2023
Simple method for quantification of metal-based particles in biopsy samples of patients with long bone implants - Pilot study
OLSOVSKA, Eva; Kristina CABANOVA; Oldrich MOTYKA; Hana BIELNIKOVA KRYSTOFOVA; Petra MATEJKOVA et. al.Základní údaje
Originální název
Simple method for quantification of metal-based particles in biopsy samples of patients with long bone implants - Pilot study
Autoři
OLSOVSKA, Eva; Kristina CABANOVA; Oldrich MOTYKA; Hana BIELNIKOVA KRYSTOFOVA; Petra MATEJKOVA; Jirf VOVES; Vladimfr ZIDLIK; Roman MADEJA; Jiří DEMEL; Jan HALFAR a Jana KUKUTSCHOVA
Vydání
Environmental Toxicology and Pharmacology, Amsterdam, Elsevier Science B.V. 2023, 1382-6689
Další údaje
Jazyk
angličtina
Typ výsledku
Článek v odborném periodiku
Obor
30212 Surgery
Stát vydavatele
Nizozemské království
Utajení
není předmětem státního či obchodního tajemství
Odkazy
Impakt faktor
Impact factor: 4.200
Kód RIV
RIV/00216224:14110/23:00133659
Organizační jednotka
Lékařská fakulta
UT WoS
001097249400001
EID Scopus
2-s2.0-85172249185
Klíčová slova anglicky
Traumatology; Biopsy samples; Metal-based particles; Automated analysis in the area; Scanning electron microscopy
Příznaky
Mezinárodní význam, Recenzováno
Změněno: 27. 2. 2024 14:06, Mgr. Tereza Miškechová
Anotace
V originále
The presence of particles fixed in tissue samples due to implant degradation or disintegration plays an important role in post-operative complications. The ability to determine the size, shape, chemical composition and, above all, the number of these particles can be used in many areas of medicine. This study presents a novel, simple metal-based particle detection method using scanning electron microscopy with energy dispersive spectrometer (SEM-EDS). The presence of metal particles in biopsy specimens from long bone nail-fixated implants (10 patients with titanium steel nails and 10 patients with stainless steel nails) was studied. The samples were analysed using automated area analysis based on image binarization and brightness to 255 grayscale. The results were supplemented with histological data and statistically analysed. The method based on the software used was found to be accurate and easy to use and, thus, appears to be very suitable for particle detection in similar samples.