Mr. Gurneet Sangha Profile

Gurneet Sangha

at Purdue Univ

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Proceedings Article | 19 February 2018 Presentation + Paper

Motorized photoacoustic tomography probe for label-free improvement in image quality

Gurneet Sangha, Nick Hale, Craig Goergen

Proceedings Volume 10486, 1048604 (2018) https://doi.org/10.1117/12.2289062

KEYWORDS: Acquisition tracking and pointing, Ultrasonography, Signal to noise ratio, Transducers, Tissue optics, Fiber optics, Aluminum, Image quality, In vivo imaging, Aorta

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One of the challenges in high-resolution in vivo lipid-based photoacoustic tomography (PAT) is improving penetration depth and signal-to-noise ratio (SNR) past subcutaneous fat absorbers. A potential solution is to create optical manipulation techniques to maximize the photon density within a region of interest. Here, we present a motorized PAT probe that is capable of tuning the depth in which light is focused, as well as substantially reducing probe-skin artifacts that can obscure image interpretation. Our PAT system consists of a Nd:YAG laser (Surelite EX, Continuum) coupled with a 40 MHz central frequency ultrasound transducer (Vevo2100, FUJIFILM Visual Sonics). This system allows us to deliver 10 Hz, 5 ns light pulses with fluence of 40 mJ/cm² to the tissue interest and reconstruct PAT and ultrasound images with axial resolutions of 125 µm and 40 µm, respectively. The motorized PAT holder was validated by imaging a polyethylene-50 tubing embedded polyvinyl alcohol phantom and periaortic fat on apolipoprotein-E deficient mice. We used 1210 nm light for this study, as this wavelength generates PAT signal for both lipids and polyethylene-50 tubes. Ex vivo results showed a 2 mm improvement in penetration depth and in vivo experiments showed an increase in lipid SNR of at least 62%. Our PAT probe also utilizes a 7 μm aluminum filter to prevent in vivo probe-skin reflection artifacts that have been previously resolved using image post-processing techniques. Using this optimized PAT probe, we can direct light to various depths within tissue to improve image quality and prevent reflection artifacts.

Proceedings Article | 13 February 2018 Presentation + Paper

Multi-modality photoacoustic tomography, ultrasound, and light sheet microscopy for volumetric tumor margin detection

Gurneet Sangha, Bihe Hu, Daniel Bolus, Mei Wang, Shelby Skidmore, Andrew Sholl, J. Quincy Brown, Craig Goergen

Proceedings Volume 10487, 104870D (2018) https://doi.org/10.1117/12.2289047

KEYWORDS: Tissues, Acquisition tracking and pointing, Tumors, Biopsy, Breast, Breast cancer, Ultrasonography, Microscopy, Photoacoustic tomography, Cancer

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Current methods for breast tumor margin detection are invasive, time consuming, and typically result in a reoperative rate of over 25%. This marks a clear clinical need to develop improved tools to intraoperatively differentiate negative versus positive tumor margins. Here, we utilize photoacoustic tomography (PAT), ultrasound (US), and inverted Selective Plane Illumination Microscopy (iSPIM) to assess breast tumor margins in eight human breast biopsies. Our PAT/US system consists of a tunable Nd:YAG laser (NT 300, EKSPLA) coupled with a 40MHz central frequency US probe (Vevo2100, FUJIFILM Visual Sonics). This system allows for the delivery of 10Hz, 5ns pulses with fluence of 40mJ/cm² to the tissue with PAT and US axial resolutions of 125μm and 40μm, respectively. For this study, we used a linear stepper motor to acquire volumetric PAT/US images of the breast biopsies using 1100nm light to identify bloodrich “tumor” regions and 1210nm light to identify lipid-rich “healthy” regions. iSPIM (Applied Scientific Instrumentation) is an advanced microscopy technique with lateral resolution of 1.5μm and axial resolution of 7μm. We used 488nm laser excitation and acridine orange as a general comprehensive histology stain. Our results show that PAT/US can be used to identify lipid-rich regions, dense areas of arterioles and arteries, and other internal structures such as ducts. iSPIM images correlate well with histopathology slides and can verify nuclear features, cell type and density, stromal features, and microcalcifications. Together, this multimodality approach has the potential to improve tumor margin detection with a high degree of sensitivity and specificity.

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