Imaging in inflammatory arthritis: progress towards precision medicine

Exploring explainable AI features in the vocal biomarkers of lung disease

This review delves into the burgeoning field of explainable artificial intelligence (XAI) in the detection and analysis of lung diseases through vocal biomarkers. Lung diseases, often elusive in their early stages, pose a significant public health challenge. Recent advancements in AI have ushered in innovative methods for early detection, yet the black-box nature of many AI models limits their clinical applicability. XAI emerges as a pivotal tool, enhancing transparency and interpretability in AI-driven diagnostics. This review synthesizes current research on the application of XAI in analyzing vocal biomarkers for lung diseases, highlighting how these techniques elucidate the connections between specific vocal features and lung pathology. We critically examine the methodologies employed, the types of lung diseases studied, and the performance of various XAI models. The potential for XAI to aid in early detection, monitor disease progression, and personalize treatment strategies in pulmonary medicine is emphasized. Furthermore, this review identifies current challenges, including data heterogeneity and model generalizability, and proposes future directions for research. By offering a comprehensive analysis of explainable AI features in the context of lung disease detection, this review aims to bridge the gap between advanced computational approaches and clinical practice, paving the way for more transparent, reliable, and effective diagnostic tools.

Enhancing NIR-II Upconversion Monochromatic Emission for Temperature Sensing

The upconversion luminescence (UCL) in the second near-infrared window (NIR-II) is highly attractive due to its excellent performance in high-resolution bioimaging, anticounterfeiting, and temperature sensing. However, upconvertion nanoparticles (UCNPs) are normally emitted in visible light, potentially impacting the imaging quality. Here, a monochromatic Er3+-rich (NaErF4:x%Yb@NaYF4) nanoparticles with excitation at 1532 nm and emission at 978 nm is proposed, both situated in the NIR-II region. The proper proportion of Yb3+ ions doping has a positive effect on the NIR-II emission, by enhancing the cross relaxation efficiency and accelerating the energy transfer rate. Owing to the interaction between the Er3+ and Yb3+ is inhibited at low temperatures, the UCL emission intensities at visible and NIR-II regions show opposite trend with temperature changing, which establishes a fitting formula to derive temperature from the luminous intensity ratio, promoting the potential application of UCL in NIR-II regions for the temperature sensing.

Improving Magnetic Resonance Imaging and Chemodynamic Therapy Properties via Tuning the Fe(II)/Fe(III) Ratio in Hydrophilic Single-Atom Nanobowls

We developed an intrinsic hydrophilic single-atom iron nanobowl (Fe-SANB) for magnetic resonance imaging (MRI)-guided tumor microenvironment-triggered cancer therapy. Benefiting from the sufficient exposure of Fe single atoms and the intrinsic hydrophilicity of the bowl-shaped structure, the Fe-SANBs exhibited a superior performance for T1-weighted MRI with an r1 value of 11.48 mM-1 s-1, which is 3-fold higher than that of the commercial Gd-DTPA (r1 = 3.72 mM-1 s-1). After further coembedding Gd single atoms in the nanobowls, the r1 value can be greatly improved to 19.54 mM-1 s-1. In tumor microenvironment (TME), the Fe-SANBs can trigger pH-induced Fenton-like activity to generate highly toxic hydroxyl radicals for high-efficiency chemodynamic therapy (CDT). Both the MRI and CDT efficiency of these nanobowls can be optimized by tuning the ratio of Fe(II)/Fe(III) in the Fe-SANBs via controlling the calcination temperature. Furthermore, the generation of •OH at the tumor site can be accelerated via the photothermal effect of Fe-SANBs, thus promoting CDT efficacy. Both in vitro and in vivo results confirmed that our nanoplatform exhibited high T1-weighted MRI contrast, robust biocompatibility, and satisfactory tumor treatment, providing a potential nanoplatform for MRI-guided TME-triggered precise cancer therapy.

Metabolic and molecular imaging in inflammatory arthritis

It is known that metabolic shifts and tissue remodelling precede the development of visible inflammation and structural organ damage in inflammatory rheumatic diseases such as the inflammatory arthritides. As such, visualising and measuring metabolic tissue activity could be useful to identify biomarkers of disease activity already in a very early phase. Recent advances in imaging have led to the development of so-called 'metabolic imaging' tools that can detect these changes in metabolism in an increasingly accurate manner and non-invasively.Nuclear imaging techniques such as 18F-D-glucose and fibroblast activation protein inhibitor-labelled positron emission tomography are increasingly used and have yielded impressing results in the visualisation (including whole-body staging) of inflammatory changes in both early and established arthritis. Furthermore, optical imaging-based bedside techniques such as multispectral optoacoustic tomography and fluorescence optical imaging are advancing our understanding of arthritis by identifying intra-articular metabolic changes that correlate with the onset of inflammation with high precision and without the need of ionising radiation.Metabolic imaging holds great potential for improving the management of patients with inflammatory arthritis by contributing to early disease interception and improving diagnostic accuracy, thereby paving the way for a more personalised approach to therapy strategies including preventive strategies. In this narrative review, we discuss state-of-the-art metabolic imaging methods used in the assessment of arthritis and inflammation, and we advocate for more extensive research endeavours to elucidate their full field of application in rheumatology.