The protective properties of breast milk are invaluable for premature infants. However, breast milk alone does not always guarantee optimal mental and physical development for these vulnerable infants. Therefore, enrichment by Human Milk Fortifiers (HMF) is inevitable. The problem is that the current HMF composition cannot be fine-tuned to the patient’s individual nutritional needs, because of the unknown breast milk consumption by the infant. Our solution is to use Multi-angle Light Scattering to answer the question: what is in the breast milk consumed by these infants? This information can potentially help to formulate an individualized approach to HMF dosage.
Dr.ir. Nienke Bosschaart (UT), Drs. Ageeth Kaspers (MST), Lya den Haan (MST)
Follow-up in patients who are treated for breast cancer aims to detect recurrent disease in an early stage, but varies in daily practice and is not based on the personalized risk of recurrence. With help of procesmining techniques daily practice of follow-up can be mapped from the combined databases of SANTEON, the Netherlands Cancer Registry and Performation. The effect of re-structuring of follow-up based on individual risks of recurrence (estimated using the INFLUENCE nomogram) and the wish of the patient on organization of care, the burden for the patient and the costs will be simulated in models.
Prof.dr. Sabine Siesling (UT), Dr. Erik Koffijberg (UT), Dr. Karin Groothuis-Oudshoorn (UT), Dr. Sandra Oude Wesselink (MST), Dr. Esther van 't Riet (DZ), Ir. Steven Lugard (Performation), Drs. Kay Schreuder (IKNL/UT), Dr. A. Dassen (MST), Dr. Jeroen Veldman (ZGT).
Early stage detection of cancer is crucial and determining for the chances of curing a patient and the costs of treatment. The aim of this study is to investigate how the expression profile of the microRNAs (a class of biomarkers) in urine and blood of lung cancer patients is different from that of healthy persons with statistical learning techniques. This will tell us if the urinary microRNA profile can be used to detect lung cancer in a non-invasive manner and will answer the question whether or not urine-based microRNA detection methods can form the basis of novel health-monitoring tests.
Dr. Karin Groothuis-Oudshoorn (UT), Dr. E. Citgez (MST), Dr. J.H. Schouwink (MST), Dr. J. de Rooij (JR&D Services)
Surgical treatment of esophageal cancer is known to have a high risk of severe complications where early intervention is critical to prevent unnecessary damage. Unfortunately, deterioration in patients may remain unnoticed within the hospital ward despite daily nurse controls. To detect instability in an early phase, we are developing an unobtrusive system to continuously monitor vital signs. For this aim, we make use of wireless sensors, and are working on algorithms to identify relevant trends and abnormalities in the continuous data. This technology supports care professionals in early recognition of deterioration, and enables timely treatment of patients.
Dr. Ewout Kouwenhoven (ZGT), Mathilde Hermans MSc. (UT)
During simultaneous drug delivery to neonates via IV-systems undesired and harmful dosing errors can occur, by a combination of low flow levels and relatively high medicine concentrations. In this proposal the application of a multi-parameter chip is investigated for locally determining the composition of the IV fluid just before it is introduced into the patient. The chip measures the composition by analysis of the physical parameters of the IV fluid. By comparing these properties with the expected values based on the setpoint of the pumps, drug administration can be carried out with higher confidence, yielding a better clinical result.
Prof.dr.ir. Joost Lötters (UT), Dr.ir. Cas Damen (Saxion), Dr.ir. Bärbel van den Berg (MST)
In order to support the failing heart, in 2017 we demonstrated a proof of principle by sending an electrical signal through a smart material to improve the hearts pump function. With this research we aim at a proof-of concept of electro-mechanical resynchronization therapy and bring this therapy closer to patientcare. We apply shape-memory alloys around a failing heart (model) and use experts from UT (materials science), MST (cardio-thoracic surgery), ZGT (cardiology, heart failure) and Saxion (ambient intelligence, smart materials). Shape-memory alloys are tested in different designs and in increasing complex heart models with a goal to improve contractility of the heart.
Dr. Salah A.M. Said (ZGT), Dr.ir. Jos Paulusse (UT), Prof.dr. Jan Grandjean (MSY), Drs. Frank Halfwerk (MST/UT), Dr.ir. Wouter Teeuw (Saxion), Ir. Ger Brinks (Saxion)
Personalized mobile alcohol avoidance training to reduce alcohol consumption in problem drinking gastroenterology patients
Many gastroenterology patients drink excessively, but since most patients experience a high threshold to regular addiction care, they often do not get adequate support for their problematic drinking. Furthermore, regular care is not 24/7 available, which makes it often unavailable during the difficult craving moments. Therefore, gastroenterologists are in need for an easily accessible, low-effort, 24/7 intervention that they can provide to their patients. A personalized version of the mobile Cognitive Bias Modification Alcohol Avoidance Training could fulfill these needs. Within this project, the personalized version of the app, including gamification elements, will be developed and evaluated.
Dr. Marloes Postel (UT), Dr. Maureen Guichelaar (MST), Drs. Melissa Laurens (Saxion), Dr. Somaya Ben Allouch (Saxion), Dr. Randy Klaassen (UT), Dr. Marjolein Brusse-Keizer (MST), Dr. Marcel Pieterse (UT)
In the Netherlands, roughly 8% of all newborns are born prematurely. Although survival of these prematurely born children has increased dramatically over the last decades, morbidity remains high. Pulmonary, ocular and development disorders are frequent in this population. In standard follow-up motor development is regularly evaluated with the Movement Assessment Battery for Children-2 (ABC-2), a validated, but time consuming and insensitive method. An automated and sensitive evaluation of motor development in prematurely born children is new and will prove to be a technical challenge, which, if successful, can revolutionize therapeutic modalities in this vulnerable population.
Dr. Jean Driessen (ZGT), Ageeth Kaspers (MST), Jaap Buurke (RRD/UT), Rianne Huis in 't Veld (ZGT), Anne Schoot (MST), Bart Koopman (UT), Wouter Teeuw (Saxion)
Sleep disorders such as insomnias, sleep apnea and sleep movement disorders affect nearly 50-70 million adults every year. Overnight polysomnography (PSG) is the gold standard tool for diagnosing sleep disorders. Currently, sleep staging is done through visual analysis of PSG recordings by experienced sleep technicians, which is a tedious task and such manual annotation is subject to both intra and inter-rater variability. The aim of this study is to develop a robust, reliable and automated sleep staging tool DEEPSLEEP using deep learning techniques which can assist sleep technicians for more reliable, cost-effective and efficient diagnosis and monitoring of sleep disorders.
Dr. Sunil Belur Nagaraj (UT), Dr. Ainara Garde (UT), Prof.dr.ir. Michel van Putten (MST/UT), Prof.dr. Hermie Hermens (RRD/UT), Mirjam Stappenbelt (MST), Dr. Iris Knottnerus (MST)
Unhealthy eating and activity behaviors result in insufficient weight loss following bariatric surgery. In current treatment, the importance of individual variation in behavioral components (such as eating, activity, emotion, cognition and context) and how these components might influence each other, are barely taken into consideration. This project focuses on development of an ambulant system that monitors behavioral components unobtrusively in daily life of patients, and the integration of the data into individual behavioral patterns. The results will be used for a personalized intervention that promotes healthy behavior in daily life, tailored to the specific needs, preferences and conditions of patients.
Dr. M.J. van Det (ZGT), Dr. M. Poel (UT), Mevr. J.G. Timmerman (ZGT), Dr. I.F. Faneyte (ZGT), Dr. Oresti Banos (UT),
Improving breast cancer treatment: mapping of histological findings in dissected breast specimen to 3D locations in the patient
Lumpectomy is very common in patients with breast cancer. After dissecting the lump, specimen changes ex-vivo, which results in uncertainty in the resection margin. As a result, follow-up treatment might be unnecessarily intensified (reoperation or radiation therapy). In this feasibility study, it will be investigated whether (positive) resection margins can be determined more accurately by visualizing/ reconstructing the specimen of a lumpectomy to represent the in-vivo situation. To do so, a 3D virtual volume will be created based on 2D histological features. This 3D virtual volume will be compared to pre-pathological 3D images.
Dr. Mirre de Noo (DZ), Dr.ir. Ferdinand van der Heijden (UT), Dr. Esther van 't Riet (DZ), Dr. Françoise J. Siepel (UT)