Imaging the oxygenation distribution at a high spatial resolution in deep tissues such as bone marrow is important because it helps us in understanding the oxygenation’s role on stem cell proliferation and differentiation inside the bone marrow. Current technologies have limitations in imaging the oxygenation of deep targets. To overcome these limitations, x-ray Luminescence Computed Tomography (XLCT) has the potentials to image the oxygenation of bone marrow at a spatial resolution close to the focused x-ray beam size, which is better than 150 micrometers. In this study, oxygenation sensing films have been developed. Then, we have improved our XLCT imaging system by adding optical filters for measurements of photons at multiple wavelengths so that we are able to image the oxygenation of deep film targets. Then, we have conducted a phantom experiment to validate this approach. We obtained the oxygen concentration images by measuring the ratios of the XLCT images at two wavelengths.
Oxygenation concentration of tissue is an important factor in culturing stem cells and in studying the therapy response of cancer cells. The hypoxia bone marrow is the site to harbor cancer cells. Thus, direct high-resolution measurements of molecular O2 would provide powerful means of monitoring cultured stem cells and therapied cancer cells. We proposed an imaging approach to measure oxygenation concentration in deep tissues, based on the XLCT, with combined strengths of high chemical sensitivity and high spatial resolution. We have developed different biosensing films for oxygenation measurements and tested these films with X-ray luminescent experiments. We have also performed phantom experiments with multiple targets to validate the XLCT imaging system with measurements at two channels.
X-ray luminescence computed tomography (XLCT) is a hybrid molecular imaging modality combining the merits of both X-ray imaging (high spatial resolution) and optical imaging (high sensitivity to tracer nanophosphors). Narrow X-ray beam based XLCT imaging has been demonstrated to have the capacity of high spatial resolution imaging at the cost of the data acquisition time. We have primarily focused on improving the performance of the narrow X-ray beam based XLCT imaging. In a previous study, we proposed a scanning strategy achieved by reducing the scanning step size for improving the spatial resolution from double the X-ray beam size to close to the X-ray beam size. For the imaging speed, we recently introduced a continuous scanning scheme to replace the selective excitation scheme and used a photon counter to replace the oscilloscope to acquire measurement data, yielding a 16 times faster scanning time compared with what used in traditional XLCT systems. In addition, we developed a deep learning based XLCT reconstruction algorithm to reduce the number of projection views in a previous work. Moreover, we previously synthesized and compared biocompatible nanophosphors of distinct X-ray luminescence spectra to make multi-color XLCT imaging possible. Here, based on the previous work, we designed and built a first-of-its-kind fast and three-dimensional XLCT imaging system with the capacity of multi-wavelength measurements. A lab-made image acquisition software has been developed to control the system. We have performed physical experiments and verified the system performance.
X-ray luminescence computed tomography (XLCT) is a hybrid molecular imaging modality combining the merits of both x-ray imaging (high spatial resolution) and optical imaging (high sensitivity to tracer nanophosphors). Narrow x-ray beam based XLCT imaging has shown promise for high spatial resolution imaging, but the slow acquisition speed limits its applications for in vivo imaging. We introduced a continuous scanning scheme to replace the selective excitation scheme to improve imaging speed in a previous study. Under the continuous scanning scheme, the main factor that limits the scanning speed is the data acquisition time at each interval position. In this work, we have used a gated photon counter (SR400, Stanford Research Systems) to replace the high-speed oscilloscope (MDO3104, Tektronix) to acquire measurement data. The gated photon counter only counts the photon peaks in each measurement interval, while the oscilloscope records the entire waveform including both background noise data and photon peak data. The photon counter records much less data without losing any relevant information, which makes it ideal for super-fast three-dimensional (3D) imaging. We have built prototype XLCT imaging systems of both types and performed both single target and multiple target phantom experiments in 3D. The results have verified the feasibility of our proposed photon counter based system and good 3D imaging capabilities of XLCT within a reasonable time, yielding a 14 times faster scanning time compared with the oscilloscope based XLCT system. Now, the total scan time is reduced to 27 seconds per transverse section.
Significance: The ability to detect and localize specific molecules through tissue is important for elucidating the molecular basis of disease and treatment. Unfortunately, most current molecular imaging tools in tissue either lack high spatial resolution (e.g., diffuse optical fluorescence tomography or positron emission tomography) or lack molecular sensitivity (e.g., micro-computed tomography, μCT). X-ray luminescence imaging emerged about 10 years ago to address this issue by combining the molecular sensitivity of optical probes with the high spatial resolution of x-ray imaging through tissue. In particular, x-ray luminescence computed tomography (XLCT) has been demonstrated as a powerful technique for the high-resolution imaging of deeply embedded contrast agents in three dimensions (3D) for small-animal imaging.
Aim: To facilitate the translation of XLCT for small-animal imaging, we have designed and built a small-animal dedicated focused x-ray luminescence tomography (FXLT) scanner with a μCT scanner, synthesized bright and biocompatible nanophosphors as contrast agents, and have developed a deep-learning-based reconstruction algorithm.
Approach: The proposed FXLT imaging system was designed using computer-aided design software and built according to specifications. NaGdF4 nanophosphors doped with europium or terbium were synthesized with a silica shell for increased biocompatibility and functionalized with biotin. A deep-learning-based XLCT image reconstruction was also developed based on the residual neural network as a data synthesis method of projection views from few-view data to enhance the reconstructed image quality.
Results: We have built the FXLT scanner for small-animal imaging based on a rotational gantry. With all major imaging components mounted, the motor controlling the gantry can be used to rotate the system with a high accuracy. The synthesized nanophosphors displayed distinct x-ray luminescence emission, which enables multi-color imaging, and has successfully been bound to streptavidin-coated substrates. Lastly, numerical simulations using the proposed deep-learning-based reconstruction algorithm has demonstrated a clear enhancement in the reconstructed image quality.
Conclusions: The designed FXLT scanner, synthesized nanophosphors, and deep-learning-based reconstruction algorithm show great potential for the high-resolution molecular imaging of small animals.
X-ray luminescence imaging emerged for about a decade and combines both the high spatial resolution of x-ray imaging with the high measurement sensitivity of optical imaging, which could result in a great molecular imaging tool for small animals. So far, there are two types of x-ray luminescence computed tomography (XLCT) imaging. One uses a pencil beam x-ray for high spatial resolution at a cost of longer measurement time. The other uses cone beam x-ray to cover the whole mouse to obtain XLCT images at a very short time but with a compromised spatial resolution. Here we review these two methods in this paper and highlight the synthesized nanophosphors by different research groups.
We are building a focused x-ray luminescence tomography (FXLT) imaging system, developing a machinelearning based FXLT reconstruction algorithm, and synthesizing nanophosphors with different emission wavelengths. In this paper, we will report our current progress from these three aspects. Briefly, we mount all main components, including the focused x-ray tube, the fiber detector, and the x-ray tube and x-ray detector for a microCT system, on a rotary which is a heavy-duty ring track. A microCT scan will be performed before FXLT scan. For a FXLT scan, we will have four PMTs to measure four fiber detectors at two different wavelengths simultaneously for each linear scan position. We expect the spatial resolution of the FXLT imaging will be around 100 micrometers and a limit of detection of approximately 2 μg/mL (for Gd2O2S:Eu).
X-ray imaging is well-suited for deep tissue analysis, and is routinely used in medical diagnosis, but is normally blind to local biochemical signals. Here we describe simple passive implantable sensors that can report local chemical concentrations (e.g. pH), which are important for detecting and studying infection and other diseases or conditions. The sensors contain hydrogels with chemically-responsive swelling; the chemical concentration is determined using an X-ray to measure the position of radio-opaque markers in embedded in the hydrogel. For example, to measure local pH near the surface of an orthopedic plate, a sensor containing a polyacrylic acid hydrogel was attached to the plate. The hydrogel displayed a pH-dependent swelling, expanding approximately and moving an embedded radio-opaque tungsten marker. The sensor was calibrated in standard pH buffers and tested during bacterial growth in culture. Its response was negligibly affected by changes in temperature and sodium chloride concentration within the normal physiological range. Radiographic measurements were also performed in cadaveric tissue with the sensor attached to an implanted orthopedic plate fixed to a tibia. Pin position readings varied by 100 µm between observers surveying the same radiographs, corresponding to 0.065 pH unit precision in the range pH 4-8 (1.5 mm/pH unit). We are expanding the approach to other analytes (infection markers and mechanical strain sensors to track bone heaing), miniaturized injectable sensors, and imaging at multiple locations.
Acknowledgement: This research was supported by the following grants: NSF CHE1255535, NIH NIGMS 5P20GM103444-07, NIH 1R21EB019709-01A1, and NIH NIAMS R01 AR070305-01.
Passive chemical and mechanical sensors were developed with readout via X-ray projection imaging (plain radiography). Physicians routinely use X-rays to image anatomy and associated pathologies because they penetrate through deep tissue and show contrast between air, soft tissue, bone, and metal hardware. However, X-rays are usually blind to local biochemical information (e.g., pH) and insensitive to small biomechanical changes (e.g., in mechanical strain and pressure). Such information is critical for studying, detecting, and monitoring pathologies associated with implanted medical hardware, such as fracture non-union and implant-associated infection. We developed sensors attached to implanted medical devices to augment plain radiographs with chemical or mechanical signals shown on a radiopaque dial. For example, a polyacrylic acid-based hydrogel with pH-dependent swelling was attached to an orthopedic plate; the local pH was then determined by measuring the position of a radiopaque tungsten indicator pin embedded within the hydrogel. The pH sensor was calibrated in standard pH buffers and tested during bacterial growth in culture. Its response was negligibly affected by changes in temperature and ionic strength within the normal physiological range. Radiographic measurements were also performed in cadaveric tissue with the sensor attached to an implanted orthopedic plate fixed to a tibia. Pin position readings varied by 100 µm between observers surveying the same radiographs, corresponding to 0.065 pH unit precision in the range pH 4-8. We have also developed mechanical pin and hydraulic fluid-level sensor to amplify and display mechanical strain/bending of orthopedic implants for monitoring bone fracture healing.
An orthopaedic screw was designed with an optical tension-indicator to non-invasively quantify screw tension and monitor the load sharing between the bone and the implant. The screw both applies load to the bone, and measures this load by reporting the strain on the screw. The screw contains a colorimetric optical encoder that converts axial strain into colorimetric changes visible through the head of the screw, or luminescent spectral changes that are detected through tissue. Screws were tested under cyclic mechanical loading to mimic in-vivo conditions to verify the sensitivity, repeatability, and reproducibility of the sensor. In the absence to tissue, color was measured using a digital camera as a function of axial load on a stainless steel cannulated (hollow) orthopedic screw, modified by adding a passive colorimetric strain gauge through the central hole. The sensor was able to quantify clinically-relevant bone healing strains. The sensor exhibited good repeatability and reproducibility but also displayed hysteresis due to the internal mechanics of the screw. The strain indicator was also modified for measurement through tissue by replacing the reflective colorimetric sensor with a low-background X-ray excited optical luminescence signal. Luminescent spectra were acquired through 6 mm of chicken breast tissue. Overall, this research shows feasibility for a unique device which quantifies the strain on an orthopedic screw. Future research will involve reducing hysteresis by changing the mechanism of strain transduction in the screw, miniaturizing the luminescent strain gauge, monitoring bending as well as tension, using alternative luminescent spectral rulers based upon near infrared fluorescence or upconversion luminescence, and application to monitoring changes in pretension and load sharing during bone healing.
X-ray excited luminescent chemical imaging (XELCI) uses a combination of X-ray excitation to provide high resolution and optical detection to provide chemical sensing. A key application is to detect and study implant-associated infection. The implant is coated with a layer of X-ray scintillators which generate visible near infrared light when irradiated with an X-ray beam. This light first passes through a pH indicator dye-loaded film placed over the scintillator film in order to modulate the luminescence spectrum according to pH. The light then passes through tissue is collected and the spectral ratio measured to determine pH. A focused X-ray beam irradiates a point in the scintillator film, and a pH image is formed point-by-point by scanning the beam across the sample. The sensor and scanning system are described along with preliminary results showing images in rabbit models.
Metallic nanoparticles are known to experience enhanced optical trap strengths compared to dielectric particles due to the increased optical volume, or polarizability. In our experience, larger metallic particles (~micron) are not easily trapped because momentum effects due to reflection become significant. Hybrid particles comprised of both metal and dielectric materials can circumvent this limitation while still utilizing a larger polarizability. Heterogeneous nanosystems were fabricated by embedding/coating silica nanoparticles with gold or silver in varying amounts and distributions. These compound particles were manipulated via optical tweezers, and their trapping characteristics quantitatively and qualitatively compared to homogeneous particles of comparable size. The parameters explored include the dependence of the trapping force on the percentage of loading of gold, the size of the embedded colloids, and the distribution of metal within the surrounding matrix or on its surface.
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