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

Abstract

BACKGROUND AND PURPOSE: Differentiating nodal metastases from reactive adenopathy in HIV-infected patients with [ 18 F] FDG-PET/CT can be challenging because lymph nodes in HIV-positive patients often show increased [ 18 F] FDG uptake. The purpose of this study was to assess CT textural analysis characteristics of HIV-positive and HIV-negative lymph nodes on [ 18 F] FDG-PET/CT to differentiate nodal metastases from disease-specific nodal reactivity. MATERIALS AND METHODS: Nine HIV-positive patients with head and neck squamous cell carcinoma (7 men, 2 women; 29-62 years of age; median age, 48 years) with 22 lymph nodes (Ն1 cm) who underwent contrast-enhanced CT with [ 18 F] FDG-PET followed by pathologic evaluation of cervical lymph nodes were retrospectively reviewed. Twenty-six HIV-negative patients with head and neck squamous cell carcinoma with 61 lymph nodes were evaluated as a control group. Each lymph node was manually segmented, and an in-house-developed Matlab-based texture analysis program extracted 41 texture features from each segmented volume. A mixed linear regression model was used to compare the pathologically proved malignant lymph nodes with benign nodes in the 2 enrolled groups. RESULTS: Thirteen (59%) lymph nodes in the HIV-positive group and 22 (36%) lymph nodes in the HIV-negative control group were confirmed as positive for metastases. There were 7 histogram features (P ϭ .017-0.032), 3 gray-level co-occurrence features (P ϭ .009-.025), and 9 gray-level run-length features (P Ͻ .001-.033) that demonstrated a significant difference in HIV-positive patients with either benign or malignant lymph nodes. CONCLUSIONS: CT texture analysis may be useful as a noninvasive method of obtaining additional quantitative information to differentiate nodal metastases from disease-specific nodal reactivity in HIV-positive patients with head and neck squamous cell carcinoma. ABBREVIATIONS: AUC ϭ area under receiver operating characteristic curve; HNSCC ϭ head and neck squamous cell carcinoma; GLCM ϭ gray-level co-occurrence matrix; GLGM ϭ gray-level gradient matrix; GLN ϭ gray-level nonuniformity; GLRL ϭ gray-level run-length; HGRE ϭ high gray-level run emphasis; LGRE ϭ low gray-level run emphasis; LRE ϭ long-run emphasis; LRHGE ϭ long-run high gray-level emphasis; max ϭ maximum; RLN ϭ run-length nonuniformity; RP ϭ run percentage; SRE ϭ short-run emphasis; SRLGE ϭ short-run low gray-level emphasis; SUV ϭ standard uptake value

Dual-Energy CT Texture Analysis With Machine Learning for the Evaluation and Characterization of Cervical Lymphadenopathy

“…So far, there have been few investigations performing texture or radiomic analysis of lymph nodes, especially in the neck. In a recent study performed on [18F]-FDG-PET scans that included a contrast-enhanced CT, it was reported that there are statistically significant differences between texture features of benign HIV-related lymphadenopathy compared to metastatic HNSCC nodes [48]. Another recent study reported that texture features of the primary HNSCC tumor may be useful for predicting associated cervical lymphadenopathy [49].…”

Role of textural analysis parameters derived from FDG PET/CT in differentiating hepatocellular carcinoma and hepatic metastases

“…Bianconi et al found that significant associations emerged between PET features, CT features, and histological type in Non small cell lung cancer (NSCLC) [20]. Kuno et al found that CT texture analysis may be a noninvasive method of obtaining additional quantitative information to differentiate nodal metastases from disease-specific nodal reactivity in HIV-positive patients with head and neck squamous cell carcinoma [21]. According to Li et al The newly developed 18F-FDG PET/CT radiomics signature was an independent biomarker for the estimation of micro-vascular invasion (MVI) and Disease Free Survival (DFS) in patients with very-early and early-stage HCC [22].…”

Radiological differences in computed tomography findings and texture analysis between cystic lymph node metastases of human papillomavirus-positive oropharyngeal cancer and second branchial cysts

“…It is a method in which the shading of pixels in the region of interest is numerically measured, and parameters of "non-uniformity" such as uniformity, directionality, and contrast change are calculated. In recent years, texture analysis has been studied to predict outcomes and survival of patients with head and neck cancer, colorectal cancer, lung cancer, oesophageal cancer, and glioblastoma [10][11][12][13][14] as well as to differentiate between benign and malignant maxillary sinus masses, cervical lymph nodes, lung nodules, liver masses, adrenal nodules, and renal masses [15][16][17][18][19][20]. In the current study, there were significant differences in 8 of the 40 texture parameters between CNM-HPV-OPC and 2 nd BC.…”