Patients With Cancer in the Countries of South-East Europe (the Balkans) Region and Prospective of the Particle Therapy Center: South-East European International Institute for Sustainable Technologies (SEEIIST).
Advances in radiation oncology 6:6 (2021) 100772
Abstract:
Purpose
A recent initiative was launched for establishing the South-East European International Institute for Sustainable Technologies (SEEIIST), which will provide a cutting-edge Hadron radiation therapy treatment and research institute for treating cancer patients with Hadron therapy (HT). To justify the initiative for building the SEEIIST facility, a study was conducted to estimate the number of patients with cancer from the SEE region that would be eligible for HT.Methods and materials
Two different methods for projecting the future annual cancer incidence have been applied: (1) using the International Agency on Research on Cancer@World Health Organization's (WHO) Globocan model which uses country's demographic factors, and (2) averaging the crude incidence data of 3 SEE countries with available national cancer registries, using a linear regression model of combined incidence per 100,000, and applying it to the entire SEE region. Cancer epidemiology data were collected and studied by using the countries' cancer datasheets from WHO. The top 10 cancers were presented for the SEE region. Studies of other countries were used to develop a primordial model for estimating the number of SEE patients who could be treated most successfully with HT upon SEEIIST commissioning in 2030.Results
A model was developed to estimate the number of eligible patients for HT from SEE. It is estimated that 2900 to 3200 patients per year would be eligible for HT in the new SEEIIST facility in 2030.Conclusions
After commissioning, SEEIIST will initially treat approximately 400 patients per year, progressing toward 1000. Creation of SEEIIST dedicated patient selection criteria will be both necessary and highly challenging.South East European International Institute for Sustainable Technologies (SEEIIST)
Frontiers in Physics Frontiers 8 (2021) 567466
CANCER IN THE COUNTRIES OF THE SEE (BALKANS) REGION AND THE FUTURE PARTICLE THERAPY CENTER – SEEIIST
RAD Centre (2021)
Achieving flexible competence: bridging the investment dichotomy between infectious diseases and cancer.
BMJ global health 5:12 (2020) e003252
Abstract:
Today's global health challenges in underserved communities include the growing burden of cancer and other non-communicable diseases (NCDs); infectious diseases (IDs) with epidemic and pandemic potential such as COVID-19; and health effects from catastrophic 'all hazards' disasters including natural, industrial or terrorist incidents. Healthcare disparities in low-income and middle-income countries and in some rural areas in developed countries make it a challenge to mitigate these health, socioeconomic and political consequences on our globalised society. As with IDs, cancer requires rapid intervention and its effective medical management and prevention encompasses the other major NCDs. Furthermore, the technology and clinical capability for cancer care enables management of NCDs and IDs. Global health initiatives that call for action to address IDs and cancer often focus on each problem separately, or consider cancer care only a downstream investment to primary care, missing opportunities to leverage investments that could support broader capacity-building. From our experience in health disparities, disaster preparedness, government policy and healthcare systems we have initiated an approach we call flex-competence which emphasises a systems approach from the outset of program building that integrates investment among IDs, cancer, NCDs and disaster preparedness to improve overall healthcare for the local community. This approach builds on trusted partnerships, multi-level strategies and a healthcare infrastructure providing surge capacities to more rapidly respond to and manage a wide range of changing public health threats.Arbitrarily large tomography with iterative algorithms on multiple GPUs using the TIGRE toolbox
Journal of Parallel and Distributed Computing Elsevier 146 (2020) 52-63