China 
Africa 
Explore chapters and articles related to this topic
Biological Imaging and Radiobiological Modeling for Treatment Planning and Response Assessment in Radiation Therapy
Published in Siyong Kim, John Wong, Advanced and Emerging Technologies in Radiation Oncology Physics, 2018
Vitali Moiseenko, Stephen R. Bowen, John P. Kirkpatrick, Robert Jeraj, Lawrence B. Marks
Imaging biomarkers of tumor hypoxia, another hallmark of cancer progression and metastatic potential, provide more specific definitions of radiation-resistant subregions. Hypoxia-induced radioresistance follows from historical data demonstrating the oxygen effect (Hall and Giaccia, 2006) and the significant impact of baseline tumor oxygenation status on clinical outcomes (Nordsmark et al., 2005). Hypoxia imaging biomarkers are generally grouped into two distinct families of tracers: (1) nitroimidizoles radiolabeled with 18F that include fluoromisonidizole (FMISO) and FAZA PET, as well as more recent optimization of HX4 imaging (van Loon et al., 2010, Zegers et al., 2013), and (2) metal complexes, including Cu-ATSM. Pretreatment FAZA PET could successfully stratify head and neck cancer patients by their disease-free survival (DFS) rates, with two-year DFS of 93% in non-hypoxic tumors compared to 60% in hypoxic ones (Mortensen, 2012). Combination FDG PET and FMISO PET in a multivariate analysis correlated best with long-term survival of head and neck cancer patients receiving radiation therapy (Thorwarth et al., 2006). High overlap of FMISO PET regions with local recurrences has further motivated feasibility studies for hypoxia image-guided dose escalation in head and neck cancer (Hendrickson et al., 2011), including advanced dose-painting-by-numbers approaches (Thorwarth et al., 2007a). In non-small-cell lung cancer, HX4 PET regions provide complementary targets that are generally smaller than conventional FDG PET regions (Zegers et al., 2014) for further individualized therapy. HX4 PET has also been investigated in head and neck, esophageal, and pancreatic cancers within the construct of prospective clinical trials designed in part to test its degree of repeatability (Klaassen et al., 2015, Zegers et al., 2015).
Advances in treatment planning
Published in Jing Cai, Joe Y. Chang, Fang-Fang Yin, Principles and Practice of Image-Guided Radiation Therapy of Lung Cancer, 2017
Besides glucose metabolism, regional tumor hypoxia has also been associated with increased radio resistance and treatment failure. Studies evaluating hypoxia imaging with FMISO have shown that it is possible to use this imaging technique to evaluate oxygenation status in tumors (Figure 14.7). This information can be potentially used to guide dose escalation to the hypoxic fraction of the tumor [118,119].
Feature extraction and qualification
Published in Ruijiang Li, Lei Xing, Sandy Napel, Daniel L. Rubin, Radiomics and Radiogenomics, 2019
For time varying acquisition protocols, such as dynamic PET and MR, radiomic features are extracted based on kinetic analysis of the dynamic images. Compartment models are widely used for the tracer transport, its binding rates, and metabolism. For example, the FDG-PET imaging has shown great success in tumor detection and cancer staging, which uses 18F-labeled FDG as the tracer to visualize the intra-tumoral glucose metabolism. General concepts for the interpretation of PET data are four compartment model as shown in Figure 8.6 (Watabe et al. 2006), with the first compartment being the arterial blood, second the free compartment, and third and fourth specific and non-specific binding. There are four radioactivity concentrations at each time point for each compartment: Cp(t), Cf(t),Cb(t), and Cn(t) and six transport and binding rates K1, K2, K3, K4, K5, K6. These rates are assumed to be linearly related to the concentrations between two compartments by simple differential equations. By fitting the model and solving these parameters, the glucose metabolic rate can be calculated, which can be used as dynamic radiomic features in outcome modeling. Since the rapid equilibrium between the non-specific-binding and free compartments for FDG tracer, three compartments model is good enough to obtain the kinetics for this example (Watabe et al. 2006). There are some literature about using the dynamic features to do the prediction. Thorwarth et al. reported that by using a compartmental model based on dynamic [18F]-Fmiso PET patient data, identification and quantification of hypoxia in human head-and-neck tumors are better than standardized uptake value alone (Thorwarth et al. 2005). Choi et al. showed that there is a good correlation between residual regional metabolic rate of glucose (MRglc) after chemoradiotherapy and the degree of pathologic tumor control in locally advanced-stage non-small cell lung cancer (NSCLC), where the MRglc is calculated by a three-compartment kinetic model (Choi et al. 2002).
Relaxometric investigations addressing the determination of intracellular water lifetime: a novel tumour biomarker of general applicability
Published in Molecular Physics, 2018
Maria Rosaria Ruggiero, Simona Baroni, Silvio Aime, Simonetta Geninatti Crich
With respect to the other methodologies currently proposed for hypoxia imaging, the herein described approach shows many advantages. For example, positron emission tomography (PET) exploits the tracer [18F]fluoromisonidazole ([18F]FMISO) [23,24], for hypoxia molecular imaging. In hypoxic environments, [18F]FMISO radical anion persists long enough to react with macromolecules, trapping the tracer in the intracellular compartment. However, considering the low target-to-background ratio and slow uptake in malignant tissues, the use of [18F]FMISO was quite limited and new tracers are still under scrutiny. On the contrary, the relaxometric method herein described avoids the use of exogenous tracers being responsive to an endogenous parameter, i.e. the osmotically driven changes of water exchange rate. Oxygen enhanced MRI represents another approach to hypoxia imaging [25]. It is based on the use of molecular oxygen as a contrast agent as it causes a decrease of R1 after its inhalation. In hypoxic tissue, the inhaled oxygen molecules bind preferentially to deoxygenated haemoglobin molecules, converting the paramagnetic deoxyhaemoglobin to diamagnetic oxyhaemoglobin. Therefore, hypoxic tumour regions can be detected by the absence of measurable positive ΔR1. The main limitation is that ΔR1 can be strongly influenced by differences in gas delivery and inhalation.
An efficient glioma classification and grade detection using hybrid convolutional neural network-based SVM model
Published in The Imaging Science Journal, 2023
It is a multi-center clinical trial to measure the relation between the baseline FMISO PET (hypoxic volume, maximal tumor to blood proportion) and parameters of MRI (CVB) including survival, and disease growing time. For the training and testing, 70% is used for the training, 20% is used for the testing phase, and 10% for validation. This captured other standard brain cancer data like GLUT1, CAIX, and CD31. MRI scans help to determine blood flow changes, blood volume, size of the blood vessels and oxygenation status, etc. This trial was conducted between 2010 and 2013 with 50 patients from 11 academic centers in the US.