Validation of kinetic modeling of [15O]H2O PET using an image derived input function on hybrid PET/MRI

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In present study we aimed to validate the use of image-derived input functions (IDIF) in the kinetic modeling of cerebral blood flow (CBF) measured by [15O]H2O PET by comparing with the accepted reference standard arterial input function (AIF). Additional comparisons were made to mean cohort AIF and CBF values acquired by methodologically independent phase-contrast mapping (PCM) MRI. Using hybrid PET/MRI an IDIF was generated by measuring the radiotracer concentration in the internal carotid arteries and correcting for partial volume effects using the intravascular volume measured from MRI-angiograms. Seven patients with carotid steno-occlusive disease and twelve healthy controls were examined at rest, after administration of acetazolamide, and, in the control group, during hyperventilation. Agreement between the techniques was examined by linear regression and Bland-Altman analysis. Global CBF values modeled using IDIF correlated with values from AIF across perfusion states in both patients (p<10−6, R2=0.82, 95% limits of agreement (LoA)=[-11.3–9.9] ml/100 g/min) and controls (p<10−6, R2=0.87, 95% LoA=[-17.1–13.7] ml/100 g/min). The reproducibility of gCBF using IDIF was identical to AIF (15.8%). Values from IDIF and AIF had equally good correlation to measurements by PCM MRI, R2=0.86 and R2=0.84, (p<10−6), respectively. Mean cohort AIF performed substantially worse than individual IDIFs (p<10−6, R2=0.63, LoA=[-12.8–25.3] ml/100 g/min). In the patient group, use of IDIF provided similar reactivity maps compared to AIF. In conclusion, global CBF values modeled using IDIF correlated with values modeled by AIF and similar perfusion deficits could be established in a patient group.

OriginalsprogEngelsk
Artikelnummer117950
TidsskriftNeuroImage
Vol/bind233
Antal sider14
ISSN1053-8119
DOI
StatusUdgivet - 2021

Bibliografisk note

Funding Information:
Mark B. Vestergaard supported by grant from Danish Council for Independent Research ( 8020-00251B ) and Rigshospitalets Forskningspulje . Oriol P. Calvo is supported by a training grant from the Fundación Alfonso Martín Escudero .

Publisher Copyright:
© 2021

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