Title: The ARTFIBio web platform

Authors: J. Carlos Mouriño; Andrés Gómez; Mariano Sánchez; A. López-Medina

Addresses: Fundación Pública Galega Centro Tecnológico de Supercomputación de Galicia (CESGA), Santiago de Compostela, Spain ' Fundación Pública Galega Centro Tecnológico de Supercomputación de Galicia (CESGA), Santiago de Compostela, Spain ' Fundación Pública Galega Centro Tecnológico de Supercomputación de Galicia (CESGA), Santiago de Compostela, Spain ' Medical Physics Department, Complexo Hospitalario Universitario de Vigo (CHUVI), Spain

Abstract: In the last years, there were big steps in the treatment of head and neck cancer (HNC), but local relapse rates are still very high. For this reason, multicentric research is needed to overcome them, focused on quantifying tumour response of HNC patients by functional images like PET/CT and MRI. The joint use of MRI and PET/CT can be useful for delimiting the hypoxic areas. To leverage the collaboration among hospitals and researchers, a platform architecture specifically designed to suit the needs of the study of tumour response quantification is being developed. It allows the sharing of the patient's images, the radiotherapy treatment planning, and the information of the final delivered doses. Other additional information can be added for each patient, as chemotherapy treatment data or the surgical procedures, so a full set of information can be gathered for each treatment. Additionally, the platform includes a registration tool to analyse correctly the different patient's images. Our tool is being successfully used in the frame of the ARTFIBio project, focused on the study of predictive individualised models of head and neck tumour response to radiotherapy.

Keywords: scientific data management; data sharing; computer supported collaborative tool; head and neck cancer; HNC; positron emission tomography; PET/CT; computed tomography; magnetic resonance imaging; MRI; digital imaging; DICOM; noVNC; radiotherapy; tumour response; web platforms; healthcare technology; hospital collaboration; image sharing; treatment planning; delivered doses; medical images; predictive modelling; individualised models; internet.

DOI: 10.1504/IJIM.2015.073014

International Journal of Image Mining, 2015 Vol.1 No.2/3, pp.159 - 174

Received: 24 Jan 2015
Accepted: 28 Jan 2015
Published online: 12 Nov 2015 *

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