Systems and methods for tissue sample processing
Tissue sample management systems include a central network, a medical professional system, and a pathology lab system for processing a tissue sample in a matrix having a sectionable code. At least the pathology lab system includes at least one imaging device, and the central network is configured to process images from the at least one imaging device to identify and record at least the sectionable code of the matrix. Methods for tissue sample processing include providing a matrix having a sectionable code and measurement marks, the matrix for receiving a tissue sample, and identifying the sectionable code from an image taken of the tissue sample in the matrix. Tissue sample-receiving matrices include a sectionable alphanumeric code or bar code, a tissue sample receptacle, and measurement marks formed along a sidewall thereof. The matrices include one or more proteins and one or more lipids.
1. A tissue sample management system comprising:
a central network including at least a central processor and a database;
a medical professional system in communication with the central network, the medical professional system including at least one first data input device, the at least one first data input device configured for inputting information about a tissue sample received in a matrix that includes sectionable code, wherein the sectionable code comprises a portion of the matrix that is configured to be embedded with the tissue sample after tissue processing, wherein the sectionable code further comprises a representation of data that is configured to be present in each section made of the matrix that also includes portions of the tissue sample; and
a pathology lab system in communication with the central network, the pathology lab system including at least one imaging device and at least one second data input device, the at least one imaging device configured for taking images of at least one section of the tissue sample and the corresponding matrix including the sectionable code;
wherein the central network is configured to receive data from the at least one first data input device and from the at least one second data input device and to automatically process the images taken by the at least one imaging device to identify and record at least the sectionable code of the matrix.
2. The system of claim 1 , further comprising a machine learning system in communication with the central network, the machine learning system configured to further process the images taken by the at least one imaging device to identify at least the sectionable code.
3. The system of claim 2 , wherein the machine learning system is further configured to identify, from the images taken by the at least one imaging device, measurement marks formed in the matrix.
4. The system of claim 2 , wherein the machine learning system is further configured to identify, from the images taken by the at least one imaging device, a location of cellular material of interest in the tissue sample.
5. The system of claim 2 , wherein the machine learning system is further configured to identify, from the images taken by the at least one imaging device, gross measurements of the tissue sample.
6. The system of claim 2 , wherein the machine learning system is further configured to distinguish the tissue sample from at least surrounding portions of the matrix.
7. The system of claim 2 , wherein the machine learning system is further configured to correlate an identified portion of the tissue sample with an original location of the identified portion of the tissue sample on an organ of a patient from which the tissue sample was received.
8. The system of claim 2 , wherein the machine learning system is further configured to determine an estimated value of the percent involvement of abnormal cellular material in the tissue sample.
9. The system of claim 1 , wherein the medical professional system further comprises at least one additional imaging device configured for taking images of the tissue sample and the corresponding matrix including the sectionable code.