Label Efficient Deep Learning in Medical Imaging

Recent state-of-the-art deep learning frameworks require large, fully annotated training datasets that are, depending on the objective, time-consuming to generate. While in most fields, these labelling tasks can be parallelized massively or even outsourced, this is not the case for medical images. Usually, only a highly trained expert is able to generate these datasets. However, since additional manual annotation, especially for the purpose of segmentation or tracking, is typically not part of a radiologist's workflow, large and fully annotated datasets are a rare and scarce good. In this context, a variety of frameworks are proposed in this work to solve the problems that arise due to the lack of annotated training data across different medical imaging tasks and modalities. The first contribution as part of this thesis was to investigate weakly supervised learning on PET/CT data for the task of lesion segmentation. Using only class labels (tumor vs. no tumor), a classifier was first trained and subsequently used to generate Class Activation Maps highlighting regions with lesions. Based on these region proposals, final tumor segmentation could be performed with high accuracy in clinically relevant metrics. This drastically simplifies the process of training data generation, as only class labels have to be assigned to each slice of a scan instead of a full pixel-wise segmentation. To further reduce the time required to prepare training data, two self-supervised methods were investigated for the task of anatomical tissue segmentation and landmark detection. To this end, as a second contribution, a state-of-the-art tracking framework based on contrastive random walks was transferred, adapted and extended to the medical imaging domain. As contrastive learning often lacks real-time capability, a self-supervised template matching network was developed to address the task of real-time anatomical tissue tracking, yielding the third contribution of this work. Both of these methods have in common that only during inference the object or region of interest is defined, reducing the number of required labels to as few as one and allowing adaptation to different tasks without having to re-train or access the original training data. Despite the limited amount of labelled data, good results could be achieved for both tracking of organs across subjects as well as tissue tracking within time-series. State-of-the-art self-supervised learning in medical imaging is usually performed on 2D slices due to the lack of training data and limited computational resources. To exploit the three-dimensional structure of this type of data, self-supervised contrastive learning was performed on entire volumes using over 40,000 whole-body MRI scans forming the fourth contribution. Due to this pre-training, a large number of downstream tasks could be successfully addressed using only limited labelled data. Furthermore, the learned representations allows to visualize the entire dataset in a two-dimensional view. To encourage research in the field of automated lesion segmentation in PET/CT image data, the autoPET challenge was organized, which represents the fifth contribution

Three-dimensional cell culture and tissue engineering in a T-CUP (tissue culture under perfusion)

The aim of this study was to develop and validate a simple and compact bioreactor system for perfusion cell seeding and culture through 3-dimensional porous scaffolds. The developed Tissue Culture Under Perfusion (T-CUP) bioreactor is based on the concept of controlled and confined alternating motion of scaffolds through a cell suspension or culture medium, as opposed to pumping of the fluid through the scaffolds. Via the T-CUP, articular chondrocytes and bone marrow stromal cells could be seeded into porous scaffolds of different compositions and architectures (chronOS, Hyaff-11, and Polyactive) at high efficiency (greater than 75%), uniformity (cells were well distributed throughout the scaffold pores), and viability (greater than 97%). Culture of articular chondrocytes seeded into 4-mm thick Polyactive scaffolds for 2 weeks in the T-CUP resulted in uniform deposition of cartilaginous matrix. Cultivation of freshly isolated human bone marrow nucleated cells seeded into ENGipore ceramic scaffolds for 19 days in the T-CUP resulted in stromal cell-populated constructs capable of inducing ectopic bone formation in nude mice. The T-CUP bioreactor represents an innovative approach to simple, efficient, and reliable 3D cell culture, and could be used either as a model to investigate mechanisms of tissue development or as a graft manufacturing system in the context of regenerative medicine

Oviposition of Aedes japonicus japonicus (Diptera: Culicidae) and associated native species in relation to season, temperature and land use in western Germany

Background: Aedes japonicus japonicus, first detected in Europe in 2000 and considered established in Germany 10 years later, is of medical importance due to its opportunistic biting behaviour and its potential to transmit pathogenic viruses. Its seasonal phenology, temperature and land use preference related to oviposition in newly colonised regions remain unclear, especially in the context of co-occurring native mosquito species. Methods: Focussing on regions in Germany known to be infested by Ae. japonicus japonicus, we installed ovitraps in different landscapes and their transition zones and recorded the oviposition activity of mosquitoes in relation to season, temperature and land use (arable land, forest, settlement) in two field seasons (May-August 2017, April-November 2018). Results: Ae. japonicus japonicus eggs and larvae were encountered in 2017 from June to August and in 2018 from May to November, with a markedly high abundance from June to September in rural transition zones between forest and settlement, limited to water temperatures below 30 degrees C. Of the three native mosquito taxa using the ovitraps, the most frequent was Culex pipiens s.l., whose offspring was found in high numbers from June to August at water temperatures of up to 35 degrees C. The third recorded species, Anopheles plumbeus, rarely occurred in ovitraps positioned in settlements and on arable land, but was often associated with Ae. japonicus japonicus. The least frequent species, Aedes geniculatus, was mostly found in ovitraps located in the forest. Conclusions: The transition zone between forest and settlement was demonstrated to be the preferred oviposition habitat of Ae. japonicus japonicus, where it was also the most frequent container-inhabiting mosquito species in this study. Compared to native taxa, Ae. japonicus japonicus showed an extended seasonal activity period, presumably due to tolerance of colder water temperatures. Higher water temperatures and arable land represent distribution barriers to this species. The frequently co-occurring native species An. plumbeus might be useful as an indicator for potentially suitable oviposition habitats of Ae. japonicus japonicus in hitherto uncolonised regions. The results contribute to a better understanding of mosquito ecology and provide a basis for more targeted monitoring, distribution modelling and risk management of mosquitoes

Alcohol consumption and neurocognitive deficits in people with well-treated HIV in Switzerland

BACKGROUND Hazardous alcohol consumption and HIV infection increase the risk of neurocognitive impairment (NCI). We examined the association between alcohol consumption and specific neurocognitive domain function in people with HIV (PWH) taking modern antiretroviral therapy. METHODS The Neurocognitive Assessment in the Metabolic and Aging Cohort (NAMACO) study is a prospective, longitudinal, multicentre and multilingual (French, German and Italian) study of patients aged ≥45 years old enrolled in the Swiss HIV Cohort Study (SHCS). Baseline data from 981 study participants were examined. Five neurocognitive domains were evaluated: motor skills, speed of information processing, attention/working memory, executive function and verbal episodic memory. NCI was examined as binary (presence/absence) and continuous (mean z-score) outcomes against Alcohol Use Disorders Identification Test for Consumption (AUDIT-C) scores using logistic and linear regression models, respectively. RESULTS Most participants (96.2%) had undetectable viral loads and 64% were aged >50 years old. Hazardous alcohol consumption was observed in 49.4% of participants and binge drinking in 4.2%. While alcohol consumption frequency and quantity were not associated with NCI, the practice of binge drinking was significantly associated with impaired motor skills and overall neurocognitive function in both binary (odds ratio, OR ≥2.0, P <0.05) and continuous (mean z-score difference -0.2 to -0.4, P ≤0.01) outcomes. A significant U-shaped distribution of AUDIT-C score was also observed for motor skills and overall neurocognitive function. CONCLUSIONS In this cohort of PWH with well-controlled HIV infection, NCI was associated with the practice of binge drinking rather than alcohol consumption frequency or quantity. Longitudinal analysis of alcohol consumption and NCI in this population is currently underway

The association between depressive symptoms and neurocognitive impairment in people with well-treated HIV in Switzerland.

Depression may contribute to neurocognitive impairment (NCI) in people with HIV (PWH). Attributing NCI to depression rather than to HIV is complicated as depression may be both a causal factor and an effect of NCI. This study aimed to determine the association between depressive symptoms and NCI among PWH with well-controlled infection. The Neurocognitive Assessment in the Metabolic and Ageing Cohort study is an ongoing, prospective, longitudinal study of PWH aged ≥45 years old nested within the Swiss HIV Cohort Study. Neurocognitive Assessment in the Metabolic and Ageing Cohort study participants underwent neurocognitive assessment and grading of depressive symptoms using the Centre for Epidemiological Studies Depression Scale. Neurocognitive impairment categories were defined using Frascati criteria. Participants with NCI related to neurological or psychiatric confounders other than depression were excluded. The cross-sectional association between the Centre for Epidemiological Studies Depression score and neurocognitive impairment was examined taking Centre for Epidemiological Studies Depression score as a continuous variable and then as a binary variable using two score thresholds, 16 and 27. Excluding 79 participants with confounding factors, 902 participants were studied: 81% were men; 96% had plasma viral loads &lt;50 copies/ml; 35% had neurocognitive impairment; 28% had Centre for Epidemiological Studies Depression scores ≥16. Higher Centre for Epidemiological Studies Depression scores were associated with female sex (p = 0.0003), non-Caucasian origin (p = 0.011) and current/past intravenous drug use (p = 0.002). Whilst neurocognitive impairment was associated with higher Centre for Epidemiological Studies Depression scores, the Centre for Epidemiological Studies Depression score was a poor predictor of having neurocognitive impairment (area under the ROC curve 0.604). Applying a Centre for Epidemiological Studies Depression score threshold of 16 predicted the presence of neurocognitive impairment with a sensitivity of 38.3% (specificity 77.2%), increasing the threshold to 27 lowered sensitivity to 15.4% (specificity 93.6%). In this large cohort of PWH in Switzerland, we did not observe a Centre for Epidemiological Studies Depression score threshold that was sensitive in predicting neurocognitive impairment. As neurocognitive impairment was however associated with higher Centre for Epidemiological Studies Depression scores, the data support the screening for and treatment of depression among PWH diagnosed with neurocognitive impairment