IP Library Granted Patent US 12669692
Granted Patent B2
US 12669692 · App. 17/766,962 · Granted Jun 30, 2026

Microscope slide and method for selecting the same

Inventors: Toru Fujimura (Tokyo, JP); Takahito Hashimoto (Tokyo, JP); Shigehiko Kato (Tokyo, JP); Eiko Nakazawa (Tokyo, JP); Masahiko Ajima (Tokyo, JP); Akira Sawaguchi (Miyazaki, JP)
Assignee: Hitachi High-Tech Corporation
G02B21/34G01N1/30G01N2001/302
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Quick Facts
Patent No.
US 12669692
App. No.
17/766,962
Granted
Jun 30, 2026
Kind
B2
Abstract

Provided is an efficient method for attaching a tissue section. In the invention, one of problems is solved by changing attachment conditions of the tissue section depending on an organ from which the tissue section is derived. A technique of achieving good adhesiveness between a microscope slide and a section by introducing unevenness on a front surface of the microscope slide using reactive ion etching as one of the attachment conditions is provided. Further, a technique of optimizing the attachment of the section using a machine learning technique or the like is provided.

Claims (29)

1 . An attachment method comprising:

changing an attachment condition for attaching a tissue section to a microscope slide depending on an organ from which the tissue section is derived, wherein

the attachment condition is changed based on data registered in a database in association with at least one of an image of the tissue section and information on the organ from which the tissue section is derived, and surface treatment information on the microscope slide, and

the attachment condition comprises at least one of: i) selecting the type of surface treatment of the microscope slide prior to attachment, ii) adjusting processing parameters configured to prepare the microscope slide prior to attachment, or iii) modifying extension or heating conditions during attachment of the tissue section to the microscope slide, wherein

a microscope slide used for attaching the tissue section is selected, prior to the step of changing the attachment condition, based on an output of a learned model learned with training data, the training data using the image of the tissue section as an input and using data that includes at least surface treatment information on the microscope slide used for attaching the tissue section as an output.

2 . The attachment method according to claim 1 , wherein

the attachment condition is a condition for changing surface roughness formed on a front surface of the microscope slide prepared prior to attachment of the tissue section.

3 . The attachment method according to claim 2 , wherein

the attachment condition is a condition for changing the unevenness depending on stretchability of the organ to be attached.

4 . The attachment method according to claim 2 , wherein

the unevenness is formed by dry-etching the front surface of the prepared microscope slide with reactive ions.

5 . The attachment method according to claim 4 , wherein

the microscope slide on which the unevenness is formed is coated with a silane coupling agent or a polymer having an amino group after the dry-etching.

6 . The attachment method according to claim 1 , wherein

the organ is derived from induced pluripotent stem cells.

7 . An attachment method comprising:

changing an attachment condition for attaching a tissue section to a microscope slide depending on an organ from which the tissue section is derived, wherein

the attachment condition is changed based on data registered in a database in association with at least one of an image of the tissue section and information on the organ from which the tissue section is derived, and surface treatment information on the microscope slide, and

the attachment condition comprises at least one of: i) selecting the type of surface treatment of the microscope slide prior to attachment, ii) adjusting processing parameters configured to prepare the microscope slide prior to attachment, or iii) modifying extension or heating conditions during attachment of the tissue section to the microscope slide, wherein

a microscope slide used for attaching the tissue section is selected, prior to the step of changing the attachment condition, based on an output of a learned model learned with training data, the training data using the information on the organ from which the tissue section is derived as an input, and using data that includes at least surface treatment information on the microscope slide used for attaching the tissue section as an output.

8 . An attachment method comprising:

changing an attachment condition for attaching a tissue section to a microscope slide depending on an organ from which the tissue section is derived, wherein

the attachment condition is changed based on data registered in a database in association with at least one of an image of the tissue section and information on the organ from which the tissue section is derived, and surface treatment information on the microscope slide, and

the attachment condition comprises at least one of: i) selecting the type of surface treatment of the microscope slide prior to attachment, ii) adjusting processing parameters configured to prepare the microscope slide prior to attachment, or iii) modifying extension or heating conditions during attachment of the tissue section to the microscope slide, wherein

the attachment condition is changed based on data registered in a database in association with an image of a cut surface of a paraffin-embedded sample and surface treatment information on the microscope slide.

9 . The attachment method according to claim 8 , wherein

a microscope slide used for attaching the tissue section is selected, prior to the step of changing the attachment condition, based on an output of a learned model learned with training data, the training data using the image of the cut surface of the paraffin-embedded sample as an input, and using data that includes at least surface treatment information on the microscope slide used for attaching the tissue section as an output.

10 . The attachment method according to claim 8 , wherein

the image of the cut surface is an image captured from above a sample block of the sample or above a cutter that cuts the sample block.