-
公开(公告)号：US20240202920A1
公开(公告)日：2024-06-20
申请号：US18542088
申请日：2023-12-15
Applicant: Genentech, Inc. , Ventana Medical Systems, Inc. , Hoffmann-La Roche Inc.
Inventor： Xiao LI , Yao NIE , Karol BADOWSKI
CPC classification number: G06T7/0012 , G06T7/11 , G06T7/194 , G06T7/62 , G06T7/77 , G06T2207/30096
Abstract: A method may include identifying, within an image of a biological sample, a plurality of mitotic figures associated with a tumor tissue present in the biological sample. Each mitotic figure of the plurality of mitotic figures may correspond to a tumor cell that is undergoing mitosis. A mitotic metric quantifying a spatial distribution of the plurality of mitotic figures within the biological sample may be determined based on the plurality of mitotic figures in the biological sample. A tumor grade for the tumor tissue present in the biological sample may be determined based on the mitotic metric. In some cases, at least one of a disease diagnosis, a disease progression, a disease burden, a treatment response, and a survival prognosis for a patient associated with the biological sample may be determined based on the tumor grade. Related systems and computer program products are also provided.
-
公开(公告)号：US20230140977A1
公开(公告)日：2023-05-11
申请号：US17987647
申请日：2022-11-15
Applicant: Genentech, Inc.
Inventor： Xiao LI
CPC classification number: G06T7/0012 , G16H50/20 , G06V20/698 , G06T2207/30024 , G06T2207/10056
Abstract: Systems and methods relate to processing digital pathology images. More specifically, depictions of objects of a first class (e.g., lymphocytes) and depictions of objects of a second class (e.g., tumor cells) are detected. Locations of each biological object depiction are identified, which are used to generate multiple spatial-distribution metrics that characterize where depictions of objects of a first class are located relative to objects of a second class. The spatial-distribution metrics are used to generate a result corresponding to a predicted biological state of or a potential treatment of a subject. For example, the result may predict whether and/or an extent to which lymphocytes have infiltrated a tumor, whether checkpoint blockade therapy would be an effective treatment for the subject, and/or whether a subject is eligible for a clinical trial.
-
Patent Agency Ranking
公开(公告)号：US20240346804A1
公开(公告)日：2024-10-17
申请号：US18612987
申请日：2024-03-21
Applicant: Genentech, Inc.
Inventor： Jeffrey Ryan EASTHAM , Hartmut KOEPPEN , Xiao LI , Darya Yuryevna ORLOVA
IPC: G06V10/764 , G06T7/00 , G06V10/25
CPC classification number: G06V10/764 , G06T7/0012 , G06V10/25 , G06T2207/20081 , G06T2207/30096
Abstract: Described herein are systems, methods, and programming describing various pipelines for determining an immunophenotype of a tumor depicted by a digital pathology image based on immune cell density in the tumor epithelium and/or the tumor stroma and/or spatial information across all or part of the image. One or more machine learning models may be implemented by some or all of the pipelines. The pipelines may include a first pipeline using density thresholds for immunophenotyping, a second pipeline using immune cell density in tumor epithelium and tumor stroma for immunophenotyping, a third pipeline using spatial information of the digital pathology image for immunophenotyping, and a fourth pipeline that combines aspects of the second and third pipelines for immunophenotyping.
-
公开(公告)号：US20240046671A1
公开(公告)日：2024-02-08
申请号：US18491609
申请日：2023-10-20
Applicant: Genentech, Inc.
Inventor： Xiao LI , Darya Yuryevna ORLOVA , Joaquin PECHUAN JORGE , Rajiv Edillon JESUDASON
CPC classification number: G06V20/698 , G06T7/11 , G06T2207/10056
Abstract: A method for high dimensional spatial analysis includes segmenting, into a plurality of segments, an image depicting a plurality of cells comprising a biological sample. Each segment of the plurality of segments may correspond to one cell of the plurality of cells. A phenotype for each cell of the plurality of cells depicted in the image may be determined based on the segmented image. The determining of the phenotype may include identifying, within the plurality of cells, a first cell type having a first phenotype and a second cell type having a second phenotype. One or more metrics, such as a colocation quotient or an Earth Mover's Distance, quantifying a co-occurrence pattern between the first cell type and the second cell type may be determined. A visual representation of the co-occurrence pattern between the first cell type and the second cell type may be generated based on the metric.
-
公开(公告)号：US20240087726A1
公开(公告)日：2024-03-14
申请号：US18506905
申请日：2023-11-10
Applicant: Genentech, Inc. , Hoffmann-La Roche Inc. , Ventana Medical Systems, Inc.
Inventor： Paolo Santiago Syjuco OCAMPO , Bernhard STIMPEL , Yao NIE , Fahime SHEIKHZADEH , Xiao LI , Przemyslaw SZOSTAK , Prasanna PORWAL , Faranak AGHAEI
CPC classification number: G16H30/40 , G06T7/0012 , G16H20/00 , G16H50/20
Abstract: A method includes accessing a digital pathology image that depicts tumor cells sampled from a subject. A plurality of patches may be selected from the digital pathology image, wherein each of the patches depicts tumor cells. A mutation prediction may be generated for each of the patches, wherein the mutation prediction represents a prediction of a likelihood that an actionable mutation appears in the patch. Based on the plurality of mutation predictions, a prognostic prediction related to one or more treatment regimens for the subject may be generated. The prognostic prediction may be based on determining one or more mutational contexts of the digital pathology image as an unknown driver or a tumor suppressor, an oncogene driver mutation, or a gene fusion.
-
公开(公告)号：US20240079138A1
公开(公告)日：2024-03-07
申请号：US18139873
申请日：2023-04-26
Applicant: Genentech, Inc. , Hoffmann-La Roche Inc. , Ventana Medical Systems, Inc.
Inventor： Yao NIE , Xiao LI , Trung Kien NGUYEN , Fabien GAIRE , Eldad KLAIMAN , Ido BEN-SHAUL , Jacob GILDENBLAT , Ofir Etz HADAR
CPC classification number: G16H50/20 , G06T7/0012 , G16H30/40 , G06T2207/20084
Abstract: Systems and methods relate to predicting disease progression by processing digital pathology images using neural networks. A digital pathology image that depicts a specimen stained with one or more stains is accessed. The specimen may have been collected from a subject. A set of patches are defined for the digital pathology image. Each patch of the set of patches depicts a portion of the digital pathology image. For each patch of the set of patches and using an attention-score neural network, an attention score is generated. The attention-score neural network may have been trained using a loss function that penalized attention-score variability across patches in training digital pathology images labeled to indicate no or low subsequent disease progression. Using a result-prediction neural network and the attention scores, a result is generated that represents a prediction of whether or an extent to which a disease of the subject will progress.
-
公开(公告)号：US20230143860A1
公开(公告)日：2023-05-11
申请号：US17986737
申请日：2022-11-14
Applicant: Genentech, Inc. , Hoffmann-La Roche Inc.
Inventor： Xiao LI , Jian DAI , Fabien GAIRE
CPC classification number: G06T7/0012 , G16H50/20 , G06V20/698 , G06T2207/10024 , G06T2207/10056 , G06T2207/30096
Abstract: Systems and methods relate to processing digital pathology mages. More specifically, depictions of objects of a first class (e.g., lymphocytes) and depictions of objects of a second class (e.g., tumor cells) are detected. Locations of each biological object depiction are identified, which are used to generate multiple spatial-distribution metrics that characterize where depictions of objects of a first class are located relative to objects of a second class. The spatial-distribution metrics are used to generate a result corresponding to a predicted biological state of or a potential treatment of a subject. For example, the result may predict whether and/or an extent to which lymphocytes have infiltrated a tumor, whether checkpoint blockade therapy would be an effective treatment for the subject, and/or whether a subject is eligible for a clinical trial.
-
-
-
-
-
-
Search Results
7
records
(took 0.011 seconds)
