Biology subjects

Kothapalli, S.-R.

Publications and source records attributed to Kothapalli, S.-R..

3 recordsLinked to original sources

bioRxiv2021

Awake mouse brain photoacoustic and optical imaging through a transparent ultrasound cranial window

Optical resolution photoacoustic microscopy (OR-PAM) can map the cerebral vasculature at capillary level resolution. However, the OR-PAM setups bulky imaging head makes awake mouse brain imaging challenging and inhibits its integration with other optical neuroimaging modalities. Moreover, the glass cranial windows used for optical microscopy are unsuitable for OR-PAM due to the acoustic impedance mismatch between the glass plate and the tissue. To overcome these challenges, we propose a lithium niobate based transparent ultrasound trans-ducer (TUT) as a cranial window on a thinned mouse skull. The TUT cranial window simplifies the imaging head considerably due to its dual functionality as an optical window and ultrasound transducer. The window remains stable for six weeks, with no noticeable inflammation and minimal bone regrowth. The TUT windows potential is demonstrated by imaging the awake mouse cerebral vasculature using OR-PAM, intrinsic optical signal imaging and two-photon microscopy. The TUT cranial window can potentially also be used for ultrasound stimulation and simultaneous multimodal imaging of the awake mouse brain.

bioengineering↗

bioRxiv2021

A Transparent Ultrasound Array for Real-time Optical, Ultrasound and Photoacoustic Imaging

Objective and Impact StatementSimultaneous imaging of ultrasound and optical contrasts can help map structural, functional and molecular biomarkers inside living subjects with high spatial resolution. There is a need to develop a platform to facilitate this multimodal imaging capability to improve diagnostic sensitivity and specificity. IntroductionCurrently, combining ultrasound, photoacoustic and optical imaging modalities is challenging because con-ventional ultrasound transducer arrays are optically opaque. As a result, complex geometries are used to co-align both optical and ultrasound waves in the same field of view. MethodsOne elegant solution is to make the ultrasound transducer transparent to light. Here, we demonstrate a novel transparent ultrasound transducer (TUT) liner array fabricated using a transparent lithium niobate piezoelectric material for real-time multimodal imaging. ResultsThe TUT array consisted of 64 elements and centered at [~] 6 MHz frequency. We demonstrate a quad-mode ultrasound, Doppler ultrasound, photoacoustic and fluorescence imaging in real-time using the TUT array directly coupled to the tissue mimicking phantoms. ConclusionThe TUT array successfully showed a multimodal imaging capability, and has potential applications in diagnosing cancer, neuro and vascular diseases, including image-guided endoscopy and wearable imaging.

bioengineering↗

bioRxiv2020

Modeling Combined Ultrasound and Photoacoustic Imaging: Simulations aiding Device Development and Deep Learning

Combined ultrasound and photoacoustic (USPA) imaging has attracted several clinical applications due to its ability to simultaneously display structural and molecular information of deep biological tissue in real time. However, the depth dependent optical attenuation and the unknown optical and acoustic heterogeneities, limit the USPA imaging performance, especially from deeper tissue regions. Novel instrumentation, image reconstruction and deep learning methods are currently being explored to improve the USPA image quality. Effective implementation of these approaches requires a reliable USPA simulation tool capable of generating US based anatomical and PA based molecular information. Here, we developed a hybrid USPA simulation platform by integrating finite element models of light and ultrasound propagation. The feasibility of modeling US combined with optical fluence dependent multispectral PA imaging is demonstrated using in silico homogeneous and heterogeneous prostate tissue. The platform allows optimization of device design parameters, such as the aperture size and frequency of light source and ultrasound detector arrays. In addition, the potential of this simulation platform to generative massive USPA datasets aiding the data driven deep-learning enhanced USPA imaging has been validated using both simulations and experiments.

bioengineering↗