Source: https://pubs.rsc.org/en/content/articlehtml/2019/pp/c8pp00410b
Timestamp: 2019-04-20 11:09:02+00:00

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Fluorescence offers unprecedented sensitivity due to the intense electronic transition dipole moment. However, many samples are intrinsically non-fluorescent or only weakly fluorescent and saturation might pose a problem since the excited electrons remain in the excited state for a few nanoseconds before returning to the ground state to become available for another excitation. In addition, exogenous fluorescent labels are perturbative and not recommended for in vivo medical applications. Hence, additional optical imaging methods with high sensitivity and specific complementary molecular contrasts are highly desirable.
TPEF and SHG can easily be combined in multimodal settings.5,15,24,25 Various studies have utilized the combination on unstained tissue sections to observe the morphological changes that arise in diseased or cancerous tissues and to generate images, with information content comparable to standard haematoxylin-eosin (HE) stained slides typically used by pathologists.14,26,27 Although studies have shown the potential of this combination as a substitute to conventional histopathological diagnosis, there are still associated limitations.
A main limitation in NLOI arises from the tight focusing condition restricting fast scanning of large areas. Hence, despite the multifaceted abilities of conventional NLOI, its ability to identify and locate morphological landmarks in 3-D and in real-time is lacking. Overcoming the effect of motion artefacts with scanning areas in the mm2 to cm2 range, and penetration depths in the mm range (wide-field), calls for integration of a complementary technique into a traditional NLOI platform.
Optical coherence tomography (OCT) provides fast label-free, non-invasive and high-resolution optical sectioning of tissues through the coherence gating of light sources covering a broad bandwidth either by the means of broad emission spectra or fast sweeping. It enables spatial resolution down to microns over areas of a couple of cm2.36 With typical penetration depths of several millimetres, OCT reveals the intrinsic 3D structure of tissue in situ based on interferometry with vast applications in the medical field at video rate acquisition speeds.36 Within two decades OCT has become the prime diagnostic imaging modality in ophthalmology37,38 and has increased its impact in cardiology,39 dermatology,40,41 dentistry,42 cancer research43–45 and a variety of other applications. Detecting structural information on a cellular level broadens the understanding of tissue environment for in vivo studies, but the lacking molecular specificity hinders differentiation between pathologic and healthy tissues with similar scattering or structural properties. Structural changes of tissues and cells typically occur only after carcinogenic biochemical alterations. OCT contrast can be enhanced by different implementations,46 e.g. polarization-sensitive OCT,47 spectroscopic OCT48 and Doppler OCT49 as important functional variants. Nonetheless, molecular specificity on a cellular level is still limited. Hence, despite the prowess of this technology, the sensitivity and specificity to detect pathologic tissue is restricted.
In this paper, we have developed a multimodal imaging platform that incorporates OCT, spectral focusing CARS, SHG, and TPEF to collect structural and biochemical information by merging well-developed optical imaging techniques with ultra-fast Ti:sapphire lasers integrated in a LSM. Since each modality measures different tissue characteristics, we predict that their combination will increase the sensitivity and specificity for detecting early tissue alteration compared to standard diagnostic methods and may provide a new insight in the diagnosis of different diseases.
One major consideration in the development of the multi-modality imaging platform lies in the ability to perform fast wide-field OCT and consecutive simultaneous NLOI in the backward propagation direction without causing one modality to interfere with the others and compromising image quality. Our approach is designed on the base of a custom-modified LSM where we combine OCT with spectral focusing CARS, SHG and TPEF.
The limited penetration offered by standard microscopy techniques is overcome by OCT which allows volumetric morphological imaging for ex vivo and in vivo cell-based imaging approaches – not only surface scanning determination. Specific regions of interest (ROI) or landmarks can be identified by OCT and then correlated with label-free molecular biomarkers. Overall the integration of all modalities offers the unique opportunity to non-destructively, non-invasively and partly simultaneously analyse the morphological and molecular composition of the sample to be investigated.
Fig. 1 illustrates the principal features of our customized multimodal setup. In our system, spectral focusing CARS, TPEF, and SHG can currently be performed simultaneously after finding a structure of interest in our OCT real-time preview. The developed platform can be logically divided into several subsystems, namely the OCT engine, the NLOI engine, and the LSM for imaging. OCT and NLOI are optically and electronically synchronized such that the multimodal images are intrinsically co-registered and collected consecutively. Wide-field OCT images are recorded first and real-time preview enables localization of ROIs to be imaged with NLOI. A platform to secure the samples is situated on the top of programmable xy and z stages (PILine xy M687, PInano z P736, Physik Instrumente GmbH & Co. KG) directly beneath the objective lens. OCT and NLOI use two different sets of light sources and detectors with all acquisition channels combined into a customized upright microscope (Nikon Eclipse E400). The LSM is driven by a pair of galvanometric mirrors (6220H 8 mm, Cambridge Technology) to allow for raster scanning. NLOI and OCT utilize only one optical excitation scanning path facilitating co-registration. Light is focused on the sample by means of two different objectives to obtain reasonable lateral resolution and FOV for each modality. The different imaging modalities, OCT and NLOI can be simply switched by a flipping mirror.
Fig. 1 Setup of the multimodal platform. Three main parts of the multimodal platform can be distinguished: the NLOI engine, the OCT engine and the common LSM imaging unit. In dashed gray lines are the electrical connections to electronically control and synchronize the collection of the excited signals. BPF: band pass filter (BPF1: 1040 nm/40 nm, BPF2: 640 nm/50 nm, BPF3: 400 nm/50 nm); SPF: 715 nm short pass filter; PBS: polarization beamsplitter; SF57: 5 cm glass block of SF57; DM: dichroic mirror; FM: flipping mirror; PP: polarization paddle; ND: neutral density filter; GS: galvanometric scanner; PMT: photomultiplier tube.
The schematic of the spectral domain (SD) OCT engine uniting coherence gated depth information of OCT with high lateral resolution of confocal microscopy for isotropic ultra-high resolution imaging and sufficient penetration depth is shown in Fig. 1. A low-coherence, ultra-broadband compact Ti:sapphire laser centered at ∼800 nm with 150 nm bandwidth at full width half maximum (FWHM) and 75 MHz repetition rate is used as a light source for SD OCT.88,89 The laser output is focused into a single mode fiber to direct the beam into a fiber-based Michelson interferometer with a 90 : 10 single mode fiber coupler (45-U7980-20-23162, Gould Fiber Optics, USA). Two reflective fiber collimators (RC04FC-01, Thorlabs, USA) at the exits of the fiber coupler direct and collimate the light in the free space part of reference and sample arm.
Polarization paddles are used to match the polarization of the light in both arms before recombination in the detection arm. Neutral density filters (Thorlabs, NDC-50C-4) are inserted in both arms to reduce the laser power in order to not saturate the detector. In the reference arm, glass blocks composed of BK7 balance the dispersion introduced by all the optical elements present in the sample arm. At the end of the reference arm, a silver (Ag) mirror is placed on a translation stage to match the optical path length between the reference arm and the sample arm, and to couple the light back into the detection arm. In the sample arm, a mirror on a flipping mount is inserted to direct the light from the SD OCT engine into the microscope and focus on the sample with a 10× objective (Nikon CFI Achro 10× 0.25NA). The backscattered light from the sample is de-scanned by propagating backwards through the 4f system and galvanometric scanning mirrors, recollected by the fiber collimator, recombined with light from the reference arm and directed to the detection arm with a spectrometer supporting a bandwidth of 260 nm. The collimated light (collimator focal length f = 100 mm, OZ, Ottawa, Canada) is sent through the 1200 lines per mm grating (Wasatch Photonics, Logan, USA) with 840 nm central wavelength. Then the diffracted light is focused with an f = 85 mm objective (ZEISS PLANAR T 1.4/85 ZF-IR-I, Carl Zeiss, Oberkochen, Germany) onto the 2048 pixels of the 12-bit CCD line scan camera with 70 kHz maximum line-rate (AViiVA Atmel EM4CL 2014, Essex, UK). The spectrometer acquires 2048 samples for each A-scan at a measured rate of 67 kHz and is calibrated with an external commercial spectrometer. The maximum depth samples are around 1.3 mm in free space, approximately corresponding to 1.3 μm depth resolution. The axial resolution achievable by the imaging system is 2.1 μm in air corresponding to ∼1.4 μm in tissue and is almost constant over the whole depth range with a 9 dB signal roll-off over 1 mm. The sensitivity is measured as 96 dB in tissue including the losses in the microscope (50% single pass). In the experimental set-up a lateral resolution better than 2.19 μm can be measured with an USAF 1951 Resolution Target. The SD OCT system is set-up to acquire volumes consisting of 400 B-Scans with 400 A-Scans/B-Scan and 2048 pixels/A-Scan. From 2048 pixels/A-Scan, only 1024 pixels are usable to extract the depth profile due to the complex-conjugate artefact. The maximum volume size in one acquisition is 1.2 mm × 1.2 mm × 1.3 mm. The acquisition speed of 166 B-Scans per s gives the total time of 2.4 s to acquire one volume. The maximum incident power at the samples is 2.5 mW. Data acquisition is performed using a PC with a NI PCIe-1430 frame-grabber and controlled using a NI PCI-6115 data acquisition card (National Instruments) with a custom software written in MATLAB. Only one PC is required to operate the data acquisition control boards in the microscope for OCT and NLOI. Real-time preview facilitates the identification of ROIs and controls the zoom into specific regions with high resolution and molecular specificity.
In brief, the integrated spectral focusing CARS, SHG and TPEF imaging platform is based on two-color excitation beams and three detection channels as described in detail elsewhere.86 In our previous work on the development of a compact epi-directed non-linear imaging device several unique strategies were implemented to seamlessly and simultaneously acquire hyperspectral CARS, SHG and TPEF signals within the focal volume in the epi-direction. These strategies included the implementation of a compact and cost-effective Ti:sapphire laser centered at ∼805 nm with 15 nm bandwidth at FWHM compressed to ∼70 fs and 75 MHz repetition rate used as pump beam for CARS and to excite TPEF and SHG. It is also used to pump a polarization-maintaining photonic crystal fiber (PCF) whose filtered output is further amplified with a Yb:fiber amplifier to generate the Stokes beam used in CARS centered at 1050 nm with 18 nm bandwidth at FWHM and compressed to ∼100 fs generated by the Ti:sapphire laser as shown in Fig. 1. Spectral focusing CARS (adding a spectral dimension to CARS images) is realized by introducing equal chirp on pump and Stokes pulses with the insertion of SF57 glass blocks31,32,83 enabling a spectral resolution for CARS spectroscopy of about ∼35 cm−1. The change of the temporal overlap controlled by a computer-controlled delay stage allows for fast tuning of Raman frequencies corresponding to the CH stretching vibrations. Pump and Stokes beams are recombined with a dichroic beamsplitter, directed into the LSM and focused on the sample (NIR Apo 40× Nikon). Epi-detected signals from CARS, TPEF and SHG are collected in a non-descanned geometry by the objective and discriminated from the excitation signal by means of a dichroic mirror immediately above the objective. In addition, the excited light signals are guided to an array of photomultiplier tubes using a lens, dichroic mirror and detection filters. The detector consisting of three channels covers the range of CARS, SHG, and TPEF signals (Channel 1: 640 nm ± 25 nm, Channel 2: 400 nm ± 25 nm, and Channel 3: 512 nm ± 100 nm). ScanImage 3.8 software90 controls the galvanometer scanners and data acquisition in combination with the custom Matlab program to ensure impeccable communication between the programs and different modalities.
The performance of the label-free multimodal optical imaging platform is demonstrated by recording OCT and NLOI images of a portion of freshly excised mouse ear tissue within less than one hour after excision. We use a real-time preview to located different ROIs and acquire OCT volumes with a size of 1.2 × 1.2 × 1.3 mm3 within 2.4 s. OCT provides en face images to visualize the topology of the mouse ear and OCT cross-sections to obtain the capability to differentiate between the different layers the skin, the epidermis and dermis with the epidermis junction as shown in Fig. 2. The orthogonal views of the skin reveal the epidermis (E), which is the surface of the skin, at the very top. Underneath the epidermis, the dermis junction can be seen, followed by the dermis (D) where hair follicles with follicle shaft and the follicle bulb as well as sebaceous glands (SG) and small blood and lymph vessels are located. The dark layer inside the tissue is the auricular cartilage (AC) of the ear followed by adipose tissue (AT). Sebaceous glands can be identified within the dermis layer, 50 μm below the epidermis as indicated in Fig. 2 by the yellow cross-hairs. The cross-hairs in the orthogonal views indicate the position of our ROI (the sebaceous gland) where the NLOI is performed. As outlined before, OCT and NLOI have different FOVs. The three dimensional topological overview obtained by wide-field screening with OCT allows for zooming into specific ROIs with simultaneous collection of SHG, TPEF, and CARS signals in the CH stretching region.
Fig. 2 OCT orthogonal views of freshly excised mouse ear tissue allowing identification of epidermis (E), dermis (D), sebaceous gland (SG), auricular cartilage (AC) and adipose tissue (AT). Panel A, B and C are 2D views of the volumetric information in panel D used to localize a single sebaceous gland (yellow cross-hairs): panel A represents xz plane, panel B yz plane and panel C xy plane. In (D) we show the 3D visualization of the mouse ear tissue with a volume cut corresponding to the plane in panel (A), (B) and (C). Pixel aspect ratio 1 : 1 : 1.
The multimodal NLOI images in Fig. 3 were taken 50 μm deep in the tissue with a FOV of 256 × 256 pixels corresponding to 70 × 70 μm and with 6.4 μs pixel dwell time. A compromise between image quality and acquisition speed, depending on the strength of the excited signal has been made in this case. NLOI is capable of visualizing the bright structures surrounding the follicle in the second layer of the skin, the sebaceous glands. Due to its CH bonding and high Raman cross section, fatty components can be easily visualized with CARS. Hence, the sebocytes forming the sebaceous gland can be perfectly visualized in the CARS channel due to their high lipid content shown in Fig. 3C (red color-coded). They are multicellular compartments packed with sebum reservoirs containing triglycerides and wax esters. Intracellular lipid lobuli inside each sebocyte forming the sebaceous gland are clearly visible as bright granuli due to their high lipid content. Nuclei marked with N and cell membranes marked with M appear as dark structures due to their poor lipid content. Also, the hair shaft marked with F can be visualized. The contrast in the CARS image in Fig. 3 arises from the Raman resonance located at 2860 cm−1 with an indicated spectral resolution of 35 cm−1. Additional contrast from collagen and elastin can be revealed in SHG and TPEF channels as shown in Fig. 3A and B. The ECM in the dermis providing structural and biochemical support for the sebaceous gland mainly consists of collagen fibers, accompanied by reticular and elastic fibers. While collagen fibers generate SHG signal detected in channel 2 (blue color-coded), elastin fibers generate strong autofluorescence as visible in channel 3 (green color-coded). Also, the signal from the hair follicle, especially from the hair shaft (F) is visible through its elastin, keratin and lipid content appears in the TPEF and CARS channels. Fig. 3D shows a merged multimodal image of the sebaceous gland. The epi-detected CARS, SHG, and TPEF images are represented with red, blue, and green, respectively. All images are obtained with a frame rate of about 1 Hz. The pump and Stokes powers are 19 and 6 mW on the sample, respectively. As already reported sebaceous glands and subcutaneous fat cells have different lipid compositions which can be probed at different locations in the CH stretching region (2800–3100 cm−1). This variance indicates the difference between highly saturated lipids in the gland and the mono-unsaturated lipid acyl chain in the adipocytes. Since our CARS signals are generated by means of chirped pulses (spectral focusing) a spectral dimension is added to the CARS image providing molecule-specific information of the tissue for better interpretation of images where heterogeneous molecular composition aggravates the analysis and discrimination, e.g. between protein and lipids. The spectroscopic capability of the system is demonstrated by recording hyperspectral images. A projection of a 120 image dataset from the mouse ear is recorded along the spectral range from ∼2550 to 3200 cm−1, corresponding to a time delay between the pump and Stokes pulses of ∼1.5 ps. Fig. 4A represents the spectral profile of a single lipid droplet within the sebaceous gland, identified by the OCT engine, embedded 50 μm in mouse ear tissue. Two red dotted lines indicate two different Raman shifts, 2760 cm−1 and 2860 cm−1, respectively. The images in Fig. 4C and D are acquired at these Raman shifts. Thus, our platform is not only capable of spatial discrimination, but also spectral discrimination. The Raman shift at 2860 cm−1 in Fig. 4D visualizes structures based on intrinsic vibrational properties without staining or labelling the specimen and reveal the lipid distribution in the CH stretching region, while the Raman shift at 2760 cm−1 shows the off resonant contribution of the sebaceous gland and enhances the surrounding medium as visualized in Fig. 4C. The intensity profiles (red and blue) shown in Fig. 4B correspond to the yellow dotted lines in the on (Fig. 4D) and off (Fig. 4C) resonant images and reveal the local distribution of the lipid droplets, on and off resonance, within the sebocytes. Especially the red profile reveals the location of lipid droplets (LDs) within the sebocytes, the cell membrane (M), nuclei (N) and hair shaft (F).
Fig. 3 Epi-detected multimodal NLOI images of a sebaceous gland. (A) Elastin and (B) collagen content of the ECM supporting the gland visualized through TPEF and SHG, respectively; (C) lipid content of the gland imaged by CARS where it is possible to identify the sebocytes’ membranes (M) and nuclei (N) and as well the location of the follicle (F). (D) Merged image of (A), (B) and (C) showing the complementary information provided by TPEF, SHG and CARS.
Fig. 4 Contrast equalized hyperspectral CARS images of a sebaceous gland identified by the OCT engine 50 μm deep into tissue at different Raman shifts. (A) Spectral profile of a single lipid droplet within a sebocyte. The hyperspectral scan is superimposed by the location of two specific shifts (2760 cm−1 (off resonance), 2860 cm−1 (on resonance)) indicated with red dotted lines. (B) The intensity profiles (red (on resonance), and blue (off resonance)) correspond to the yellow dotted lines in (C) and (D) revealing the local distribution of the cell membranes (M), nuclei (N), lipid droplets (LDs) and hair shafts (F). (C) Off resonance image at a Raman shift of 2760 cm−1 highlighting the sebaceous gland surrounding structure. (D) On resonance image at a Raman shift of 2860 cm−1 highlighting the lipid content within the sebaceous gland.
An epi-detected hyperspectral microscope based on an ultra-fast Ti:sapphire laser is an ideal platform providing structural, molecular and biochemical information with high sensitivity and specificity. In biomedical imaging applications, however, imaging speed is also very important. As we demonstrate in this work, the integration of OCT and NLOI into a LSM with ultra-fast Ti:sapphire lasers provides fast structural ultra-high resolution wide-field pre-screening to localize specific ROIs and zoom into the structure, function and metabolism of biological tissue on a cellular level with high contrast in a non-contact and non-destructive endogenous manner where no stains are required to enhance the contrast. Hence, the specimen does not suffer from perturbation by dye or photo-bleaching.
Current limited penetration offered by standard microscopy techniques is overcome with OCT allowing for deeper tissue interrogation for in situ cell-based imaging approaches and not only surface scanning determination. Particularly interesting areas can be correlated with label-free molecular biomarkers that can be instantaneously interpreted. TPEF, SHG and spectral focusing CARS imaging is integrated into a LSM and OCT is added to obtain complementary structural and functional information within tissue samples and cells. The potential of the platform is demonstrated in an established animal model. One significant difference compared with previous combined methods is that this device intrinsically has the multi-functionalities of OCT and OCM adding highly specific molecular and spectroscopic information with spectral focusing CARS on a cellular level. Overall integration of all the complementary modalities offers the opportunity to non-destructively and partly simultaneously investigate the structure, molecular distribution and function of biological tissue in three dimensions and in real-time with isotropic micron-scale resolution in a label-free manner. The current limitations of our systems are that the co-localisation is done only optically, there is no registration based feedback system, and that the flipping mirror prevents simultaneous acquisition of OCT and NLOI. These drawbacks can be overcome by integration of an automatic feedback system interfacing the stage and scanner control as well as the implementation of a beam combiner. Hence, our platform can potentially address a wide variety of unmet clinical needs for disease detection and localization by providing a wealth of intrinsic molecular and morphological information quickly and with high sensitivity and specificity. Due to the modular concept, our proposed system can also be interfaced to commercial LSM systems and could be used in conjunction with super-resolution methods including structured illumination or Airyscan. We hope that our contribution is a step further to shift the current gold standard of histopathology and adopt a new paradigm of in vivo molecular histopathology – truly enacting the concept of optical biopsy.
This work was supported by the European Union's Horizon 2020 research and innovation programme (MIB H2020-PHC-2015-two-stage and MOON H2020-ICT-2016-1) under grant agreement No. 667933 and 732969. The author M. T. E. has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 721766. The authors acknowledge the contribution of Tuan Le from Medical University of Vienna for technical assistance with the light sources.
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