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Value of Dynamic Contrast-Enhanced MRI to Detect Local Tumor Recurrence in Primary Head and Neck Cancer Patients

Treatment failures in head and neck cancer patients are mainly related to locoregional tumor recurrence. The objective of the present study was to evaluate the diagnostic accuracy of model-free dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to detect local recurrence during the surve...

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Detalles Bibliográficos
Autores principales: Choi, Young Jun, Lee, Jeong Hyun, Sung, Yu Sub, Yoon, Ra Gyoung, Park, Ji Eun, Nam, Soon Yuhl, Baek, Jung Hwan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer Health 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4902554/
https://www.ncbi.nlm.nih.gov/pubmed/27175712
http://dx.doi.org/10.1097/MD.0000000000003698
Descripción
Sumario:Treatment failures in head and neck cancer patients are mainly related to locoregional tumor recurrence. The objective of the present study was to evaluate the diagnostic accuracy of model-free dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to detect local recurrence during the surveillance of head and neck cancer patients. Our retrospective study enrolled 24 patients with primary head and neck cancer who had undergone definitive treatment. Patients were grouped into local recurrence (n = 12) or posttreatment change (n = 12) groups according to the results of biopsy or clinicoradiologic follow-up. The types of time-signal intensity (TSI) curves were classified as follows: “progressive increment” as type I, “plateau” as type II, and “washout” as type III. TSI curve types and their parameters (i.e., wash-in, E(max), T(max), area under the curve [AUC]60, AUC90, and AUC120) were compared between the 2 study groups. The distributions of TSI curve types for local recurrence versus posttreatment change were statistically significant (P < 0.001) (i.e., 0% vs 83.3% for type I, 58.3% vs 16.7% for type II, and 41.7% vs 0% for type III). There were statistically significant differences in E(max), T(max), and all of the AUC parameters between 2 groups (P < 0.0083 [0.05/6]). Receiver operating characteristic (ROC) curve analyses indicated that the TSI curve type was the best predictor of local recurrence with a sensitivity of 100% (95% CI, 73.5–100.0) and a specificity of 83.3% (95% CI, 51.6–97.9) (cutoff with type II). Model-free DCE-MRI using TSI curves and TSI curve-derived parameters detects local recurrence in head and neck cancer patients with a high diagnostic accuracy.