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Assessing accuracy and consistency in intracranial aneurysm sizing : human expertise vs. artifcial intelligence
ID
Planinc, Andrej
(
Author
),
ID
Špegel, Nina
(
Author
),
ID
Podobnik, Zala
(
Author
),
ID
Šinigoj, Uroš
(
Author
),
ID
Skubic, Petra
(
Author
),
ID
Choi, June Ho
(
Author
),
ID
Park, Wonhyoung
(
Author
),
ID
Robič, Tina
(
Author
),
ID
Tabor, Nika
(
Author
),
ID
Jarabek, Leon
(
Author
),
ID
Špiclin, Žiga
(
Author
),
ID
Bizjak, Žiga
(
Author
)
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MD5: 86071F2CA6E8A6E718825F34521BD901
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https://www.nature.com/articles/s41598-024-65825-4
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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.
Language:
English
Keywords:
intrarater variability
,
interrater variability
,
deep learning
,
intracranial aneurysms
Work type:
Article
Typology:
1.01 - Original Scientific Article
Organization:
FE - Faculty of Electrical Engineering
MF - Faculty of Medicine
Publication status:
Published
Publication version:
Version of Record
Publisher:
Springer Nature
Year:
2024
Number of pages:
11 str.
Numbering:
14, art. 16080
PID:
20.500.12556/RUL-160094
UDC:
004.8:616-007.64
ISSN on article:
2045-2322
DOI:
10.1038/s41598-024-65825-4
COBISS.SI-ID:
204579587
Publication date in RUL:
20.08.2024
Views:
22
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0
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Record is a part of a journal
Title:
Scientific reports
Shortened title:
Sci. rep.
Publisher:
Nature Publishing Group
ISSN:
2045-2322
COBISS.SI-ID:
18727432
Licences
License:
CC BY 4.0, Creative Commons Attribution 4.0 International
Link:
http://creativecommons.org/licenses/by/4.0/
Description:
This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Secondary language
Language:
Slovenian
Keywords:
variabilnost ocenjevalcev
,
globoko učenje
,
intrakranialne anevrizme
Projects
Funder:
ARIS - Slovenian Research and Innovation Agency
Project number:
J2-3059
Name:
Sprotno prilagajanje načrta protonske in radioterapije
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