Systems and methods for event-based tissue activity quantification

Abstract

Systems and methods for event-based tissue activity quantification are disclosed comprising obtaining a plurality of images of tissue activity of a tissue over a first time period and having at least two spatial dimensions and a temporal dimension. A response matrix is generated from the plurality of images, each element within the response matrix comprising a time series of tissue activity values determined along the temporal dimension of the plurality of images at a respective spatial location within the at least two spatial dimensions. A plurality of events within the response matrix is identified, wherein each event is associated with a plurality of spatiotemporally contiguous locations within the response matrix at which a predetermined event criterion is met. A first descriptor is generated based on the plurality of events, wherein the first descriptor quantifies tissue activity of the tissue over the first time period.

Description

A system and method for event-based quantification of organizational activity are disclosed, comprising: acquiring multiple images of organizational activity within a first time period, the multiple images having at least two spatial dimensions and a temporal dimension; generating a response matrix based on the multiple images, each element of the response matrix comprising a time series of organizational activity values ​​determined along the temporal dimension of the multiple images at a corresponding spatial location within at least two spatial dimensions; identifying multiple events within the response matrix, wherein each event is associated with multiple spatiotemporally consecutive locations within the response matrix that satisfy predetermined event criteria; and generating a first descriptor based on the multiple events, wherein the first descriptor quantifies the organizational activity of the organization within the first time period.

Claims

CLAIMS 1. A method for event-based quantification of tissue activity, the method comprising: obtaining, by one or more processors, a plurality of images of tissue activity of a tissue over a first time period, the plurality of images having at least two spatial dimensions and a temporal dimension; generating, by the one or more processors, a response matrix from the plurality of images, each element within the response matrix comprising a time series of tissue activity values determined along the temporal dimension of the plurality of images at a respective spatial location within the at least two spatial dimensions; identifying, by the one or more processors, a plurality of events within the response matrix, wherein each event of the plurality of events is associated with a plurality of spatiotemporally contiguous locations within the response matrix at which a predetermined event criterion is met; and generating, by the one or more processors, a first descriptor based on the plurality of events, wherein the first descriptor quantifies tissue activity of the tissue over the first time period.

2. The method of claim 1 further comprising: outputting, by the one or more processors, the first descriptor.

3. The method of claim 1 wherein the plurality of images are calcium response images of the tissue.

4. The method of claim 3 wherein the tissue activity is related to calcium activity such that the first descriptor quantifies calcium response of the tissue over the first time period.

5. The method of claim 1 wherein the plurality of images are voltage response images of the tissue.

6. The method of claim 5 wherein the tissue activity is voltage activity such that the first descriptor quantifies voltage response of the tissue over the first time period.

7. The method of claim 1 wherein the tissue is associated with a first set of conditions over the first time period.

8. The method of claim 7 wherein the first set of conditions comprises one or more of: a reference condition, a drug treatment; a disease model; or a cell line.

9. The method of claim 7 further comprising: obtaining, by the one or more processors, a second descriptor associated with tissue activity of the tissue under a second set of conditions over a second time period; and determining, by the one or more processors, a functional change in the tissue based on a comparison of the first descriptor and the second descriptor, wherein the functional change is indicative of a change from the first set of conditions to the second set of conditions.

10. The method of claim 9 further comprising: determining, by the one or more processors, an effect associated with the change from the first set of conditions to the second set of conditions based on the functional change.

11. The method of claim 10 further comprising: outputting, by the one or more processors, the functional change and / or the effect.

12. The method of claim 9 wherein the second set of conditions comprises one or more of: a drug treatment; a disease model; or a cell line.

13. The method of claim 1 wherein the first descriptor comprises a value associated with a homogeneity or heterogeneity feature indicative of a local similarity or diversity of the plurality of events.

14. The method of claim 1 wherein the first descriptor comprises a value associated with a relative intracellular calcium concentration feature indicative of a relative difference in intracellular calcium release.

15. The method of claim 1 further comprising: extracting, by the one or more processors, one or more patterns from the plurality of events, each of the one or more patterns comprising one or more spatially related events within the plurality of events.

16. The method of claim 15 wherein the first descriptor is further based on the one or more patterns.

17. The method of claim 16 wherein the first descriptor comprises a periodicity value indicative of firing rates of the one or more patterns.

18. The method of claim 16 wherein the first descriptor comprises a value associated with a dysfunction feature indicative of an extent of the one or more patterns.

19. The method of claim 16 wherein the first descriptor comprises a ratio of a number of events within a first group of the one or more patterns to a number of events within a second group of the one or more patterns.

20. The method of claim 15 further comprising: generating, by the one or more processors, an event matrix from the plurality of events such that a first value at a first location within the event matrix is indicative of the first location being associated with an event within the plurality of events; wherein the one or more patterns are extracted from the event matrix.

21. The method of claim 20 further comprising: applying, by the one or more processors, one or more noise filtering operations to the event matrix.

22. The method of claim 21 wherein the one or more noise filtering operations include one or more of a convolution operation and a thresholding operation.

23. The method of claim 20 further comprising: convolving, by the one or more processors, the event matrix with one or more predetermined kernels thereby spatially and temporally expanding each event within the event matrix.

24. The method of claim 15 wherein the extracting one or more patterns from the plurality of events further comprises: when a relative spatial overlap between a first event of the plurality of events and a second event of the plurality of events meets a predetermined overlap threshold, linking, by the one or more processors, the first event and the second event to form a first pattern of the one or more patterns.

25. The method of claim 24 wherein the relative spatial overlap comprises a ratio of a number of spatial locations shared by the first event and the second event to a total number of spatial locations involving either the first event or the second event.

26. The method of claim 24 wherein the predetermined overlap threshold is greater than 0% and less than or equal to 5%.

27. The method of claim 24 wherein the predetermined overlap threshold is 1%.

28. The method of claim 15 further comprising: generating, by the one or more processors, one or more graphical representations of the plurality of events and / or the one or more patterns; and outputting, by the one or more processors, the one or more graphical representations for display to a user.

29. The method of claim 1 further comprising, prior to generating the response matrix:downsampling, by the one or more processors, the plurality of images by a predetermined factor.

30. The method of claim 29 wherein the predetermined factor is between 2 and 6.

31. The method of claim 29 wherein the predetermined factor is 4.

32. The method of claim 1 further comprising, prior to generating the response matrix: normalizing, by the one or more processors, each image in the plurality of images.

33. The method of claim 1 further comprising, prior to identifying the plurality of events: filtering, by the one or more processors, the response matrix using a local filtering strategy.

34. The method of claim 33 wherein the local filtering strategy applies a low-pass filter to each element within the response matrix.

35. The method of claim 1 wherein the predetermined event criterion comprises a local maxima criterion.

36. The method of claim 1 wherein the predetermined event criterion comprises a threshold criterion.

37. The method of claim 1 wherein the tissue is an engineered tissue.

38. The method of claim 37 wherein the plurality of images are obtained from a bioreactor containing the engineered tissue.

39. The method of claim 37 wherein the engineered tissue is an engineered cardiac tissue.

40. The method of claim 37 wherein the engineered tissue is an engineered skeletal tissue.

41. The method of claim 1 wherein the tissue is an in vivo tissue.

42. A non-transitory computer readable medium storing computing instructions which, when executed by one or more processors, cause the one or more processors to: obtain a plurality of images of tissue activity of a tissue over a first time period, the plurality of images having at least two spatial dimensions and a temporal dimension; generate a response matrix from the plurality of images, each element within the response matrix comprising a time series of tissue activity values determined along the temporal dimension of the plurality of images at a respective spatial location within the at least two spatial dimensions; identify a plurality of events within the response matrix, wherein each event of the plurality of events is associated with a plurality of spatiotemporally contiguous locations within the response matrix at which a predetermined event criterion is met; and generate a first descriptor based on the plurality of events, wherein the first descriptor quantifies tissue activity of the tissue over the first time period.

43. A device comprising one or more processors and a memory storing computing instructions which, when executed by the one or more processors, cause the one or more processors to: obtain a plurality of images of tissue activity of a tissue over a first time period, the plurality of images having at least two spatial dimensions and a temporal dimension; generate a response matrix from the plurality of images, each element within the response matrix comprising a time series of tissue activity values determined along the temporal dimension of the plurality of images at a respective spatial location within the at least two spatial dimensions; identify a plurality of events within the response matrix, wherein each event of the plurality of events is associated with a plurality of spatiotemporally contiguous locations within the response matrix at which a predetermined event criterion is met; andgenerate a first descriptor based on the plurality of events, wherein the first descriptor quantifies tissue activity of the tissue over the first time period.

44. A system for event-based tissue activity quantification, the system comprising: a bioreactor comprising: a device configured for growing tissue; and a sensor assembly configured to obtain tissue activity images of a tissue within the device; and a control unit communicatively coupled to the bioreactor, wherein the control unit comprises one or more processors and a memory storing computing instructions, which when executed by the one or more processors, causes the one or more processors to: obtain a plurality of images of tissue activity of a tissue over a first time period, the plurality of images having at least two spatial dimensions and a temporal dimension, generate a response matrix from the plurality of images, each element within the response matrix comprising a time series of tissue activity values determined along the temporal dimension of the plurality of images at a respective spatial location within the at least two spatial dimensions, identify a plurality of events within the response matrix, wherein each event of the plurality of events is associated with a plurality of spatiotemporally contiguous locations within the response matrix at which a predetermined event criterion is met, and generate a first descriptor based on the plurality of events, wherein the first descriptor quantifies tissue activity of the tissue over the first time period.

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