Angiogenesis Imaging Using 68Ga-RGD PET/CT: Therapeutic Implications

Eo, Jae Seon; Jeong, Jae Min

doi:10.1053/j.semnuclmed.2016.04.001

Cited by 37 publications

(29 citation statements)

References 54 publications

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“…As a result, a variety of RGD-based molecular probes have been developed to visualize integrin a v b 3 expression (4-6). Because of the superiority of PET molecular imaging technique, RGD tracers labeled with positron-emitting radionuclides such as 18 F, 64 Cu, 68 Ga, and 89 Zr have attracted much attention (7)(8)(9)(10). As a PET tracer based on dimeric RGD peptide, 18 F-alfatide II has been recently proven to possess excellent clinical translational potential in several studies (11)(12)(13)(14)(15)(16).…”

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confidence: 99%

¹⁸F-Alfatide II PET/CT for Identification of Breast Cancer: A Preliminary Clinical Study

Wang

Zhang

et al. 2018

J Nucl Med

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F-alfatide II has been proven to have excellent clinical translational potential. In this study, we investigated F-alfatide II for identifying breast cancer and compared the performances betweenF-alfatide II and F-FDG. Forty-four female patients with suspected primary breast cancer were recruited. PET/CT images using F-alfatide II andF-FDG were acquired within 7 d. Tracer uptake in breast lesions was evaluated by visual analysis, and semiquantitative analysis with SUV and SUV Forty-two breast cancer lesions and 11 benign breast lesions were confirmed by histopathology in 44 patients. BothF-alfatide II and F-FDG had higher uptake in breast cancer lesions than in benign breast lesions ( < 0.05 for F-alfatide II, < 0.05 for F-FDG). The area under the curve ofF-alfatide II was slightly less than that of F-FDG. BothF-alfatide II and F-FDG had high sensitivity (88.1% vs. 90.5%), high positive predictive value (88.1% vs. 88.4%), moderate specificity (54.5% vs. 54.5%), and moderate negative predictive value (54.5% vs. 60.0%) for differentiating breast cancer from benign breast lesions. By combiningF-alfatide II and F-FDG, the sensitivity and negative predictive value significantly increased to 97.6% and 85.7%, respectively, with positive predictive value slightly increased to 89.1% and no change to the specificity (54.5%). The uptake ofF-alfatide II (SUV: 3.77 ± 1.78) was significantly lower than that of F-FDG (SUV: 7.37 ± 4.48) in breast cancer lesions ( < 0.05). F-alfatide II uptake in triple-negative subtype was significantly lower than that in luminal A and luminal B subtypes. By contrast, human epidermal growth factor receptor-2 (HER-2)-overexpressing subtype had higherF-FDG uptake than the other 3 subtypes. There were 8 breast cancer lesions with higher F-alfatide II uptake thanF-FDG uptake, which all had a common characteristic that HER-2 expression was negative and estrogen receptor expression was strongly positive. F-alfatide II is suitable for clinical use in breast cancer patients.F-alfatide II is of good performance, but not superior to F-FDG in identifying breast cancer.F-alfatide II may have superiority to F-FDG in detecting breast cancer with strongly positive estrogen receptor expression and negative HER-2 expression.

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confidence: 99%

¹⁸F-Alfatide II PET/CT for Identification of Breast Cancer: A Preliminary Clinical Study

Wang

Zhang

et al. 2018

J Nucl Med

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“…In fact, other integrins (e.g., a v b 5 , a v b 6 ) are also related to RGD amino acid sequence binding (28,29). The a v b 3 integrin is targetable by various radiolabeled RGD peptides (30). Histologically, RGD peptides target tumor vasculature via RGD-integrin a v b 3 interaction, with little extravasation.…”

Section: Discussionmentioning

confidence: 99%

Response Assessment of ⁶⁸Ga-DOTA-E-[c(RGDfK)]² PET/CT in Lung Adenocarcinoma Patients Treated with Nintedanib Plus Docetaxel

et al. 2017

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Nintedanib is an oral angiokinase inhibitor used as second-line treatment for non-small cell lung cancer. New radiotracers, such as Ga-DOTA-E-[c(RGDfK)], that target αβ integrin might have an impact as a noninvasive method for assessing angiogenesis inhibitors. From July 2011 through October 2015, 38 patients received second-line nintedanib plus docetaxel. All patients underwent PET/CT withGa-DOTA-E-[c(RGDfK)] radiotracer and blood-sample tests to quantify angiogenesis factors (fibroblast growth factor, vascular endothelial growth factor, and platelet-derived growth factor AB) before and after completing 2 therapy cycles. Of the 38 patients, 31 had available baseline and follow-up PET/CT. Baseline lung tumor volume addressed withGa-DOTA-E-[c(RGDfK)] PET/CT correlated with serum vascular endothelial growth factor levels, whereas baseline lung/liver SUV index correlated with platelet-derived growth factor AB. After treatment, the overall response rate and disease control rate were 7.9% and 47.3%, respectively. A greater decrease in lung tumor volume (-37.2% vs. -27.6%) was associated with a better disease control rate in patients ( = 0.005). Median progression-free survival was 3.7 mo. Nonsmokers and patients with a higher baseline lung tumor volume were more likely to have a higher progression-free survival (6.4 vs. 3.74 [ = 0.023] and 6.4 vs. 2.1 [ = 0.003], respectively). Overall survival was not reached. Patients with a greater decrease in lung SUV (not reached vs. 7.1 mo; = 0.016) and a greater decrease in the lung/spleen SUV index (not reached vs. 7.1; = 0.043) were more likely to have a longer overall survival.Ga-DOTA-E-[c(RGDfK)] PET/CT is a potentially useful tool for assessing responses to angiogenesis inhibitors. Further analysis and novel studies are warranted to identify patients who might benefit from this therapy.

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“…In addition to mathematical models, angiogenesis imaging is largely studied to examine tumor growth, characterization of tumor vasculature, and the response of the therapies. Employing various imaging modalities such as computer tomography (CT) and magnetic resonance imaging (MRI) gives an insight into the progress of tumor and vascular structure [22,23]. Additionally, photoacoustic imaging is exploited to monitor tumor angiogenesis due to its higher contrast and spatial resolution [24][25][26].…”

Section: Introductionmentioning

confidence: 99%

Chemotherapy response prediction with diffuser elapser network

Koyuncu

Melek

Yιlmaz

et al. 2020

Preprint

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In solid tumors, elevated fluid pressure and inadequate blood perfusion resulting from unbalanced angiogenesis are the prominent reasons for the ineffective drug delivery inside tumors. To normalize the heterogeneous and tortuous tumor vessel structure, antiangiogenic treatment is an effective approach. Additionally, the combined therapy of antiangiogenic agents and chemotherapy drugs has shown promising effects on enhanced drug delivery. However, the need to find the appropriate scheduling and dosages of the combination therapy is one of the main problems in anticancer therapy. Our study aims to generate a realistic response to the treatment schedule, making it possible for future works to use these patient-specific responses to decide on the optimal starting time and dosages of cytotoxic drug treatment. Our dataset is based on our previous in-silico model with a framework for the tumor microenvironment, consisting of a tumor layer, vasculature network, interstitial fluid pressure, and drug diffusion maps. In this regard, the chemotherapy response prediction problem is discussed in the study, putting forth a proof-of-concept for deep learning models to capture the tumor growth and drug response behaviors simultaneously. The proposed model utilizes multiple convolutional neural network submodels to predict future tumor microenvironment maps considering the effects of ongoing treatment. Since the model has the task of predicting future tumor microenvironment maps, we use two image quality evaluation metrics, which are structural similarity and peak signal-to-noise ratio, to evaluate model performance. We track tumor cell density values of ground truth and predicted tumor microenvironments. The model predicts tumor microenvironment maps seven days ahead with the average structural similarity score of 0.973 and the average peak signal ratio of 35.41 in the test set. It also predicts tumor cell density at the end day of 7 with the mean absolute percentage error of 2.292 ± 1.820.

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Angiogenesis Imaging Using 68Ga-RGD PET/CT: Therapeutic Implications

Cited by 37 publications

References 54 publications

¹⁸F-Alfatide II PET/CT for Identification of Breast Cancer: A Preliminary Clinical Study

¹⁸F-Alfatide II PET/CT for Identification of Breast Cancer: A Preliminary Clinical Study

Response Assessment of ⁶⁸Ga-DOTA-E-[c(RGDfK)]² PET/CT in Lung Adenocarcinoma Patients Treated with Nintedanib Plus Docetaxel

Chemotherapy response prediction with diffuser elapser network

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Angiogenesis Imaging Using 68Ga-RGD PET/CT: Therapeutic Implications

Cited by 37 publications

References 54 publications

18F-Alfatide II PET/CT for Identification of Breast Cancer: A Preliminary Clinical Study

18F-Alfatide II PET/CT for Identification of Breast Cancer: A Preliminary Clinical Study

Response Assessment of 68Ga-DOTA-E-[c(RGDfK)]2 PET/CT in Lung Adenocarcinoma Patients Treated with Nintedanib Plus Docetaxel

Chemotherapy response prediction with diffuser elapser network

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¹⁸F-Alfatide II PET/CT for Identification of Breast Cancer: A Preliminary Clinical Study

¹⁸F-Alfatide II PET/CT for Identification of Breast Cancer: A Preliminary Clinical Study

Response Assessment of ⁶⁸Ga-DOTA-E-[c(RGDfK)]² PET/CT in Lung Adenocarcinoma Patients Treated with Nintedanib Plus Docetaxel