The ULS23 Challenge Public Training Dataset Part 3

<p>This dataset contains part of the imaging data for the <a href="https://uls23.grand-challenge.org/">Universal Lesion Segmentation Challenge (ULS23).</a> It contains lesion volumes-of-interest (VOI's) for previously released data. It consists of 76 lung lesions from the MDSC_Task06 dataset, 283 pancreas lesion from MDSC_Task07 and 133 colon lesions from MDSC_Task10, 558 abdominal lymph nodes, 379 mediastinal lymph nodes from the NIH-LN dataset. It also contains the weakly annotated CCC18 data, 1.211 lesions, and part of the DeepLesion dataset. The annotations are made available through the <a href="https://github.com/MJJdG/ULS23">Challenge repository on GitHub</a>.<br><br>The Universal Lesion Segmentation 2023 (ULS23) data is licensed under CC BY-NC-SA 4.0 </p&gt

The ULS23 Challenge Public Training Dataset Part 6

<p>This dataset contains part of the imaging data for the <a href="https://uls23.grand-challenge.org/">Universal Lesion Segmentation Challenge (ULS23).</a> It contains lesion volumes-of-interest (VOI's) for part of the weakly annotated DeepLesion data. The annotations are made available through the <a href="https://github.com/MJJdG/ULS23">Challenge repository on GitHub</a>.<br><br>The Universal Lesion Segmentation 2023 (ULS23) data is licensed under CC BY-NC-SA 4.0 </p&gt

The ULS23 Challenge Public Training Dataset Part 2

<p>This dataset contains part of the imaging data for the <a href="https://uls23.grand-challenge.org/">Universal Lesion Segmentation Challenge (ULS23).</a> It contains lesion volumes-of-interest (VOI's) for previously released data. It consists of 333 kidney lesions from the KiTS21 dataset, 2.246 lung lesion from LIDC-IDRI and 888 liver lesions from the LiTS challenge. The annotations are made available through the <a href="https://github.com/MJJdG/ULS23">Challenge repository on GitHub</a>.<br><br>The Universal Lesion Segmentation 2023 (ULS23) data is licensed under CC BY-NC-SA 4.0 </p&gt

The ULS23 Challenge Public Training Dataset Part 5

<p>This dataset contains part of the imaging data for the <a href="https://uls23.grand-challenge.org/">Universal Lesion Segmentation Challenge (ULS23).</a> It contains lesion volumes-of-interest (VOI's) for part of the weakly annotated DeepLesion data. The annotations are made available through the <a href="https://github.com/MJJdG/ULS23">Challenge repository on GitHub</a>.<br><br>The Universal Lesion Segmentation 2023 (ULS23) data is licensed under CC BY-NC-SA 4.0 </p&gt

The ULS23 Challenge Public Training Dataset Part 4

<p>This dataset contains part of the imaging data for the <a href="https://uls23.grand-challenge.org/">Universal Lesion Segmentation Challenge (ULS23).</a> It contains lesion volumes-of-interest (VOI's) for part of the weakly annotated DeepLesion data. The annotations are made available through the <a href="https://github.com/MJJdG/ULS23">Challenge repository on GitHub</a>.<br><br>The Universal Lesion Segmentation 2023 (ULS23) data is licensed under CC BY-NC-SA 4.0 </p&gt

Daily intranasal palivizumab to prevent respiratory syncytial virus infection in healthy preterm infants: a phase 1/2b randomized placebo-controlled trialResearch in context

Summary: Background: Mucosal administration of monoclonal antibodies (mAbs) against respiratory pathogens is a promising alternative for systemic administration because lower doses are required for protection. Clinical development of mucosal mAbs is a highly active field yet clinical proof-of-concept is lacking. Methods: In this investigator-initiated, double-blind, randomized placebo-controlled trial, we evaluated intranasal palivizumab for the prevention of RSV infection in preterm infants (Dutch Trial Register NTR7378 and NTR7403). We randomized infants 1:1 to receive intranasal palivizumab (1 mg/mL) or placebo once daily during the RSV season. Any RSV infection was the primary outcome and RSV hospitalization was the key secondary outcome. The primary outcome was analyzed with a mixed effect logistic regression on the modified intention-to-treat population. Findings: We recruited 268 infants between Jan 14, 2019 and Jan 28, 2021, after which the trial was stopped for futility following the planned interim analysis. Adverse events were similar in both groups (22/134 (16.4%) palivizumab arm versus 26/134 (19.4%) placebo arm). There were 6 dropouts and 168 infants were excluded from the efficacy analyses due to absent RSV circulation during the SARS-CoV-2 pandemic. Any RSV infection was similar in infants in both groups (18/47 (38.3%) palivizumab arm versus 11/47 (23.4%) placebo arm; aOR 2.2, 95% CI 0.7–6.5). Interpretation: Daily intranasal palivizumab did not prevent RSV infection in late preterm infants. Our findings have important implications for the clinical development of mucosal mAbs, namely the necessity of timely interim analyses and further research to understand mucosal antibody half-life. Funding: Funded by the Department of Pediatrics, University Medical Centre Utrecht, the Netherlands