Texture Indices of 18F-FDG PET/CT for Differentiating Squamous Cell Carcinoma and Non-Hodgkin's Lymphoma of the Oropharynx.
Adult
Aged
Aged, 80 and over
Carcinoma, Squamous Cell
/ diagnostic imaging
Diagnosis, Differential
Female
Fluorodeoxyglucose F18
/ metabolism
Humans
Lymphoma, Non-Hodgkin
/ diagnostic imaging
Male
Middle Aged
Oropharyngeal Neoplasms
/ diagnostic imaging
Positron-Emission Tomography
Retrospective Studies
18F-FDG
PET/CT
malignant lymphoma
oropharyngeal squamous cell carcinoma
texture
Journal
Acta medica Okayama
ISSN: 0386-300X
Titre abrégé: Acta Med Okayama
Pays: Japan
ID NLM: 0417611
Informations de publication
Date de publication:
Jun 2021
Jun 2021
Historique:
entrez:
28
6
2021
pubmed:
29
6
2021
medline:
15
12
2021
Statut:
ppublish
Résumé
We assessed the role of 18F-FDG PET/CT texture indices for the differentiation of squamous cell carcinoma (SCC) and non-Hodgkin's lymphoma (NHL) in the oropharynx. 18F-FDG PET/CT data for 27 patients with SCC and 25 patients with NHL in the oropharynx were investigated. The maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), total lesion glycolysis (TLG), and six texture indices (homogeneity, entropy, short-run emphasis, long-run emphasis, low gray-level zone emphasis [LGZE], and high graylevel zone emphasis [HGZE]) were derived from PET images. PET/CT parameters of the SCC patients were compared with those of the NHL patients. The diagnostic accuracy of the indices for differentiating SCC from NHL was calculated by a receiver operating characteristic curve analysis. 18F-FDG uptake in the oropharynx was observed in all of the patients. The SUVmax, MTV, and TLG did not differ significantly between the SCC and NHL groups, but two of the six texture indices (LGZE [p=0.004] and HGZE [p=0.03]) showed significant differences between the groups. LGZE was the best discriminative index for the differentiation of SCC and NHL (55.6% sensitivity, 88.0% specificity). The LGZE and HGZE texture indices derived from 18F-FDG PET/CT images may be useful in differentiating SCC and NHL in the oropharynx.
Substances chimiques
Fluorodeoxyglucose F18
0Z5B2CJX4D
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
351-356Déclaration de conflit d'intérêts
No potential conflict of interest relevant to this article was reported.
Références
Ichikawa Y, Sumi M, Sasaki M, Sumi T and Nakamura T: Efficacy of diffusion-weighted imaging for the differentiation between lymphomas and carcinomas of the nasopharynx and oropharynx: correlations of apparent diffusion coefficients and histologic features. AJNR (2012) 33: 761-766.
Kato H, Kanematsu M, Kawaguchi S, Watanabe H, Mizuta K and Aoki M: Evaluation of imaging findings differentiating extranodal non-Hodgkin's lymphoma from squamous cell carcinoma in nasoand oropharynx. Clin Imaging (2013) 37: 657-663.
Rohren EM, Turkington TG and Coleman RE: Clinical applications of PET in oncology. Radiology (2004) 231: 305-332.
Davnall F, Yip CS, Ljungqvist G, Selmi M, Ng F, Sanghera B, Ganeshan B, Miles KA, Cook GJ and Goh V: Assessment of tumor heterogeneity: an emerging imaging tool for clinical practice? Insights Imaging (2012) 3: 573-589.
Chan SC, Cheng NM, Hsieh CH, Ng SH, Lin CY, Yen TC, Hsu CL, Wan HM, Liao CT, Chang KP and Wang JJ: Multiparametric imaging using 18F-FDG PET/CT heterogeneity parameters and functional MRI techniques: prognostic significance in patients with primary advanced oropharyngeal or hypopharyngeal squamous cell carcinoma treated with chemoradiotherapy. Oncotarget (2017) 8: 62606- 62621.
Chen SW, Shen WC, Lin YC, Chen RY, Hsieh TC, Yen KY and Kao CH: Correlation of pretreatment 18F-FDG PET tumor textural features with gene expression in pharyngeal cancer and implications for radiotherapy-based treatment outcomes. Eur J Nucl Med Mol Imaging (2017) 44: 567-580.
Cheng NM, Fang YH, Lee LY, Chang JT, Tsan DL, Ng SH, Wang HM, Liao CT, Yang LY, Hsu CH and Yen TC: Zone-size non-uniformity of 18F-FDG PET regional textural features predicts survival in patients with oropharyngeal cancer. Eur J Nucl Med Mol Imaging (2015) 42: 419-428.
Fujima N, Hirata K, Shiga T, Li R, Yasuda K, Onimaru R, Tsuchiya K, Kano S, Mizumachi T, Homma A, Kudo K and Shirato H: Integrating quantitative morphological and intratumoural textural characteristics in FDG-PET for the prediction of prognosis in pharynx squamous cell carcinoma patients. Clin Radiol (2018) 73: 1059. e1-8.
Nioche C, Orlhac F, Boughdad S, Reuzé S, Goya-Outi J, Robert C, Pellot-Barakat C, Soussan M, Frouin F and Buvat I: LIFEx: a freeware for radiomic feature calculation in multimodality imaging to accelerate advances in the characterization of tumor heterogeneity. Cancer Research (2018) 78: 4786-4789.
Orlhac F, Nioche C, Soussan M and Buvat I: Understanding changes in tumor texture indices in PET: A comparison between visual assessment and index values in simulated and patient data. J Nucl Med (2017) 58: 387-392.
Orlhac F, Soussan M, Maisonobe JA, Garcia CA, Vanderlinden B and Buvat I: Tumor texture analysis in 18F-FDG PET: relationships between texture parameters, histogram indices, standardized uptake values, metabolic volumes, and total lesion glycolysis. J Nucl Med (2014) 55: 414-422.
Nicolau C, Sala E, Kumar A, Goldman DA, Schoder H, Hricak H and vargas HA: Renal masses detected on FDG PET/CT in patients with lymphoma: imaging features differentiating primary renal cell carcinomas from renal lymphomatous involvement. Am J Roentgenol (2017) 208: 849-853.
Ou X, Wang J, Zhou R, Zhu S, Pang F, Zhou Y, Tian R and Ma X: Ability of 18F-FDG PET/CT radiomic features to distinguish breast carcinoma from breast lymphoma. Contrast Media Mol Imaging (2019) 4507694.
Cho KS, Kang DW, Kim HJ, Lee JK and Roh HJ: Differential diagnosis of primary nasopharyngeal lymphoma and nasopharyngeal carcinoma focusing on CT, MRI, and PET/CT. Otolaryngol Head Neck Surg (2012) 146: 574-578.
Lv W, Yuan Q, Wang Q, Ma J, Jiang J, Yang W, Feng Q, Chen W, Rahmim A and Lu L: Robustness versus disease differentiation when varying parameter settings in radiomics features: application to nasopharyngeal PET/CT. European Radiology (2018) 28: 3245- 3254.
Chen S, Harmon S, Perk T, Li X, Chen M, Li Y and Jeraj R: Diagnostic classification of solitary pulmonary nodules using dual time 18F-FDG PET/CT image texture features in granuloma-endemic regions. Sci Rep (2017) 7: 9370.
Kirienko M, Cozzi L, Rossi A, Voulaz E, Antunovic L, Fogliata A, Chiti A and Sollini M: Ability of FDG PET and CT radiomics features to differentiate between primary and metastatic lung lesions. Eur J Nucl Med Mol Imaging (2018) 45: 1649-1660.
Ha S, Choi H, Cheon GJ, Kang KW, Chung JK, Kim EE and Lee DS: Autoclustering of non-small cell lung carcinoma subtypes on 18FFDG PET using texture analysis: a preliminary result. Nucl Med Mol Imaging (2014) 48: 278-286.
Orlhac F, Soussan M, Chouahnia K, Martinod E and Buvat I: 18F-FDG PET-derived textural indices reflect tissue-specific uptake pattern in non-small cell lung cancer. PLoS One (2015) 10: e0145063.
Xu H, Guo W, Cui X, Zhuo H, Xiao Y, Ou X, Zhao Y, Zhang T and Ma X: Three-dimensional texture analysis based on PET/CT images to distinguish hepatocellular carcinoma and hepatic lymphoma. Front Oncol (2019) 9: 844.
Huang YT, Kumar AR and Bhuta S: 18F-FDG PET/CT as a semiquantitative imaging marker in HPV-p16-positive oropharyngeal squamous cell cancers. Nucl Med Commun (2015) 36: 16-20.