Sarcopenia and adipose tissue evaluation by artificial
intelligence predicts the overall survival after TAVI

J 2024

Sarcopenia and adipose tissue evaluation by artificial intelligence predicts the overall survival after TAVI

PEKAŘ, Matej, Otakar JIRAVSKÝ, Jan NOVÁK, Piotr BRANNY, Jakub BALUŠÍK et. al.

Basic information

Original name

Sarcopenia and adipose tissue evaluation by artificial intelligence predicts the overall survival after TAVI

Authors

PEKAŘ, Matej (703 Slovakia, guarantor, belonging to the institution), Otakar JIRAVSKÝ (203 Czech Republic), Jan NOVÁK (203 Czech Republic, belonging to the institution), Piotr BRANNY (203 Czech Republic), Jakub BALUŠÍK (203 Czech Republic), Daniel DANIŠ (203 Czech Republic), Jan HEČKO (203 Czech Republic), Marek KANTOR (203 Czech Republic), Robert PROSECKÝ (203 Czech Republic, belonging to the institution), Lubomír BLAHA (203 Czech Republic) and Radek NEUWIRTH (203 Czech Republic)

Edition

SCIENTIFIC REPORTS, BERLIN, NATURE PORTFOLIO, 2024, 2045-2322

Other information

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

30201 Cardiac and Cardiovascular systems

Country of publisher

Germany

Confidentiality degree

není předmětem státního či obchodního tajemství

References:

URL

Impact factor

Impact factor: 4.600 in 2022

Organization unit

Faculty of Medicine

DOI

http://dx.doi.org/10.1038/s41598-024-59134-z

UT WoS

001205348700026

Keywords in English

Sarcopenia; Artifcial intelligence; Visceral adipose tissue; Subcutaneous adipose tissue; Survival; TAVI

Abstract

V originále

Sarcopenia is a serious systemic disease that reduces overall survival. TAVI is selectively performed in patients with severe aortic stenosis who are not indicated for open cardiac surgery due to severe polymorbidity. Artificial intelligence-assisted body composition assessment from available CT scans appears to be a simple tool to stratify these patients into low and high risk based on future estimates of all-cause mortality. Within our study, the segmentation of preprocedural CT scans at the level of the lumbar third vertebra in patients undergoing TAVI was performed using a neural network (AutoMATiCA). The obtained parameters (area and density of skeletal muscles and intramuscular, visceral, and subcutaneous adipose tissue) were analyzed using Cox univariate and multivariable models for continuous and categorical variables to assess the relation of selected variables with all-cause mortality. 866 patients were included (median(interquartile range)): age 79.7 (74.9–83.3) years; BMI 28.9 (25.9–32.6) kg/m2. Survival analysis was performed on all automatically obtained parameters of muscle and fat density and area. Skeletal muscle index (SMI in cm2/m2), visceral (VAT in HU) and subcutaneous adipose tissue (SAT in HU) density predicted the all-cause mortality in patients after TAVI expressed as hazard ratio (HR) with 95% confidence interval (CI): SMI HR 0.986, 95% CI (0.975–0.996); VAT 1.015 (1.002–1.028) and SAT 1.014 (1.004–1.023), all p < 0.05. Automatic body composition assessment can estimate higher all-cause mortality risk in patients after TAVI, which may be useful in preoperative clinical reasoning and stratification of patients.

Links

MUNI/A/1547/2023, interní kód MU

Name: Analýza (dys)funkce: od molekul k živému organismu

Investor: Masaryk University, Analysis of (dys)function: from molecules to the living organism

MUNI/A/1555/2023, interní kód MU

Name: Patofyziologie, epidemiologie, diferenciální diagnostika a odhad prognózy vybraných vnitřních nemocí

Investor: Masaryk University, Pathophysiology, epidemiology, differential diagnostics and prognostic stratification in selected internal diseases

Citovat

PEKAŘ, Matej, Otakar JIRAVSKÝ, Jan NOVÁK, Piotr BRANNY, Jakub BALUŠÍK, Daniel DANIŠ, Jan HEČKO, Marek KANTOR, Robert PROSECKÝ, Lubomír BLAHA and Radek NEUWIRTH. Sarcopenia and adipose tissue evaluation by artificial intelligence predicts the overall survival after TAVI. SCIENTIFIC REPORTS. BERLIN: NATURE PORTFOLIO, 2024, vol. 14, No 1, p. 1-9. ISSN 2045-2322. Available from: https://dx.doi.org/10.1038/s41598-024-59134-z.

@article{2394829,
   author = {Pekař, Matej and Jiravský, Otakar and Novák, Jan and Branny, Piotr and Balušík, Jakub and Daniš, Daniel and Hečko, Jan and Kantor, Marek and Prosecký, Robert and Blaha, Lubomír and Neuwirth, Radek},
   article_location = {BERLIN},
   article_number = {1},
   doi = {http://dx.doi.org/10.1038/s41598-024-59134-z},
   keywords = {Sarcopenia; Artifcial intelligence; Visceral adipose tissue; Subcutaneous adipose tissue; Survival; TAVI},
   language = {eng},
   issn = {2045-2322},
   journal = {SCIENTIFIC REPORTS},
   title = {Sarcopenia and adipose tissue evaluation by artificial intelligence predicts the overall survival after TAVI},
   url = {https://link.springer.com/article/10.1038/s41598-024-59134-z?utm_source=rct_congratemailt&utm_medium=email&utm_campaign=oa_20240417&utm_content=10.1038/s41598-024-59134-z},
   volume = {14},
   year = {2024}
}

TY  - JOUR
ID  - 2394829
AU  - Pekař, Matej - Jiravský, Otakar - Novák, Jan - Branny, Piotr - Balušík, Jakub - Daniš, Daniel - Hečko, Jan - Kantor, Marek - Prosecký, Robert - Blaha, Lubomír - Neuwirth, Radek
PY  - 2024
TI  - Sarcopenia and adipose tissue evaluation by artificial intelligence predicts the overall survival after TAVI
JF  - SCIENTIFIC REPORTS
VL  - 14
IS  - 1
SP  - 1-9
EP  - 1-9
PB  - NATURE PORTFOLIO
SN  - 20452322
KW  - Sarcopenia
KW  - Artifcial intelligence
KW  - Visceral adipose tissue
KW  - Subcutaneous adipose tissue
KW  - Survival
KW  - TAVI
UR  - https://link.springer.com/article/10.1038/s41598-024-59134-z?utm_source=rct_congratemailt&utm_medium=email&utm_campaign=oa_20240417&utm_content=10.1038/s41598-024-59134-z
N2  - Sarcopenia is a serious systemic disease that reduces overall survival. TAVI is selectively performed in patients with severe aortic stenosis who are not indicated for open cardiac surgery due to severe polymorbidity. Artificial intelligence-assisted body composition assessment from available CT scans appears to be a simple tool to stratify these patients into low and high risk based on future estimates of all-cause mortality. Within our study, the segmentation of preprocedural CT scans at the level of the lumbar third vertebra in patients undergoing TAVI was performed using a neural network (AutoMATiCA). The obtained parameters (area and density of skeletal muscles and intramuscular, visceral, and subcutaneous adipose tissue) were analyzed using Cox univariate and multivariable models for continuous and categorical variables to assess the relation of selected variables with all-cause mortality. 866 patients were included (median(interquartile range)): age 79.7 (74.9–83.3) years; BMI 28.9 (25.9–32.6) kg/m2. Survival analysis was performed on all automatically obtained parameters of muscle and fat density and area. Skeletal muscle index (SMI in cm2/m2), visceral (VAT in HU) and subcutaneous adipose tissue (SAT in HU) density predicted the all-cause mortality in patients after TAVI expressed as hazard ratio (HR) with 95% confidence interval (CI): SMI HR 0.986, 95% CI (0.975–0.996); VAT 1.015 (1.002–1.028) and SAT 1.014 (1.004–1.023), all p < 0.05. Automatic body composition assessment can estimate higher all-cause mortality risk in patients after TAVI, which may be useful in preoperative clinical reasoning and stratification of patients.
ER  -

PEKAŘ, Matej, Otakar JIRAVSKÝ, Jan NOVÁK, Piotr BRANNY, Jakub BALUŠÍK, Daniel DANIŠ, Jan HEČKO, Marek KANTOR, Robert PROSECKÝ, Lubomír BLAHA and Radek NEUWIRTH. Sarcopenia and adipose tissue evaluation by artificial intelligence predicts the overall survival after TAVI. \textit{SCIENTIFIC REPORTS}. BERLIN: NATURE PORTFOLIO, 2024, vol.~14, No~1, p.~1-9. ISSN~2045-2322. Available from: https://dx.doi.org/10.1038/s41598-024-59134-z.

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