DEcreased Cognitive functiON, NEurovascular CorrelaTes and myocardial changes in women with a history of pre-eclampsia (DECONNECT): research protocol for a cross-sectional pilot study

INTRODUCTION

Pre-eclampsia is a hypertensive disorder affecting up to 8% of pregnancies. After pre-eclampsia, women are at increased risk of cognitive problems, and cerebrovascular and cardiovascular disorders. These sequelae could result from microvascular dysfunction persisting after pre-eclampsia. This study will explore differences in cerebral and myocardial microvascular function between women after pre-eclampsia and women after normotensive gestation. We hypothesise that pre-eclampsia alters cerebral and myocardial microvascular functions, which in turn are related to diminished cognitive and cardiac performance.

METHODS AND ANALYSIS

The cross-sectional 'DEcreased Cognitive functiON, NEurovascular CorrelaTes and myocardial changes in women with a history of pre-eclampsia' (DECONNECT) pilot study includes women after pre-eclampsia and controls after normotensive pregnancy between 6 months and 20 years after gestation. We recruit women from the Queen of Hearts study, a study investigating subclinical heart failure after pre-eclampsia. Neuropsychological tests are employed to assess different cognitive domains, including attention, processing speed, and cognitive control. Cerebral images are recorded using a 7 Tesla MRI to assess blood-brain barrier integrity, perfusion, blood flow, functional and structural networks, and anatomical dimensions. Cardiac images are recorded using a 3 Tesla MRI to assess cardiac perfusion, strain, dimensions, mass, and degree of fibrosis. We assess the effect of a history of pre-eclampsia using multivariable regression analyses.

ETHICS AND DISSEMINATION

This study is approved by the Ethics Committee of Maastricht University Medical Centre (METC azM/UM, NL47252.068.14). Knowledge dissemination will include scientific publications, presentations at conferences and public forums, and social media.

TRIAL REGISTRATION NUMBER

NCT02347540.

PET imaging of unruptured intracranial aneurysm inflammation (PET-IA) study: a feasibility study protocol

INTRODUCTION

Positron emission tomography (PET) imaging can be used to evaluate arterial wall inflammation in extracranial vascular diseases. However, the application of PET imaging in unruptured intracranial aneurysms (UIA) remains unexplored. Our objective is to investigate feasibility of PET imaging using 18F-FDG and 68Ga-DOTANOC tracers to evaluate arterial wall inflammation in UIA.

METHODS AND ANALYSIS

This PET imaging feasibility study will enrol patients scheduled for surgical treatment of UIA. The study subjects will undergo PET imaging of the intracranial arteries within 1 month before planned surgery. The imaging protocol includes 18F-FDG PET MRI, MRA with gadolinium enhancement, and 68Ga-DOTANOC PET CT. The study will also involve preoperative blood samples, intraoperative cerebrospinal fluid (CSF) samples, and aneurysm sac biopsy. Planned sample size is at least 18 patients. Primary outcome is uptake of 18F-FDG or 68Ga-DOTANOC in intracranial arterial aneurysms compared with contralateral normal vessel as maximum standardised uptake value or target-to-blood pool ratio and correlation of uptake of 18F-FDG or 68Ga-DOTANOC to aneurysm histological findings. Secondary outcomes include estimating the correlations between uptake of 18F-FDG or 68Ga-DOTANOC and histological findings with blood and CSF miRNA-levels, arterial wall enhancement in gadolinium enhanced MRA, aneurysm size and shape, smoking, hypertension, and location of the aneurysm.

ETHICS AND DISSEMINATION

This study is approved by the Human Research Ethics Committee of the Hospital District of Southwest Finland, Finnish Medicines Agency Fimea, and Turku University Hospital. Findings will be disseminated through peer-reviewed journal articles and presentations at national and international conferences.

TRIAL REGISTRATION NUMBER

NCT04715503.

AI assisted reader evaluation in acute CT head interpretation (AI-REACT): protocol for a multireader multicase study

INTRODUCTION

A non-contrast CT head scan (NCCTH) is the most common cross-sectional imaging investigation requested in the emergency department. Advances in computer vision have led to development of several artificial intelligence (AI) tools to detect abnormalities on NCCTH. These tools are intended to provide clinical decision support for clinicians, rather than stand-alone diagnostic devices. However, validation studies mostly compare AI performance against radiologists, and there is relative paucity of evidence on the impact of AI assistance on other healthcare staff who review NCCTH in their daily clinical practice.

METHODS AND ANALYSIS

A retrospective data set of 150 NCCTH will be compiled, to include 60 control cases and 90 cases with intracranial haemorrhage, hypodensities suggestive of infarct, midline shift, mass effect or skull fracture. The intracranial haemorrhage cases will be subclassified into extradural, subdural, subarachnoid, intraparenchymal and intraventricular. 30 readers will be recruited across four National Health Service (NHS) trusts including 10 general radiologists, 15 emergency medicine clinicians and 5 CT radiographers of varying experience. Readers will interpret each scan first without, then with, the assistance of the qER EU 2.0 AI tool, with an intervening 2-week washout period. Using a panel of neuroradiologists as ground truth, the stand-alone performance of qER will be assessed, and its impact on the readers' performance will be analysed as change in accuracy (area under the curve), median review time per scan and self-reported diagnostic confidence. Subgroup analyses will be performed by reader professional group, reader seniority, pathological finding, and neuroradiologist-rated difficulty.

ETHICS AND DISSEMINATION

The study has been approved by the UK Healthcare Research Authority (IRAS 310995, approved 13 December 2022). The use of anonymised retrospective NCCTH has been authorised by Oxford University Hospitals. The results will be presented at relevant conferences and published in a peer-reviewed journal.

TRIAL REGISTRATION NUMBER

NCT06018545.

Artificial intelligence in detecting dentomaxillofacial fractures in diagnostic imaging: a scoping review protocol

INTRODUCTION

The dentomaxillofacial (DMF) area, which includes the teeth, maxilla, mandible, zygomaticum, orbits and midface, plays a crucial role in the maintenance of the physiological functions despite its susceptibility to fractures, which are mostly caused by mechanical trauma. As a diagnostic tool, radiographic imaging helps clinicians establish a diagnosis and determine a treatment plan; however, the presence of human factors in image interpretation can result in missed detection of fractures. Therefore, an artificial intelligence (AI) computing system with the potential to help detect abnormalities on radiographic images is currently being developed. This scoping review summarises the literature and assesses the current status of AI in DMF fracture detection in diagnostic imaging.

METHODS AND ANALYSIS

This proposed scoping review will be conducted using the framework of Arksey and O'Malley, with each step incorporating the recommendations of Levac et al. By using relevant keywords based on the research questions. PubMed, Science Direct, Scopus, Cochrane Library, Springerlink, Institute of Electrical and Electronics Engineers, and ProQuest will be the databases used in this study. The included studies are published in English between 1 January 2000 and 30 June 2023. Two independent reviewers will screen titles and abstracts, followed by full-text screening and data extraction, which will comprise three components: research study characteristics, comparator and AI characteristics.

ETHICS AND DISSEMINATION

This study does not require ethical approval because it analyses primary research articles. The research findings will be distributed through international conferences and peer-reviewed publications.

Protocol for a living systematic review for the management of concussion in adults

INTRODUCTION

Concussion/mild traumatic brain injury (mTBI) often presents initially with disabling symptoms that resolve, but for an unfortunate minority some of these symptoms may become prolonged. Although research into diagnosis and interventions for concussion is increasing, study quality overall remains low. A living systematic review that is updated as evidence becomes available is the ideal research activity to inform a living guideline targeting clinicians and patients. The purpose of this paper is to present the protocol of an ongoing living systematic review for the management of adult concussion that will inform living guidelines building off the Guideline for Concussion/Mild Traumatic Brain Injury and Persistent Symptoms: third Edition.

METHODS AND ANALYSIS

The Preferred Reporting Items for Systematic Review and Meta-Analysis Protocol guidelines were followed in the reporting of this systematic review protocol. We are including English peer-reviewed observational studies, trials, qualitative studies, systematic reviews and clinical practice guidelines related to diagnosis/assessment or treatment of adult concussion. Future searches will be conducted at minimum every 6 months using the following databases: MEDLINE ALL, EMBASE, Cochrane, PsycInfo and CINAHL. The data are managed in the Covidence website. Screening, data extraction and risk-of-bias assessments are being done through multiple raters working independently. Multiple validated tools are being used to assess risk of bias, and the tool applied matches the document or study design (eg, Downs and Black Scale for healthcare interventions). Many concussion experts in various clinical disciplines from across North America have volunteered to examine the evidence in order to make recommendations for the living guidelines.

ETHICS AND DISSEMINATION

No ethical approval is necessary because primary data are not collected. The results will be disseminated through peer-reviewed publications and on the living guidelines website once built.

PROSPERO REGISTRATION NUMBER

CRD42022301786.