Magma (New York, N.Y.) · 2026
Impact of different pre-processing methods combined with combat harmonization on the reproducibility of radiomics features in healthy human brain MRI.
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Chen Lihua, Zheng Bowen, Zeng Weixiong, Lv Yijun, Zhong Haijian, Qin Genggeng
Аннотация
OBJECTIVE: To explore the effect of different pre-processing methods combined with ComBat harmonization on improving the stability of MRI radiomic features in healthy human brains.
METHODS: T1FLAIR and T2W scans from 416 healthy subjects across four MRI systems underwent seven pipelines (Original, N4, Z-Score, DTN, Nyul, WhiteStripe, RAVEL). SynthSeg segmented white/gray matter for 93 IBSI radiomic features. Stability was quantified via covariate-adjusted standardized scanner effect (d = β_scanner/σ_res, |d|< 0.2) with 95% bootstrap CIs, supplemented by PCA and LOOCV AUC. Friedman and post-hoc McNemar tests with Bonferroni correction compared pipelines. FDR-corrected partial correlations assessed retention of significant age and sex associations after ComBat.
RESULTS: Raw data exhibited extremely low stability with substantial scanner-induced effects, while scanner classification AUC was close to 1.0. ComBat harmonization significantly improved stability across all pipelines and reduced AUC to near 0.5. Within this dataset, DTN_ComBat demonstrated consistently high stability; pairwise statistical comparisons indicated it showed more favourable stability performance relative to most other pipelines for the majority of tested contrasts, with stable proportions exceeding 90% across all sequences and tissues, and retained 75.0-100.0% of statistically significant age and sex-related associations.
CONCLUSION: Unprocessed brain MRI radiomic features exhibit poor cross‑scanner stability. Within this dataset, ComBat effectively reduces scanner‑related feature‑distribution differences, while preserving most statistically‑significant age and sex‑related associations. Among tested pre-processing pipelines, DTN_ComBat showed comparatively favourable performance under the present healthy‑brain MRI scanner‑protocol configurations.
METHODS: T1FLAIR and T2W scans from 416 healthy subjects across four MRI systems underwent seven pipelines (Original, N4, Z-Score, DTN, Nyul, WhiteStripe, RAVEL). SynthSeg segmented white/gray matter for 93 IBSI radiomic features. Stability was quantified via covariate-adjusted standardized scanner effect (d = β_scanner/σ_res, |d|< 0.2) with 95% bootstrap CIs, supplemented by PCA and LOOCV AUC. Friedman and post-hoc McNemar tests with Bonferroni correction compared pipelines. FDR-corrected partial correlations assessed retention of significant age and sex associations after ComBat.
RESULTS: Raw data exhibited extremely low stability with substantial scanner-induced effects, while scanner classification AUC was close to 1.0. ComBat harmonization significantly improved stability across all pipelines and reduced AUC to near 0.5. Within this dataset, DTN_ComBat demonstrated consistently high stability; pairwise statistical comparisons indicated it showed more favourable stability performance relative to most other pipelines for the majority of tested contrasts, with stable proportions exceeding 90% across all sequences and tissues, and retained 75.0-100.0% of statistically significant age and sex-related associations.
CONCLUSION: Unprocessed brain MRI radiomic features exhibit poor cross‑scanner stability. Within this dataset, ComBat effectively reduces scanner‑related feature‑distribution differences, while preserving most statistically‑significant age and sex‑related associations. Among tested pre-processing pipelines, DTN_ComBat showed comparatively favourable performance under the present healthy‑brain MRI scanner‑protocol configurations.