Acromegaly: the disease of gigantism that appears in adulthood

At our University, we have assumed a firm commitment to addressing the problem of acromegaly, a rare disease caused by tumors in the pituitary gland that results in an excess of growth hormone in adults. This debilitating condition manifests itself with serious symptoms, such as facial changes, limb growth, and heart problems. One of the main challenges in the fight against this disease is late diagnosis, which can take up to ten years.

Our tireless dedication has focused on improving the early detection of acromegaly. In collaboration with the Rovira i Virgili University, we have conceived an innovative project that uses artificial intelligence and facial recognition as tools for early diagnosis. Early identification of this disease is essential to ensure timely treatment and enhance the quality of life of patients.

Our project is based on the analysis of facial images with the purpose of identifying the characteristic changes derived from acromegaly in an initial stage of the disease. This early detection will allow doctors to initiate treatment before the disease causes irreparable damage.

We have carried out research that has shown that facial recognition can provide guidance regarding the therapeutic response of a new medication called pasireotide. This innovative technology, supported by an independent multicenter study, provides a promising approach for treating acromegaly and improving patients’ quality of life.

Acromegaly is a rare disease, and our commitment is to promote research and development of treatments that benefit affected patients. Despite the challenges that rare diseases pose, we are firmly determined to continue moving forward in the search for effective and promising solutions. Acromegaly, although rare, deserves proper attention and treatment.

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Projectes Transversals Industry Meeting Day: Conference on road safety and sustainability

The Industry Meeting Day gave visibility and disseminated the results of the research carried out on road sustainability and safety within the framework of PECT Cuidem el que que us. It also became a meeting place between administration, university, companies, research centers and the various actors, both from the public and private spheres, which direct their activity to the road construction, infrastructure and waste management sector.

It had an exhibition space that made known the results of the work carried out by the different operations of the project. These are emerging technological solutions aimed at the business world, which contribute to improving the sustainability and safety of the road network and to the competitiveness of the sector, through innovation.

A round table with representatives of various agents from the territory enabled the debate on the challenges of the future in the areas of work of the PECT We care for what unites us.

During the day, the following investigations in safety and sustainability were presented:


The day was addressed to companies in the sectors related to roads and infrastructures, the Administration, research centers… The aim was to promote strategic alliances between them and transfer knowledge.

More information about our project:

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The URV coordinates an international project that will improve the detection and prevention of breast cancer recurrence

A research group from the Rovira i Virgili University, led by the Professor Domènec Puig, classifies the types of breast cancer and predict the probability of metastasis.

Domènec Puig, on the left, and Hatem Rashwan, two of those responsible for the BosomShield project on behalf of the URV

The Universitat Rovira i Virgili is taking the lead in an ambitious international project known as BosomShield, with the potential to play a pivotal role in the detection and prevention of breast cancer. At its core, BosomShield is focused on the development of a sophisticated software platform designed to analyze both radiological and histopathological images. This groundbreaking approach brings together the analysis of traditional imaging methods like mammograms and MRIs with the examination of microscopic cell-level images. By amalgamating these two types of images, the project seeks to enhance the precision of breast cancer classification, predict the severity of the condition, and estimate the probability of metastasis recurrence. This collaborative endeavor is spearheaded by the URV’s Laboratory of Intelligent Robotics and Vision, led by researcher Domènec Puig, and is a part of the ITAKA research group within the Department of Computer Engineering and Mathematics. Notably, BosomShield enjoys the support of universities, hospitals, biomedical research groups, and technology centers in Europe, Asia, and North America, with funding secured from the European Union’s Marie-Sklodowska Curie Actions program, set to run until 2026.

BosomShield comprises ten distinct subprojects, each undertaken by one of the collaborating institutions, addressing various stages of the process. These encompass the analysis of radiological and histopathological images, prediction of recurrence possibilities, and platform design. Doctoral candidates selected by the participating institutions lead each subproject, fostering an enriching international exchange of expertise among researchers. The URV team, for instance, is overseeing the first subproject, aiming to determine the molecular subtype of breast cancer through multimodal radiological images. This endeavor leverages deep learning and artificial intelligence to identify tumor markers in radiological images, providing crucial insights into the potential danger and likelihood of recurrence, particularly in collaboration with Swedish partners. Ultimately, the BosomShield project aspires to create a practical clinical platform accessible within hospitals, offering specialists alerts and valuable assistance in making well-informed and efficient decisions regarding breast cancer diagnosis and treatment. It represents the culmination of collaborative efforts between the URV and IISPV, signaling a significant stride towards a universal and effective breast cancer diagnosis system.

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