Deep Learning Radiomics Nomogram to Predict Lung Metastasis in Soft-Tissue Sarcoma: A Multi-Center Study.

Objectives: To build and evaluate a deep learning radiomics nomogram (DLRN) for preoperative prediction of lung metastasis (LM) status in patients with soft tissue sarcoma (STS). Methods: In total, 242 patients with STS (training set, n=116; external validation set, n=126) who underwent magnetic resonance imaging were retrospectively enrolled in this study. We identified independent predictors for LM-status and evaluated their performance. The minimum redundancy maximum relevance (mRMR) method and least absolute shrinkage and selection operator (LASSO) algorithm were adopted to screen radiomics features. Logistic regression, decision tree, random forest, support vector machine (SVM), and adaptive boosting classifiers were compared for their ability to predict LM. To overcome the imbalanced distribution of the LM data, we retrained each machine-learning classifier using the synthetic minority over-sampling technique (SMOTE). A DLRN combining the independent clinical predictors with the best performing radiomics prediction signature (mRMR+LASSO+SVM+SMOTE) was established. Area under the receiver operating characteristics curve (AUC), calibration curves, and decision curve analysis (DCA) were used to assess the performance and clinical applicability of the models. Result: Comparisons of the AUC values applied to the external validation set revealed that the DLRN model (AUC=0.833) showed better prediction performance than the clinical model (AUC=0.664) and radiomics model (AUC=0.799). The calibration curves indicated good calibration efficiency and the DCA showed the DLRN model to have greater clinical applicability than the other two models. Conclusion: The DLRN was shown to be an accurate and efficient tool for LM-status prediction in STS.

The signal intensity characteristics of normal bone marrow in diffusion weighted imaging at various menstrual status women.

PURPOSE: Diffuse hyperintensities of the bone marrow in whole-body diffusion-weighted (DW) imaging (DWI) have been encountered more frequently in females aged 21-50 compared to elder females or men. Therefore, we aimed to visually evaluate DWI among pre-, peri- and postmenopausal women and to verify whether it correlates also quantitatively with hormonal status. METHOD: The prospective study was approved by our institutional review board and informed consent was obtained in a total of 70 healthy premenopausal, perimenopausal, and postmenopausal women aged 40-58 years from February 2017 to October 2017. The bone marrow DW imaging signal characteristics were visually evaluated in comparison to the erector spinae muscle. Imaging data were acquired using a 1.5 T MRI yielding signal intensity values from a DWI-pulse sequence (b-value of 800 s/mm2; apparent diffusion coefficient (ADC) maps from b-values of 0-800 s/mm2), and a T2 mapping sequence covering the L2-L4 lumbar vertebrae. Serous estradiol (E2), follicle stimulating hormone (FSH), and luteinizing hormone (LH) were measured through venous blood assay. The relationship of the mean DW signal intensity (SIDWI) with T2 values, female hormone level, and mean ADC were analyzed using Spearman's rho test. RESULTS: The proportion of diffuse DWI hyperintensities of the bone marrow was significantly higher in premenopausal (91% (21/23)) women compared to peri- (75% (18/24)) and postmenopausal (8% (2/23)) women. A positive correlation was observed for the mean SIDWI (median [interquartile range], 47.33 [30.14]) and mean T2 (mean ± SD, 121.01 ± 13.54) (r = 0.438, p < 0.001) as well as for the mean SIDWI and E2 (median [interquartile range], 52.45 [92.78]) (r = 0.407, p < 0.001). A negative correlation was observed for the mean SIDWI and serous FSH (median [interquartile range], 15.55 [42.08]) as well as for the mean SIDWI and serous LH (median [interquartile range], 6.96 [31.06]) (r = -0.557, p < 0.001; r = -0.535, p < 0.001; respectively), but no significant correlation was found for mean SIDWI and mean ADC (mean ± SD, 599.36 ± 82.70) (r = 0.099, p = 0.415). A negative correlation was also encountered for the mean T2 values and serous FSH (r = -0.339, p = 0.004) as well as for the mean T2 values and serous LH (r = -0.281, p = 0.018). CONCLUSIONS: The mean SIDWI correlates positively with mean T2 and serous E2 values, while there's no significant correlation with mean ADC, indicating that T2 shine-through effects might interfere with bone marrow signaling on DW images. Knowledge of the bone marrow signal characteristics changing in DW images in close relationship with menstrual status is essential to correctly interpret DWI in clinical practice.

Characterizing the Blood Oxygen Level-Dependent Fluctuations in Musculoskeletal Tumours Using Functional Magnetic Resonance Imaging.

This study characterized the blood oxygen level-dependent (BOLD) fluctuations in benign and malignant musculoskeletal tumours via power spectrum analyses in pre-established low-frequency bands. BOLD MRI and T1-weighted imaging (T1WI) were collected for 52 patients with musculoskeletal tumours. Three ROIs were drawn on the T1WI image in the tumours' central regions, peripheral regions and neighbouring tissue. The power spectrum of the BOLD within each ROI was calculated and divided into the following four frequency bands: 0.01-0.027 Hz, 0.027-0.073 Hz, 0.073-0.198 Hz, and 0.198-0.25 Hz. ANOVA was conducted for each frequency band with the following two factors: the location of the region of interest (LoR, three levels: tumour "centre", "peripheral" and "healthy tissue") and tumour characteristic (TC, two levels: "malignant" and "benign"). There was a significant main effect of LoR in the frequencies of 0.073-0.198 Hz and 0.198-0.25 Hz. These data were further processed with post-hoc pair-wise comparisons. BOLD fluctuations at 0.073-0.198 Hz were stronger in the peripheral than central regions of the malignant tumours; however, no such difference was observed for the benign tumours. Our findings provide evidence that the BOLD signal fluctuates with spatial heterogeneity in malignant musculoskeletal tumours at the frequency band of 0.073-0.198 Hz.