2023年10月27日
The combination of multiple imaging modalities is often necessary to gain a comprehensive understanding of pathophysiology. This approach utilizes phantoms to generate a differential transformation between the coordinate systems of two modalities, which is then applied for co-registration. This method eliminates the need for fiducials in production scans.
We developed software tools for preclinical imaging, including industry construction, fusion, segmentation, and quantification. Our software is meant to be user friendly, efficient, and compatible with any small animal imaging device to enable reproducible quantitative analysis of the acquired multimodal image data. Automation is an important topic in our field because manual analysis is often too time consuming, error prone, and hardly reproducible.
Software-based automation can make the analysis efficient and reproducible, but the challenge is in making the automation robust enough. Small animal imaging devices provide volumetric image data of anesthetized laboratory mice and rats, and allow non-invasive assessment of pathological and physiological changes. Integrated multimodal devices combine the strengths of multiple modalities, such as micro CT and PET.
It is also possible to combine two separate devices. We developed software for the automated fusion of special modalities, such as micro CT and FMT. We also provided efficient software for interactive image fusion and defined a new file format to store the image data considering aspects from data curation.
Last year we published an approach for retrospective respiratory gating and the high throughput settings. Our protocol results in a transformation matrix, which is generated using a calibration step that involves visible structures such as fiduciary markers. Then the image fusion can be automated using this transformation matrix, which eliminates the need for markers.
Begin by loading the images of both modalities. To do so, open the analysis software. To load the CT Image A as underlay, go to File, followed by Underlay, and click Load Underlay.
In the dialogue that appears, choose and open the image file. Similarly, to load the PET Image A as an overlay click File, Overlay, Load Overlay, and choose the image file to open it. For marker based fusion, hide the underlay by navigating to Menu, View, and Layer Visibility.
Then uncheck overlay and keep underlay. Switch the selected layer to the underlay if required. To show multiple slice views, press alt plus A for the axial, alt plus S for the sagittal, and alt plus C for the coronal views.
If necessary, press CTRL plus W and adjust the left and right vertical bars in the windowing dialogue to better see the fiducials. Click on Okay to close the dialogue. Click the marker symbol on the vertical toolbar on the left side to activate the mouse action mode, Create Marker.
Navigate to one fiducial of the phantom. Place the mouse pointer in its center and left click. Select Okay To save the marker, place the mouse pointer over the view of a plane, and use alt plus mouse wheel to slice through the planes.
Adjust the viewing settings by navigating to Menu, View, Layer Visibility, and check Overlay to show the overlay. Switch the selected layer to overlay. Adjust the windowing as demonstrated if necessary.
Navigate to each fiducial of the phantom. Place the mouse pointer in the center of the fiducial and left click. Click on Okay to save the marker.
Place the mouse pointer over the view of a plane and use alt plus mouse wheel to slice through the planes. Align the markers of underlay and overlay by navigating to Fusion, followed by Register Overlay to Underlay, and selecting Compute Rotation and Translation. Note this measurement and click Okay.
Check the result of the alignment. As demonstrated previously, activate the views of underlay and overlay layers. Click on the symbol on the left side vertical toolbar to activate the mouse mode Interactive Image Fusion.
Check overlay, uncheck underlay and segmentation. Perform translation by placing the mouse pointer near the center of a view. Hold the left mouse button and move the mouse to move the overlay.
Perform rotation by placing the pointer near the edge of a view, axial, coronal, or sagittal. Hold the left mouse button and move the mouse to rotate the overlay. Keep performing rotations and translations on the different views until the underlay and overlay are aligned as best as possible.
Create and save the differential transformation by navigating Fusion, Overlay Transformation, and select Create and Save Differential Transformation. In the first dialogue, select the original overlay file and click on Open. In the second dialogue, enter a file name for the differential transformation and press Save.
To begin, launch the analysis software. Import the CT file as an underlay by clicking on File, Underlay, and Load Underlay. In the ensuing dialogue, select the CT image file to open it.
Load the PET file as an overlay by sequentially selecting File, Overlay, and Load Overlay. In the dialogue that appears, choose the PET image file. To enable the display of both layers, go to Menu, View, followed by Layer Visibility, and check both Underlay and Overlay.
To load and apply the previously saved differential transformation matrix, click on Fusion, Overlay Transformation, and then Load and Apply Transform. Then select the file containing the matrix from the calibration process to open it.
本研究介绍了专为临床前成像设计的软件工具,重点在于多模态图像分析的自动化。这些工具可提高对小型动物成像设备获取的容积图像数据进行分析的效率和可重复性。
稳定且无需标记物的临床前成像模态共配准技术,通过实现多模态数据集的可重复、定量整合,解决了转化研究中的关键瓶颈问题。该技术可提高疾病模型的预测可信度,并在药物发现流程中支持更可靠的靶点验证和机制性风险排除。简化且具备自动化准备条件的工作流程可减少人为变异,促进企业级研发项目中可扩展的、跨机构的成像研究。
这种无标记共配准工作流程通过实现多种成像模式和设备的影像数据无缝整合,连接了早期发现、先导物识别和临床前验证。