US 12,327,618 B2
Systems and methods for tissue sample processing
Matthew O. Leavitt, Salt Lake City, UT (US); and Sorin Musat, Bucharest (RO)
Assigned to LEAVITT MEDICAL, INC., Lehi, UT (US)
Filed by Leavitt Medical, Inc., Lehi, UT (US)
Filed on Mar. 15, 2024, as Appl. No. 18/607,070.
Application 18/607,070 is a division of application No. 16/984,134, filed on Aug. 3, 2020, granted, now 11,935,632.
Application 16/984,134 is a division of application No. 15/893,061, filed on Feb. 9, 2018, granted, now 10,734,100, issued on Jul. 15, 2020.
Claims priority of provisional application 62/556,910, filed on Sep. 11, 2017.
Claims priority of provisional application 62/457,078, filed on Feb. 9, 2017.
Prior Publication US 2024/0221876 A1, Jul. 4, 2024
Int. Cl. B01L 3/00 (2006.01); A61B 6/00 (2024.01); A61B 8/00 (2006.01); B01F 23/00 (2022.01); B01F 23/41 (2022.01); B01F 101/23 (2022.01); B23Q 17/24 (2006.01); C07K 14/705 (2006.01); C12M 1/34 (2006.01); C12Q 1/04 (2006.01); C12Q 1/18 (2006.01); C12Q 1/686 (2018.01); G01N 1/31 (2006.01); G01N 21/3577 (2014.01); G01N 21/359 (2014.01); G01N 21/39 (2006.01); G01N 21/45 (2006.01); G01N 21/64 (2006.01); G01N 21/77 (2006.01); G01N 21/78 (2006.01); G01N 27/414 (2006.01); G01N 27/62 (2021.01); G01N 30/12 (2006.01); G01N 30/68 (2006.01); G01N 30/70 (2006.01); G01N 30/72 (2006.01); G01N 30/88 (2006.01); G01N 33/00 (2006.01); G01N 33/18 (2006.01); G01N 33/50 (2006.01); G01N 33/53 (2006.01); G01N 33/543 (2006.01); G01N 33/68 (2006.01); G01N 33/74 (2006.01); G01N 35/00 (2006.01); G01N 35/10 (2006.01); G06K 7/10 (2006.01); G06K 7/14 (2006.01); G06K 19/06 (2006.01); G06K 19/07 (2006.01); G06T 7/00 (2017.01); G06T 7/90 (2017.01); G16H 10/40 (2018.01); G16H 10/60 (2018.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01); G16H 80/00 (2018.01); H01J 49/00 (2006.01); H04M 17/00 (2024.01); H10K 10/46 (2023.01); H10K 85/00 (2023.01); H10K 85/20 (2023.01)
CPC G16H 10/40 (2018.01) [A61B 6/5252 (2013.01); A61B 8/5292 (2013.01); B01L 3/508 (2013.01); G01N 1/312 (2013.01); G01N 35/00029 (2013.01); G01N 35/00732 (2013.01); G01N 35/00871 (2013.01); G16H 10/60 (2018.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01); G16H 80/00 (2018.01); H04M 17/307 (2013.01); B01L 2300/021 (2013.01); B01L 2300/12 (2013.01); G01N 2035/00772 (2013.01); G01N 2035/00831 (2013.01); G01N 2035/00851 (2013.01); G01N 2035/00881 (2013.01)] 9 Claims
OG exemplary drawing
 
1. A method for tissue sample processing, comprising:
providing a matrix for receiving a tissue sample, wherein the matrix has a sectionable code and
measurement marks positioned in the matrix at predetermined initial intervals, and wherein the matrix is configured to exhibit a shrinkage rate substantially the same as a shrinkage rate of the tissue sample when subjected to a pathological process; taking a first image of the tissue sample in the matrix; transmitting the first image to a central network including at least a processor and a database;
wherein the processor is programmed to process images of the tissue sample and matrix so as to one or more of: interpret measurement marks, distinguish between the tissue sample and adjacent portions of the matrix, measure features of the tissue sample, or identify the sectionable code in the matrix;
and wherein the processor further is programmed to correlate the tissue sample and images thereof with a particular sectionable code in the corresponding matrix, for digitally registering the matrix and the tissue sample and correlating the matrix and the tissue sample to a patient from which the tissue sample was obtained and wherein said processor is programmed through machine learning;
identifying, from the first image, the sectionable code with the processor;
digitally storing the sectionable code in the database; correlating the stored sectionable code with identification information of a patient from which the tissue sample was obtained;
taking a second image of the tissue sample in the matrix having the sectionable code and measurement marks after at least some pathological processing;
transmitting the second image to the central network;
identifying, from the second image, the sectionable code with the processor;
identifying, from the second image, the measurement marks with the processor; and
correlating the second image with the identification information of the patient from which the tissue sample was obtained.