Evidence map›Paper›PMID 38992041›Full record

ArticleScientific reports2024

Assessing accuracy and consistency in intracranial aneurysm sizing: human expertise vs. artificial intelligence.

Andrej Planinc, Nina Špegel, Zala Podobnik, Uroš Šinigoj, Petra Skubic, June Ho Choi, Wonhyoung Park, Tina Robič, Nika Tabor, Leon Jarabek and 2 more

Erratum issuedAbstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors.

Andrej PlanincMedilab Diagnostic Imaging, Vodovodna 100, 1000, Ljubljana, Slovenia. andrej.planinc@gmail.com.
Nina ŠpegelFaculty of Medicine, University of Ljubljana, Ljubljana, Slovenia.
Zala PodobnikFaculty of Medicine, University of Ljubljana, Ljubljana, Slovenia.
Uroš ŠinigojFaculty of Medicine, University of Ljubljana, Ljubljana, Slovenia.
Petra SkubicFaculty of Medicine, University of Ljubljana, Ljubljana, Slovenia.
June Ho ChoiDepartment of Neurological Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
Wonhyoung ParkDepartment of Neurological Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
Tina RobičFaculty of Medicine, University of Ljubljana, Ljubljana, Slovenia.
Nika TaborFaculty of Medicine, University of Ljubljana, Ljubljana, Slovenia.
Leon JarabekLaboratory of Imaging Technologies, Faculty of Electrical Engineering, University of Ljubljana, Ljubljana, Slovenia.
Žiga ŠpiclinLaboratory of Imaging Technologies, Faculty of Electrical Engineering, University of Ljubljana, Ljubljana, Slovenia.
Žiga BizjakLaboratory of Imaging Technologies, Faculty of Electrical Engineering, University of Ljubljana, Ljubljana, Slovenia.

Funding

Javna Agencija za Raziskovalno Dejavnost RS (Slovenian Research Agency) J2-2500Javna Agencija za Raziskovalno Dejavnost RS (Slovenian Research Agency) J2-3059
6 · The paper itself

Abstract

Intracranial aneurysms (IAs) are a common vascular pathology and are associated with a risk of rupture, which is often fatal. Aneurysm growth of more than 1 mm is considered a surrogate of rupture risk, therefore, this study presents a comprehensive analysis of intracranial aneurysm measurements utilizing a dataset comprising 358 IA from 248 computed tomography angiography (CTA) scans measured by four junior raters and one senior rater. The study explores the variability in sizing assessments by employing both human raters and an Artificial Intelligence (AI) system. Our findings reveal substantial inter- and intra-rater variability among junior raters, contrasting with the lower intra-rater variability observed in the senior rater. Standard deviations of all raters were above the threshold for IA growth (1 mm). Additionally, the study identifies a systemic bias, indicating a tendency for human experts to measure aneurysms smaller than the AI system. Our findings emphasize the challenges in human assessment while also showcasing the capacity of AI technology to improve the precision and reliability of intracranial aneurysm assessments, especially beneficial for junior raters. The potential of AI was particularly evident in the task of monitoring IA at various intervals, where the AI-based approach surpassed junior raters and achieved performance comparable to senior raters.

Indexed as

Artificial IntelligenceComputed Tomography AngiographyIntracranial AneurysmAgedFemaleHumansMaleMiddle AgedObserver VariationReproducibility of Results

Identifiers

PMID38992041
PMCPMC11239926

What OpenQuestion holds

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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.