Deep Vascular Imaging in the Eye with Flow-Enhanced Ultrasound

The Flow-Enhanced Ultrasound technique allows us to image the vasculature of the eye in three dimensions, without use of contrast agents. The main advantage of this technique is its stability to image the vesture, behind the pigmented retina, which is challenging with several optical imaging techniques. We demonstrate this technique in goldfish but it can be applied to all species with nucleated red blood cells, allowing researchers to gain insight into the eyes functional evolution.

This technique can be applied by researchers with basic training in ultrasound imaging, and animal handling. After confirming an optimal level of anesthesia, position the animal in a posture that allows direct access from above, to the eye. Place a suitable ultrasound medium on the eye of the animal.

If scaled eyelids cover the eye, then, displace these gently with a cotton swab. For aquatic animals, water works well as an ultrasound medium, Next, position the ultrasound transducer, medial to the eye, in either a dorsal ventral or rostral caudal orientation, depending on desired image orientation. In B-Mode, with a maximum depth of field, image the medial and deepest portion of the eye, to make sure that all structures of interest are visible in the image field.

Slowly translate the transducer to each side, while inspecting the real time images. Make sure all structures of interest are visible in the image field. If not, switch to a transducer with a lower frequency, and larger depth of field.

Adjust image depth, depth offset, image width, and number of position of focal zones, to cover the desired region of interest in all three spatial dimensions. Then, set frame rate in the range of 50 to 120 frames per second. Next, adjust the 2D gain to a level, such that the anatomical structures are only just visible in the B-Mode acquisition to increase the signal to noise ratio in the subsequent flow-enhanced reconstruction.

To acquire a 2D flow-enhanced image at a single slice position, translate the transducer to this position, and proceed to flow-enhanced image reconstruction. To acquire a 3D recording of an entire region of interest, translate the transducer to one extreme of the region of interest. To determine the exact position of the extreme end, increase the 2D gain, briefly.

After the transducer is placed correctly, lower the 2D gain before recording, to ensure maximal signal to noise ratio in the subsequent flow-enhanced reconstruction. For each step or slice in the 3D recording, acquire greater than 100 frames. Then, using a micro manipulator or built-in transducer motor, translate the transducer across the entire region of interest, in steps of either 25 or 50 micrometers, and repeat the acquisition of more than 100 frames for each step.

For flow-enhanced imagery construction, export the recordings into the DICOM file format. To produce a single flow-enhanced image based on a greater than 100 frames scene recording, calculate the standard deviation on a pixel level using this formula, and repeat the calculation for each slice in the 3D recording. To automate the standard deviation calculation and image reconstruction process for multiple slices in a 3D recording, conduct this operation in batch mode using ImageJ and the macro script, provided in the text manuscript.

Combine all reconstructed images into one image stack using the Images to Stack command in ImageJ. Then, using the Properties command, specifies slice thickness from the step size used during acquisition, and save the image stack as a 3D TIFF file. The presence of nucleated red blood cells in non-ad adult mammalian vertebrates, provides positive contrast of flowing blood, compared to static tissue in scene recordings.

However, when now analyzed frame by frame, the clear distinction between blood and surrounding tissue is less obvious. This blood flow-enhancement procedure, essentially, compiles a multi-time point recording in 2D space, into a single image, where in the inherent signal value fluctuation in pixels, positioned in flowing blood, score a higher standard deviation, than surrounding static tissue, producing positive contrast. In 3D acquisitions, multiple parallel slices with known spacing can be combined into 3D image data.

It can be used for three dimensional volume rendering and anatomical modeling. Doppler based ultrasound imaging also provides the option to specifically image blood flow, however, with less sensitivity than this method. This flow-enhanced ultrasound procedure allows for blood flow imaging in a range of species with nucleated red blood cells.

Deep ocular vascular beds, such as the choroid rete mirabile in some fish, can be imaged if present in the species. The method is limited by the absence of nucleated red blood cells in mammals, in which the flow-enhancement procedure produces some degree of blood flow contrast, but not as distinct as in species with nucleated red blood cells. Flow-enhanced ultrasound is sensitive to motion noise.

Respiratory movements can cause image blurring and artifacts, such as tissue border enhancement. Prospective or retrospective gating can be used to adjust for motion noise. For both 2D and 3D acquisitions, it is crucial to limit motion artifacts caused by the animal moving, due to inadequate anesthesia on unstable transducer set up.

The development of this technique, paved the way for non-invasive in vivo examination of deep vascular networks in the eye of the vast majority of vertebrates, which possess nucleated erythrocytes.

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Journal (Biology)

Journal (Biology)

Deep Vascular Imaging in the Eye with Flow-Enhanced Ultrasound

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