Imaging drug delivery to the lungs: Methods and applications in oncology

Man, Francis; Tang, Jie; Swedrowska, Magda; Forbes, Ben; Rosales, Rafael T. M. de

doi:10.1016/j.addr.2022.114641

Cited by 8 publications

(3 citation statements)

References 263 publications

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“…In addition, the deposition rate varies with NPs properties, like size, shape, density, hydrophobicity, and charge, and is also influenced by physiological parameters, such as airway geometry, flowrate, lung morphology, lung surfactant, breathing pattern, and mucociliary clearance (Borghardt et al, 2018). Moreover, the deposition efficiency of pulmonary‐delivered NPs is affected by the location and size of lung tumors (Man et al, 2023). It is well established that negatively charged tumor cell plasma membranes have a higher affinity to absorb neutral or positively charged than negatively charged NPs (Cheng et al, 2022), and the NP morphology correlates with the systemic adverse effects or immune effects (W. Zhang et al, 2022).…”

Section: Respiratory Routes For Pulmonary Nps Delivery Challenges And...mentioning

confidence: 99%

“…Moreover, the drug may retrograde through the tissue channels formed by the needle. In comparison, nano‐particles, irrespective of their possession of targeting properties, demonstrate effective tumor accumulation through the adhesion and retention (EPR) effect (Man et al, 2023). Furthermore, the modification of nano‐particles can enhance their targeted delivery to lung tumors, thereby mitigating off‐target‐induced side effects (Shi et al, 2023).…”

Section: Comparison With Other Existing Techniquesmentioning

confidence: 99%

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Pulmonary delivery of nano‐particles for lung cancer diagnosis and therapy: Recent advances and future prospects

Han,

Wang

et al. 2023

WIREs Nanomed Nanobiotechnol

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Although our understanding of lung cancer has significantly improved in the past decade, it is still a disease with a high incidence and mortality rate. The key reason is that the efficacy of the therapeutic drugs is limited, mainly due to insufficient doses of drugs delivered to the lungs. To achieve precise lung cancer diagnosis and treatment, nano‐particles (NPs) pulmonary delivery techniques have attracted much attention and facilitate the exploration of the potential of those in inhalable NPs targeting tumor lesions. Since the therapeutic research focusing on pulmonary delivery NPs has rapidly developed and evolved substantially, this review will mainly discuss the current developments of pulmonary delivery NPs for precision lung cancer diagnosis and therapy.This article is categorized under: Therapeutic Approaches and Drug Discovery > Nanomedicine for Respiratory Disease Therapeutic Approaches and Drug Discovery > Emerging Technologies Diagnostic Tools > In Vivo Nanodiagnostics and Imaging

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Section: Respiratory Routes For Pulmonary Nps Delivery Challenges And...mentioning

confidence: 99%

Section: Comparison With Other Existing Techniquesmentioning

confidence: 99%

Pulmonary delivery of nano‐particles for lung cancer diagnosis and therapy: Recent advances and future prospects

Han,

Wang

et al. 2023

WIREs Nanomed Nanobiotechnol

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“…PB-XLCT offers superior image quality through selective excitation, albeit at the cost of longer scan durations. While certain techniques, such as the continuous scanning scheme [18,19], have been shown to enhance imaging efficiency, their imaging geometry necessitates linear steps that are not conducive to rapid imaging, such as in the case of drug biokinetics [20]. The scanning time of cone-beam XLCT is significantly reduced due to the simultaneous irradiation of the entire object.…”

Section: Introductionmentioning

confidence: 99%

Automated Restarting Fast Proximal Gradient Descent Method for Single-View Cone-Beam X-ray Luminescence Computed Tomography Based on Depth Compensation

Gao,

Pu,

Liu

et al. 2024

Bioengineering

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Single-view cone-beam X-ray luminescence computed tomography (CB-XLCT) has recently gained attention as a highly promising imaging technique that allows for the efficient and rapid three-dimensional visualization of nanophosphor (NP) distributions in small animals. However, the reconstruction performance is hindered by the ill-posed nature of the inverse problem and the effects of depth variation as only a single view is acquired. To tackle this issue, we present a methodology that integrates an automated restarting strategy with depth compensation to achieve reconstruction. The present study employs a fast proximal gradient descent (FPGD) method, incorporating L0 norm regularization, to achieve efficient reconstruction with accelerated convergence. The proposed approach offers the benefit of retrieving neighboring multitarget distributions without the need for CT priors. Additionally, the automated restarting strategy ensures reliable reconstructions without the need for manual intervention. Numerical simulations and physical phantom experiments were conducted using a custom CB-XLCT system to demonstrate the accuracy of the proposed method in resolving adjacent NPs. The results showed that this method had the lowest relative error compared to other few-view techniques. This study signifies a significant progression in the development of practical single-view CB-XLCT for high-resolution 3−D biomedical imaging.

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