Evaluation of human epidermal growth factor receptor 2 status of breast cancer using preoperative multidetector computed tomography with deep learning and handcrafted radiomics features

Objective:To evaluate the human epidermal growth factor receptor 2(HER2)status in patients with breast cancer using multidetector computed tomography(MDCT)-based handcrafted and deep radiomics features.Methods:This retrospective study enrolled 339 female patients(primary cohort,n=177;validation cohort,n=162)with pathologically confirmed invasive breast cancer.Handcrafted and deep radiomics features were extracted from the MDCT images during the arterial phase.After the feature selection procedures,handcrafted and deep radiomics signatures and the combined model were built using multivariate logistic regression analysis.Performance was assessed by measures of discrimination,calibration,and clinical usefulness in the primary cohort and validated in the validation cohort.Results:The handcrafted radiomics signature had a discriminative ability with a C-index of 0.739[95%confidence interval(95%CI):0.661-0.818]in the primary cohort and 0.695(95%CI:0.609-0.781)in the validation cohort.The deep radiomics signature also had a discriminative ability with a C-index of 0.760(95%CI:0.690-0.831)in the primary cohort and 0.777(95%CI:0.696-0.857)in the validation cohort.The combined model,which incorporated both the handcrafted and deep radiomics signatures,showed good discriminative ability with a C-index of 0.829(95%CI:0.767-0.890)in the primary cohort and 0.809(95%CI:0.740-0.879)in the validation cohort.Conclusions:Handcrafted and deep radiomics features from MDCT images were associated with HER2 status in patients with breast cancer.Thus,these features could provide complementary aid for the radiological evaluation of HER2 status in breast cancer.

Optics‑guided Robotic System for Dental Implant Surgery

At present,dental implant surgery mainly relies on the clinical experience of the doctor and the assistance of preoperative medical imaging.However,there are some problems in dental implant surgery,such as narrow space,sight obstruction,inaccurate positioning,and high requirements of doctors’proficiency.Therefore,a dental implant robot system(DIRS)guided by optical navigation is developed in this study,with an x-shaped tool and an irregular pentagonal tracer are designed for spatial registration and needle tip positioning strategy respectively.The coordinate system of each unit in DIRS is unified through system calibration,spatial registration,and needle tip positioning strategy.Then the surgical path is planned on the computed tomography(CT)images in the navigation software before operation.The automatic positioning method and the auxiliary positioning method can be used in the operation to achieve accurate positioning and assist doctors to complete the operation.The errors of spatial registration,needle tip positioning strategy,and the overall accuracy of the system were evaluated respectively,and the results showed that they all met the needs of clinical surgery.This study preliminarily verified the feasibility of the precise positioning method for dental surgery robots and provided certain ideas for subsequent related research.