Quantification of perfusion and metabolism in an autism mouse model assessed by diffuse correlation spectroscopy and near-infrared spectroscopy.

There is a need for quantitative biomarkers for early diagnosis of autism. Cerebral blood flow and oxidative metabolism parameters may show superior contrasts for improved characterization. Diffuse correlation spectroscopy (DCS) has been shown to be reliable method to obtain cerebral blood flow contrast in animals and humans. Thus, in this study, we evaluated the combination of DCS and fNIRS in an established autism mouse model. Our results indicate that autistic group had significantly (P = .001) lower (~40%) blood flow (1.16 ± 0.26) × 10  cm /s), and significantly (P = .015) lower (~70%) oxidative metabolism (52.4 ± 16.6 μmol/100 g/min) compared to control group ([1.93 ± 0.74] × 10  cm /s, 177.2 ± 45.8 μmol/100 g/min, respectively). These results suggest that the combination of DCS and fNIRS can provide hemodynamic and metabolic contrasts for in vivo assessment of autism pathological conditions noninvasively.