npj Imaging最新文献

Radiopharmaceuticals that combine diagnostic and therapeutic isotopes are at the forefront of novel cancer treatments. A crucial element is the method of attaching radioisotopes to biomolecules using chelator-based techniques that are widely used clinically. Selection from available chelators is essential because this choice influences the physicochemical and biological characteristics of the final radiopharmaceutical. Numerous chelators exist because none fulfill all ideal conditions: rapid and complete binding to radiometals at low concentrations and with metallic impurities, high thermodynamic and kinetic stability in vivo, easy bioconjugation, and, key for this work, achieving these for many radiometals from the growing list of medical isotopes. We demonstrate how nanotechnology may change this. Ten nano-radiotracers were synthesized, incorporating radiometals such as ⁶⁸Ga, ⁶⁴Cu, ⁸⁹Zr, ^99mTc, ²⁰¹Tl, ¹¹¹In, ⁶⁷Ga, ¹⁷⁷Lu, ²²³Ra, and ²²⁵Ac into the nanoparticle core. The versatility of the platform was demonstrated through proof-of-concept experiments, including passive targeting in glioblastoma, active targeting of thrombosis, intratumoral radiotherapy in glioblastoma, and renal clearance optimization. This nanotracer addresses traditional challenges in radiopharmaceutical development, offering a single platform with consistent physicochemical and biological properties regardless of the radioisotope used for robust diagnostic and therapeutic applications.

Imaging is essential for probing cancer biology and tumor surveillance in humans. Combining isotopically labeled substrates with advanced imaging approaches yields a new platform, metabolic imaging. Although cancer metabolism research began ~100 years ago, breakthroughs in magnetic resonance imaging (MRI) like hyperpolarization, deuterium metabolic imaging, and novel probes have revolutionized our ability to appreciate deregulated glycolysis in cancer. Here, we discuss the state and future of glycolytic imaging with MRI.

Parkinson's disease (PD) is characterized by alpha-synuclein (α-syn) aggregation, dopaminergic (DA) neuron loss, and neuroinflammation. Synucleinopathy, the α-syn-related pathology, is the central to the pathogenetic processes observed in the brains of patients with PD, dementia with Lewy bodies (DLB), and multiple system atrophy (MSA). We are seeking an animal model with synucleinopathy that can comprehensively replicate these pathologies and adhere to suitable timeframes for preclinical research for positron emission tomography (PET) imaging studies. Adeno-associated virus (AAV) carrying the mutated human α-syn gene and S87N α-syn preformed fibrils (PFF) were co-injected into the left substantia nigra (SN) of mouse brains. Immunohistochemistry (IHC) and PET/CT imaging were performed at different time points to detect the key pathologies in the brain. This model resulted in accelerated α-syn pathology, detectable as early as two weeks post-injection, alongside DA neuron loss, microglial activation, reduced synaptic density, and impaired mitochondrial function within five weeks. Pathology remained spatially localized. In summary, this AAV/PFF hybrid model offers a rapid, region-specific platform for studying synucleinopathies such as PD, as well as for evaluating PET ligands for disease diagnosis and monitoring.

Gold nanoparticles (AuNPs) absorbing light in the near-infrared (NIR) range offer unparalleled benefits for both optoacoustic (OA) imaging and photothermal therapy (PTT), stemming from their ability to transform optical energy into heat. These unique theranostic capabilities are further complemented by the high sensitivity of OA signals to temperature variations. However, AuNPs typically experience rapid photodegradation when exposed to high laser intensities, which hinders their efficient monitoring with OA. To address this critical limitation, we synthesized silica-coated gold nanorods (AuNRs) featuring enhanced photostability and an absorption peak in the second NIR window (NIR-II, 1064 nm) for optimal tissue penetration. Their comprehensive evaluation under exposure to nanosecond-pulsed and continuous-wave (CW) radiation revealed that the synthesized AuNRs are photostable under laser energy densities required for efficient therapy under OA imaging guidance, which was confirmed with electron microscopy images. Real-time volumetric OA mapping of PTT-induced temperature variations was verified using simultaneous thermal camera readings, whilst post-mortem experiments in mice corroborated the viability of this theranostic approach in deep biological tissues.

Computerized features derived from medical imaging have shown great potential in building machine learning models for predicting and prognosticating disease outcomes. However, the performance of such models depends on the robustness of extracted features to institutional and acquisition variability inherent in clinical imaging. To address this challenge, we propose Variability Regularized Feature Selection (VaRFS), a framework that integrates feature variability as a regularization term to identify features that are both discriminable between outcome groups and generalizable across imaging differences. VaRFS employs a novel sparse regularization strategy within the within the Least Absolute Shrinkage and Selection Operator (LASSO) framework, for which we analytically confirm convergence guarantees as well as present an accelerated proximal variant for computational efficiency. We evaluated VaRFS across five clinical applications using over 700 multi-institutional imaging datasets, including disease detection, treatment response characterization, and risk stratification. Compared to three conventional feature selection methods, VaRFS yielded consistently higher classifier AUCs in hold-out validation; balancing reproducibility, sparsity, and discriminability in medical imaging feature selection.

Organic anion transporting polypeptides (OATPs) are hepatic membrane transporters responsible for the uptake of numerous endogenous compounds and drugs. Among these, OATP1B1 and OATP1B3 in humans, and their orthologs in other species, mediate the cellular uptake of clinically approved hepatospecific MRI contrast agents, rendering them suitable candidates for use as MRI reporter proteins. This review examines the structural biology, evolutionary divergence, and transport mechanisms of hepatic OATPs, with a focus on their capacity to serve as genetically encoded imaging reporters. We survey the uptake and imaging characteristics of clinically available and experimental contrast agents in species-specific contexts and detail how hepatic OATPs have been leveraged in preclinical models for tracking engineered cells in oncology, regenerative medicine, and immunotherapy. Special attention is given to the pioneering studies that established OATP1A1 and OATP1B3 as MRI reporter proteins, the challenges related to contrast dose and imaging timing, and the emerging solutions such as dual-reporter systems and dynamic imaging protocols. Compared to traditional labeling strategies like iron oxide nanoparticles, OATP-based reporters enable positive contrast on T1-weighted MRI, avoid signal ambiguity, and permit multimodal imaging using clinically approved probes. The integration of hepatic OATPs as MRI reporter proteins offers a translationally feasible platform for non-invasive, longitudinal imaging of therapeutic cells in clinical trials and medicine. This technology has the potential to improve safety, efficacy, and mechanistic understanding across a wide array of biomedical applications.

Efficient application of immunotherapy necessitates advanced whole-body imaging techniques to monitor sites of immune cell activation. Deoxycytidine kinase (dCK), a key enzyme in the deoxynucleotide salvage pathway, is upregulated in proliferating immune cells and can be targeted by the radiotracers [¹⁸F]FAC (preclinical) and [¹⁸F]CFA (clinical), allowing for noninvasive monitoring of immune activation in lymphatic organs via positron emission tomography (PET). In this study, we aimed to assess the efficacy of [¹⁸F]FAC in detecting immune activation upon immune checkpoint inhibitor therapy (CIT). In vitro, activated T cells and macrophages exhibited significantly higher [¹⁸F]FAC uptake compared to their naïve counterparts. In vivo, preclinical [¹⁸F]FAC-PET/MRI revealed a CIT-induced significant increase in [¹⁸F]FAC uptake in tumor-draining lymph nodes (TDLNs) compared to contralateral lymph nodes, independent of tumor responsiveness. This phenomenon was absent in TDLNs of sham-treated experimental mice. Ex vivo cell sorting further confirmed elevated [¹⁸F]FAC uptake in T cells from TDLNs following CIT. Consistently, [¹⁸F]CFA-PET/CT imaging in metastatic melanoma patients demonstrated CIT-induced enhanced regional LN uptake. Together, these findings establish a strong correlation between CIT-induced immune activation and [¹⁸F]FAC/[¹⁸F]CFA uptake, underscoring the critical role of TDLNs in cancer immuotherapy. The radiotracers [¹⁸F]FAC and [¹⁸F]CFA provide valuable tools for noninvasive monitoring of immune cell activation, potentially unveiling tumor-microenvironment-related resistance mechanisms and advancing the utility of PET imaging in immunotherapy monitoring and patient stratification.

Renal cell carcinomas (RCCs) have multiple subtypes that are difficult to distinguish using imaging alone. This study characterises renal tumour microstructure using diffusion MRI (dMRI) and the Vascular, Extracellular and Restricted Diffusion for Cytometry in Tumours (VERDICT)-MRI framework. Patients were prospectively recruited from the RIM trial (ClinicalTrials.gov: NCT07173140, 20/11/2024). Fourteen patients with 17 renal tumours (including benign and various RCC subtypes) underwent dMRI using nine b-values (0-2500 s/mm²). A three-compartment VERDICT model was fitted with a self-supervised neural network. Compared to simpler dMRI models, VERDICT more accurately captured the diffusion data in tumour and healthy tissue. VERDICT revealed significant differences in intracellular volume fraction between cancerous and normal tissue, and in vascular volume fraction between vascular and non-vascular regions. A feature selection method identified a reduced 4 b-value protocol (b = [70, 150, 1000, 2000]), cutting scan time by over 30 min, enabling more efficient imaging in larger cohorts.

Current biomedical imaging focuses on spatial detail but overlooks time, limiting our understanding of disease progression. There is an unmet need for temporal atlases that align multiscale and multimodal data across defined timepoints, enabling dynamic mapping of pathophysiology. This framework will pave the way for more personalised, time-aware diagnostics and interventions.