KEYWORDS: Luminescence, Microsoft Foundation Class Library, Visualization, Intravascular ultrasound, Arteries, Imaging systems, In vivo imaging, Fluorescence lifetime imaging, Tissues, Biological research
Fluorescence Lifetime Imaging (FLIm) is a label-free technique that provides biochemical information from biological samples derived from tissue autofluorescence. Using a custom multispectral FLIm/IVUS catheter system, fluorescence lifetime data (n=33,980 locations) was collected from ex vivo human artery segments (n=32 samples). Our findings indicate that intravascular spectroscopy with FLIm supports the identification of early progression-prone lesions, characterized by the accumulation of extracellular lipids, as well as the quantification of inflammatory activity, characterized by macrophage foam cells accumulation. This information improves our understanding of plaque development, which may ultimately be used to improve risk assessment of acute coronary events.
Breast cancer is the second most common cancer worldwide and by far the most frequent cancer among women. A major limiting factor for complete surgical resection is the physician’s ability to intraoperatively assess presence of tumor positive resection margins. Many surgeons still rely on visual or tactile guidance and this leads in incomplete cancer resection rate that ranges between 20% and 50%. In this study we use multi-spectral Time-Resolved Fluorescence Spectroscopy (ms-TRFS), allowing for dynamic raster tissue scanning by merging a 450 nm aiming beam with the pulsed fluorescence excitation light in a single fiber collection. We developed a device that combines multispectral time resolved fluorescence lifetime with state-of-the-art machine learning techniques to delineate tumor margins of excised breast cancer specimen in real-time. In order to train the classifier, we precisely registered ex-vivo specimen with histology slides using fiducial markers and piecewise shape matching. A probabilistic random forest classifier was trained to rapidly delineate tumor regions. Moreover, the system not only provides binary output on tumor regions, but also quantifies the classifier’s certainty of each prediction. This allows the surgeon to either rescan the ambiguous area to increase certainty or extend the resection area to decrease the probability of positive tumor margins. The outcome is visualized by a simple color scheme showing tumor in red and adipose and fibrous tissue in blue and green and the certainty is encoded in color saturation. The system has been evaluated for n=10 lumpectomy specimen showing promising agreement between the classifier’s predictions and histology.
An important step in establishing the diagnostic potential for emerging optical imaging techniques is accurate registration between imaging data and the corresponding tissue histopathology typically used as gold standard in clinical diagnostics. We present a method to precisely register data acquired with a point-scanning spectroscopic imaging technique from fresh surgical tissue specimen blocks with corresponding histological sections. Using a visible aiming beam to augment point-scanning multispectral time-resolved fluorescence spectroscopy on video images, we evaluate two different markers for the registration with histology: fiducial markers using a 405-nm CW laser and the tissue block’s outer shape characteristics. We compare the registration performance with benchmark methods using either the fiducial markers or the outer shape characteristics alone to a hybrid method using both feature types. The hybrid method was found to perform best reaching an average error of 0.78±0.67 mm. This method provides a profound framework to validate diagnostical abilities of optical fiber-based techniques and furthermore enables the application of supervised machine learning techniques to automate tissue characterization.
The current standard of care for early stages of breast cancer is breast-conserving surgery (BCS). BCS involves a lumpectomy procedure, during which the tumor is removed with a rim of normal tissue-if cancer cells found in that rim of tissue, it is called a positive margin and means part of the tumor remains in the breast. Currently there is no method to determine if cancer cells exist at the margins of lumpectomy specimens aside from time-intensive histology methods that result in reoperations in up to 38% of cases. We used fluorescence lifetime imaging (FLIm) to measure time-resolved autofluorescence from N=13 ex vivo human breast cancer specimens (N=10 patients undergoing lumpectomy or mastectomy) and compared our results to histology. Tumor (both invasive and ductal carcinoma in situ), fibrous tissue, fat and fat necrosis have unique fluorescence signatures. For instance, between 500-580 nm, fluorescence lifetime of tumor was shortest (4.7 ± 0.4 ns) compared to fibrous tissue (5.5 ± 0.7 ns) and fat (7.0 ± 0.1 ns), P<0.05 (ANOVA). These differences are due to the biochemical properties of lipid, nicotineamide adenine dinucleotide (NADH) and collagen fibers in the fat, tumor and fibrous tissue, respectively. Additionally, the FLIm data is augmented to video of the breast tissue with image processing algorithms that track a blue (450 nm) aiming beam used in parallel with the 355 nm excitation beam. This allows for accurate histologic co-registration and in the future will allow for three-dimensional lumpectomy surfaces to be imaged for cancer margin delineation.
FL-IVUS combines intravascular ultrasound with fluorescence lifetime imaging to obtain morphologic and biochemical details from the arterial wall. Ultrasound measurements alone provide morphologic information (plaque burden, remodeling index and presence of calcium). Fluorescence lifetime can determine the presence of a thick fibrous cap, macrophage infiltration, and lipid cores beneath thin fibrous caps. These details are important to assess plaque vulnerability. In this study, we focused on the ability of FL-IVUS to differentiate between early and advanced lipid cores-advanced cores are vulnerable to rupture. We imaged N=12 ex vivo human coronary arteries and performed hematoxylin and eosin, Movat’s pentachrome and CD68 immunohistochemistry at 500 micron intervals throughout the length of the vessels. We found only N=1 thin-capped fibroatheroma (TCFA) with an advanced necrotic core and N=7 cases of foam cell infiltration, early lipid cores or deep necrotic cores. IVUS was able to observe the increased plaque burden and calcification of the advanced and deep necrotic cores, but could not identify early lipid cores, foam cell infiltration or discriminate between deep necrotic cores and TCFA. The addition of FLIm to IVUS allowed the TCFA to be discriminated from early lipid accumulation, particularly at 542±50 nm (355 nm pulsed excitation): 7.6 ± 0.5 ns compared to 6.6 ± 0.4 ns, respectively (P<0.001 by ANOVA analysis). These differences need to be validated in a larger cohort, but exist due to specific lipid content in the necrotic core as well as increased extracellular matrix in early lesions.
Autofluorescence lifetime spectroscopy is a promising non-invasive label-free tool for characterization of biological tissues and shows potential to report structural and biochemical alterations in tissue owing to pathological transformations. In particular, when combined with fiber-optic based instruments, autofluorescence lifetime measurements can enhance intraoperative diagnosis and provide guidance in surgical procedures. We investigate the potential of a fiber-optic based multi-spectral time-resolved fluorescence spectroscopy instrument to characterize the autofluorescence fingerprint associated with histologic, morphologic and metabolic changes in tissue that can provide real-time contrast between healthy and tumor regions in vivo and guide clinicians during resection of diseased areas during transoral robotic surgery. To provide immediate feedback to the surgeons, we employ tracking of an aiming beam that co-registers our point measurements with the robot camera images and allows visualization of the surgical area augmented with autofluorescence lifetime data in the surgeon’s console in real-time. For each patient, autofluorescence lifetime measurements were acquired from normal, diseased and surgically altered tissue, both in vivo (pre- and post-resection) and ex vivo. Initial results indicate tumor and normal regions can be distinguished based on changes in lifetime parameters measured in vivo, when the tumor is located superficially. In particular, results show that autofluorescence lifetime of tumor is shorter than that of normal tissue (p < 0.05, n = 3). If clinical diagnostic efficacy is demonstrated throughout this on-going study, we believe that this method has the potential to become a valuable tool for real-time intraoperative diagnosis and guidance during transoral robot assisted cancer removal interventions.
Multi-Spectral Time-Resolved Fluorescence Spectroscopy (ms-TRFS) can provide label-free real-time feedback on tissue composition and pathology during surgical procedures by resolving the fluorescence decay dynamics of the tissue. Recently, an ms-TRFS system has been developed in our group, allowing for either point-spectroscopy fluorescence lifetime measurements or dynamic raster tissue scanning by merging a 450 nm aiming beam with the pulsed fluorescence excitation light in a single fiber collection. In order to facilitate an augmented real-time display of fluorescence decay parameters, the lifetime values are back projected to the white light video. The goal of this study is to develop a 3D real-time surface reconstruction aiming for a comprehensive visualization of the decay parameters and providing an enhanced navigation for the surgeon. Using a stereo camera setup, we use a combination of image feature matching and aiming beam stereo segmentation to establish a 3D surface model of the decay parameters. After camera calibration, texture-related features are extracted for both camera images and matched providing a rough estimation of the surface. During the raster scanning, the rough estimation is successively refined in real-time by tracking the aiming beam positions using an advanced segmentation algorithm. The method is evaluated for excised breast tissue specimens showing a high precision and running in real-time with approximately 20 frames per second. The proposed method shows promising potential for intraoperative navigation, i.e. tumor margin assessment. Furthermore, it provides the basis for registering the fluorescence lifetime maps to the tissue surface adapting it to possible tissue deformations.
The ability to distinguish macrophage subtypes noninvasively could have diagnostic potential in cancer, atherosclerosis, and diabetes, where polarized M1 and M2 macrophages play critical and often opposing roles. Current methods to distinguish macrophage subtypes rely on tissue biopsy. Optical imaging techniques based on light scattering are of interest as they can be translated into biopsy-free strategies. Because mitochondria are relatively strong subcellular light scattering centers, and M2 macrophages are known to have enhanced mitochondrial biogenesis compared to M1, we hypothesized that M1 and M2 macrophages may have different angular light scattering profiles. To test this, we developed an in vitro angle-resolved forward light scattering measurement system. We found that M1 and M2 macrophage monolayers scatter relatively unequal amounts of light in the forward direction between 1.6 deg and 3.2 deg with M2 forward scattering significantly more light than M1 at increasing angles. The ratio of forward scattering can be used to identify the polarization state of macrophage populations in culture.
This study investigates the ability of a flexible fiberoptic-based fluorescence lifetime imaging microscopy (FLIM) technique to resolve biochemical features in plaque fibrotic cap associated with plaque instability and based solely on fluorescence decay characteristics. Autofluorescence of atherosclerotic human aorta (11 autopsy samples) was measured at 48 locations through two filters, F377: 377/50 and F460: 460/60 nm (center wavelength/bandwidth). The fluorescence decay dynamic was described by average lifetime (τ) and four Laguerre coefficients (LECs) retrieved through a Laguerre deconvolution technique. FLIM-derived parameters discriminated between four groups [elastin-rich (ER), elastin and macrophage-rich (E+M), collagen-rich (CR), and lipid-rich (LR)]. For example, τF377 discriminated ER from CR (R = 0.84); τF460 discriminated E+M from CR and ER (R = 0.60 and 0.54, respectively); LEC-1F377 discriminated CR from LR and E+M (R = 0.69 and 0.77, respectively); P < 0.05 for all correlations. Linear discriminant analysis was used to classify this data set with specificity >87% (all cases) and sensitivity as high as 86%. Current results demonstrate for the first time that clinically relevant features (e.g., ratios of lipid versus collagen versus elastin) can be evaluated with a flexible-fiber based FLIM technique without the need for fluorescence intensity information or contrast agents.
We demonstrate for the first time the application of an endoscopic fluorescence lifetime imaging microscopy (FLIM) system to the intraoperative diagnosis of glioblastoma multiforme (GBM). The clinically compatible FLIM prototype integrates a gated (down to 0.2 ns) intensifier imaging system with a fiber-bundle (fiber image guide of 0.5 mm diameter, 10,000 fibers with a gradient index lens objective 0.5 NA, and 4 mm field of view) to provide intraoperative access to the surgical field. Experiments conducted in three patients undergoing craniotomy for tumor resection demonstrate that FLIM-derived parameters allow for delineation of tumor from normal cortex. For example, at 460±25-nm wavelength band emission corresponding to NADH/NADPH fluorescence, GBM exhibited a weaker florescence intensity (35% less, p-value <0.05) and a longer lifetime GBM-Amean=1.59±0.24 ns than normal cortex NC-Amean=1.28±0.04 ns (p-value <0.005). Current results demonstrate the potential use of FLIM as a tool for image-guided surgery of brain tumors.
The objective of this study was to develop an automated algorithm which uses fluorescence lifetime imaging microscopy
(FLIM) images of human aortic atherosclerotic plaque to provide quantitative and spatial information regarding
compositional features related to plaque vulnerability such as collagen degradation, lipid accumulation, and macrophage
infiltration. Images were acquired through a flexible fiber imaging bundle with intravascular potential at two wavelength
bands optimal to recognizing markers of vulnerability: F377: 377/55 nm and F460: 460/50 nm (center
wavelength/bandwidth). A classification method implementing principal components analysis and linear discriminant
analysis to correlate FLIM data sets with histopathology was validated on a training set and then used to classify a
validation set of FLIM images. The output of this algorithm was a false-color image with each pixel color coded to
represent the chemical composition of the sample. Surface areas occupied by elastin, collagen, and lipid components
were then calculated and used to define the vulnerability of each imaged location. Four groups were defined: early
lesion, stable, mildly vulnerable and extremely vulnerable. Each imaged location was categorized in one of the groups
based on histopathology and classification results; sensitivities (SE) and specificities (SP) were calculated (SE %/SP %):
early lesion: 95/96, stable: 71/97, mildly vulnerable: 75/94, and extremely vulnerable: 100/93. The capability of this
algorithm to use FLIM images to quickly determine the chemical composition of atherosclerotic plaque, particularly
related to vulnerability, further enhances the potential of this system for implementation as an intravascular diagnostic
modality.
Atherosclerotic plaque composition has been associated with plaque instability and rupture. This study investigates the use of fluorescence lifetime imaging microscopy (FLIM) for mapping plaque composition and assessing features of vulnerability. Measurements were conducted in atherosclerotic human aortic samples using an endoscopic FLIM system (spatial resolution of 35 µm; temporal resolution 200 ps) developed in our lab which allows mapping in one measurement the composition within a volume of 4 mm diameter x 250 µm depth. Each pixel in the image represents a corresponding fluorescence lifetime value; images are formed through a flexible 0.6 mm side-viewing imaging bundle which allows for further intravascular applications. Based on previously recorded spectra of human atherosclerotic plaque, fluorescence emission was collected through two filters: f1: 377/50 and f2: 460/60 (center wavelength/bandwidth), which together provides the greatest discrimination between intrinsic fluorophores related to plaque vulnerability. We have imaged nine aortas and lifetime images were retrieved using a Laguerre expansion deconvolution technique and correlated with histopathology. Early results demonstrate discrimination using fluorescence lifetime between early, lipid-rich, and collagen-rich lesions which are consistent with previously reported time-resolved atherosclerotic plaque measurements.
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