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The current study aimed to evaluate the association of endorectal ultrasound (EUS) radiomics features at different denoising filters based on machine learning algorithms and to predict radiotherapy response in locally advanced rectal cancer (LARC) patients.The EUS images of forty-three LARC patients, as a predictive biomarker for predicting the treatment response of neoadjuvant chemoradiotherapy (NCRT), were investigated. For despeckling, the EUS images were preprocessed by traditional filters (bilateral, wiener, lee, frost, median, and wavelet filters). The rectal tumors were delineated by two readers separately, and radiomics features were extracted. The least absolute shrinkage and selection operator were used for feature selection. Classifiers including logistic regression (LR), K-nearest neighbor (KNN), support vector machine (SVM), random forest, naive Bayes, and decision tree were trained using stratified fivefold cross-validation for model development. The area under the curve (AUC) of the receiver operating characteristic curve followed by accuracy, precision, sensitivity, and specificity were obtained for model performance assessment.The wavelet filter had the best results with means of AUC: 0.83, accuracy: 77.41%, precision: 82.15%, and sensitivity: 79.41%. LR and SVM by having AUC: 0.71 and 0.76; accuracy: 70.0% and 71.5%; precision: 75.0% and 73.0%; sensitivity: 69.8% and 80.2%; and specificity: 70.0% and 60.9% had the highest model's performance, respectively.This study demonstrated that the EUS-based radiomics model could serve as pretreatment biomarkers in predicting pathologic features of rectal cancer. The wavelet filter and machine learning methods (LR and SVM) had good results on the EUS images of rectal cancer.

For the treatment of giant cell tumour of the bone (GCTB) around the knee, preserving the native joint confers advantages over scarifying it. But, there is a controversy about the efficacy of intralesional curettage versus en bloc resection for treatment of such lesions. In this study, we compared local recurrence, functional outcomes, and complications of extended curettage and en bloc resection in these lesions. Patients with grade 3 GCTB of the distal femur or proximal tibia who were presented with a pathologic fracture and treated with either en bloc resection (n = 22) or extended curettage (n = 20) were included. The mean follow-up of the patients was 6.4 ± 1.9 years in the resection group and 5.5 ± 2.4 years in the extended curettage group. The primary outcome was a local recurrence. Secondary outcomes were limb function evaluated by the Musculoskeletal Tumor Society (MSTS) score and rate of complications. Local recurrence was seen in four (20%) patients of the curettage group and three (13.7%) patients of the resection group (P = 0.69). The mean MSTS score was 24 ± 1.9 in the resection group and 26.5 ± 1.3 in the curettage group (P