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Elastic deformation in thin-walled parts during machining is affected by the coupling of force and flexibility. Obtaining flexibility information along machining tool paths is crucial for online monitoring of this deformation. However, the current finite element method (FEM) is limited by mesh nodes, hampering its ability to accurately determine flexibility along tool paths. To overcome this limitation, this paper proposes a method that combines FEM with the surrogate model to predict flexibility accurately at any position on thin-walled parts' surfaces. The surrogate model is the hybrid model K-K-CNN based on two K-nearest neighbor (KNN-KNN) algorithms and a convolutional neural network (CNN) model. Initially, an initial dataset containing positions and flexibility of mesh nodes is generated automatically through secondary development of ABAQUS. Then, the K-K-CNN hybrid model is introduced and trained on this dataset to calculate flexibility accurately at any position on the surface of thin-walled parts. The hybrid model employs a CNN to address the nonlinear spatial correlation issue in flexibility prediction. Moreover, the hybrid model incorporates two KNN algorithms to alleviate the overfitting challenge stemming from the straightforward input features and extensive dataset size. In comparison to traditional deep learning models, the K-K-CNN hybrid model presents notable benefits in predicting flexibility for complex thin-walled parts at any given position, which affirms its robustness and accuracy. The proposed prediction method for flexibility can provide high-quality data-driven information for monitoring the elastic deformation of thin-walled parts. [ABSTRACT FROM AUTHOR]

The integral blisk has been widely used in aerospace, and its structural performance is inextricably linked to the blade surface quality. To improve the surface integrity of polished surface, ultrasonic vibration assisted belt flapwheel flexible polishing (UBFP) is proposed. In this study, the polishing principle of UBFP and the effects of vibration on surface generation are investigated, and kinematic analyses and trajectory simulations are performed. Furthermore, the influences of the main processing parameters on the polishing force and surface roughness in UBFP are explored experimentally, and the sensitivity of the main parameters is distinguished by multi-parameter relative sensitivity analysis based on Monte Carlo simulation. The results show that the ultrasonic vibration contributes to the polishing process primarily through kinematic state changing and trajectories interlacing of abrasives. Compared with conventional belt flapwheel flexible polishing, the polishing force decreases by 15.72% and the surface roughness decreases by 17.39%. The compression depth is the most sensitive parameter in the process of UBFP. This study demonstrates the feasibility of UBFP and provides a theoretical and experimental reference for improving the polishing surface quality of the blisk blade. [ABSTRACT FROM AUTHOR]

As the performance potential of composite materials continues to be explored, CFRP has gradually become an important candidate material in various fields. However, CFRP is a typical difficult-to-process material because of its anisotropy and inhomogeneity. Inappropriate tool structure or parameters will lead to substandard surface quality. For this reason, a series of experiments are designed in this paper, including tool structure optimization experiment, milling parameter single factor experiment, and milling parameter orthogonal experiment. And because of the complexity of the composite surface, the surface roughness Ra commonly used in metal cutting is not used, but a series of 3D surface roughness indexes are used to evaluate the surface. The effect of process parameters on the processing quality was explored by single variable analysis, range analysis and grey relational analysis. It is concluded that better surface quality can be obtained by using multi-blade cutters with moderate helix angle. Furthermore, Medium feed per tooth is more beneficial to the surface quality. The small depth of cut can effectively reduce the milling force, but when the depth of cut is less than the thickness of CFRP single layer, the surface quality will decline sharply. [ABSTRACT FROM AUTHOR]

With their high specific stiffness, corrosion resistance and other characteristics, especially their outstanding performance in product weight loss, fiber-reinforced resin matrix composites are widely used in the aviation, shipbuilding and automotive fields. The difficulties in minimizing defects are an important factor in the high cost of composite material component fabrication. Fiber steering is one of the typical means of producing composite parts with increased strength or stiffness. However, fiber waviness is an important defect induced by fiber steering during the fiber placement process. Meanwhile, the laying speeds of the inner and outer tows along the path width direction are different during the fiber steering process, resulting in different interlaminar bond strengths. Therefore, the fiber waviness and uneven interlaminar bonding strength during fiber steering not only affect the dimensions of a composite product, but also influence the mechanical properties of the part. This study aims to reduce fiber waviness and improve interlaminar bonding uniformity along the path width direction using a multi-piece compaction roller. By analyzing the mechanism of the generation of fiber waviness, the interlaminar bonding strength for each tow during fiber steering is investigated. Through analyzing and optimizing the compaction force, laying temperature and laying velocity during fiber steering experiments, the optimization approach is verified. [ABSTRACT FROM AUTHOR]

Tool wear is inevitable in actual manufacturing, especially in extreme processing conditions for machining difficult-to-cut materials. The monitoring of the tool state has an important influence on the surface quality and dimensional accuracy of the precision parts. In the previous studies, the original total power consumption is usually used to predict tool wear while ignoring the cutting power consumption accounts for a small proportion of the total power consumption of machine tools. Therefore, the accuracy is difficult to achieve the expected target. For better prediction results, a novel prediction method based on net cutting power consumption by Gaussian process regression (GPR) with ARD Matern 5/2 kernel is proposed in this study. Firstly, the physical model of net cutting power consumption is established. Then, tool wear under fixed working conditions is predicted by using the net cutting power consumption and GPR, and the advantage of the proposed method in this study is verified by comparing it with the existing methods. Finally, the proposed method is verified to obtain better prediction performance with variable cutting parameters than using total power consumption with the neural network. This study reveals that low-cost sensors like power meter can be used as an important supplement to monitoring tool conditions in the industry and also provides a research basis for predicting tool wear under different cutting conditions. [ABSTRACT FROM AUTHOR]

GH738 superalloy offers exceptional material properties at elevated temperature and is widely applied to the critical components of aero-engines and gas turbine. However, high strength and poor thermal conductivity bring significant challenges for the machining and surface qualities of GH738 superalloy. In this work, the creep feed grinding performance of GH738 was investigated. The variation laws and formation mechanism of surface integrity were explored with three common types of alumina grinding wheels under various grinding parameters. The experimental results showed that there is considerable impact of grinding parameters on the grinding force and grinding temperature. The stronger coupling of thermal and mechanical aggravates worse surface integrity. The propensity of grinding burn could be more sensitive when the maximum undeformed chip thickness is greater than 0.45–0.5 μm. With the material removal rate in the range of 0.83–1.67 mm3/mm·s, surface defects are visible, and the thickness of plastic deformation layer is about 4–6 μm. In addition, the surface quality ground by the white and pink fused alumina mixed abrasive grinding wheel (WA-PA) is slightly superior to that of the WA and BA grinding wheels. Finally, the grinding parameters for creep feed grinding GH738 are recommended as vw ∈ [50, 150] mm/min, vs ∈ [25, 35] m/s, and ap ∈ [0.2, 0.6] mm. [ABSTRACT FROM AUTHOR]

Objectives: This study was conducted in order to explore the value of histogram analysis of the intravoxel incoherent motion-kurtosis (IVIM-kurtosis) model in the diagnosis and grading of prostate cancer (PCa), compared with monoexponential model (MEM). Materials and Methods: Thirty patients were included in this study. Single-shot echo-planar imaging (SS-EPI) diffusion-weighted images (b -values of 0, 20, 50, 100, 200, 500, 1,000, 1,500, 2,000 s/mm2) were acquired. The pathologies were confirmed by in-bore MR-guided biopsy. The postprocessing and measurements were processed using the software tool Matlab R2015b for the IVIM-kurtosis model and MEM. Regions of interest (ROIs) were drawn manually. Mean values of D , D *, f , K , ADC, and their histogram parameters were acquired. The values of these parameters in PCa and benign prostatic hyperplasia (BPH)/prostatitis were compared. Receiver operating characteristic (ROC) curves were used to investigate the diagnostic efficiency. The Spearman test was used to evaluate the correlation of these parameters and Gleason scores (GS) of PCa. Results: For the IVIM-kurtosis model, D (mean, 10th, 25th, 50th, 75th, 90th), D * (90th), and f (10th) were significantly lower in PCa than in BPH/prostatitis, while D (skewness), D * (kurtosis), and K (mean, 75th, 90th) were significantly higher in PCa than in BPH/prostatitis. For MEM, ADC (mean, 10th, 25th, 50th, 75th, 90th) was significantly lower in PCa than in BPH/prostatitis. The area under the ROC curve (AUC) of the IVIM-kurtosis model was higher than MEM, without significant differences (z = 1.761, P = 0.0783). D (mean, 50th, 75th, 90th), D * (mean, 10th, 25th, 50th, 75th), and f (skewness, kurtosis) correlated negatively with GS, while D (kurtosis), D * (skewness, kurtosis), f (mean, 75th, 90th), and K (mean, 75th, 90th) correlated positively with GS. The histogram parameters of ADC did not show correlations with GS. Conclusion: The IVIM-kurtosis model has potential value in the differential diagnosis of PCa and BPH/prostatitis. IVIM-kurtosis histogram analysis may provide more information in the grading of PCa than MEM. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the diagnostic performance of histogram analysis of intravoxel incoherent motion (IVIM) parameters for differentiating prostate cancer (PCa) from benign prostatic hyperplasia (BPH), and compare with the monoexponential model, with in-bore MR-guided biopsy as pathological reference. Methods: Thirty patients were included in this study. DWI images were processed with Matlab R2015b software by IVIM and monoexponential model for quantitation of diffusion coefficient (D), pseudo diffusion coefficient (D*), perfusion fraction (f), and apparent diffusion coefficient (ADC). The multiparametric data were compared between PCa and BPH group. Correlations between parameters and Gleason scores of PCa were assessed with Spearman rank test. ROC analysis was used to evaluate and compare the diagnostic ability of each parameter for discriminating PCa from BPH. Logistic regression model was used to evaluate the diagnostic performance of combination of different histogram parameters. Results: Sixteen PCa lesions and 20 BPH nodules were analyzed in this study. For IVIM-derived D, the histogram mean, 75th, 90th, and max of PCa were significantly lower than BPH. PCa had significantly lower min and 10th D* than BPH. For f, histogram mean, min, 10th, 25th, 50th, 75th, 90th, max and skew showed significant differences between PCa and BPH. For ADC, PCa were significantly lower than BPH in terms of histogram mean, min, 10th, 25th, 50th, 75th, 90th, max and kurtosis. Histogram mean D and min, 25th D* show significantly negative correlation with Gleason score (r = − 0.582, − 0.534, − 0.554, respectively). Histogram max D and mean f and min ADC showed higher diagnostic performance than other parameters (AUC = 0.925, 0.881, 0.969, respectively). The IVIM model (combined with max D, min D* and mean f) (AUC = 0.950 [0.821, 0.995]) didn't show significant difference from the monoexponential model (AUC = 0.969 [0.849, 0.999], p = 0.23). Besides, combination of the IVIM and monoexponential model didn't improve diagnostic performance compared with the single model (p = 0.362 and 0.763, respectively). Conclusions: Histogram analyses of IVIM and monoexponential model were both useful methods for discriminating PCa from BPH. The diagnostic performance of IVIM model seemed to be not superior to that of monoexponential model. Combination of IVIM and monoexponential model did not add significant information to the single model alone. [ABSTRACT FROM AUTHOR]

Background: There is still little research about histogram analysis of diffusion kurtosis imaging (DKI) using in prostate cancer at present.Purpose: To verify the utility of histogram analysis of DKI model in detection and assessment of aggressiveness of prostate cancer, compared with monoexponential model (MEM).Material and Methods: Twenty-three patients were enrolled in this study. For DKI model and MEM, the Dapp, Kapp, and apparent diffusion coefficient (ADC) were obtained by using single-shot echo-planar imaging sequence. The pathologies were confirmed by in-bore magnetic resonance (MR)-guided biopsy. Regions of interest (ROI) were drawn manually in the position where biopsy needle was put. The mean values and histogram parameters in cancer and noncancerous foci were compared using independent-samples T test. Receiver operating characteristic curves were used to investigate the diagnostic efficiency. Spearman's test was used to evaluate the correlation of parameters and Gleason scores.Results: The mean, 10th, 25th, 50th, 75th, and 90th percentiles of ADC and Dapp were significantly lower in prostate cancer than non-cancerous foci (P < 0.001). The mean, 50th, 75th, and 90th percentiles of Kapp were significantly higher in prostate cancer (P < 0.05). There was no significant difference between the AUCs of two models (0.971 vs. 0.963, P > 0.05). With the increasing Gleason scores, the 10th ADC decreased (ρ = -0.583, P = 0.018), but the 90th Kapp increased (ρ = 0.642, P = 0.007).Conclusion: Histogram analysis of DKI model is feasible for diagnosing and grading prostate cancer, but it has no significant advantage over MEM. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to compare the potential of monoexponential model (MEM), intravoxel incoherent motion (IVIM) model, kurtosis model, and IVIM–kurtosis model in the diagnosis and aggressiveness assessment of prostate cancer (PCa). Materials and Methods: Thirty-six patients were recruited. Diffusion-weighted images were acquired on a 3.0-T magnetic resonance imaging (MRI) system using 0 b values up to 2,000 s/mm2 and analyzed using four models: MEM (ADCMEM), IVIM (D IVIM, D *IVIM, f IVIM), kurtosis (D kurtosis, K kurtosis), and IVIM–kurtosis (D IVIM−kurtosis, D *IVIM−kurtosis, f IVIM−kurtosis, D IVIM−kurtosis) models. The values of these parameters were calculated and compared between PCa, benign prostatic hyperplasia (BPH), and prostatitis. Correlations between these parameters and the Gleason score (GS) of PCa were evaluated using the Pearson test. Results: Forty-five lesions were studied, including 18 PCa, 12 prostatitis, and 15 BPH lesions. The ADCMEM, D IVIM, f IVIM, D kurtosis, and D IVIM−kurtosis values were significantly lower and K kurtosis and K IVIM−kurtosis values were significantly higher in PCa compared with prostatitis and BPH. The area under the curve (AUC) of ADCMEM showed significantly higher values than that of f IVIM and K IVIM−kurtosis, but no statistical differences were found between the other parameters. The D *IVIM−kurtosis value correlated negatively and f IVIM−kurtosis and K IVIM−kurtosis values correlated positively with the GS. Conclusion: The MEM, IVIM, kurtosis, and IVIM–kurtosis models were all useful for the diagnosis of PCa, and the diagnostic efficacy seemed to be similar. The IVIM–kurtosis model may be superior to the MEM, IVIM, and kurtosis models in the grading of PCa. [ABSTRACT FROM AUTHOR]

The fillet is a typical transitional form for a region with a common edge between combinatorial surfaces of blisk parts, and the processing quality of that has a strong influence on the aerodynamic performances of the parts. As a special type, the incomplete fillet is generated due to missing data of the combinatorial surfaces, which is not tangent to the combinatorial surfaces. For machining the clean-up region with incomplete fillet, the planned tool path using the conventional method may result in excess residual material, which will affect the part performance. To address this issue, a novel clean-up tool path planning method based on the cutter center point of the fillet boundary is proposed. In this paper, the method constructs a mapping model from a point on the fillet boundary to the cutter center point. The model is solved with a point-searching algorithm so that the tool path of the fillet boundary can be calculated. Then, the region between the adjacent tool path of the fillet boundary is equivalent to circular curve for planning the clean-up tool path. Finally, this method is applied to the clean-up machining between the blade and hub of an open blisk using a computational simulation and experiment to verify its effectiveness. The results show that the maximum allowance is 0.311 mm with the conventional method, whereas it is approximately 0 mm with the proposed method, which satisfies the design requirement. Thus, the correctness and effectiveness of the proposed method are validated. [ABSTRACT FROM AUTHOR]

Background: To investigate whether MRI findings, including texture analysis, can differentiate KRAS mutation status in rectal cancer.Methods: Totally, 158 patients with pathologically proved rectal cancers and preoperative pelvic MRI examinations were enrolled. Patients were stratified into two groups: KRAS wild-type group (KRASwt group) and KRAS mutation group (KRASmt group) according to genomic DNA extraction analysis. MRI findings of rectal cancers (including texture features) and relevant clinical characteristics were statistically evaluated to identify the differences between the two groups. The independent samples t test or Mann-Whitney U test were used for continuous variables. The differences of the remaining categorical polytomous variables were analyzed using the Chi-square test or Fisher exact test. A receiver operating characteristic (ROC) curve analysis was performed to evaluate the discriminatory power of MRI features. The area under the ROC curve (AUC) and the optimal cut-off values were calculated using histopathology diagnosis as a reference; meanwhile, sensitivity and specificity were determined.Results: Mean values of six texture parameters (Mean, Variance, Skewness, Entropy, gray-level nonuniformity, run-length nonuniformity) were significantly higher in KRASmt group compared to KRASwt group (p < 0.0001, respectively). The AUC values of texture features ranged from 0.703~0.813. In addition, higher T stage and lower ADC values were observed in the KRASmt group compared to KRASwt group (t = 7.086, p = 0.029; t = - 2.708, p = 0.008).Conclusion: The MRI findings of rectal cancer, especially texture features, showed an encouraging value for identifying KRAS status. [ABSTRACT FROM AUTHOR]

Tool path generation is an important task in end milling. In the existing literature, the tool path pattern/style is determined based on geometric analysis. However, there is little analysis from the viewpoint of machining dynamics/cutting force, which is more related to the final manufacturing performance. Although there are many types of tool paths (e.g., zigzag, spiral, and ISO-scallop tool path), they can be decomposed into a number of circular tool paths with various path radii and cutting angles. Firstly, by investigating chip formation mechanism, the effect of tool path radius on uncut chip thickness is obtained. Analysis shows that tool path radius has a significant influence on uncut chip thickness, thus affecting the cutting force, especially when the tool path radius is small. Then, the effect of cutting angle on cutting force distribution is analyzed. It is found that the feed direction could vary the distribution of cutting force in X and Y direction in 3-axis end milling. Based on such analysis, the cutting force prediction model considering tool path effect is established. To validate the proposed model, various experiments have been carried out based on well-designed tool paths. The comparative results show that (1) tool path has great effect on cutting force through the tool path radius, rotation direction, and start/end point, and (2) the proposed model is capable of providing accurate cutting force prediction considering tool path effect. From a physical viewpoint, the proposed method provides huge potential in automated/intelligent tool path optimization towards better surface quality via minimizing cutting force, which significantly contributes to the state of the art in tool path generation. [ABSTRACT FROM AUTHOR]

Background: Intravoxel incoherent motion (IVIM) parameters derived from iZOOM diffusion-weighted imaging (DWI) can be used to quantitatively identify malignant thyroid nodules. However, the criteria are not standardized. Purpose: To determine IVIM parameter values derived from iZOOM DWI that can differentiate malignant from benign thyroid nodules. Material and Methods: Forty-two patients with 46 pathologically confirmed thyroid nodules. All patients underwent preoperative examinations with conventional and iZOOM DWI. A three-dimensional region of interest was drawn on multiple slices to cover the entire nodule. IVIM parameters (D, pure diffusion; f, perfusion fraction; and D*, pseudodiffusion) were measured. The IVIM parameters of the malignant and benign thyroid nodules were compared using independent samples t - tests, a multiple logistic regression, and receiver operating characteristic (ROC) curve analysis. Results: D, D*, and f exhibited good reproducibility. The D and f values in the malignant nodules (D = [0.72 ± 0.14] × 10−3 mm2/s, [29.94 ± 7.36] %) were significantly lower than those in benign nodules (D = [1.23 ± 0.35] × 10−3 mm2/s, [36.00 ± 8.35] %). The D value achieved the highest area under curve (0.939). The optimal cut-off value for D was 0.87 × 10−3 mm2/s (sensitivity = 95.83%, specificity = 90.91%, positive predictive value [PPV] = 92.00%, negative predictive value [NPV] = 95.24%, and accuracy rate = 93.48%). The area under ROC curve (AUC) of D combined with the f value did not significantly differ from that of D. Conclusion: IVIM parameter D derived from iZOOM DWI may be helpful in differentiating malignant from benign thyroid nodules. [ABSTRACT FROM AUTHOR]

The effect of material removal on workpiece dynamics has a great influence on suppressing resonance and regenerative vibrations in milling of thin-walled structures. Although some works have been done to obtain the varying dynamics of the workpiece, many researchers take plate structures as research objects. In this paper, a method based on FEM and Taylor series is proposed to predict the time-varying dynamics of thin-walled blade structures in milling. The input data in the method is the mass and stiffness matrices of the initial workpiece and the change of the matrices caused by material removal. The initial matrices can be obtained through the FEM model established by the mechanical analysis of the eight-node shell element, and the change of the matrices can be obtained by a third-order Taylor series. In comparison with three-dimensional cube elements, the shell elements can reduce the number of degrees of freedom of the FEM model by 74%, which leads to about 9 times faster computation of the characteristic equation. Meanwhile, the proposed method eliminates the necessities of re-building and re-meshing the FEM model at each cutting position, then the computational efficiency of workpiece dynamics is improved. Finally, the result of experiments shows that the maximum prediction error of the proposed method is about 4%. [ABSTRACT FROM AUTHOR]

Constitutive model plays an important role in finite element (FE) simulation of machining, especially the Johnson-Cook (J-C) model. Although many researches have completed on modifying the J-C model to improve FE simulation of cutting, the systematic determination scheme of the added coefficients is heretofore not available. Inverse identification approach presents a promising advantage on determining constitutive coefficient compared with traditional methods, such as Split Hopkinson Pressure Bar (SHPB). In this work, a new inverse method based on finite element analysis (FEA) is developed for determining added J-C coefficients. A modified J-C constitutive model (MJC) including hyperbolic tangent failure function is introduced for machining titanium alloy Ti-6Al-4V. The determination process of the added coefficients is taken as an optimization problem, where experimental cutting forces and the added J-C coefficients are considered as the optimization objectives and design variables, respectively. An FE model of orthogonal cutting titanium alloy Ti-6Al-4V is established on the Deform-2D simulation platform. The response surface method (RSM) is subsequently used to build the mapping relation of the simulated cutting forces and the added coefficients. Then, orthogonal cutting experiments are conducted to obtain the objective cutting forces. The firefly algorithm (FA) is employed to solve the optimization model for the optimal added J-C coefficients. Verification results show that the identified constitutive model has higher accuracy on predicting cutting forces compared with other models including the origin J-C model and the Calamaz’s model. [ABSTRACT FROM AUTHOR]

Background: Many locally advanced rectal cancer (LARC) patients can benefit from neoadjuvant chemotherapy (NACT), with some achieving a pathological complete response (pCR). However, there is limited research reporting on the value of intravoxel incoherent motion (IVIM) in monitoring pCR in patients with LARC.Purpose: To identify whether IVIM parameters derived from whole-tumor volume (WTV) before and after NACT could accurately assess pCR in patients with LARC.Study Type: Prospective patient control study.Population: Fifty-one patients with LARC before and after NACT, prior to surgery.Field Strength/sequence: IVIM-diffusion imaging at 3T.Assessment: Apparent diffusion coefficient (ADC), slow diffusion coefficient (D), fast diffusion coefficient (D*), and perfusion-related diffusion fraction (f) values were obtained on diffusion-weighted magnetic resonance images (DW-MRI) using WTV methods and calculated using a biexponential model before and after NACT.Statistical Tests: DWI-derived ADC and IVIM-derived parameters and their percentage changes (ΔADC%, ΔD%, ΔD*%, and Δf%) were compared using independent-samples t-test and Mann-Whitney U-test between the pCR and non-pCR groups. The diagnostic performance of IVIM parameters and their percentage changes were evaluated using receiver operating characteristic curves.Results: Compared with the non-pCR group, the pCR group exhibited significantly lower pre-ADCmean (P = 0.003) and pre-D values (P = 0.024), and significantly higher post-f (P = 0.002), ΔADCmean % (P = 0.002), ΔD% (P = 0.001), and Δf% values (P = 0.017). Receiver operating characteristic curves showed that the pre-D value had the best specificity (95.12%) and accuracy (86.27%) in predicting the pCR status, and ΔD% had the highest area under the curve (0.832) in assessing the pCR response to NACT.Data Conclusions: The IVIM-derived D value is a promising tool in predicting the pCR status before therapy. The percentage changes in D values after therapy may help assess the pCR status prior to surgery.Level Of Evidence: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2017. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the diagnostic potential of DW-MRI relative parameters for differentiation of rectal cancers with different Kirsten rat sarcoma viral oncogene homologue (KRAS) mutation status.Methods: Fifty-one patients with rectal cancer underwent diffusion-weighted MR imaging with eight b values. ADCs (including Max-ADC, Min-ADC and Mean-ADC) and IVIM parameters (D, pure diffusion; f, perfusion fraction; D*, pseudodiffusion coefficient) were respectively calculated by mono- and bi-exponential analysis. Patients were stratified into two groups: KRAS wild type and mutant. The DW-MRI-derived parameters between the KRAS wild-type group and KRAS mutant group were compared using the Mann-Whitney U test. Receiver-operating characteristic (ROC) analysis of discrimination between KRAS wild-type and KRAS mutant rectal cancer was performed for the DW-MRI-derived parameters.Results: Max-ADC, Mean-ADC and D values were significantly lower in the KRAS mutant group than in the KRAS wild-type group, whereas a higher D* value was demonstrated in the KRAS mutant group. According to the ROC curve, Mean-ADC and D* values showed moderate diagnostic significance with the AUC values of 0.756 and 0.710, respectively. The cut-off values for Mean-ADC and D* were 1.43 × 10-3mm2/s and 26.58 × 10-3mm2/s, respectively.Conclusion: Rectal cancers had distinctive diffusion/perfusion characteristics in different KRAS mutation statuses. The DW-MRI-derived parameters, specifically Mean-ADC and D*, show a moderate diagnostic significance for KRAS status.Key Points: • Rectal cancers with different KRAS mutation statuses demonstrated distinctive diffusion/perfusion characteristics. • Max-ADC, Mean-ADC and D values were lower in the KRAS mutant group. • A higher D* value was demonstrated in the KRAS mutant group. • IVIM-DW MRI may potentially help preoperative KRAS mutant status prediction. [ABSTRACT FROM AUTHOR]

The Johnson and Cook (J-C) constitutive model is widely employed in finite element analysis for machining. Currently, inverse approach shows greater superiority on identifying the J-C parameters than the traditional way, like the split Hopkinson pressure bar (SHPB) test. In this paper, a modified parallel-sided shear zone model at primary zone is presented for determining J-C parameters. Based on the assumption of nonequidistant primary zone, the distribution of velocity, strain rate, strain, and temperature is successfully predicted. Finite element simulation (FEM) is subsequently used to verify the theoretical prediction. Based on the proposed shear band model, an inverse approach is developed for determining the J-C parameters. In this method, the parameter determining process is taken as an optimization problem. The J-C parameters are considered as the design variable while the optimization objective is cutting force. In conjugation with the measured cutting forces and chip thickness, the particle swarm optimization (PSO) algorithm was introduced to solve the optimization model. The Johnson-Cook's model of nickel-base superalloy Inconel 718 is successfully identified from orthogonal cutting test. Finite element models with seven constitutive models from Deform, references and this work are established to predict cutting force. The results showed that the proposed J-C models have higher prediction precision compared with other constitutive models. With the proposed J-C models, the errors between the simulated and measured cutting forces are controlled within 7.3%. [ABSTRACT FROM AUTHOR]

This present study aimed at the wear behaviors of uncoated carbide tools and its effect on machinability in dry milling of magnesium alloy at high cutting speeds. Through the experimental observations, the dominant wear mechanisms for the carbide tool were determined, namely adhesion, abrasion, and diffusion wear. Compared to lower speed, the experimental results indicated that the higher speed could bring much better surface quality in the steady wear stage; however, the duration of this stage was shorter than the lower. Within each steady wear, surface roughness declined gradually with the increasing cutting edge radius. Meanwhile, a mass of workpiece material piled up the stagnant zone below the cutting edge on the flank face, causing the flank built-up edge formation. Besides that, the built-up edge accumulated to a certain size that is beneficial to improve the machined surface quality. In addition, the chip morphologies depended on the severity of the tool wear. The cutting tool during the early period of cutting operation predominantly produced inerratic flake chips. However, with the development of built-up edge, there was a great quantity of threadlike chips formed, as well as the plentiful needlelike chips. [ABSTRACT FROM AUTHOR]

In this study, Taguchi with grey relational analysis of experimental data was carried out to determine an optimum combination of process parameters for promoting the surface roughness and the microhardness of dry milling magnesium alloy. According to Taguchi's signal-to-noise ratio, the optimal process parameters were obtained for desired surface roughness and microhardness, respectively. Moreover, in order to achieve an improved surface quality, the optimum combination of process parameters was determined by grey relational grade. The analysis of variance for grey relational grade showed that feed rate was the most dominant factor influencing surface integrity in milling of magnesium alloy. Finally, the optimum combination of process parameters were validated by confirmation experiments that yield substantially improved multiple quality characteristics. The outcome of the confirmation experiment indicated that the Taguchi with grey relational analysis is an effective method to determine available cutting parameters for a desired surface quality for milling magnesium alloy under dry condition. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the usefulness of three-dimensional (3D) MR black-blood sequence flow-dephasing-prepared fast spoiled gradient recalled echo (FDP-FSPGR) in screening the basilar artery (BA) wall and the ostia of the adjacent branch arteries.Materials and Methods: Twenty-one patients with BA stenosis >50% on digital subtraction angiography (DSA) were imaged. Three-dimensional FDP-FSPGR images were acquired using a flow-dephasing-prepared segmented technique, including two spin echoes to overcome the inhomogeneity of the radiofrequency field. Precontrast and postcontrast 3D FDP-FSPGR sequences were performed.Results: The wall of the BA could be visualized in 20 patients with good contrast, and 82 ostia of the adjacent branch arteries were identified on 3D FDP-FSPGR images. Compared with DSA, the accuracy of it was 0.94 (95% confidence interval [CI], 0.89 to 0.99) for reader 1 and 0.92 (95% CI, 0.86 to 0.98) for reader 2, with strong agreement between the two readers (κ = 0.82). BA plaque enhancement was noted in 16 of the 20 patients after contrast administration.Conclusion: The 3D FDP-FSPGR can be used for high-spatial-resolution demonstration and large coverage of the BA wall and the ostia of the adjacent branch arteries. This sequence will make it possible to evaluate therapeutic effects in clinical studies. [ABSTRACT FROM AUTHOR]

Purpose To evaluate the usefulness of three-dimensional (3D) MR black-blood sequence flow-dephasing-prepared fast spoiled gradient recalled echo (FDP-FSPGR) in screening the basilar artery (BA) wall and the ostia of the adjacent branch arteries. Materials and Methods Twenty-one patients with BA stenosis >50% on digital subtraction angiography (DSA) were imaged. Three-dimensional FDP-FSPGR images were acquired using a flow-dephasing-prepared segmented technique, including two spin echoes to overcome the inhomogeneity of the radiofrequency field. Precontrast and postcontrast 3D FDP-FSPGR sequences were performed. Results The wall of the BA could be visualized in 20 patients with good contrast, and 82 ostia of the adjacent branch arteries were identified on 3D FDP-FSPGR images. Compared with DSA, the accuracy of it was 0.94 (95% confidence interval [CI], 0.89 to 0.99) for reader 1 and 0.92 (95% CI, 0.86 to 0.98) for reader 2, with strong agreement between the two readers (κ = 0.82). BA plaque enhancement was noted in 16 of the 20 patients after contrast administration. Conclusion The 3D FDP-FSPGR can be used for high-spatial-resolution demonstration and large coverage of the BA wall and the ostia of the adjacent branch arteries. This sequence will make it possible to evaluate therapeutic effects in clinical studies. J. Magn. Reson. Imaging 2014;39:911-916. © 2013 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Cerebral blood flow (CBF) in the human primary visual cortex is correlated with the loss of visual function in neuro-ophthalmological diseases. Advanced three-dimensional pseudo-continuous arterial spin labeling (3D pCASL), as a non-invasive method to access the CBF, can be a novel measurement to detect the visual cortex. The objective of the study was to assess the intra- and inter-scanner reliability of 3D pCASL of the visual cortex in healthy adults and suggest the selection of different post-labeling delay times (PLDs). For this reason, 3D pCASL was conducted in two 3.0T MR three times with twelve healthy volunteers at an interval of 10–15 days. The 1st and 3rd tests were performed on scanner-1, and the 2nd test was performed on scanner-2. The value of the CBF was abstracted from the visual cortex with two PLDs. The intra- and inter-scanner reliability and reproducibility were evaluated with the intraclass correlation coefficient (ICC) and Bland-Altman plots. By estimating the mean value of the CBF in the visual cortex, the intra-scanner results demonstrated the higher reliability (ICC for PLD = 1.5 second presented at 0.743 compared with 0.829 for PLD = 2.5 seconds), and the Bland-Altman plots showed the reproducibility at a longer PLD. We conclude that the calibrated 3D pCASL approach provides a highly reproducible measurement of the CBF of the visual cortex that can serve as a useful quantitative probe for research conducted at multiple centers and for the long-term observation of the clinical effects of neuro-opthalmological diseases. [ABSTRACT FROM AUTHOR]

Purpose: Fast low-angle shot (FLASH) imaging is widely used in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) because it permits fast and accurate T1 measurement in vivo. Suppression of the fat signal is necessary for most FLASH applications; otherwise, fat will appear hyperintense. The fat saturation technique is one popular method to reduce fat images on clinical scanners. However, fat saturation combined with the 3D FLASH sequence in breast DCE-MRI scans results in heavy ghosting artifacts caused by heartbeat. We used simulation and experimental scans to determine the cause of these artifact-enhancement phenomena.Methods: We simulated imaging of motion in the x, y, and z directions, with and without fat saturation, to investigate the origin of artifacts. Fourier transform (FT) of the whole field of view was used in the simulation, and we assumed that the uniform phantom was static during one TR. The amplitude of each echo was considered a factor in the FT data. Images were reconstructed using FT data from different phantom positions multiplied by the amplitude factor. Phantom experiments and volunteer studies were implemented to verify the conclusion.Results: Both phantom and volunteer results showed artifacts similar to those in simulation images. We found that FLASH sequence without fat saturation is insensitive to motion. Fat saturation radiofrequency pulses placed before each group of echoes disrupted the steady state of the signal amplitude and produced a low-pass filter effect that enhanced the motion artifacts.Conclusions: We conclude that the low-pass filter effect associated with the fat saturation technique is responsible for dramatically increased motion artifacts. [ABSTRACT FROM AUTHOR]