Investigation of injection dose and camera integration time on quantifying pharmacokinetics of a Cy5.5-GX1 probe with dynamic fluorescence imaging<i>in vivo</i>

Dai, Yunpeng; Chen, Xueli; Yin, Jiaqi; Kang, Xiaoyu; Wang, Guodong; Zhang, Xianghan; Nie, Yongzhan; Wu, Kaichun; Liang, Jimin

doi:10.1117/1.jbo.21.8.086001

Cited by 7 publications

(4 citation statements)

References 34 publications

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“…The imaging of gastric cancer using tumor vascular-targeted peptides and molecular imaging technology is an important method for the early diagnosis of gastric cancer (26,27). We sought to use GX1 with independent intellectual property rights to image gastric cancer (28)(29)(30)(31). However, previous studies found that the targeting and affinity of GX1 still need to be improved, and there is still some distance to go before application.…”

Section: Discussionmentioning

confidence: 99%

68Ga-Labeled GX1 Dimer: A Novel Probe for PET/Cerenkov Imaging Targeting Gastric Cancer

Yin

Xin²,

Zhang

et al. 2021

Front. Oncol.

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PurposeTo synthesize the dimer of GX1 and identify whether its affinity and targeting are better than those of GX1. To prepare 68Ga-DOTA-KEK-(GX1)2 and to apply it to PET and Cerenkov imaging of gastric cancer.Methods68Ga-DOTA-KEK-(GX1)2 was prepared, and the labeling yield and stability were determined. Its specificity and affinity were verified using an in vitro cell binding assay and competitive inhibition test, cell immunofluorescence, and cell uptake and efflux study. Its tumor-targeting ability was determined by nano PET/CT and Cerenkov imaging, standardized uptake value (SUV), signal-to-background ratio (SBR) quantification, and a biodistribution study in tumor-bearing nude mice.Results68Ga-DOTA-KEK-(GX1)2 was successfully prepared, and the labeling yield was more than 97%. It existed stably for 90 min in serum. The binding of 68Ga-DOTA-KEK-(GX1)2 to cocultured HUVECs (Co-HUVECs) was higher than that to human umbilical vein endothelial cells (HUVECs), BGC823 cells, and GES cells. It was also higher than that of 68Ga-DOTA-GX1, indicating that the dimer did improve the specificity and affinity of GX1. The binding of KEK-(GX1)2 to Co-HUVECs was significantly higher than that of GX1. Additionally, the uptake of 68Ga-DOTA-KEK-(GX1)2 by Co-HUVECs was higher than that of 68Ga-DOTA-GX1 and reached a maximum at 60 min. Nano PET/CT and Cerenkov imaging showed that the tumor imaging of the nude mice injected with 68Ga-DOTA-KEK-(GX1)2 was clear, and the SUV and SBR value of the tumor sites were significantly higher than those of the nude mice injected with 68Ga-DOTA-GX1, indicating that the probe had better targeting in vivo. Finally, the biodistribution showed quantitatively that when organs such as the kidney and liver metabolized rapidly, the radioactivity of the tumor site of the nude mice injected with 68Ga-DOTA-KEK-(GX1)2 decreased relatively slowly. At the same time, the percentage of injected dose per gram (%ID/g) of the tumor site was higher than that of other normal organs except the liver and kidney at 60 min, which indicated that the tumor had good absorption of the probe.ConclusionGX1 was modified successfully, and the in vivo and in vitro properties of the GX1 dimer were significantly better than those of GX1. The imaging probe, 68Ga-DOTA-KEK-(GX1)2, was successfully prepared, which provides a candidate probe for PET and Cerenkov diagnosis of gastric cancer.

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Section: Discussionmentioning

confidence: 99%

68Ga-Labeled GX1 Dimer: A Novel Probe for PET/Cerenkov Imaging Targeting Gastric Cancer

Yin

Xin²,

Zhang

et al. 2021

Front. Oncol.

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“…After collecting five background images, the Cy5.5-GX1 was intravenously injected with a dose of 2 nmol [17]. Then, we collected dynamic fluorescent images for 63 minutes immediately after the injection of the probe.…”

Section: Dynamic Fluorescence Imagesmentioning

confidence: 99%

“…If we can get relatively robust dynamic parameters in case of missing some time points immediately after the injection of the probe, the experimental operations can be much simpler. In current dynamic FI, the sampling sparsity and sampling uniformity were usually empirically determined [8][9][10][11][12][13]. Too small a sampling interval results in heavier camera burden and data processing burden, but too large a sampling interval results in an unsatisfactory recovery of the time activity curve (TAC), which may affect the accuracy of the determination of kinetic parameters.…”

Section: Introductionmentioning

confidence: 99%

Investigation of the influence of sampling schemes on quantitative dynamic fluorescence imaging

Dai

Chen

Yin

et al. 2018

Biomed. Opt. Express

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Dynamic optical data from a series of sampling intervals can be used for quantitative analysis to obtain meaningful kinetic parameters of probe in vivo. The sampling schemes may affect the quantification results of dynamic fluorescence imaging. Here, we investigate the influence of different sampling schemes on the quantification of binding potential (BP) with theoretically simulated and experimentally measured data. Three groups of sampling schemes are investigated including the sampling starting point, sampling sparsity, and sampling uniformity. In the investigation of the influence of the sampling starting point, we further summarize two cases by considering the missing timing sequence between the probe injection and sampling starting time. Results show that the mean value of BP exhibits an obvious growth trend with an increase in the delay of the sampling starting point, and has a strong correlation with the sampling sparsity. The growth trend is much more obvious if throwing the missing timing sequence. The standard deviation of BP is inversely related to the sampling sparsity, and independent of the sampling uniformity and the delay of sampling starting time. Moreover, the mean value of BP obtained by uniform sampling is significantly higher than that by using the non-uniform sampling. Our results collectively suggest that a suitable sampling scheme can help compartmental modeling of dynamic fluorescence imaging provide more accurate results and simpler operations.

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“…With static BLI imaging, the relationship between tumor cell number and BLI signal intensity for the Original Article Kinetic modeling and analysis of dynamic bioluminescence imaging of substrates administered by intraperitoneal injection Yunpeng Dai 1# , Duofang Chen 1# , Guodong Wang 2 , Jipeng Yin 2 , Yonghua Zhan 1 , Kaichun Wu 2 , Jimin Liang 1 , Xueli Chen 1 subcutaneously implanted tumor model has been validated (12,13), and the results show that they are positively correlated. Based on dynamic imaging, kinetic analysis models offer more quantitative information on the probe environment in vivo, including data on peak metabolic rates, clearance rates, and distribution volume, thus enabling the more comprehensive characterization of physiological and pathological features in the region of interest (ROI) (9,(14)(15)(16)(17). Therefore, it is necessary to conduct quantitative research into the use of dynamic BLI techniques for the real-time detection of tumor microenvironments and the evaluation of anti-cancer therapies.…”

Section: Introductionmentioning

confidence: 99%

Kinetic modeling and analysis of dynamic bioluminescence imaging of substrates administered by intraperitoneal injection

Dai¹,

Chen²,

Wang³

et al. 2020

Quant Imaging Med Surg

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Background: Bioluminescence imaging (BLI) has been found to have diverse applications in the life sciences and medical research due to its ease of use and high sensitivity. From kinetics analysis, dynamic imaging studies have significant advantages for diagnosis when compared to traditional static imaging studies. This work focuses on modeling and quantitatively analyzing the dynamic data produced from the intraperitoneal (IP) injection of D-luciferin in longitudinal BLI, aiming to provide a powerful tool for monitoring the growth of tumors. Methods: We constructed a three-compartment pharmacokinetic (PK) model and employed the standard Michaelis-Menten (M-M) kinetics to investigate the dynamic BLI data produced from the IP injection of D-luciferin. The 3 compartments were the plasma compartment, the non-specific compartment, and the specific compartment. The validity of this PK model was tested by the dynamic BLI data of MKN28M-luc xenograft mice, along with the published longitudinal dynamic BLI data of B16F10-luc xenograft mice. Results:The R-squares between the simulated lines and the measurement were 1 and 0.99, respectively, for the mice data and the published data. In addition, the 2 kinetic macroparameters obtained reflected the rate of tumor growth in vivo. In particular, the values of macroparameters A showed a significant dependence on tumor surface area. Conclusions:The proposed PK model may be an effective tool for use in drug development programs and for monitoring the response of tumors to treatment.

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Investigation of injection dose and camera integration time on quantifying pharmacokinetics of a Cy5.5-GX1 probe with dynamic fluorescence imagingin vivo

Cited by 7 publications

References 34 publications

68Ga-Labeled GX1 Dimer: A Novel Probe for PET/Cerenkov Imaging Targeting Gastric Cancer

68Ga-Labeled GX1 Dimer: A Novel Probe for PET/Cerenkov Imaging Targeting Gastric Cancer

Investigation of the influence of sampling schemes on quantitative dynamic fluorescence imaging

Kinetic modeling and analysis of dynamic bioluminescence imaging of substrates administered by intraperitoneal injection

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