TY  - JOUR
T1  - Fourier Dönüşümlü Kızılötesi Spektroskopisinin Prostat Kanseri Teşhisinde Kullanılabilirliğinin Araştırılması
TT  - Investigation of the Usability of Fourier Transform Infrared Spectroscopy in Diagnosis of Prostate Cancer
AU  - Albayrak, Mevlut
PY  - 2018
DA  - December
Y2  - 2018
DO  - 10.21597/jist.430052
JF  - Journal of the Institute of Science and Technology
JO  - J. Inst. Sci. and Tech.
PB  - Iğdır Üniversitesi
WT  - DergiPark
SN  - 2536-4618
SP  - 223
EP  - 227
VL  - 8
IS  - 4
LA  - tr
AB  - Fourier Dönüşümlü Kızılötesi Spektroskopisi (FT-IR) yöntemi, organik ve bazı durumlarda inorganikmateryalleri tanımlamak için kullanılan analitik bir tekniktir. Bu teknik, dalga boyuna karşı numune tarafındanabsorblanan kızılötesi radyasyonu ölçemeye yarar. Kızılötesi absorpsiyon bantları ise molekülün bileşenleri veyapıları hakkında bilgi verir. Prostat kanseri, erkeklerde spermi besleyen ve taşıyan seminal sıvıyı üreten, cevizşekilli küçük bir bez olan prostatta meydana gelen bir kanserdir. Prostat kanseri, erkeklerde en sık görülen kansertiplerinden biridir. Erken teşhis edilen prostat kanseri, prostat bezi ile sınırlı olduğu zaman tedavi şansı dahabaşarılı olur. Prostat kanseri tümörlerini sağlıklı hücrelerden ayırmak ve karakterize etmek için kemometrik yöntemdestekli, iyi bir doğruluk ve hassasiyete sahip basit, ucuz ve hızlı yeni bir alternatif FT-IR yönteminin geliştirilmesiamaçlanmıştır. Çalışmanın gerçekleştirilebilmesi için, histopatolojik ölçümlerle belirlenen hem kanser hem desağlıklı hücreleri içeren parafin bloklardan 20 mikron kalınlığında kesildi, lam üzerine yerleştirildi ve deparafinizeedildi. Hem sağlıklı (n = 10) hem de kanserli dokular (n = 10) 50-4000 cm-1 dalga boyu arasındaki kızılötesiışığa maruz bırakıldı. 20 örneğe 50-4000 cm-1 arasındaki kızılötesi ışığa karşı davranışlarını saptamak için temelbileşenler analizi (Principle Component Analysis, PCA) ileri bir formu olan ortogonal kısmi en küçük kareleranaliz (Ortogonal Partial Least Square, O-PLS) algoritması uygulandı. Elde edilen spektrumlar MATLAB softwarePLS Toolbox paket programında değerlendirildi. Kanserli ve sağlıklı hücreleri ayırmak için O-PLS analizi yapıldı.Önerilen yöntemin hassaslığı ve özgüllüğü, Ortogonal Sinyal Düzeltme (Orthogonal Signal Correction, OSC) önişlem yöntemi yardımıyla çok yüksek olduğu görüldü. Sonuç olarak, parafin bloklardan prostat kanser teşhisi içinalternatif bir FT-IR yöntemi geliştirildi ve başarıyla uygulandı.
KW  - FT-IR Spektroskopisi
KW  - kanser teşhisi
KW  - kalitatif analiz
KW  - prostat kanseri
KW  - kanser teşhisi
N2  - Fourier Transform-Infrared Spectroscopy (FT-IR) is an analytical technique used to identify inorganic and some cases inorganic materials. This technique measures the absorption of infrared radiation by thesample material versus wavelength. The infrared absorption bands identify molecular components and structures.Prostate cancer is cancer that occurs in the prostate a small walnut shaped gland in men that produces the seminalfluid that nourishes and transports sperm. Prostate cancer is one of the most common types of cancer in men.Prostate cancer that is detected early when it’s still confined to the prostate gland has a better chance of successfultreatment. It is aimed to develop a new alternative chemometrics assisted method to separate and characterizeprostat cancer tumors from healthy cells by simple, cheap and rapid FT-IR method with good accuracy andsensitivity. In order to perform such a study paraffin embedded blocks including both cancer and healthy cellswhich are labelled by the histopathologic measurements were cut to 20 microns thick were located on a microscopeslide and deparafinized. Both healthy (n=10) and cancerous tissues (n=10) were exposured to infrared light betweenwavenumber of 50-4000 cm-1. Orthogonal partial least square analysis (O-PLS) algorithm which is an advancedform of Principle Component Analysis (PCA) was applied to 20 samples to detect their behaviour against infraredlight in between 50-4000 cm-1. Obtained spectrums were evaluated on MATLAB software PLS Toolbox packageprogram. O-PLS analysis were carried out in order to separate cancer and healthy tissues. Sensitivity and specificityof the proposed method is so high with the aid of Orthogonal Signal Correction (OSC) preprocessing method. Asa result, an alternative FT-IR method for the diagnosis of prostate cancer from paraffin blocks has been developedand successfully applied.
CR  - Anonim, 2015. Fourier Transform-Infrared Spectroscopy, https://chem.libretexts.org/Core/Physical_and_Theoretical_Chemistry/Spectroscopy/Vibrational_Spectroscopy/Infrared_Spectroscopy/How_an_FTIR_Spectrometer_Operates (Erişim Tarihi: 12.05.2018).
CR  - Anonim, 2018. American Cancer Society, Prostate cancer, https://www.cancer.org/cancer/prostate-cancer.html (Erişim Tarihi: 11.05.2018).
CR  - Baker MJ, Gazi E, Brown MD, Shanks JH, Gardner P, Clarke NW, 2008. FTIR-based spectroscopic analysis in the identification of clinically aggressive prostate cancer. British journal of cancer, 99(11): 1859-1866.
CR  - Catalona WJ, Richie JP, Ahmann FR, M’Liss AH, Scardino PT, Flanigan RC, DeKernion JB, Ratliff TL, Kavoussi LR, Dalkin BL, Waters WB, MacFarlane MT, Southwick PC, 1994. Comparison of digital rectal examination and serum prostate specific antigen in the early detection of prostate cancer: results of a multicenter clinical trial of 6,630 men. The Journal of Urology, 151(5): 1283-1290.
CR  - Catalona WJ, Smith DS, Ornstein DK, 1997. Prostate cancer detection in men with serum PSA concentrations of 2.6 to 4.0 ng/mL and benign prostate examination: enhancement of specificity with free PSA measurements. Jama, 277(18): 1452-1455.
CR  - Khanmohammadi M, Garmarudi AB, 2011. Infrared spectroscopy provides a green analytical chemistry tool for direct diagnosis of cancer. TrAC Trends in Analytical Chemistry, 30(6): 864-874.
CR  - Ly E, Piot O, Wolthuis R, Durlach A, Bernard P, Manfait M, 2008. Combination of FTIR spectral imaging and chemometrics for tumour detection from paraffin-embedded biopsies. Analyst, 133(2): 197-205.
CR  - Mackanos MA, Contag C H, 2010. Fiber-optic probes enable cancer detection with FTIR spectroscopy. Trends in biotechnology, 28(6): 317-323.
CR  - Mantsch HH, Chapman D, 1996. Infrared spectroscopy of biomolecules. Wiley Publications, New York, USA.
CR  - Otto M, 2016. Chemometrics: statistics and computer application in analytical chemistry. Third edition, John Wiley-VCH, pp. 2, 28-44, 231, Weinheim-Germany.
CR  - Paraskevaidi M, Martin-Hirsch PL, Martin FL, 2018. ATR-FTIR Spectroscopy Tools for Medical Diagnosis and Disease Investigation. In Nanotechnology Characterization Tools for Biosensing and Medical Diagnosis (pp. 163-211). Springer, Berlin, Heidelberg.
CR  - Partin AW, Kattan MW, Subong EN, Walsh PC, Wojno KJ, Oesterling JE, Scardino PT, Pearson JD, 1997. Combination of prostate-specific antigen, clinical stage, and Gleason score to predict pathological stage of localized prostate cancer: a multi-institutional update. Jama, 277(18): 1445-1451.
CR  - Petibois C, Deleris G, 2006. Chemical mapping of tumor progression by FT-IR imaging: towards molecular histopathology. Trends in Biotechnology, 24(10): 455-462.
CR  - Pinthus JH, Pacik D, Ramon J, 2007. Diagnosis of prostate cancer. In Prostate Cancer (pp. 83-99). Springer, Berlin, Heidelberg.
CR  - Siqueira LFS, 2017. Multivariate classification and Fourier-Transform Mid-Infrared Spectroscopy (FT-MIR) in cancer prostate tissue. Chemistry Postgraduate Program of Fedaral University of Rio Grande Do Norte, Doctora Thesis, (Printed).
CR  - Siqueira LFS, Júnior RFA, de Araújo AA, Morais CL, Lima KM, 2017. LDA vs. QDA for FT-MIR prostate cancer tissue classification. Chemometrics and Intelligent Laboratory Systems, 162: 123-129.
CR  - Talari ACS, Martinez MAG, Movasaghi Z, Rehman S, Rehman IU, 2017. Advances in Fourier transform infrared (FTIR) spectroscopy of biological tissues. Applied Spectroscopy Reviews, 52(5): 456-506.
CR  - Taylor BS, Schultz N, Hieronymus H, Gopalan A, Xiao Y, Carver BS, Arora VK, Kaushik P, Cerami E, Reva B, Antipin, Y, Mitsiades N, Landers T, Dolgalev I, Major JE, Wilson M, Socci ND, Lash AE, Heguy A, Eastham JA, Scher HI, Reuter VE, Scardino PT, Sander C, Sawyers CL, Gerald WL,  2010. Integrative genomic profiling of human prostate cancer. Cancer cell, 18(1): 11-22.
CR  - Worley B, Powers R, 2013. Multivariate analysis in metabolomics. Current Metabolomics, 1 (1): 92–107.
UR  - https://doi.org/10.21597/jist.430052
L1  - https://dergipark.org.tr/tr/download/article-file/594252
ER  -