Textural Analysis of Ultrasound Images of Reactive and Neoplastic Cervical Lymph Nodes: an exploratory study

Antonione Santos Bezerra Pinto; Letícia de Brito Teixeira; Rhayssa Ellen Sousa Santos; Ayrton Galvão de Araujo Junior; Nayze Lucena Sangreman Aldeman; Carlos Alberto Monteiro Falcão; Paulo de Camargo Moraes; Marcelo Sperandio; Victor Angelo Martins Montalli

doi:10.5327/2525-5711.502

Authors

Antonione Santos Bezerra Pinto Department of Oral Medicine and Pathology, Faculdade São Leopoldo Mandic, Research Institute, Campinas, São Paulo, Brasil. https://orcid.org/0000-0002-6577-2816
Letícia de Brito Teixeira Universidade Estadual do Piauí (UESPI), Curso de Odontologia. Parnaíba, Piauí, Brasil. https://orcid.org/0009-0000-6149-0929
Rhayssa Ellen Sousa Santos Centro Universitário Mauricio de Nassau, Parnaíba-PI https://orcid.org/0009-0007-5053-9652
Ayrton Galvão de Araujo Junior Faculdade AFYA Parnaíba, Curso de Medicina. Parnaíba, Piauí, Brasil. https://orcid.org/0000-0003-0550-5019
Nayze Lucena Sangreman Aldeman Faculdade AFYA Parnaíba, Curso de Medicina; Universidade Federal do Delta do Parnaíba (UFDPar), Curso de Medicina. Parnaíba, Piauí, Brasil. https://orcid.org/0000-0002-1957-9724
Carlos Alberto Monteiro Falcão Universidade Estadual do Piauí (UESPI), Curso de Odontologia. Parnaíba, Piauí, Brasil https://orcid.org/0000-0001-7787-0280
Paulo de Camargo Moraes Department of Oral Medicine and Pathology, Faculdade São Leopoldo Mandic, Research Institute, Campinas, São Paulo, Brasil. https://orcid.org/0000-0002-1927-7718
Marcelo Sperandio Department of Oral Medicine and Pathology, Faculdade São Leopoldo Mandic, Research Institute, Campinas, São Paulo, Brasil. https://orcid.org/0000-0003-3836-1891
Victor Angelo Martins Montalli Department of Oral Medicine and Pathology, Faculdade São Leopoldo Mandic, Research Institute, Campinas, São Paulo, Brasil. https://orcid.org/0000-0003-3836-1891

DOI:

https://doi.org/10.5327/2525-5711.502

Keywords:

Image Analysis, Lymph Node, Neoplasm, Ultrasound 11

Abstract

Objective: To evaluate textural parameters of ultrasound images of reactive and neoplastic cervical lymph nodes, investigating differences between the groups and the potential of texture analysis to characterize these differences. Materials and Methods: We analyzed 36 B-mode (2D) cervical ultrasound images, corresponding to 16 reactive and 20 neoplastic lymph nodes, from examinations performed between 2010 and 2024 at a diagnostic imaging clinic in Parnaíba, Piauí, Brazil. Reactive lymph nodes were classified based on clinical course and response to treatment, while neoplastic lymph nodes were confirmed histopathologically. The images were analyzed using MaZda, with parameters based on the gray-level co-occurrence matrix (GLCM), considering different variables, directions, and distances between pixels. The Mann–Whitney test was used, with a significance level of 5%. Results: Four variables were statistically significant: Sum of Squares (SumOfSqs) in the direction S(1,-1), Entropy Difference (DifEntrp) S(2,0), Sum of Means (SumAverg) S(4,0), and Sum of Entropy (SumEntrp) S(0,4). Greater dispersion of SumOfSqs, DifEntrp, and SumEntrp was observed in reactive lymph nodes, while SumAverg was elevated in neoplastic lymph nodes. Conclusion: Textural analysis identified significant differences between the groups, suggesting its potential as a complementary quantitative approach to conventional ultrasound evaluation. Future studies may validate these findings and expand their clinical application.

References

[1] Daniel AP, Castro ATS, Froes BB, Corrêa LE, Mendonça MFM, Carvalho MGF. Parâmetros anatômicos e características radiológicas relevantes para a avaliação dos linfonodos cervicais: uma revisão bibliográfica. Rev Assoc Bras Saúde Educ. 2022;8(9):1001-13. Available from: https://periodicorease.pro.br/rease/article/view/6927

[2] Sahu N, Padhy RN. Bayesian analysis of high-resolution ultrasonography and guided fine needle aspiration cytology in diagnosis of palpable thyroid nodules. Braz J Otorhinolaryngol. 2018;84(1):20-7. https://doi.org/10.1016/j.bjorl.2016.10.010

[3] Appa SK, Ramya BV, Bhushan GP, Vuppala C. Clinical study and management of cervical lymphadenopathy. Int J Acad Med Pharm. 2023;:794-800.

[4] Kawashima Y, Miyakoshi M, Kawabata Y, Indo H. Efficacy of texture analysis of ultrasonographic images in the differentiation of metastatic and non-metastatic cervical lymph nodes in patients with squamous cell carcinoma of the tongue. Oral Surg Oral Med Oral Pathol Oral Radiol. 2023;136(2):247-54. https://doi.org/10.1016/j.oooo.2023.04.012

[5] Ogassavara B, Tucunduva Neto RR, Souza RR, Tucunduva MJ. Padrão ultrassonográfico dos linfonodos da face e do pescoço em jovens e indivíduos de meia-idade. Radiol Bras. 2016;49(4):225-8.

[6] Abbasian Ardakani A, Rasekhi A, Mohammadi A, Motevalian E, Khalili Najafabad B. Differentiation between metastatic and tumour-free cervical lymph nodes in patients with papillary thyroid carcinoma by grey-scale sonographic texture analysis. Pol J Radiol. 2018;83:e37-46. https://doi.org/10.5114/pjr.2018.75017

[7] Kim SY, Lee E, Nam SJ, Kim EK, Moon HJ, Yoon JH, et al. Ultrasound texture analysis: association with lymph node metastasis of papillary thyroid microcarcinoma. PLoS One. 2017;12(4):e0176103. https://doi.org/10.1371/journal.pone.0176103

[8] Barioni ED, Lopes SLPC, Silvestre PR, Yasuda CL, Costa ALF. Análise de textura em imagens volumétricas para radiologia dentomaxilofacial: transformando abordagens diagnósticas e direções futuras. J Imaging. 2024;10(11):263. https://doi.org/10.3390/jimaging10110263

[9] Gomes JPP, Ogawa CM, Silveira RV, Castellano G, De Rosa CS, Yasuda CL, et al. Análise de textura por ressonância magnética para diferenciar ameloblastoma de ceratocisto odontogênico. Sci Rep. 2022;12(1):20047. https://doi.org/10.1038/s41598-022-20802-7

[10] Haralick RM, Shanmugam K, Dinstein I. Textural features for image classification. IEEE Trans Syst Man Cybern. 1973;SMC-3(6):610-21. https://doi.org/10.1109/TSMC.1973.4309314

[11] Chammas MC, Lundberg JS, Juliano AG, Saito OC, Marcelino ASZ, Cerri GG. Linfonodos cervicais: um dilema para o ultrassonografista. Radiol Bras. 2004;37:357-64. Available from: https://www.scielo.br/j/rb/a/MxpfNbqtrnCHjBLqYq9Zysy

[12] Ahuja AT, Ying M. Sonographic evaluation of cervical lymph nodes. AJR Am J Roentgenol. 2005;184(5):1691-9.

[13] Safakish A, Sannachi L, DiCenzo D, Kolios C, Pejović-Milić A, Czarnota GJ. Predicting head and neck cancer treatment outcomes with pre-treatment quantitative ultrasound texture features and optimising machine learning classifiers with texture-of-texture features. Front Oncol. 2023;13:1258970. https://doi.org/10.3389/fonc.2023.1258970

[14] Safakish A, Moslemi A, Moore-Palhares D, Sannachi L, Poon I, Karam I, et al. Enhanced deep texture radiomics analysis of magnetic resonance imaging to predict head and neck cancer treatment outcomes using machine learning classifiers. Radiation. 2024;4(2):192-212. https://doi.org/10.3390/radiation4020015

[15] Costa ALF, Fardim KAC, Ribeiro IT, Jardini MAN, Braz-Silva PH, Orhan K, et al. Cone beam computed tomography texture analysis may help differentiate odontogenic from non-odontogenic maxillary sinusitis. Imaging Sci Dent. 2023;53(1):43-51. https://doi.org/10.5624/isd.20220166

[16] Oliveira VGB, Araujo ECBC, Costa ALF, Moraes MB, Lopes SLPC. Texture analysis as a marker for identifying joint alterations in temporomandibular disorders on magnetic resonance imaging. Braz Dent Sci. 2024;27(3):e4312. https://doi.org/10.4322/bds.2024.e4312

[17] Oliveira LAP, Lopes DLG, Gomes JPP, Silveira RV, Nozaki DVA, Santos LF, et al. Enhanced diagnostic precision: assessing tumor differentiation in head and neck squamous cell carcinoma using multi-slice spiral CT texture analysis. J Clin Med. 2024;13(14):4038. https://doi.org/10.3390/jcm13144038

[18] Lambin P, Rios-Velazquez E, Leijenaar R, Carvalho S, van Stiphout RGPM, Granton P, et al. Radiomics: extracting more information from medical images using advanced feature analysis. Eur J Cancer. 2012;48(4):441-6. https://doi.org/10.1016/j.ejca.2011.11.036

[19] Lopes DLG, Lopes SLPC, Ungaro DMT, Gomes APM, Moura NB, Gonçalves BC, Costa ALF. Radiomics-driven CBCT texture analysis as a novel biosensor for quantifying periapical bone healing: a comparative study of intracanal medications. Biosensors (Basel). 2025;15(2):98. https://doi.org/10.3390/bios15020098

[20] de Oliveira PJR, Lima CCL, Fernandes LM, Vieira RAC, Leite AF, Lucena EHG, et al. HPV status prediction in oropharyngeal squamous cell carcinomas using CT texture analysis and machine learning: a preliminary study. Cancers (Basel). 2025;17(9):2317. https://doi.org/10.3390/cancers17092317