What does this research mean for the field?

Non-contrast CT-derived perfusion estimates (CT:VQ) are highly correlated with dual-energy CT iodine perfusion maps at the lobar level, validating CT:VQ as an accurate method for assessing pulmonary perfusion without intravenous contrast. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

This analysis aims to validate a new non-contrast CT index of pulmonary perfusion against dual-energy CT maps.

May 20, 2026

C108-19 Quantitative Comparison of Pulmonary Perfusion From Paired Non-contrast CT (CT:VQ) and Dual-Energy CT Iodine Maps: A SPIROMICS Analysis

Key Points

This analysis aims to validate a new non-contrast CT index of pulmonary perfusion against dual-energy CT maps.
Included SPIROMICS participants with paired inspiratory and expiratory chest CT scans and DECT scans.
Performed standard imaging protocol and used Pearson coefficients for correlation analysis across lobes.
Analyzed 61 subjects, calculating relative pulmonary blood volume using both imaging modalities.
DECT-derived perfusion showed strong correlation with CT:VQ perfusion (Pearson r = 0.921, p < 0.001).
Significant correlation between CT:VQ perfusion signal and obstruction (FEV1/FVC), with r-squared = 0.229, p < 0.001.
Findings support physiological validity of CT:VQ for assessing pulmonary perfusion without intravenous contrast.

Abstract

Abstract Rationale Dual-energy CT (DECT) enables generation of iodine perfusion maps that reflect regional pulmonary blood volume (PBV) at the voxel level. Recent advances in a non-contrast CT derived index (CT:VQ) of regional pulmonary perfusion (4DMedical, Melbourne, AUS) allows for quantification of regional ventilation and perfusion from paired inspiratory and expiratory CT scans. However, cross-validation between a DECT-derived index of PBV and CT:VQ perfusion in the same subjects has not been previously demonstrated. Methods This analysis included SPIROMICS participants who underwent (1) paired inspiratory and expiratory chest CT scans following a standardized imaging protocol, and (2) an additional contrast-enhanced chest DECT scan acquired at functional residual capacity using a quantitative (Univ of Iowa) GE Discovery 750HD dual-energy PBV protocol. DECT and non-contrast HRCT paired scans were acquired at separate visits. Iodine maps were reconstructed and registered to each subject’s expiratory non-contrast image. Lung lobes were automatically segmented using the CT:VQ. For each lobe, relative PBV and CT:VQ was calculated as the lobe’s perfusion index divided by the respective total lung perfusion index. Correlations were computed across all lobes for each subject using Pearson coefficients. Results The comparison was conducted across a cohort of N = 61 subjects (41.0% female, mean age 63.689), of which 45.9% had COPD (mean GOLD score 1.429). Across all subjects and lobes, DECT-derived perfusion showed a strong and significant correlation with CT:VQ perfusion (Pearson r = 0.921, 0.805, p 0.001 ; see Figure 1c). The strong correlation suggests that both modalities capture similar relative perfusion gradients despite different underlying physics (contrast enhancement vs. dynamic parenchymal density change). The coefficient of variation of the CT:VQ perfusion signal also demonstrated a relationship with obstruction, FEV1/FVC (Pearson r-squared = 0.229, p 0.001). Conclusions Dual-energy CT iodine perfusion maps and CT:VQ perfusion estimates are highly correlated at the lobar level. This finding supports the physiological validity of CT:VQ for assessing pulmonary perfusion without the need for intravenous contrast. Further work will compare voxel-wise distributions and evaluate potential systematic biases across lung regions and disease phenotypes. This abstract is funded by: SPIROMICS was supported by contracts from the NIH/NHLBI (HHSN268200900013C, HHSN268200900014C, HHSN268200900015C, HHSN268200900016C, HHSN268200900017C, HHSN268200900018C, HHSN268200900019C, HHSN268200900020C, 75N92024D00012), grants from the NIH/NHLBI (U01HL137880, U24HL141762, R01HL182622, R01HL144718, and R01HL093081), and supplemented by contributions made through the Foundation for the NIH and the COPD Foundation from Amgen; AstraZeneca/MedImmune; Bayer; Bellerophon Therapeutics; Boehringer-Ingelheim Pharmaceuticals, Inc.; Bristol Myers Squibb; Chiesi Farmaceutici S.p.A.; Forest Research Institute, Inc.; Genentech; GlaxoSmithKline; Grifols Therapeutics, Inc.; Ikaria, Inc.; MGC Diagnostics; Novartis Pharmaceuticals Corporation; Nycomed GmbH; Polarean; ProterixBio; Regeneron Pharmaceuticals, Inc.; Sanofi; Sunovion; Takeda Pharmaceutical Company; Theravance Biopharma; Verona; and Mylan/Viatris.

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