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High-resolution diffusion imaging in the unfixed post-mortem infant brain at 7 T
Abstract Diffusion MRI of the infant brain allows investigation of the organizational structure of maturing fibers during brain development. Post-mortem imaging has the potential to achieve high resolution by using long scan times, enabling precise assessment of small structures. Technical development for post-mortem diffusion MRI has primarily focused on scanning of fixed tissue, which is robust to effects like temperature drift that can cause unfixed tissue to degrade. The ability to scan unfixed tissue in the intact body would enable post-mortem studies without organ donation, but poses new technical challenges. This paper describes our approach to scan setup, protocol optimization, and tissue protection in the context of the Developing Human Connectome Project (dHCP) of neonates. A major consideration was the need to preserve the integrity of unfixed tissue during scanning in light of energy deposition at ultra-high magnetic field strength. We present results from one of the first two subjects recruited to the study, who died on postnatal day 46 at 29+6 weeks postmenstrual age, demonstrating high-quality diffusion MRI data. We find altered diffusion properties consistent with post-mortem changes reported previously. Preliminary voxel-wise and tractography analyses are presented with comparison to age-matched in vivo dHCP data. These results show that high-quality, high-resolution post-mortem data of unfixed tissue can be acquired to explore the developing human brain.
Statistical analysis plan for the Petal trial: the effects of parental touch on relieving acute procedural pain in neonates
Background Infants undergo multiple clinically-required painful procedures during their time in hospital, and there is an increasing desire from both parents and clinical staff to have parents directly involved in their newborn’s pain relief. To avoid biases due to selective analysis and reporting, a clinical trial’s statistical analysis plan (SAP) should be finalised and registered prior to dataset lock and unblinding. Here, we outline the SAP for the Petal trial, which was registered on the ISRCTN registry prior to dataset lock and unblinding. Methods The Petal trial is a multicentre, individually randomised, parallel-group interventional superiority trial. The study involves in-patient neonates born at or after 35+0 weeks gestation with a postnatal age of ≤7 days, in two hospital research sites (John Radcliffe Hospital, Oxford, UK; Royal Devon and Exeter Hospital, Exeter, UK). The primary objective is to investigate the potential efficacy of a non-pharmacological parent-led stroking intervention on reducing the magnitude of neonates’ noxious stimulus-evoked brain activity. The primary outcome is the neonate’s brain activity recorded using electroencephalography (EEG) in response to a heel lance blood sampling procedure. Secondary outcomes include neonatal clinical pain scores and tachycardia, and parental anxiety. The study hypothesis is neonates’ pain responses and parents’ anxiety scores are lower in the intervention group. Randomisation will be via a minimisation algorithm to maintain balance in five prognostic factors. Conclusions Paediatric pain trials have been highlighted by regulatory bodies as an important and challenging topic, with interest increasing in brain imaging outcomes. The Petal trial, to which this SAP relates, is part of a larger effort of establishing a brain-based EEG outcome measure of infant pain for use in clinical trials. This SAP is thus likely to be of interest to those in academia, pharmaceutical companies, and regulatory bodies. Trial registration ClinicalTrials.gov: NCT04901611, 25/05/2021; ISRCTN: ISRCTN14135962, 23/08/2021).
Statistical analysis plan for the Petal trial: the effects of parental touch on relieving acute procedural pain in neonates
Background Infants undergo multiple clinically-required painful procedures during their time in hospital, and there is an increasing desire from both parents and clinical staff to have parents directly involved in their newborn’s pain relief. To avoid biases due to selective analysis and reporting, a clinical trial’s statistical analysis plan (SAP) should be finalised and registered prior to dataset lock and unblinding. Here, we outline the SAP for the Petal trial, which was registered on the ISRCTN registry prior to dataset lock and unblinding. Methods The Petal trial is a multicentre, individually randomised, parallel-group interventional superiority trial. The study involves in-patient neonates born at or after 35+0 weeks gestation with a postnatal age of ≤7 days, in two hospital research sites (John Radcliffe Hospital, Oxford, UK; Royal Devon and Exeter Hospital, Exeter, UK). The primary objective is to investigate the potential efficacy of a non-pharmacological parent-led stroking intervention on reducing the magnitude of neonates’ noxious stimulus-evoked brain activity. The primary outcome is the neonate’s brain activity recorded using electroencephalography (EEG) in response to a heel lance blood sampling procedure. Secondary outcomes include neonatal clinical pain scores and tachycardia, and parental anxiety. The study hypothesis is neonates’ pain responses and parents’ anxiety scores are lower in the intervention group. Randomisation will be via a minimisation algorithm to maintain balance in five prognostic factors. Conclusions Paediatric pain trials have been highlighted by regulatory bodies as an important and challenging topic, with interest increasing in brain imaging outcomes. The Petal trial, to which this SAP relates, is part of a larger effort of establishing a brain-based EEG outcome measure of infant pain for use in clinical trials. This SAP is thus likely to be of interest to those in academia, pharmaceutical companies, and regulatory bodies. Trial registration ClinicalTrials.gov: NCT04901611, 25/05/2021; ISRCTN: ISRCTN14135962, 23/08/2021).
Which AI doctor would you like to see? Emulating healthcare provider-patient communication models with GPT-4: proof-of-concept and ethical exploration.
Large language models (LLMs) have demonstrated potential in enhancing various aspects of healthcare, including health provider-patient communication. However, some have raised the concern that such communication may adopt implicit communication norms that deviate from what patients want or need from talking with their healthcare provider. This paper explores the possibility of using LLMs to enable patients to choose their preferred communication style when discussing their medical cases. By providing a proof-of-concept demonstration using ChatGPT-4, we suggest LLMs can emulate different healthcare provider-patient communication approaches (building on Emanuel and Emanuel's four models: paternalistic, informative, interpretive and deliberative). This allows patients to engage in a communication style that aligns with their individual needs and preferences. We also highlight potential risks associated with using LLMs in healthcare communication, such as reinforcing patients' biases and the persuasive capabilities of LLMs that may lead to unintended manipulation.
Physiological responses to retinopathy of prematurity screening: indirect ophthalmoscopy versus ultra-widefield retinal imaging.
BACKGROUND/AIMS: Retinopathy of prematurity (ROP) screening is vital for early disease detection in very premature infants but can cause physiological instability. This study compares the physiological response to binocular indirect ophthalmoscopy (BIO) with indentation and non-contact ultra-widefield (UWF) retinal imaging in non-ventilated neonates. The impact of the Dandle WRAP, a specialised swaddling aid, on UWF imaging was also assessed. METHODS: This retrospective study included 86 ROP screening events in 66 non-ventilated infants aged 35.3 weeks (range 30.6-44.6). Vital signs were continuously recorded, evaluating immediate (within 15 min) and longer-term (within 12 h) physiological responses. RESULTS: ROP screening significantly increased heart and respiratory rates and decreased oxygen saturation within 15 min of screening. No significant differences in physiological responses were found between BIO and UWF imaging, although there was a trend towards lower maximum heart rate with UWF imaging. The Dandle WRAP did not significantly alter physiological responses but improved the ease and speed of UWF imaging. CONCLUSION: UWF imaging does not increase physiological instability compared to BIO in non-ventilated infants. Specialised swaddling aids may facilitate the imaging procedure. IMPACT: ROP screening can be distressing for premature infants and induce physiological instability during and after the examination. We deployed non-contact ultra-widefield retinal imaging as the default method of ROP screening and show that it induces comparable physiological responses as traditional indirect ophthalmoscopy in non-ventilated babies. Dandle WRAP swaddling facilitated handling and speed of retinal imaging. The study demonstrates that imaging-based ROP screening is safe and efficacious in non-ventilated neonates, and continuous multimodal physiological recordings can provide detailed assessment of the effects of procedures and medications.
Severe cognitive disability, medically complex children and long-term ventilation
Children with complex medical conditions including those with severe intellectual disability are living longer. For some, support with medical technology such as Long-Term Ventilation can prolong their lives further. Such technological supports can have significant implications for the child and her family and consume considerable resources though they can also offer real benefits. Sometimes clinicians question whether children with very severe cognitive impairments should have their life prolonged by technology, though they would be prepared to provide the same treatment in equivalent cases without cognitive disability. We describe and analyse four ways in which this view might be justified. Although it could be claimed that children with severe cognitive disability have lives that are not worth living, in most cases this view can and should be rejected. However, the burdens of life-prolonging technology may outweigh the benefits of such treatment either in the present or in the future. Consequently it might not be in their interests to provide such technology, or to ensure that it is provided as part of a time-limited trial. We also consider circumstances where medical technology could offer modest benefits to an individual, but resources are scarce. In the face of resource imitation, treatment may be prioritised to children who stand to benefit the most. This may in some circumstances, justify selectively withholding treatment from some children with significant cognitive disability.
Pushing the boundaries: future directions in the management of spinal muscular atrophy.
Spinal muscular atrophy (SMA) is a devastating, degenerative, paediatric neuromuscular disease which until recently was untreatable. Discovery of the responsible gene 30 years ago heralded a new age of pioneering therapeutic developments. Three disease-modifying therapies (DMTs) have received regulatory approval and have transformed the disease, reducing disability and prolonging patient survival. These therapies - with distinct mechanisms, routes of administration, dosing schedules, side effect profiles, and financial costs - have dramatically altered the clinical phenotypes of this condition and have presented fresh challenges for patient care. In this review article we discuss potential strategies to maximise clinical outcomes through early diagnosis and treatment, optimised dosing, use of therapeutic combinations and state-of-the-art physiotherapy techniques, and the development of innovative therapies targeting alternative mechanisms.
Automated detection of cerebral microbleeds on MR images using knowledge distillation framework.
INTRODUCTION: Cerebral microbleeds (CMBs) are associated with white matter damage, and various neurodegenerative and cerebrovascular diseases. CMBs occur as small, circular hypointense lesions on T2*-weighted gradient recalled echo (GRE) and susceptibility-weighted imaging (SWI) images, and hyperintense on quantitative susceptibility mapping (QSM) images due to their paramagnetic nature. Accurate automated detection of CMBs would help to determine quantitative imaging biomarkers (e.g., CMB count) on large datasets. In this work, we propose a fully automated, deep learning-based, 3-step algorithm, using structural and anatomical properties of CMBs from any single input image modality (e.g., GRE/SWI/QSM) for their accurate detections. METHODS: In our method, the first step consists of an initial candidate detection step that detects CMBs with high sensitivity. In the second step, candidate discrimination step is performed using a knowledge distillation framework, with a multi-tasking teacher network that guides the student network to classify CMB and non-CMB instances in an offline manner. Finally, a morphological clean-up step further reduces false positives using anatomical constraints. We used four datasets consisting of different modalities specified above, acquired using various protocols and with a variety of pathological and demographic characteristics. RESULTS: On cross-validation within datasets, our method achieved a cluster-wise true positive rate (TPR) of over 90% with an average of <2 false positives per subject. The knowledge distillation framework improves the cluster-wise TPR of the student model by 15%. Our method is flexible in terms of the input modality and provides comparable cluster-wise TPR and better cluster-wise precision compared to existing state-of-the-art methods. When evaluating across different datasets, our method showed good generalizability with a cluster-wise TPR >80 % with different modalities. The python implementation of the proposed method is openly available.
Newborn resuscitation and support of transition of infants at birth
The European Resuscitation Council has produced these newborn life support guidelines, which are based on the International Liaison Committee on Resuscitation (ILCOR) 2020 Consensus on Science and Treatment Recommendations (CoSTR) for Neonatal Life Support. The guidelines cover the management of the term and preterm infant. The topics covered include an algorithm to aid a logical approach to resuscitation of the newborn, factors before delivery, training and education, thermal control, management of the umbilical cord after birth, initial assessment and categorisation of the newborn infant, airway and breathing and circulation support, communication with parents, considerations when withholding and discontinuing support.