Visual mining of moving flock patterns in large spatio-temporal data sets using a frequent pattern approach

The popularity of tracking devices continues to contribute to increasing volumes of spatio-temporal data about moving objects. Current approaches in analysing these data are unable to capture collective behaviour and correlations among moving objects. An example of these types of patterns is moving flocks. This article develops an improved algorithm for mining such patterns following a frequent pattern discovery approach, a well-known task in traditional data mining. It uses transaction-based data representation of trajectories to generate a database that facilitates the application of scalable and efficient frequent pattern mining algorithms. Results were compared with an existing method (Basic Flock Evaluation or BFE) and are demonstrated for both synthetic and real data sets with a large number of trajectories. The results illustrate a significant performance increase. Furthermore, the improved algorithm has been embedded into a visual environment that allows manipulation of input parameters and interactive recomputation of the resulting flocks. To illustrate the visual environment a data set containing 30 years of tropical cyclone tracks with 6 hourly observations is used. The example illustrates how the visual environment facilitates exploration and verification of flocks by changing the input parameters and instantly showing the spatio-temporal distribution of the resulting flocks in the Space-Time Cube and interactively selecting

Recurrent differentiated thyroid cancer: Towards personalized treatment based on evaluation of tumor characteristics with PET (THYROPET Study): Study protocol of a multicenter observational cohort study

Background: After initial treatment of differentiated thyroid carcinoma (DTC) patients are followed with thyroglobulin (Tg) measurements to detect recurrences. In case of elevated levels of Tg and negative neck ultrasonography, patients are treated 'blindly' with Iodine-131 (131I). However, in up to 50% of patients, the post-therapy scan reveals no 131I-targeting of tumor lesions. Such patients derive no benefit from the blind therapy but are exposed to its toxicity. Alternatively, iodine-124 (124I) Positron Emission Tomography/Computed Tomography (PET/CT) has become available to visualize DTC lesions and without toxicity. In addition to this, 18F-fluorodeoxyglucose (18F-FDG) PET/CT detects the recurrent DTC phenotype, which lost the capacity to accumulate iodine. Taken together, the combination of 124I and 18F-FDG PET/CT has potential to stratify patients for treatment with 131I.Methods/Design: In a multicenter prospective observational cohort study the hypothesis that the combination of 124I and 18F-FDG PET/CT can avoid futile 131I treatments in patients planned for 'blind' therapy with 131I, is tested.One hundred patients planned for 131I undergo both 124I and 18F-FDG PET/CT after rhTSH stimulation. Independent of the outcome of the scans, all patients will subsequently receive, after thyroid hormone withdrawal, the 131I therapy. The post 131I therapeutic scintigraphy is compared with the outcome of the 124I and 18F-FDG PET/CT in order to evaluate the diagnostic value of the combined PET modalities.This study primary aims to reduce the number of futile 131I therapies. Secondary aims are the nationwide introduction of 124I PET/CT by a quality assurance and quality control (QA/QC) program, to correlate imaging outcome with histopathological features, to compare 124I PET/CT after rhTSH and after withdrawal of thyroid hormone, and to compare 124I and 131I dosimetry.Discussion: This study aims to evaluate the potential value of the combination of 124I and 18F-FDG PET/CT in the prevention of futile 131I therapies in patients with biochemically suspected recurrence of DTC. To our best knowledge no studies addressed this in a prospective cohort of patients. This is of great clinical importance as a futile 131I is a costly treatment associated with morbidity and therefore should be restricted to those likely to benefit from this treatment.Trial registration: Clinicaltrials.gov identifier: NCT01641679