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1.
Artículo en Chino | WPRIM (Pacífico Occidental) | ID: wpr-826337

RESUMEN

To make a preliminary pathological classification of lung adenocarcinoma with pure ground glass nodules(pGGN)on CT by using a deep learning model. CT images and pathological data of 219 patients(240 lesions in total)with pGGN on CT and pathologically confirmed adenocarcinoma were collected.According to pathological subtypes,the lesions were divided into non-invasive lung adenocarcinoma group(which included atypical adenomatous hyperplasia and adenocarcinoma in situ and micro-invasive adenocarcinoma)and invasive lung adenocarcinoma group.First,the lesions were outlined and labeled by two young radiologists,and then the labeled data were randomly divided into two datasets:the training set(80%)and the test set(20%).The prediction Results of deep learning were compared with those of two experienced radiologists by using the test dataset. The deep learning model achieved high performance in predicting the pathological types(non-invasive and invasive)of pGGN lung adenocarcinoma.The accuracy rate in pGGN diagnosis was 0.8330(95% =0.7016-0.9157)for of deep learning model,0.5000(95% =0.3639-0.6361)for expert 1,0.5625(95% =0.4227-0.6931)for expert 2,and 0.5417(95% =0.4029-0.6743)for both two experts.Thus,the accuracy of the deep learning model was significantly higher than those of the experienced radiologists(=0.002).The intra-observer agreements were good(Kappa values:0.939 and 0.799,respectively).The inter-observer agreement was general(Kappa value:0.667)(=0.000). The deep learning model showed better performance in predicting the pathological types of pGGN lung adenocarcinoma compared with experienced radiologists.


Asunto(s)
Humanos , Adenocarcinoma del Pulmón , Aprendizaje Profundo , Neoplasias Pulmonares , Estudios Retrospectivos , Tomografía Computarizada por Rayos X
2.
Zhonghua Yi Xue Za Zhi ; 93(19): 1494-8, 2013 May 21.
Artículo en Chino | MEDLINE | ID: mdl-24029576

RESUMEN

OBJECTIVE: To explore the osteogenetic capacity of cross-linked adjustable anti-tuberculosis drug sustained-release artificial composite (TPB/SA-RFP/PLA). METHODS: The model of femur bone defect was established in rabbits.TPB/SA-RFP/PLA complex was implanted into defect parts in the experimental group while TPB/SA/PLA in the blank control group. At Weeks 4, 8 and 12, gross specimens received radiographic, histological and immunohistochemical examinations to determine the osteogenetic performance of TPB/SA-RFP/PLA. RESULTS: As compared with the control group, TPB/SA-RFP/PLA complex had excellent osteogenic capacities while the TPB/SA/PLA group had no obvious osteogenic difference. Lane-sandhu histological and radiographic ratings demonstrated significant difference between TPB/SA-RFP/PLA (8.3 ± 0.3) and blank groups (2.2 ± 0.4) (P < 0.05). And TPB/SA/PLA showed no significant intragroup significance (P > 0.05). Two groups immunohistochemical Alkaline phosphatase was strongly positive in two test groups and weakly positive in the control group. CONCLUSION: TPB/ SA-RFP/PLA has excellent profiles of bone conductivity and regeneration.And the incorporation of rifampin does not affect its osteogenetic capacity.


Asunto(s)
Antibióticos Antituberculosos/farmacología , Regeneración Ósea/efectos de los fármacos , Osteogénesis/efectos de los fármacos , Rifampin/farmacología , Animales , Antibióticos Antituberculosos/administración & dosificación , Órganos Artificiales , Preparaciones de Acción Retardada , Nanoestructuras , Conejos , Rifampin/administración & dosificación , Ingeniería de Tejidos
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