Dataset Information

Characterizing a photoacoustic and fluorescence imaging platform for preclinical murine longitudinal studies.

ABSTRACT:

Significance

To effectively study preclinical animal models, medical imaging technology must be developed with a high enough resolution and sensitivity to perform anatomical, functional, and molecular assessments. Photoacoustic (PA) tomography provides high resolution and specificity, and fluorescence (FL) molecular tomography provides high sensitivity; the combination of these imaging modes will enable a wide range of research applications to be studied in small animals.

Aim

We introduce and characterize a dual-modality PA and FL imaging platform using in vivo and phantom experiments.

Approach

The imaging platform's detection limits were characterized through phantom studies that determined the PA spatial resolution, PA sensitivity, optical spatial resolution, and FL sensitivity.

Results

The system characterization yielded a PA spatial resolution of 173±17 μm in the transverse plane and 640±120 μm in the longitudinal axis, a PA sensitivity detection limit not less than that of a sample with absorption coefficient μa=0.258 cm-1 , an optical spatial resolution of 70 μm in the vertical axis and 112 μm in the horizontal axis, and a FL sensitivity detection limit not <0.9 μM concentration of IR-800. The scanned animals displayed in three-dimensional renders showed high-resolution anatomical detail of organs.

Conclusions

The combined PA and FL imaging system has been characterized and has demonstrated its ability to image mice in vivo, proving its suitability for biomedical imaging research applications.

SUBMITTER: Thompson WR

PROVIDER: S-EPMC9990133 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature

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Publications

Characterizing a photoacoustic and fluorescence imaging platform for preclinical murine longitudinal studies.

Thompson Weylan R WR Brecht Hans-Peter F HF Ivanov Vassili V Yu Anthony M AM Dumani Diego S DS Lawrence Dylan J DJ Emelianov Stanislav Y SY Ermilov Sergey A SA

Journal of biomedical optics 20230307 3

<h4>Significance</h4>To effectively study preclinical animal models, medical imaging technology must be developed with a high enough resolution and sensitivity to perform anatomical, functional, and molecular assessments. Photoacoustic (PA) tomography provides high resolution and specificity, and fluorescence (FL) molecular tomography provides high sensitivity; the combination of these imaging modes will enable a wide range of research applications to be studied in small animals.<h4>Aim</h4>We i ...[more]

PMID: 36895414

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Project description:SignificancePhotoacoustic tomography (PAT) has great potential in monitoring disease progression and treatment response in breast cancer. However, due to variations in breast repositioning, there is a chance of geometric misalignment between images. Further, poor repositioning can affect light fluence distribution and imaging field-of-view, making images different from one another. The net effect is that it becomes challenging to distinguish between image changes due to repositioning effects and those due to true biological variations.AimThe aim is to develop a three-dimensional image registration framework for geometrically aligning repeated PAT volumetric images, which are potentially affected by repositioning effects such as misalignment, changed radiant exposure conditions, and different fields-of-view.ApproachThe proposed framework involves the use of a coordinate-based neural network to represent the displacement field between pairs of PAT volumetric images. A loss function based on normalized cross correlation and Frangi vesselness feature extraction at multiple scales was implemented. We refer to our image registration framework as MUVINN-reg, which stands for multiscale vesselness-based image registration using neural networks. The approach was tested on a longitudinal dataset of healthy volunteer breast PAT images acquired with the hybrid photoacoustic-ultrasound Photoacoustic Mammoscope 3 imaging system. The registration performance was also tested under unfavorable repositioning conditions such as intentional mispositioning, and variation in breast-supporting cup size between measurements.ResultsA total of 13 pairs of repeated PAT scans were included in this study. MUVINN-reg showed excellent performance in co-registering each pair of images. The proposed framework was shown to be robust to image intensity shifts and field-of-view changes. Furthermore, MUVINN-reg could align vessels at imaging depths greater than 4 cm.ConclusionsThe proposed framework will enable the use of PAT for quantitative and reproducible monitoring of disease progression and treatment response.

Dataset Information

Characterizing a photoacoustic and fluorescence imaging platform for preclinical murine longitudinal studies.

Significance

Aim

Approach

Results

Conclusions

Publications

Characterizing a photoacoustic and fluorescence imaging platform for preclinical murine longitudinal studies.

Similar Datasets

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