BMC Cancer (Jan 2023)

Risk stratification and prognostic value of multi-modal MRI-based radiomics for extranodal nasal-type NK/T-cell lymphoma

  • Yu-Ting Zhao,
  • Si-Ye Chen,
  • Xin Liu,
  • Yong Yang,
  • Bo Chen,
  • Yong-Wen Song,
  • Hui Fang,
  • Jing Jin,
  • Yue-Ping Liu,
  • Hao Jing,
  • Yuan Tang,
  • Ning Li,
  • Ning-Ning Lu,
  • Shu-Lian Wang,
  • Han Ouyang,
  • Chen Hu,
  • Jin Liu,
  • Zhi Wang,
  • Fan Chen,
  • Lin Yin,
  • Qiu-Zi Zhong,
  • Kuo Men,
  • Jian-Rong Dai,
  • Shu-Nan Qi,
  • Ye-Xiong Li

DOI
https://doi.org/10.1186/s12885-023-10557-3
Journal volume & issue
Vol. 23, no. 1
pp. 1 – 11

Abstract

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Abstract Background Magnetic resonance imaging (MRI) performs well in the locoregional assessment of extranodal nasal-type NK/T-cell lymphoma (ENKTCL). It’s important to assess the value of multi-modal MRI-based radiomics for estimating overall survival (OS) in patients with ENKTCL. Methods Patients with ENKTCL in a prospectively cohort were systemically reviewed and all the pretreatment MRI were acquisitioned. An unsupervised spectral clustering method was used to identify risk groups of patients and radiomic features. A nomogram-revised risk index (NRI) plus MRI radiomics signature (NRI-M) was developed, and compared with the NRI. Results The 2 distinct type I and II groups of the MRI radiomics signatures were identified. The 5-year OS rates between the type I and type II groups were 87.2% versus 67.3% (P = 0.002) in all patients, and 88.8% versus 69.2% (P = 0.003) in early-stage patients. The discrimination and calibration of the NRI-M for OS prediction demonstrated a better performance than that of either MRI radiomics or NRI, with a mean area under curve (AUC) of 0.748 and 0.717 for predicting the 5-year OS in all-stages and early-stage patients. Conclusions The NRI-M model has good performance for predicting the prognosis of ENKTCL and may help design clinical trials and improve clinical decision making.

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