AUTOMATED PROSTATE TISSUE REFERENCING FOR CANCER DETECTION AND DIAGNOSIS

• US 20120226709A1
• Filed: 01/05/2012
• Published: 09/06/2012
• Est. Priority Date: 01/05/2011
• Status: Active Grant

• Current Assignee: Board of Trustees of The University of Illinois
• Original Assignee: Board of Trustees of The University of Illinois
• Inventors: Bhargava, Rohit, Kwak, Jin Tae, Sinha, Saurabh
• Granted Patent: US 9,779,283 B2
• Time in Patent Office: Days
• US Class Current: 707/769
• CPC Class Codes: G06F 18/211 Selection of the most significant subset of features
• CPC Class Codes: G06F 18/251 of input or preprocessed data
• CPC Class Codes: G06T 2207/30081 Prostate
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G06T 7/60 Analysis of geometric attributes
• CPC Class Codes: G06V 10/771 Feature selection, e.g. selecting representative features from a multi-dimensional feature space
• CPC Class Codes: G06V 10/803 of input or preprocessed data
• CPC Class Codes: G06V 20/693 Acquisition
• CPC Class Codes: G06V 20/695 Preprocessing, e.g. image segmentation

Abstract

This application provides to a method for identifying one or more prostate tissue samples in a database that are closest to a test prostate sample, which can be used to aid pathologists when examining prostate tissues to attain reliable and consistent diagnoses of prostate cancer. Also provided are databases and computer algorithms that can be used with such methods.

Claims

1. A method of identifying one or more prostate tissue samples in a database that are most similar to a test prostate sample, comprising:

extracting at least 20 morphological features from the test prostate tissue sample;

determining similarities based on the morphological features between the test prostate sample and a plurality of prostate tissue samples in a database; and

retrieving from the database one or more prostate tissue samples in the database that are the most similar to the test prostate tissue sample.

2. The method of claim 1, wherein the morphological features comprise the morphological features listed in Table 1.

3. The method of claim 1, wherein the morphological features comprise size of epithelial cells, size of a nucleus, number of nuclei, distance to lumen, distance to epithelial cell boundary, number of isolated nuclei, fraction of distant nuclei, entropy of nuclei spatial distribution, size of a lumen, number of lumens, lumen roundness, lumen distortion, lumen minimum bounding circle ratio, lumen convex hull ratio, symmetric index of lumen boundary, symmetric index of lumen area, spatial association of lumens and cytoplasm-rich regions, number of stroma cells, minimum lumen distance, minimum gland distance, ratio of lumen to epithelial cells, ratio of epithelial cells to stroma cells, ratio of cell separation, ratio of sheets of cells, degree of cell dispersion and spatial autocorrelation of cells.

4. The method of claim 1, further comprising:

selecting a subset of the at least 20 morphological features from the plurality of prostate tissue samples in a database, and wherein determining similarities based on the morphological features between the test prostate sample and a plurality of prostate tissue samples in a database comprises determining similarities based on the selected subset of morphological features between the test prostate sample and a plurality of prostate tissue samples in a database.

5. The method of claim 1, further comprising outputting the one or more prostate tissue samples retrieved from the database to a computer screen.

6. The method of claim 1, wherein the one or more prostate tissue samples in the database retrieved are those having the most similar k to the test prostate tissue sample.

7. The method of claim 1, wherein the test prostate sample is suspected of being cancerous.

8. The method of claim 1, wherein the database comprises a plurality of Gleason grade 2, 3, 4, and 5 cancer samples, benign prostatic hyperplasia (BPH) samples, normal prostate samples, or combinations thereof.

9. The method of claim 1, wherein the database comprises:

morphological feature data for the plurality of prostate tissue samples;

H&

E stained images of the plurality of prostate tissue samples;

IR classified images of the plurality of prostate tissue samples;

clinical information for the plurality of prostate tissue samples;

or

combinations thereof.

10. The method of claim 1, wherein the test prostate tissue sample comprises an H&

E stained image, an IR classified image, or both.

11. The method of claim 1, further comprising selecting a subject suspected of having prostate cancer and obtaining the test prostate tissue sample from the subject.

12. The method of claim 1, wherein the test prostate tissue sample and/or the prostate tissue samples in the database are human samples.

13. The method of claim 1, further comprising obtaining IR data or immunohistochemical data from the test prostate tissue sample and/or the prostate tissue samples in the database.

14. The method of claim 1, further comprising comparing the retrieved prostate tissue samples in the database to the test prostate tissue sample.

15. The method of claim 1, wherein each of the steps is performed on a suitably programmed computer.

16. The method of claim 1, wherein the method has at least 90%, at least 95%, or at least 98% sensitivity.

17. The method of claim 1, wherein the method has at least 90%, at least 95%, or at least 98% specificity.

18. A database comprising:

digital images of a plurality of prostate cancer tissue samples, normal prostate tissue samples, and BPH tissue samples; and

data for at least 20 morphological features for each tissue sample in the database.

19. A computer-readable storage medium having instructions thereon for performing a method of identifying one or more prostate tissue samples in a database that are closest to a test prostate sample, comprising:

extracting a plurality of morphological features from a test prostate tissue sample;

retrieving a plurality of morphological features from a plurality of prostate tissue samples in a database;

comparing the plurality of morphological features from a test prostate tissue sample to the same plurality of morphological features from the plurality of prostate tissue samples in the database;

determining similarities based on the plurality of morphological features between the test prostate sample and a plurality of prostate tissue samples in the database; and

retrieving from the database one or more prostate tissue samples in the database that are the most similar to the test prostate tissue sample based on the plurality of morphological features.

20. The computer-readable storage medium of claim 19, further including comparing the retrieved prostate tissue samples from the database to the test prostate tissue sample.