Radiomics Based on MRI as a Biomarker to Guide Therapy by Predicting Upgrading of Prostate Cancer From Biopsy to Radical Prostatectomy.

BACKGROUND: Biopsy Gleason score (GS) is crucial for prostate cancer (PCa) treatment decision-making. Upgrading in GS from biopsy to radical prostatectomy (RP) puts a proportion of patients at risk of undertreatment. PURPOSE: To develop and validate a radiomics model based on multiparametric magnetic resonance imaging (mp-MRI) to predict PCa upgrading. STUDY TYPE: Retrospective, radiomics. POPULATION: A total of 166 RP-confirmed PCa patients (training cohort, n = 116; validation cohort, n = 50) were included. FIELD STRENGTH/SEQUENCE: 3.0T/T2 -weighted (T2 W), apparent diffusion coefficient (ADC), and dynamic contrast enhancement (DCE) sequences. ASSESSMENT: PI-RADSv2 score for each tumor was recorded. Radiomic features were extracted from T2 W, ADC, and DCE sequences and Mutual Information Maximization criterion was used to identify the optimal features on each sequence. Multivariate logistic regression analysis was used to develop predictive models and a radiomics nomogram and their performance was evaluated. STATISTICAL TESTS: Student's t or chi-square were used to assess the differences in clinicopathologic data between the training and validation cohorts. Receiver operating characteristic (ROC) curve analysis was performed and the area under the curve (AUC) was calculated. RESULTS: In PI-RADSv2 assessment, 67 lesions scored 5, 70 lesions scored 4, and 29 lesions scored 3. For each sequence, 4404 features were extracted and the top 20 best features were selected. The radiomics model incorporating signatures from the three sequences achieved better performance than any single sequence (AUC: radiomics model 0.868, T2 W 0.700, ADC 0.759, DCE 0.726). The combined mode incorporating radiomics signature, clinical stage, and time from biopsy to RP outperformed the clinical model and radiomics model (AUC: combined model 0.910, clinical model 0.646, radiomics model 0.868). The nomogram showed good performance (AUC 0.910) and calibration (P-values: training cohort 0.624, validation cohort 0.294). DATA CONCLUSION: Radiomics based on mp-MRI has potential to predict upgrading of PCa from biopsy to RP. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 5 J. Magn. Reson. Imaging 2020;52:1239-1248.

Radiomics Facilitates Candidate Selection for Irradiation Stents Among Patients With Unresectable Pancreatic Cancer.

Purpose: To develop a model to select appropriate candidates for irradiation stent placement among patients with unresectable pancreatic cancer with malignant biliary obstruction (UPC-MBO). Methods: This retrospective study included 106 patients treated with an irradiation stent for UPC-MBO. These patients were randomly divided into a training group (74 patients) and a validation group (32 patients). A clinical model for predicting restenosis-free survival (RFS) was developed with clinical predictors selected by univariate and multivariate analyses. After integrating the radiomics signature, a combined model was constructed to predict RFS. The predictive performance was evaluated with the concordance index (C-index) in both the training and validation groups. The median risk score of progression in the training group was used to divide patients into high- and low-risk subgroups. Results: Radiomics features were integrated with clinical predictors to develop a combined model. The predictive performance was better in the combined model (C-index, 0.791 and 0.779 in the training and validation groups, respectively) than in the clinical model (C-index, 0.673 and 0.667 in the training and validation groups, respectively). According to the median risk score of 1.264, the RFS was significantly different between the high- and low-risk groups (p < 0.001 for the training group, and p = 0.016 for the validation group). Conclusions: The radiomics-based model had good performance for RFS prediction in patients with UPC-MBO who received an irradiation stent. Patients with slow progression should consider undergoing irradiation stent placement for a longer RFS.

[Study on different digestion methods for determination of twelve metal elements in the plant Platycodon Grandi florum (Jacq.) A. DC. by FAAS].

In the present paper the effects of different digestion methods on determining the amount of metal elements in the plant platycodon grandi florum (Jacq.) A. DC. by flame atomic absorption spectrophotometry(FAAS) are reported. FAAS method was established for the determination of K, Mg, Ca, Cu, Zn, Mn, Fe, Co, Ni, Cd and Cr and Pb in the plant platycodon grandi florum (Jacq.) A. DC. The samples were incinerated and followed by digestion with HNO3-HClO (phi, 4 : 1) at 90-95 degrees C and normal pressure. In the meantime, the optimum parameters of FAAS and effects of solution medium on the results were discussed. The analytical results of K, Mg, Ca, Mn, Fe, Cu and Zn were 13 226.32, 922.57, 1 710.72, 9.23, 336.66, 8.75 and 19.62 microg x g(-1) respectively, while Co, Ni, Cd, Cr and Pb were not checked out in the samples. The results showed that the recovery of standard addition was 95.45Y-105.50% and the relative standard deviation (n = 9) was 0.34%-5.78%. The method is quick, simple and convenient, and the results are satisfactory.

[Determination of six metal elements in plant Bupleurum scorzoneri folium Willd. by flame atomic absorption spectrophotometry (FAAS)].

The objective in this paper was to determine the amount of metal elements in the Plant Bupleurum scorzoneri folium Willd. by flame atomic absorption spectrophotometry (FAAS). FAAS method was established for the determination of Ca, Mg, Fe, Cu, Zn and Pb in the Plant Bupleurum scorzoneri folium Willd. after digestion with HNO3-HClO4 (V : V= 4 : 1) at 90-95 degrees C and at normal pressure. In the meantime, the optimum parameters of FAAS and the effects of solution medium on the results were studied. The analytical results of Ca, Mg, Fe, Cu and Zn were 5,588.9, 1,790.5, 869.3, 78.4, 44.3 microg x g(-1) respectively, and Pb was not checked out in the samples. The results showed that the recovery of standard addition was 99.57%-102.10%, the relative standard deviation (n= 9) was 0.18%-2.26%. The method is quick, simple and convenient, and the results are satisfactory.

[Determination of thirteen metal elements in the plant Foeniculum vulgare Mill. by flame atomic absorption spectrophotometry].

The objective of the paper is to determine the amount of metal elements of Na, K, Mg, Ca, Cu, Zn, Mn, Fe, Co, Ni, Cd, Cr and Pb in the planted Foeniculum vulgare Mill. by flame atomic absorption spectrophotometry (FAAS), after the cinefaction and the digestion with HNO3-HClO4 (phi 4:1) at 90-95 degrees C and normal pressure. The optimum parameters of FAAS and the effects of solution medium on the results were investigated. The analytical results show that the amount of Na, K, Mg, Ca, Mn, Fe, Cu, Zn and Pb was 1508.7, 27653.0, 2036.0, 4848.1, 24.8, 323.5, 15.2, 23.7 and 10.8 microg x g(-1), respectively, and that of Co, Ni, Cd and Cr was not checked out in the samples. The recovery of standard addition is 97.45%-102.50%, the relative standard deviation (n=9) was 0.34%-2.77%. The characteristic method is quick, simple and convenient and the results are satisfactory.

[Determination of fifteen metal elements in Cynomorium songaricum by flame atomic absorption spectrophotometry (FAAS)].

A FAAS method was established for the determination of Na, K, Mg, Ca, Cu, Zn, Fe, Mn, Ni, Co, Pb, Cr, Cd, Ag and Au in Cynomorium songaricum after digestion with HNO3-HClO4 (phi 4:1) at 90-95 degrees C and at normal pressure. In this paper, the parameters in FAAS were studied. The analytical results of Na, K, Mg, Ca, Fe, Zn, Cu, Mn, Pb, Ni and Ag were 13,572.0, 14,260.0, 358.3, 168.3, 238.5, 19.4, 5.9, 3.4, 2.6, 1.3 and 0.4 microg x g(-1) respectively and Co, Cr, Cd and Au were not found in the samples. The results showed that the recovery of standard addition was 97.8%-104.5%, and the relative standard deviation (n = 9) was 0.2%-5.0%. The method is fast, simple and convenient. The results were satisfactory.