Title

Quantitative lung perfusion blood volume (PBV) using dual energy CT (DECT)-based effective atomic number (Zeff) imaging

Document Type

Article

Publication Date

9-14-2021

Publication Title

Medical physics

Abstract

BACKGROUND: Iodine material images (aka iodine basis images) generated from dual energy CT (DECT) have been used to assess potential perfusion defects in the pulmonary parenchyma. However, iodine material images do not provide the needed absolute quantification of the pulmonary blood pool, as materials with effective atomic numbers (Z(eff) ) different from those of basis materials may also contribute to iodine material images, thus confounding the quantification of perfusion defects.

PURPOSE: The purposes of this work were to (i) demonstrate the limitations of iodine material images in pulmonary perfusion defect quantification and (ii) develop and validate a new quantitative biomarker using effective atomic numbers derived from DECT images.

METHODS: The quantitative relationship between the perfusion blood volume (PBV) in pulmonary parenchyma and the effective atomic number (Z(eff) ) spatial distribution was studied to show that the desired quantitative PBV maps are determined by the spatial maps of Z(eff) as PBV(Zeff) (x) = a Z(eff) (β) (x) + b, where a, b, and β are three constants. Namely, quantitative PBV(Zeff) is determined by Z(eff) images instead of the iodine basis images. Perfusion maps were generated for four human subjects to demonstrate the differences between conventional iodine material image-based PBV (PBV(iodine) ) derived from two-material decompositions and the proposed PBV(Zeff) method.

RESULTS: Among patients with pulmonary emboli, the proposed PBV(Zeff) maps clearly show the perfusion defects while the PBV(iodine) maps do not. Additionally, when there are no perfusion defects present in the derived PBV maps, no pulmonary emboli were diagnosed by an experienced thoracic radiologist.

CONCLUSION: Effective atomic number based quantitative PBV maps provide the needed sensitive and specific biomarker to quantify pulmonary perfusion defects.

PubMed ID

34520066

ePublication

ePub ahead of print

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