Monitoring Tumor Hypoxia Using 18F-FMISO PET and Pharmacokinetics Modeling after Photodynamic Therapy

Tong, Xiaoyong; Srivatsan, Avinash; Jacobson, Orit; Yu, Wei; Wang, Zhantong; Yang, Xiangyu; Niu, Gang; Kiesewetter, Dale O.; Zheng, Hairong; Chen, Xiaoyuan

doi:10.1038/srep31551

Cited by 29 publications

(27 citation statements)

References 33 publications

(63 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The consumption of oxygen is caused by uncontrolled proliferation of cancer cells. In addition, the shutdown effects of vascular mediated by PDT would further aggravate hypoxia and in turn limit PDT efficiency 16,17 . To solve this problem, catalysts (catalase and MnO 2 ) [18][19][20] were used to improve the local O 2 partial pressure in tumors through the decomposition of endogenous H 2 O 2 .…”

mentioning

confidence: 99%

A Cu9S5 nanoparticle-based CpG delivery system for synergistic photothermal-, photodynamic- and immunotherapy

Zhou

Chen

et al. 2020

Commun Biol

View full text Add to dashboard Cite

Despite its great potential in cancer therapy, phototherapy, including photothermal therapy (PTT) and photodynamic therapy (PDT), often cause metastasis of tumors. Immunotherapy has revolutionized the cancer treatment owing to the capability of activating immune system to eliminate tumors. However, the integration of phototherapy and immunotherapy in a single nanoagent for cancer therapy is still a challenging task. Here, we fabricated (Cu 9 S 5 @mSiO 2-PpIX@MnO 2 @CpG (CSPM@CpG)) as a synergistic therapeutic model for phototherapy enhanced immunotherapy. The intracellular uptake of cytosine-phosphate-guanine (CpG) promoted the infiltration of cytotoxic T lymphocytes (CTLs) in tumor tissue, further stimulating the production of interferon gamma (IFN-γ) and remarkably elevating the immune response level. Excellent anti-tumor effects have been achieved by synergistic PTT/PDT/ immunotherapy. The metastasis of tumors was effectively inhibited by the immune response of CpG. Thus, our proposed work provides a strategy to combine phototherapy with immunotherapy to enhance the therapeutic efficiency and further inhibit metastasis of tumors.

show abstract

mentioning

confidence: 99%

A Cu9S5 nanoparticle-based CpG delivery system for synergistic photothermal-, photodynamic- and immunotherapy

Zhou

Chen

et al. 2020

Commun Biol

View full text Add to dashboard Cite

show abstract

“…The antihypoxia potential of our platform was further assessed using micro‐PET imaging measurement. Here, 18 F‐fluoromisonidazole ( 18 FMISO) was chosen as the probe . As an oxygen‐susceptible molecule, 18 FMISO could only stably exist under hypoxic condition, making it a sensitive label for monitoring hypoxia.…”

Section: Resultsmentioning

confidence: 99%

Overcoming Hypoxia by Multistage Nanoparticle Delivery System to Inhibit Mitochondrial Respiration for Photodynamic Therapy

Xia

Luo

et al. 2019

Adv Funct Materials

146

112

View full text Add to dashboard Cite

Hypoxia, as characterized by the low local oxygen, confers on cancer cells resistance to oxygen-consuming photodynamic therapy (PDT). The limited success reached by current approaches harnessing reoxygenation to enhance PDT outcome promotes the reconsideration of the design of the therapeutic approach. In this study, a multistage delivery system capable of reversing hypoxia is demonstrated. Unlike previous strategies that only expect to affect the peripheral tumor tissue, the size-shrinkable system allows those deeply located hypoxia regions to be treated. Specifically, therapeutics, including atovaquone and indocyanine green derivatives that are respectively responsible for oxidative phosphorylation blockage and PDT, are encapsulated in a gelatin nanoparticle, whose structure would rupture to promote deep penetration when facing matrix metallopeptidase 2 enzyme overexpression in tumor tissue. The antihypoxic performance of the platform has been evaluated using a variety of analyses including flow-cytometry assay, immunofluorescence, and micro-positron-emission tomography imaging. Tumor regression in animal models confirms the feasibility and effectiveness of conquering the PDT-resistance through abrogating the oxygen consumption. It is hopeful that such a strategy could shed light on the development of next-generation PDT-adjuvant treatment.

show abstract

“…In addition, when other radiotracers for PET images such as F18‐FMISO (fluoromisonidazole) or F18‐FLT are used, then specific subtumor regions are identified based on molecularly defined criteria. F18‐FMISO PET images present hypoxic tumor regions while F18‐FLT PET images efficiently identify proliferating tumor regions . In general, the identified tumor regions using molecular imaging are considerably different from anatomical CT imaging which identifies high electron density regions.…”

Section: Discussionmentioning

confidence: 99%

Simultaneous cosegmentation of tumors in PET‐CT images using deep fully convolutional networks

et al. 2019

View full text Add to dashboard Cite

Purpose To investigate the use and efficiency of 3‐D deep learning, fully convolutional networks (DFCN) for simultaneous tumor cosegmentation on dual‐modality nonsmall cell lung cancer (NSCLC) and positron emission tomography (PET)‐computed tomography (CT) images. Methods We used DFCN cosegmentation for NSCLC tumors in PET‐CT images, considering both the CT and PET information. The proposed DFCN‐based cosegmentation method consists of two coupled three‐dimensional (3D)‐UNets with an encoder‐decoder architecture, which can communicate with the other in order to share complementary information between PET and CT. The weighted average sensitivity and positive predictive values denoted as Scores, dice similarity coefficients (DSCs), and the average symmetric surface distances were used to assess the performance of the proposed approach on 60 pairs of PET/CTs. A Simultaneous Truth and Performance Level Estimation Algorithm (STAPLE) of 3 expert physicians’ delineations were used as a reference. The proposed DFCN framework was compared to 3 graph‐based cosegmentation methods. Results Strong agreement was observed when using the STAPLE references for the proposed DFCN cosegmentation on the PET‐CT images. The average DSCs on CT and PET are 0.861 ± 0.037 and 0.828 ± 0.087, respectively, using DFCN, compared to 0.638 ± 0.165 and 0.643 ± 0.141, respectively, when using the graph‐based cosegmentation method. The proposed DFCN cosegmentation using both PET and CT also outperforms the deep learning method using either PET or CT alone. Conclusions The proposed DFCN cosegmentation is able to outperform existing graph‐based segmentation methods. The proposed DFCN cosegmentation shows promise for further integration with quantitative multimodality imaging tools in clinical trials.

show abstract

Monitoring Tumor Hypoxia Using 18F-FMISO PET and Pharmacokinetics Modeling after Photodynamic Therapy

Cited by 29 publications

References 33 publications

A Cu9S5 nanoparticle-based CpG delivery system for synergistic photothermal-, photodynamic- and immunotherapy

A Cu9S5 nanoparticle-based CpG delivery system for synergistic photothermal-, photodynamic- and immunotherapy

Overcoming Hypoxia by Multistage Nanoparticle Delivery System to Inhibit Mitochondrial Respiration for Photodynamic Therapy

Simultaneous cosegmentation of tumors in PET‐CT images using deep fully convolutional networks

Contact Info

Product

Resources

About