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Quantitative Photoacoustic Imaging for the Assessment of Targeted Lipo-JICG in a Preclinical Model

C Wood1,2*, C Kim1 , S Han1 , Y Wen1 , M Naser1 , C Kaffes1 , J Cook3 , A Sood1,2 , K Sokolov1,2 , R Bouchard1,2 , (1) The University of Texas MD Anderson Cancer Center, Houston, TX, (2) The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, TX, (3) NanoHybrids, Inc., Austin, TX


(Sunday, 7/14/2019) 2:00 PM - 3:00 PM

Room: 303

Purpose: To optimize the iThera Medical MSOT inVision 256-TF photoacoustic (PA) imaging system to quantitatively assess a novel PA contrast agent based on antibody-targeted liposomes loaded with J-aggregates of indocyanine green (ICG) dye (Lipo-JICG) in a preclinical model.

Methods: 10 athymic nu/nu mice were injected with SKOV3 ovarian cancer cells in the left ovary. Once tumors reached a volume of at least 5 mm² measured on MRI, mice were imaged on the MSOT PA imaging system at 8 wavelengths and with 15-frame averaging. PA imaging was performed at five time-points: pre-injection, and immediately, 30 min, 1 hour, and 24 hours post-injection. Mice were injected with either targeted (a-FR�) or non-targeted (a-RG16) Lipo-JICGs. Because there is not significant contrast from the ovary in PA images, the tumor position and size were determined from MR images, localizing relative to the left kidney. Regions of interest were then placed inside the tumor on 800-nm PA images for quantitative assessment. Linear unmixing was performed for oxyhemoglobin, deoxyhemoglobin, and Lipo-JICG with different wavelength combinations to maximize the enhancement from pre- to 1-hour-post-injection images. To improve the accuracy of quantification, an FEM-based model of the fluence distribution in the surrounding water bath was developed and a surface-fluence correction was applied to the mouse-surface boundary before unmixing.

Results: The optimal wavelengths selected were 730, 760, 780, 800, 830, 890, & 920 nm. Using these wavelengths for linear unmixing, the SOâ‚‚ in an artery, which we expect to be near 100%, was measured to be 86% without correction; after surface-fluence correction, arterial SOâ‚‚ increased to 93%. Lipo-JICG signal in the tumor increased by 15% after surface-fluence correction was applied.

Conclusion: We have developed and optimized an imaging protocol to assess Lipo-JICG in vivo, and applied an FEM-based fluence distribution model to improve the accuracy of our quantification.


Photoacoustics, Optical Modeling


IM- Ultrasound : Quantitative imaging/analysis

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