Method for detecting a binding of antibodies from a patient sample to double-stranded DNA using Crithidia luciliae cells and fluorescence microscopy

A device for detecting a binding of autoantibodies from a patient sample to double-stranded deoxyribonucleic acid using Crithidia luciliae cells by means of fluorescence microscopy and by means of digital image processing, the device comprising:

• a mounting device for a substrate which has multiple Crithidia luciliae cells and which has been incubated with a patient sample having the autoantibodies and, furthermore, with secondary antibodies which have each been labelled with a green fluorescent dye;
• at least one image acquisition unit for acquiring a fluorescence image of the substrate in a green color channel which corresponds to the fluorescent dye;
• and
• at least one computing unit which is configured to:
• identify by means of a first pretrained convolutional neural network respective sub-images in the one fluorescence image that each represent at least one Crithidia luciliae cell;
• respectively process at least one subset of the respective sub-images by means of a second pretrained convolutional neural network for determining respective binding measures which indicate a respective extent of a binding of autoantibodies in a respective kinetoplast region of a respective Crithidia luciliae cell of a respective sub-image;
• and
• determine an overall binding measure of a binding of autoantibodies from the patient sample to double-stranded deoxyribonucleic acid on the basis of the respective binding measures.

A computing unit configured, in the course of a digital image processing, to:

• receive a fluorescence image which represents a staining of a substrate, which in turn has multiple Crithidia luciliae cells, by a green fluorescent dye;
• identify by means of a first pretrained convolutional neural network respective sub-images in the one fluorescence image that each represent at least one Crithidia luciliae cell;
• respectively process at least one subset of the respective sub-images by means of a second pretrained convolutional neural network for determining respective binding measures which indicate a respective extent of a binding of autoantibodies in a respective kinetoplast region of a respective Crithidia luciliae cell of a respective sub-image;
• and
• determine an overall binding measure of a binding of autoantibodies from the patient sample to double-stranded deoxyribonucleic acid on the basis of the respective binding measures.

A data network device comprising:

• at least one data interface for receiving a fluorescence image which represents a staining of a substrate, which in turn has multiple Crithidia luciliae cells, by a green fluorescent dye;
• and
• at least one computing unit configured, in the course of a digital image processing, to:
• identify by means of a first pretrained convolutional neural network respective sub-images in the one fluorescence image that each represent at least one Crithidia luciliae cell;
• respectively process at least one subset of the respective sub-images by means of a second pretrained convolutional neural network for determining respective binding measures which indicate a respective extent of a binding of autoantibodies in a respective kinetoplast region of a respective Crithidia luciliae cell of a respective sub-image;
• and
• determine an overall binding measure of a binding of autoantibodies from the patient sample to double-stranded deoxyribonucleic acid on the basis of the respective binding measures.

A method for digital image processing, comprising:

• receiving of a fluorescence image which represents a staining of a substrate, which in turn has multiple Crithidia luciliae cells, by a green fluorescent dye;
• identification by means of a first pretrained convolutional neural network of respective sub-images in the fluorescence image that each represent a Crithidia luciliae cell;
• respective processing of at least one subset of the respective sub-images by means of a second pretrained convolutional neural network for determining respective binding measures which indicate a respective extent of a binding of autoantibodies in a respective kinetoplast region of a respective Crithidia luciliae cell of a respective sub-image;
• and
• determination of an overall binding measure of a binding of autoantibodies from the patient sample to double-stranded deoxyribonucleic acid on the basis of the respective binding measures.