Influence of Different Measurement Methods of Arterial Input Function on Quantitative Dynamic Contrast‐Enhanced MRI Parameters in Head and Neck Cancer

Abstract

Background: Head and neck cancer (HNC) is the sixth most prevalent cancer worldwide. DCE-MRI helps in diagnosis and prognosis. Quantitative DCE-MRI requires an arterial input function (AIF), which affects the values of pharmacokinetic parameters (PKP).

Quantitative dynamic contrast-enhanced magnetic resonance imaging in head and neck cancer: A systematic comparison of different modelling approaches

“…Since the variability of K trans TM and v e, TM obtained with different population AIFs was low (ICCs ≥ 0.83), the population AIF and resulting TM parameters were not affected by alignment method and removal of baseline. Other AIF calculation steps, such as artery segmentation method [29] , [30] and AIF scaling [31] , are more important and need to be standardised. Contrary to our results, Onxley et al [16] and Shuckla-Dave et al [17] found that TM parameters calculated with population and individual AIF did not differ for HNC, but their results were from small patient cohorts.…”

Editorial for “Influence of Different Measurement Methods of Arterial Input Function on Quantitative Dynamic Contrast‐Enhanced MRI Parameters in Head and Neck Cancer”

“…The automatic AIF implemented in commercial software selects 50 voxels from the entire imaged volume and averages these values to generate the automatic AIF. Dong et al emphasized the importance of selecting AIF from the center of the large vessels to avoid partial volume effects 9 . In addition, they measured the ratio between tumor and muscle, found fewer variations between the manual and automatic AIFs, and concluded that some type of normalization, such as tumor to muscle, might be potential mitigation to address the variabilities of tumor Ktrans.…”

“…In this issue of JMRI, an article by Dong et al addressed the exact problem. 9 They prospectively evaluated the influence of manual vs. automatic AIF measurement methods with and without motion correction on quantitative DCE-MRI parameters in 34 patients with head and neck cancers. They found that the peak contrast concentration value was up to 70% higher with the manual method than with automatic AIF.…”