Caixia Cheng

Impact of Angiogenesis-Related Gene Expression on the Tracer Kinetics of 18F-FDG in Colorectal Tumors

18F-FDG kinetics are primarily dependent on the expression of genes associated with glucose transporters and hexokinases but may be modulated by other genes. The dependency of 18F-FDG kinetics on angiogenesis-related gene expression was evaluated in this study. Methods: Patients with primary colorectal tumors (n = 25) were examined with PET and 18F-FDG within 2 days before surgery. Tissue specimens were obtained from the tumor and the normal colon during surgery, and gene expression was assessed using gene arrays. Results: Overall, 23 angiogenesis-related genes were identified with a tumor-to-normal ratio exceeding 1.50. Analysis revealed a significant correlation between k1 and vascular endothelial growth factor (VEGF-A, r = 0.51) and between fractal dimension and angiopoietin-2 (r = 0.48). k3 was negatively correlated with VEGF-B (r = −0.46), and a positive correlation was noted for angiopoietin-like 4 gene (r = 0.42). A multiple linear regression analysis was used for the PET parameters to predict the gene expression, and a correlation coefficient of r = 0.75 was obtained for VEGF-A and of r = 0.76 for the angiopoietin-2 expression. Thus, on the basis of these multiple correlation coefficients, angiogenesis-related gene expression contributes to about 50% of the variance of the 18F-FDG kinetic data. The global 18F-FDG uptake, as measured by the standardized uptake value and influx, was not significantly correlated with angiogenesis-associated genes. Conclusion: 18F-FDG kinetics are modulated by angiogenesis-related genes. The transport rate for 18F-FDG (k1) is higher in tumors with a higher expression of VEGF-A and angiopoietin-2. The regression functions for the PET parameters provide the possibility to predict the gene expression of VEGF-A and angiopoietin-2.

Shortened Acquisition Protocols for the Quantitative Assessment of the 2-Tissue-Compartment Model Using Dynamic PET/CT 18F-FDG Studies

18F-FDG kinetics are quantified by a 2-tissue-compartment model. The routine use of dynamic PET is limited because of this modalitys 1-h acquisition time. We evaluated shortened acquisition protocols up to 0–30 min regarding the accuracy for data analysis with the 2-tissue-compartment model. Methods: Full dynamic series for 0–60 min were analyzed using a 2-tissue-compartment model. The time–activity curves and the resulting parameters for the model were stored in a database. Shortened acquisition data were generated from the database using the following time intervals: 0–10, 0–16, 0–20, 0–25, and 0–30 min. Furthermore, the impact of adding a 60-min uptake value to the dynamic series was evaluated. The datasets were analyzed using dedicated software to predict the results of the full dynamic series. The software is based on a modified support vector machines (SVM) algorithm and predicts the compartment parameters of the full dynamic series. Results: The SVM-based software provides user-independent results and was accurate at predicting the compartment parameters of the full dynamic series. If a squared correlation coefficient of 0.8 (corresponding to 80% explained variance of the data) was used as a limit, a shortened acquisition of 0–16 min was accurate at predicting the 60-min 2-tissue-compartment parameters. If a limit of 0.9 (90% explained variance) was used, a dynamic series of at least 0–20 min together with the 60-min uptake values is required. Conclusion: Shortened acquisition protocols can be used to predict the parameters of the 2-tissue-compartment model. Either a dynamic PET series of 0–16 min or a combination of a dynamic PET/CT series of 0–20 min and a 60-min uptake value is accurate for analysis with a 2-tissue-compartment model.

Correlation of the Ga-68-Bombesin Analog Ga-68-BZH3 with Receptors Expression in Gliomas as Measured by Quantitative Dynamic Positron Emission Tomography (dPET) and Gene Arrays

PurposeThe kinetics of Ga-68-BZH3, a Ga-68-bombesin analog, was compared to molecular biological data obtained from gene arrays in seven patients with a recurrent glioma. The primary aim of this study was the correlation of receptor expression and tracer kinetics.ProceduresDynamic positron emission tomography studies were performed and the data were analyzed by a volume-of-interest technique using a two-tissue compartment model as well as a non-compartment model. Gene array data were obtained from gene array analysis of tumor tissue samples.ResultsThe correlation analysis revealed a significant nonlinear correlation of r = 0.89 (p < 0.03) for k1 and BB2 (gastrin-releasing peptide receptor). BB1 and BB3 were not significantly correlated with k1. vb and k3 were not significantly correlated with the expression data of the receptors on the p < 0.05 level.ConclusionsThe parameter k1 is correlated with the expression of BB2 based on gene array data. The quantitative analysis of the Ga-68-BZH3 kinetics can be used to predict the receptor expression of BB2 in gliomas based on k1 of the compartment analysis. However, this study is limited to the expression data on the mRNA level and further studies are needed to assess the correlation of gene expression on the protein level.

Comparison between 68Ga-bombesin (68Ga-BZH3) and the cRGD tetramer 68Ga-RGD4 studies in an experimental nude rat model with a neuroendocrine pancreatic tumor cell line

ObjectivesReceptor scintigraphy gains more interest for diagnosis and treatment of tumors, in particular for neuroendocrine tumors (NET). We used a pan-Bombesin analog, the peptide DOTA-PEG2-[D-tyr6, β-Ala11, Thi13, Nle14] BN(6-14) amide (BZH3). BZH3 binds to at least three receptor subtypes: the BB1 (Neuromedin B), BB2 (Gastrin-releasing peptide, GRP), and BB3. Imaging of ανβ3 integrin expression playing an important role in angiogenesis and metastasis was accomplished with a 68Ga-RGD tetramer. The purpose of this study was to investigate the kinetics and to compare both tracers in an experimental NET cell line.MethodsThis study comprised nine nude rats inoculated with the pancreatic tumor cell line AR42J. Dynamic positron emission tomography (PET) scans using 68Ga-BZH3 and 68Ga-RGD tetramer were performed (68Ga-RGD tetramer: n = 4, 68Ga-BZH3: n = 5). Standardized uptake values (SUVs) were calculated, and a two-tissue compartmental learning-machine model (calculation of K 1 - k 4 vessel density (VB) and receptor binding potential (RBP)) as well as a non-compartmental model based on the fractal dimension was used for quantitative analysis of both tracers. Multivariate analysis was used to evaluate the kinetic data.ResultsThe PET kinetic parameters showed significant differences when individual parameters were compared between groups. Significant differences were found in FD, VB, K 1, and RBP (p = 0.0275, 0.05, 0.05, and 0.0275 respectively). The 56- to 60-min SUV for 68Ga-BZH3, with a range of 0.86 to 1.29 (median, 1.19) was higher than the corresponding value for the 68Ga-RGD tetramer, with a range of 0.78 to 1.31 (median, 0.99). Furthermore, FD, VB, K 1, and RBP for 68Ga-BZH3 were generally higher than the corresponding values for the 68Ga-RGD tetramer, whereas k 3 was slightly higher for 68Ga-RGD tetramer.ConclusionsAs a parameter that reflects receptor binding, the increase of K 1 for 68Ga-BZH3 indicated higher expression of bombesin receptors than that of the ανβ3 integrin in neuroendocrine tumors. 68Ga-BZH3 seems better suited for diagnosis of NETs owing to higher global tracer uptake.

Preliminary evaluation of different biomaterials for defect healing in an experimental osteoporotic rat model with dynamic PET-CT (dPET-CT) using F-18-Sodium Fluoride (NaF)

UNLABELLED The aim of the current study was to measure and compare the effect of calcium phosphate cement (CPC) and CPC enriched with strontium (SrCPC) for the healing of osteoporotic bone defects in the rat femur using (18)F-Sodium Fluoride dPET-CT. METHODS Osteoporosis was induced by ovariectomy and a calcium restricted diet. After three months, rats were operated to create a 4 mm defect in the distal metaphyseal femur with internal fixation. 7 Rats have been treated either with CPC (Group 2) or with SrCPC (Group 3) for bone replacement and defect healing. Furthermore, a control group of 7 rats without any biomaterial (Group 1) was used for reference. 18 weeks after osteoporosis induction and 6 weeks following femoral surgery, dPET-CT studies scan were performed with (18)F-Sodium Fluoride. SUVs and a 2-tissue compartmental learning-machine model (K1-k4, VB, influx) were used for quantitative analysis. RESULTS VB, reflecting the fractional blood volume and k3, reflecting the formation of fluoroapatite were the most sensitive parameters for the characterisation of healing process and revealed the best differentiation for the control group and the CPC group (Group 2) as well as for the CPC with strontium carbonate group (Group 3) (p<0.05). VB was decreased by the order of Group 1, Group 2 and Group 3, while k3 was increased by the same order. Therefore, the data direct to a decreased fractional blood volume and increased fixation of fluoride in rats with these biomaterials. CONCLUSION We found PET scanning using (18)F-Sodium Fluoride to be a sensitive and useful method for evaluation of bone healing after replacement with CPC or SrCPC.

Application of F-18-sodium fluoride (NaF) dynamic PET-CT (dPET-CT) for defect healing: a comparison of biomaterials in an experimental osteoporotic rat model.

Background The aim of the current study was to measure and compare the effect of various biomaterials for the healing of osteoporotic bone defects in the rat femur using 18F-sodium fluoride dPET-CT. Material/Methods Osteoporosis was induced by ovariectomy and a calcium-restricted diet. After 3 months, rats were operated on to create a 4-mm wedge-shaped defect in the distal metaphyseal femur. Bone substitution materials of calcium phosphate cement (CPC), composites of collagen and silica, and iron foams with interconnecting pores were inserted. Strontium or bisphosphonate, which are well known for having positive effects in osteoporosis treatment, were added into the materials. Eighteen weeks after osteoporosis induction and 6 weeks following femoral surgery, dPET-CT studies scan were performed with 18F-Sodium Fluoride. Standardized uptake values (SUVs) and a 2-tissue compartmental learning-machine model (K1-k4, vessel density [VB], influx [ki]) were used for quantitative analysis. Results k3, reflecting the formation of fluoroapatite, revealed a statistically significant increase at the biomaterial-bone interface due to the Sr release from strontium-modified calcium phosphate cement (SrCPC) compared to CPC, which demonstrated enhanced new bone formation. In addition, k3 as measured in the porous scaffold silica/collagen xerogel (Sc-B30), showed a significant increase based on Wilcoxon rank-sum test (p<0.05) as compared with monolithic silica/collagen xerogel (B30) in the defect region. Furthermore, ki, reflecting the net plasma clearance of tracer to bone mineral measured in the iron foam with coating of the bisphosphonate zoledronic acid (Fe-BP), was enhanced as compared with plain iron foam (Fe) in the defect region. Conclusions k3 was the most significant parameter for the characterization of healing processes and revealed the best differentiation between the 2 different biomaterials. PET scanning using 18F-sodium fluoride seems to be a sensitive and useful method for evaluation of bone healing after replacement with these biomaterials.

Imaging therapy response of gastrointestinal stromal tumors (GIST) with FDG PET, CT and MRI: a systematic review

PurposeImprovement of the therapeutic approaches in gastrointestinal stromal tumors (GIST) by the introduction of targeted therapies requires appropriate diagnostic tools, which allow sufficient assessment of therapeutic response, including differentiation of true progression from pseudoprogression due to myxoid degeneration or intratumoral hemorrhage. In this literature review the impact and limitations of different imaging modalities used in GIST therapy monitoring are discussed.MethodsPubMed and Cochrane library search were performed using appropriate keywords. Overall, 39 original papers fulfilled the defined criteria and were included in this systematic review.ResultsMorphological imaging modalities like computed tomography (CT) are primarily used for both diagnosis and therapy monitoring. However, therapy with tyrosine kinase inhibitors and other targeted therapies in GIST may lead only to a minor tumor volume reduction even in cases of response. Therefore, the use of Response Evaluation Criteria in Solid Tumors (RECIST) has limitations. To overcome those limitations, modified response criteria have been introduced for the CT-based therapy assessment, like the Choi criteria as well as criteria based on dual energy CT studies. Functional imaging techniques, mostly based on FDG PET-CT are in use, in particular for the assessment of early treatment response.ConclusionsThe impact and the limitations of PET-based therapy monitoring, as well as its comparison with CT, MRI and survival data are discussed in this review. CT is still the standard method for the evaluation of therapy response despite its several limitations. FDG PET-CT is helpful for the assessment of early therapy response; however, more prospective data are needed to define its role as well as the appropriate time intervals for therapy monitoring. A multiparametric evaluation based on changes in both morphological and functional data has to be assessed in further prospective studies.

Machine learning-based kinetic modeling: A robust and reproducible solution for quantitative analysis of dynamic PET data

A variety of compartment models are used for the quantitative analysis of dynamic positron emission tomography (PET) data. Traditionally, these models use an iterative fitting (IF) method to find the least squares between the measured and calculated values over time, which may encounter some problems such as the overfitting of model parameters and a lack of reproducibility, especially when handling noisy data or error data. In this paper, a machine learning (ML) based kinetic modeling method is introduced, which can fully utilize a historical reference database to build a moderate kinetic model directly dealing with noisy data but not trying to smooth the noise in the image. Also, due to the database, the presented method is capable of automatically adjusting the models using a multi-thread grid parameter searching technique. Furthermore, a candidate competition concept is proposed to combine the advantages of the ML and IF modeling methods, which could find a balance between fitting to historical data and to the unseen target curve. The machine learning based method provides a robust and reproducible solution that is user-independent for VOI-based and pixel-wise quantitative analysis of dynamic PET data.

Correction to: Imaging therapy response of gastrointestinal stromal tumors (GIST) with FDG PET, CT and MRI: a systematic review

The article “Imaging therapy response of gastrointestinal stromal tumors (GIST) with FDG PET, CT and MRI: a systematic review”, written by Antonia Dimitrakopoulou-Strauss, Ulrich Ronellenfitsch, Caixia Cheng, Leyun Pan, Christos Sachpekidis, Peter Hohenberger, and Thomas Henzler, was originally published Online First without open access. After publication in volume 5, issue 3, pages 183‒197, the author decided to opt for Open Choice and to make the article an open access publication. Therefore, the copyright of the article has been changed to