Changing the paradigm of defining, detecting, and diagnosing NEC: Perspectives on Bell’s stages and biomarkers for NEC

Gephart, Sheila M.; Gordon, Phillip V.; Penn, Alexander H.; Gregory, Katherine E.; Swanson, Jonathan R.; Maheshwari, Akhil; Sylvester, Karl G.

doi:10.1053/j.sempedsurg.2017.11.002

Cited by 89 publications

(88 citation statements)

References 51 publications

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“…Diagnosing NEC can be difficult, especially in the early stages of the disease, because there is no unambiguous case definition . This diagnostic uncertainty is particularly relevant to clinical evaluation and medical management and potentially leads to unnecessary and extended period of cessation of enteral feedings and prolonged courses of parenteral nutrition and antibiotics.…”

Section: Defining Nec and Utility Of Biomarkersmentioning

confidence: 99%

“…15 Much recent work has focused on specific biomarkers for prediction, early diagnosis, and determination of disease severity. 8,16 Various specific proteins, including cytokines, measured in blood, urine, and stool, have been evaluated, but most have poor specificity for making an accurate diagnosis. 17 However, blood inter-alpha inhibitor proteins are able to distinguish NEC from SIP and NEC from matched controls with feeding intolerance.…”

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confidence: 99%

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Necrotizing enterocolitis

Sanchez

Kadrofske

2019

Neurogastroenterology Motil

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Necrotizing enterocolitis (NEC) is an acute inflammatory disease of the intestine which primarily affects preterm infants and is a leading cause of morbidity and mortality in the neonatal intensive care unit. From a clinical standpoint, and during the early course of the disease, NEC can be difficult to distinguish from other diseases and conditions common to the preterm infant, and this warrants the need for specific disease biomarkers. The pathogenesis of NEC is only partly understood but likely involves an altered intestinal barrier immune response to feeding and the developing microbiome. Recent evidence points toward a role of the enteric nervous system in NEC pathogenesis. In this issue, Meister and colleagues use a rodent model of NEC to demonstrate that NEC is associated with diminished vagal tone, as determined by decreased high‐frequency heart rate variability (HF‐HRV), and altered myenteric nitrergic inhibitory neurotransmission. These results augment their previous findings that describe decreased HF‐HRV in human preterm infants with NEC. This mini‐review provides a brief summary of clinical and pathophysiologic aspects of NEC with focus on certain aspects of neurogastroenterology.

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Section: Defining Nec and Utility Of Biomarkersmentioning

confidence: 99%

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confidence: 99%

Necrotizing enterocolitis

Sanchez

Kadrofske

2019

Neurogastroenterology Motil

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“…These include identifying novel biomarkers through comprehensive study of human biologic samples (fluids, tissues), using high content multi-omics technologies (eg, proteomics, metabolomics, genomics), and integrating (clinical and biologic) computational analyses. 10 The BEST Resource defines a biomarker as: "A defined characteristic that is measured as an indicator of normal biological processes, pathogenic processes, or response to an exposure or intervention. Molecular, histologic, radiographic, or physiologic characteristics are types of biomarkers (https://www.ncbi.nlm.nih.gov/books/NBK338448/)."…”

Section: Biomarkersmentioning

confidence: 99%

Necrotizing Enterocolitis: Using Regulatory Science and Drug Development to Improve Outcomes

Caplan

Underwood

Modi

et al. 2019

The Journal of Pediatrics

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“…Despite significant investment in time and resources, our understanding of the causation of NEC has not progressed enough to improve outcomes [4]- [7]. The lack of progress in outcomes for NEC is, to a large extent, related to a lack of consensus for a case definition and data sets could better inform practice but are difficult to aggregate and are contaminated and as such limited, unreliable and inaccurate in the insights they can offer [5], [8]. Much hope still hinges on biomarker research [8], but for now, we are still without reliable biomarkers to predict or detect NEC early or delineate it from various confounders.…”

Section: Introductionmentioning

confidence: 99%

A Deep Learning Based Suggested Model to Detect Necrotising Enterocolitis in Abdominal Radiography Images

Druten

Sharif

Chan

et al. 2019

2019 International Conference on Computing, Electronics &Amp; Communications Engineering (iCCECE)

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Despite decades of exploration into necrotising enterocolitis (NEC), we still lack the capacity to accurately diagnose the disease to improve outcomes in its management. Existing diagnostics struggle to delineate NEC from other neonatal intestinal diseases; it is also unable to highlight those likely to deteriorate to needing emergency life-saving surgery before it is too late. The diagnosis of NEC is heavily dependent on interpretation of radiological findings, especially abdominal radiography (AR) and abdominal ultrasound (AUS). Interexpert variability in interpreting AR imaging, and in the case of AUS, performing and interpreting the test, remains an unresolved challenge. With the compounding impact of the shrinking radiology workforce, a novel approach is imperative. Computer assisted detection (CAD) and classification of abnormal pathology in medical imaging is a rapidly evolving field of clinical and biomedical research. This technology is widely used as a preliminary screening tool. This research paper proposes a deep learning-based model to classify AR images in an automated manner, generating class activation maps (CAM) from various imaging features consistent with NEC pathology, as agreed by expert consensus papers (in neonatology and paediatric radiology). It also compares it with conventional machine learning methods. The suggested model aims to produce heatmaps for various imaging features to highlight NEC pathology in AR (or in future AUS). Once the model is trained, validation is done through quantitative measures and visually by the attending radiologist (clinician) reviewing the validity of the colour maps highlighting the pathology of the AR image (future extension to AUS). As the volume of imaging data is increasing year by year, CAD can be a key strategy to assist radiology departments meet service needs. This technology can greatly assist in screening for NEC, improving the detection of NEC and potentially aid in the earlier identification of disease. Furthermore, it can fast track research cost effectively by creating big data through the automatic labeling of imaging data to create big-data for NEC databases.

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Changing the paradigm of defining, detecting, and diagnosing NEC: Perspectives on Bell’s stages and biomarkers for NEC

Cited by 89 publications

References 51 publications

Necrotizing enterocolitis

Necrotizing enterocolitis

Necrotizing Enterocolitis: Using Regulatory Science and Drug Development to Improve Outcomes

A Deep Learning Based Suggested Model to Detect Necrotising Enterocolitis in Abdominal Radiography Images

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