3 results about "Well differentiated" patented technology

The present disclosure relates to a method of treating highly differentiated G2 or G3 neuroendocrine neoplasms (NET) in a patient in need thereof, the method comprising administering to the patient a treatment of a radioligand therapy (RLT) agent comprising a therapeutically effective dose of a targeted somatostatin receptor (SSTR), in particular [177Lu] Lu-DOTA0-Tyr3-octoic acid, as a first-tier therapy.

The application discloses a prognosis prediction model for medium-highly differentiated esophageal squamous cell carcinoma (ESCC) and a construction method and application thereof, and the construction method comprises the following steps: establishing an input module, establishing an analysis module and establishing an output module, and specific contents are described in the body of the application. The application detects whether 12q13.13 amplification occurs in the esophageal squamous cell carcinoma, so as to predict the prognosis of the medium-highly differentiated ESCC. Compared with the medium-highly differentiated ESCC patients without 12q13.13 amplification, the prognosis of the medium-highly differentiated ESCC patients with 12q13.13 amplification is poorer. The application can provide certain help for diagnosis and prognosis evaluation of the medium-highly differentiated esophageal squamous cell carcinoma patients.

The invention discloses a gastric cancer pathological tissue biopsy digital image analysis method, and relates to the field of image segmentation. The method mainly comprises the following steps: acquiring a pathological grayscale image; determining a first evaluation index according to the distribution deviation of the gray values in the connected domain; determining a second evaluation index according to the local saliency features at the pixel points in the connected domain and the overall gray level gradient trend; performing segmentation based on a comprehensive judgment index determined by the first evaluation index and the second evaluation index to obtain a region of interest; sequentially screening out a first type of regions and a second type of regions from all the regions of interest; dividing the second type of region into a low differentiation cell region and a suspected high differentiation cell region according to the area of the second type of region; and based on the local density of the pixel points in the suspected highly-differentiated cell region, segmenting the highly-differentiated cell region. According to the invention, region segmentation is carried out according to the wettability growth and shape features of the lesion region in the pathological grayscale image, and the segmentation precision of the pathological grayscale image is improved.