Effects of tracer arrival time on flow estimates in MR perfusion-weighted imaging

Area of Science:

• Medical Imaging
• Neuroscience
• Biophysics

Background:

• Perfusion-weighted MRI (PWI) with deconvolution using singular value decomposition (SVD) is a standard method for calculating cerebral blood flow (CBF) and mean transit time (MTT).
• Existing PWI methods can overestimate infarct volume and produce flow maps inconsistent with clinical findings, particularly in severe vasculopathy.
• The accuracy of CBF and MTT estimates is sensitive to the arterial input function (AIF) used in the deconvolution process.

Purpose of the Study:

• To investigate the impact of temporal discrepancies between the AIF and tissue signals on CBF and MTT calculations.
• To evaluate how variations in tracer arrival times affect quantitative perfusion parameters derived from PWI data.
• To identify potential sources of error in PWI-based flow estimation related to AIF selection.

Main Methods:

• Calculated CBF and MTT using simulated and real PWI data.
• Introduced controlled time shifts between the user-selected global AIF and tissue concentration signals.
• Analyzed the effects of AIF leading and lagging the tissue signal on flow estimates.

Main Results:

• When the AIF precedes the tissue signal, CBF is consistently underestimated, with dependence on MTT.
• When the AIF lags the tissue signal, CBF can be over- or underestimated, influenced by MTT and the magnitude of the time delay.
• These timing differences, arising from non-ideal AIF selection, directly impact the reliability of calculated CBF and MTT.

Conclusions:

• Temporal alignment between the AIF and tissue signals is critical for accurate PWI-derived CBF and MTT quantification.
• User-selected global AIFs may not perfectly represent the true AIF, leading to significant estimation errors.
• Caution is advised when interpreting CBF and MTT values, especially in the presence of potential timing mismatches in PWI data.