Brain iron homeostasis is disrupted in neurodegeneration and areas of iron overload partially overlap with regions of amyloid and tau burden in Alzheimer’s disease (AD). Previous studies demonstrated alterations in brain iron accumulation in AD using quantitative susceptibility mapping (QSM).
Objective:
Here, we investigate brain alterations of QSM values in AD and non-AD patients as compared to healthy controls (HC) in the superior temporal sulcus and its banks (BANKSSTS), one of the top AD-affected regions.
Methods:
Thirty-four patients who underwent brain MRI including a multi-echo gradient-echo sequence were subdivided into AD (n = 19) and non-AD (n = 15) groups according to their clinical profile, CSF (Aβ42/40) and/or amyloid-PET status. Ten HC were also included. QSM values were extracted from left and right BANKSSTS and compared among groups. Correlation and binomial regression analyses between QSM values and CSF-AD biomarkers were conducted.
Results:
QSM in left BANKSSTS was significantly different among groups (p = 0.003, H = 11.40), being higher in AD. QSM values in left BANKSSTS were correlated with Aβ42 (rho –0.55, p = 0.005), Aβ42/40 (rho –0.66, p < 0.001), pTau (rho 0.63, p < 0.001), tTau (rho 0.56, p = 0.005), tTau/Aβ42 (rho 0.68, p < 0.001) and pTau/Aβ42 (rho 0.71, p < 0.001). No correlations between QSM values and amyloid-PET SUVR in the left BANKSSTS were found. QSM values in left BANKSSTS showed good accuracy in discriminating AD (AUC = 0.80, CI95 % [0.66–0.93]). Higher QSM values were independent predictors of Aβ42 (B = 0.63, p = 0.032), Aβ42/40 (B = 0.81, p = 0.028), pTau (B = 0.96, p = 0.046), tTau (B = 0.55, p = 0.027), and tTau/Aβ42 (B = 1.13, p = 0.042) positivity.
Conclusion:
Our preliminary data support the potential role of increased QSM values in the left BANKSSTS as an auxiliary imaging biomarker in AD diagnosis.
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