surgical oncology and cardiovascular diagnostics. Finally, we conclude with an outlook on the future directions of clinical FLIm.     

Concept of photonic hook scalpel generated by shaped fiber tip with asymmetric radiation

Structured light have made deep impacts on modern biotechnology and clinical practice, with numerous optical systems and lasers currently being used in medicine to treat disease. We demonstrate a new concept of fiber-based optical hook scalpel. The subwavelength photonic hook is obtained in the vicinity of a shaped fiber tip with asymmetric radiation. A 1550 nm continuous-wave source, commonly used for medical imaging, has been required. Photonic hook with a lateral feature size less than the half-wavelength is achieved using a hemispherical shaped fiber tip with metallic mask. This breakthrough is carried out in ambient air by using a 4-μm-diameter fiber with a shaped tip. A good correlation is observed between the computed intensity distribution of photonic hook and the tip sizes. Photonic hook generated with a shaped fiber tip, easier to manipulate, shows far-reaching benefits for potential applications such as ophthalmic laser surgery, super-resolution microscopy, photolithography and material processing.     

In vivo detection of tumor boundary using ultrahigh‐resolution optical coherence angiography and fluorescence imaging

Accurate detection of early tumor margin is of great preclinical and clinical implications for predicting the survival rate of subjects and assessing the response of tumor microenvironment to chemotherapy or radiation therapy. Here, we report a multimodality optical imaging study on in vivo detection of tumor boundary by analyzing neoangiogenesis of tumor microenvironment (microangiography), microcirculatory blood flow (optical Doppler tomography) and tumor proliferation (green fluorescent protein [GFP] fluorescence). Microangiography demonstrates superior sensitivity (77.7 ± 6.4%) and specificity (98.2 ± 1.7%) over other imaging technologies (eg, optical coherence tomography) for tumor margin detection. Additionally, we report longitudinal in vivo imaging of tumor progression and show that the abrupt tumor cell proliferation did not occur until local capillary density and cerebral blood flow reached their peak approximately 2 weeks after tumor implantation. The unique capability of longitudinal multimodality imaging of tumor angiogenesis may provide new insights in tumor biology and in vivo assessment of the treatment effects on anti‐angiogenesis therapy for brain cancer.     

Widefield fluorescence lifetime imaging of protoporphyrin IX for fluorescence‐guided neurosurgery: An ex vivo feasibility study

Achieving a maximal safe extent of resection during brain tumor surgery is the goal for improved patient prognosis. Fluorescence‐guided neurosurgery using 5‐aminolevulinic acid (5‐ALA) induced protoporphyrin IX has thereby become a valuable tool enabling a high frequency of complete resections and a prolonged progression‐free survival in glioblastoma patients. We present a widefield fluorescence lifetime imaging device with 250 mm working distance, working under similar conditions such as surgical microscopes based on a time‐of‐flight dual tap CMOS camera. In contrast to intensity‐based fluorescence imaging, our method is invariant to light scattering and absorption while being sensitive to the molecular composition of the tissue. We evaluate the feasibility of lifetime imaging of protoporphyrin IX using our system to analyze brain tumor phantoms and fresh 5‐ALA‐labeled human tissue samples. The results demonstrate the potential of our lifetime sensing device to go beyond the limitation of current intensity‐based fluorescence‐guided neurosurgery.      

Lightsheet fluorescence lifetime imaging microscopy with wide‐field time‐correlated single photon counting

We report on wide‐field time‐correlated single photon counting (TCSPC)‐based fluorescence lifetime imaging microscopy (FLIM) with lightsheet illumination. A pulsed diode laser is used for excitation, and a crossed delay line anode image intensifier, effectively a single‐photon sensitive camera, is used to record the position and arrival time of the photons with picosecond time resolution, combining low illumination intensity of microwatts with wide‐field data collection. We pair this detector with the lightsheet illumination technique, and apply it to 3D FLIM imaging of dye gradients in human cancer cell spheroids, and C. elegans.     

Deep-skin multiphoton microscopy in vivo excited at 1600 nm: A comparative investigation with silicone oil and deuterium dioxide immersion

Multiphoton microscopy (MPM) excited at the 1700-nm window has enabled deep-tissue penetration in biological tissue, especially brain. MPM of skin may also benefit from this deep-penetration capability. Skin is a layered structure with varying refractive index (from 1.34 to 1.5). Consequently, proper immersion medium should be selected when imaging with high numerical aperture objective lens. To provide guidelines for immersion medium selection for skin MPM, here we demonstrate comparative experimental investigation of deep-skin MPM excited at 1600 nm in vivo, using both silicone oil and deuterium dioxide (D₂O) immersion. We specifically characterize imaging depths, signal levels and spatial resolution. Our results show that both immersion media give similar performance in imaging depth and spatial resolution, while signal levels are slightly better with silicone oil immersion. We also demonstrate that local injection of fluorescent beads into the skin is a viable technique for spatial resolution characterization in vivo.      

High-speed volumetric imaging in vivo based on structured illumination microscopy with interleaved reconstruction

Wide-field fluorescence microscopy (WFFM) is widely adopted in biomedical studies, due to its high imaging speed over large field-of-views. However, WFFM is susceptible to out-of-focus background. To overcome this problem, structured illumination microscopy (SIM) was proposed as a wide-field, optical-sectioning technique, which needs multiple raw images for image reconstruction and thus has a lower imaging speed. Here we propose SIM with interleaved reconstruction, to make SIM of lossless speed. We apply this method in volumetric imaging of neural network dynamics in brains of zebrafish larva in vivo.     

Distinguishing metastatic triple‐negative breast cancer from nonmetastatic breast cancer using second harmonic generation imaging and resonance Raman spectroscopy

Triple‐negative breast cancer (TNBC) is an aggressive subset of breast cancer that is more common in African‐American and Hispanic women. Early detection followed by intensive treatment is critical to improving poor survival rates. The current standard to diagnose TNBC from histopathology of biopsy samples is invasive and time‐consuming. Imaging methods such as mammography and magnetic resonance (MR) imaging, while covering the entire breast, lack the spatial resolution and specificity to capture the molecular features that identify TNBC. Two nonlinear optical modalities of second harmonic generation (SHG) imaging of collagen, and resonance Raman spectroscopy (RRS) potentially offer novel rapid, label‐free detection of molecular and morphological features that characterize cancerous breast tissue at subcellular resolution. In this study, we first applied MR methods to measure the whole‐tumor characteristics of metastatic TNBC (4T1) and nonmetastatic estrogen receptor positive breast cancer (67NR) models, including tumor lactate concentration and vascularity. Subsequently, we employed for the first time in vivo SHG imaging of collagen and ex vivo RRS of biomolecules to detect different microenvironmental features of these two tumor models. We achieved high sensitivity and accuracy for discrimination between these two cancer types by quantitative morphometric analysis and nonnegative matrix factorization along with support vector machine. Our study proposes a new method to combine SHG and RRS together as a promising novel photonic and optical method for early detection of TNBC.     

Inside Cover

A novel volumetric information fusion based on joint weighted evaluation and stationary wavelet transform is proposed. Threedimensional stationary wavelet transform was performed on multi-focus data to obtain wavelet coefficients. Differential evolution based on joint weighted evaluation was then employed to optimize the block size of division. Corresponding sub-coefficients of multi-focus data were fused with the proposed fusion rule. Finally, large volumetric and high-resolution photoacoustic imaging can be achieved by applying the inverse stationary wavelet transform. Further details can be found in the article by Xianlin Song, Sihang Li, Zhuangzhuang Wang, and| Xiongjun Cao ( e202200234 )

     

Superpixel Raman spectroscopy for rapid skin cancer margin assessment

Spontaneous Raman micro‐spectroscopy has been demonstrated great potential in delineating tumor margins; however, it is limited by slow acquisition speed. We describe a superpixel acquisition approach that can expedite acquisition between ~×100 and ×10 000, as compared to point‐by‐point scanning by trading off spatial resolution. We present the first demonstration of superpixel acquisition on rapid discrimination of basal cell carcinoma tumor from eight patients undergoing Mohs micrographic surgery. Results have been demonstrated high discriminant power for tumor vs normal skin based on the biochemical differences between nucleus, collagen, keratin and ceramide. We further perform raster‐scanned superpixel Raman imaging on positive and negative margin samples. Our results indicate superpixel acquisition can facilitate the use of Raman microspectroscopy as a rapid and specific tool for tumor margin assessment.     

Inside Cover

A high‐efficiency computer‐aided diagnostic model of ovarian cancer was developed, integrating SHG imaging technology for non‐invasive imaging of living tissue and machine learning method based on radiomics and TPOT. This model can rapidly, non‐destructively, and accurately perform ovarian cancer diagnosis and has great potential in improving diagnostic efficacy and efficiency of medical pathologists. Further details can be found in the article by Guangxing Wang, Yang Sun, Youting Chen, Qiqi Gao, Dongqing Peng, Hongxin Lin, Zhenlin Zhan, Zhiyi Liu, and Shuangmu Zhuo ( e202000050 ).

     

Pseudo‐real‐time retinal layer segmentation for high‐resolution adaptive optics optical coherence tomography

We present a pseudo‐real‐time retinal layer segmentation for high‐resolution Sensorless Adaptive Optics‐Optical Coherence Tomography (SAO‐OCT). Our pseudo‐real‐time segmentation method is based on Dijkstra's algorithm that uses the intensity of pixels and the vertical gradient of the image to find the minimum cost in a geometric graph formulation within a limited search region. It segments six retinal layer boundaries in an iterative process according to their order of prominence. The segmentation time is strongly correlated to the number of retinal layers to be segmented. Our program permits en face images to be extracted during data acquisition to guide the depth specific focus control and depth dependent aberration correction for high‐resolution SAO‐OCT systems. The average processing times for our entire pipeline for segmenting six layers in a retinal B‐scan of 496 × 400 and 240 × 400 pixels are around 25.60 and 13.76 ms, respectively. When reducing the number of layers segmented to only two layers, the time required for a 240 × 400 pixel image is 8.26 ms.