Deep Few-view High-resolution Photon-counting Extremity CT at Halved Dose for a Clinical Trial.

The latest X-ray photon-counting computed tomography (PCCT) for extremity allows multi-energy high-resolution (HR) imaging for tissue characterization and material decomposition. However, both radiation dose and imaging speed need improvement for contrast-enhanced and other studies. Despite the success of deep learning methods for 2D few-view reconstruction, applying them to HR volumetric reconstruction of extremity scans for clinical diagnosis has been limited due to GPU memory constraints, training data scarcity, and domain gap issues. In this paper, we propose a deep learning-based approach for PCCT image reconstruction at halved dose and doubled speed in a New Zealand clinical trial. Particularly, we present a patch-based volumetric refinement network to alleviate the GPU memory limitation, train network with synthetic data, and use model-based iterative refinement to bridge the gap between synthetic and real-world data. The simulation and phantom experiments demonstrate consistently improved results under different acquisition conditions on both in- and off-domain structures using a fixed network. The image quality of 8 patients from the clinical trial are evaluated by three radiologists in comparison with the standard image reconstruction with a full-view dataset. It is shown that our proposed approach is essentially identical to or better than the clinical benchmark in terms of diagnostic image quality scores. Our approach has a great potential to improve the safety and efficiency of PCCT without compromising image quality.

Hitchhiking probiotic vectors to deliver ultra-small hafnia nanoparticles for 'Color' gastrointestinal tract photon counting X-ray imaging.

Gastrointestinal (GI) tract is one of the hard-to-reach target tissues for the delivery of contrast agents and drugs mediated by nanoparticles due to its harsh environment. Herein, we overcame this barrier by designing orally ingestible probiotic vectors for 'hitchhiking' ultrasmall hafnia (HfO2) (∼1-2 nm) nanoparticles. The minute-made synthesis of these nanoparticles is accomplished through a simple reduction reaction. These nanoparticles were incubated with probiotic bacteria with potential health benefits and were non-specifically taken up due to their small size. Subsequently, the bacteria were lyophilized and packed into a capsule to be administered orally as the radiopaque contrast agents for delineating the GI features. These nano-bio-hybrid entities could successfully be utilized as contrast agents in vivo in the conventional and multispectral computed tomography (CT). We demonstrated in 'color' the accumulated nanoparticles using advanced detectors of the photon counting CT. The enhanced nano-bio-interfacing capability achieved here can circumvent traditional nanoparticle solubility and delivery problems while offering a patient friendly approach for GI imaging to replace the currently practiced barium meal.

Quantitative imaging of excised osteoarthritic cartilage using spectral CT.

OBJECTIVES: To quantify iodine uptake in articular cartilage as a marker of glycosaminoglycan (GAG) content using multi-energy spectral CT. METHODS: We incubated a 25-mm strip of excised osteoarthritic human tibial plateau in 50 % ionic iodine contrast and imaged it using a small-animal spectral scanner with a cadmium telluride photon-processing detector to quantify the iodine through the thickness of the articular cartilage. We imaged both spectroscopic phantoms and osteoarthritic tibial plateau samples. The iodine distribution as an inverse marker of GAG content was presented in the form of 2D and 3D images after applying a basis material decomposition technique to separate iodine in cartilage from bone. We compared this result with a histological section stained for GAG. RESULTS: The iodine in cartilage could be distinguished from subchondral bone and quantified using multi-energy CT. The articular cartilage showed variation in iodine concentration throughout its thickness which appeared to be inversely related to GAG distribution observed in histological sections. CONCLUSIONS: Multi-energy CT can quantify ionic iodine contrast (as a marker of GAG content) within articular cartilage and distinguish it from bone by exploiting the energy-specific attenuation profiles of the associated materials. KEY POINTS: • Contrast-enhanced articular cartilage and subchondral bone can be distinguished using multi-energy CT. • Iodine as a marker of glycosaminoglycan content is quantifiable with multi-energy CT. • Multi-energy CT could track alterations in GAG content occurring in osteoarthritis.