scholarly journals Gadolinium and Platinum in Tandem: Real-time Multi-Modal Monitoring of Drug Delivery by MRI and Fluorescence Imaging

2017 ◽  
Vol 1 (2) ◽  
pp. 186-195 ◽  
Author(s):  
Hongguang Li ◽  
Bethany I. Harriss ◽  
Alkystis Phinikaridou ◽  
Sara Lacerda ◽  
Gregory Ramniceanu ◽  
...  
Keyword(s):  
Drug Delivery ◽  
Real Time ◽  
Fluorescence Imaging

scholarly journals Real-time fluorescence imaging for visualization and drug uptake prediction during drug delivery by thermosensitive liposomes

2019 ◽  
Vol 36 (1) ◽  
pp. 816-825 ◽  
Author(s):  
Anjan Motamarry ◽  
Ayele H. Negussie ◽  
Christian Rossmann ◽  
James Small ◽  
A. Marissa Wolfe ◽  
...  
Keyword(s):  
Drug Delivery ◽  
Real Time ◽  
Fluorescence Imaging ◽  
Drug Uptake ◽  
Thermosensitive Liposomes

scholarly journals pH and redox dual-sensitive drug delivery system constructed based on fluorescent carbon dots

RSC Advances ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 2656-2663
Author(s):  
Boye Zhang ◽  
Qianqian Duan ◽  
Yi Li ◽  
Jianming Wang ◽  
Wendong Zhang ◽  
...  
Keyword(s):  
Drug Delivery ◽  
Controlled Release ◽  
Cancer Cells ◽  
Fluorescence Imaging ◽  
Drug Delivery System ◽  
Delivery System ◽  
Carbon Dots ◽  
Ph Responsive ◽  
Charge Reversal ◽  
Fluorescent Carbon Dots

The system is pH-responsive and redox-controlled release. And the charge reversal and size transitions of the system can enhance the targeted ability. Moreover, the system can recognize the cancer cells by the fluorescence imaging.

scholarly journals Real-time fluorescence imaging of anthocyanins complexed with diphenylboric acid 2-aminoethyl inside B16–F10 melanoma cells

2021 ◽  
Vol 189 ◽  
pp. 112849
Author(s):  
Madalina Nistor ◽  
Monica Focsan ◽  
Luiza Gaina ◽  
Mihai Cenariu ◽  
Adela Pintea ◽  
...  
Keyword(s):  
Real Time ◽  
Fluorescence Imaging ◽  
Melanoma Cells

Real-time quantitative monitoring of in vitro nasal drug delivery by a nasal epithelial mucosa-on-a-chip model

2021 ◽  
Author(s):  
Hanieh Gholizadeh ◽  
Hui Xin Ong ◽  
Peta Bradbury ◽  
Agisilaos Kourmatzis ◽  
Daniela Traini ◽  
...  
Keyword(s):  
Drug Delivery ◽  
Real Time ◽  
Nasal Drug Delivery ◽  
Quantitative Monitoring

scholarly journals Real-time intraoperative glioma diagnosis using fluorescence imaging and deep convolutional neural networks

2021 ◽  
Author(s):  
Biluo Shen ◽  
Zhe Zhang ◽  
Xiaojing Shi ◽  
Caiguang Cao ◽  
Zeyu Zhang ◽  
...  
Keyword(s):  
Neural Networks ◽  
Real Time ◽  
Fluorescence Imaging ◽  
Convolutional Neural Networks ◽  
Frozen Section ◽  
Fluorescent Imaging ◽  
Pathological Diagnosis ◽  
Pathological Examination ◽  
Deep Convolutional Neural Networks ◽  
Fluorescence Images

Abstract Purpose Surgery is the predominant treatment modality of human glioma but suffers difficulty on clearly identifying tumor boundaries in clinic. Conventional practice involves neurosurgeon’s visual evaluation and intraoperative histological examination of dissected tissues using frozen section, which is time-consuming and complex. The aim of this study was to develop fluorescent imaging coupled with artificial intelligence technique to quickly and accurately determine glioma in real-time during surgery. Methods Glioma patients (N = 23) were enrolled and injected with indocyanine green for fluorescence image–guided surgery. Tissue samples (N = 1874) were harvested from surgery of these patients, and the second near-infrared window (NIR-II, 1000–1700 nm) fluorescence images were obtained. Deep convolutional neural networks (CNNs) combined with NIR-II fluorescence imaging (named as FL-CNN) were explored to automatically provide pathological diagnosis of glioma in situ in real-time during patient surgery. The pathological examination results were used as the gold standard. Results The developed FL-CNN achieved the area under the curve (AUC) of 0.945. Comparing to neurosurgeons’ judgment, with the same level of specificity >80%, FL-CNN achieved a much higher sensitivity (93.8% versus 82.0%, P < 0.001) with zero time overhead. Further experiments demonstrated that FL-CNN corrected >70% of the errors made by neurosurgeons. FL-CNN was also able to rapidly predict grade and Ki-67 level (AUC 0.810 and 0.625) of tumor specimens intraoperatively. Conclusion Our study demonstrates that deep CNNs are better at capturing important information from fluorescence images than surgeons’ evaluation during patient surgery. FL-CNN is highly promising to provide pathological diagnosis intraoperatively and assist neurosurgeons to obtain maximum resection safely. Trial registration ChiCTR ChiCTR2000029402. Registered 29 January 2020, retrospectively registered

A Magnetically Guided Self‐Rolled Microrobot for Targeted Drug Delivery, Real‐Time X‐Ray Imaging, and Microrobot Retrieval

2021 ◽  
pp. 2001681
Author(s):  
Kim Tien Nguyen ◽  
Gwangjun Go ◽  
Zhen Jin ◽  
Bobby Aditya Darmawan ◽  
Ami Yoo ◽  
...  
Keyword(s):  
Drug Delivery ◽  
Real Time ◽  
Targeted Drug Delivery ◽  
X Ray ◽  
X Ray Imaging ◽  
Targeted Drug

Exploiting the Nanoparticle Plasmon Effect: Observing Drug Delivery Dynamics in Single Cells via Raman/Fluorescence Imaging Spectroscopy

ACS Nano ◽  
2013 ◽  
Vol 7 (8) ◽  
pp. 7420-7427 ◽  
Author(s):  
Bin Kang ◽  
Marwa M. Afifi ◽  
Lauren A. Austin ◽  
Mostafa A. El-Sayed
Keyword(s):  
Drug Delivery ◽  
Fluorescence Imaging ◽  
Single Cells ◽  
Imaging Spectroscopy ◽  
Plasmon Effect

scholarly journals Interventional MRI-guided catheter placement and real time drug delivery to the central nervous system

2016 ◽  
Vol 16 (6) ◽  
pp. 635-639 ◽  
Author(s):  
Seunggu J. Han ◽  
Krystof Bankiewicz ◽  
Nicholas A. Butowski ◽  
Paul S. Larson ◽  
Manish K. Aghi
Keyword(s):  
Drug Delivery ◽  
Central Nervous System ◽  
Nervous System ◽  
Real Time ◽  
Interventional Mri ◽  
Catheter Placement ◽  
The Central Nervous System ◽  
Mri Guided
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