H. Piyadasa was supported by the Canadian Institutes of Health Research (CIHR) Fellowship (MFE-176490). B. Oberlton was supported by the National Science Foundation (NSF) Fellowship (2020298220). A. Tsai was supported by a Damon Runyon Cancer Research Foundation (DRCRF) Fellowship (DRG-118-16), the Stanford Department of Pathology, the Annelies Gramberg Fund, and NIH 1U54HL165445-01. Additional acknowledgments go to Dr. Avery Lam, Dr. Davide Franchina, and Mako Goldston for helping to test and debug the program.

1. Loading of TSAI
<ol>
	<li>Run TSAI by opening&#160;https://tsai.stanford.edu/research/mibi_tsai in the web browser of the MIBI user control computer.
	<ol>
		<li>This instance of TSAI contains custom presets which do not apply to all instruments. When using it, build tiles only from template FOV(s) as generated&#160;below in step 2.6. TSAI runs locally within the web browser, and no image, .json, or file name data is sent to or stored on the server.</li>
	</ol>
	</li>
	<li>Alternatively, set up TSAI...

Accelerating MIBI Run Setup Using TSAI for Tissue Microarray Imaging

<ol>
	<li>Liu, C. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multiplexed+Ion+Beam+Imaging:+Insights+into+Pathobiology.">Multiplexed Ion Beam Imaging: Insights into Pathobiology.</a> Annu Rev Pathol. 17, 403-423 (2022).</li><li>Keren, L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MIBI-TOF:+A+multiplexed+imaging+platform+relates+cellular+phenotypes+and+tissue+structure.">MIBI-TOF: A multiplexed imaging platform relates cellular phenotypes and tissue structure.</a> Sci Adv. 5 (10), 1-16 (2019).</li><li>Elhanani, O., Keren, L., Angelo, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High-Dimensional+Tissue+Profiling+by+Multiplexed+Ion+Beam+Imaging.">High-Dimensional Tissue Profiling by Multiplexed Ion Beam Imaging.</a> Methods Mol Biol. 2386, 147-156 (2022).</li><li>Greenwald, N. F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Whole-cell+segmentation+of+tissue+images+with+human-level+performance+using+large-scale+data+annotation+and+deep+learning.">Whole-cell segmentation of tissue images with human-level performance using large-scale data annotation and deep learning.</a> Nat Biotechnol. 40 (4), 555-565 (2022).</li><li>Risom, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Transition+to+invasive+breast+cancer+is+associated+with+progressive+changes+in+the+structure+and+composition+of+tumor+stroma.">Transition to invasive breast cancer is associated with progressive changes in the structure and composition of tumor stroma.</a> Cell. 185 (2), 299.e18-310.e18 (2022).</li><li>McCaffrey, E. F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+immunoregulatory+landscape+of+human+tuberculosis+granulomas.">The immunoregulatory landscape of human tuberculosis granulomas.</a> Nat. Immunol. 23 (2), 318-329 (2022).</li><li>Greenbaum, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+spatially+resolved+timeline+of+the+human+maternal&#8211;fetal+interface.">A spatially resolved timeline of the human maternal&#8211;fetal interface.</a> Nature. 619 (7970), 595-605 (2023).</li><li>Hartmann, F. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Single-cell+metabolic+profiling+of+human+cytotoxic+T+cells.">Single-cell metabolic profiling of human cytotoxic T cells.</a> Nat Biotechnol. 39 (2), 186-197 (2021).</li><li>Patwa, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multiplexed+imaging+analysis+of+the+tumor-immune+microenvironment+reveals+predictors+of+outcome+in+triple-negative+breast+cancer.">Multiplexed imaging analysis of the tumor-immune microenvironment reveals predictors of outcome in triple-negative breast cancer.</a> Commun Biol. 4 (1), 852 (2021).</li><li>Keren, L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+Structured+Tumor-Immune+Microenvironment+in+Triple+Negative+Breast+Cancer+Revealed+by+Multiplexed+Ion+Beam+Imaging.">A Structured Tumor-Immune Microenvironment in Triple Negative Breast Cancer Revealed by Multiplexed Ion Beam Imaging.</a> Cell. 174 (6), 1373.e19-1387.e19 (2018).</li><li>Vijayaragavan, K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Single-cell+spatial+proteomic+imaging+for+human+neuropathology.">Single-cell spatial proteomic imaging for human neuropathology.</a> Acta Neuropathol. Commun. 10 (1), 158 (2022).</li><li>. GitHub - angelolab/toffy: Scripts for interacting with and generating data from the commercial MIBIScope. (n.d.) Available from: <a target="_blank" href="https://github.com/angelolab/toffy">https://github.com/angelolab/toffy</a> (2023)</li><li>. HTML Living Standard Available from: <a target="_blank" href="https://html.spec.whatwg.org/multipage">https://html.spec.whatwg.org/multipage</a> (2023)</li><li>. ECMAScript 2022 Language Specification Available from: <a target="_blank" href="https://www.ecma-international.org/publications-and-standards/standards/ecma-262">https://www.ecma-international.org/publications-and-standards/standards/ecma-262</a> (2023)</li><li>. Cascading Style Sheets (CSS) Available from: <a target="_blank" href="https://www.w3.org/Style/CSS/Overview.en.html">https://www.w3.org/Style/CSS/Overview.en.html</a> (2023)</li></ol>

Multiplexed ion beam imaging (MIBI) is a powerful technique for dissecting detailed cellular phenotypes and tissue histoarchitecture5,6,7,8,9,10,11. Computational efforts around MIBI have largely focused on processing the data after imaging, but little has been done to improve the instrument...

Multiplexed ion beam imaging (MIBI) is a technique to image 40+ proteins simultaneously on histologic tissue sections at up to 250 nm resolution1,2,3. After a histologic tissue section is stained using antibodies tagged with isotopically pure elemental metals, the MIBI instrument performs secondary ion mass spectrometry to simultaneously quantify all the isotopes - and thus expression of all 40+ antigens - at individual spots on the tissue. Performed across grids of millions of spots, the resulting 40+ plex images of protein expression enable the delineation of cell boundaries and identification of specific cell types while preserving spatial context1,2,3,4. This technique has been used by hundreds of users at roughly 20 sites to study the cellular composition, metabolic profiles, and/or architecture of dozens of tissue types as part of examining the immune response to tumors, tissue inflammation caused by infectious agents, neuropathology of dementia, and immune tolerance in pregnancy5,6,7,8,9,10,11.
A key bottleneck in MIBI instrument operation is setting up fields of view (FOVs) - 200&#160;x 200 &#181;m2 to 800&#160;x 800 &#181;m2 areas of the tissue - for imaging. The MIBI images one FOV at a time, up to 800&#160;x 800 &#181;m2, thus imaging larger areas requires stitching multiple FOVs together. Imaging a tissue microarray (e.g., eight circular tissues in Figure 1A) involves placing multiple FOVs spaced apart. To set up FOVs, the manufacturer interface provides 1) an optical camera image of the slide with a crosshair that roughly corresponds to the specified imaging coordinate (Figure 1A) and 2) a secondary electron detector (SED) image that shows the exact area at the coordinate, reportedly accurate to within 0.1 &#181;m (Figure 1B). First, the user roughly positions a single FOV using the optical image. Because the image resolution is only about 60 &#181;m per pixel, if the placement is off by two pixels (2 pixels&#160;x 60 &#181;m per pixel), a standard 400 &#181;m FOV will be off by 30%. Thus, the user must use the SED image to fine-tune the position - a tedious sequence of a dozen steps involving multiple popup windows, typing coordinates into text boxes, slowly nudging the SED with directional control buttons, and often even writing down coordinates on paper (Supplementary Figure 1). This process must be repeated for each spot of a 100+ core tissue microarray (TMA). Some third-party tools can help with the initial rough positioning12. However, they still require some programming knowledge, and final positioning is still done through the dozen-step process. It is also highly troublesome to position grids of adjacent FOVs, which will be later stitched together into a tiled panoramic image.
Thus, the tile/SED/array Interface (TSAI) was developed with the goal of enabling users to rapidly position large numbers of FOVs using an intuitive, interactive graphical interface. TSAI consists of two main components: 1) A web-based graphical user interface (web UI) for rapidly placing TMA points and tissue tiles, and 2) Integrations into the MIBI user control interface for generating a tiled SED image and adjusting FOV positions. If only using the optical image, many FOVs can be roughly positioned and then quickly adjusted using the FOV navigation/adjustment tools (Figure 2, TSAI, left branch). However, if the SED tiling is performed, FOVs can be accurately positioned on the tiled SED image without needing further adjustments in SED mode (Figure 2, TSAI, right branch). Of general interest to hundreds of current MIBI users, these tools make tiling and TMA positioning very simple even for novices and reduce complex MIBI run setups from several hours to a few dozen minutes.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>MIBI computer</td>
			<td>Ionpath</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>MIBIcontrol (software)</td>
			<td>Ionpath</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>MIBIscope</td>
			<td>Ionpath</td>
			<td></td>
			<td>Multiplexed Ion Beam Imaging (MIBI) microscope</td>
		</tr>
		<tr>
			<td>MIBIslide</td>
			<td>Ionpath</td>
			<td>567001</td>
			<td>Conductive slide for MIBI</td>
		</tr>
		<tr>
			<td>Tile/SED/Array Interface (TSAI) (software)</td>
			<td></td>
			<td>https://github.com/ag-tsai/mibi_tsai/</td>
			<td></td>
		</tr>
	</tbody>
</table>

rapid setup of tissue microarray and tiled area imaging on the multiplexed ion beam imaging microscope using the tile/sed/array interface 

Multiplexed ion beam imaging (MIBI) is a next-generation mass spectrometry-based microscopy technique&#160;that generates 40+ plex images of protein expression in histologic tissues, enabling detailed dissection of cellular phenotypes and histoarchitectural organization. A key bottleneck in&#160;operation occurs when users select the physical locations on the tissue for imaging. As the scale and complexity of MIBI experiments have increased, the manufacturer-provided interface and third-party tools have become increasingly unwieldy for imaging large tissue microarrays and tiled tissue areas. Thus, a web-based, interactive, what-you-see-is-what-you-get (WYSIWYG) graphical interface layer - the tile/SED/array Interface (TSAI) - was developed for users to set imaging locations using familiar and intuitive mouse gestures such as drag-and-drop, click-and-drag, and polygon drawing. Written according to web standards already built into modern web browsers, it requires no installation of external programs, extensions, or compilers. Of interest to the hundreds of current MIBI users, this interface dramatically simplifies and accelerates the setup of large, complex MIBI runs.

Author Spotlight: Introducing the Tile/SED/Array Interface for Rapid Field of View Positioning in Tissue Imaging

Rapid Setup of Tissue Microarray and Tiled Area Imaging on the Multiplexed Ion Beam Imaging Microscope Using the Tile/SED/Array Interface 

Multiplexed ion beam imaging, or MIBI, is a technique to image protein expression in histological tissues across dozens of proteins simultaneously. Using MIBI, researchers can identify, locate, and characterize cells in their native tissue environments. A key bottleneck in MIBI instrument operation is setting up fields of view, or FOVs, for imaging.FOVs are 200 by 200 micron to 800 by 800 micron areas on the slide which users position to cover tissue regions of interest. Positioning FOVs for large contiguous areas of tissue and large tissue microarrays is unwieldy using the manufacturer's interface. We developed the tile/SED/array interface to help users this rapidly position large numbers of FOVs using an intuitive, interactive graphical interface.

TSAI provides two methods for setting up FOVs (Figure 2). One uses only the optical image (Figure 2, TSAI, left branch), similar to other existing methods. The second method - generating a tiled SED image - is unique to TSAI (Figure 2, TSAI, right branch). TSAI draws FOVs accurately onto this image, eliminating the need to spend hours nudging FOVs into place in the manufacturer interface SED mode. However, the correction coefficient...

Read this Scientific Article Protocol about Rapid Setup of Tissue Microarray and Tiled Area Imaging on the Multiplexed Ion Beam Imaging Microscope using the Tile/SED/Array Interface at JoVE.com

Multiplexed ion beam imaging (MIBI) is often used to image tissue microarrays and tiled, contiguous tissue areas, but current software for setting up these experiments is cumbersome. The tile/SED/array interface is an intuitive, interactive graphical tool developed to dramatically simplify and accelerate MIBI run setup.

Multiplexed ion beam imaging (MIBI) is a next-generation mass spectrometry-based microscopy technique&#160;that generates 40+ plex images of protein ...

rapid-setup-tissue-microarray-tiled-area-imaging-on-multiplexed-ion

Research

JoVE Journal

Biology

Optical Image-Stage Motor Coregistration and Tiled SED Scan Setup for Tile/SED/Array Interface (TSAI)

To begin, open the TSAI web user interface in the web browser. Then, open the optical coregistration menu and click copy automatic registration code to clipboard. Open the MIBI user control interface in the web browser and press Control Shift J to open the browser console.Paste the code into the console and press enter. Click the link generated in the console to load the coregistration into the TSAI web user interface and save it as a cookie. Drag and drop the optical image PNG and JSON files onto the TSAI web user interface.Open the SED tiler menu and click on a text box in the top row. Click and drag on the optical image to select the top left corner for the SED scan. Press the D key, then click and drag on the optical image to select the bottom right corner for the SED scan.In the SED tiler menu, click copy SED scan and shift correction code to clipboard. Next, open the MIBI user control interface in the web browser. Paste the code into the console and press enter.Put the MIBI into SED mode on the QC 300 setting, and move to an area that will not be acquired. Then, adjust the gain, focus, and stigmation. Press Shift T to start the tiled SED scan.Upon completion, the system automatically saves a new PNG file of the tiled SED image. Next, inspect the tiled SED scan for large misalignments. When tiled SED is adequate, press escape and return to the TSAI web user interface.Drag and drop the tiled SED PNG file onto the TSAI web user interface. Click on the SED tab and adjust the zoom. Use the slide options menu above the SED image to adjust line thickness, and cursor size, and brightness, and contrast.A properly tiled SED image shows minimal misalignments between SED tiles. In contrast, the suboptimal setup results in large misalignments between SED tiles.

Optimizing Tissue Microarrays and Area/Polygon Tiles for Efficient Large-Scale Imaging

To set a field of views or FOVs for a grid of tissue microarray or TMA spots, open a tiled SED image. In the relevant tile of the tiles column, adjust the columns and rows. Then check or uncheck the boxes in the map.In the relevant tile, click TMA to open the TMA Options menu. Set the number of rows and columns of TMA spots. If necessary, add a naming prefix and edit the starting row and column numbering.On the slide image, click on the four corners of the TMA. Then click and drag the circled corners to adjust the positioning of the crosshairs to best match the TMA spots. From the TMA Options menu, click Build TMA.To check the tile's positioning, hover over each tile in the Tiles column. Click Move to adjust the tile's positioning. Then click and drag on the slide image.To set FOVs to cover a contiguous area of tissue, first adjust FOV settings in the relevant tile of the tile's column. In the relevant tile, click Polygon to cover a contiguous area of tissue. Then click on the slide image to set the vertices and corners of the area to be tiled.Double-click to close the polygon and cover the area with FOVs. Scroll to the bottom of the Tile column and click the three stacked lines button in the new polygon tile to see the tile map. Click on Eraser to toggle off multiple FOVs.Then click and drag on the tiled FOVs in the slide image. To toggle on multiple FOVs, click on Clicker. Then click and drag on the empty areas in the slide image covered by the tile map.To insert the rows above, click the up arrow button. Click the left arrow button to insert columns to the left. To adjust tile positioning, click Move.Then click and drag on the slide image.

285 Views.  Stanford University.  Multiplexed ion beam imaging (MIBI) is often used to image tissue microarrays and tiled, contiguous tissue areas, but current software for setting up these experiments is cumbersome. The tile/SED/array interface is an intuitive, interactive graphical tool developed to dramatically simplify and accelerate MIBI run setup.

Accelerating MIBI Run Setup Using TSAI for Tissue Microarray Imaging

概要