Method and system for the automatic recognition of lesions in a set of breast magnetic resonance images

A method of identification of potential lesions of a breast from tomographic image datasets of a chest region of a patient, the- datasets comprising a plurality of voxels (2) each having an intensity value, the images including a region of interest (10) which comprises at least one breast (6). The method comprises the steps of: acquiring a set of images after the administration of a contrast agent to the patient; normalizing (254) the intensity of voxels (2) belonging to the region of interest (10) of the acquired images according to at least one normalization factor; classifying (255) each of the normalized voxels (2) on the basis of a classification criterion, in such a way as to identify regions (40) representing potential lesions. The method is characterized in that the normalization factor is based on normalization voxels (2) corresponding to an anatomical structure (34), the normalization voxels (2) having intensity values enhanced due to the administration of the contrast agent

Performance of a fully automatic lesion detection system for breast DCE-MRI

PURPOSE: To describe and test a new fully automatic lesion detection system for breast DCE-MRI. MATERIALS AND METHODS: Studies were collected from two institutions adopting different DCE-MRI sequences, one with and the other one without fat-saturation. The detection pipeline consists of (i) breast segmentation, to identify breast size and location; (ii) registration, to correct for patient movements; (iii) lesion detection, to extract contrast-enhanced regions using a new normalization technique based on the contrast-uptake of mammary vessels; (iv) false positive (FP) reduction, to exclude contrast-enhanced regions other than lesions. Detection rate (number of system-detected malignant and benign lesions over the total number of lesions) and sensitivity (system-detected malignant lesions over the total number of malignant lesions) were assessed. The number of FPs was also assessed. RESULTS: Forty-eight studies with 12 benign and 53 malignant lesions were evaluated. Median lesion diameter was 6 mm (range, 5-15 mm) for benign and 26 mm (range, 5-75 mm) for malignant lesions. Detection rate was 58/65 (89%; 95% confidence interval [CI] 79%-95%) and sensitivity was 52/53 (98%; 95% CI 90%-99%). Mammary median FPs per breast was 4 (1st-3rd quartiles 3-7.25). CONCLUSION: The system showed promising results on MR datasets obtained from different scanners producing fat-sat or non-fat-sat images with variable temporal and spatial resolution and could potentially be used for early diagnosis and staging of breast cancer to reduce reading time and to improve lesion detection. Further evaluation is needed before it may be used in clinical practice

Diferencias en el efecto de los factores socioeconómicos del hogar y las escuelas en el rendimiento escolar entre regiones argentinas

Ningun

Deep learning-based algorithm for postoperative glioblastoma MRI segmentation: a promising new tool for tumor burden assessment

Objective: Clinical and surgical decisions for glioblastoma patients depend on a tumor imaging-based evaluation. Artificial Intelligence (AI) can be applied to magnetic resonance imaging (MRI) assessment to support clinical practice, surgery planning and prognostic predictions. In a real-world context, the current obstacles for AI are low-quality imaging and postoperative reliability. The aim of this study is to train an automatic algorithm for glioblastoma segmentation on a clinical MRI dataset and to obtain reliable results both pre- and post-operatively. Methods: The dataset used for this study comprises 237 (71 preoperative and 166 postoperative) MRIs from 71 patients affected by a histologically confirmed Grade IV Glioma. The implemented U-Net architecture was trained by transfer learning to perform the segmentation task on postoperative MRIs. The training was carried out first on BraTS2021 dataset for preoperative segmentation. Performance is evaluated using DICE score (DS) and Hausdorff 95% (H95). Results: In preoperative scenario, overall DS is 91.09 (± 0.60) and H95 is 8.35 (± 1.12), considering tumor core, enhancing tumor and whole tumor (ET and edema). In postoperative context, overall DS is 72.31 (± 2.88) and H95 is 23.43 (± 7.24), considering resection cavity (RC), gross tumor volume (GTV) and whole tumor (WT). Remarkably, the RC segmentation obtained a mean DS of 63.52 (± 8.90) in postoperative MRIs. Conclusions: The performances achieved by the algorithm are consistent with previous literature for both pre-operative and post-operative glioblastoma's MRI evaluation. Through the proposed algorithm, it is possible to reduce the impact of low-quality images and missing sequences

Effect of natalizumab on disease progression in secondary progressive multiple sclerosis (ASCEND). a phase 3, randomised, double-blind, placebo-controlled trial with an open-label extension

Background: Although several disease-modifying treatments are available for relapsing multiple sclerosis, treatment effects have been more modest in progressive multiple sclerosis and have been observed particularly in actively relapsing subgroups or those with lesion activity on imaging. We sought to assess whether natalizumab slows disease progression in secondary progressive multiple sclerosis, independent of relapses. Methods: ASCEND was a phase 3, randomised, double-blind, placebo-controlled trial (part 1) with an optional 2 year open-label extension (part 2). Enrolled patients aged 18–58 years were natalizumab-naive and had secondary progressive multiple sclerosis for 2 years or more, disability progression unrelated to relapses in the previous year, and Expanded Disability Status Scale (EDSS) scores of 3·0–6·5. In part 1, patients from 163 sites in 17 countries were randomly assigned (1:1) to receive 300 mg intravenous natalizumab or placebo every 4 weeks for 2 years. Patients were stratified by site and by EDSS score (3·0–5·5 vs 6·0–6·5). Patients completing part 1 could enrol in part 2, in which all patients received natalizumab every 4 weeks until the end of the study. Throughout both parts, patients and staff were masked to the treatment received in part 1. The primary outcome in part 1 was the proportion of patients with sustained disability progression, assessed by one or more of three measures: the EDSS, Timed 25-Foot Walk (T25FW), and 9-Hole Peg Test (9HPT). The primary outcome in part 2 was the incidence of adverse events and serious adverse events. Efficacy and safety analyses were done in the intention-to-treat population. This trial is registered with ClinicalTrials.gov, number NCT01416181. Findings: Between Sept 13, 2011, and July 16, 2015, 889 patients were randomly assigned (n=440 to the natalizumab group, n=449 to the placebo group). In part 1, 195 (44%) of 439 natalizumab-treated patients and 214 (48%) of 448 placebo-treated patients had confirmed disability progression (odds ratio [OR] 0·86; 95% CI 0·66–1·13; p=0·287). No treatment effect was observed on the EDSS (OR 1·06, 95% CI 0·74–1·53; nominal p=0·753) or the T25FW (0·98, 0·74–1·30; nominal p=0·914) components of the primary outcome. However, natalizumab treatment reduced 9HPT progression (OR 0·56, 95% CI 0·40–0·80; nominal p=0·001). In part 1, 100 (22%) placebo-treated and 90 (20%) natalizumab-treated patients had serious adverse events. In part 2, 291 natalizumab-continuing patients and 274 natalizumab-naive patients received natalizumab (median follow-up 160 weeks [range 108–221]). Serious adverse events occurred in 39 (13%) patients continuing natalizumab and in 24 (9%) patients initiating natalizumab. Two deaths occurred in part 1, neither of which was considered related to study treatment. No progressive multifocal leukoencephalopathy occurred. Interpretation: Natalizumab treatment for secondary progressive multiple sclerosis did not reduce progression on the primary multicomponent disability endpoint in part 1, but it did reduce progression on its upper-limb component. Longer-term trials are needed to assess whether treatment of secondary progressive multiple sclerosis might produce benefits on additional disability components. Funding: Biogen

Patient adherence to and tolerability of self-administered interferon β-1a using an electronic autoinjection device: a multicentre, open-label, phase IV study

<p>Abstract</p> <p>Background</p> <p>Achieving good adherence to self-injected treatments for multiple sclerosis can be difficult. Injection devices may help to overcome some of the injection-related barriers to adherence that can be experienced by patients. We sought to assess short-term adherence to, and tolerability of, interferon (IFN) β-1a administered via electronic autoinjection device in patients with relapsing-remitting multiple sclerosis (RRMS).</p> <p>Methods</p> <p>BRIDGE (RebiSmart to self-inject Rebif serum-free formulation in a multidose cartridge) was a 12-week, multicentre, open-label, single-arm, observational, Phase IV study in which patients self-administered IFN β-1a (titrated to 44 μg), subcutaneously (sc), three times weekly, via electronic autoinjection device. Patients were assessed at baseline and 4-weekly intervals to Week 12 or early termination (ET) for: physical examinations; diary card completion (baseline, Weeks 4, 8 only); neurological examinations (baseline, Week 12/ET only); MS Treatment Concern Questionnaire (MSTCQ; Weeks 4, 8, 12 only); Convenience Questionnaire (Week 12 only); Hospital Anxiety and Depression Scale (HADS); and Paced Auditory Serial Addition Task (PASAT; baseline only). Adherence was defined as administration of ≥ 80% of scheduled injections, recorded by the autoinjection device.</p> <p>Results</p> <p>Overall, 88.2% (105/119; intent-to-treat population) of patients were adherent; 67.2% (80/119) administered all scheduled injections. Medical reasons accounted for 35.6% (31/87) of missed injections, forgetfulness for 20.6% (18/87). Adherence did not correlate with baseline Expanded Disability Status Scale (<it>P </it>= 0.821) or PASAT (<it>P </it>= 0.952) scores, or pre-study therapy (<it>P </it>= 0.303). No significant changes (baseline-Week 12) in mean HADS depression (<it>P </it>= 0.482) or anxiety (<it>P </it>= 0.156) scores were observed. 'Overall convenience' was the most important reported benefit of the autoinjection device. Device features associated with handling and ease of use were highly rated. Mean MSTCQ scores for 'flu-like' symptoms (<it>P </it>= 0.022) and global side effects (<it>P </it>= 0.002) significantly improved from Week 4-12. Mean MSTCQ scores for pain at injection site and injection pain increased from Week 4-12 (<it>P </it>< 0.001). Adverse events were mild/moderate. No new safety signals were identified.</p> <p>Conclusion</p> <p>Convenience and ease of use of the autoinjection device may improve adherence and, therefore, outcomes, in patients with RRMS receiving sc IFN β-1a.</p> <p>Trial registration</p> <p>EU Clinical Trials Register (EU-CTR; <url>http://www.clinicaltrialsregister.eu</url>): 2009-013333-24</p

Enhancing Students' Critical Reflection on Smart Things Design Through an End-User Development Toolkit

We live in an increasingly connected society, and technology plays a vital part in it. The impact of its social transformation can be seen across many facets of everyday life, including how people relate to others and the environment, as well as how people perceive themselves, their needs and emotions. This assumption led researchers to investigate the need of educating young generations to a reflective attitude toward technology and its impact on society. This paper reports on a study with IoTgo, an end-user development design toolkit that helps young generations to become active protagonists in the design of inclusive smart things, reflecting deeply on the pros and cons of technology in use in their everyday life. Initial results of the study show how design with IoTgo toolkit can lead youth to critically reflect on the design and use of technology in the form of smart things.</p