Nazofarenks karsinomu olan hastalarda metastatik lenf nodlarının saptanmasında manyetik rezonans görüntüleme doku analizi
Öz
Özet
Amaç: Nazofarenks karsinomu (NK) olan hastalarda metastatik lenf nodlarının saptanmasında manyetik rezonans görüntüleme (MRG) doku analizinin (DA) rolünü araştırmak.
Gereç ve yöntemler: Ocak 2020-Ekim 2021 tarihleri arasında 32 metastatik lenf nodu olan 15 NK hastası ve benign lenf nodu olan 30 sağlıklı birey çalışmaya dahil edildi. Doku özellikleri, metastatik ve benign lenf nodları arasında karşılaştırıldı. Çok değişkenli regresyon analizi kullanılarak metastatik lenf nodlarını tahmin için bağımsız değişkenler belirlendi. Regresyon modellerinin tanısal performansını değerlendirmek için receiver operator characteristics (ROC) analizi kullanıldı.
Bulgular: First order doku özellikleri gruplar arasında anlamlı farklılık göstermedi (p>0,05). Metastatik lenf nodlarındaki correlation dışında tüm gray-level co-occurrence matrix (GLCM) ve gray-level run length matrix (GLRLM) özellikleri anlamlı olarak farklıydı (p<0,05). GLCM özelliklerinden joint entropy, joint energy ve maximum probability; GLRLM özelliklerinden gray level non uniformity ve low gray level run emphasis metastatik lenf nodlarının tahmininde bağımsız değişkenlerdi. GLCM regresyon modeli ve GLRLM regresyon modeli için eğri altındaki alan (AUC) değerleri sırasıyla 0,975 ve 0,928 idi.
Sonuç: MRG doku analizi, doku heterojenitesi ve hücresel kompozisyon hakkında kantitatif bilgi sağlayarak NK’li hastalarda metastatik lenf nodlarını saptamada yararlı olabilir.
Anahtar Kelimeler
Manyetik rezonans görüntüleme doku analizi nazofarenks karsinomu metastatik lenf nodları
Kaynakça
- Guo R, Mao Y-P, Tang L-L, Chen L, Sun Y, Ma J. The evolution of nasopharyngeal carcinoma staging. Br J Radiol 2019;92(1102):20190244.
- King AD. MR Imaging of Nasopharyngeal Carcinoma. Magn Reson Imaging Clin N Am 2022;30(1):19-33.
- Siti-Azrin AH, Norsa'adah B, Naing NN. Prognostic factors of nasopharyngeal carcinoma patients in a tertiary referral hospital: a retrospective cohort study. BMC Res Notes 2017;10(1):705.
- Abdel Khalek Abdel Razek A, King A. MRI and CT of nasopharyngeal carcinoma. AJR Am J Roentgenol 2012;198(1):11-8.
- Lan M, Huang Y, Chen CY, Han F, Wu SX, Tian L, et al. Prognostic Value of Cervical Nodal Necrosis in Nasopharyngeal Carcinoma: Analysis of 1800 Patients with Positive Cervical Nodal Metastasis at MR Imaging. Radiology 2015;276(2):536-44.
- Zhang GY, Liu LZ, Wei WH, Deng YM, Li YZ, Liu XW. Radiologic criteria of retropharyngeal lymph node metastasis in nasopharyngeal carcinoma treated with radiation therapy. Radiology 2010;255(2):605-12.
- Gupta A, Rahman K, Shahid M, Kumar A, Qaseem SM, Hassan SA, et al. Sonographic assessment of cervical lymphadenopathy: role of high-resolution and color Doppler imaging. Head Neck 2011;33(3):297-302.
- Ahuja AT, Ying M. Sonographic evaluation of cervical lymph nodes. AJR Am J Roentgenol 2005;184(5):1691-9.
- Wang XS, Hu CS, Ying HM, Zhou ZR, Ding JH, Feng Y. Patterns of retropharyngeal node metastasis in nasopharyngeal carcinoma. Int J Radiat Oncol Biol Phys 2009;73(1):194-201.
- Varghese BA, Cen SY, Hwang DH, Duddalwar VA. Texture Analysis of Imaging: What Radiologists Need to Know. AJR Am J Roentgenol 2019;212(3):520-8.
- Scheckenbach K, Colter L, Wagenmann M. Radiomics in Head and Neck Cancer: Extracting Valuable Information from Data beyond Recognition. ORL J Otorhinolaryngol Relat Spec 2017;79(1-2):65-71.
- Park JH, Bae YJ, Choi BS, Jung YH, Jeong W-J, Kim H, et al. Texture Analysis of Multi-Shot Echo-Planar Diffusion-Weighted Imaging in Head and Neck Squamous Cell Carcinoma: The Diagnostic Value for Nodal Metastasis. J Clin Med 2019;8(11):1767.
- Yuan Y, Ren J, Tao X. Machine learning-based MRI texture analysis to predict occult lymph node metastasis in early-stage oral tongue squamous cell carcinoma. Eur Radiol 2021;31(9):6429-37.
- Kuno H, Garg N, Qureshi MM, Chapman MN, Li B, Meibom SK, et al. CT Texture Analysis of Cervical Lymph Nodes on Contrast-Enhanced [18F] FDG-PET/CT Images to Differentiate Nodal Metastases from Reactive Lymphadenopathy in HIV-Positive Patients with Head and Neck Squamous Cell Carcinoma. AJNR Am J Neuroradiol 2019;40(3):543-50.
- Tomita H, Yamashiro T, Iida G, Tsubakimoto M, Mimura H, Murayama S. Unenhanced CT texture analysis with machine learning for differentiating between nasopharyngeal cancer and nasopharyngeal malignant lymphoma. Nagoya J Med Sci 2021;83(1):135-49.
- Liu L, Pei W, Liao H, Wang Q, Gu D, Liu L, et al. A Clinical-Radiomics Nomogram Based on Magnetic Resonance Imaging for Predicting Progression-Free Survival After Induction Chemotherapy in Nasopharyngeal Carcinoma. Front Oncol 2022;12:792535.
- Tomita H, Yamashiro T, Heianna J, Nakasone T, Kimura Y, Mimura H, et al. Nodal-based radiomics analysis for identifying cervical lymph node metastasis at levels I and II in patients with oral squamous cell carcinoma using contrast-enhanced computed tomography. Eur Radiol 2021;31(10):7440-9.
- Forghani R, Chatterjee A, Reinhold C, Pérez-Lara A, Romero-Sanchez G, Ueno Y, et al. Head and neck squamous cell carcinoma: prediction of cervical lymph node metastasis by dual-energy CT texture analysis with machine learning. Eur Radiol 2019;29(11):6172-81.
- Lu S, Ling H, Chen J, Tan L, Gao Y, Li H, et al. MRI-based radiomics analysis for preoperative evaluation of lymph node metastasis in hypopharyngeal squamous cell carcinoma. Front Oncol 2022;12:936040.
- Zhao L, Gong J, Xi Y, Xu M, Li C, Kang X, et al. MRI-based radiomics nomogram may predict the response to induction chemotherapy and survival in locally advanced nasopharyngeal carcinoma. Eur Radiol 2020;30(1):537-46.
Magnetic Resonance Imaging Texture Analysis in the Detection of Metastatic Lymph Nodes in Patients with Nasopharyngeal Carcinoma
Öz
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.
Anahtar Kelimeler
Magnetic resonance imaging texture analysis nasopharyngeal carcinoma metastatic lymph nodes
Kaynakça
- Guo R, Mao Y-P, Tang L-L, Chen L, Sun Y, Ma J. The evolution of nasopharyngeal carcinoma staging. Br J Radiol 2019;92(1102):20190244.
- King AD. MR Imaging of Nasopharyngeal Carcinoma. Magn Reson Imaging Clin N Am 2022;30(1):19-33.
- Siti-Azrin AH, Norsa'adah B, Naing NN. Prognostic factors of nasopharyngeal carcinoma patients in a tertiary referral hospital: a retrospective cohort study. BMC Res Notes 2017;10(1):705.
- Abdel Khalek Abdel Razek A, King A. MRI and CT of nasopharyngeal carcinoma. AJR Am J Roentgenol 2012;198(1):11-8.
- Lan M, Huang Y, Chen CY, Han F, Wu SX, Tian L, et al. Prognostic Value of Cervical Nodal Necrosis in Nasopharyngeal Carcinoma: Analysis of 1800 Patients with Positive Cervical Nodal Metastasis at MR Imaging. Radiology 2015;276(2):536-44.
- Zhang GY, Liu LZ, Wei WH, Deng YM, Li YZ, Liu XW. Radiologic criteria of retropharyngeal lymph node metastasis in nasopharyngeal carcinoma treated with radiation therapy. Radiology 2010;255(2):605-12.
- Gupta A, Rahman K, Shahid M, Kumar A, Qaseem SM, Hassan SA, et al. Sonographic assessment of cervical lymphadenopathy: role of high-resolution and color Doppler imaging. Head Neck 2011;33(3):297-302.
- Ahuja AT, Ying M. Sonographic evaluation of cervical lymph nodes. AJR Am J Roentgenol 2005;184(5):1691-9.
- Wang XS, Hu CS, Ying HM, Zhou ZR, Ding JH, Feng Y. Patterns of retropharyngeal node metastasis in nasopharyngeal carcinoma. Int J Radiat Oncol Biol Phys 2009;73(1):194-201.
- Varghese BA, Cen SY, Hwang DH, Duddalwar VA. Texture Analysis of Imaging: What Radiologists Need to Know. AJR Am J Roentgenol 2019;212(3):520-8.
- Scheckenbach K, Colter L, Wagenmann M. Radiomics in Head and Neck Cancer: Extracting Valuable Information from Data beyond Recognition. ORL J Otorhinolaryngol Relat Spec 2017;79(1-2):65-71.
- Park JH, Bae YJ, Choi BS, Jung YH, Jeong W-J, Kim H, et al. Texture Analysis of Multi-Shot Echo-Planar Diffusion-Weighted Imaging in Head and Neck Squamous Cell Carcinoma: The Diagnostic Value for Nodal Metastasis. J Clin Med 2019;8(11):1767.
- Yuan Y, Ren J, Tao X. Machine learning-based MRI texture analysis to predict occult lymph node metastasis in early-stage oral tongue squamous cell carcinoma. Eur Radiol 2021;31(9):6429-37.
- Kuno H, Garg N, Qureshi MM, Chapman MN, Li B, Meibom SK, et al. CT Texture Analysis of Cervical Lymph Nodes on Contrast-Enhanced [18F] FDG-PET/CT Images to Differentiate Nodal Metastases from Reactive Lymphadenopathy in HIV-Positive Patients with Head and Neck Squamous Cell Carcinoma. AJNR Am J Neuroradiol 2019;40(3):543-50.
- Tomita H, Yamashiro T, Iida G, Tsubakimoto M, Mimura H, Murayama S. Unenhanced CT texture analysis with machine learning for differentiating between nasopharyngeal cancer and nasopharyngeal malignant lymphoma. Nagoya J Med Sci 2021;83(1):135-49.
- Liu L, Pei W, Liao H, Wang Q, Gu D, Liu L, et al. A Clinical-Radiomics Nomogram Based on Magnetic Resonance Imaging for Predicting Progression-Free Survival After Induction Chemotherapy in Nasopharyngeal Carcinoma. Front Oncol 2022;12:792535.
- Tomita H, Yamashiro T, Heianna J, Nakasone T, Kimura Y, Mimura H, et al. Nodal-based radiomics analysis for identifying cervical lymph node metastasis at levels I and II in patients with oral squamous cell carcinoma using contrast-enhanced computed tomography. Eur Radiol 2021;31(10):7440-9.
- Forghani R, Chatterjee A, Reinhold C, Pérez-Lara A, Romero-Sanchez G, Ueno Y, et al. Head and neck squamous cell carcinoma: prediction of cervical lymph node metastasis by dual-energy CT texture analysis with machine learning. Eur Radiol 2019;29(11):6172-81.
- Lu S, Ling H, Chen J, Tan L, Gao Y, Li H, et al. MRI-based radiomics analysis for preoperative evaluation of lymph node metastasis in hypopharyngeal squamous cell carcinoma. Front Oncol 2022;12:936040.
- Zhao L, Gong J, Xi Y, Xu M, Li C, Kang X, et al. MRI-based radiomics nomogram may predict the response to induction chemotherapy and survival in locally advanced nasopharyngeal carcinoma. Eur Radiol 2020;30(1):537-46.
Ayrıntılar
| Birincil Dil | İngilizce |
|---|---|
| Konular | Radyoloji ve Organ Görüntüleme |
| Bölüm | Original Article |
| Yazarlar | |
| Erken Görünüm Tarihi | 29 Ağustos 2023 |
| Yayımlanma Tarihi | 31 Ağustos 2023 |
| Gönderilme Tarihi | 8 Haziran 2023 |
| Yayımlandığı Sayı | Yıl 2023 Cilt: 33 Sayı: 4 |
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