Prognostic Assessment in Patients With Primary Diffuse Large B-Cell Lymphoma of the Central Nervous System Using MRI-Based Radiomics

Jianpeng Liu, Jiaqi Tu, Bin Hu, Chao Li, Sirong Piao, Yucheng Lu, Anning Li, Tianling Ding, Ji Xiong, Fengping Zhu (Lead / Corresponding author), Yuxin Li (Lead / Corresponding author)

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Background
Primary central nervous system lymphoma (PCNSL) carries a poor prognosis. Radiomics may hold potential value in prognostic assessment.

Purpose
To develop and validate an MRI-based radiomics model and combine it with clinical factors to assess progression-free survival (PFS) and overall survival (OS) of patients with PCNSL.

Study Type
Retrospective and prospective.

Population
Three hundred seventy-nine patients (179 female, 53 ± 7 years) from 2014 to 2022.

Field Strength/Sequence
T2/fluid-attenuated inversion recovery, contrast-enhanced T1WI and diffusion-weighted echo-planar imaging sequences on 3.0 T.

Assessment
Radiomics features were extracted from enhanced tumor regions on preoperative multi-sequence MRI. Using a least absolute shrinkage and selection operator (LASSO) Cox regression model to select radiomic signatures in training cohort (N = 169). Cox proportional hazards models were constructed for clinical, radiomics, and combined models, with internal (N = 72) and external (N = 32) cohorts validating model performance.

Statistical Tests
Chi-squared, Mann–Whitney, Kaplan–Meier, log-rank, LASSO, Cox, decision curve analysis, time-dependent Receiver Operating Characteristic, area under the curve (AUC), and likelihood ratio test. P-value <0.05 was considered significant.

Results
Follow-up duration was 28.79 ± 22.59 months (median: 25). High-risk patients, determined by the median radiomics score, showed significantly lower survival rates than low-risk patients. Compared with NCCN-IPI, conventional imaging and clinical models, the combined model achieved the highest C-index for both PFS (0.660 internal, 0.802 external) and OS (0.733 internal, 0.781 external) in validation. Net benefit was greater with radiomics than with clinical alone. The combined model exhibited performance with AUCs of 0.680, 0.752, and 0.830 for predicting 1-year, 3-year, and 5-year PFS, and 0.770, 0.789, and 0.863 for OS in internal validation, with PFS AUCs of 0.860 and 0.826 and OS AUCs of 0.859 and 0.748 for 1-year and 3-year survival in external validation.

Data Conclusion
Incorporating a multi-sequence MR-based radiomics model into clinical models enhances the assess accuracy for the prognosis of PCNSL.

Evidence Level
4

Technical Efficacy
Stage 2
Original languageEnglish
Pages (from-to)1142-1152
Number of pages11
JournalJournal of Magnetic Resonance Imaging
Volume61
Issue number3
Early online date6 Jul 2024
DOIs
Publication statusPublished - 7 Feb 2025

Keywords

  • magnetic resonance imaging
  • primary central nervous system lymphoma
  • prognosis
  • radiomics

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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