Coregistered transcranial optoacoustic and magnetic resonance angiography of the human brain

Multimodal optoacoustic imaging: methods and contrast materials

Optoacoustic (OA) imaging offers powerful capabilities for interrogating biological tissues with rich optical absorption contrast while maintaining high spatial resolution for deep tissue observations. The spectrally distinct absorption of visible and near-infrared photons by endogenous tissue chromophores facilitates extraction of diverse anatomic, functional, molecular, and metabolic information from living tissues across various scales, from organelles and cells to whole organs and organisms. The primarily blood-related contrast and limited penetration depth of OA imaging have fostered the development of multimodal approaches to fully exploit the unique advantages and complementarity of the method. We review the recent hybridization efforts, including multimodal combinations of OA with ultrasound, fluorescence, optical coherence tomography, Raman scattering microscopy and magnetic resonance imaging as well as ionizing methods, such as X-ray computed tomography, single-photon-emission computed tomography and positron emission tomography. Considering that most molecules absorb light across a broad range of the electromagnetic spectrum, the OA interrogations can be extended to a large number of exogenously administered small molecules, particulate agents, and genetically encoded labels. This unique property further makes contrast moieties used in other imaging modalities amenable for OA sensing.

Unsupervised Fusion of Misaligned PAT and MRI Images via Mutually Reinforcing Cross-Modality Image Generation and Registration

Photoacoustic tomography (PAT) and magnetic resonance imaging (MRI) are two advanced imaging techniques widely used in pre-clinical research. PAT has high optical contrast and deep imaging range but poor soft tissue contrast, whereas MRI provides excellent soft tissue information but poor temporal resolution. Despite recent advances in medical image fusion with pre-aligned multimodal data, PAT-MRI image fusion remains challenging due to misaligned images and spatial distortion. To address these issues, we propose an unsupervised multi-stage deep learning framework called PAMRFuse for misaligned PAT and MRI image fusion. PAMRFuse comprises a multimodal to unimodal registration network to accurately align the input PAT-MRI image pairs and a self-attentive fusion network that selects information-rich features for fusion. We employ an end-to-end mutually reinforcing mode in our registration network, which enables joint optimization of cross-modality image generation and registration. To the best of our knowledge, this is the first attempt at information fusion for misaligned PAT and MRI. Qualitative and quantitative experimental results show the excellent performance of our method in fusing PAT-MRI images of small animals captured from commercial imaging systems.

Shedding light on ultrasound in action: Optical and optoacoustic monitoring of ultrasound brain interventions

Monitoring brain responses to ultrasonic interventions is becoming an important pillar of a growing number of applications employing acoustic waves to actuate and cure the brain. Optical interrogation of living tissues provides a unique means for retrieving functional and molecular information related to brain activity and disease-specific biomarkers. The hybrid optoacoustic imaging methods have further enabled deep-tissue imaging with optical contrast at high spatial and temporal resolution. The marriage between light and sound thus brings together the highly complementary advantages of both modalities toward high precision interrogation, stimulation, and therapy of the brain with strong impact in the fields of ultrasound neuromodulation, gene and drug delivery, or noninvasive treatments of neurological and neurodegenerative disorders. In this review, we elaborate on current advances in optical and optoacoustic monitoring of ultrasound interventions. We describe the main principles and mechanisms underlying each method before diving into the corresponding biomedical applications. We identify areas of improvement as well as promising approaches with clinical translation potential.

Automatic analysis of skull thickness, scalp-to-cortex distance and association with age and sex in cognitively normal elderly

Personalized neurostimulation has been a potential treatment for many brain diseases, which requires insights into brain/skull geometry. Here, we developed an open source efficient pipeline BrainCalculator for automatically computing the skull thickness map, scalp-to-cortex distance (SCD), and brain volume based on T 1 -weighted magnetic resonance imaging (MRI) data. We examined the influence of age and sex cross-sectionally in 407 cognitively normal older adults (71.9±8.0 years, 60.2% female) from the ADNI. We demonstrated the compatibility of our pipeline with commonly used preprocessing packages and found that BrainSuite Skullfinder was better suited for such automatic analysis compared to FSL Brain Extraction Tool 2 and SPM12- based unified segmentation using ground truth. We found that the sphenoid bone and temporal bone were thinnest among the skull regions in both females and males. There was no increase in regional minimum skull thickness with age except in the female sphenoid bone. No sex difference in minimum skull thickness or SCD was observed. Positive correlations between age and SCD were observed, faster in females (0.307%/y) than males (0.216%/y) in temporal SCD. A negative correlation was observed between age and whole brain volume computed based on brain surface (females -1.031%/y, males -0.998%/y). In conclusion, we developed an automatic pipeline for MR-based skull thickness map, SCD, and brain volume analysis and demonstrated the sex-dependent association between minimum regional skull thickness, SCD and brain volume with age. This pipeline might be useful for personalized neurostimulation planning.