Deep learning and black-blood magnetic resonance thrombus imaging can be used for predicting the staging of deep vein thrombosis in the lower limbs
Objective To construct a staging prediction model on deep vein thrombosis(DVT)based on the deep learning and black-blood magnetic resonance thrombus imaging(BTI),and investigate its prediction value.Methods A retrospective observational study was conducted,where clinical data and BTI from 196 patients admitted to Guangzhou Panyu Central Hospital from November 2015 to July 2022 were collected and analyzed.The dataset was split into a training set(70%,n=136),a validation set(15%,n=30),and a test set(15%,n=30).The experimental group were annotated in rectangular boxes manually,then the corresponding minimum bounding rectangular boxes of the lesion areas were cropped,resized,and sliced,and input to the deep learning model.The three models,ResNet50,Vit and EfficientNet,were established for lower limb staging prediction.Their predict value were compared by accuracy rate and the area under the curve(AUC).Results The accuracy of ResNet50,Vit and EfficientNet-b0 in the testing set were 0.693,0.733,0.787.The EfficientNet-b0 outperforms than other two models in the test set.The area under the curve of the acute,sub-acute and chronic phase were 0.700(0.568-0.811),0.778(0.652-0.875),0.850(0.737-0.914),respectively.Conclusion Deep learning combined with BTI has certain application values in staging prediction of DVT.It provides an effective technique for the precisive staging for DVT.
deep learningMRIlower limbs deep vein thrombosisthrombosis staging
国家科技期刊平台
NSTL
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