FIELD OF THE DISCLOSURE

Various embodiments of the present disclosure pertain generally to image processing methods. More specifically, particular embodiments of the present disclosure relate to systems and methods for continuous biomarker prediction based on processing images of tissue specimens.

BACKGROUND

Biomarkers are measurable indicators of disease state that may help guide treatment. Biomarker interpretation may be binary (present/absent) or continuous, the latter providing greater information to the clinician and patient. In oncology, many biomarkers are genomic in nature and furthermore, are measured from formalin fixed paraffin embedded (FFPE) tissue found within histology blocks in tumor tissue visualized using hematoxylin and eosin (H&E) or other tissue staining schemes. Some examples may include OncoType DX, Breast Cancer Index, and the Prosigna Breast Cancer Prognostic Gene Signature Assay, all of which provide continuous measures for recurrence of breast cancer, as well as homologous recombination deficiency (HRD), which indicates the severity of the mutations present that impair normal DNA damage repair, and tumor mutation burden (TMB), which measures the total number of mutations found in the DNA of cancer cells.

These biomarkers and many others are measured from FFPE tumor tissue. This may require comprehensive histologic assessment of salient regions (e.g., invasive tumor, stroma around an invasive tumor, the invasive tumor margin, etc.) by a pathologist. After histologic assessment, which may take days, for genomic tests the tissue may be sent (e.g., mailed) to an external lab to perform tumor extraction and molecular testing. These steps are expensive, have aspects of subjectivity in terms of pathologic assessment of the tissue specimen, and may result in a large time lag between tissue removal and the results of the assay being sent to the clinician and patient.

One or more exemplary embodiments of the present disclosure may overcome the problems described above.

The background description provided herein is for the purpose of generally presenting the context of the disclosure. Unless otherwise indicated herein, the materials described in this section are not prior art to the claims in this application and are not admitted to be prior art, or suggestions of the prior art, by inclusion in this section.

SUMMARY

According to certain aspects of the present disclosure, systems and methods are disclosed for processing digital images to predict at least one continuous value.

A computer-implemented method for method for processing digital images to predict at least one continuous value comprising receiving one or more digital medical images, determining whether the one or more digital medical images includes at least one salient region, upon determining that the one or more digital medical images includes the at least one salient region, predicting, by a trained machine learning system, at least one continuous value corresponding to the at least one salient region, and outputting the at least one continuous value to an electronic storage device and/or display.

A computer system for processing digital images to predict at least one continuous value for one or more digital medical images comprising at least one memory storing instructions, and at least one processor configured to execute the instructions to perform operations comprising access the at least one memory and execute processor-readable instructions, which when executed by the at least one processor configures the at least one processor to perform a plurality of functions, including functions for: receiving one or more digital medical images, determining whether the one or more digital medical images includes at least one salient region, upon determining that the one or more digital medical images includes the at least one salient region, predicting, by a trained machine learning system, at least one continuous value corresponding to the at least one salient region, and outputting the at least one continuous value to an electronic storage device and/or display.

A non-transitory computer-readable medium storing instructions that, when executed by a processor, cause the processor to perform operations for processing digital images to predict at least one continuous value for one or more digital medical images comprising: receiving one or more digital medical images, determining whether the one or more digital medical images includes at least one salient region, upon determining that the one or more digital medical images includes the at least one salient region, predicting, by a trained machine learning system, at least one continuous value corresponding to the at least one salient region, and outputting the at least one continuous value to an electronic storage device and/or display.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosed embodiments, as claimed.

