Validation of a Software-Defined 100-Gb/s RDMA Streaming Architecture for Ultrafast Optoacoustic and Ultrasound Imaging

2026-01-26

AI Summary

This work addresses the clinical translation bottleneck of photoacoustic imaging systems, which are typically constrained by bulky and costly ultrasound-optimized hardware that struggles to simultaneously achieve high bandwidth, multi-channel capability, and laser synchronization. To overcome these limitations, the authors propose a software-defined data acquisition architecture tailored for ultrafast photoacoustic and ultrasound imaging. The design innovatively employs a continuous, cache-free RDMA (Remote Direct Memory Access) streaming mechanism, bypassing the frame-rate and recording-duration constraints inherent in conventional burst-mode transfers and enabling sustained high-speed raw data streaming. The system integrates a broadband analog front-end, a Zynq UltraScale+ MPSoC, and a 100 GbE RDMA backend to form a scalable platform. A 16-channel prototype validates the architecture’s feasibility and demonstrates its potential scalability to 256 channels, supporting a sustained data throughput of up to 95.6 Gb/s.

Technology Category

• Machine Learning: Hardware-aware ML
• Computer Vision: Medical and Biological Imaging
• Data Mining & Knowledge Management: Scalability, Parallel & Distributed Systems

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Data management and stream processing for Web, mobile and wireless applications
• Search and Retrieval-Augmented AI: Personalized, context-aware and across-device search
• Security and Privacy: Data transparency and provenance

Abstract

Optoacoustic (OA) imaging has emerged as a powerful investigation tool, with demonstrated applicability in oncology, neuroscience, and cardiovascular biology. However, its clinical translation is limited with the existing OA systems, which often rely on bulky and expensive acquisition hardware mainly optimized for pulse-echo ultrasound (US) imaging. Despite the fact that OA imaging has different requirements for receive bandwidths and timing synchronization with external laser sources, there is a strong need for unified OA-US imaging platforms, as pulse-echo US remains the standard tool for visualizing soft tissues. To address these challenges, we propose a new data acquisition architecture for ultrafast OA and US imaging that fully covers the requirements for large channel counts, wide bandwidth, and software-defined operation. LtL combines state-of-the-art wideband analog front-ends, a Zynq UltraScale+ MPSoC integrating FPGA fabric with an Application Processing Unit, and a 100 GbE Remote Direct Memory Access (RDMA) backend enabling raw-data streaming at up to 95.6 Gb/s. The architecture avoids local buffers followed by burst transfers, which commonly constrain sustainable frame rate and recording intervals, thus achieving true continuous and sustained streaming of raw data. We validate the core elements of the LtL architecture using a 16-channel demonstration system built from commercial evaluation boards. We further verify the signal chain for up to 256-channel scalability, confirming the wide bandwidth capabilities to support state-of-the-art data transmission speeds.

Problem

• Optoacoustic imaging
• Ultrasound imaging
• Data acquisition architecture
• Clinical translation
• Hardware limitations

Innovation

• RDMA streaming
• software-defined architecture
• optoacoustic imaging
• ultrafast ultrasound
• Zynq MPSoC