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https://hdl.handle.net/1889/3749
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DC Field | Value | Language |
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dc.contributor.advisor | Poli, Tito | - |
dc.contributor.author | Lanfranco, Davide | - |
dc.date.accessioned | 2019-04-08T09:28:35Z | - |
dc.date.available | 2019-04-08T09:28:35Z | - |
dc.date.issued | 2018-03 | - |
dc.identifier.uri | http://hdl.handle.net/1889/3749 | - |
dc.description.abstract | The idea behind Oramod project rised from the need felt by experts working in head-neck cancer field to improve the multilevel representation of the biological processes notoriously implicated in the cancerogenesis to foresee the growth and the dissemination of the tumors, particularly of the oral and oropharyngeal squamous cell carcinoma. As a comprehensive vision of the patient is hampered by a sectoralized evaluation accomplished in each different field of competence (clinical, radiological, pathological, biomolecular) it would be extremely useful to dispose of an informatic system able to assemble data of various origin each one characterized by a different staircase of evaluation (numerical alpha, percentage, etc.). OraMod will translate into the clinical practice a VPH-based approach for supporting the management of key aspects in the prediction of the reoccurrence of oral cancer. The supporting VPH model has already been validated in the previous ICT project NeoMark (ICT-VPH-224483), where some of the OraMod clinical and technical Partners (including the Coordinator) were participating, and will be advanced into a clinically-oriented system. The proposed approach, relying on secure integration of huge health datasets, medical knowledge, multidisciplinary collaborative best clinical practices and cutting-edge technologies, including modelling and insilico simulation, will improve (1) the multi-specialist approach to diagnosis, risk assessment, and treatment decisions and (2) the integration of research-derived evidences into the clinical practice (i.e. the evidencedriven approach). A pre-clinical trial on Oral Cavity Cancer will demonstrate the effectiveness of the model to improve clinical decisions and will evaluate the socioeconomic impacts and benefits for patients, clinicians, the Healthcare Systems and the external payers. The key IT pillars of the project are: (1) the VPH concept of disease and patient virtualization, (2) the integration with the current IT hospital infrastructures, (3) the compliance with the current international standards in the field, and in the device industry, and (4) the integration with the current clinical workflow. The NeoMark model will be adapted for clinical implementation, and advanced to include interactivity and simulation functionalities and to dynamically improve prediction accuracy from a variety of multi-scale data. Finally this enhanced model will be integrated into a web-based modular framework of tools, services and diagnostic devices including: i. an Electronic Health Records (EHRs) management and decision support system, ii. a multi-source data collection layer, interoperable with legacy hospital systems, iii. a highly interactive Knowledge Assisted Visualization and Simulation environment for the "virtual" presentation of patients' data, in line with the "Digital Patient" concept, iv. a collaborative decision-making space, the "Virtual Tumour Board", to support the multi-disciplinary approach through the interaction of the different specialists concerned with treatment decisions, v. a sophisticated suite for image analysis and feature extraction for head&neck diagnostics vi. a RT-PCR device and lab-on-chip for fast, precise, quantitative detection of the genomic markers included in the prediction model. The predictive model will envisage multi-domain data collection (clinical, imaging, histology, genomics, etc.) and will be built on the integration of automated data extraction (i.e. biomarkers and imaging analysis), self-learning automated modelling techniques, and clinical experience of the user. The scientific objectives of the Oramod project are the identification of the patients with higher risk of relapse and the preclinical diagnosis of tumor recurrence. Identification of patients with higher or lower risk of recurrence should rationalize the decision to complete the patient’s treatment with adjuvant (radio/chemotherapy), limiting the use of such complementary therapies only to patients for whom the therapeutic effects are of paramount importance to justify a still elevated toxicity, as well as to allow the containment of the costs for the S.S.N.. A earlier diagnosis of recurrence would finally allow to perform less demolitive treatments in patients effected by oral and oropharyngeal carcinoma increasing their quality of life. In this study the above mentioned results of the Oramod project are presented. | it |
dc.language.iso | Italiano | it |
dc.publisher | Università di Parma. Dipartimento di Medicina e chirurgia | it |
dc.relation.ispartofseries | Dottorato di ricerca in Medicina molecolare | it |
dc.rights | © Davide Lanfranco, 2019 | it |
dc.subject | oscc gene signature, gene profiling | it |
dc.title | Modelli prognostici e Gene Signatures per la stratificazione dei pazienti affetti da carcinoma del cavo orale | it |
dc.title.alternative | Prognostic models and Gene Signatures for the stratification of patients with OSCC | it |
dc.type | Doctoral thesis | it |
dc.subject.miur | MED/29 | it |
Appears in Collections: | Medicina molecolare. Tesi di dottorato |
Files in This Item:
File | Description | Size | Format | |
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Tesi dottorato medicina molecolare XXXI Ciclo Dott. Lanfranco Davide.pdf | Tesi di dottorato | 2.08 MB | Adobe PDF | View/Open |
Relazione finale dottorato XXXI ciclo III anno Dott. Lanfranco.pdf Until 2100-01-01 | Relazione finale attività di dottorato | 867.09 kB | Adobe PDF | View/Open Request a copy |
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