Reliable blood flow measurements in the neonatal brain are difficult to obtain with conventional Power Doppler (PD) due to small vessel size, slow flow, and strong reverberation from the cranium. Under such imaging conditions, it is important to use long ensemble lengths and to reduce the acoustic noise in order to separate the slow-flow signal from the stationary-tissue clutter. We have recently developed the short-lag angular coherence (SLAC) beamforming method to reduce noise in the Doppler data, and used it to track blood-flow changes in the brains of neonates. SLAC suppresses the incoherent portion of the beam-summed signals and utilizes Fourier beamforming for fast processing of large Doppler ensembles. To remove stationary tissue signal from the data, we have also utilized spatiotemporal filtering prior to the SLAC processing step. The matching frames of SLAC-based PD and conventional PD were reconstructed from the same Doppler data captured on the neonatal brain vasculature over 4 cm depth. To achieve a fair comparison, the Doppler signal of each modality was normalized by its respective noise profile measured as a function of depth from a stationary speckle phantom. The SLAC images showed better delineation of small vessels, and the vessel SNR was measured to be up to 2 dB higher in SLAC images than in matching PD images. To demonstrate the quantitative aspect of SLAC-based PD, we have also created matched conventional PD and SLAC-based PD videos from the ten-second Doppler scans of neonatal brains. For the vasculature of interest, integrated pixel intensity was computed as a function of time. SLAC-based PD was able to capture changes in the cortical flow, and it closely followed the corresponding conventional PD signal for the duration of the acquisition. No external stimuli were applied during the scans. Normalized cross-correlation between the two signals was 0.991.
Improved techniques for breast cancer screening are critically needed as current methods lack diagnostic accuracy. Using spectroscopic photoacoustic (sPA) molecular imaging with a priori knowledge of optical absorption spectra allows suppression of endogenous background signal, increasing the overall sensitivity and specificity of the modality to exogenous contrast agents. Here, sPA imaging was used to monitor antibody-indocyanine green (ICG) conjugates as they undergo optical absorption spectrum shifts after cellular endocytosis and degradation to allow differentiation between normal murine mammary glands from breast cancer by enhancing molecular imaging signal from target (B7-H3)-bound antibody-ICG. First, B7-H3 was shown to have highly specific (AUC of 0.93) expression on both vascular endothelium and tumor stroma in malignant lesions through quantitative immunohistochemical staining of B7-H3 on 279 human samples (normal (n=53), benign lesions (11 subtypes, n=182), breast cancers (4 subtypes, n=97)), making B7-H3 a promising target for sPA imaging. Second, absorption spectra of intracellular and degraded B7-H3-ICG and Isotype control (Iso-ICG) were characterized through in vitro and in vivo experiments. Finally, a transgenic murine breast cancer model (FVB/N-Tg(MMTVPyMT)634Mul) was imaged, and sPA imaging in found a 3.01 (IQR 2.63, 3.38, P<0.001) fold increase in molecular B7-H3-ICG signal in tumors (n=80) compared to control conditions (B7-H3-ICG in tumor negative animals (n=60), Iso-ICG (n=30), blocking B7-H3+B7-H3-ICG (n=20), and free ICG (n=20)) despite significant tumor accumulation of Iso-ICG, confirmed through ex vivo histology. Overall, leveraging anti-B7-H3 antibody-ICG contrast agents, which have dynamic optical absorption spectra representative of molecular interactions, allows for highly specific sPA imaging of murine breast cancer.
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