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.

Základní údaje

Originální název

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

Autoři

PEKAŘ, Matej (703 Slovensko, garant, domácí), Otakar JIRAVSKÝ (203 Česká republika), Jan NOVÁK (203 Česká republika, domácí), Piotr BRANNY (203 Česká republika), Jakub BALUŠÍK (203 Česká republika), Daniel DANIŠ (203 Česká republika), Jan HEČKO (203 Česká republika), Marek KANTOR (203 Česká republika), Robert PROSECKÝ (203 Česká republika, domácí), Lubomír BLAHA (203 Česká republika) a Radek NEUWIRTH (203 Česká republika)

Vydání

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

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

30201 Cardiac and Cardiovascular systems

Stát vydavatele

Německo

Utajení

není předmětem státního či obchodního tajemství

Odkazy

URL

Impakt faktor

Impact factor: 4.600 v roce 2022

Organizační jednotka

Lékařská fakulta

DOI

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

UT WoS

001205348700026

Klíčová slova anglicky

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

Štítky

14110116, 14110515, rivok

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 21. 5. 2024 08:54, Mgr. Tereza Miškechová

Anotace

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.

Návaznosti

MUNI/A/1547/2023, interní kód MU

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

Investor: Masarykova univerzita, Analýza (dys)funkce: od molekul k živému organismu

MUNI/A/1555/2023, interní kód MU

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

Investor: Masarykova univerzita, Patofyziologie, epidemiologie, diferenciální diagnostika a odhad prognózy vybraných vnitřních nemocí

Citovat

PEKAŘ, Matej, Otakar JIRAVSKÝ, Jan NOVÁK, Piotr BRANNY, Jakub BALUŠÍK, Daniel DANIŠ, Jan HEČKO, Marek KANTOR, Robert PROSECKÝ, Lubomír BLAHA a Radek NEUWIRTH. Sarcopenia and adipose tissue evaluation by artificial intelligence predicts the overall survival after TAVI. SCIENTIFIC REPORTS. BERLIN: NATURE PORTFOLIO, 2024, roč. 14, č. 1, s. 1-9. ISSN 2045-2322. Dostupné z: 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 a Radek NEUWIRTH. Sarcopenia and adipose tissue evaluation by artificial intelligence predicts the overall survival after TAVI. \textit{SCIENTIFIC REPORTS}. BERLIN: NATURE PORTFOLIO, 2024, roč.~14, č.~1, s.~1-9. ISSN~2045-2322. Dostupné z: https://dx.doi.org/10.1038/s41598-024-59134-z.

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