A Survey on Deep Learning in Medical Image Analysis

Deep learning algorithms, in particular convolutional networks, have rapidly become a methodology of choice for analyzing medical images. This paper reviews the major deep learning concepts pertinent to medical image analysis and summarizes over 300 contributions to the field, most of which appeared in the last year. We survey the use of deep learning for image classification, object detection, segmentation, registration, and other tasks and provide concise overviews of studies per application area. Open challenges and directions for future research are discussed.Comment: Revised survey includes expanded discussion section and reworked introductory section on common deep architectures. Added missed papers from before Feb 1st 201

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 349)

This bibliography lists 149 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during April, 1991. Subject coverage includes: aerospace medicine and psychology, life support systems and controlled environments, safety equipment, exobiology and extraterrestrial life, and flight crew behavior and performance

The gut microbiome modulates post stroke outcome

15 million people suffer from stroke per year. Fundamentally, stroke is caused by a lack of oxygenated blood to brain tissue which results in tissue death. This entails a complex pathophysiology which encompasses 3 phases. Within minutes to hours, brain resident cells initiate excitotoxicity leading to irreversible neuronal death. From days to months, peripheral recruitment of immune cells to the brain drives neuroinflammation and exacerbates stroke outcome. Finally, within months to years, there is an increase in neuronal plasticity which enables reorganisation of cortical networks and restoration of broken circuits. Despite decades of research and intricate understanding of the physiological processes occurring after stroke, only one acute therapy is approved for use in clinics. An interesting therapeutic target for scientific researchers is modulation of the peripheral host immune system. Experimental research has shown that polarisation of the immune cell sub populations towards pro-/anti-inflammatory state can exacerbate or alleviate stroke outcome respectively. Polarised immune cell subsets migrate from peripheral secondary lymphoid organs to the brain lesion. While the intestinal immune compartment contains the majority of the immune cells in the body, it is the intestinal lumen that is the home to 1000 different readily adapting bacterial species. The gut microbiota has been shown to intimately interact with the immune system and alter the function of particular immune cell subsets. Recent experimental evidence has indicated a potential role for the interaction the gut microbiota and immune system in brain disease. We hypothesised that the gut microbiota could therefore play a role in the outcome of stroke. Within this thesis we explore the gut microbiota and its derived metabolites in experimental ischemic stroke models. This thesis incorporates four publications which have unravelled different aspects of how the gut microbiota affects stroke. The key experimental findings within this thesis can be summarised in five key concepts. 1) The gut microbiota and stroke have a bidirectional interaction, both having the ability to change the other. 2) The gut microbiota alters peripheral immune cells which after stroke, were shown to migrate to the brain and alter the inflammatory milieu. 3) The presence of the gut microbiota, or treatment with healthy gut microbiota transfer, improved stroke outcome. 4) Small changes in the gut microbiota can alter response to stroke immunotherapies. 5) Short-chain fatty acids, the dietary metabolites derived from the gut microbiota, improve functional post stroke recovery. Taken together, I hope this thesis reflects and demonstrates the interesting therapeutic potential of gut microbiota manipulation for treatment of stroke. The addition of microbiota-based treatments may not only be a stand-alone therapy to aid recovery after stroke, but additionally could be a practical add-on for existing procedural treatments

The influence of hypoxia in erythropoiesis and morphology of red blood cells in sickle cell disease and hereditary spherocytosis.

Die Lebensfahigkeit menschlicher Zellen h ¨ angt in hohem Maße vom Sauerstoff ab, der von den roten ¨ Blutkorperchen transportiert und zur Verf ¨ ugung gestellt wird. In dieser Arbeit wird untersucht, wie ¨ Sauerstoff die Physiologie und Pathophysiologie jener roten Blutkorperchen beeinflusst. Die Arbeit ¨ ist in zwei wesentliche Teile gegliedert. Zunachst werden Ergebnisse einer gr ¨ oßeren Studie mit Probanden vorgestellt, die in großer H ¨ ohe ¨ (3450 m) durchgefuhrt wurde. In dieser H ¨ ohe sorgt der reduzierte Luftdruck f ¨ ur eine Abnahme ¨ der Sauerstoffsattigung im Blut und f ¨ uhrt so zu einer erh ¨ ohten Produktion an roten Blutk ¨ orperchen ¨ (Erythropoese). Nach der Ruckkehr aus großer H ¨ ohe f ¨ allt die Zahl an roten Blutk ¨ orperchen nach ¨ kurzer Zeit wieder auf das vorherige Niveau Es ist bislang nicht verstanden, ob die neugebildeten roten Blutzellen dazu abgebaut werden. Der hyptothetische Mechanismus der Neozytolyse (engl. Neocytolisis) geht davon aus, dass ausgerechnet die neu gebildeten, roten Blutzellen als erste wieder abgebaut werden, wenn die Ruckkehr auf Meeresniveau erfolgt. Die wissenschaftliche Fragestellung, ¨ die im Rahmen dieser Studie beantwortet wurde, ist, ob und in welchem Maß Neocytolyse nach einem 3-wochigen Aufenthalt in großer H ¨ ohe stattfindet. Dazu wurden zun ¨ achst Untersuchungen an aller ¨ Probanden mittels in-vitro Zellkulturen durchgefuhrt, um sowohl die Erythropoese als auch (neu ent- ¨ standende) Retikulozyten zu charakterisieren. Die Ergebnisse zeigen eine beschleunigte Reifung der Vorlauferzellen in Zellkulturen bei niedrigerem Sauerstoffgehalt (3%) verglichen mit normaler Atmo- ¨ sphare (20%) und eine unerwartet verbesserte ¨ Uberlebensrate der Retikulozyten. Dies stimmt mit dem ¨ Ergebnis der Studie uberein, dass nach der R ¨ uckkehr von der gew ¨ ahlten H ¨ ohe keine Neozytolyse, d.h. ¨ kein bevorzugter Abbau von neu gebildeten roten Blutzellen, auftrat, was die Hypothese eines selektiven, vorzeitigen Abbaus von unreifen roten Blutzellen widerlegt. Weiterhin wurde in der Zellkultur unter verringerter Sauerstoffgabe eine erhohte Zahl bikonkaver Zellen beobachtet, was eine typische ¨ Gestalt fur einen fortgeschrittenen Reifegrad ist. Diese Beobachtung k ¨ onnte ein Anhaltspunkt daf ¨ ur¨ sein, dass der Reifeprozess von roten Blutzellen durch die Reduzierung des atmospharischen Sauer- ¨ stoffgehaltes begunstigt werden kann. Im Rahmen dieser Arbeit wurde zus ¨ atzlich ein Protokoll zur ¨ Isolation der Retikulozyten vom Vollblut der Probanden entwickelt, um die pure Zell-RNA jeweils vor und in großer Hohe zu sequenzieren. Jedoch muss die Ausbeute an RNA weiter optimiert werden, ¨ um einen detaillierten Vergleich der Gen-Expressions-Niveaus anstellen zu konnen. ¨ Der zweite Teil der Arbeit konzentriert sich auf die Untersuchung der Morphologie der roten Blutkor- ¨ perchen bei zwei Arten von Anamie. Aufgrund der hohen Empfindlichkeit der roten Blutk ¨ orperchen ¨ gegenuber Formvariationen, mussten die Proben vor jeder experimentellen Manipulation fixiert wer- ¨ den. Dazu musste ein angemessenes Verfahren entwicklelt werden, das im Rahmen dieser Arbeit vorgestellt wird. Zunachst wird auf die Sichelzellenan ¨ amie eingegangen, bei der es unter Desoxy- ¨ genierung des Hamoglobins zur starken Verformung der roten Blutk ¨ orperchen (Sichelzellen) kommt. ¨ Dies beintrachtigt sowohl deren Funktion als auch Lebensdauer. Eine quantitative Analyse von Zell- ¨ Projektionsbildern aus konfokalen Mikroskopieaufnahmen wurde mit Hilfe eines maßgeschneiderten Computerprogramms im Rahmen einer klinischen Pilotstudie der Phase II zur Therapie der Sichelzellanamie durchgef ¨ uhrt. Es konnte gezeigt werden, dass diese Methode in Kombination mit anderen ¨ experimentellen Verfahren ein wirkungsvolles Instrument zur Beurteilung des Zellhydratationszustands von Sichelzellenpatienten ist. Daher kann diese Technik zur Beurteilung der Wirksamkeit von Sichelzellen-Therapien oder zur Beurteilung des Zustands der roten Blutkorperchen eines Pa- ¨ tienten verwendet werden. Da die roten Blutkorperchen bei verschiedenen Arten von An ¨ amie auch ¨ verschiedene Formvariationen aufweisen, wurde eine weitere Blutkrankheit, die hereditare Sph ¨ arozy- ¨ tose, untersucht. In diesem Fall lag der Schwerpunkt auf der automatisierten Formerkennung der roten Blutkorperchen, die in der Regel manuell durchgef ¨ uhrt wird und daher einer Bewertungsinkonsistenz ¨ unterliegt. Die Untersuchung nutzt die 3D-Rekonstruktion der Zellen aus konfokalen Mikroskopieaufnahmen und die anschließende Formerkennung mittels kunstlicher neuronaler Netze. Die Beurteilung ¨ dieses Systems zeigte sowohl eine sehr gute Erkennungsrate, hohe Prazision, eine schnelle Prozesszeit, ¨ als auch ein objektives Ergebnis verglichen mit der manuellen Klassifikation. Verglichen mit der Analyse von 2D Mikroskopieaufnahmen von Blutabstrichen, konnten durch die Auswertung korrespondierender 3D Aufnahmen außerdem andere Formspektren abgeleitet werden. Dies legt die Empfehlung nahe, die manuelle Klassifizierung von Zellformen (Stand der Technik) im Kontext von hereditarer Sph ¨ arozytose zu ¨ uberdenken.Human cell viability highly depends on oxygen, which is carried and provided by red blood cells. This thesis aimed to investigate how oxygen influences physiology and pathophysiology of red blood cells and is divided in two main parts. The first one presents results that are part of a larger study performed at high altitude (3450 m). Here, the reduced air pressure causes a decrease in blood oxygenation, which is balanced by an increase in red blood cells production (erythropoiesis). Upon return from high altitude, the amount of red blood cells is restored to the original levels within a few days, which is in contrast with the average red blood cell lifespan of 120 days. The reasons leading to such red blood cells premature clearance are not well understood. A hypothetical mechanism previously proposed is defined as neocytolisis, i.e. the selective clearance of the red blood cells formed at high altitude upon return to sea level. The scientific question of the study was therefore to assess if and how neocytolisis occurs after a 3-week stay at high altitude. The investigations performed in this thesis involved in vitro culture of erythroid precursors of the donors participating in the study to characterize both erythropoiesis and the obtained immature red blood cells, namely reticulocytes. Results highlighted an accelerated maturation of erythroid precursors in cultures performed at lower oxygen (3%) compared to atmospheric oxygen (20%) ones and an unexpected improved cell survival of the obtained reticulocytes. This was in accordance with the finding that after the stay at the chosen altitude no neocytolisis occurred, denying the hypothesis of a higher fragility of cells formed at low oxygen causing their selective premature clearance upon return from high altitude. Moreover, cultures performed at low oxygen resulted in the formation of more biconcave cells, the typical shape of mature red blood cells. This suggests that reducing oxygen levels in cultures may contribute to advance their maturation in vitro. In addition to cell cultures, another objective was to perform RNA sequencing of isolated reticulocytes from whole blood of the donors to compare pre- and high altitude conditions. A protocol for the isolation of a pure fraction of reticulocytes and their RNA was developed. However, total RNA yield needs to be increased to perform an accurate comparison of gene expression levels. The second part of the thesis focused on studying red blood cell morphology in two types of anemia. Because of the high sensitivity of red blood cells to shape variation, samples were always fixed before any experimental manipulation. A thorough study describing how to perform red blood cell fixation is presented. The first blood disease of study was sickle cell anemia. In this pathology, deoxygenation of hemoglobin causes the deformation of red blood cells to the shape of a sickle that impairs their functions and lifespan. The quantitative analysis of cell projections from confocal images by means of a customized computer program was employed within a pilot phase II clinical trial for the therapy of sickle cell disease. The obtained results combined with other experimental evaluations showed that red blood cell shape analysis of sickle cell disease patients is a simple but powerful tool to evaluate cell hydration state. Therefore, this technique may be used for the assessment of the efficacy of sickle cell disease therapies or to evaluate the state of red blood cells of a patient. Since red blood cells display shape variations in different types of anemia, a second blood disease was investigated, namely hereditary spherocytosis. In this case, the focus was the automation of red blood cells shape recognition, which is usually performed manually and therefore subjected to evaluation inconsistency. The investigation made use of 3D cell reconstructions from confocal images and automated shape recognition by means of artificial neural networks. System benchmarks showed a good recognition performance, high accuracy, fast processing time as well unbiased results compared to the manual classification. Moreover, the application of 3D imaging in contrast to the traditional 2D-microscopy typically employed in blood smear analysis revealed a different red blood cell shapes spectrum. These results therefore suggest to revise the state-of-the art manual shape classification applied in hereditary spherocytosis

Effect of space conditions on neuronal plasticity and connectivity

Looking for opportunities to explore new frontiers and developing new technologies have always been in the nature of mankind. In 1957, the first rocket in space opened a new era for space traveling towards other planets. Concomitantly, a wide range of concerns related to human health risks that could occur during spaceflight was raised. Up to now, a large number of experiments has been performed to determine the biological effects of space conditions on human health, in order to develop appropriate countermeasures. However, extensive investigations still need to be performed before considering long-term spaceflight towards other planets such as Mars. Since the first human space flight, it has been observed that in weightlessness conditions, equilibrium sense organs can send misleading inputs to the central nervous system which is forced to develop new strategies and adapt to adequately translate these messages. Furthermore, cosmic radiations are known to induce oxidative stress as well as genomic damages. In this thesis, we studied concomitant microgravity and radiation exposures as models for space conditions and developed various methods to analyse their specific and combined effects on in vitro neuronal network models. In vitro primary neuronal network cultures were established and exposed to simulated space conditions to investigate neuronal network remodelling (plasticity and connectivity) as well as genomic damage/repair dynamics. This work was performed to address questions on neuronal network disorders occurring during spaceflights and, in the future, to develop strategies against these effects

IMCAD: Computer Aided System for Breast Masses Detection based on Immune Recognition

Computer Aided Detection (CAD) systems are very important tools which help radiologists as a second reader in detecting early breast cancer in an efficient way, specially on screening mammograms. One of the challenging problems is the detection of masses, which are powerful signs of cancer, because of their poor apperance on mammograms. This paper investigates an automatic CAD for detection of breast masses in screening mammograms based on fuzzy segmentation and a bio-inspired method for pattern recognition: Artificial Immune Recognition System. The proposed approach is applied to real clinical images from the full field digital mammographic database: Inbreast. In order to validate our proposition, we propose the Receiver Operating Characteristic Curve as an analyzer of our IMCAD classifier system, which achieves a good area under curve, with a sensitivity of 100% and a specificity of 95%. The recognition system based on artificial immunity has shown its efficiency on recognizing masses from a very restricted set of training regions

A Combination of Multilayer Perceptron, Radial Basis Function Artificial Neural Networks and Machine Learning Image Segmentation for the Dimension Reduction and the Prognosis Assessment of Diffuse Large B-Cell Lymphoma

The prognosis of diffuse large B-cell lymphoma (DLBCL) is heterogeneous. Therefore, we aimed to highlight predictive biomarkers. First, artificial intelligence was applied into a discovery series of gene expression of 414 patients (GSE10846). A dimension reduction algorithm aimed to correlate with the overall survival and other clinicopathological variables; and included a combination of Multilayer Perceptron (MLP) and Radial Basis Function (RBF) artificial neural networks, gene-set enrichment analysis (GSEA), Cox regression and other machine learning and predictive analytics modeling [C5.0 algorithm, logistic regression, Bayesian Network, discriminant analysis, random trees, tree-AS, Chi-squared Automatic Interaction Detection CHAID tree, Quest, classification and regression (C&R) tree and neural net)]. From an initial 54,613 gene-probes, a set of 488 genes and a final set of 16 genes were defined. Secondly, two identified markers of the immune checkpoint, PD-L1 (CD274) and IKAROS (IKZF4), were validated in an independent series from Tokai University, and the immunohistochemical expression was quantified, using a machine-learning-based Weka segmentation. High PD-L1 associated with poor overall and progression-free survival, non-GCB phenotype, Epstein–Barr virus infection (EBER+), high RGS1 expression and several clinicopathological variables, such as high IPI and absence of clinical response. Conversely, high expression of IKAROS was associated with a good overall and progression-free survival, GCB phenotype and a positive clinical response to treatment. Finally, the set of 16 genes (PAF1, USP28, SORT1, MAP7D3, FITM2, CENPO, PRCC, ALDH6A1, CSNK2A1, TOR1AIP1, NUP98, UBE2H, UBXN7, SLC44A2, NR2C2AP and LETM1), in combination with PD-L1, IKAROS, BCL2, MYC, CD163 and TNFAIP8, predicted the survival outcome of DLBCL with an overall accuracy of 82.1%. In conclusion, building predictive models of DLBCL is a feasible analytical strategy

Gravity Network for end-to-end small lesion detection

This paper introduces a novel one-stage end-to-end detector specifically designed to detect small lesions in medical images. Precise localization of small lesions presents challenges due to their appearance and the diverse contextual backgrounds in which they are found. To address this, our approach introduces a new type of pixel-based anchor that dynamically moves towards the targeted lesion for detection. We refer to this new architecture as GravityNet, and the novel anchors as gravity points since they appear to be "attracted" by the lesions. We conducted experiments on two well-established medical problems involving small lesions to evaluate the performance of the proposed approach: microcalcifications detection in digital mammograms and microaneurysms detection in digital fundus images. Our method demonstrates promising results in effectively detecting small lesions in these medical imaging tasks

A Study of Raman Spectroscopy as a Clinical Diagnostic Tool for the Detection of Lynch Syndrome/Hereditary NonPolyposis Colorectal Cancer (HNPCC)

Lynch syndrome also known as hereditary non-polyposis colorectal cancer (HNPCC) is a highly penetrant hereditary form of colorectal cancer that accounts for approximately 3% of all cases. It is caused by mutations in DNA mismatch repair resulting in accelerated adenoma to carcinoma progression. The current clinical guidelines used to identify Lynch Syndrome (LS) are known to be too stringent resulting in overall underdiagnoses. Raman spectroscopy is a powerful analytical tool used to probe the molecular vibrations of a sample to provide a unique chemical fingerprint. The potential of using Raman as a diagnostic tool for discriminating LS from sporadic adenocarcinoma is explored within this thesis. A number of experimental parameters were initially optimized for use with formalin fixed paraffin embedded colonic tissue (FFPE). This has resulted in the development of a novel cost-effective backing substrate shown to be superior to the conventionally used calcium fluoride (CaF2). This substrate is a form of silanized super mirror stainless steel that was found to have a much lower Raman background, enhanced Raman signal and complete paraffin removal from FFPE tissues. Performance of the novel substrate was compared against CaF2 by acquiring large high resolution Raman maps from FFPE rat and human colonic tissue. All of the major histological features were discerned from steel mounted tissue with the benefit of clear lipid signals without paraffin obstruction. Biochemical signals were comparable to those obtained on CaF2 with no detectable irregularities. By using principal component analysis to reduce the dimensionality of the dataset it was then possible to use linear discriminant analysis to build a classification model for the discrimination of normal colonic tissue (n=10) from two pathological groups: LS (n=10) and sporadic adenocarcinoma (n=10). Using leaveone-map-out cross-validation of the model classifier has shown that LS was predicted with a sensitivity of 63% and a specificity of 89% - values that are competitive with classification techniques applied routinely in clinical practice

A Pharmaceutical Paradigm for Cardiovascular Composite Risk Assessment Using Novel Radiogenomics Risk Predictors in Precision Explainable Artificial Intelligence Framework: Clinical Trial Tool

Cardiovascular disease (CVD) is challenging to diagnose and treat since symptoms appear late during the progression of atherosclerosis. Conventional risk factors alone are not always sufficient to properly categorize at-risk patients, and clinical risk scores are inadequate in predicting cardiac events. Integrating genomic-based biomarkers (GBBM) found in plasma/serum samples with novel non-invasive radiomics-based biomarkers (RBBM) such as plaque area, plaque burden, and maximum plaque height can improve composite CVD risk prediction in the pharmaceutical paradigm. These biomarkers consider several pathways involved in the pathophysiology of atherosclerosis disease leading to CVD.This review proposes two hypotheses: (i) The composite biomarkers are strongly correlated and can be used to detect the severity of CVD/Stroke precisely, and (ii) an explainable artificial intelligence (XAI)-based composite risk CVD/Stroke model with survival analysis using deep learning (DL) can predict in preventive, precision, and personalized (aiP3) framework benefiting the pharmaceutical paradigm.The PRISMA search technique resulted in 214 studies assessing composite biomarkers using radiogenomics for CVD/Stroke. The study presents a XAI model using AtheroEdgeTM 4.0 to determine the risk of CVD/Stroke in the pharmaceutical framework using the radiogenomics biomarkers.Our observations suggest that the composite CVD risk biomarkers using radiogenomics provide a new dimension to CVD/Stroke risk assessment. The proposed review suggests a unique, unbiased, and XAI model based on AtheroEdgeTM 4.0 that can predict the composite risk of CVD/Stroke using radiogenomics in the pharmaceutical paradigm