184 research outputs found

    Segmentation of Multiple Sclerosis Lesions across Hospitals: Learn Continually or Train from Scratch?

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    Segmentation of Multiple Sclerosis (MS) lesions is a challenging problem. Several deep-learning-based methods have been proposed in recent years. However, most methods tend to be static, that is, a single model trained on a large, specialized dataset, which does not generalize well. Instead, the model should learn across datasets arriving sequentially from different hospitals by building upon the characteristics of lesions in a continual manner. In this regard, we explore experience replay, a well-known continual learning method, in the context of MS lesion segmentation across multi-contrast data from 8 different hospitals. Our experiments show that replay is able to achieve positive backward transfer and reduce catastrophic forgetting compared to sequential fine-tuning. Furthermore, replay outperforms the multi-domain training, thereby emerging as a promising solution for the segmentation of MS lesions. The code is available at this link: https://github.com/naga-karthik/continual-learning-msComment: Accepted at the Medical Imaging Meets NeurIPS (MedNeurIPS) Workshop 202

    Effectiveness of regional diffusion MRI measures in distinguishing multiple sclerosis abnormalities within the cervical spinal cord

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    ABSTRACT: Introduction Multiple sclerosis (MS) is an inflammatory disorder of the central nervous system. Although conventional magnetic resonance imaging (MRI) is widely used for MS diagnosis and clinical follow-up, quantitative MRI has the potential to provide valuable intrinsic values of tissue properties that can enhance accuracy. In this study, we investigate the efficacy of diffusion MRI in distinguishing MS lesions within the cervical spinal cord, using a combination of metrics extracted from diffusion tensor imaging and Ball-and-Stick models. Methods We analyzed spinal cord data acquired from multiple hospitals and extracted average diffusion MRI metrics per vertebral level using a collection of image processing methods and an atlas-based approach. We then performed a statistical analysis to evaluate the feasibility of these metrics for detecting lesions, exploring the usefulness of combining different metrics to improve accuracy. Results Our study demonstrates the sensitivity of each metric to underlying microstructure changes in MS patients. We show that selecting a specific subset of metrics, which provide complementary information, significantly improves the prediction score of lesion presence in the cervical spinal cord. Furthermore, the Ball-and-Stick model has the potential to provide novel information about the microstructure of damaged tissue. Conclusion Our results suggest that diffusion measures, particularly combined measures, are sensitive in discriminating abnormal from healthy cervical vertebral levels in patients. This information could aid in improving MS diagnosis and clinical follow-up. Our study highlights the potential of the Ball-and-Stick model in providing additional insights into the microstructure of the damaged tissue

    First Evidence of Palytoxin and 42-Hydroxy-palytoxin in the Marine Cyanobacterium Trichodesmium

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    Marine pelagic diazotrophic cyanobacteria of the genus Trichodesmium (Oscillatoriales) are widespread throughout the tropics and subtropics, and are particularly common in the waters of New Caledonia. Blooms of Trichodesmium are suspected to be a potential source of toxins in the ciguatera food chain and were previously reported to contain several types of paralyzing toxins. The toxicity of water-soluble extracts of Trichodesmium spp. were analyzed by mouse bioassay and Neuroblastoma assay and their toxic compounds characterized using liquid chromatography coupled with tandem mass spectrometry techniques. Here, we report the first identification of palytoxin and one of its derivatives, 42-hydroxy-palytoxin, in field samples of Trichodesmium collected in the New Caledonian lagoon. The possible role played by Trichodesmium blooms in the development of clupeotoxism, this human intoxication following the ingestion of plankton-eating fish and classically associated with Ostreopsis blooms, is also discussed

    Protein expression, survival and docetaxel benefit in node-positive breast cancer treated with adjuvant chemotherapy in the FNCLCC - PACS 01 randomized trial

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    International audienceABSTRACT: INTRODUCTION: The PACS01 trial has demonstrated that docetaxel addition to adjuvant anthracycline-based chemotherapy improves disease-free survival (DFS) and overall survival of node-positive early breast cancer (EBC). We searched for prognostic and predictive markers for docetaxel benefit. METHODS: Tumor samples from 1.099 recruited women were analyzed for the expression of 34 selected proteins using immunohistochemistry. The prognostic and predictive values of each marker and four molecular subtypes (luminal A, luminal B, HER2-overexpressing, and triple-negative) were tested. RESULTS: Progesterone receptor-negativity (HR=0.66; 95%CI 0.47-0.92, P=0.013), and Ki67-positivity (HR=1.53; 95%CI 1.12-2.08, P=0.007) were independent adverse prognostic factors. Out of the 34 proteins, only Ki67-positivity was associated with DFS improvement with docetaxel addition (adjusted HR=0.51, 95%CI 0.33-0.79 for Ki67-positive versus HR=1.10, 95%CI 0.75-1.61 for Ki67-negative tumors, P for interaction=0.012). Molecular subtyping predicted the docetaxel benefit, but without providing additional information to Ki67 status. The luminal A subtype did not benefit from docetaxel (HR=1.16, 95%CI 0.73-1.84); the reduction in the relapse risk was 53% (HR=0.47, 95%CI 0.22-1.01), 34% (HR=0.66, 95%CI 0.37-1.19), and 12% (HR=0.88, 95%CI 0.49-1.57) in the luminal B, HER2-overexpressing, and triple-negative subtypes, respectively. CONCLUSIONS: In patients with node-positive EBC receiving adjuvant anthracycline-based chemotherapy, the most powerful predictor of docetaxel benefit is Ki67-positivity

    JAMA Neurol

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    Importance: Moderately effective therapies (METs) have been the main treatment in pediatric-onset multiple sclerosis (POMS) for years. Despite the expanding use of highly effective therapies (HETs), treatment strategies for POMS still lack consensus.Objective: To assess the real-world association of HET as an index treatment compared with MET with disease activity.Design, setting, and participants: This was a retrospective cohort study conducted from January 1, 2010, to December 8, 2022, until the last recorded visit. The median follow-up was 5.8 years. A total of 36 French MS centers participated in the Observatoire Français de la Sclérose en Plaques (OFSEP) cohort. Of the total participants in OFSEP, only treatment-naive children with relapsing-remitting POMS who received a first HET or MET before adulthood and at least 1 follow-up clinical visit were included in the study. All eligible participants were included in the study, and none declined to participate.Exposure: HET or MET at treatment initiation.Main outcomes and measures: The primary outcome was the time to first relapse after treatment. Secondary outcomes were annualized relapse rate (ARR), magnetic resonance imaging (MRI) activity, time to Expanded Disability Status Scale (EDSS) progression, tertiary education attainment, and treatment safety/tolerability. An adapted statistical method was used to model the logarithm of event rate by penalized splines of time, allowing adjustment for effects of covariates that is sensitive to nonlinearity and interactions.Results: Of the 3841 children (5.2% of 74 367 total participants in OFSEP), 530 patients (mean [SD] age, 16.0 [1.8] years; 364 female [68.7%]) were included in the study. In study patients, both treatment strategies were associated with a reduced risk of first relapse within the first 2 years. HET dampened disease activity with a 54% reduction in first relapse risk (adjusted hazard ratio [HR], 0.46; 95% CI, 0.31-0.67; P < .001) sustained over 5 years, confirmed on MRI activity (adjusted odds ratio [OR], 0.34; 95% CI, 0.18-0.66; P = .001), and with a better tolerability pattern than MET. The risk of discontinuation at 2 years was 6 times higher with MET (HR, 5.97; 95% CI, 2.92-12.20). The primary reasons for treatment discontinuation were lack of efficacy and intolerance. Index treatment was not associated with EDSS progression or tertiary education attainment (adjusted OR, 0.51; 95% CI, 0.24-1.10; P = .09).Conclusions and relevance: Results of this cohort study suggest that compared with MET, initial HET in POMS was associated with a reduction in the risk of first relapse with an optimal outcome within the first 2 years and was associated with a lower rate of treatment switching and a better midterm tolerance in children. These findings suggest prioritizing initial HET in POMS, although long-term safety studies are needed.Observatoire Français de la Sclérose en Plaque

    Genetic predisposition to in situ and invasive lobular carcinoma of the breast.

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    Invasive lobular breast cancer (ILC) accounts for 10-15% of all invasive breast carcinomas. It is generally ER positive (ER+) and often associated with lobular carcinoma in situ (LCIS). Genome-wide association studies have identified more than 70 common polymorphisms that predispose to breast cancer, but these studies included predominantly ductal (IDC) carcinomas. To identify novel common polymorphisms that predispose to ILC and LCIS, we pooled data from 6,023 cases (5,622 ILC, 401 pure LCIS) and 34,271 controls from 36 studies genotyped using the iCOGS chip. Six novel SNPs most strongly associated with ILC/LCIS in the pooled analysis were genotyped in a further 516 lobular cases (482 ILC, 36 LCIS) and 1,467 controls. These analyses identified a lobular-specific SNP at 7q34 (rs11977670, OR (95%CI) for ILC = 1.13 (1.09-1.18), P = 6.0 × 10(-10); P-het for ILC vs IDC ER+ tumors = 1.8 × 10(-4)). Of the 75 known breast cancer polymorphisms that were genotyped, 56 were associated with ILC and 15 with LCIS at P<0.05. Two SNPs showed significantly stronger associations for ILC than LCIS (rs2981579/10q26/FGFR2, P-het = 0.04 and rs889312/5q11/MAP3K1, P-het = 0.03); and two showed stronger associations for LCIS than ILC (rs6678914/1q32/LGR6, P-het = 0.001 and rs1752911/6q14, P-het = 0.04). In addition, seven of the 75 known loci showed significant differences between ER+ tumors with IDC and ILC histology, three of these showing stronger associations for ILC (rs11249433/1p11, rs2981579/10q26/FGFR2 and rs10995190/10q21/ZNF365) and four associated only with IDC (5p12/rs10941679; rs2588809/14q24/RAD51L1, rs6472903/8q21 and rs1550623/2q31/CDCA7). In conclusion, we have identified one novel lobular breast cancer specific predisposition polymorphism at 7q34, and shown for the first time that common breast cancer polymorphisms predispose to LCIS. We have shown that many of the ER+ breast cancer predisposition loci also predispose to ILC, although there is some heterogeneity between ER+ lobular and ER+ IDC tumors. These data provide evidence for overlapping, but distinct etiological pathways within ER+ breast cancer between morphological subtypes

    DMTs and Covid-19 severity in MS: a pooled analysis from Italy and France

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    We evaluated the effect of DMTs on Covid-19 severity in patients with MS, with a pooled-analysis of two large cohorts from Italy and France. The association of baseline characteristics and DMTs with Covid-19 severity was assessed by multivariate ordinal-logistic models and pooled by a fixed-effect meta-analysis. 1066 patients with MS from Italy and 721 from France were included. In the multivariate model, anti-CD20 therapies were significantly associated (OR&nbsp;=&nbsp;2.05, 95%CI&nbsp;=&nbsp;1.39–3.02, p&nbsp;&lt;&nbsp;0.001) with Covid-19 severity, whereas interferon indicated a decreased risk (OR&nbsp;=&nbsp;0.42, 95%CI&nbsp;=&nbsp;0.18–0.99, p&nbsp;=&nbsp;0.047). This pooled-analysis confirms an increased risk of severe Covid-19 in patients on anti-CD20 therapies and supports the protective role of interferon

    Fine-Scale Mapping of the 4q24 Locus Identifies Two Independent Loci Associated with Breast Cancer Risk

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    Background: A recent association study identified a common variant (rs9790517) at 4q24 to be associated with breast cancer risk. Independent association signals and potential functional variants in this locus have not been explored. Methods: We conducted a fine-mapping analysis in 55,540 breast cancer cases and 51,168 controls from the Breast Cancer Association Consortium. Results: Conditional analyses identified two independent association signals among women of European ancestry, represented by rs9790517 [conditional P = 2.51 × 10−4; OR, 1.04; 95% confidence interval (CI), 1.02–1.07] and rs77928427 (P = 1.86 × 10−4; OR, 1.04; 95% CI, 1.02–1.07). Functional annotation using data from the Encyclopedia of DNA Elements (ENCODE) project revealed two putative functional variants, rs62331150 and rs73838678 in linkage disequilibrium (LD) with rs9790517 (r2 ≥ 0.90) residing in the active promoter or enhancer, respectively, of the nearest gene, TET2. Both variants are located in DNase I hypersensitivity and transcription factor–binding sites. Using data from both The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), we showed that rs62331150 was associated with level of expression of TET2 in breast normal and tumor tissue. Conclusion: Our study identified two independent association signals at 4q24 in relation to breast cancer risk and suggested that observed association in this locus may be mediated through the regulation of TET2. Impact: Fine-mapping study with large sample size warranted for identification of independent loci for breast cancer risk
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