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Improved middle-ear soft-tissue visualization using synchrotron radiation phase-contrast imaging
Accepted Manuscript Improved middle-ear soft-tissue visualization using synchrotron radiation phasecontrast imaging Mai Elfarnawany, Seyed Alireza Rohani, Soroush Ghomashchi, Daniel G. Allen, Ning Zhu, Sumit K. Agrawal, Hanif M. Ladak PII:
S0378-5955(17)30029-1
DOI:
10.1016/j.heares.2017.08.001
Reference:
HEARES 7408
To appear in:
Hearing Research
Received Date: 22 February 2017 Revised Date:
30 July 2017
Accepted Date: 2 August 2017
Please cite this article as: Elfarnawany, M., Rohani, S.A., Ghomashchi, S., Allen, D.G., Zhu, N., Agrawal, S.K., Ladak, H.M., Improved middle-ear soft-tissue visualization using synchrotron radiation phasecontrast imaging, Hearing Research (2017), doi: 10.1016/j.heares.2017.08.001. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Improved Middle-Ear Soft-Tissue Visualization Using Synchrotron Radiation Phase-Contrast Imaging
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Mai Elfarnawany1,§, Seyed Alireza Rohani2, Soroush Ghomashchi3, Daniel G. Allen3, Ning Zhu4, Sumit K. Agrawal1, 2, 3, 5,*, and Hanif M. Ladak1, 2, 3, 5,* 1
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Department of Otolaryngology-Head and Neck Surgery, Western University, London, ON, Canada 2 Biomedical Engineering Graduate Program, Western University, London, ON, Canada 3 Department of Medical Biophysics, Western University, London, ON, Canada 4 Bio-Medical Imaging and Therapy Facility, Canadian Light Source Inc., University of Saskatchewan, Saskatoon, SK, Canada 5 Department of Electrical and Computer Engineering, Western University, London, ON, Canada *co-senior authors
§ Corresponding author: Tel: (519)-661-2111 ext. 85683, Fax: (519)-661-2123, email:[email protected]
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Abstract High resolution images are used as a basis for finite-element modeling of the middle-ear structures to study their biomechanical function. Commonly used imaging techniques such as micro-computed tomography (CT) and optical microscopy require extensive sample preparation, processing or staining using contrast agents to achieve sufficient soft-tissue contrast. We compare imaging of middle-ear structures in unstained, non-decalcified human temporal bones using conventional absorption-contrast micro-CT and using synchrotron radiation phase-contrast imaging (SR-PCI). Four cadaveric temporal bones were imaged using SR-PCI and conventional micro-CT. Images were qualitatively compared in terms of visualization of structural details and soft-tissue contrast using intensity profiles and histograms. In order to quantitatively compare SR-PCI to micro-CT, three-dimensional (3D) models of the ossicles were constructed from both modalities using a semi-automatic segmentation method as these structures are clearly visible in both types of images. Volumes of the segmented ossicles were computed and compared between the two imaging modalities and to estimates from the literature. SR-PCI images provided superior visualization of soft-tissue microstructures over conventional micro-CT images. Intensity profiles emphasized the improved contrast and detectability of soft-tissue in SR-PCI in comparison to absorption-contrast micro-CT. In addition, the semi-automatic segmentations of SR-PCI images yielded accurate 3D reconstructions of the ossicles with mean volumes in accord with volume estimates from micro-CT images and literature. Sample segmentations of the ossicles and soft tissue structures were provided on an online data repository for benefit of the research community. The improved visualization, modeling accuracy and simple sample preparation make SR-PCI a promising tool for generating reliable FE models of the middle-ear structures, including both soft tissues and bone.
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Keywords: Micro-computed tomography, synchrotron radiation, phase-contrast imaging, middle ear, soft tissue, image segmentation
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Introduction
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Finite-element (FE) models are computational models used to simulate and understand the relationship between structure and function of modeled anatomies. FE models of the complex and small middle-ear bones and surrounding soft tissue have been used to study their biomechanical properties (Sun et al., 2002; Decraemer et al., 2003; Huber et al., 2003; Funnell et al., 2005; Homma et al., 2009; Chou et al., 2011; Gan et al., 2011; Zhang and Gan, 2011) and as modeling tools for improving and optimizing middle-ear prostheses (Kelly et al., 2003; Neudert et al., 2007; Gan et al., 2010). Constructing these computational models requires having accurate and realistic representations of the anatomical geometries of the modeled structures.
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Histological sectioning provides very high resolution anatomical representations, which can be used as the basis for FE modeling of the middle-ear structures (Funnell et al., 1992; Gan et al., 2002, 2004; Sun et al., 2002; Wang et al., 2007). However, challenges of histological sectioning include sample destruction, the risk of structural deformation and long processing time.
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Modern imaging modalities provide an alternative method to obtain anatomical and geometrical representations of the middle-ear structures while overcoming some of the challenges of histological sectioning. Clinical computed tomography (CT) can be used to acquire in-vivo images of the middle ear from patients. Clinical CT was previously used to derive models of the middle ear for finite-element analysis (Lee et al., 2006; Wen et al., 2006; Chou et al., 2011). However, clinical CT images are restricted by low spatial resolution and by radiation dose and exposure time when used to image patients, therefore limiting achievable image quality and contrast resolution. Micro-CT is more commonly used in obtaining models of the middle ear in human (Decraemer et al., 2003; Lane et al., 2004; Homma et al., 2009) and animal (Elkhouri et al., 2006; Tuck-Lee et al., 2008; Puria and Steele, 2010; Buytaert et al., 2011) temporal bones. Micro-CT is characterized by having micrometer-range resolution and the ability to increase beam intensities to improve image contrast. With its micrometer-range resolution, micro-CT is suitable for accurately imaging high-density tissue such as the ossicles and surrounding bone. However, it does not provide sufficient contrast resolution to easily visualize soft tissues such as the tympanic membrane, ligaments and muscles.
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A number of tissue staining agents have been proposed for contrast-enhancement of the middleear soft tissues when using micro-CT (Metscher, 2009). Phosphotungstic acid has been used to visualize middle-ear geometrical features and to create 3D surface models of the middle-ear soft tissues (Buytaert et al., 2014; De Greef et al., 2015). Iodine potassium iodide was reported to result in significant improvement of contrast of middle-ear soft tissues (Rohani et al., 2016). However, the staining process is time-consuming and may cause tissue shrinkage (Buytaert et al., 2014).
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An alternative approach to staining is combining data from two imaging modalities. Buytaert et al. combined data from high-resolution micro-CT recordings with data from high-resolution orthogonal-plane fluorescence optical-sectioning microscopy (OPFOS) (Buytaert et al., 2011; Maftoon et al., 2015; Motallebzadeh et al., 2017). OPFOS is an optical technique with very high resolution that is used to visualize both soft tissues and bone if the structures can be made transparent (Voie et al., 1993; Buytaert et al., 2012). Achieving the necessary level of transparency can be challenging and requires substantial amount of chemical processing involving decalcification of bone, clearing and staining with fluorescent dye, steps that aid light
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transmission and imaging of deeper bone encapsulated tissue (Decraemer et al., 2003). Optical coherence tomography has also been used to produce cross sectional (Park et al., 2003) or 3D images of the middle ear (Pitris et al., 2001; MacDougall et al., 2015). However, similar to OPFOS, OCT can suffer from degraded image quality, and shadowing artifacts due to the attenuation of the optical signal and scattering in non optically transparent structures such as the TM (Pitris et al., 2001).
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Synchrotron radiation (SR)-based X-ray imaging provides coherent collimated X-rays with high photon flux and submicron source stability. These high-energy X-ray beams pass through dense structures easily, making internal structures visible without the need for staining or bone decalcification. SR-CT has been previously used to image middle-ear structures (Vogel and Schmitt, 1998; Vogel, 2000; Neudert et al., 2010; Kanzaki et al., 2011). Kanzaki et al. used SRCT microscopy to study the cartilaginous constitution of auditory ossicles in osteopetrotic mice (Kanzaki et al., 2011). Since SR can provide monochromatic beams, it does not suffer from beam-hardening artifacts, which result from the variations in absorption of photons of different energies in polychromatic beams. Neudert et al. (2010) relied on this advantage of SR microtomography to evaluate the bone-implant contact surface area of stapes and titanium prostheses (Neudert et al., 2010). Vogel et al. used SR-CT to image middle-ear ossicles and reported very good segmentation results because of the high contrast of bone and surrounding air, whereas soft tissues (e.g., tympanic membrane) were much more difficult to segment yielding 3D reconstructions with structural discontinuities (Vogel and Schmitt, 1998).
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While conventionally, CT imaging is absorption-contrast based, phase-contrast imaging (PCI) can potentially be combined with SR-CT (called “SR-PCI” henceforth), to improve soft-tissue contrast while maintaining accurate visualization of bone. Conventional absorption-contrast based CT depends on the attenuation of X-rays as they traverse the sample, whereas in PCI the phase shift caused by the sample is transformed into detectable variations in X-ray intensity. In addition, PCI can provide edge enhancement by emphasizing the contrast between boundaries of different structures in the image.
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In this paper, we present the first use of SR-PCI to image and model the middle-ear structures of unstained, non-decalcified human temporal bone. Our objective is to demonstrate that SR-PCI can be used to improve the visualization of both bone and soft tissue simultaneously while yielding accurate volume estimates of imaged structures. Accurate visualization and modeling of the middle-ear structures is fundamental for generating accurate and reliable FE models used to study its biomechanical response.
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Four fresh-frozen then fixed adult cadaveric temporal bones were used in this study. All cadaveric specimens were obtained with permission from the body bequeathal program at Western University, London, Ontario, Canada in accordance with the Anatomy Act of Ontario and Western's Committee for Cadaveric Use in Research. Following thawing, a cylindrical cutter was used to core a sample (40 mm diameter and 60 mm length) of the middle ear from each temporal bone.
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Materials and Methods
Temporal bone preparation
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The samples were fixed in a 4F1G (3.7% formaldehyde + 1% gluteraldehyde in phosphate buffer) bath for 5 days. The samples were then rinsed twice and dehydrated using an ethanol series (50%, 60%, 70%, 80%, 90%, 95%, 100% and 100%). No additional processing (i.e., staining, sectioning or decalcification) was performed on the samples. Sample fixation eliminated the risk of degradation during the two-month time difference between imaging sessions and during scanning. Samples were transferred to the imaging facilities in motion-proof containers to avoid risk of damage during shipping.
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2.2.1 SR-PCI imaging
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The PCI technique used in this study is in-line PCI, which is similar to the setup used for conventional radiography, is comprised of an X-ray source, a sample, and a detector but no other optical elements are required. However, it differs in that it requires the detector to be placed at a distance from the sample to allow the phase-shifted beam to interfere with the original beam and produce measurable fringes. These fringes correspond to surfaces and structural boundaries of the sample (edge enhancement) compared with a conventional radiogram.
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To acquire the SR-PCI images, each sample was scanned using the Bio-Medical Imaging and Therapy (BMIT) 05ID-2 beamline at the Canadian Light Source Inc. (CLSI) in Saskatoon, SK, Canada. The BMIT 05ID-2 beamline provides an SR beam produced by a superconducting wiggler source (Wysokinski et al., 2015). The beam is filtered using a monochromator and yields an energy bandwidth of ∆E/E = 10-3 over an energy range of 25 – 150 keV. The imaging setup installed at the beamline length of 55 m from source, consists of a sample stage and a chargecoupled-device based detector system both placed on a vibration isolation table. The distance between the sample and detector was set to 2 m and the photon energy was set to 47 keV. Motorized alignment stages were used to align the sample and detector for high resolution tomography. The detector (a beam monitor AA-60 coupled with a camera C9300-124, Hamamatsu Photonics, Shizuoka, Japan) has a 12-bit resolution and an effective pixel size of 9 x 9 µm2. The imaging field of view was set to 4000 x 950 pixels corresponding to 36.0 x 8.6 mm and 3000 projections over 180º rotation were acquired per view. The 3D image volume had an isotropic voxel size of 9 µm. The whole middle-ear region of interest was covered by 2 to 3 fields of view depending on the size of the sample. The acquisition time to capture all projections per view was ~30 minutes. Both flat-field and dark-field corrections (i.e., removal of beamspecific and detector-specific artifacts) were applied during reconstructions. The reconstructed grayscale images were of 12-bit resolution.
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For comparison, conventional absorption-contrast micro-CT imaging was performed. To acquire conventional micro-CT images, samples were imaged using an eXplore Locus micro-CT scanner (GE Healthcare Biosciences, London, Ontario, Canada) at the Robarts Research Institute, Western University in London, ON. The scanner operated with an X-ray source of 80 kV voltage and a current of 0.45 mA. The source-to-sample distance was 256.03 mm whereas the source-todetector distance was 361.34 mm. The temperature of the whole system was controlled during scanning. The temperature and the moisture level of the fixed samples was controlled by placing
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Experimental setup and image acquisition
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them in a plastic container. Using an angular increment of 0.4 degrees, 900 projections were acquired. For each projection, the object was exposed for about 4.5 s per frame and an average of 5 frames was taken to increase the signal-to-noise ratio. There were no overlapping slices in the micro-CT image dataset. The total acquisition time to capture all projections was ~7 hours. A modified cone-beam algorithm (Feldkamp et al., 1984) was used to reconstruct the data into a 3D image volume with an isotropic voxel size of 20 µm. A sub-volume of ~200 slices was selected to span the entire middle ear.
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Prior to segmentation, the SR-PCI and conventional micro-CT images were co-registered to allow for visual and quantitative comparisons. Fiducial-based registration using three landmarks (umbo, lateral process of malleus and short body of incus) placed on the two corresponding images was performed using Fiducial Registration module in the 3D Slicer 4.5 platform (Fedorov et al., 2012).
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Following co-registration, a semi-automatic segmentation algorithm, “FastGrowCut” (Zhu et al., 2014), was applied to extract models of the ossicles. The FastGrowCut algorithm is a singlethreaded algorithm that uses manually selected pixels as seeds for structures of interest and for background. These seeds are iteratively “grown” to be classified into pixels corresponding to the structures of interest and to background. The segmentation process was performed on a quadcore workstation (Intel Core i7-3930K 3.2GHz, 64 GB RAM and GeForce GTX 970) with a total running time of ~60 minutes for the ossicles.
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The following soft tissue structures: (TM, Incudomalleal joint, Incudostapedial joint, Tensor tympani muscle, Anterior mallear ligament, Lateral mallear ligament, Posterior incudal ligament, Stapedial annular ligament and Stapedius muscle) were segmented using a combination of thresholding followed by manual editing performed using the Editor module in 3D Slicer platform.
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Although the SR-PCI images allowed for the semi-automated segmentation of the stapes, it was more challenging to completely isolate the stapes in the micro-CT images. Therefore, the 3D models of the incus and malleus only were used for quantitative comparison of the two imaging modalities by calculated their volumes.
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The co-registered SR-PCI and micro-CT volumes of middle-ear bones and soft tissues including membranes, joints, ligaments and muscles were visually compared. Intensity profiles and histograms were computed in order to highlight changes in contrast. Matching SR-PCI and micro-CT images were exported after normalizing their intensities to 0-255 grey-scale levels. The intensity normalization was performed by scaling the full range of intensities in each image while avoiding clipping or saturation of image intensities. This normalization was essential to compare and analyze variations in image intensity by plotting intensity histograms and intensity profiles.
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As noted in the Introduction, SR-PCI results in enhancement of edges, and at the outset, it was not clear if this enhancement affects geometrical properties. Since mass density is an important
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parameter for developing accurate FE models of the middle-ear structures (Abel and Lord, 2001; Koike et al., 2005; Sim and Puria, 2008) and is affected by volume, we evaluated the accuracy of volume estimates derived from segmentations of the SR-PCI images. A preliminary imaging study showed that the edge enhancement effect is more prominent in bones than in soft tissue. Therefore, quantitative comparison was performed by computing the volume of the malleus and incus using the 3D reconstructions from both types of images. Mean volumes and mean absolute differences between volume estimates were computed and compared between the two imaging modalities and to derived values from mass and density estimates in literature: 12.67±1.6 mm3 and 14.10±2.6 mm3 for the malleus and incus, respectively (Sim and Puria, 2008). A power calculation was performed to confirm the suitability of the available sample size of n=4 for statistical comparisons (HyLown LLC, 2017). A 1-sample, 2-sided equality power test was performed using the following values: µ=14, µ 0=12, σ=1.5, n=4, where µ is the mean volume from our preliminary study, µ 0 and σ are a reference mean and standard deviation (Sim and Puria, 2008). The calculated power was ~ 0.8 which justified our sample size for statistical comparisons. Paired Student’s t-tests were also used to compare the computed volumes and p < 0.05 was considered to indicate a significant difference.
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Images of the middle-ear ossicles (malleus, incus and stapes) acquired using SR-PCI and conventional micro-CT are illustrated in Fig. 1. The edge-enhancement provided by SR-PCI provided clearer visualization of structural details of the bones including small processes as shown in Fig. 1a. In addition, the edge-enhancement resulted in brighter borders for high density structures (clearly seen in the malleus and incus in Fig.1a). The effect of this border on the accuracy of the segmentations was evaluated by computing and comparing the volumes of the bones as will be presented in section 3.3.
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SR-PCI makes soft tissue structures easily discernible in comparison to conventional micro-CT images. The tympanic membrane, chorda tympani (Fig. 2a), stapedius muscle (Fig. 2c) and tensor tympani muscle (Fig. 2d) are clearly seen in SR-PCI images but are faint in corresponding micro-CT images (Fig. 2e, g and h). Other fine structures such as the incudomalleolar joint, lateral malleolar ligament (Fig. 2a), superior malleolar ligament (Fig. 2b), stapes annular ligament, incudostapedial joint (Fig. 2c) are clear in the images acquired using SR-PCI but are completely absent in the micro-CT images (Fig. 2e, f and g).
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The two imaging modalities display bones and soft tissue differently. In absorption-contrast micro-CT images, bones are much brighter than soft tissue whereas in SR-PCI, bones and soft tissue appear to be of similar brightness. This can be seen by comparing the intensities of the two sample images in Fig. 3a and d. The intensity profiles along the dashed lines in the SR-PCI image (Fig. 3a) and micro-CT image (Fig. 3d) running across the tympanic membrane and a section of the incus are plotted in Fig. 3b and e, respectively. A distinct intensity peak (marked by the dashed oval in Fig. 3b) corresponding to the tympanic membrane is found in the SR-PCI profile only. This explains the improved visualization of the soft tissue in SR-PCI images and
Results and Discussion
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supports the usability of this imaging modality to image bones and soft tissue simultaneously. The histograms of the intensities of the two images are shown in Fig. 3c and f. The range of intensities and positions of peaks in the histograms help explain the different intensity mapping of bones and soft-tissue using the two imaging modalities. In the SR-PCI histogram (Fig. 3c) the intensities are distributed over a narrower range of intensities within which the background (i.e. air) is represented by the first peak and the tissue (bones and soft-tissue combined) correspond to the second peak. The histogram from the micro-CT image (Fig. 3f) also includes two peaks, but they are farther away from each other, hence, covering a wider range of intensities. The first peak corresponds to air while the second peak corresponds to bone only, with other tissue (including soft tissue) represented by the intensities in-between the two peaks. This indicates that it can sometimes be more challenging to visually differentiate structures of different densities (e.g. bone and soft tissue) in SR-PCI images than in conventional absorption-contrast CT imaging. Nevertheless, SR-PCI provides improved sensitivity to density variations, and enhanced ability to detect fine edges of structures (Lewis, 2004).
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The high contrast and clear visualization in SR-PCI images allowed very robust and distinct segmentation of the ossicles using the semi-automatic 3D FastGrowCut algorithm. Figure 4 illustrates a sample of the segmentation results using SR-PCI (Fig. 4a) and micro-CT (Fig. 4b) and the corresponding 3D reconstructed model from the SR-PCI image (c). The separation between the malleus and incus was clearer and sharper in the SR-PCI segmentations because of the presence of distinct borders. There was also less colour bleed between the different segmentations. It is also noted that the incus-stapes separation was much more defined in the SRPCI segmentations (Fig. 4a). These segmentations did not require any further manual modifications and indicate that SR-PCI images are very reliable in semi-automatically segmenting adjacent bones.
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Similarly, the improved soft-tissue contrast provided segmentations with sharp edges and clear endings for the delicate structures. A sample of the generated colour maps and 3D models of the middle ear soft tissue structures using SR-PCI images is shown in Fig. 5. The colour maps in Fig. 5b illustrate the sharpness of segmenting the ISJ and the adjacent bones (Stapes and Incus). Similarly, Fig. 5c represents a plane through the IMJ, TM and cross sections of AML and PIL and their clear connections to the Malleus and Incus.
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A sample of the segmented structures and the corresponding raw images are provided to the research community through an online data repository at: http://abl.uwo.ca/data_repository/middle_ear.html
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Volume estimates using SR-PCI and micro-CT of all 4 samples are summarized in Table 1. The volume estimates and mean volumes for both malleus and incus using the two imaging modalities were within the range of volumes derived from the literature (12.67 ± 1.6 mm3 for the malleus and 14.10 ± 2.6 mm3 for the incus (Sim and Puria, 2008)). The mean absolute difference in computed volumes using the two imaging modalities was 0.57 mm3 (4.5%) for the malleus and 0.3 mm3 (2.1%) for the incus. These small variations were not significantly different (p=0.54 and p=0.89). This further emphasizes the negligible effect of the enhanced borders of the
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Quantitative comparison of SR-PCI and conventional micro-CT
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bones on volume estimates. Note that a comparison to the volumes reported by Sim and Puria (2008) is justified as their micro-CT images have approximately the same spatial resolution as our SR-PCI data.
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The edge enhancement provided by the phase-contrast method and the depth of penetration provided by synchrotron radiation makes SR-PCI images sharper than corresponding conventional micro-CT images that have the same spatial resolution. Indeed, the two imaging modalities used in this work had similar spatial resolutions of approximately 20 µm. Higher spatial resolutions can still be achieved with SR-PCI and is the focus of on-going investigation. The edge-sharpening capability of SR-PCI allows it to depict bones as well as boundaries of fine soft tissues such as the tympanic membrane, ligaments, muscles, joints and their points of contact to adjacent structures (Fig. 2). This edge-enhancement-based visualization is not attainable in corresponding absorption-contrast micro-CT images.
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With the remarkable improvement of soft-tissue contrast provided by phase-contrast imaging, more research groups are recently experimenting integrating phase-contrast imaging in commercial lab-based micro-CT systems (Wilkins et al., 1996; Pfeiffer et al., 2006; Tuohimaa et al., 2007; Bartels et al., 2013; Bidola et al., 2017). One of the main challenges with phasecontrast imaging is that it requires a highly monochromatic beam (achievable using synchrotron radiation imaging) and sophisticated X-ray optics which restricts its integrations with commonly available polychromatic CT systems (Wilkins et al., 1996). Methods to overcome these challenges require special setups or designing customized X-ray systems such as using nanometric phase gratings (Miao et al., 2015), liquid-metal-jet microfocus sources (Tuohimaa et al., 2007; Zhou et al., 2013) or laser plasma-based Xray sources (Kincaid, 2010). These methods are still in the development phase, therefore limiting their application to imaging a wide range ear structures that would benefit from the improved soft-tissue contrast.
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A comparable level of realistic visualization was only reported in studies involving the use of staining (De Greef et al., 2015; Rohani et al., 2016); higher resolution systems (Sim and Puria, 2008; Puria and Steele, 2010), which require further reduction of samples sizes to fit small sample holders; or combining micro-CT imaging with OPFOS (Buytaert et al., 2011), which requires elaborate specimen preparation to make specimens transparent. SR-PCI achieves comparable and possibly higher contrast visualization in lieu of further processing or dissection of temporal bones.
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Synchrotron radiation phase-contrast imaging can be used as a tool to improve visualization of middle-ear bones and soft tissues simultaneously without the need for staining, decalcification, or excessive sample size reduction. It enhances edges of structures allowing the detection of fine soft-tissue structures such as ligaments and joints. This edge enhancement also makes semiautomatic segmentation of structures possible without compromising the accuracy of volume representations of structures. Combining the achievable visualization quality and modeling accuracy with ease of sample preparation makes SR-PCI a promising tool for generating reliable FE models to study biomechanical properties of the middle-ear components.
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Acknowledgements
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Financial support for Mai Elfarnawany, Ph.D. was provided by a MITACS Accelerate postdoctoral internship (number: IT04392), Canada. Part of the research described in this paper was performed at the BMIT facility at the Canadian Light Source, which is funded by the Canada Foundation for Innovation, the Natural Sciences and Engineering Research Council of Canada, the National Research Council Canada, the Canadian Institutes of Health Research, the Government of Saskatchewan, Western Economic Diversification Canada, and the University of Saskatchewan.
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Bidola, P., Morgan, K., Willner, M., Fehringer, A., Allner, S., Prade, F., Pfeiffer, F., Achterhold, K., 2017. Application of sensitive, high-resolution imaging at a commercial lab-based X-ray micro-CT system using propagation-based phase retrieval. J. Microsc. 266, 211–220. doi:10.1111/jmi.12530
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Fig. 1 Comparison of middle-ear ossicle visualization using SR-PCI and conventional micro-CT. Malleus, incus and stapes are clearer and have more structural details in SR-PCI images (a) and (b) than in the corresponding micro-CT images (c) and (d). Edge enhancement provided by SRPCI allows clear visualization of internal structural details (white arrows in (a)). Corresponding images were captured from co-registered images of the same sample.
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Fig. 2 Improved soft-tissue visualization in SR-PCI images over conventional micro-CT images. Sample SR-PCI images show soft tissues such as tympanic membrane (TM), chorda tympani (Ct), incudomalleolar joint (IMJ), lateral malleolar ligament (LML) in (a), superior malleolar ligament (SML) in (b), stapes annular ligament (SAL), incudostapedial joint (ISJ), stapedius muscle (SM) in (c) and tensor tympani muscle (TTM) in (d) that are depicted with higher contrast than in the corresponding conventional micro-CT images (e), (f), (g) and (h). Corresponding images were captured from co-registered images of the same sample.
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Fig. 3 Differences between SR-PCI and conventional micro-CT image intensities. The Intensity profiles along the dashed lines in (a) and (d) running across the tympanic membrane and a section of the incus are shown in (b) and (e). In addition to the main peak corresponding to the bone (between 0.4-0.5 cm), a distinct peak (dashed circle in (b)) corresponds to the tympanic membrane and cannot be seen in (e) indicating improved visualization of soft tissue in SR-PCI images. Intensity histograms (c) and (f) show two peaks. In SR-PCI (c), the first peak (air) is close to the second peak (tissue: bone and soft tissue combined) whereas in micro-CT (f), there is a wider distribution of intensities separating other tissue (including soft tissue) from bone peak. This indicates the lower sensitivity of SR-PCI in distinguishing structures of different intensities while improving contrast by detecting their fine edges. Corresponding images were captured from co-registered images of the same sample.
Fig. 4 A sample of the segmentation results using SR-PCI (a) and absorption-contrast micro-CT (b) and the corresponding 3D reconstructed model from SR-PCI is shown in (c). SR-PCI segmentations (a) showed clearer separation between the malleus and incus. The incus-stapes separation was also more defined in (a) than (b). Corresponding images were captured from coregistered images of the same sample.
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Fig. 5 A sample of the segmentation results of soft tissue structures from SR-PCI images. (a) illustrates all 9 segmented soft tissue structures: (tympanic membrane (TM), tensor tympani muscle (TTM), incudostapedial joint (ISJ), stapedial annular ligament (SAL), stapedius muscle (SM), posterior incudal ligament (PIL), incudomalleolar joint (IMJ), lateral malleolar ligament (LML) and anterior mallear ligament (AML)) and their connections to the three ossicles: (malleus, incus and stapes). (b) a sample plane through the generated colour maps illustrating the sharpness of segmenting the ISJ and the adjacent bones (stapes and incus). (c) represents a plane 15
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through colour maps showing the IMJ, TM and cross sections of AML and PIL and their clear connections to the malleus and incus.
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Table 1: Volume Estimates of Malleus and Incus from SR-PCI, Micro-CT Images and Literature Malleus (mm3) Ear 1
Ear 2 Ear 3
Mean ± std
Ear 1
Ear 2
SR-PCI
14.33
11.77 12.46 11.92 12.62 ± 1.2
16.03
13.31 13.02 14.29 14.16 ± 1.4
Micro-CT
13.95
11.47 13.14 11.02 12.40 ± 1.4
16.40
13.15 13.19 13.79 14.13 ± 1.5
Abs. Difference
0.38
0.30 0.68
0.37
0.16
0.57 ± 0.28
Ear 4
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Table 1: Volume Estimates of Malleus and Incus from SR-PCI, Micro-CT Images and Literature Malleus (mm3) Ear 1
Ear 2 Ear 3
Mean ± std
Ear 1
Ear 2
SR-PCI
14.33
11.77 12.46 11.92 12.62 ± 1.2
16.03
13.31 13.02 14.29 14.16 ± 1.4
Micro-CT
13.95
11.47 13.14 11.02 12.40 ± 1.4
16.40
13.15 13.19 13.79 14.13 ± 1.5
Abs. Difference
0.38
0.30 0.68
0.37
0.16
0.57 ± 0.28
Ear 4
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Ear 3
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Highlights:
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Synchrotron-radiation phase contrast imaging is proposed for middle-ear imaging It provides superior visualization of microstructures over conventional micro-CT It is an improved tool to visualize middle-ear bones and soft tissue simultaneously These improvements are achieved without the need for staining or decalcification It is a promising tool for generating reliable FE models of the middle-ear structures
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DOI:
10.1016/j.heares.2017.08.001
Reference:
HEARES 7408
To appear in:
Hearing Research
Received Date: 22 February 2017 Revised Date:
30 July 2017
Accepted Date: 2 August 2017
Please cite this article as: Elfarnawany, M., Rohani, S.A., Ghomashchi, S., Allen, D.G., Zhu, N., Agrawal, S.K., Ladak, H.M., Improved middle-ear soft-tissue visualization using synchrotron radiation phasecontrast imaging, Hearing Research (2017), doi: 10.1016/j.heares.2017.08.001. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Improved Middle-Ear Soft-Tissue Visualization Using Synchrotron Radiation Phase-Contrast Imaging
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Mai Elfarnawany1,§, Seyed Alireza Rohani2, Soroush Ghomashchi3, Daniel G. Allen3, Ning Zhu4, Sumit K. Agrawal1, 2, 3, 5,*, and Hanif M. Ladak1, 2, 3, 5,* 1
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Department of Otolaryngology-Head and Neck Surgery, Western University, London, ON, Canada 2 Biomedical Engineering Graduate Program, Western University, London, ON, Canada 3 Department of Medical Biophysics, Western University, London, ON, Canada 4 Bio-Medical Imaging and Therapy Facility, Canadian Light Source Inc., University of Saskatchewan, Saskatoon, SK, Canada 5 Department of Electrical and Computer Engineering, Western University, London, ON, Canada *co-senior authors
§ Corresponding author: Tel: (519)-661-2111 ext. 85683, Fax: (519)-661-2123, email:[email protected]
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Abstract High resolution images are used as a basis for finite-element modeling of the middle-ear structures to study their biomechanical function. Commonly used imaging techniques such as micro-computed tomography (CT) and optical microscopy require extensive sample preparation, processing or staining using contrast agents to achieve sufficient soft-tissue contrast. We compare imaging of middle-ear structures in unstained, non-decalcified human temporal bones using conventional absorption-contrast micro-CT and using synchrotron radiation phase-contrast imaging (SR-PCI). Four cadaveric temporal bones were imaged using SR-PCI and conventional micro-CT. Images were qualitatively compared in terms of visualization of structural details and soft-tissue contrast using intensity profiles and histograms. In order to quantitatively compare SR-PCI to micro-CT, three-dimensional (3D) models of the ossicles were constructed from both modalities using a semi-automatic segmentation method as these structures are clearly visible in both types of images. Volumes of the segmented ossicles were computed and compared between the two imaging modalities and to estimates from the literature. SR-PCI images provided superior visualization of soft-tissue microstructures over conventional micro-CT images. Intensity profiles emphasized the improved contrast and detectability of soft-tissue in SR-PCI in comparison to absorption-contrast micro-CT. In addition, the semi-automatic segmentations of SR-PCI images yielded accurate 3D reconstructions of the ossicles with mean volumes in accord with volume estimates from micro-CT images and literature. Sample segmentations of the ossicles and soft tissue structures were provided on an online data repository for benefit of the research community. The improved visualization, modeling accuracy and simple sample preparation make SR-PCI a promising tool for generating reliable FE models of the middle-ear structures, including both soft tissues and bone.
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Keywords: Micro-computed tomography, synchrotron radiation, phase-contrast imaging, middle ear, soft tissue, image segmentation
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Introduction
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Finite-element (FE) models are computational models used to simulate and understand the relationship between structure and function of modeled anatomies. FE models of the complex and small middle-ear bones and surrounding soft tissue have been used to study their biomechanical properties (Sun et al., 2002; Decraemer et al., 2003; Huber et al., 2003; Funnell et al., 2005; Homma et al., 2009; Chou et al., 2011; Gan et al., 2011; Zhang and Gan, 2011) and as modeling tools for improving and optimizing middle-ear prostheses (Kelly et al., 2003; Neudert et al., 2007; Gan et al., 2010). Constructing these computational models requires having accurate and realistic representations of the anatomical geometries of the modeled structures.
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Histological sectioning provides very high resolution anatomical representations, which can be used as the basis for FE modeling of the middle-ear structures (Funnell et al., 1992; Gan et al., 2002, 2004; Sun et al., 2002; Wang et al., 2007). However, challenges of histological sectioning include sample destruction, the risk of structural deformation and long processing time.
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Modern imaging modalities provide an alternative method to obtain anatomical and geometrical representations of the middle-ear structures while overcoming some of the challenges of histological sectioning. Clinical computed tomography (CT) can be used to acquire in-vivo images of the middle ear from patients. Clinical CT was previously used to derive models of the middle ear for finite-element analysis (Lee et al., 2006; Wen et al., 2006; Chou et al., 2011). However, clinical CT images are restricted by low spatial resolution and by radiation dose and exposure time when used to image patients, therefore limiting achievable image quality and contrast resolution. Micro-CT is more commonly used in obtaining models of the middle ear in human (Decraemer et al., 2003; Lane et al., 2004; Homma et al., 2009) and animal (Elkhouri et al., 2006; Tuck-Lee et al., 2008; Puria and Steele, 2010; Buytaert et al., 2011) temporal bones. Micro-CT is characterized by having micrometer-range resolution and the ability to increase beam intensities to improve image contrast. With its micrometer-range resolution, micro-CT is suitable for accurately imaging high-density tissue such as the ossicles and surrounding bone. However, it does not provide sufficient contrast resolution to easily visualize soft tissues such as the tympanic membrane, ligaments and muscles.
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A number of tissue staining agents have been proposed for contrast-enhancement of the middleear soft tissues when using micro-CT (Metscher, 2009). Phosphotungstic acid has been used to visualize middle-ear geometrical features and to create 3D surface models of the middle-ear soft tissues (Buytaert et al., 2014; De Greef et al., 2015). Iodine potassium iodide was reported to result in significant improvement of contrast of middle-ear soft tissues (Rohani et al., 2016). However, the staining process is time-consuming and may cause tissue shrinkage (Buytaert et al., 2014).
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An alternative approach to staining is combining data from two imaging modalities. Buytaert et al. combined data from high-resolution micro-CT recordings with data from high-resolution orthogonal-plane fluorescence optical-sectioning microscopy (OPFOS) (Buytaert et al., 2011; Maftoon et al., 2015; Motallebzadeh et al., 2017). OPFOS is an optical technique with very high resolution that is used to visualize both soft tissues and bone if the structures can be made transparent (Voie et al., 1993; Buytaert et al., 2012). Achieving the necessary level of transparency can be challenging and requires substantial amount of chemical processing involving decalcification of bone, clearing and staining with fluorescent dye, steps that aid light
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transmission and imaging of deeper bone encapsulated tissue (Decraemer et al., 2003). Optical coherence tomography has also been used to produce cross sectional (Park et al., 2003) or 3D images of the middle ear (Pitris et al., 2001; MacDougall et al., 2015). However, similar to OPFOS, OCT can suffer from degraded image quality, and shadowing artifacts due to the attenuation of the optical signal and scattering in non optically transparent structures such as the TM (Pitris et al., 2001).
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Synchrotron radiation (SR)-based X-ray imaging provides coherent collimated X-rays with high photon flux and submicron source stability. These high-energy X-ray beams pass through dense structures easily, making internal structures visible without the need for staining or bone decalcification. SR-CT has been previously used to image middle-ear structures (Vogel and Schmitt, 1998; Vogel, 2000; Neudert et al., 2010; Kanzaki et al., 2011). Kanzaki et al. used SRCT microscopy to study the cartilaginous constitution of auditory ossicles in osteopetrotic mice (Kanzaki et al., 2011). Since SR can provide monochromatic beams, it does not suffer from beam-hardening artifacts, which result from the variations in absorption of photons of different energies in polychromatic beams. Neudert et al. (2010) relied on this advantage of SR microtomography to evaluate the bone-implant contact surface area of stapes and titanium prostheses (Neudert et al., 2010). Vogel et al. used SR-CT to image middle-ear ossicles and reported very good segmentation results because of the high contrast of bone and surrounding air, whereas soft tissues (e.g., tympanic membrane) were much more difficult to segment yielding 3D reconstructions with structural discontinuities (Vogel and Schmitt, 1998).
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While conventionally, CT imaging is absorption-contrast based, phase-contrast imaging (PCI) can potentially be combined with SR-CT (called “SR-PCI” henceforth), to improve soft-tissue contrast while maintaining accurate visualization of bone. Conventional absorption-contrast based CT depends on the attenuation of X-rays as they traverse the sample, whereas in PCI the phase shift caused by the sample is transformed into detectable variations in X-ray intensity. In addition, PCI can provide edge enhancement by emphasizing the contrast between boundaries of different structures in the image.
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In this paper, we present the first use of SR-PCI to image and model the middle-ear structures of unstained, non-decalcified human temporal bone. Our objective is to demonstrate that SR-PCI can be used to improve the visualization of both bone and soft tissue simultaneously while yielding accurate volume estimates of imaged structures. Accurate visualization and modeling of the middle-ear structures is fundamental for generating accurate and reliable FE models used to study its biomechanical response.
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Four fresh-frozen then fixed adult cadaveric temporal bones were used in this study. All cadaveric specimens were obtained with permission from the body bequeathal program at Western University, London, Ontario, Canada in accordance with the Anatomy Act of Ontario and Western's Committee for Cadaveric Use in Research. Following thawing, a cylindrical cutter was used to core a sample (40 mm diameter and 60 mm length) of the middle ear from each temporal bone.
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Materials and Methods
Temporal bone preparation
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The samples were fixed in a 4F1G (3.7% formaldehyde + 1% gluteraldehyde in phosphate buffer) bath for 5 days. The samples were then rinsed twice and dehydrated using an ethanol series (50%, 60%, 70%, 80%, 90%, 95%, 100% and 100%). No additional processing (i.e., staining, sectioning or decalcification) was performed on the samples. Sample fixation eliminated the risk of degradation during the two-month time difference between imaging sessions and during scanning. Samples were transferred to the imaging facilities in motion-proof containers to avoid risk of damage during shipping.
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The PCI technique used in this study is in-line PCI, which is similar to the setup used for conventional radiography, is comprised of an X-ray source, a sample, and a detector but no other optical elements are required. However, it differs in that it requires the detector to be placed at a distance from the sample to allow the phase-shifted beam to interfere with the original beam and produce measurable fringes. These fringes correspond to surfaces and structural boundaries of the sample (edge enhancement) compared with a conventional radiogram.
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To acquire the SR-PCI images, each sample was scanned using the Bio-Medical Imaging and Therapy (BMIT) 05ID-2 beamline at the Canadian Light Source Inc. (CLSI) in Saskatoon, SK, Canada. The BMIT 05ID-2 beamline provides an SR beam produced by a superconducting wiggler source (Wysokinski et al., 2015). The beam is filtered using a monochromator and yields an energy bandwidth of ∆E/E = 10-3 over an energy range of 25 – 150 keV. The imaging setup installed at the beamline length of 55 m from source, consists of a sample stage and a chargecoupled-device based detector system both placed on a vibration isolation table. The distance between the sample and detector was set to 2 m and the photon energy was set to 47 keV. Motorized alignment stages were used to align the sample and detector for high resolution tomography. The detector (a beam monitor AA-60 coupled with a camera C9300-124, Hamamatsu Photonics, Shizuoka, Japan) has a 12-bit resolution and an effective pixel size of 9 x 9 µm2. The imaging field of view was set to 4000 x 950 pixels corresponding to 36.0 x 8.6 mm and 3000 projections over 180º rotation were acquired per view. The 3D image volume had an isotropic voxel size of 9 µm. The whole middle-ear region of interest was covered by 2 to 3 fields of view depending on the size of the sample. The acquisition time to capture all projections per view was ~30 minutes. Both flat-field and dark-field corrections (i.e., removal of beamspecific and detector-specific artifacts) were applied during reconstructions. The reconstructed grayscale images were of 12-bit resolution.
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For comparison, conventional absorption-contrast micro-CT imaging was performed. To acquire conventional micro-CT images, samples were imaged using an eXplore Locus micro-CT scanner (GE Healthcare Biosciences, London, Ontario, Canada) at the Robarts Research Institute, Western University in London, ON. The scanner operated with an X-ray source of 80 kV voltage and a current of 0.45 mA. The source-to-sample distance was 256.03 mm whereas the source-todetector distance was 361.34 mm. The temperature of the whole system was controlled during scanning. The temperature and the moisture level of the fixed samples was controlled by placing
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them in a plastic container. Using an angular increment of 0.4 degrees, 900 projections were acquired. For each projection, the object was exposed for about 4.5 s per frame and an average of 5 frames was taken to increase the signal-to-noise ratio. There were no overlapping slices in the micro-CT image dataset. The total acquisition time to capture all projections was ~7 hours. A modified cone-beam algorithm (Feldkamp et al., 1984) was used to reconstruct the data into a 3D image volume with an isotropic voxel size of 20 µm. A sub-volume of ~200 slices was selected to span the entire middle ear.
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Prior to segmentation, the SR-PCI and conventional micro-CT images were co-registered to allow for visual and quantitative comparisons. Fiducial-based registration using three landmarks (umbo, lateral process of malleus and short body of incus) placed on the two corresponding images was performed using Fiducial Registration module in the 3D Slicer 4.5 platform (Fedorov et al., 2012).
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Following co-registration, a semi-automatic segmentation algorithm, “FastGrowCut” (Zhu et al., 2014), was applied to extract models of the ossicles. The FastGrowCut algorithm is a singlethreaded algorithm that uses manually selected pixels as seeds for structures of interest and for background. These seeds are iteratively “grown” to be classified into pixels corresponding to the structures of interest and to background. The segmentation process was performed on a quadcore workstation (Intel Core i7-3930K 3.2GHz, 64 GB RAM and GeForce GTX 970) with a total running time of ~60 minutes for the ossicles.
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The following soft tissue structures: (TM, Incudomalleal joint, Incudostapedial joint, Tensor tympani muscle, Anterior mallear ligament, Lateral mallear ligament, Posterior incudal ligament, Stapedial annular ligament and Stapedius muscle) were segmented using a combination of thresholding followed by manual editing performed using the Editor module in 3D Slicer platform.
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Although the SR-PCI images allowed for the semi-automated segmentation of the stapes, it was more challenging to completely isolate the stapes in the micro-CT images. Therefore, the 3D models of the incus and malleus only were used for quantitative comparison of the two imaging modalities by calculated their volumes.
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The co-registered SR-PCI and micro-CT volumes of middle-ear bones and soft tissues including membranes, joints, ligaments and muscles were visually compared. Intensity profiles and histograms were computed in order to highlight changes in contrast. Matching SR-PCI and micro-CT images were exported after normalizing their intensities to 0-255 grey-scale levels. The intensity normalization was performed by scaling the full range of intensities in each image while avoiding clipping or saturation of image intensities. This normalization was essential to compare and analyze variations in image intensity by plotting intensity histograms and intensity profiles.
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As noted in the Introduction, SR-PCI results in enhancement of edges, and at the outset, it was not clear if this enhancement affects geometrical properties. Since mass density is an important
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parameter for developing accurate FE models of the middle-ear structures (Abel and Lord, 2001; Koike et al., 2005; Sim and Puria, 2008) and is affected by volume, we evaluated the accuracy of volume estimates derived from segmentations of the SR-PCI images. A preliminary imaging study showed that the edge enhancement effect is more prominent in bones than in soft tissue. Therefore, quantitative comparison was performed by computing the volume of the malleus and incus using the 3D reconstructions from both types of images. Mean volumes and mean absolute differences between volume estimates were computed and compared between the two imaging modalities and to derived values from mass and density estimates in literature: 12.67±1.6 mm3 and 14.10±2.6 mm3 for the malleus and incus, respectively (Sim and Puria, 2008). A power calculation was performed to confirm the suitability of the available sample size of n=4 for statistical comparisons (HyLown LLC, 2017). A 1-sample, 2-sided equality power test was performed using the following values: µ=14, µ 0=12, σ=1.5, n=4, where µ is the mean volume from our preliminary study, µ 0 and σ are a reference mean and standard deviation (Sim and Puria, 2008). The calculated power was ~ 0.8 which justified our sample size for statistical comparisons. Paired Student’s t-tests were also used to compare the computed volumes and p < 0.05 was considered to indicate a significant difference.
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Images of the middle-ear ossicles (malleus, incus and stapes) acquired using SR-PCI and conventional micro-CT are illustrated in Fig. 1. The edge-enhancement provided by SR-PCI provided clearer visualization of structural details of the bones including small processes as shown in Fig. 1a. In addition, the edge-enhancement resulted in brighter borders for high density structures (clearly seen in the malleus and incus in Fig.1a). The effect of this border on the accuracy of the segmentations was evaluated by computing and comparing the volumes of the bones as will be presented in section 3.3.
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SR-PCI makes soft tissue structures easily discernible in comparison to conventional micro-CT images. The tympanic membrane, chorda tympani (Fig. 2a), stapedius muscle (Fig. 2c) and tensor tympani muscle (Fig. 2d) are clearly seen in SR-PCI images but are faint in corresponding micro-CT images (Fig. 2e, g and h). Other fine structures such as the incudomalleolar joint, lateral malleolar ligament (Fig. 2a), superior malleolar ligament (Fig. 2b), stapes annular ligament, incudostapedial joint (Fig. 2c) are clear in the images acquired using SR-PCI but are completely absent in the micro-CT images (Fig. 2e, f and g).
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The two imaging modalities display bones and soft tissue differently. In absorption-contrast micro-CT images, bones are much brighter than soft tissue whereas in SR-PCI, bones and soft tissue appear to be of similar brightness. This can be seen by comparing the intensities of the two sample images in Fig. 3a and d. The intensity profiles along the dashed lines in the SR-PCI image (Fig. 3a) and micro-CT image (Fig. 3d) running across the tympanic membrane and a section of the incus are plotted in Fig. 3b and e, respectively. A distinct intensity peak (marked by the dashed oval in Fig. 3b) corresponding to the tympanic membrane is found in the SR-PCI profile only. This explains the improved visualization of the soft tissue in SR-PCI images and
Results and Discussion
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supports the usability of this imaging modality to image bones and soft tissue simultaneously. The histograms of the intensities of the two images are shown in Fig. 3c and f. The range of intensities and positions of peaks in the histograms help explain the different intensity mapping of bones and soft-tissue using the two imaging modalities. In the SR-PCI histogram (Fig. 3c) the intensities are distributed over a narrower range of intensities within which the background (i.e. air) is represented by the first peak and the tissue (bones and soft-tissue combined) correspond to the second peak. The histogram from the micro-CT image (Fig. 3f) also includes two peaks, but they are farther away from each other, hence, covering a wider range of intensities. The first peak corresponds to air while the second peak corresponds to bone only, with other tissue (including soft tissue) represented by the intensities in-between the two peaks. This indicates that it can sometimes be more challenging to visually differentiate structures of different densities (e.g. bone and soft tissue) in SR-PCI images than in conventional absorption-contrast CT imaging. Nevertheless, SR-PCI provides improved sensitivity to density variations, and enhanced ability to detect fine edges of structures (Lewis, 2004).
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The high contrast and clear visualization in SR-PCI images allowed very robust and distinct segmentation of the ossicles using the semi-automatic 3D FastGrowCut algorithm. Figure 4 illustrates a sample of the segmentation results using SR-PCI (Fig. 4a) and micro-CT (Fig. 4b) and the corresponding 3D reconstructed model from the SR-PCI image (c). The separation between the malleus and incus was clearer and sharper in the SR-PCI segmentations because of the presence of distinct borders. There was also less colour bleed between the different segmentations. It is also noted that the incus-stapes separation was much more defined in the SRPCI segmentations (Fig. 4a). These segmentations did not require any further manual modifications and indicate that SR-PCI images are very reliable in semi-automatically segmenting adjacent bones.
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Similarly, the improved soft-tissue contrast provided segmentations with sharp edges and clear endings for the delicate structures. A sample of the generated colour maps and 3D models of the middle ear soft tissue structures using SR-PCI images is shown in Fig. 5. The colour maps in Fig. 5b illustrate the sharpness of segmenting the ISJ and the adjacent bones (Stapes and Incus). Similarly, Fig. 5c represents a plane through the IMJ, TM and cross sections of AML and PIL and their clear connections to the Malleus and Incus.
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A sample of the segmented structures and the corresponding raw images are provided to the research community through an online data repository at: http://abl.uwo.ca/data_repository/middle_ear.html
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Volume estimates using SR-PCI and micro-CT of all 4 samples are summarized in Table 1. The volume estimates and mean volumes for both malleus and incus using the two imaging modalities were within the range of volumes derived from the literature (12.67 ± 1.6 mm3 for the malleus and 14.10 ± 2.6 mm3 for the incus (Sim and Puria, 2008)). The mean absolute difference in computed volumes using the two imaging modalities was 0.57 mm3 (4.5%) for the malleus and 0.3 mm3 (2.1%) for the incus. These small variations were not significantly different (p=0.54 and p=0.89). This further emphasizes the negligible effect of the enhanced borders of the
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Quantitative comparison of SR-PCI and conventional micro-CT
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bones on volume estimates. Note that a comparison to the volumes reported by Sim and Puria (2008) is justified as their micro-CT images have approximately the same spatial resolution as our SR-PCI data.
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The edge enhancement provided by the phase-contrast method and the depth of penetration provided by synchrotron radiation makes SR-PCI images sharper than corresponding conventional micro-CT images that have the same spatial resolution. Indeed, the two imaging modalities used in this work had similar spatial resolutions of approximately 20 µm. Higher spatial resolutions can still be achieved with SR-PCI and is the focus of on-going investigation. The edge-sharpening capability of SR-PCI allows it to depict bones as well as boundaries of fine soft tissues such as the tympanic membrane, ligaments, muscles, joints and their points of contact to adjacent structures (Fig. 2). This edge-enhancement-based visualization is not attainable in corresponding absorption-contrast micro-CT images.
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With the remarkable improvement of soft-tissue contrast provided by phase-contrast imaging, more research groups are recently experimenting integrating phase-contrast imaging in commercial lab-based micro-CT systems (Wilkins et al., 1996; Pfeiffer et al., 2006; Tuohimaa et al., 2007; Bartels et al., 2013; Bidola et al., 2017). One of the main challenges with phasecontrast imaging is that it requires a highly monochromatic beam (achievable using synchrotron radiation imaging) and sophisticated X-ray optics which restricts its integrations with commonly available polychromatic CT systems (Wilkins et al., 1996). Methods to overcome these challenges require special setups or designing customized X-ray systems such as using nanometric phase gratings (Miao et al., 2015), liquid-metal-jet microfocus sources (Tuohimaa et al., 2007; Zhou et al., 2013) or laser plasma-based Xray sources (Kincaid, 2010). These methods are still in the development phase, therefore limiting their application to imaging a wide range ear structures that would benefit from the improved soft-tissue contrast.
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A comparable level of realistic visualization was only reported in studies involving the use of staining (De Greef et al., 2015; Rohani et al., 2016); higher resolution systems (Sim and Puria, 2008; Puria and Steele, 2010), which require further reduction of samples sizes to fit small sample holders; or combining micro-CT imaging with OPFOS (Buytaert et al., 2011), which requires elaborate specimen preparation to make specimens transparent. SR-PCI achieves comparable and possibly higher contrast visualization in lieu of further processing or dissection of temporal bones.
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Synchrotron radiation phase-contrast imaging can be used as a tool to improve visualization of middle-ear bones and soft tissues simultaneously without the need for staining, decalcification, or excessive sample size reduction. It enhances edges of structures allowing the detection of fine soft-tissue structures such as ligaments and joints. This edge enhancement also makes semiautomatic segmentation of structures possible without compromising the accuracy of volume representations of structures. Combining the achievable visualization quality and modeling accuracy with ease of sample preparation makes SR-PCI a promising tool for generating reliable FE models to study biomechanical properties of the middle-ear components.
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Acknowledgements
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Financial support for Mai Elfarnawany, Ph.D. was provided by a MITACS Accelerate postdoctoral internship (number: IT04392), Canada. Part of the research described in this paper was performed at the BMIT facility at the Canadian Light Source, which is funded by the Canada Foundation for Innovation, the Natural Sciences and Engineering Research Council of Canada, the National Research Council Canada, the Canadian Institutes of Health Research, the Government of Saskatchewan, Western Economic Diversification Canada, and the University of Saskatchewan.
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Figure Captions
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Fig. 1 Comparison of middle-ear ossicle visualization using SR-PCI and conventional micro-CT. Malleus, incus and stapes are clearer and have more structural details in SR-PCI images (a) and (b) than in the corresponding micro-CT images (c) and (d). Edge enhancement provided by SRPCI allows clear visualization of internal structural details (white arrows in (a)). Corresponding images were captured from co-registered images of the same sample.
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Fig. 2 Improved soft-tissue visualization in SR-PCI images over conventional micro-CT images. Sample SR-PCI images show soft tissues such as tympanic membrane (TM), chorda tympani (Ct), incudomalleolar joint (IMJ), lateral malleolar ligament (LML) in (a), superior malleolar ligament (SML) in (b), stapes annular ligament (SAL), incudostapedial joint (ISJ), stapedius muscle (SM) in (c) and tensor tympani muscle (TTM) in (d) that are depicted with higher contrast than in the corresponding conventional micro-CT images (e), (f), (g) and (h). Corresponding images were captured from co-registered images of the same sample.
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Fig. 3 Differences between SR-PCI and conventional micro-CT image intensities. The Intensity profiles along the dashed lines in (a) and (d) running across the tympanic membrane and a section of the incus are shown in (b) and (e). In addition to the main peak corresponding to the bone (between 0.4-0.5 cm), a distinct peak (dashed circle in (b)) corresponds to the tympanic membrane and cannot be seen in (e) indicating improved visualization of soft tissue in SR-PCI images. Intensity histograms (c) and (f) show two peaks. In SR-PCI (c), the first peak (air) is close to the second peak (tissue: bone and soft tissue combined) whereas in micro-CT (f), there is a wider distribution of intensities separating other tissue (including soft tissue) from bone peak. This indicates the lower sensitivity of SR-PCI in distinguishing structures of different intensities while improving contrast by detecting their fine edges. Corresponding images were captured from co-registered images of the same sample.
Fig. 4 A sample of the segmentation results using SR-PCI (a) and absorption-contrast micro-CT (b) and the corresponding 3D reconstructed model from SR-PCI is shown in (c). SR-PCI segmentations (a) showed clearer separation between the malleus and incus. The incus-stapes separation was also more defined in (a) than (b). Corresponding images were captured from coregistered images of the same sample.
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Fig. 5 A sample of the segmentation results of soft tissue structures from SR-PCI images. (a) illustrates all 9 segmented soft tissue structures: (tympanic membrane (TM), tensor tympani muscle (TTM), incudostapedial joint (ISJ), stapedial annular ligament (SAL), stapedius muscle (SM), posterior incudal ligament (PIL), incudomalleolar joint (IMJ), lateral malleolar ligament (LML) and anterior mallear ligament (AML)) and their connections to the three ossicles: (malleus, incus and stapes). (b) a sample plane through the generated colour maps illustrating the sharpness of segmenting the ISJ and the adjacent bones (stapes and incus). (c) represents a plane 15
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through colour maps showing the IMJ, TM and cross sections of AML and PIL and their clear connections to the malleus and incus.
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Table 1: Volume Estimates of Malleus and Incus from SR-PCI, Micro-CT Images and Literature Malleus (mm3) Ear 1
Ear 2 Ear 3
Mean ± std
Ear 1
Ear 2
SR-PCI
14.33
11.77 12.46 11.92 12.62 ± 1.2
16.03
13.31 13.02 14.29 14.16 ± 1.4
Micro-CT
13.95
11.47 13.14 11.02 12.40 ± 1.4
16.40
13.15 13.19 13.79 14.13 ± 1.5
Abs. Difference
0.38
0.30 0.68
0.37
0.16
0.57 ± 0.28
Ear 4
Mean ± std
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Ear 3
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Ear 4
Incus (mm3)
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Table 1: Volume Estimates of Malleus and Incus from SR-PCI, Micro-CT Images and Literature Malleus (mm3) Ear 1
Ear 2 Ear 3
Mean ± std
Ear 1
Ear 2
SR-PCI
14.33
11.77 12.46 11.92 12.62 ± 1.2
16.03
13.31 13.02 14.29 14.16 ± 1.4
Micro-CT
13.95
11.47 13.14 11.02 12.40 ± 1.4
16.40
13.15 13.19 13.79 14.13 ± 1.5
Abs. Difference
0.38
0.30 0.68
0.37
0.16
0.57 ± 0.28
Ear 4
Mean ± std
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Ear 3
0.17
0.50
0.3 ± 1.1
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Ear 4
Incus (mm3)
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Highlights:
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Synchrotron-radiation phase contrast imaging is proposed for middle-ear imaging It provides superior visualization of microstructures over conventional micro-CT It is an improved tool to visualize middle-ear bones and soft tissue simultaneously These improvements are achieved without the need for staining or decalcification It is a promising tool for generating reliable FE models of the middle-ear structures
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