pH-Responsive nanocomposite fibres allowing MRI monitoring of drug release

Zhang, Ziwei; Wells, Connor J. R.; King, Aaron A.; Bear, Joseph C.; Davies, G. R.; Williams, Gareth R.

doi:10.1039/d0tb01033b

Cited by 26 publications

(19 citation statements)

References 39 publications

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“…At present, targeted drug therapy is one of the standard treatments for patients with advanced liver cancer [ 17 ]. This method designs targeted therapeutic drugs for the identified carcinogenic sites at the cellular and molecular levels.…”

Section: Discussionmentioning

confidence: 99%

“…In this study, the release of diagnostic targeted drugs in MRI images was correctly defined as A, and the release error was defined as B. e actual targeted drug release was correctly defined as C, and the release error was defined as D. Accuracy referred to the proportion of correct MRI image determination samples in the total number of samples, as shown in equation (16). Precision, also known as the precision ratio, represented the proportion of actual targeted release correct samples in the total samples, as shown in equation (17). Sensitivity, also known as recall rate, represented the proportion of correct samples determined by MRI images among all correct samples in actual targeted release, as shown in equation (18).…”

Section: Evaluation Of Mri Image Segmentation Effect Based Onmentioning

confidence: 99%

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The Value of Convolutional Neural Network-Based Magnetic Resonance Imaging Image Segmentation Algorithm to Guide Targeted Controlled Release of Doxorubicin Nanopreparation

Liu

Gao

Jia

2021

Contrast Media & Molecular Imaging

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There was an investigation of the auxiliary role of convolutional neural network- (CNN-) based magnetic resonance imaging (MRI) image segmentation algorithm in MRI image-guided targeted drug therapy of doxorubicin nanomaterials so that the value of drug-controlled release in liver cancer patients was evaluated. In this study, 80 patients with liver cancer were selected as the research objects. It was hoped that the CNN-based MRI image segmentation algorithm could be applied to the guided analysis of MRI images of the targeted controlled release of doxorubicin nanopreparation to analyze the imaging analysis effect of this algorithm on the targeted treatment of liver cancer with doxorubicin nanopreparation. The results of this study showed that the upgraded three-dimensional (3D) CNN-based MRI image segmentation had a better effect compared with the traditional CNN-based MRI image segmentation, with significant improvement in indicators such as accuracy, precision, sensitivity, and specificity, and the differences were all statistically marked ( p < 0.05 ). In the monitoring of the targeted drug therapy of doxorubicin nanopreparation for liver cancer patients, it was found that the MRI images of liver cancer patients processed by 3D CNN-based MRI image segmentation neural algorithm could be observed more intuitively and guided to accurately reach the target of liver cancer. The accuracy of targeted release determination of nanopreparation reached 80 ± 6.25%, which was higher markedly than that of the control group (66.6 ± 5.32%) ( p < 0.05 ). In a word, the MRI image segmentation algorithm based on CNN had good application potential in guiding patients with liver cancer for targeted therapy with doxorubicin nanopreparation, which was worth promoting in the adjuvant treatment of targeted drugs for cancer.

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Section: Discussionmentioning

confidence: 99%

Section: Evaluation Of Mri Image Segmentation Effect Based Onmentioning

confidence: 99%

The Value of Convolutional Neural Network-Based Magnetic Resonance Imaging Image Segmentation Algorithm to Guide Targeted Controlled Release of Doxorubicin Nanopreparation

Liu

Gao

Jia

2021

Contrast Media & Molecular Imaging

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“…91 This work was recently built upon by Zhang et al, who prepared Eudragit fibres loaded with an anticancer drug and Fe oxide nanoparticles. 92 It was shown that there was a direct correlation between the extent of drug release and the MRI signal, which could potentially allow for indirect monitoring of drug release.…”

Section: Theranostic Formulationsmentioning

confidence: 99%

Electrospinning for healthcare: recent advancements

Dziemidowicz

Sang

et al. 2021

J. Mater. Chem. B

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“…Zhang et al [101] explored pH-responsive nanocomposite fibers for magnetic resonance imaging (MRI) drug release monitoring. In their study, composite pH-sensitive NFs were produced via electrospinning.…”

Section: Phmentioning

confidence: 99%

On-Demand Drug Delivery Systems Using Nanofibers

2021

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On-demand drug-delivery systems using nanofibers are extensively applicable for customized drug release based on target location and timing to achieve the desired therapeutic effects. A nanofiber formulation is typically created for a certain medication and changing the drug may have a significant impact on the release kinetics from the same delivery system. Nanofibers have several distinguishing features and properties, including the ease with which they may be manufactured, the variety of materials appropriate for processing into fibers, a large surface area, and a complex pore structure. Nanofibers with effective drug-loading capabilities, controllable release, and high stability have gained the interest of researchers owing to their potential applications in on-demand drug delivery systems. Based on their composition and drug-release characteristics, we review the numerous types of nanofibers from the most recent accessible studies. Nanofibers are classified based on their mechanism of drug release, as well as their structure and content. To achieve controlled drug release, a suitable polymer, large surface-to-volume ratio, and high porosity of the nanofiber mesh are necessary. The properties of nanofibers for modified drug release are categorized here as protracted, stimulus-activated, and biphasic. Swellable or degradable polymers are commonly utilized to alter drug release. In addition to the polymer used, the process and ambient conditions can have considerable impacts on the release characteristics of the nanofibers. The formulation of nanofibers is highly complicated and depends on many variables; nevertheless, numerous options are available to accomplish the desired nanofiber drug-release characteristics.

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pH-Responsive nanocomposite fibres allowing MRI monitoring of drug release

Abstract:
pH-responsive nanofibres containing iron oxide nanoparticles (NPs) and a model drug demonstrate on-demand dissolution, triggering release of both drug and NPs and allowing magnetic resonance imaging-guided therapeutic delivery.

Cited by 26 publications

References 39 publications

The Value of Convolutional Neural Network-Based Magnetic Resonance Imaging Image Segmentation Algorithm to Guide Targeted Controlled Release of Doxorubicin Nanopreparation

The Value of Convolutional Neural Network-Based Magnetic Resonance Imaging Image Segmentation Algorithm to Guide Targeted Controlled Release of Doxorubicin Nanopreparation

Electrospinning for healthcare: recent advancements

On-Demand Drug Delivery Systems Using Nanofibers

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pH-Responsive nanocomposite fibres allowing MRI monitoring of drug release

Abstract: pH-responsive nanofibres containing iron oxide nanoparticles (NPs) and a model drug demonstrate on-demand dissolution, triggering release of both drug and NPs and allowing magnetic resonance imaging-guided therapeutic delivery.

Cited by 26 publications

References 39 publications

The Value of Convolutional Neural Network-Based Magnetic Resonance Imaging Image Segmentation Algorithm to Guide Targeted Controlled Release of Doxorubicin Nanopreparation

The Value of Convolutional Neural Network-Based Magnetic Resonance Imaging Image Segmentation Algorithm to Guide Targeted Controlled Release of Doxorubicin Nanopreparation

Electrospinning for healthcare: recent advancements

On-Demand Drug Delivery Systems Using Nanofibers

Contact Info

Product

Resources

About

Abstract:
pH-responsive nanofibres containing iron oxide nanoparticles (NPs) and a model drug demonstrate on-demand dissolution, triggering release of both drug and NPs and allowing magnetic resonance imaging-guided therapeutic delivery.