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Combined Diffuse Optical Spectroscopic Imaging (DOSI) and Diffuse Correlation Spectroscopy (DCS) for real time subsurface imaging of tissue composition, metabolism, and vascular dynamics

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Abstract

Abnormal tissue metabolism has been documented in a wide variety of diseases including cancer, arterial disease and neurodegenerative disorders. A common underlying factor of these diseases is the down-regulation of tissue oxygen metabolism (tMRO_2) during tissue hypoxia. tMRO_2 has been quantified and used for both diagnosing and monitoring various diseases. Near-infrared spectroscopy (NIRS) provides a non-invasive and comparatively inexpensive modality for quantifying sub-surface tissue metabolism. Diffuse optical spectroscopic imaging (DOSI) and diffuse correlation spectroscopy (DCS) are model-based NIRS methods. DOSI and DCS are capable of measuring tissue oxygenation and blood flow, respectively.

In this study, we developed and validated a spatially co-registered DOSI/DCS metabolic imaging system. We documented that quantitative DOSI/DCS metabolic imaging provides an enhanced view and thereby, better understanding of breast cancer tumor composition and metabolism.

In addition, tMRO_2 and composition are critical to quantify during surgery to help identify sub-surface tissue viability invisible to the naked eye. The integrated DOSI/DCS laparoscopic probe was developed to demonstrate measurement capabilities in non-survival preclinical model.

Next, we optimized data acquisition frequency and enabled data collection of both DOSI and DCS concurrently. Relying on an improved high-speed DOSI/DCS system enabled us to extract real-time pulsatile information pertaining to vascular dynamics. Then, we quantified tMRO_2 at two tissue sites, as well as the abdomen and forearm. We observed lower metabolic activity in tissues with higher subcutaneous adipose compared to tissues with leaner muscle. In conclusion, we developed a high-speed DOSI/DCS system and illustrated its effectiveness in a variety of clinical applications.

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