Evidence map›Paper›PMID 34021845›Full record

ArticleEmergency radiology2021

Pseudo-pneumatosis of the gastrointestinal tract: its incidence and the accuracy of a checklist supported by artificial intelligence (AI) techniques to reduce the misinterpretation of pneumatosis.

Andrea Alessandro Esposito, Stefania Zannoni, Laura Castoldi, Caterina Giannitto, Emanuele Avola, Elena Casiraghi, Onofrio Catalano, Gianpaolo Carrafiello

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Article in Emergency radiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.4field-weighted citation impact, top 38% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 4 institutions in 2 countries.

Andrea Alessandro EspositoDepartment of Radiology, Foundation IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via Sforza 35, 20122, Milan, Italy. andrea.esposito@policlinico.mi.it.ORCID http://orcid.org/0000-0001-5534-2620
Stefania ZannoniPost-Graduate School in Radiodiagnostics, Università Degli Studi Di Milano, Via Festa del Perdono 7, 20122, Milan, Italy.
Laura CastoldiDepartment of Surgical Emergency, Foundation IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via Sforza 35, 20122, Milan, Italy.
Caterina GiannittoDepartment of Radiology, Istituto Clinico Humanitas, Via Manzoni 56, 20089, Rozzano, MI, Italy.
Emanuele AvolaPost-Graduate School in Radiodiagnostics, Università Degli Studi Di Milano, Via Festa del Perdono 7, 20122, Milan, Italy.
Elena CasiraghiDepartment of Computer Science, University of Milan, Via Celoria 18, 20133, Milan, Italy.
Onofrio CatalanoDepartment of Radiology, Massachusetts General Hospital, 55 Fruit St, Boston, MA, 02114, USA.
Gianpaolo CarrafielloDepartment of Radiology, Foundation IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via Sforza 35, 20122, Milan, Italy.
Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico · ITUniversity of Milan · ITFondazione Humanitas per la Ricerca · ITMassachusetts General Hospital · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo assess the incidence of erroneous diagnosis of pneumatosis (pseudo-pneumatosis) in patients who underwent an emergency abdominal CT and to verify the performance of imaging features, supported by artificial intelligence (AI) techniques, to reduce this misinterpretation.

methodsWe selected 71 radiological reports where the presence of pneumatosis was considered definitive or suspected. Surgical findings, clinical outcomes, and reevaluation of the CT scans were used to assess the correct diagnosis of pneumatosis. We identified four imaging signs from literature, to differentiate pneumatosis from pseudo-pneumatosis: gas location, dissecting gas in the bowel wall, a circumferential gas pattern, and intramural gas beyond a gas-fluid/faecal level. Two radiologists reevaluated in consensus all the CT scans, assessing the four above-mentioned variables. Variable discriminative importance was assessed using the Fisher exact test. Accurate and statistically significant variables (p-value < 0.05, accuracy > 75%) were pooled using boosted Random Forests (RFs) executed using a Leave-One-Out cross-validation (LOO cv) strategy to obtain unbiased estimates of individual variable importance by permutation analysis. After the LOO cv, the comparison of the variable importance distribution was validated by one-sided Wilcoxon test.

resultsTwenty-seven patients proved to have pseudo-pneumatosis (error: 38%). The most significant features to diagnose pneumatosis were presence of dissecting gas in the bowel wall (accuracy: 94%), presence of intramural gas beyond a gas-fluid/faecal level (accuracy: 86%), and a circumferential gas pattern (accuracy: 78%).

conclusionThe incidence of pseudo-pneumatosis can be high. The use of a checklist which includes three imaging signs can be useful to reduce this overestimation.

Indexed as

Artificial IntelligencePneumatosis Cystoides IntestinalisChecklistHumansIncidenceIntestinesAbdomen, acuteEmergencyMultidetector computed tomographyPneumatosis intestinalisPseudo-pneumatosis intestinalis

Identifiers

PMID34021845
OpenAlexW3163759224

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.