## Resumen

Purpose: To evaluate the potential contribution of quantitative DWI parameters including ADC _{mean} and ADC _{ratio} values to help in distinguishing the histopathological types of sinonasal neoplasms. Methods: This retrospective study included 83 patients (50 males, 33 females; mean age 61 years) with pathologically proven untreated sinonasal neoplasms who have undergone diffusion-weighted MRI imaging from February 2010 to August 2017. Diffusion-weighted MRI was performed on a 3 T unit with b factors of 0 and 1000 s/mm ^{2} , and ADC maps were generated. Mean ADC values of sinonasal tumors and ADC ratios (ADC _{mean} of the tumor to ADC _{mean} of pterygoid muscles) were compared with the histopathological diagnosis by utilizing the Kruskal-Wallis non-parametric test. Results: Mean ADC _{mean} and ADC _{ratio} were 0.8 (SD, ±0.4) × (10 ^{−3} mm ^{2} /s) and 1.2 (SD, ±0.5), respectively, and each parameter was significantly different between histopathological types (p < 0.05). Mean ADC _{mean} and ADC _{ratio} were higher in adenoid cystic carcinoma (ACC) than in SCC, lymphoma, neuroendocrine carcinoma and sinonasal undifferentiated carcinoma (SNUC) (p < 0.05). Optimized ADC _{mean} thresholds of 0.79, 0.81, 0.74 and 0.78 (10 ^{−3} mm ^{2} /s) achieved maximal discriminatory accuracies of 100%, 79%, 100% and 89% for ACC/SNUC, ACC/SCC, ACC/neuroendocrine carcinoma, and ACC/lymphoma, respectively. Conclusions: The optimized ADC _{mean} threshold of 0.80 (10 ^{−3} mm ^{2} /s) could be used to differentiate ACC from non-ACC sinonasal neoplasms with maximal discriminatory accuracy (82%) and sensitivity of 100%. However, there is considerable overlapping of the ADC _{mean} and ADC _{ratio} values among non-ACC sinonasal neoplasms hence surgical biopsy is still needed.

Idioma original | English (US) |
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Páginas (desde-hasta) | 76-82 |

Número de páginas | 7 |

Publicación | Clinical Imaging |

Volumen | 55 |

DOI | |

Estado | Published - may 1 2019 |

Publicado de forma externa | Sí |

## ASJC Scopus subject areas

- Radiology Nuclear Medicine and imaging