Mark C. Pierce

Small animal imaging platform for quantitative assessment of short-wave infrared-emitting contrast agents

We report the design, calibration, and testing of a pre-clinical small animal imaging platform for use with short-wave infrared (SWIR) emitting contrast agents. Unlike materials emitting at visible or near-infrared wavelengths, SWIR-emitting agents require detection systems with sensitivity in the 1-2 μm wavelength region, beyond the range of commercially available small animal imagers. We used a collimated 980 nm laser beam to excite rare-earth-doped NaYF4:Er,Yb nanocomposites, as an example of a SWIR emitting material under development for biomedical imaging applications. This beam was raster scanned across the animal, with fluorescence in the 1550 nm wavelength region detected by an InGaAs area camera. Background adjustment and intensity non-uniformity corrections were applied in software. The final SWIR fluorescence image was overlaid onto a standard white-light image for registration of contrast agent uptake with respect to anatomical features.

A compressed sensing approach for resolution improvement in fiber-bundle based endomicroscopy

Endomicroscopy techniques such as confocal, multi-photon, and wide-field imaging have all been demonstrated using coherent fiber-optic imaging bundles. While the narrow diameter and flexibility of fiber bundles is clinically advantageous, the number of resolvable points in an image is conventionally limited to the number of individual fibers within the bundle. We are introducing concepts from the compressed sensing (CS) field to fiber bundle based endomicroscopy, to allow images to be recovered with more resolvable points than fibers in the bundle. The distal face of the fiber bundle is treated as a low-resolution sensor with circular pixels (fibers) arranged in a hexagonal lattice. A spatial light modulator is located conjugate to the object and distal face, applying multiple high resolution masks to the intermediate image prior to propagation through the bundle. We acquire images of the proximal end of the bundle for each (known) mask pattern and then apply CS inversion algorithms to recover a single high-resolution image. We first developed a theoretical forward model describing image formation through the mask and fiber bundle. We then imaged objects through a rigid fiber bundle and demonstrate that our CS endomicroscopy architecture can recover intra-fiber details while filling inter-fiber regions with interpolation. Finally, we examine the relationship between reconstruction quality and the ratio of the number of mask elements to the number of fiber cores, finding that images could be generated with approximately 28,900 resolvable points for a 1,000 fiber region in our platform.

Rare-earth doped nanocomposites enable multiscale targeted short-wave infrared imaging of metastatic breast cancer

We are investigating the ability of targeted rare earth (RE) doped nanocomposites to detect and track micrometastatic breast cancer lesions to distant sites in pre-clinical in vivo models. Functionalizing RE nanocomposites with AMD3100 promotes targeting to CXCR4, a recognized marker for highly metastatic disease. Mice were inoculated with SCP-28 (CXCR4 positive) and 4175 (CXCR4 negative) cell lines. Whole animal in vivo SWIR fluorescence imaging was performed after bioluminescence imaging confirmed tumor burden in the lungs. Line-scanning confocal fluorescence microscopy provided high-resolution imaging of RE nanocomposite uptake and native tissue autofluorescence in ex vivo lung specimens. Co-registered optical coherence tomography imaging allowed assessment of tissue microarchitecture. In conclusion, multiscale optical molecular imaging can be performed in pre-clinical models of metastatic breast cancer, using targeted RE-doped nanocomposites.

Evaluation of computational endomicroscopy architectures for minimally-invasive optical biopsy

We are investigating compressive sensing architectures for applications in endomicroscopy, where the narrow diameter probes required for tissue access can limit the achievable spatial resolution. We hypothesize that the compressive sensing framework can be used to overcome the fundamental pixel number limitation in fiber-bundle based endomicroscopy by reconstructing images with more resolvable points than fibers in the bundle. An experimental test platform was assembled to evaluate and compare two candidate architectures, based on introducing a coded amplitude mask at either a conjugate image or Fourier plane within the optical system. The benchtop platform consists of a common illumination and object path followed by separate imaging arms for each compressive architecture. The imaging arms contain a digital micromirror device (DMD) as a reprogrammable mask, with a CCD camera for image acquisition. One arm has the DMD positioned at a conjugate image plane (“IP arm”), while the other arm has the DMD positioned at a Fourier plane (“FP arm”). Lenses were selected and positioned within each arm to achieve an element-to-pixel ratio of 16 (230,400 mask elements mapped onto 14,400 camera pixels). We discuss our mathematical model for each system arm and outline the importance of accounting for system non-idealities. Reconstruction of a 1951 USAF resolution target using optimization-based compressive sensing algorithms produced images with higher spatial resolution than bicubic interpolation for both system arms when system non-idealities are included in the model. Furthermore, images generated with image plane coding appear to exhibit higher spatial resolution, but more noise, than images acquired through Fourier plane coding.

Computational imaging through a fiber-optic bundle

Compressive sensing (CS) has proven to be a viable method for reconstructing high-resolution signals using low-resolution measurements. Integrating CS principles into an optical system allows for higher-resolution imaging using lower-resolution sensor arrays. In contrast to prior works on CS-based imaging, our focus in this paper is on imaging through fiber-optic bundles, in which manufacturing constraints limit individual fiber spacing to around 2 μm. This limitation essentially renders fiber-optic bundles as low-resolution sensors with relatively few resolvable points per unit area. These fiber bundles are often used in minimally invasive medical instruments for viewing tissue at macro and microscopic levels. While the compact nature and flexibility of fiber bundles allow for excellent tissue access in-vivo, imaging through fiber bundles does not provide the fine details of tissue features that is demanded in some medical situations. Our hypothesis is that adapting existing CS principles to fiber bundle-based optical systems will overcome the resolution limitation inherent in fiber-bundle imaging. In a previous paper we examined the practical challenges involved in implementing a highly parallel version of the single-pixel camera while focusing on synthetic objects. This paper extends the same architecture for fiber-bundle imaging under incoherent illumination and addresses some practical issues associated with imaging physical objects. Additionally, we model the optical non-idealities in the system to get lower modelling errors.

Early detection and longitudinal imaging of cancer micrometastases using biofunctionalized rare-earth albumin nanocomposites

Success of personalized medicine in cancer therapy depends on the ability to identify and molecularly phenotype tumors. Current clinical imaging techniques cannot be integrated with precision molecular medicine at the level of single cells or microlesions due to limited resolution. In this work we use molecularly targeted infrared emitting optical probes to identify and characterize metastatic microlesions prior to their detection with clinically relevant imaging modalities. These contrast agents form the basis of an in vivo optical imaging system capable of resolving internal microlesions, filling a critical unmet need in cancer imaging.

Large area 3-D optical coherence tomography imaging of lumpectomy specimens for radiation treatment planning

Our long term goal is to develop a high-resolution imaging method for comprehensive assessment of tissue removed during lumpectomy procedures. By identifying regions of high-grade disease within the excised specimen, we aim to develop patient-specific post-operative radiation treatment regimens. We have assembled a benchtop spectral-domain optical coherence tomography (SD-OCT) system with 1320 nm center wavelength. Automated beam scanning enables “sub-volumes” spanning 5 mm x 5 mm x 2 mm (500 A-lines x 500 B-scans x 2 mm in depth) to be collected in under 15 seconds. A motorized sample positioning stage enables multiple sub-volumes to be acquired across an entire tissue specimen. Sub-volumes are rendered from individual B-scans in 3D Slicer software and en face (XY) images are extracted at specific depths. These images are then tiled together using MosaicJ software to produce a large area en face view (up to 40 mm x 25 mm). After OCT imaging, specimens were sectioned and stained with HE, allowing comparison between OCT image features and disease markers on histopathology. This manuscript describes the technical aspects of image acquisition and reconstruction, and reports initial qualitative comparison between large area en face OCT images and HE stained tissue sections. Future goals include developing image reconstruction algorithms for mapping an entire sample, and registering OCT image volumes with clinical CT and MRI images for post-operative treatment planning.

High-Resolution Imaging of Molecularly Targeted Rare-Earth Based Nanocomposites

We describe the development and testing of a line-scanning confocal microscope and integrated confocal / optical coherence tomography system for imaging biological cells and tissues labeled with molecularly-targeted rare-earth-doped nanocomposites.

Design and Characterization of a Computational Endomicroscopy Platform for Optical Biopsy

We are using compressive sensing concepts to overcome the resolution limitation imposed by discrete fibers in coherent bundle-based endomicroscopy. Resolution can be improved by integrating system-specific information into reconstruction algorithms.

High-resolution, 3-D imaging of lumpectomy tissue using optical coherence tomography

Pathology image guidance may enhance the effectiveness of adjuvant radiation treatment by identifying high-risk regions that would benefit from escalated radiation dose and low-risk regions at which little to no radiation dose is necessary. We present 3-D high-resolution optical coherence tomography (OCT) images of breast lumpectomy specimens. Formalin-fixed, paraffin-embedded lumpectomy tissue specimens and mouse breast glands were imaged with OCT in the form of multiple series of 2-D axial depth scans. The computationally-combined series of 2D images forms a reconstructed volume. Ongoing studies will establish whether these images can capture features comparable to the corresponding pathology for localized adjuvant radiation treatment planning.