Citations

Abstract Background and study aims Use of fluoroscopy in gastrointestinal endoscopy is an essential aid in advanced endoscopic interventions. However, it also raises concerns about radiation exposure. This study aimed to develop consensus-based statements for safe and effective use of fluoroscopy in gastrointestinal endoscopy, prioritizing the safety and well-being of healthcare workers and patients. Methods A modified Delphi approach was employed to achieve consensus over three rounds of surveys. Proposed statements were generated in Round 1. In the second round, panelists rated potential statements on a 5-point scale, with consensus defined as ≥80% agreement. Statements were subsequently prioritized in Round 3, using a 1 (lowest priority) to 10 (highest priority) scale. Results Forty-six experts participated, consisting of 34 therapeutic endoscopists and 12 endoscopy nurses from six continents, with an overall 45.6% female representation (n = 21). Forty-three item statements were generated in the first round. Of these, 31 statements achieved consensus after the second round. These statements were categorized into General Considerations (n = 6), Education (n = 10), Pregnancy (n = 4), Family Planning (n = 2), Patient Safety (n = 4), and Staff Safety (n = 5). In the third round, accepted statements received mean priority scores ranging from 7.28 to 9.36, with 87.2% of statements rated as very high priority (mean score ≥ 9). Conclusions This study presents consensus-based statements for safe and effective use of fluoroscopy in gastrointestinal endoscopy, addressing the well-being of healthcare workers and patients. These consensus-based statements aim to mitigate risks associated with radiation exposure while maintaining benefits of fluoroscopy, ultimately promoting a culture of safety in healthcare settings.

Background Piecemeal endoscopic mucosal resection (EMR) is an acceptable technique for T1a esophageal adenocarcinoma, but en bloc R0 excision is advocated for T1b disease as it may offer a potential cure and mitigate recurrence. Thus, distinguishing between T1a and T1b disease is imperative under current treatment paradigms. We investigated whether expert Barrett’s endoscopists could make this distinction based on optical evaluation. Methods Endoscopic images of histologically confirmed high grade dysplasia (HGD), T1a, and T1b disease (20 sets for each) were compiled from consecutive patients at a single institution. Each set contained four images including an overview, a close-up in high definition white light, a near-focus magnification image, and a narrow-band image. Experts predicted the histology for each set. Results 19 experts from 8 countries (Australia, USA, Italy, Netherlands, Germany, Canada, Belgium, and Portugal) participated. The majority had been practicing for > 20 years, with a median (interquartile range) annual case volume of 50 (18–75) for Barrett’s EMR and 25 (10–45) for Barrett’s endoscopic submucosal dissection. Esophageal adenocarcinoma (T1a/b) could be distinguished from HGD with a pooled sensitivity of 89.1 % (95 %CI 84.7–93.4). T1b adenocarcinoma could be predicted with a pooled sensitivity of 43.8 % (95 %CI 29.9–57.7). Fleiss’ kappa was 0.421 (95 %CI 0.399–0.442; P < 0.001), indicating fair-to-moderate agreement. Conclusions Expert Barrett’s endoscopists could reliably differentiate T1a/T1b esophageal adenocarcinoma from HGD. Despite fair-to-moderate agreement for T staging, T1b disease could not be reliably distinguished from T1a disease. This may impact clinical decision making and selection of endoscopic techniques.

AbstractBackgroundAs the only optically accessible part of the central nervous system, the retina represents an intriguing opportunity for the detection of biomarkers for Alzheimer’s disease (AD). This study evaluated the performance of the Retinal Deep PhenotypingTM platform, a digital biomarker platform comprising a hyperspectral retinal camera and image analysis algorithms, for the detection of likely positron‐emission tomography (PET) amyloid status (negative or positive) in older adults. A set of phenotypic features that correlates with the cerebral amyloid status as determined by amyloid PET scan were identified and used to train a classifying algorithm.MethodHyperspectral retinal images acquired with a Mydriatic Hyperspectral Retinal Camera from 194 participants (age ≥ 50 years), including cognitively normal and cognitively impaired (mild cognitive impairment and dementia) across 5 imaging sites were processed in order to train the model. Of these 194 participants, 73 individuals (38%) were amyloid‐positive, as confirmed by unanimous readings of PET scans by a panel of 3 expert reviewers. The pre‐processed hyperspectral images were segmented into various anatomical sites, and a texture‐based approach was used to extract several thousands of spatial‐spectral features. The most relevant features for the classification task were selected using a minimum redundancy maximum relevance (MRMR) algorithm and used to train a linear support vector machine (SVM) classifier. A nested, cross‐validation technique was used to evaluate the performance of the classifier.ResultThe resulting model based on the 17 most significant features showed high performance to discriminate between amyloid positive and negative subjects with an area under the receiver operating curve (AUCROC) of 0.87 (95% CI: 0.83 – 0.92).ConclusionThe Retinal Deep PhenotypingTM platform shows promise for detecting the likely cerebral amyloid PET status in adults 50 years and older from a simple, non‐invasive retinal scan and could provide an accessible means to identify individuals with abnormal cerebral amyloid in a clinical or drug development context. This phenotyping platform provides a flexible approach that could also be used for the detection of multiple biomarkers involved in cognitive decline from the same hyperspectral images of the retina.

The scientific basis of intracranial aneurysm (IA) formation, its rupture and further development of cerebral vasospasm is incompletely understood. Aberrant protein expression may drive structural alterations of vasculature found in IA. Deciphering the molecular mechanisms underlying these events will lead to identification of early detection biomarkers and in turn, improved treatment outcomes. To unravel differential protein expression in three clinical subgroups of IA patients: (1) unruptured aneurysm, (2) ruptured aneurysm without vasospasm, (3) ruptured aneurysm who developed vasospasm, we performed untargeted quantitative proteomic analysis of aneurysm tissue and serum samples from three subgroups of IA patients and control subjects. Candidate molecules were then validated in a larger cohort of patients using enzyme-linked immunosorbent assay. A total of 937 and 294 proteins were identified from aneurysm tissue and serum samples, respectively. Several proteins that are known to maintain structural integrity of vasculature were found to be dysregulated in the context of aneurysm. ORM1 , a glycoprotein, was significantly upregulated in both tissue and serum samples of unruptured aneurysm patients. We employed a larger cohort of subjects ( n = 26) and validated ORM1 as a potential biomarker for screening of unruptured aneurysms. Samples from ruptured aneurysms with vasospasm showed significant upregulation of MMP9 , a protease, compared with ruptured aneurysms without vasospasm. We validated MMP9 as a potential biomarker for vasospasm in a larger cohort ( n = 52). This study reports the first global proteomic analysis of the entire clinical spectrum of IA. Furthermore, this study suggests ORM1 and MMP9 as potential biomarkers for unruptured aneurysm and cerebral vasospasm, respectively.