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A novel tri-modal microscope combining optical coherence tomography (OCT), spectrally encoded confocal microscopy (SECM) and fluorescence imaging is presented. This system aims at providing a tool for rapid identification of head and neck tissues during thyroid surgery. The development of a dual-wavelength polygon-based swept laser allows for synchronized, co-registered and simultaneous imaging with all three modalities. Further ameliorations towards miniaturization include a custom lens for optimal compromise between orthogonal imaging geometries as well as a double-clad fiber coupler for increased throughput. Image quality and co-registration is demonstrated on freshly excised swine head and neck tissue samples to illustrate the complementarity of the techniques for identifying signature cellular and structural features.
© 2016 Optical Society of America
1. Introduction
Intraoperative tissue identification is standard practice in head and neck surgeries, especially during total or partial removal of the thyroid gland, a procedure called thyroidectomy. Thyroid is one of the largest endocrine gland of the human body. Located in the neck below the thyroid cartilage, it is typically covered by a thin fibrous capsule, to which are often attached the small-sized (3-4 mm in diameter) parathyroid glands. These glands regulate calcium concentration in the body and are typically located at each corner of the thyroid gland, with left-right symmetry, although their precise location and number (4 on average) varies from one individual to another [1].
Partial or total thyroidectomy is the recommended choice of treatment for most of the malignant or suspicious thyroid diseases and for some benign cases [2,3]. While thyroidectomy is considered a safe surgery, complications may arise. Inadvertent removal of or damage to the parathyroid is the most common complication, with iatrogenic removal ranging from 9 to 21% of cases [4]. Inadvertent damage is harder to quantify, but studies relate transient or permanent hypocalcaemia to damage to, and/or removal of, parathyroid glands. From retrospective studies, persistent hypocalcaemia has been observed in 0.5 to 4% [5] of patients undergoing total thyroidectomy, while transient hypocalcaemia is more common, with numbers ranging from 5.4 to 20% [5]. Severe postoperative hypocalcemia translates into a prolonged hospitalization and heavier economic burden. All these studies suggest careful dissection and examination of the thyroid capsule and gland in order to identify and preserve parathyroid glands during the operative procedure. Unfortunately in some cases, parathyroid glands can be embedded within the thyroid, increasing the risk of inadvertent removal during total thyroidectomy. A significant number of these could be prevented with a dedicated tool for examination of the thyroid capsule and surrounding tissues intra-operatively [6].
Intraoperative tissue identification is typically performed by frozen section biopsy [7]. This procedure allows rapid histological examination of fresh samples to be performed under a microscope. It is faster than conventional paraffin-embedded histopathology, which usually takes up to one day. It is performed on a biopsy sample frozen in liquid nitrogen before being cut in ~5 µm slices and stained for examination by a pathologist with a wide-field microscope. This procedure takes up to 20 minutes, but is less reliable than conventional histopathology [8]. Additionally, since a frozen section relies on imaging a very small sample of a larger gland, sampling errors can lead to false negative diagnoses. Multiple frozen section biopsies may also be required to obtain a satisfying diagnosis or identification. While frozen section is more sparsely used for thyroidectomy, a significant amount of time and money could be saved with a dedicated tool capable of rapidly identifying tissues with great accuracy. If these procedures were replaced with minimally invasive optical techniques that do not require tissue slicing, results could be obtained in vivo and in real time.
We herein investigate techniques for rapid intra-operative tissue identification using a combination of optical imaging modalities allowing for the visualization of microscopic features in real time and minimally invasively, but without the burden associated with the sampling–based time-consuming frozen section examination.
While frozen section relies on microscopic inspection of the tissue of interest, optical imaging modalities may provide similar information, without tissue resection or degradation. Candidates for real-time tissue identification include reflectance confocal microscopy (RCM) [9], optical coherence tomography (OCT) [10,11] and fluorescence imaging [12,13]. Identification of parathyroid glands requires distinguishing its key histological features from that of neighboring glands and tissues including: thyroid, lymph node, adipose and connective tissues. Table 1 summarizes these three imaging modalities and how accurately relevant neck tissue samples can be identified qualitatively. The + and – signs indicate how adequate a modality is at identifying key features of a particular tissue type and at differentiating it from others.
Table 1. Imaging modalities applied to neck tissue
Certain requirements need to be met for an instrument to be clinically relevant. One of the main requirements is to image sufficiently fast to avoid motion artifacts. Size can also be a constraint, thus small footprint scanning mechanisms are favorable. When possible, changing a distal scanning mechanism in a proximal scanning mechanism can also improve the odds of success in a clinical setting.
RCM [22] provides en-face images at cellular resolution using optical sectioning. Typical lateral resolution is on the order of 1 µm, with a depth resolution of a few microns (~5 µm). The field of view is approximately hundreds of microns wide with a penetration depth of up to 300 µm [9] depending on tissue and wavelength. To ease its use in a clinical setting, we opted for a spectrally encoded implementation of RCM, named spectrally encoded confocal microscopy (SECM) [23]. In this implementation the fast scanning mechanism is replaced with a wavelength swept laser and a grating, removing one distal mechanical scanning mechanism.
On the other hand, OCT provides cross-sectional images, with a lateral resolution of about 20 µm and a depth resolution of approximately 10 µm. The field of view is larger, typically a few millimeters, with a penetration depth of 1 to 3 mm depending of tissue. Its fast imaging speed allows for comprehensive volumetric imaging. OCT can also be performed with a light source based on a wavelength-swept laser [24].The combination of OCT and RCM has already been demonstrated on gastro-intestinal (sequential acquisition) [25] and skin burn lesion assessment (simultaneous acquisition) [26]. Recently, autofluorescence of some neck structures has been observed near 800 nm, with excitation at 785 nm and with higher signal for parathyroid with an emission peaking at 820 nm [14]. Thyroids appear to be barely autofluorescent, while other tissues are not at all, thus potentially providing additional specificity. While RCM can provide images with resolutions on the same scale as frozen section histology, it lacks penetration depth to see through the thyroid capsule. It also has a small field of view, leading to sampling errors when imaging heterogeneous areas. OCT, on the other hand, has a greater penetration depth, an intrinsic cross-sectional point of view, but lacks the higher resolution of microscopy techniques or the specificity of molecular contrast. Fluorescence offers a different contrast mechanism that can be implemented in a wide-field imaging system, or a in a point measurement system. This contrast can potentially be more specific and in a smaller footprint instrument.
In this article, we demonstrate a tri-modal imaging system based on a dedicated wavelength-swept laser optimized for simultaneous OCT, SECM and spectrally encoded fluorescence imaging (SEFI). Demonstration of this imaging system was performed quantitatively on standard resolution targets, and qualitatively on ex vivo samples of head and neck tissues.
2. Methodology
In this section we describe the tri-modal microscope. We first present the dual-band wavelength-swept laser for simultaneous OCT and SECM at 1300 nm and 780 nm, respectively. We then present the benchtop tri-modal microscope, as a combination of three imaging sub-systems: OCT, SECM and SEFI. All three sub-systems are merged through the same objective lens to allow for co-registration. We finally present three improvements to the benchtop implementation that facilitates clinical translation and handheld probe development.
2.1 Dual-band wavelength-swept laser
Figure 1 shows a schematic of the dual-band wavelength-swept laser and the corresponding output spectra. It consists of two polygon-based wavelength-swept filters [24] coupled to two laser cavities. Two facets of the same rotating polygon scanner are used to provide synchronized wavelength scanning, with wavelength bands specifically chosen for this application. A similar source was previously reported by [27] albeit at different wavelengths and using different cavity configurations. The first laser is made of a ring-fiber cavity and consists of a booster optical amplifier (BOA, Covega, BOA-4892) with gain centered at 1300 nm and 70 nm 3-dB bandwidth. A 60/40 fiber optic coupler is used for the laser output, extracting 40% of intra-cavity light. An optical circulator is used to send light to the rapid wavelength tunable filter. A second BOA (Covega, BOA-6170) (not shown) is used to increase source stability and to reach a maximum output power of 33 mW. Instantaneous coherence length is approximately 6 mm, measured as the full-width half maximum of the autocorrelation.
Fig. 1 Schematic diagram of the dual band wavelength-swept laser. A detailed diagram of the dual band laser (a) shows the 1310 nm OCT laser in red and the 780nm laser for SECM in blue. Output spectra are shown at 1300nm (b) and 800nm (c). (d) 780 nm (blue), 1310 nm (red) laser and trigger (green) signals as a function of time.
The second laser cavity at 780 nm was previously published in [28]. It consists of a Sacher LaserTechnik 780 nm external-cavity laser diode, with a 3-dB bandwidth of 30 nm. The diode cavity was modified to allow wavelength dispersion by a diffraction grating and selection by the polygon scanner. Maximum output power is 110 mW, but due to beam ellipticity, a maximum of 35 mW was coupled into a single mode fiber to reach the imaging system.
Synchronized wavelength sweep is achieved by using the same polygon scanner for both wavelength bands. Each laser cavity has a separate optical fiber output. With careful alignment, the delay between both scans can be adjusted to have both scans start at the same time. This also eliminates the need for doubling the acquisition trigger setup. Figure 1(b) and 1(c) show spectra of the 1310 nm and the 780 nm, respectively. Figure 1(d) shows the linear scale output of each laser (red and blue lines, respectively) with the trigger signal (green) as a function of time. Polygon rotating speed was chosen to provide 12,000 spectra per second. Speed can be increased to over 30,000 spectra per second where faster imaging speed is required. Curves were offset and amplitude-adjusted for visibility purposes.
2.2 Benchtop multimodal optical microscope
Figure 2 shows a schematic diagram of the co-registered tri-modality microscope exploiting the dual-band wavelength-swept laser. The two different wavelengths take different paths and are combined near the objective lens for simultaneous imaging. Light from the 780 nm laser is used for confocal microscopy to provide high resolution from a shorter wavelength and to excite near-infrared fluorescence. The 1310 nm band is used for OCT to benefit from increased penetration depth.
Fig. 2 Schematic diagram of the tri-modal imaging microscope. The OCT path (1300nm) is shown in red, the SECM path (800nm) is shown in blue and the fluorescence detection path is shown in green. C: Circulator, G: Galvanometer-mounted mirror, DB: Dual-balanced detector, Obj.: Objective lens, PD: Photodiode, BD: Beam dump, sDCFC: small inner cladding double-clad fiber coupler, APD: Avalanche photodiode, SMF: single mode fiber, MMF: multimode fiber
The blue path represents 780 nm light used for SECM imaging and fluorescence. Light from the 780 nm laser output is connected to a small-ratio double-clad fiber coupler [29] allowing for single-mode illumination and multi-mode detection The imaging fiber output is then connected to the collimator of the SECM imaging arm. Slow axis scanning is performed with a galvanometer-mounted mirror while a transmission diffraction grating (1800 l/mm, Wasatch Photonics) combined with the wavelength sweep of the source serves as fast axis scanning. Telecentric telescopes are used to magnify the beam and relay the scanning to the objective lens. A dichroic mirror (LWP-45-RU780-TU1250-PW-1025-C, CVI Melles-Griot) is used to reflect the SECM laser beam towards the objective lens.
Fluorescence at 800 nm can be detected on the setup with minor modification of the SECM arm based on previous work [28]. The fluorescent light passes through the diffraction grating and is deviated at a greater angle due to the Stokes shift. This light is collected by an off-axis parabolic mirror and focused on a silicon avalanche photodiode (APD110A, Thorlabs) by an achromatic doublet. Two long-pass filters (ET810LP, Chroma) were used to reject ambient and laser light.
Light from the 1310 nm band is represented in red in Fig. 2. The laser beam is sent through a 90/10 coupler (not shown) to trigger acquisition for both wavelengths. The trigger consists of a fixed wavelength filter formed by a diffraction grating (GR13-1210, Thorlabs) and a mirror. The remaining 90% of the laser is split again in two arms of the interferometer. 1% of the signal is sent to the reference arm, as the 99% remaining is going through the OCT imaging arm. The imaging arm consists of 5 mm focal length collimator (Thorlabs), a galvanometer mounted mirror and a telecentric telescope. The dichroic mirror transmits a large wavelength band centered at 1310 nm. An optical circulator is used in both arms to connect the input coupler to the interference coupler (50/50). A dual-balanced detector (PDB420C, Thorlabs) detects the resulting interference signal.
Signal acquisition and processing was performed on custom C++ software controlling a high-speed DAQ board (ATS9440, AlazarTech). OCT signal is interpolated to be linear in wavenumber (k) [30]. The source spectrum is then divided and a Hanning window is applied to reduce spectral leakage. Fast Fourier Transform (FFT) is finally applied to obtain the depth reflectivity profile. Images are displayed in real-time at more than 10 frames per second (fps).
2.3 Towards a hand-held device
Technological improvements were developed towards translating this tri-modality system towards the operating room. The first is spectral encoding as the fast axis scanning mechanism for the confocal imaging sub-system. Spectrally encoded confocal microscopy [23] was shown to allow rapid imaging [31] of large FOVs [32], while being miniaturizable for endoscopic use [33]. This paper presents the first swept-source implementation of SECM at 800nm to allow for simultaneous reflectance and fluorescence based imaging.
The second improvement is the incorporation of a small inner-cladding double-clad fiber coupler (sDCFC) for higher collection efficiency and reduced speckle noise for the confocal sub-system. The sDCFC is an all-fiber device made of a small inner-cladding double-clad fiber (sDCF) and a highly multimode fiber. The fabrication and characterization of such device, as well as the proof-of-principle for optical sectioning are presented in [29]. This coupler transmits light injected into the single-mode core quasi-losslessly to the imaging port of the coupler. Light backscattered from the sample is coupled to the small inner cladding, which behaves as the traditional detection pinhole. Light traveling in the inner cladding is extracted from the double clad fiber and transferred to the highly multimode fiber to get to the confocal detector. Such coupler allows for a significant increase in signal detected and a substantial decrease in speckle contrast. From a clinical point of view, this coupler replaces a beam splitter, adding mechanical stability and ease of alignment. These advantages lead to ease of use and reduced downtime between imaging sessions, which are valuable in a clinical setting.
The third improvement is a custom made and designed objective lens for efficient combination of OCT and confocal microscopy. A custom objective lens is a key component in this system as the combination of the requirements for OCT imaging and confocal imaging are very different. A Hasting’s triplet was especially designed for confocal operation in the 780 nm range and OCT operation centered at 1310 nm. The final lens is 8 mm in diameter with a focal length of 10 mm and allows for a field of view of 500 µm for the confocal sub-system and a numerical aperture of 0.3 as well as field of view of 2.5 mm for the OCT sub-system and a numerical aperture of 0.05. The design and characterization of this lens will be detailed in a future article.
3. Results
3.1 Characterization of the tri-modality imaging system
In this section, we present the imaging performances of the tri-modal system. The field-of-view, lateral resolution and axial resolution are described for the OCT and confocal modalities.
Characterization of the reflectance performance of the system (SECM and OCT) was performed on a USAF 1951 resolution target. The 10%-90% edge response criterion is used to measure lateral resolution. En-face imaging is obtained in OCT by scanning the resolution target with a translating stage. Axial resolution is measured in SECM by axially scanning a mirror and taking the full width at half maximum (FWHM) of the resulting intensity profile. Axial resolution in OCT was measured on a custom-made phantom and uses the FWHM criteria. Table 2 presents the resolution values based on the images presented in Fig. 3. Co-registration was measured and adjusted using the corner of a square mirror. Translation of the mirror allowed for field of view measurements in both modalities. Theoretical values are presented for comparison.
Table 2. Theoretical and experimental resolution values for the tri-modal imaging system
Fig. 3 SECM (a) and OCT (b) images of a USAF 1951 resolution target. Co-registered images (c) of SECM (grey) and fluorescence (green) of three sewing threads dipped in AlexaFluor 790 at different concentrations: (from left to right) 0 µMol, 6.5 µMol and 65 µMol fluorophore concentration. Scale bar is 50 µm. Co-registered in vivo SECM (d) and OCT (e) images of a human finger. Features such as a sweat duct (arrow) can be observed in both images. The red line in (d) represents the projection of the OCT image plane in the confocal image. The blue line in (e) represents the projection of the confocal image in the OCT plane. Arrows show a sweat duct. Scale bar is 100 µm.
Figure 3(a) and 3(b) show a USAF1951 resolution target in SECM and OCT, respectively. A 3D volume was acquired in OCT by scanning the sample with a translation stage. Image distortion can be observed in the SECM image. Figure 3(c) shows an overlay of the confocal (gray) and fluorescence (green) images of three sewing threads where two have been dipped in fluorescent solutions of 6.5 µMol and 65 µMol respectively. One can notice the lack of optical sectioning in fluorescence imaging resulting in a seemingly imperfect registration between the confocal and fluorescence images. Figure 3(d)-3(e) show a SECM image (d) and an OCT image (e) of a finger pad of a volunteer. Colored lines represent the location of the perpendicular field of view of the complementary modality. A sweat duct (arrows) can be seen in both images, showing co-registration.
3.2 Ex vivo tissue imaging
This section presents results from ex vivo imaging performed on freshly excised swine neck tissue samples. Co-registered images are presented for different tissue types: thyroid, adipose, lymph node and parathyroid. A video recording of a typical imaging session is presented to show the ease of use of the system for ex vivo imaging. In addition, this video was recorded using a heterogeneous sample to simulate real per-operative conditions.
Figure 4 shows four different samples imaged with the tri-modality system. These ex vivo samples were taken in a swine model during necropsy where tissues were identified by an experienced veterinarian. Parathyroid localization procedure was based on [34].
Fig. 4 Images of different ex vivo neck tissue samples. The left and right columns show the SECM image and the center column shows the co-registered OCT image. The position of the SECM image in the OCT image is shown with the curly bracket ({) and black arrows. (a) and (b) show thyroid tissue, (c) and (d) show thyroid tissue, (e) lymph node (f) lymph node and adipose lobules, (g) parathyroid gland, cellular area, (h) parathyroid gland with heterogeneous aspect. OCT scale bars are 200 µm, SECM scale bars are 100 µm.
The left and right columns of Fig. 4 show SECM images (a, c, e, g) and center column the co-registered and simultaneously acquired OCT images (b, d, f, h). Thyroid tissue can be seen in (a) and (b), adipose tissue in (c) and (d), lymph node in (e) and (f), and parathyroid gland tissue in (g) and (h). The curly bracket in Fig. 4 represents the lateral position of the SECM image relatively to the OCT image. Arrows point at the corresponding depth where the SECM images are taken on the OCT images. Tissue identification was confirmed post-imaging with frozen section histology by a pathologist.
Some of the key features of each tissue type as highlighted by Table 1 can be observed on the results of Fig. 4. In Fig. 4(a)-4(b), for both SECM and OCT images, thyroid follicles can be seen as oval, hypoechoic, empty-looking structures, surrounded by a bright epithelial lining in a honeycomb-like pattern. Figure 4(c) shows bright, round, solid lobules of adipocytes, fairly uniform in size and distribution in a mosaic pattern. OCT does not have a sufficient lateral resolution to resolve individual adipocytes and presents a more uniform signal with small brighter areas. This tissue type is very scattering and OCT signal is attenuated faster than other tissue types. Since fat has a higher index of refraction, intense light reflection is received from this tissue type, both in SECM and OCT. Lymph nodes consist of uniformly backscattering tissue in a diffuse pattern and the occasional adipose tissue inclusion as seen in SECM (Fig. 4(e)). This uniform signal is due to the structure of the lymph node, consisting of tightly packed lymphocytes. This uniform signal is also seen in OCT, with less attenuation than adipose tissue. Parathyroid gland tissue is composed of glandular cells in clusters and fat cells, the proportion of fat increasing with age. While glandular cell clusters cannot be clearly distinguished in SECM (Fig. 4(g)), regions rich in stromal fat can be seen, represented by bright round structures. In Fig. 4(h), the heterogeneous texture of the parathyroid is a mixture of irregular size and shape areas of tissue resembling adipose tissue and interspersed areas (especially the right section of the image) with a different, more diffuse attenuation profile. Again, in human tissue, the parathyroid adipose contents will vary with age, body weight, pathological conditions (such as renal failure), etc.
An example of a very heterogeneous sample is presented in Fig. 5 where a fibrous/fatty capsule is located above the thyroid tissue. In this case, the confocal imaging sub-system cannot image deep enough to display the thyroid tissue underneath the capsule, but the OCT sub-system shows the representative structure of thyroid follicles. This video demonstrates the ease of use of the imaging system, as the user places the sample directly into contact with the objective lens for real time simultaneous and co-registered imaging. Aspect ratios of images were modified to better fit in the video. Video frame rate was slowed down to 7 fps, from 10 fps, to better assess the visible structures in the sample.
Fig. 5 Still frame from the video recording of an ex vivo thyroid tissue sample covered by a fibrous capsule. On the left is presented the SECM image and on the right the co-registered OCT image.
No fluorescence signal was detected while scanning several thyroid and parathyroid glands. We further attempted to record fluorescence using a four fiber optic probe [35] with a spectrometer (Maya 2000 Pro, Ocean Optics, USA) and a 100 mW, 785 nm laser diode. The same filters from the setup were used for laser-light rejection. The protocol used was similar to what is reported in [13] albeit on ex vivo swine tissue. No signal was measured with this probe either.
4. Discussion
In this paper, we investigate a novel technique for rapid intra-operative identification of tissue. Frozen section histology provides high contrast and high resolution of a thin slice of the sample, at the cost of tissue fixation, slicing and staining prior to analysis. The surgeon obtains the identification of the tissue tens of minutes later. Our approach allows for rapid identification of fresh tissue intra-operatively. While contrast, resolution or penetration depth may not be as high, images show clear distinction between the four tissue types to enable fast recognition. Feedback can be given to the surgeon within a few minutes. In some cases, additional frozen sections may still be required to ascertain the result given by the optical probe or allow the screening of structures deeper than a few millimeters, but the probe could shorten the procedure in many cases. Distinguishing healthy and pathological specimens requires additional research beyond the scope of this paper.
The reported tri-modality imaging system combines SECM for microscopic scale real-time tissue assessment, OCT for in-depth morphological tissue identification and fluorescence imaging for a molecular and specific identification of parathyroid. The combination of these three imaging modalities allows for multi-scale optical imaging using orthogonal field of views. The complementarity of the three techniques is relevant for functional and morphological contrast. This synergistic combination is well suited for head and neck tissue identification, as some tissue may look similar under the same imaging modality.
For example, adipose tissue, lymph node and parathyroid gland may look qualitatively similar in OCT (Fig. 4(d), 4(f), and 4(h)), but images in RCM (Fig. 4(c), 4(e), and 4(g)) show distinctive features for each tissue type. RCM (or SECM) does present some difficulties for use in ex vivo or in vivo imaging, mostly due to the limited penetration depth. In our setup, penetration depth is fixed by the imaging window, facilitating the positioning of the sample at the focal plane of the objective lens. This may result in incorrect tissue identification with tissue sample covered by adipose tissue or a connective tissue capsule, as can be seen in Fig. 5. However, the combination with OCT allows for observation of tissue heterogeneities and the determination that the image in RCM is not a representative sample of the tissue.
The dual-band wavelength-swept laser offers adequate power (over 30 mW at each output) at a scanning rate of 12 kHz, which can be increased up to 30 kHz. The limit in scanning speed is dictated by the settings of the polygon. However, vibrations and increased air flow cause instability in the laser output signal at speeds of 30 kHz (50,000 rpm). Recent articles have shown schemes for increasing the laser scanning rate without increasing the polygon rotation speed [36]. Even if only half of the 6 mm a coherence length of the 1310 nm laser can be used in our OCT implementation, it should not limit the penetration depth in our application where sample attenuation is the main limiting factor. If required, several techniques could be implemented to remove depth degeneracy [37–39] and thus use all the coherence length.
Imaging with an sDCFC in SECM presents several advantages: increased signal intensity, reduced speckle contrast and auto-alignment. This comes at the cost of a factor of 2 in axial resolution due to the larger effective pinhole. In the context of imaging biological samples, the benefits outweigh the limitations, as was previously shown [29,40]. A greater numerical aperture could be used to obtain the desired lateral and axial resolutions if the need for better resolution arises.
Image distortion can be observed in the SECM images, most notably on the resolution target image presented in Fig. 3(a). This distortion is due to the interaction between the diffraction grating and the galvanometer scan. Using conical diffraction formalism [41], it is possible to show that the diffracted beam direction not only depends on the beam wavelength but also on the galvanometer scan angle. Because this is fixed, and not dependent of the objective lens, it could be corrected using post-processing. Discrepancies between theoretical and experimental values for axial and lateral resolutions can be explained by a slight under-filling of the objective lens pupil.
While SEFI provides an interesting, more functional contrast in regard to the morphological information collected with SECM and OCT, some limitations must be mentioned. This imaging scheme provides a non-uniform illumination along the spectral axis, in addition to the non-uniform response of the fluorophores to different excitation wavelengths. This leads to images that are difficult to interpret and quantitatively analyze. However, in the context of parathyroid identification, the aim here is to detect parathyroid glands which would exhibit a much larger signal than surrounding tissues. SEFI images could be interpreted in this context as a binary map of fluorescence presence. Human parathyroid glands are also typically larger than the field of view in SECM and SEFI, therefore non-uniform illumination would be a minor issue.
We are still investigating on the lack of autofluorescence signal from our ex vivo swine tissue samples. The molecule responsible for autofluorescence is still unknown, and since reported measurements have been performed on human patients, in vivo, it is possible that ex vivo swine samples do not exhibit, or exhibit a much weaker, fluorescence signal. We are moving our setup to a hospital to acquire images from freshly excised human tissues. We are also working on miniaturizing the setup into a handheld probe for in vivo measurements on human patients.
Imaging performances of a clinically compatible tri-modality system were demonstrated, leveraging from three technological improvements. A dedicated dual-color wavelength-swept laser allows combining OCT, SECM and fluorescence detection for rapid, synchronized, co-registered imaging. The DCFC with a small inner cladding specially designed for confocal applications at 780 nm paves the ways towards clinical applications since it allows for higher signal collection, reduction of speckle contrast and increased mechanical stability. Auto-alignment of the confocal pinholes decrease down-time due to alignment. Additionally, the contact window of the custom objective lens permits tissue placement, which is furthermore facilitated by the co-registered OCT cross-sectional imaging. With a mostly fiber-based setup coupled to a contact objective lens, this imaging scheme is a step closer to a hand-held probe for rapid intra-operative tissue identification. This is made easier with only one slow scanning mechanism necessary for both modalities. The dual-band laser can be packaged on a medical cart for easy transportation. This system coupled to an imaging probe will allow in situ neck tissue imaging.
5. Conclusion
We demonstrated a tri-modal imaging system based on a dedicated wavelength-swept laser optimized for simultaneous OCT, SECM and spectrally encoded fluorescence imaging. This system is designed for head and neck tissue identification and can be translated from bench top microscope to a handheld probe. Such probe could be used in vivo within the surgical field for live and real-time tissue assessment. This could translate into shorter operative times and less postoperative complications. Future work includes ex vivo tissue identification and development of a hand-held probe for in vivo experiments during thyroidectomies or similar procedures.
Acknowledgment
Authors would like to gratefully acknowledge Prof. Frédéric Leblond and his team for the fluorescence probe and help with fluorescence data processing, Fouzi Benboujja for fruitful discussions, and Hélène Héon and Maryse Boulay for help with the swine tissue excision. This work was supported by an NSERC grant.
References and links
1. D. Linos and W. Y. Chung, Minimally Invasive Thyroidectomy (Springer, 2012).
2. E. I. Efremidou, M. S. Papageorgiou, N. Liratzopoulos, and K. J. Manolas, “The efficacy and safety of total thyroidectomy in the management of benign thyroid disease: a review of 932 cases,” Can. J. Surg. 52(1), 39–44 (2009). [PubMed]
3. I. Vassiliou, A. Tympa, N. Arkadopoulos, F. Nikolakopoulos, T. Petropoulou, and V. Smyrniotis, “Total thyroidectomy as the single surgical option for benign and malignant thyroid disease: a surgical challenge,” Arch. Med. Sci. 1(1), 74–78 (2013). [CrossRef] [PubMed]
4. A. Manouras, H. Markogiannakis, E. Lagoudianakis, P. Antonakis, M. Genetzakis, A. Papadima, E. Konstantoulaki, D. Papanikolaou, and P. Kekis, “Unintentional parathyroidectomy during total thyroidectomy,” Head Neck 30(4), 497–502 (2008). [CrossRef] [PubMed]
5. T. E. Rix and P. Sinha, “Inadvertent parathyroid excision during thyroid surgery,” Surgeon 4(6), 339–342 (2006). [CrossRef] [PubMed]
6. R. S. Sippel, O. Ozgül, G. K. Hartig, E. A. Mack, and H. Chen, “Risks and consequences of incidental parathyroidectomy during thyroid resection,” ANZ J. Surg. 77(1-2), 33–36 (2007). [CrossRef] [PubMed]
7. E. Brender, A. Burke, and R. M. Glass, “Frozen section biopsy,” JAMA 294(24), 3200 (2005). [CrossRef] [PubMed]
8. L. J. DiNardo, J. Lin, L. S. Karageorge, and C. N. Powers, “Accuracy, utility, and cost of frozen section margins in head and neck cancer surgery,” Laryngoscope 110(10), 1773–1776 (2000).
9. J. B. Pawley, and B. R. Masters, Handbook of Biological Confocal Microscopy, 2nd ed. (Springer, 1996).
10. D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, and C. A. Puliafito, “Optical coherence tomography,” Science 254(5035), 1178–1181 (1991). [CrossRef]
11. S. Yuan, C. A. Roney, J. Wierwille, C.-W. Chen, B. Xu, J. Jiang, H. Ma, A. Cable, R. M. Summers, and Y. Chen, “Combining optical coherence tomography with fluorescence molecular imaging: towards simultaneous morphology and molecular imaging,” Phys. Med. Biol. 55(1), 191–206 (2010). [CrossRef] [PubMed]
12. J. V. Frangioni, “In vivo near-infrared fluorescence imaging,” Curr. Opin. Chem. Biol. 7(5), 626–634 (2003). [CrossRef] [PubMed]
13. E. A. te Velde, T. Veerman, V. Subramaniam, and T. Ruers, “The use of fluorescent dyes and probes in surgical oncology,” Eur. J. Surg. Oncol. 36(1), 6–15 (2010). [CrossRef] [PubMed]
14. C. Paras, M. Keller, L. White, J. Phay, and A. Mahadevan-Jansen, “Near-infrared autofluorescence for the detection of parathyroid glands,” J. Biomed. Opt. 16(6), 067012 (2011). [CrossRef] [PubMed]
15. M. A. McWade, C. Paras, L. M. White, J. E. Phay, A. Mahadevan-Jansen, and J. T. Broome, “A novel optical approach to intraoperative detection of parathyroid glands,” Surgery 154(6), 1371–1377 (2013). [CrossRef] [PubMed]
16. W. M. White, M. Baldassano, M. Rajadhyaksha, S. Gonzalez, G. J. Tearney, R. R. Anderson, and R. L. Fabian, “Confocal reflectance imaging of head and neck surgical specimens. A comparison with histologic analysis,” Arch. Otolaryngol. Head Neck Surg. 130(8), 923–928 (2004). [CrossRef] [PubMed]
17. L. C. Conti de Freitas, E. Phelan, L. Liu, J. Gardecki, E. Namati, W. C. Warger, G. J. Tearney, and G. W. Randolph, “Optical coherence tomography imaging during thyroid and parathyroid surgery: A novel system of tissue identification and differentiation to obviate tissue resection and frozen section,” Head Neck 36(9), 1329–1334 (2014). [PubMed]
18. L. Pantanowitz, P.-L. Hsiung, T. H. Ko, K. Schneider, P. R. Herz, J. G. Fujimoto, S. Raza, and J. L. Connolly, “High-resolution imaging of the thyroid gland using optical coherence tomography,” Head Neck 26(5), 425–434 (2004). [CrossRef] [PubMed]
19. C. Zhou, Y. Wang, A. D. Aguirre, T.-H. Tsai, D. W. Cohen, J. L. Connolly, and J. G. Fujimoto, “Ex vivo imaging of human thyroid pathology using integrated optical coherence tomography and optical coherence microscopy,” J. Biomed. Opt. 15(1), 016001 (2010). [CrossRef] [PubMed]
20. W. M. White, G. J. Tearney, B. Z. Pilch, R. L. Fabian, R. R. Anderson, and R. D. Gaz, “A novel, noninvasive imaging technique for intraoperative assessment of parathyroid glands: confocal reflectance microscopy,” Surgery 128(6), 1088–1101 (2000). [CrossRef] [PubMed]
21. C. Boudoux, “Wavelength swept spectrally encoded confocal microscopy for biological and clinical applications,” Ph.D. Thesis, Massachusetts Institute of Technology, (2007).
22. M. Rajadhyaksha, S. González, J. M. Zavislan, R. R. Anderson, and R. H. Webb, “In vivo confocal scanning laser microscopy of human skin II: advances in instrumentation and comparison with histology,” J. Invest. Dermatol. 113(3), 293–303 (1999). [CrossRef] [PubMed]
23. G. J. Tearney, R. H. Webb, and B. E. Bouma, “Spectrally encoded confocal microscopy,” Opt. Lett. 23(15), 1152–1154 (1998). [CrossRef] [PubMed]
24. S. Yun, G. Tearney, J. de Boer, N. Iftimia, and B. Bouma, “High-speed optical frequency-domain imaging,” Opt. Express 11(22), 2953–2963 (2003). [CrossRef] [PubMed]
25. D. K. Kang, M. J. Suter, C. Boudoux, P. S. Yachimski, W. P. Puricelli, N. S. Nishioka, M. Mino-Kenudson, G. Y. Lauwers, B. E. Bouma, and G. J. Tearney, “Co-registered spectrally encoded confocal microscopy and optical frequency domain imaging system,” J. Microsc. 239(2), 87–91 (2010). [PubMed]
26. N. Iftimia, R. D. Ferguson, M. Mujat, A. H. Patel, E. Z. Zhang, W. Fox, and M. Rajadhyaksha, “Combined reflectance confocal microscopy/optical coherence tomography imaging for skin burn assessment,” Biomed. Opt. Express 4(5), 680–695 (2013). [CrossRef] [PubMed]
27. Y. Mao, S. Chang, E. Murdock, and C. Flueraru, “Simultaneous dual-wavelength-band common-path swept-source optical coherence tomography with single polygon mirror scanner,” Opt. Lett. 36(11), 1990–1992 (2011). [CrossRef] [PubMed]
28. M. Strupler, N. Goulamhoussen, E. De Montigny, and C. Boudoux, “Rapidly Wavelength-Swept Laser at 780 nm,” IEEE Photon. Technol. Lett. 23(4), 197–199 (2011). [CrossRef]
29. E. De Montigny, W. J. Madore, O. Ouellette, G. Bernard, M. Leduc, M. Strupler, C. Boudoux, and N. Godbout, “Double-clad fiber coupler for partially coherent detection,” Opt. Express 23(7), 9040–9051 (2015). [CrossRef] [PubMed]
30. S. Vergnole, D. Lévesque, and G. Lamouche, “Experimental validation of an optimized signal processing method to handle non-linearity in swept-source optical coherence tomography,” Opt. Express 18(10), 10446–10461 (2010). [CrossRef] [PubMed]
31. C. Boudoux, S. Yun, W. Oh, W. White, N. Iftimia, M. Shishkov, B. Bouma, and G. Tearney, “Rapid wavelength-swept spectrally encoded confocal microscopy,” Opt. Express 13(20), 8214–8221 (2005). [CrossRef] [PubMed]
32. D. Yelin, C. Boudoux, B. E. Bouma, and G. J. Tearney, “Large area confocal microscopy,” Opt. Lett. 32(9), 1102–1104 (2007). [CrossRef] [PubMed]
33. D. Kang, R. W. Carruth, M. Kim, S. C. Schlachter, M. Shishkov, K. Woods, N. Tabatabaei, T. Wu, and G. J. Tearney, “Endoscopic probe optics for spectrally encoded confocal microscopy,” Biomed. Opt. Express 4(10), 1925–1936 (2013). [CrossRef] [PubMed]
34. T. Soshin, H. Takai, C. Kato, E. Fujii, S. Matsuo, T. Ito, and M. Suzuki, “A method for sampling and tissue preparation of the parathyroid glands in miniature pigs for toxicity studies,” J. Toxicol. Sci. 35(2), 235–238 (2010). [CrossRef] [PubMed]
35. A. Kim, M. Roy, F. Dadani, and B. C. Wilson, “A fiberoptic reflectance probe with multiple source-collector separations to increase the dynamic range of derived tissue optical absorption and scattering coefficients,” Opt. Express 18(6), 5580–5594 (2010). [CrossRef] [PubMed]
36. S. C. Schlachter, D. Kang, M. J. Gora, P. Vacas-Jacques, T. Wu, R. W. Carruth, E. J. Wilsterman, B. E. Bouma, K. Woods, and G. J. Tearney, “Spectrally encoded confocal microscopy of esophageal tissues at 100 kHz line rate,” Biomed. Opt. Express 4(9), 1636–1645 (2013). [PubMed]
37. S. Yun, G. Tearney, J. de Boer, and B. Bouma, “Removing the depth-degeneracy in optical frequency domain imaging with frequency shifting,” Opt. Express 12(20), 4822–4828 (2004). [CrossRef] [PubMed]
38. M. Sarunic, M. A. Choma, C. Yang, and J. A. Izatt, “Instantaneous complex conjugate resolved spectral domain and swept-source OCT using 3x3 fiber couplers,” Opt. Express 13(3), 957–967 (2005). [CrossRef] [PubMed]
39. R. K. Wang, “In vivo full range complex Fourier domain optical coherence tomography,” Appl. Phys. Lett. 90(5), 054103 (2007). [CrossRef] [PubMed]
40. C. Glazowski and M. Rajadhyaksha, “Optimal detection pinhole for lowering speckle noise while maintaining adequate optical sectioning in confocal reflectance microscopes,” J. Biomed. Opt. 17(8), 085001 (2012). [CrossRef] [PubMed]
41. T. Antonakakis, F. Baïda, A. Belkhir, K. Cherednichenko, S. Cooper, R. Craster, G. Demesy, J. DeSanto, G. Granet, B. Gralak, S. Guenneau, D. Maystre, A. Nicolet, B. Stout, F. Zolla, and B. Vial, Gratings : Theory and Numeric Applications (Marseille, 2014).
