Radiation image reconstruction and uncertainty quantification using a Gaussian process prior.

We propose a complete framework for Bayesian image reconstruction and uncertainty quantification based on a Gaussian process prior (GPP) to overcome limitations of maximum likelihood expectation maximization (ML-EM) image reconstruction algorithm. The prior distribution is constructed with a zero-mean Gaussian process (GP) with a choice of a covariance function, and a link function is used to map the Gaussian process to an image. Unlike many other maximum a posteriori approaches, our method offers highly interpretable hyperparamters that are selected automatically with the empirical Bayes method.

3D small-scale dosimetry and tumor control of Ac radiopharmaceuticals for prostate cancer.

Radiopharmaceutical therapy using -emitting Ac is an emerging treatment for patients with advanced metastatic cancers. Measurement of the spatial dose distribution in organs and tumors is needed to inform treatment dose prescription and reduce off-target toxicity, at not only organ but also sub-organ scales. Digital autoradiography with -sensitive detection devices can measure radioactivity distributions at 20-40 resolution, but anatomical characterization is typically limited to 2D.

The United States Department of Energy and National Institutes of Health Collaboration: Medical Care Advances by Discovery in Radiation Detection.

A National Institutes of Health (NIH) and U.S. Department of Energy (DOE) Office of Science virtual workshop on shared general topics was held in July of 2021 and reported on in this publication in January of 2023.

A generalization of the maximum likelihood expectation maximization (MLEM) method: Masked-MLEM.

In our previous work on image reconstruction for single-layer collimatorless scintigraphy, we developed the min-min weighted robust least squares (WRLS) optimization algorithm to address the challenge of reconstructing images when both the system matrix and the projection data are uncertain. Whereas the WRLS algorithm has been successful in two-dimensional (2D) reconstruction, expanding it to three-dimensional (3D) reconstruction is difficult since the WRLS optimization problem is neither smooth nor strongly-convex. To overcome these difficulties and achieve robust image reconstruction in the presence of system uncertainties and projection noise, we propose a generalized iterative method based on the maximum likelihood expectation maximization (MLEM) algorithm, hereinafter referred to as the Masked-MLEM algorithm.

Coded aperture and Compton imaging for the development of Ac-based radiopharmaceuticals.

Background: Targeted alpha-particle therapy (TAT) has great promise as a cancer treatment. Arguably the most promising TAT radionuclide that has been proposed is Ac. The development of Ac-based radiopharmaceuticals has been hampered due to the lack of effective means to study the daughter redistribution of these agents in small animals at the preclinical stage.

Simultaneous Imaging of Ga-DOTA-TATE and Lu-DOTA-TATE in Murine Models of Neuroblastoma.

Ga-DOTA-TATE and Lu-DOTA-TATE are radiolabeled somatostatin analogs used to detect or treat neuroendocrine tumors. They are administered separately for either diagnostic or therapeutic purposes but little experimental data for their biokinetics are measured simultaneously in the same biological model. By co-administering Ga-DOTA-TATE and Lu-DOTA-TATE in three laboratory mice bearing two IMR32 tumor xenografts expressing different levels of somatostatin receptors (SSTRs) on their shoulders and imaging both Ga and Lu simultaneously, we investigated the relationship between the uptake of Ga-DOTA-TATE and Lu-DOTA-TATE in organs and tumors.

Small-scale (sub-organ and cellular level) alpha-particle dosimetry methods using an iQID digital autoradiography imaging system.

Targeted radiopharmaceutical therapy with alpha-particle emitters (αRPT) is advantageous in cancer treatment because the short range and high local energy deposition of alpha particles enable precise radiation delivery and efficient tumor cell killing. However, these properties create sub-organ dose deposition effects that are not easily characterized by direct gamma-ray imaging (PET or SPECT). We present a computational procedure to determine the spatial distribution of absorbed dose from alpha-emitting radionuclides in tissues using digital autoradiography activity images from an ionizing-radiation quantum imaging detector (iQID).

Free-moving Quantitative Gamma-ray Imaging.

The ability to map and estimate the activity of radiological source distributions in unknown three-dimensional environments has applications in the prevention and response to radiological accidents or threats as well as the enforcement and verification of international nuclear non-proliferation agreements. Such a capability requires well-characterized detector response functions, accurate time-dependent detector position and orientation data, a digitized representation of the surrounding 3D environment, and appropriate image reconstruction and uncertainty quantification methods. We have previously demonstrated 3D mapping of gamma-ray emitters with free-moving detector systems on a relative intensity scale using a technique called Scene Data Fusion (SDF).

Collimatorless Scintigraphy for Imaging Extremely Low Activity Targeted Alpha Therapy (TAT) with Weighted Robust Least Squares (WRLS).

A technology for imaging extremely low photon flux is an unmet need, especially in targeted alpha therapy (TAT) imaging, which requires significantly improved sensitivity to detect as many photons as possible while retaining a reasonable spatial resolution. In scintigraphy using gamma cameras, the radionuclide collimator rejects a large number of photons that are both primary photons and scattered photons, unsuitable for photon-starved imaging scenarios like imaging TAT. In this paper we develop a min-min weighted robust least squares (WRLS) algorithm to solve a general reconstruction problem with uncertainties and validate it with the extreme scenario: collimatorless scintigraphy.

Advances in Nuclear Radiation Sensing: Enabling 3-D Gamma-Ray Vision.

The enormous advances in sensing and data processing technologies in combination with recent developments in nuclear radiation detection and imaging enable unprecedented and "smarter" ways to detect, map, and visualize nuclear radiation. The recently developed concept of three-dimensional (3-D) Scene-data fusion allows us now to "see" nuclear radiation in three dimensions, in real time, and specific to radionuclides. It is based on a multi-sensor instrument that is able to map a local scene and to fuse the scene data with nuclear radiation data in 3-D while the instrument is freely moving through the scene.

Erratum: Invasive house geckos ( spp.): their current, potential and future distribution.

[This corrects the article DOI: 10.1093/cz/zox052.][This corrects the article DOI: 10.

Invasive house geckos ( spp.): their current, potential and future distribution.

In this study, we identified the current distribution of five globally distributed invasive species and predicted their potential and future distribution using species distribution models based on climate and elevation data. These species included , , , , and . We show that many regions with tropical and Mediterranean climates are suitable for most of these species.

Unbiased and biased estimators in coded aperture imaging for far field standoff detection at low count rates.

In general, the reconstructed image in coded aperture imaging is affected by the source configuration. Fenimore's balanced convolution method in conjunction with the uniformly redundant array can remove the interference due to the source configuration. As an extension of Fenimore's balanced convolution method, we present general conditions for designing an unbiased mean estimator for a far-field coded aperture imaging system with a random binary mask.

Treatment planning for molecular targeted radionuclide therapy.

Molecular targeted radionuclide therapy promises to expand the usefulness of radiation to successfully treat widespread cancer. The unique properties of radioactive tags make it possible to plan treatments by predicting the radiation absorbed dose to both tumors and normal organs, using a pre-treatment test dose of radiopharmaceutical. This requires a combination of quantitative, high-resolution, radiation-detection hardware and computerized dose-estimation software, and would ideally include biological dose-response data in order to translate radiation absorbed dose into biological effects.