Določitev biomarkerjev vnetja trebušne stene s hiperspektralnim slikanjem

Marinović, Ivana (avtor), Milanič, Matija (mentor), Stergar, Jošt (komentor)

Pri peritonealni dializi so pogosti pojavi peritonitisa in zadebelitve peritonealne membrane, kar otežuje nadaljnjo dializo in lahko vodi celo v smrt. Za oceno stanja se sedaj uporabljata histološka analiza odvzetih vzorcev peritonealne membrane in analiza izraženosti genov povezanih z vnetjem. Histologija je zelo natančna, a točkovna metoda, PCR analiza pa zaznava spremembe na večjem področju brez prostorske ločljivosti, zato se lahko dejansko stanje po celotnem tkivu spregleda. Razvoj nove tehnike, ki lahko poda več podatkov iz celotnega analiziranega področja, je zato nujno potreben. Za ocenjevanje sprememb na trebušni steni in učinkovitosti zdravil resolvin in epiresolvin na potek vnetja je bilo uporabljeno mezoskopsko hiperspektralno slikanje z valovnimi dolžinami med 400 in 1000 nm z merjenjem spektra prepuščene svetlobe. Vključenih je bilo 17 miši v skupinah z induciranim vnetjem s klorheksidinom, zdravljenih z resolvinom in zdrave kontrole. Sipalne in absorpcijske lastnosti tkiva so bile pridobljene tako, da je bil model interakcije svetlobe s tkivom prilagojen na hiperspektralne podatke. Tako smo pridobili prostorske porazdelitve volumskih deležev kromoforov, sipalnih koeficientov ter sipalnih potenc po celotnih vzorcih. Iz dobljenih podatkov so bile s statističnimi orodji določene signifikantne metrike, s katerimi bi lahko zaznavali spremenjene vzorce in bi lahko predstavljale biomarkerje vnetja trebušne stene in peritonitisa. Rezultati so bili primerjani z rezultati genske analize in histologije. Ugotovljeno je bilo dobro ujemanje predvsem s histološkimi ugotovitvami.

• Jezik: Slovenski jezik
• Ključne besede: hiperspektralno slikanje, model interakcij svetlobe s tkivom, vnetje trebušne stene, peritonitis
• Vrsta gradiva: Magistrsko delo/naloga
• Tipologija: 2.09 - Magistrsko delo
• Organizacija: FMF - Fakulteta za matematiko in fiziko
• Leto izida: 2021
• PID: 20.500.12556/RUL-128278
• COBISS.SI-ID: 69583619
• Datum objave v RUL: 08.07.2021

MARINOVIĆ, Ivana, 2021, Določitev biomarkerjev vnetja trebušne stene s hiperspektralnim slikanjem [na spletu]. Magistrsko delo. [Dostopano 16 april 2025]. Pridobljeno s: https://repozitorij.uni-lj.si/IzpisGradiva.php?lang=slv&id=128278

Sekundarni jezik

• Jezik: Angleški jezik
• Naslov: Determination of Abdominal Wall Inflammation Biomarkers with Hiperspectral Imaging

Izvleček

Peritonitis and peritoneal wall thickening are common complications of peritoneal dialysis, which affect further dialysis and can even end with death. Histology of peritoneal membrane and PCR analysis are currently used for condition assessment. Histology is very accurate, but can only process small number of samples with limited size. PCR analysis can only detect changes on bigger areas without spatial resolution. Because these methods have their limitations, true condition can be easily undetected so development of new technique, which can give us more data and can examine bigger area, is urgently needed. Mesoscopic hyperspectral imaging with wavelengths between 400 and 1000 nm was used to assess changes on abdominal wall and effects of medications Resolvin and Epiresolvin on inflammation process by measuring spectrum of transmitted light. Study involved 17 murine males divided in several groups with induced inflammation with Chlorhexidine, treated with Resolvin and Epiresolvin and healthy controls. Scattering and absorption characteristics were determined by fitting model of light - tissue interactions onto hyperspectral data. Spatial distributions of chromophores, scattering coefficients and scattering power were obtained. Statistical metrics were determined with statistical tools, which could represent abdominal wall inflammation biomarkers. Results of hyperspectral imaging were compared to those of PCR and histology analysis. All of the methods had similar findings and good agreement.

• Ključne besede: hyperspectral imaging, light interactions with tissue model, abdominal wall inflammation, peritonitis