Magnetic Resonance Imaging Texture Analysis in the Detection of Metastatic Lymph Nodes in Patients with Nasopharyngeal Carcinoma
Abstract Aims: To investigate the role of magnetic resonance imaging (MRI) texture analysis (TA) in the detection of metastatic lymph nodes in patients with nasopharyngeal carcinoma (NPC). Material and methods: Between January 2020 and October 2021, 15 NPC patients with 32 metastatic lymph nodes a...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Selcuk University Press
2023-08-01
|
| Series: | Genel Tıp Dergisi |
| Subjects: | |
| Online Access: | https://dergipark.org.tr/tr/download/article-file/3196897 |
| _version_ | 1826953801978871808 |
|---|---|
| author | Mehmet Sedat Durmaz Abdussamet Batur Abidin Kılınçer Halil Özer Nurullah Özdemir |
| author_facet | Mehmet Sedat Durmaz Abdussamet Batur Abidin Kılınçer Halil Özer Nurullah Özdemir |
| author_sort | Mehmet Sedat Durmaz |
| collection | DOAJ |
| description | Abstract
Aims: To investigate the role of magnetic resonance imaging (MRI) texture analysis (TA) in the detection of metastatic lymph nodes in patients with nasopharyngeal carcinoma (NPC).
Material and methods: Between January 2020 and October 2021, 15 NPC patients with 32 metastatic lymph nodes and 30 healthy subjects with benign lymph nodes were included in the study. The texture features compared between metastatic and benign lymph nodes. The independent predictor parameters of metastatic lymph nodes were determined using multivariate regression analysis. Receiver operator characteristics (ROC) analysis was used to evaluate the diagnostic performance of the regression models.
Results: The first order texture features did not differ significantly between groups (p>0.05). Except for correlation in metastatic lymph nodes, all gray-level co-occurrence matrix (GLCM) and gray-level run length matrix (GLRLM) features were significantly different (p<0.05). The GLCM features of joint entropy, joint energy, and maximum probability; and the GLRLM features of gray level non uniformity and low gray level run emphasis were independent predictors of metastatic lymph nodes. The area under the curve (AUC) values for the GLCM regression model and GLRLM regression model were 0.975 and 0.928, respectively.
Conclusion: MRI texture analysis may be useful to detect metastatic lymph nodes in patients with NPC by providing quantitative information on tissue heterogeneity and cellular composition. |
| first_indexed | 2024-03-12T01:30:39Z |
| format | Article |
| id | doaj.art-c5ad242e657c411b96ae7883d7ef7adc |
| institution | Directory Open Access Journal |
| issn | 2602-3741 |
| language | English |
| last_indexed | 2025-02-17T23:26:34Z |
| publishDate | 2023-08-01 |
| publisher | Selcuk University Press |
| record_format | Article |
| series | Genel Tıp Dergisi |
| spelling | doaj.art-c5ad242e657c411b96ae7883d7ef7adc2024-12-02T05:11:41ZengSelcuk University PressGenel Tıp Dergisi2602-37412023-08-0133446146510.54005/geneltip.1311577154Magnetic Resonance Imaging Texture Analysis in the Detection of Metastatic Lymph Nodes in Patients with Nasopharyngeal CarcinomaMehmet Sedat Durmaz0Abdussamet Batur1Abidin Kılınçer2Halil Özer3Nurullah Özdemir4SELCUK UNIVERSITY, SCHOOL OF MEDICINEMARDIN ARTUKLU UNIVERSITYSELCUK UNIVERSITY, SCHOOL OF MEDICINESELCUK UNIVERSITY, SCHOOL OF MEDICINESELCUK UNIVERSITY, SCHOOL OF MEDICINEAbstract Aims: To investigate the role of magnetic resonance imaging (MRI) texture analysis (TA) in the detection of metastatic lymph nodes in patients with nasopharyngeal carcinoma (NPC). Material and methods: Between January 2020 and October 2021, 15 NPC patients with 32 metastatic lymph nodes and 30 healthy subjects with benign lymph nodes were included in the study. The texture features compared between metastatic and benign lymph nodes. The independent predictor parameters of metastatic lymph nodes were determined using multivariate regression analysis. Receiver operator characteristics (ROC) analysis was used to evaluate the diagnostic performance of the regression models. Results: The first order texture features did not differ significantly between groups (p>0.05). Except for correlation in metastatic lymph nodes, all gray-level co-occurrence matrix (GLCM) and gray-level run length matrix (GLRLM) features were significantly different (p<0.05). The GLCM features of joint entropy, joint energy, and maximum probability; and the GLRLM features of gray level non uniformity and low gray level run emphasis were independent predictors of metastatic lymph nodes. The area under the curve (AUC) values for the GLCM regression model and GLRLM regression model were 0.975 and 0.928, respectively. Conclusion: MRI texture analysis may be useful to detect metastatic lymph nodes in patients with NPC by providing quantitative information on tissue heterogeneity and cellular composition.https://dergipark.org.tr/tr/download/article-file/3196897manyetik rezonans görüntülemedoku analizinazofarenks karsinomumetastatik lenf nodlarımagnetic resonance imagingtexture analysisnasopharyngeal carcinomametastatic lymph nodes |
| spellingShingle | Mehmet Sedat Durmaz Abdussamet Batur Abidin Kılınçer Halil Özer Nurullah Özdemir Magnetic Resonance Imaging Texture Analysis in the Detection of Metastatic Lymph Nodes in Patients with Nasopharyngeal Carcinoma Genel Tıp Dergisi manyetik rezonans görüntüleme doku analizi nazofarenks karsinomu metastatik lenf nodları magnetic resonance imaging texture analysis nasopharyngeal carcinoma metastatic lymph nodes |
| title | Magnetic Resonance Imaging Texture Analysis in the Detection of Metastatic Lymph Nodes in Patients with Nasopharyngeal Carcinoma |
| title_full | Magnetic Resonance Imaging Texture Analysis in the Detection of Metastatic Lymph Nodes in Patients with Nasopharyngeal Carcinoma |
| title_fullStr | Magnetic Resonance Imaging Texture Analysis in the Detection of Metastatic Lymph Nodes in Patients with Nasopharyngeal Carcinoma |
| title_full_unstemmed | Magnetic Resonance Imaging Texture Analysis in the Detection of Metastatic Lymph Nodes in Patients with Nasopharyngeal Carcinoma |
| title_short | Magnetic Resonance Imaging Texture Analysis in the Detection of Metastatic Lymph Nodes in Patients with Nasopharyngeal Carcinoma |
| title_sort | magnetic resonance imaging texture analysis in the detection of metastatic lymph nodes in patients with nasopharyngeal carcinoma |
| topic | manyetik rezonans görüntüleme doku analizi nazofarenks karsinomu metastatik lenf nodları magnetic resonance imaging texture analysis nasopharyngeal carcinoma metastatic lymph nodes |
| url | https://dergipark.org.tr/tr/download/article-file/3196897 |
| work_keys_str_mv | AT mehmetsedatdurmaz magneticresonanceimagingtextureanalysisinthedetectionofmetastaticlymphnodesinpatientswithnasopharyngealcarcinoma AT abdussametbatur magneticresonanceimagingtextureanalysisinthedetectionofmetastaticlymphnodesinpatientswithnasopharyngealcarcinoma AT abidinkılıncer magneticresonanceimagingtextureanalysisinthedetectionofmetastaticlymphnodesinpatientswithnasopharyngealcarcinoma AT halilozer magneticresonanceimagingtextureanalysisinthedetectionofmetastaticlymphnodesinpatientswithnasopharyngealcarcinoma AT nurullahozdemir magneticresonanceimagingtextureanalysisinthedetectionofmetastaticlymphnodesinpatientswithnasopharyngealcarcinoma |