Quantitative phosphor imaging autoradiography of radioligands for positron emission tomography

Blind Image Restoration Enhances Digital Autoradiographic Imaging of Radiopharmaceutical Tissue Distribution

Digital autoradiography (DAR) is a powerful tool to quantitatively determine the distribution of a radiopharmaceutical within a tissue section and is widely used in drug discovery and development. However, the low image resolution and significant background noise can result in poor correlation, even errors, between radiotracer distribution, anatomical structure, and molecular expression profiles. Differing from conventional optical systems, the point spread function (PSF) in DAR is determined by properties of radioisotope decay, phosphor and digitizer. Calibration of an experimental PSF a priori is difficult, prone to error, and impractical. We have developed a content-adaptive restoration algorithm to address these problems. Methods: We model the DAR imaging process using a mixed Poisson-Gaussian model, and blindly restore the image by a Penalized Maximum-Likelihood Expectation-Maximization algorithm (PG- PEM). PG-PEM implements a patch-based estimation algorithm with "Density-Based Spatial Clus- tering of Applications with Noise" to estimate noise parameters, and utilizes L2 and Hessian Frobenius (HF) norms as regularization functions to improve performance. Results: First, PG-PEM outperformed other restoration algorithms at the denoising task (p<0.01). Next, we implemented PG-PEM on pre-clinical DAR images (¹⁸F-FDG treated mice tumor and heart, ¹⁸F-NaF treated mice femur) and clinical DAR images (bone biopsy sections from ²²³RaCl2 treated castrate resistant prostate cancer patients). DAR images restored by PG-PEM of all samples achieved significantly higher effective resolution, contrast to noise ratio (CNR), and a lower standard deviation of background (STDB) (p<0.0001). Additionally, by comparing the registration results between the clinical DAR images and the segmented bone masks from the corresponding histological images, the radiopharmaceutical distribution was significantly improved (p<0.0001). Conclusion: PG-PEM is able to increase resolution and contrast while robustly accounting for DAR noise, and demonstrates the capacity to be widely implemented to improve pre- and clinical DAR imaging of radiopharmaceutical distribution.

Null functions in three-dimensional imaging of alpha and beta particles

Null functions of an imaging system are functions in the object space that give exactly zero data. Hence, they represent the intrinsic limitations of the imaging system. Null functions exist in all digital imaging systems, because these systems map continuous objects to discrete data. However, the emergence of detectors that measure continuous data, e.g. particle-processing (PP) detectors, has the potential to eliminate null functions. PP detectors process signals produced by each particle and estimate particle attributes, which include two position coordinates and three components of momentum, as continuous variables. We consider Charged-Particle Emission Tomography (CPET), which relies on data collected by a PP detector to reconstruct the 3D distribution of a radioisotope that emits alpha or beta particles, and show empirically that the null functions are significantly reduced for alpha particles if ≥3 attributes are measured or for beta particles with five attributes measured.

Charged-particle emission tomography

Purpose

Conventional charged‐particle imaging techniques — such as autoradiography — provide only two‐dimensional (2D) black ex vivo images of thin tissue slices. In order to get volumetric information, images of multiple thin slices are stacked. This process is time consuming and prone to distortions, as registration of 2D images is required. We propose a direct three‐dimensional (3D) autoradiography technique, which we call charged‐particle emission tomography (CPET). This 3D imaging technique enables imaging of thick tissue sections, thus increasing laboratory throughput and eliminating distortions due to registration. CPET also has the potential to enable in vivo charged‐particle imaging with a window chamber or an endoscope.

Methods

Our approach to charged‐particle emission tomography uses particle‐processing detectors (PPDs) to estimate attributes of each detected particle. The attributes we estimate include location, direction of propagation, and/or the energy deposited in the detector. Estimated attributes are then fed into a reconstruction algorithm to reconstruct the 3D distribution of charged‐particle‐emitting radionuclides. Several setups to realize PPDs are designed. Reconstruction algorithms for CPET are developed.

Results

Reconstruction results from simulated data showed that a PPD enables CPET if the PPD measures more attributes than just the position from each detected particle. Experiments showed that a two‐foil charged‐particle detector is able to measure the position and direction of incident alpha particles.

Conclusions

We proposed a new volumetric imaging technique for charged‐particle‐emitting radionuclides, which we have called charged‐particle emission tomography (CPET). We also proposed a new class of charged‐particle detectors, which we have called particle‐processing detectors (PPDs). When a PPD is used to measure the direction and/or energy attributes along with the position attributes, CPET is feasible.

Characterization of a double-sided silicon strip detector autoradiography system

PURPOSE

The most commonly used technology currently used for autoradiography is storage phosphor screens, which has many benefits such as a large field of view but lacks particle-counting detection of the time and energy of each detected radionuclide decay. A number of alternative designs, using either solid state or scintillator detectors, have been developed to address these issues. The aim of this study is to characterize the imaging performance of one such instrument, a double-sided silicon strip detector (DSSD) system for digital autoradiography. A novel aspect of this work is that the instrument, in contrast to previous prototype systems using the same detector type, provides the ability for user accessible imaging with higher throughput. Studies were performed to compare its spatial resolution to that of storage phosphor screens and test the implementation of multiradionuclide ex vivo imaging in a mouse preclinical animal study.

METHODS

Detector background counts were determined by measuring a nonradioactive sample slide for 52 h. Energy spectra and detection efficiency were measured for seven commonly used radionuclides under representative conditions for tissue imaging. System dead time was measured by imaging (18)F samples of at least 5 kBq and studying the changes in count rate over time. A line source of (58)Co was manufactured by irradiating a 10 μm nickel wire with fast neutrons in a research reactor. Samples of this wire were imaged in both the DSSD and storage phosphor screen systems and the full width at half maximum (FWHM) measured for the line profiles. Multiradionuclide imaging was employed in a two animal study to examine the intratumoral distribution of a (125)I-labeled monoclonal antibody and a (131)I-labeled engineered fragment (diabody) injected in the same mouse, both targeting carcinoembryonic antigen.

RESULTS

Detector background was 1.81 × 10(-6) counts per second per 50 × 50 μm pixel. Energy spectra and detection efficiency were successfully measured for seven radionuclides. The system dead time was measured to be 59 μs, and FWHM for a (58)Co line source was 154 ± 14 μm for the DSSD system and 343 ± 15 μm for the storage phosphor system. Separation of the contributions from (125)I and (131)I was performed on autoradiography images of tumor sections.

CONCLUSIONS

This study has shown that a DSSD system can be beneficially applied for digital autoradiography with simultaneous multiradionuclide imaging capability. The system has a low background signal, ability to image both low and high activity samples, and a good energy resolution.