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From April 2022, current Deprivation of Liberty Safeguards (DoLS) will be replaced by Liberty Protection Safeguards (LPS). This review article outlines key information about these changes for patients, carers and healthcare professionals, for whom a deprivation of liberty may be relevant.Deprivation of liberty occurs within healthcare settings when someone's freedoms are limited in order to meet their care needs and lack capacity to consent to these arrangements. DoLS, enacted in 2009, ensured that patients deprived of liberties in care settings have similar rights to patients held under the Mental Health Act 1983. However, DoLS have been extensively criticised and considered unfit for purpose, therefore are being replaced by LPS.LPS intend to provide a more robust protection to a wider group of vulnerable people. This includes changes to patient age, transferability between a wider range of care settings, a reduced number of assessments for authorisation and less frequent reauthorisations.
RESUMO
Background: Spina bifida aperta (SBA) is a birth defect associated with severe anatomical changes in the developing fetal brain. Brain magnetic resonance imaging (MRI) atlases are popular tools for studying neuropathology in the brain anatomy, but previous fetal brain MRI atlases have focused on the normal fetal brain. We aimed to develop a spatio-temporal fetal brain MRI atlas for SBA. Methods: We developed a semi-automatic computational method to compute the first spatio-temporal fetal brain MRI atlas for SBA. We used 90 MRIs of fetuses with SBA with gestational ages ranging from 21 to 35 weeks. Isotropic and motion-free 3D reconstructed MRIs were obtained for all the examinations. We propose a protocol for the annotation of anatomical landmarks in brain 3D MRI of fetuses with SBA with the aim of making spatial alignment of abnormal fetal brain MRIs more robust. In addition, we propose a weighted generalized Procrustes method based on the anatomical landmarks for the initialization of the atlas. The proposed weighted generalized Procrustes can handle temporal regularization and missing annotations. After initialization, the atlas is refined iteratively using non-linear image registration based on the image intensity and the anatomical land-marks. A semi-automatic method is used to obtain a parcellation of our fetal brain atlas into eight tissue types: white matter, ventricular system, cerebellum, extra-axial cerebrospinal fluid, cortical gray matter, deep gray matter, brainstem, and corpus callosum. Results: An intra-rater variability analysis suggests that the seven anatomical land-marks are sufficiently reliable. We find that the proposed atlas outperforms a normal fetal brain atlas for the automatic segmentation of brain 3D MRI of fetuses with SBA. Conclusions: We make publicly available a spatio-temporal fetal brain MRI atlas for SBA, available here: https://doi.org/10.7303/syn25887675. This atlas can support future research on automatic segmentation methods for brain 3D MRI of fetuses with SBA.
