Project name: Methods of Prediction of Infantile Hemangioma Evolution
Aimed at Preventing
Desfigurating Complications by Multiple
Contract No. 123/2014
Program name within PN II: Joint Applied Research Projects
("Parteneriate in domenii prioritare")
Funding Agency: Executive Unit for Higher Education, Research, Development and Innovation Funding (UEFISCDI)
Project code: PN-II-PT-PCCA-2013-4-0201
Infantile Hemangiomas (IH) are tumors of vascular origin that are present at birth or develop a few weeks after. The differential diagnosis from vascular malformations is difficult to establish. IH that affect the cephalic and cervical region (the most frequent), the genital area or the extremities, due to the location, dimensions and fast evolution, can determine important functional and esthetic sequels, debilitating for the patient. To avoid these unfortunate consequences it is necessary to establish the exact appropriate moment to begin the treatment and decide which is the most adequate therapeutic procedure.
Until now, at international level there is no standard method of diagnosis of infantile hemangiomas nor any mean of predicting their progress from the clinical point of view and possible complications that may appear. Treatments currently used rely only on subjective observation, instinct and experience of the treating physician, supported by technical and pharmacological development in medicine.
The proposed project intends, based on clinical data collected by serial clinical observations correlated with imaging data, to develop a treatment algorithm to accurately predict the best final results, from esthetical and functional point of view, for a certain type of lesion.
In order to achieve this goal, we will use and/or develop modern methods to process medical images and intelligent algorithms to help the diagnosis (CAD). The software will incorporate advanced methods for accurate measurement of specific IH lesions, will integrate medical information resulting from clinical observations and integrate statistical methods and/or nature-inspired computational methods (e.g. nonlinear dynamics, cellular neural networks, artificial neural networks) to correlate this information with that obtained from the processing of images. Based on these correlations we will establish a prediction mechanism of the evolution of hemangioma. This will help determine the best method of therapeutic intervention to minimize further complications.
The scientific and technological impact of the project resides in the development of these innovative methods. Their implementation will result in a medical device type of product that will obviously help to increase the competitiveness of the Romanian economy, given that the existence of such a product, which aims to really improve the quality of life for children affected by an esthetic and functional disfiguring pathology, is a must.
The product implies real health benefits for both patients and the health system receiving a minimization of costs per patient in this condition. By decreasing the number of procedures and defining a single therapeutic strategy for treating a patient, amounts can be saved and consequently allocated for the benefit of other needs. Moreover, if the aesthetic and functional result is maximized, we save the resources allocated for the patient’s reintegration into society, which is more costly if the degree of failure is higher. Decreasing the disease follow up period, speeding the diagnosis, diminishing the hospitalization time, a faster social integration of the patients are only a few benefits that such a product would bring, not only for the patients, but also for the national and European medical system.
The consortium consisting of “Carol Davila” University of Medicine and Pharmacy Bucharest (project coordinator), University Politehnica from Bucuresti (P1), University Valahia of Târgoviste (P2) and Medical Technologies & Research company (P3) formed a close-knit team to successfully implement the project. The project will run for a period of 24 months, with a budget of 1,437,500 lei, and involve a team of 17 researchers, three PhD students and one post-doctoral student.