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Background <p>Computed tomography perfusion (CTP)-derived cerebral blood flow (CBF) maps are widely used to study infarct volume and growth. Multi-site CTPs often have site biases that can alter thresholds and increase errors. However, the clinical impact of inter-site variability on infarct quantification is unclear. We examined this variability and developed an automated harmonization pipeline for multi-site CTP datasets to mitigate infarct assessment errors.</p> Methods <p>We analyzed 741 CTP cases from the Alteplase compared to Tenecteplase trial across eight sites. CBFs were registered and segmented into grey-matter/white-matter (GM/WM). We scaled mean GM/WM CBFs into physiological ranges and applied ComBat, an empirical Bayesian method, to reduce inter-site bias. We assessed clinical utility by comparing infarct-core volumes from original versus harmonized maps with a&#xa0;relative-CBF-based reference, and comparing large-core infarct identification using CBF-based volume thresholds.</p> Results <p>The original mean CBF deviated from physiological range with high variance and significant inter-site differences. After applying the scaling factor, the mean CBF (GM/WM) shifted to physiological ranges (49.3 ± 6.0/23.5 ± 2.5 ml/100g/min), and ComBat effectively eliminated inter-site differences. In 199 cases with complete reference data for clinical evaluation, harmonization decreased mean absolute error for infarct volume by 39% (12.7 to 7.7 ml), improved agreement (bias −7.9 to −5.8 ml; narrower 95%CI), and increased accuracy of large-core classification at a&#xa0;60 ml-threshold by 5.0% (net reclassification improvement:0.310, 95%CI:0.036–0.603).</p> Conclusion <p>Our harmonization pipeline rescaled multi-site CBF maps to physiological range, reducing inter-site variability and errors in infarct core estimation and large-core classification. Multi-site harmonization should become standard in CTP datasets to avoid erroneous conclusions about infarct size and growth.</p>

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Development and Validation of a Harmonization Pipeline for Multi-Site Computed Tomography Perfusion Cerebral Blood Flow Maps—An Analysis of the AcT Trial

  • 期刊论文

  • 发表日期：

    2026年2月12日

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  • Pattarawut Charatpangoon,
  • Jianhai Zhang,
  • Nishita Singh,
  • Abdoljalil Addeh,
  • Mohammed A. Almekhlafi,
  • Brian H. Buck,
  • Luciana Catanese,
  • Tolulope Sajobi,
  • Richard H. Swartz,
  • Aleksander Tkach,
  • Bijoy K. Menon,
  • M. Ethan MacDonald,
  • Aravind Ganesh

摘要

Background

Computed tomography perfusion (CTP)-derived cerebral blood flow (CBF) maps are widely used to study infarct volume and growth. Multi-site CTPs often have site biases that can alter thresholds and increase errors. However, the clinical impact of inter-site variability on infarct quantification is unclear. We examined this variability and developed an automated harmonization pipeline for multi-site CTP datasets to mitigate infarct assessment errors.

Methods

We analyzed 741 CTP cases from the Alteplase compared to Tenecteplase trial across eight sites. CBFs were registered and segmented into grey-matter/white-matter (GM/WM). We scaled mean GM/WM CBFs into physiological ranges and applied ComBat, an empirical Bayesian method, to reduce inter-site bias. We assessed clinical utility by comparing infarct-core volumes from original versus harmonized maps with a relative-CBF-based reference, and comparing large-core infarct identification using CBF-based volume thresholds.

Results

The original mean CBF deviated from physiological range with high variance and significant inter-site differences. After applying the scaling factor, the mean CBF (GM/WM) shifted to physiological ranges (49.3 ± 6.0/23.5 ± 2.5 ml/100g/min), and ComBat effectively eliminated inter-site differences. In 199 cases with complete reference data for clinical evaluation, harmonization decreased mean absolute error for infarct volume by 39% (12.7 to 7.7 ml), improved agreement (bias −7.9 to −5.8 ml; narrower 95%CI), and increased accuracy of large-core classification at a 60 ml-threshold by 5.0% (net reclassification improvement:0.310, 95%CI:0.036–0.603).

Conclusion

Our harmonization pipeline rescaled multi-site CBF maps to physiological range, reducing inter-site variability and errors in infarct core estimation and large-core classification. Multi-site harmonization should become standard in CTP datasets to avoid erroneous conclusions about infarct size and growth.