DISCOVERING EARLY BIOMARKERS IN CIRCULATING ENDOTHELIAL CELLS
Unravelling shared microcirculatory abnormalities in hypertension and Alzheimer's disease using laser speckle contrast imaging.
Alberto Gonzalez Olmos, Department of Clinical Medicine,
DD. Postnov, Department of Clinical Medicine / Center of Functionally Integrative Neuroscience, Aarhus University;
L. Østergaard, Department of Clinical Medicine / Center of Functionally Integrative Neuroscience, Aarhus University;
T. Bek, Department of Clinical Medicine / Department of Ophthalmology, Aarhus University;
VV. Matchkov, Department of Biomedicine, Aarhus University;
Background: Dementia is a term used to refer to a set of symptoms such as progressive impairments to memory, language, and thinking. Along with cognitive dysfunction, dementia is associated with abnormal changes in brain perfusion and microcirculation.
While the exact mechanisms are still debated, it is known that hypertension predisposes an individual to early cognitive impairment and increases the risk of developing Alzheimer's Disease (AD) - the most common cause of dementia. A potential link between the diseases could be the altered functional and structural properties of resistance vessels that are associated with elevated blood pressure. Therefore, developing approaches to diagnose and treat those abnormalities at the earliest stages of hypertension might reduce the future incidence of dementia.
Aim: To develop a novel translational approach for microcirculation diagnostics based on Laser Speckle Contrast Imaging (LSCI) and apply it to study the link between hypertension and AD.
Methods: We will design and optimize LSCI for human and animal retinal imaging. We will collect a long term imaging dataset of brain and retinal blood flow in rat models in the progression of hypertension (DOCA Salt) and Alzheimer's disease (TgF344-AD). Finally, we will develop new image processing algorithms to characterize the microcirculation
condition using the LSCI data.
Perspective: In the final stages of the project, we will translate the findings from rat models to characterize the microcirculation of patients with hypertension and dementia. Overall this project promises to provide a new tool for monitoring microcirculation that can impact research and diagnostics in various fields.
Keywords: Medical technology and diagnostic techniques, Cardiovascular system, Animal models/disease models
Auto-segmentation of low contrast organs at risk in head and neck improves with minimal prior delineation input.
Mathis Ersted Rasmussen, Department of Clinical Medicine,
Jasper Albertus Nijlkamp, Danish Center for Particle Therapy; Jesper Grau Eriksen, Department of Experimental Clinical Oncology; Stine Sofia Korreman, Danish Center for Particle Therapy
Segmentation of organs-at-risk (OAR) is a crucial but time consuming step in radiotherapy.
Deep learning (DL) auto-segmentation (AS) can assist clinicians in the task, however AS of OARs with low visual contrast is often inaccurate. We aim to improve performance of DL AS of low contrast OARs by including minimal manual delineations as input to DL AS models.
We have planning CTs and manual segmentations of OARs from 301 head-neck cancer patients. 30 were randomly selected for an external test set. To simulate minimal manual delineation (MMD) input, we extracted the most cranial and caudal slice of the lower, middle and upper pharyngeal constrictor muscles (PCMs), glottic larynx (GL) and parotid glands (PG) and input these along with CT in 3D full resolution nnUNets [Isensee, F et al. 2020] (CT+MMD). For reference we trained CT-only nnUNets.
We obtained Dice on the external test set. Tests for similarity between paired models were done with two-sided Wilcoxon signed-rank tests.
Dice was significantly better for all OARs with CT+MMD compared to CT-only (p≤0.001).
Absolute improvements in median Dice ranged from 0.18 to 0.22 for PCMs and GL and 0.02 for PG.
By training DL AS models on CT along with just two manually delineated slices per OAR, Dice improved substantially for low contrast OARs such as PCMs and GL. For the included high contrast OAR (PG) the effect was marginal.
Our findings show that it may be beneficial for clinicians to manually segment a few selected slices low contrast OARs prior to running DL AS, as the subsequent predictions are likely to require much less revision than for predictions of fully automated models.
Keywords: Oncology, Medical technology and diagnostic techniques, Other
Parametrization of artery delineation and nationwide implementation in the DBCG RT Nation cohort
Emma Riis Skarsø, Department of Clinical Medicine,
L. Refsgaard, Department of Experimental Clinical Oncology, Aarhus University Hospital, Denmark; T. Ravkilde, Department of Oncology, Aarhus University Hospital, Aarhus, Denmark; HD. Nissen, Department of Oncology, Vejle Hospital, University Hospital of Southern Denmark; M. Berg, Department of Oncology, Vejle Hospital, University Hospital of Southern Denmark; K. Boye, Department of Oncology, Copenhagen University Hospital – Rigshospitalet, Copenhagen, Denmark; C. Kamby, Department of Oncology, Copenhagen University Hospital – Rigshospitalet, Copenhagen, Denmark; K. Jakobsen, Department of Clinical Oncology and Palliative Care, Zealand University Hospital, Næstved, Denmark; M.
Olesen, Department of Clinical Oncology and Palliative Care, Zealand University Hospital, Næstved, Denmark; BV. Offersen, Department of Experimental Clinical Oncology, Aarhus University Hospital, Denmark; SS. Korreman, Department of Experimental Clinical
Oncology, Aarhus University Hospital, Denmark
Purpose
With automation of delineation in radiotherapy making its entry in clinical routine, it is desirable to have a framework for quality assurance (QA) of delineation of small organs of limited visibility. In this study we develop a parameterization of left anterior descending coronary artery (LADCA) delineation.
methods
We included organ delineations from 4598 danish high-risk breast cancer patients treated with adjuvant radiotherapy across the nation during 2008-2017. A national delineation guideline was published in 2013. LADCA was parameterized using metrics describing volume, cranial-caudal (CC) and cumulative length, width, anterior-posterior and lateral- medial consistency between slices, missing organ slices and number of patients with delineations. Results were stratified by year and treating center. Significance was tested with the Mann-Whitney U-test.
Results
The method was successfully used in all patients included in the Danish Breast Cancer Group (DBCG) RT Nation cohort. In the period around the implementation of national delineation guidelines (2012-2014), the differences between the centers were smallest.
For mean width there was a significant difference between centers in the periods 2008- 2012 and 2014-2017 (p<0.001). For CC length, no significant differences were found between center 2 and 3 (2011-2016), however center 4 differed significantly in the periods 2010-2011 and 2015-2017 (p<0.001).
Conclusion
We have developed a method for parametrization of delineations of LADCA. Our results showed significant differences in delineations of LADCA among centers and need for regularly QA regarding delineations. This method is generalizable for other organs.
Keywords: Oncology, Other, Other
Robust treatment planning for anatomical variations in proton therapy
Nadine Vatterodt, Department of Clinical Medicine,
U.V. Elstrøm, Danish Center for Particle Therapy, AUH; K. Jensen, Danish Center for Particle Therapy, AUH; S.S. Korreman, Danish Center for Particle Therapy, AUH & Department of Oncology, AUH & Department of Clinical Medicine, AU
Proton therapy treatment plans are highly sensitive to uncertainties during the treatment course. Therefore, robust treatment planning strategies are used to mitigate simple variations, however, they cannot incorporate complex anatomical variations.
The PhD project addresses this issue for the most dominant components of anatomical variations in head and neck cancer (HNC) proton therapy. Individualized adaptive and robust treatment planning approaches will be identified, based on a quantification of anatomical variations and the respective dosimetric impact for individual patients.
The study is performed based on CT/PET and daily cone-beam CT (CBCT) scans of HNC patients, who have previously been treated with either photons or protons at AUH. A pre- existing method based on principal component analysis for modelling daily anatomical changes extracted from CBCT scans is used to identify modes of anatomical variations. A priority ranking is derived by correlating localization of anatomical variations with
deteriorations of the dose distribution in the patient. Individualized robust planning and adaptation strategies will then be developed and tested. The complexity of the
approaches can vary from including highly localized up to global anatomical robustness based on population and/or individually identified modes of variations. Based on plan quality and robustness, the most promising approaches will be identified for patient subgroups.
The study is expected to facilitate implementation of clinical protocols for HNC in proton therapy, including robustness towards anatomical variations. This will improve the laborious plan adaptation workflow for both personnel and patients.
Keywords: Oncology, Other, Other
The LOOP-DIY Study: The effect of LOOP-DIY in Danish children with Type 1 Diabetes Mellitus.
Amanda Ringmann Fagerberg, Department of Clinical Medicine
J. S. Sørensen, STENO Diabetes Center Aarhus and Pediatrics Department Herning, K.
Kristensen, STENO Diabetes Center Aarhus, L. Borch, Pediatrics Department Herning
Development in treatment of Type 1 Diabetes Mellitus (T1DM) have become increasingly technical, with insulin pumps and continuous blood glucose sensors replacing daily insulin injections and capillary blood glucose measures. Furthermore, integration of pumps and sensors to regulate insulin dosage are a rapidly developing field, and the company-based integrated solutions have been overtaken by patient initiated open-source solutions: LOOP Do-It-Yourself (DIY). LOOP-DIY automatically integrates values from the sensor with insulin delivery, controlling the insulin dosage through algorithms. Studies have shown increased glycemic control and better quality of life (QoL).
This cross-sectional study with current and retrospective data will be the first to assess the effect, safety and use of LOOP-DIY in Danish children aged 2-18 with T1DM.
The aim is to 1) estimate prevalence of the use of LOOP-DIY, 2) estimate the effect of LOOP-DIY on the patient’s daily glycemic control measuring glycemic parameters, 3) estimate the risk of the LOOP-DIY by measuring frequency of ketoacidosis and severe hypoglycemia, 4) assess the effect of LOOP-DIY on everyday life of the children and parents, including QoL, sleep, self-efficacy, and fear of hypoglycemia (FOH).
The participants will be found nationwide through pediatric diabetes outpatient clinics.
Their daily glycemic control will be assessed pre and post their transition to LOOP-DIY.
Participants and their parents will be sent questionnaires regarding QoL, sleep, self- efficacy and FOH, as will a matched control group.
Keywords: Molecular metabolism and endocrinology, Paediatrics, Medical technology and diagnostic techniques