Model-free parameters of IVIM combined with tumor aggressiveness indicators in predicting 5-year treatment outcome in NPC

Motivation: The postprocessing of IVIM is relatively laborious within multiple b-value settings. Streamlining the b-value configuration and postprocessing may promote its widespread use while ensuring the clinical efficacy. Goal(s): To assess the value of model-free parameters (virtual magnetic resonance elastography [vMRE] and signature-index [S-index]) of IVIM and tumor aggressiveness indicators (tumor growth type [TGT] and contralateral pharyngeal recess invasion [CPRI]) in predicting 5-year treatment outcome. Approach: Prospective inclusion of 106 patients with regular follow-up. Selection of appropriate statistical methods to construct models. Results: vMRE and S-index were the independent predictors of long-term survival. Combined with TGT and CPRI can further improved the predictive performance. Impact: Two model-free parameters simplified the clinical process without compromising the efficacy. vMRE/S-index and TGT/CPRI shown for the first time to predict long-term survival in NPC, helping with clinical treatment decisions.

Authors

Publication Details

Journal
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Published
2025-09-16
DOI
https://doi.org/10.58530/2025/1906
Primary Topic
Electromagnetic Simulation and Numerical Methods
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Model-free parameters of IVIM combined with tumor aggressiveness indicators in predicting 5-year treatment outcome in NPC

Haoran Wei, Lizhi Xie, Hongmei Zhang, Meng Lin et al.
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Electromagnetic Simulation and Numerical Methods
article

Model-free parameters of IVIM combined with tumor aggressiveness indicators in predicting 5-year treatment outcome in NPC

Haoran Wei, Lizhi Xie, Hongmei Zhang, Meng Lin, Xiaoduo Yu, Fan Yang
article en

Abstract

Motivation: The postprocessing of IVIM is relatively laborious within multiple b-value settings. Streamlining the b-value configuration and postprocessing may promote its widespread use while ensuring the clinical efficacy. Goal(s): To assess the value of model-free parameters (virtual magnetic resonance elastography [vMRE] and signature-index [S-index]) of IVIM and tumor aggressiveness indicators (tumor growth type [TGT] and contralateral pharyngeal recess invasion [CPRI]) in predicting 5-year treatment outcome. Approach: Prospective inclusion of 106 patients with regular follow-up. Selection of appropriate statistical methods to construct models. Results: vMRE and S-index were the independent predictors of long-term survival. Combined with TGT and CPRI can further improved the predictive performance. Impact: Two model-free parameters simplified the clinical process without compromising the efficacy. vMRE/S-index and TGT/CPRI shown for the first time to predict long-term survival in NPC, helping with clinical treatment decisions.

Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Openalex Percentile: Top 76%
Electromagnetic Simulation and Numerical Methods
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.