Scopus
🔓 Açık Erişim YÖKSİS Eşleşti
Texture analysis of multiparametric magnetic resonance imaging for differentiating clinically significant prostate cancer in the peripheral zone
Turkish Journal of Medical Sciences · Ocak 2023
YÖKSİS Kayıtları
Texture analysis of multiparametric magnetic resonance imaging for differentiating clinically significant prostate cancer in the peripheral zone
Turkish Journal Of Medical Sciences · 2023 SCI-Expanded
DOÇENT ABİDİN KILINÇER →
Texture analysis of multiparametric magnetic resonance imaging for differentiating clinically significant prostate cancer in the peripheral zone
The Scientific and Technological Research Council of Turkey (TUBITAK-ULAKBIM) - DIGITAL COMMONS JOURNALS · 2023 SCI-Expanded
PROFESÖR MUSTAFA KOPLAY →
Texture analysis of multiparametric magnetic resonance imaging for differentiating clinically significant prostate cancer in the peripheral zone
The Scientific and Technological Research Council of Turkey (TUBITAK-ULAKBIM) - DIGITAL COMMONS JOURNALS · 2023 SCI-Expanded
PROFESÖR SERDAR GÖKTAŞ →
Texture analysis of multiparametric magnetic resonance imaging for differentiating clinically significant prostate cancer in the peripheral zone
Turkish Journal Of Medical Sciences · 2023 SCI-Expanded
PROFESÖR MEHMET KAYNAR →
Texture analysis of multiparametric magnetic resonance imaging for differentiating clinically significant prostate cancer in the peripheral zone
The Scientific and Technological Research Council of Turkey (TUBITAK-ULAKBIM) - DIGITAL COMMONS JOURNALS · 2023 SCI-Expanded
PROFESÖR MEHMET KAYNAR →
Texture analysis of multiparametric magnetic resonance imaging for differentiating clinically significant prostate cancer in the peripheral zone
Turkish Journal Of Medical Sciences · 2023 SCI-Expanded
DOÇENT HALİL ÖZER →
Texture analysis of multiparametric magnetic resonance imaging for differentiating clinically significant prostate cancer in the peripheral zone
The Scientific and Technological Research Council of Turkey (TUBITAK-ULAKBIM) - DIGITAL COMMONS JOURNALS · 2023 SCI-Expanded
DOKTOR ÖĞRETİM ÜYESİ NUSRET SEHER →
Makale Bilgileri
DergiTurkish Journal of Medical Sciences
Yayın TarihiOcak 2023
Cilt / Sayfa53 · 701-711
Scopus ID2-s2.0-85163692172
Erişim🔓 Açık Erişim
Özet
Background/aim: Texture analysis (TA) provides additional tissue heterogeneity data that may assist in differentiating peripheral zone (PZ) lesions in multiparametric magnetic resonance imaging (mpMRI). This study investigates the role of magnetic resonance imaging texture analysis (MRTA) in detecting clinically significant prostate cancer (csPCa) in the PZ. Materials and methods: This retrospective study included 80 consecutive patients who had an mpMRI and a prostate biopsy for sus-pected prostate cancer. Two radiologists in consensus interpreted mpMRI and performed texture analysis based on their histopathology. The first-, second-, and higher-order texture parameters were extracted from mpMRI and were compared between groups. Univariate and multivariate logistic regression analyses were performed using the texture parameters to determine the independent predictors of csPCa. Receiver operating characteristic (ROC) curve analysis was conducted to assess the diagnostic performance of the texture parameters. Results: In the periferal zone, 39 men had csPCa, while 41 had benign lesions or clinically insignificant prostate cancer (cisPCa). The majority of texture parameters showed statistically significant differences between the groups. Univariate ROC analysis showed that the ADC mean and ADC median were the best variables in differentiating csPCa (p < 0.001). The first-order logistic regression model (mean + entropy) based on the ADC maps had a higher AUC value (0.996; 95% CI: 0.989–1) than other texture-based logistic regression models (p < 0.001). Conclusion: MRTA is useful in differentiating csPCa from other lesions in the PZ. Consequently, the first-order multivariate regression model based on ADC maps had the highest diagnostic performance in differentiating csPCa.
Yazarlar (8)
1
Halil Özer
ORCID: 0000-0003-1141-1094
2
M. Koplay
ORCID: 0000-0001-7513-4968
3
Ahmet Baytok
4
N. Seher
ORCID: 0000-0003-2296-556X
5
Lütfi Saltuk Demir
6
Abidin Kılınçer
7
Mehmet Kaynar
ORCID: 0000-0002-6957-9060
8
Serdar Goktas
ORCID: 0000-0001-6538-7187
Anahtar Kelimeler
magnetic resonance imaging
Prostate cancer
radiomics
texture analysis
Kurumlar
Necmettin Erbakan Üniversitesi
Meram Turkey
Selçuk Tip Fakültesi
Konya Turkey
Metrikler
1
Atıf
8
Yazar
4
Anahtar Kelime