145 research outputs found

    Deep Learning-Based Assessment of Cerebral Microbleeds in COVID-19

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    Cerebral Microbleeds (CMBs), typically captured as hypointensities from susceptibility-weighted imaging (SWI), are particularly important for the study of dementia, cerebrovascular disease, and normal aging. Recent studies on COVID-19 have shown an increase in CMBs of coronavirus cases. Automatic detection of CMBs is challenging due to the small size and amount of CMBs making the classes highly imbalanced, lack of publicly available annotated data, and similarity with CMB mimics such as calcifications, irons, and veins. Hence, the existing deep learning methods are mostly trained on very limited research data and fail to generalize to unseen data with high variability and cannot be used in clinical setups. To this end, we propose an efficient 3D deep learning framework that is actively trained on multi-domain data. Two public datasets assigned for normal aging, stroke, and Alzheimer's disease analysis as well as an in-house dataset for COVID-19 assessment are used to train and evaluate the models. The obtained results show that the proposed method is robust to low-resolution images and achieves 78% recall and 80% precision on the entire test set with an average false positive of 1.6 per scan.Comment: International Symposium on Biomedical Imaging (ISBI) 202

    Long-term recurrence and complication rates after incisional hernia repair with the open onlay technique

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    <p>Abstract</p> <p>Background</p> <p>Incisional hernia after abdominal surgery is a well-known complication. Controversy still exists with respect to the choice of hernia repair technique. The objective of this study was to evaluate the long-term recurrence rate as well as surgical complications in a consecutive group of patients undergoing open repair using an onlay mesh technique.</p> <p>Methods</p> <p>Consecutive patients undergoing open incisional hernia repair with onlay-technique between 01/05/1995 and 01/09/2007 at a single institution were included in the study. For follow-up patients were contacted by telephone, and answered a questionnaire containing questions related to the primary operation, the hernia and general risk factors. Patients were examined by a consultant surgeon in the outpatient clinic or in the patient's home if there was suspicion of an incisional hernia recurrence.</p> <p>Results</p> <p>The study included 56 patients with 100% follow-up. The median follow-up was 35 months (range 4–151). Recurrent incisional hernia was found in 8 of 56 patients (15%, 95% CI: 6–24). The overall complication rate was 13% (95% CI, 4–22). All complications were minor and needed no hospital admission.</p> <p>Conclusion</p> <p>This study with a long follow-up showed low recurrence and complication rates in patients undergoing incisional hernia repair with the open onlay technique.</p

    Allelic Lineages of the Ficolin Genes (FCNs) Are Passed from Ancestral to Descendant Primates

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    The ficolins recognize carbohydrates and acetylated compounds on microorganisms and dying host cells and are able to activate the lectin pathway of the complement system. In humans, three ficolin genes have been identified: FCN1, FCN2 and FCN3, which encode ficolin-1, ficolin-2 and ficolin-3, respectively. Rodents have only two ficolins designated ficolin-A and ficolin-B that are closely related to human ficolin-1, while the rodent FCN3 orthologue is a pseudogene. Ficolin-2 and ficolin-3 have so far only been observed in humans. Thus, we performed a systematic investigation of the FCN genes in non-human primates. The exons and intron-exon boundaries of the FCN1-3 genes were sequenced in the following primate species: chimpanzee, gorilla, orangutan, rhesus macaque, cynomolgus macaque, baboon and common marmoset. We found that the exon organisation of the FCN genes was very similar between all the non-human primates and the human FCN genes. Several variations in the FCN genes were found in more than one primate specie suggesting that they were carried from one species to another including humans. The amino acid diversity of the ficolins among human and non-human primate species was estimated by calculating the Shannon entropy revealing that all three proteins are generally highly conserved. Ficolin-1 and ficolin-2 showed the highest diversity, whereas ficolin-3 was more conserved. Ficolin-2 and ficolin-3 were present in non-human primate sera with the same characteristic oligomeric structures as seen in human serum. Taken together all the FCN genes show the same characteristics in lower and higher primates. The existence of trans-species polymorphisms suggests that different FCN allelic lineages may be passed from ancestral to descendant species

    Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: The CADDementia challenge

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    Algorithms for computer-aided diagnosis of dementia based on structural MRI have demonstrated high performance in the literature, but are difficult to compare as different data sets and methodology were used for evaluation. In addition, it is unclear how the algorithms would perform on previously unseen data, and thus, how they would perform in clinical practice when there is no real opportunity to adapt the algorithm to the data at hand. To address these comparability, generalizability and clinical applicability issues, we organized a grand challenge that aimed to objectively compare algorithms based on a clinically representative multi-center data set. Using clinical practice as the starting point, the goal was to reproduce the clinical diagnosis. Therefore, we evaluated algorithms for multi-class classification of three diagnostic groups: patients with probable Alzheimer's disease, patients with mild cognitive impairment and healthy controls. The diagnosis based on clinical criteria was used as reference standard, as it was the best available reference despite its known limitations. For evaluation, a previously unseen test set was used consisting of 354 T1-weighted MRI scans with the diagnoses blinded. Fifteen research teams participated with a total of 29 algorithms. The algorithms were trained on a small training set (n = 30) and optionally on data from other sources (e.g., the Alzheimer's Disease Neuroimaging Initiative, the Australian Imaging Biomarkers and Lifestyle flagship study of aging). The best performing algorithm yielded an accuracy of 63.0% and an area under the receiver-operating-characteristic curve (AUC) of 78.8%. In general, the best performances were achieved using feature extraction based on voxel-based morphometry or a combination of features that included volume, cortical thickness, shape and intensity. The challenge is open for new submissions via the web-based framework: http://caddementia.grand-challenge.org

    Lupus-related single nucleotide polymorphisms and risk of diffuse large B-cell lymphoma

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    Objective: Determinants of the increased risk of diffuse large B-cell lymphoma (DLBCL) in SLE are unclear. Using data from a recent lymphoma genome-wide association study (GWAS), we assessed whether certain lupus-related single nucleotide polymorphisms (SNPs) were also associated with DLBCL. Methods: GWAS data on European Caucasians from the International Lymphoma Epidemiology Consortium (InterLymph) provided a total of 3857 DLBCL cases and 7666 general-population controls. Data were pooled in a random-effects meta-analysis. Results: Among the 28 SLE-related SNPs investigated, the two most convincingly associated with risk of DLBCL included the CD40 SLE risk allele rs4810485 on chromosome 20q13 (OR per risk allele=1.09, 95% CI 1.02 to 1.16, p=0.0134), and the HLA SLE risk allele rs1270942 on chromosome 6p21.33 (OR per risk allele=1.17, 95% CI 1.01 to 1.36, p=0.0362). Of additional possible interest were rs2205960 and rs12537284. The rs2205960 SNP, related to a cytokine of the tumour necrosis factor superfamily TNFSF4, was associated with an OR per risk allele of 1.07, 95% CI 1.00 to 1.16, p=0.0549. The OR for the rs12537284 (chromosome 7q32, IRF5 gene) risk allele was 1.08, 95% CI 0.99 to 1.18, p=0.0765. Conclusions: These data suggest several plausible genetic links between DLBCL and SLE

    Genetically predicted longer telomere length is associated with increased risk of B-cell lymphoma subtypes

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    Evidence from a small number of studies suggests that longer telomere length measured in peripheral leukocytes is associated with an increased risk of non-Hodgkin lymphoma (NHL). However, these studies may be biased by reverse causation, confounded by unmeasured environmental exposures and might miss time points for which prospective telomere measurement would best reveal a relationship between telomere length and NHL risk. We performed an analysis of genetically inferred telomere length and NHL risk in a study of 10 102 NHL cases of the four most common B-cell histologic types and 9562 controls using a genetic risk score (GRS) comprising nine telomere length-associated single-nucleotide polymorphisms. This approach uses existing genotype data and estimates telomere length by weighing the number of telomere length-associated variant alleles an individual carries with the published change in kb of telomere length. The analysis of the telomere length GRS resulted in an association between longer telomere length and increased NHL risk [four B-cell histologic types combined; odds ratio (OR) = 1.49, 95% CI 1.22–1.82, P-value = 8.5 × 10−5]. Subtype-specific analyses indicated that chronic lymphocytic leukemia or small lymphocytic lymphoma (CLL/SLL) was the principal NHL subtype contributing to this association (OR = 2.60, 95% CI 1.93–3.51, P-value = 4.0 × 10−10). Significant interactions were observed across strata of sex for CLL/SLL and marginal zone lymphoma subtypes as well as age for the follicular lymphoma subtype. Our results indicate that a genetic background that favors longer telomere length may increase NHL risk, particularly risk of CLL/SLL, and are consistent with earlier studies relating longer telomere length with increased NHL risk

    Identification of a BRCA2-Specific modifier locus at 6p24 related to breast cancer risk

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    Common genetic variants contribute to the observed variation in breast cancer risk for BRCA2 mutation carriers; those known to date have all been found through population-based genome-wide association studies (GWAS). To comprehensively identify breast cancer risk modifying loci for BRCA2 mutation carriers, we conducted a deep replication of an ongoing GWAS discovery study. Using the ranked P-values of the breast cancer associations with the imputed genotype of 1.4 M SNPs, 19,029 SNPs were selected and designed for inclusion on a custom Illumina array that included a total of 211,155 SNPs as part of a multi-consortial project. DNA samples from 3,881 breast cancer affected and 4,330 unaffected BRCA2 mutation carriers from 47 studies belonging to the Consortium of Investigators of Modifiers of BRCA1/2 were genotyped and available for analysis. We replicated previously reported breast cancer susceptibility alleles in these BRCA2 mutation carriers and for several regions (including FGFR2, MAP3K1, CDKN2A/B, and PTHLH) identified SNPs that have stronger evidence of association than those previously published. We also identified a novel susceptibility allele at 6p24 that was inversely associated with risk in BRCA2 mutation carriers (rs9348512; per allele HR = 0.85, 95% CI 0.80-0.90, P = 3.9×10−8). This SNP was not associated with breast cancer risk either in the general population or in BRCA1 mutation carriers. The locus lies within a region containing TFAP2A, which encodes a transcriptional activation protein that interacts with several tumor suppressor genes. This report identifies the first breast cancer risk locus specific to a BRCA2 mutation background. This comprehensive update of novel and previously reported breast cancer susceptibility loci contributes to the establishment of a panel of SNPs that modify breast cancer risk in BRCA2 mutation carriers. This panel may have clinical utility for women with BRCA2 mutations weighing options for medical prevention of breast cancer
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