Identification of common mechanisms and biomarkers for dermatomyositis and atherosclerosis based on bioinformatics analysis.

BACKGROUND: Dermatomyositis (DM) manifests as an autoimmune and inflammatory condition, clinically characterized by subacute progressive proximal muscle weakness, rashes or both along with extramuscular manifestations. Literature indicates that DM shares common risk factors with atherosclerosis (AS), and they often co-occur, yet the etiology and pathogenesis remain to be fully elucidated. This investigation aims to utilize bioinformatics methods to clarify the crucial genes and pathways that influence the pathophysiology of both DM and AS. METHOD: Microarray datasets for DM (GSE128470, GSE1551, GSE143323) and AS (GSE100927, GSE28829, GSE43292) were retrieved from the Gene Expression Omnibus (GEO) database. The weighted gene co-expression network analysis (WGCNA) was used to reveal their co-expressed modules. Differentially expression genes (DEGs) were identified using the "limma" package in R software, and the functions of common DEGs were determined by functional enrichment analysis. A protein-protein interaction (PPI) network was established using the STRING database, with central genes evaluated by the cytoHubba plugin, and validated through external datasets. Immune infiltration analysis of the hub genes was conducted using the CIBERSORT method, along with Gene Set Enrichment Analysis (GSEA). Finally, the NetworkAnalyst platform was employed to examine the transcription factors (TFs) responsible for regulating pivotal crosstalk genes. RESULTS: Utilizing WGCNA analysis, a total of 271 overlapping genes were pinpointed. Subsequent DEG analysis revealed 34 genes that are commonly found in both DM and AS, including 31 upregulated genes and 3 downregulated genes. The Degree Centrality algorithm was applied separately to the WGCNA and DEG collections to select the 15 genes with the highest connectivity, and crossing the two gene sets yielded 3 hub genes (PTPRC, TYROBP, CXCR4). Validation with external datasets showed their diagnostic value for DM and AS. Analysis of immune infiltration indicates that lymphocytes and macrophages are significantly associated with the pathogenesis of DM and AS. Moreover, GSEA analysis suggested that the shared genes are enriched in various receptor interactions and multiple cytokines and receptor signaling pathways. We coupled the 3 hub genes with their respective predicted genes, identifying a potential key TF, CBFB, which interacts with all 3 hub genes. CONCLUSION: This research utilized comprehensive bioinformatics techniques to explore the shared pathogenesis of DM and AS. The three key genes, including PTPRC, TYROBP, and CXCR4, are related to the pathogenesis of DM and AS. The central genes and their correlations with immune cells may serve as potential diagnostic and therapeutic targets.

Association between type 2 diabetes mellitus and body composition based on MRI fat fraction mapping.

Purpose: To explore the association between type 2 diabetes mellitus (T2DM) and body composition based on magnetic resonance fat fraction (FF) mapping. Methods: A total of 341 subjects, who underwent abdominal MRI examination with FF mapping were enrolled in this study, including 68 T2DM patients and 273 non-T2DM patients. The FFs and areas of visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT) and abdominal muscle (AM) were measured at the level of the L1-L2 vertebral. The FF of bone marrow adipose tissue (BMAT) was determined by the averaged FF values measured at the level of T12 and L1 vertebral, respectively. The whole hepatic fat fraction (HFF) and pancreatic fat fraction (PFF) were measured based on 3D semi-automatic segmentation on the FF mapping. All data were analyzed by GraphPad Prism and MedCalc. Results: VAT area, VAT FF, HFF, PFF of T2DM group were higher than those of non-T2DM group after adjusting for age and sex (P < 0.05). However, there was no differences in SAT area, SAT FF, BMAT FF, AM area and AM FF between the two groups (P > 0.05). VAT area and PFF were independent risk factors of T2DM (all P < 0.05). The area under the curve (AUC) of the receiver operating characteristic (ROC) for VAT area and PFF in differentiating between T2DM and non-T2DM were 0.685 and 0.787, respectively, and the AUC of PFF was higher than VAT area (P < 0.05). Additionally, in seemingly healthy individuals, the SAT area, VAT area, and AM area were found to be significantly associated with being overweight and/or obese (BMI ≥ 25) (all P < 0.05). Conclusions: In this study, it was found that there were significant associations between T2DM and VAT area, VAT FF, HFF and PFF. In addition, VAT area and PFF were the independent risk factors of T2DM. Especially, PFF showed a high diagnostic performance in discrimination between T2DM and non-T2DM. These findings may highlight the crucial role of PFF in the pathophysiology of T2DM, and it might be served as a potential imaging biomarker of the prevention and treatment of T2DM. Additionally, in individuals without diabetes, focusing on SAT area, VAT area and AM area may help identify potential health risks and provide a basis for targeted weight management and prevention measures.

Investigation of Machining Characteristics in Electrical Discharge Machining Using a Slotted Electrode with Internal Flushing.

In die-sinking electrical discharge machining (EDM), it is challenging to implement internal flushing, mainly because it is easy to produce residual material columns on the workpiece cavity's bottom surface, affecting the processing quality and efficiency. In order to solve this problem, the internal flushing slotted electrode EDM technology was proposed. The slotted electrode was designed, and its preparation method was described. The influence of pulse width, pulse interval, and flushing pressure on the performance of the internal flushing slotted electrode EDM was studied using single-factor experiments. The experimental results indicate that, with the increase in pulse width, the material removal rate (MRR) increases first and then decreases, while the electrode wear rate (EWR) and the relative electrode wear rate (REWR) decrease gradually; with the increase in pulse interval, the MRR decreases, while the EWR and the REWR increase gradually; with the increase in flushing pressure, the MRR increases first and then decreases, while the EWR and the REWR increase gradually. When the slotted electrode is used for continuous internal flushing EDM, the appropriate pulse width, flushing pressure, and smaller pulse interval can improve the MRR and reduce the EWR and the REWR.

Intratumoral and peritumoral radiomics based on contrast-enhanced MRI for preoperatively predicting treatment response of transarterial chemoembolization in hepatocellular carcinoma.

BACKGROUND: Noninvasive and precise methods to estimate treatment response and identify hepatocellular carcinoma (HCC) patients who could benefit from transarterial chemoembolization (TACE) are urgently required. The present study aimed to investigate the ability of intratumoral and peritumoral radiomics based on contrast-enhanced magnetic resonance imaging (CE-MRI) to preoperatively predict tumor response to TACE in HCC patients. METHODS: A total of 138 patients with HCC who received TACE were retrospectively included and randomly divided into training and validation cohorts at a ratio of 7:3. Total 1206 radiomics features were extracted from arterial, venous, and delayed phases images. The inter- and intraclass correlation coefficients, the spearman's rank correlation test, and the gradient boosting decision tree algorithm were used for radiomics feature selection. Radiomics models on intratumoral region (TR) and peritumoral region (PTR) (3 mm, 5 mm, and 10 mm) were established using logistic regression. Three integrated radiomics models, including intratumoral and peritumoral region (T-PTR) (3 mm), T-PTR (5 mm), and T-PTR (10 mm) models, were constructed using TR and PTR radiomics scores. A clinical-radiological model and a combined model incorporating the optimal radiomics score and selected clinical-radiological predictors were constructed, and the combined model was presented as a nomogram. The discrimination, calibration, and clinical utilities were evaluated by receiver operating characteristic curve, calibration curve, and decision curve analysis, respectively. RESULTS: The T-PTR radiomics models performed better than the TR and PTR models, and the T-PTR (3 mm) radiomics model demonstrated preferable performance with the AUCs of 0.884 (95%CI, 0.821-0.936) and 0.911 (95%CI, 0.825-0.975) in both training and validation cohorts. The T-PTR (3 mm) radiomics score, alkaline phosphatase, tumor size, and satellite nodule were fused to construct a combined nomogram. The combined nomogram [AUC: 0.910 (95%CI, 0.854-0.958) and 0.918 (95%CI, 0.831-0.986)] outperformed the clinical-radiological model [AUC: 0.789 (95%CI, 0.709-0.863) and 0.782 (95%CI, 0.660-0.902)] in the both cohorts and achieved good calibration capability and clinical utility. CONCLUSIONS: CE-MRI-based intratumoral and peritumoral radiomics approach can provide an effective tool for the precise and individualized estimation of treatment response for HCC patients treated with TACE.

Quantification of the renal sinus fat and exploration of its relationship with ectopic fat deposition in normal subjects using MRI fat fraction mapping.

Purpose: To determine the renal sinus fat (RSF) volume and fat fraction (FF) in normal Chinese subjects using MRI fat fraction mapping and to explore their associations with age, gender, body mass index (BMI) and ectopic fat deposition. Methods: A total of 126 subjects were included in the analysis. RSF volume and FF, visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) area, and hepatic and pancreatic FFs were measured for each subject. The comparisons in gender were determined using two-tailed t-tests or the nonparametric Mann-Whitney U-test for normally or non-normally distributed data for continuous variables and the chi-square test for categorical variables. Comparisons of RFS volume and FF between right and left kidneys were determined using paired sample t-tests. Multivariable logistic models were performed to confirm whether RSF differences between men and women are independent of VAT or SAT area. When parameters were normally distributed, the Pearson correlation coefficient was used; otherwise, the Spearman correlation coefficient was applied. Results: The RSF volumes (cm3) of both kidneys in men (26.86 ± 8.81 for right and 31.62 ± 10.32 for left kidneys) were significantly bigger than those of women (21.47 ± 6.90 for right and 26.03 ± 8.55 for left kidneys) (P < 0.05). The RSF FFs (%) of both kidneys in men (28.33 ± 6.73 for right and 31.21 ± 6.29 for left kidneys) were significantly higher than those of the women (23.82 ± 7.74 for right and 27.92 ± 8.15 for left kidneys) (P < 0.05). The RSF differences between men and women are independent of SAT area and dependent of VAT area (except for right RSF volume). In addition, the RSF volumes and FFs in both kidneys in the overall subjects show significant correlations with age, BMI, VAT area, hepatic fat fraction and pancreatic fat fraction (P < 0.05). However, the patterns of these correlations varied by gender. The RSF volume and FF of left kidney were significantly larger than those of the right kidney (P < 0.05). Conclusion: The association between renal sinus fat and ectopic fat deposition explored in this study may help establish a consensus on the normal values of RSF volume and FF for the Chinese population. This will facilitate the identification of clinicopathological changes and aid in the investigation of whether RSF volume and FF can serve as early biomarkers for metabolic diseases and renal dysfunction in future studies.

Improved differentiation between stage I-II endometrial carcinoma and endometrial polyp with combination of APTw and IVIM MR imaging.

PURPOSE: To assess the value of amide proton transfer weighted (APTw) combined with intra-voxel incoherent motion (IVIM) imaging in differential diagnosis of stage I-II endometrial carcinoma (EC) and endometrial polyp (EP). METHODS: A total of 53 female patients (37 cases with EC and 16 cases with EP) confirmed by surgical resection or biopsy from June 2019 to Jan. 2022 were retrospectively reviewed. All patients underwent 3.0 T magnetic resonance imaging (MRI) examination including diffusion weighted imaging (DWI), APTw and IVIM scans. The pure diffusion coefficient (D), pseudo-diffusion coefficient (D⁎), perfusion fraction (f), apparent diffusion coefficient (ADC) and APT values were independently measured by two observers. Intra-class correlation coefficients (ICC) were used to test the consistency of measurements by the two observers. Mann-Whitney U test was performed to analyze the difference of each parameter between EC and EP groups. Receiver operator characteristic (ROC) analysis was performed, and the Delong test was used for ROC curve comparison. Pearson's correlation analysis was used to assess the correlation between APTw and IVIM parameters. RESULTS: There was no significant difference in clinical manifestations between the two groups (P > 0.05). APT and D⁎ values of the EC group were significantly higher than those of the EP group [APT: 2.64 ± 0.50% vs. 2.05 ± 0.58%; and D⁎: (54.06 ± 36.06) × 10-3 mm2/s vs. (30.54 ± 16.67) × 10-3 mm2/s]. D, f and ADC values of EC group were significantly lower than those of EP group [D: 0.62(0.53,0.76) × 10-3 mm2/s vs. (1.45 ± 0.48) × 10-3 mm2/s; f: 22.18 ± 8.08% vs. 30.80 ± 8.92%; and ADC: (0.88 ± 0.16) × 10-3 mm2/s vs. (1.57 ± 0.43) × 10-3 mm2/s]. The area under ROC curves were observed as: AUC (IVIM+APT) > AUC (D) > AUC (ADC) > AUC (APT) > AUC (f) > AUC (D⁎). Delong test suggested statistical significance between AUC by APT and D, D and D⁎, D and f, D⁎ and ADC, APT and com(IVIM+APT), D⁎ and com(IVIM+APT), as well as f and com(IVIM+APT). No significant correlation between the APT and IVIM parameters was observed in either EC or EP group. CONCLUSION: Both APT and IVIM parameters showed statistical differences between EC and EP. With combination of APT and IVIM parameters, the diagnostic accuracy between EC and EP can be significantly improved.

Association Between Perivascular Adipose Tissue Density and Atherosclerosis in the Descending Thoracic Aorta.

Radiodensity measured by computed tomography (CT) in Hounsfield Units (HU) is emerging as a clinical tool for detecting perivascular adipose tissue (PVAT) inflammation. In the present study, we hypothesized that PVAT radiodensity might predict the risk of descending thoracic aorta atherosclerosis. A total of 73 subjects who underwent CT angiography to investigate aortic disease were retrospectively analyzed. PVAT radiodensity, aortic complex plaque (ACP), mean plaque-burden score (MPBS), and plaque density were measured, and the association between them was analyzed. Perivascular adipose tissue radiodensity (HU) in patients with different aortic plaques grades (grade 1, 2, 3, and 4) were -93.71 ± 2.50, -93.63 ± 3.93, -90.24 ± 4.49, and -89.90 ± 5.18, respectively, and the difference was significant (P = .010). In the regression analysis, PVAT radiodensity was an independent predictor of ACP, with an OR of 1.263. In the linear analysis, PVAT radiodensity was an independent predictor of MPBS, with a ß-coefficient of .073. In the univariate analysis, only the PVAT radiodensity was significantly associated with plaque density, with a ß-coefficient of -1.666. In conclusion, PVAT density was independently related to descending thoracic aorta atherosclerosis.

Bone collision detection method for robot assisted fracture reduction based on vibration excitation.

BACKGROUND AND OBJECTIVE: In the process of robotic fracture reduction, there is a risk of unintended collision of broken bones, which is not conducive to ensuring the safety of the reduction system. In order to solve this problem, this paper proposed a vibration-based collision detection method for fracture reduction process. METHODS: Based on the two degree-of-freedom vibration response model, the factors affecting the respond of the vibration, including the excitation voltage, the clamping length at the proximal and distal ends, the mass and tensile force of the soft tissue, were obtained. The effects of these factors on the vibration transfer performance of broken bones and soft tissue were investigated by single factor experiments. RESULTS: The results showed that, in terms of peak value, the increase of excitation voltage would make the vibration amplitude increase linearly, and the increase of soft tissue mass and tension increased the vibration transmission capacity of soft tissue in the frequency range of 500-1000 Hz. In terms of peak frequency, the clamping length at the distal end had the greatest influence, which reached 74 Hz, followed by 45 Hz at the proximal end. While the influence of other factors was little. According to single factor experiments, the excitation frequency in the verification experiments was determined as 677 Hz. Under the vibration interference with the acceleration amplitude of 1.2 G, this method achieved correct detection. CONCLUSION: This research developed a broken bone collision detection method based on vibration excitation. The method can correctly detect the collision of broken bones with strong anti-interference ability. It is of great significance to improve the safety of fracture reduction process.

Multiparametric MRI-based nomograms in predicting positive surgical margins of prostate cancer after laparoscopic radical prostatectomy.

Background: Positive surgical margins (PSMs) are an independent risk factor of biochemical recurrence in patients with prostate cancer (PCa) after laparoscopic radical prostatectomy; however, limited MRI-based predictive tools are available. This study aimed to develop a novel nomogram combining clinical and multiparametric MRI (mpMRI) parameters to reduce PSMs by improving surgical planning. Methods: One hundred and three patients with PCa (55 patients with negative surgical margins [NSMs] and 48 patients with PSMs) were included in this retrospective study. The following parameters were obtained using GE Functool post-processing software: diffusion-weighted imaging (DWI); intravoxel incoherent motion model (IVIM); and diffusion kurtosis imaging (DKI). Patients were divided into different training sets and testing sets for different targets according to a ratio of 7:3. The least absolute shrinkage and selection operator (LASSO) regression algorithm was used to analyze the data set to select the optimal MRI predictors. Preoperatively clinical parameters used to build a clinical nomogram (C-nomogram). Multivariable logistic regression analysis was used to build an MRI nomogram (M-nomogram) by introducing the MRI parameters. Based on the MRI and clinical parameters, build an MRI combined with clinical parameters nomogram (MC-nomogram). Comparisons with the M-nomogram and MC-nomogram were based on discrimination, calibration, and decision curve analysis (DCA). A 3-fold cross-validation method was used to assess the stability of the nomogram. Results: There was no statistical difference in AUC between the C-nomogram (sensitivity=64%, specificity=65% and AUC=0.683), the M-nomogram (sensitivity=57%, specificity=88% and AUC=0.735) and the MC-nomogram (sensitivity= 64%, specificity=82% and AUC=0.756). The calibration curves of the three nomograms used to predict the risk of PSMs in patients with PCa showed good agreement. The net benefit of the MC-nomogram was higher than the others (range, 0.2-0.7). Conclusions: The mpMRI-based nomogram can predict PSMs in PCa patients. Although its AUC (0.735) is not statistically different from that of the clinical-based nomogram AUC (0.683). However, mpMRI-based nomogram has higher specificity (88% VS. 63%), model stability, and clinical benefit than clinical-based nomogram. And the predictive ability of mpMRI plus clinical parameters for PSMs is further improved.

Effect of process parameters on the temperature changes during robotic bone drilling.

In medical surgery, bone drilling is an inevitable procedure. The thermal necrosis in the drilling process can affect post-operative recovery. In this study, the method of drill bit precooling is proposed in bone drilling with robot assisted system. The influence of process parameters on the drilling temperature were investigated and analyzed. The results showed that the method of drill bit precooling could reduce the drilling temperature. The drill bit starting temperature and the feed rate were more important parameters on the drilling temperature compared with rotational speed and cooling length of the drill bit. The quadratic regression model obtained from response surface experiments can predicted the drilling temperature correctly under the range of process parameters in this study. The optimal parameter combination is rotational speed = 1610 rpm, feed rate = 0.5 mm/s, the starting temperature of drill bit = 8°C, and the cooling length = 34.8 mm. The results provide an effective method to reduce thermal necrosis of bone cells in drilling.

Influence of parameters on temperature rise and chips morphology in low-frequency vibration-assisted bone drilling.

In orthopedics and surgery, bone drilling is an important operation for inserting screws and fixing prostheses. A nonnegligible problem which can affect post-operative recovery is the thermal necrosis. For this problem, the method of low-frequency vibration-assisted drilling (LFVAD) was applied in the process of bone drilling in this paper. The influences of parameters (feed rate, rotational speed, vibration frequency and amplitude) on the cutting performances (cutting temperature and chip morphology) were investigated. The results indicate that LFVAD can produce lower temperature compared with conventional drilling (CD). In LFVAD, rotational speed and vibration amplitude are more important parameters on the drilling temperature and chip morphology compared to feed rate and vibration frequency. In addition, according to the trajectories of the cutting edge of drill bit, a mathematical model of heat generation and dissipation was developed in LFVAD.

Magnetic Resonance Imaging Assessment of Abdominal Ectopic Fat Deposition in Correlation With Cardiometabolic Risk Factors.

Purpose: Ectopic fat accumulation and abdominal fat distribution may have different cardiometabolic risk profiles. This study aimed to assess the associations between various magnetic resonance imaging (MRI)-acquired fat depots and cardiometabolic risk factors. Methods: A total of 320 subjects with median age of 59 years, 148 men and 172 women, were enrolled in the study. Visceral adipose tissue (VAT) area and fat fraction (FF), subcutaneous adipose tissue (SAT) area and FF at the L1-L2 levels, preperitoneal adipose tissue (pPAT) area and FF, hepatic FF, pancreatic FF, and intramuscular FF were assessed by MRI FF maps. The associations of various MRI-acquired fat depots with blood pressure, glucose, and lipid were examined using sex-stratified linear regression. Logistic regression stratified by sex was used to analyze the association of various MRI-acquired fat depots with the risk of hypertension, T2DM, and dyslipidemia. Results: The intraclass correlation coefficient (ICC) values were >0.9, which suggested good interobserver and intraobserver agreement. VAT area, V/S, hepatic fat, pancreatic fat, and pPAT rather than SAT area were significantly associated with multiple cardiometabolic risk factors (all p < 0.05). However, the patterns of these correlations varied by sex and specific risk factors. Also, VAT and SAT FF were only significantly associated with multiple cardiometabolic risk factors in women (all p < 0.05). Conclusions: VAT, hepatic fat, pancreatic fat, and pPAT were associated with cardiovascular metabolic risk factors independent of BMI. The patterns of these correlations were related to gender. These findings further the understanding of the association between ectopic fat deposition and cardiometabolic risk factors and help to better understand the obesity heterogeneity.

Evaluation of brown adipose tissue with intermolecular double-quantum coherence magnetic resonance spectroscopy at 3.0 T.

In the current study, we propose a single-voxel (SV) magnetic resonance spectroscopy (MRS) pulse sequence, based on intermolecular double-quantum coherence (iDQC), for in vivo specific assessment of brown adipose tissue (BAT) at 3 T. The multilocular adipocyte, present in BAT, typically contains a large number of small lipid droplets surrounded by abundant intracellular water, while the monolocular adipocyte, present in white adipose tissue (WAT), accommodates only a single large lipid droplet with much less water content. The SV-iDQC sequence probes the spatial correlation between water and fat spins at a distance of about the size of an adipocyte, thus can be used for assessment of BAT, even when mixed with WAT and/or muscle tissues. This sequence for measurement of water-to-fat (water-fat) iDQC signals was tested on phantoms and mouse BAT and WAT tissues. It was then used to differentiate adipose tissues in the supraclavicular and subcutaneous regions of healthy youth human volunteers (n = 6). Phantom results with water-fat emulsions demonstrated enhanced water-fat iDQC signal with increased voxel size, increased energy level of emulsification, or increased distribution balance of water and fat spins. The animal tissue experiments resulted in obvious water-fat iDQC signal in mouse BAT, while this signal was almost absent in the WAT spectrum. The optimal choice of the dipolar coupling distance for the observation was approximately 100 µm, as tested on both emulsion phantom and animal tissue. The water-fat iDQC signals observed in the supraclavicular adipose tissues were higher than in the subcutaneous adipose tissues in healthy young volunteers (0.43 ± 0.36 vs. 0.10 ± 0.06, p = 0.06). It was concluded that the iDQC-based sequence has potential for assessment of mouse and human BAT at 3 T, which is of interest for clinical research and the diagnosis of obesity and associated diseases.

Bone collision detection method for robot assisted fracture reduction based on force curve slope.

BACKGROUND AND OBJECTIVE: The application of robot technology in fracture reduction ensures the minimal invasiveness and accurate operation process. Most of the existing robot assisted fracture reduction systems don't have the function of bone collision detection, which is very important for system safety. In view of the deficiencies in the research of this field, a broken bone collision detection method based on the slope ratio of force curve was proposed in this paper, which could realize the real-time detection. METHODS: In order to analyze the factors influencing the slope of force curve, a collision mechanical model based on three-element viscoelastic model was established. The effects of four factors on the slope ratio of the force curve were studied based on the mechanical model. The proposed collision detection model was analyzed in detail. By drawing slope ratio curves under various experimental conditions, the universality of the collision detection model was proved; by comparative simulation, the differences between the slope ratio curves before and after optimization were analyzed. The factors that affect the performance of the detection model were also analyzed. RESULTS: The results of collision experiments show that the increase of moving speed of distal bone and soft tissue mass reduces the slope ratio, while the increase of collision angle increases the slope ratio. In the verification experiment, the minimum main peak of KRopt curve is 14.16 and the maximum is 220.7, the maximum interference value before the peak is 6.1. When the detection threshold is 10, the model can detect the collision state of the broken bone. It is also proved that after optimization, the model can effectively filter out invalid waveforms and reduce the occurrence of false detections. When a=5 and b=40, the detection model has sufficient stability and a low detection time delay. CONCLUSION: This research developed a broken bone collision detection method based on the slope ratio of the force curve. After optimization, the method has good adaptability under a variety of experimental conditions. The collision of broken bones can be judged by setting an appropriate detection threshold. The application of this method in the robot fracture reduction system will improve the safety of the system.

Hepatic fat quantification of magnetic resonance imaging whole-liver segmentation for assessing the severity of nonalcoholic fatty liver disease: comparison with a region of interest sampling method.

BACKGROUND: Accurate and early assessment of the hepatic fat content is crucial for patients with nonalcoholic fatty liver disease (NAFLD). For years, magnetic resonance imaging (MRI) has been considered the optimal noninvasive method for the assessment of fat accumulation. To avoid time-consuming manual placement of multiple regions of interest (ROI), the use of whole-liver segmentation has been proposed to measure liver fat, mainly for heterogeneous fat deposition. However, it remains uncertain whether the hepatic mean fat fraction (FF) obtained by whole-liver segmentation with the inclusion of intrahepatic vasculature is consistent with the traditional ROI sampling method. In this study, we assessed the accuracy of hepatic mean FF obtained by whole-liver segmentation in patients of NAFLD with different severities using the ROI sampling method as a reference standard. METHODS: Hepatic FFs were measured by whole-liver segmentation and the ROI sampling method (reference standard) using MRI scanning with the iterative decomposition of water and fat with echo an asymmetry at least-square estimation-iron quantification (IDEAL-IQ) sequence. SPSS version 25.0 software was used to analyze the correlation and consistency of data between the two methods. RESULTS: There was a strong correlation in hepatic FF between whole-liver segmentation and the ROI sampling method in healthy, mild, and moderate steatosis patients (r = 0.943, 0.990, and 0.961, respectively). Bland-Altman analysis showed a small bias of +0.50±0.27 and +0.05±0.30, which indicated a small overestimation when using whole-liver segmentation in healthy subjects and mild NAFLD patients. The 95% limits of agreement ranged from +1.02 to -0.03, and from +0.65 to -0.55, respectively. However, a small bias of -0.96±0.77 was also evident, which indicated a small underestimation when using whole-liver segmentation in moderate NAFLD patients. The 95% limits of agreement ranged from +0.56 to -2.48. CONCLUSIONS: Due to inclusion of the intrahepatic vasculature, whole-liver segmentation has some effects on hepatic FF assessment in patients with different NAFLD severities; yet, it does not significantly affect the assessment of whole-liver FF in MRI FF maps.

Radiomics Analysis Based on Contrast-Enhanced MRI for Prediction of Therapeutic Response to Transarterial Chemoembolization in Hepatocellular Carcinoma.

PURPOSE: To investigate the role of contrast-enhanced magnetic resonance imaging (CE-MRI) radiomics for pretherapeutic prediction of the response to transarterial chemoembolization (TACE) in patients with hepatocellular carcinoma (HCC). METHODS: One hundred and twenty-two HCC patients (objective response, n = 63; non-response, n = 59) who received CE-MRI examination before initial TACE were retrospectively recruited and randomly divided into a training cohort (n = 85) and a validation cohort (n = 37). All HCCs were manually segmented on arterial, venous and delayed phases of CE-MRI, and total 2367 radiomics features were extracted. Radiomics models were constructed based on each phase and their combination using logistic regression algorithm. A clinical-radiological model was built based on independent risk factors identified by univariate and multivariate logistic regression analyses. A combined model incorporating the radiomics score and selected clinical-radiological predictors was constructed, and the combined model was presented as a nomogram. Prediction models were evaluated by receiver operating characteristic curves, calibration curves, and decision curve analysis. RESULTS: Among all radiomics models, the three-phase radiomics model exhibited better performance in the training cohort with an area under the curve (AUC) of 0.838 (95% confidence interval (CI), 0.753 - 0.922), which was verified in the validation cohort (AUC, 0.833; 95% CI, 0.691 - 0.975). The combined model that integrated the three-phase radiomics score and clinical-radiological risk factors (total bilirubin, tumor shape, and tumor encapsulation) showed excellent calibration and predictive capability in the training and validation cohorts with AUCs of 0.878 (95% CI, 0.806 - 0.950) and 0.833 (95% CI, 0.687 - 0.979), respectively, and showed better predictive ability (P = 0.003) compared with the clinical-radiological model (AUC, 0.744; 95% CI, 0.642 - 0.846) in the training cohort. A nomogram based on the combined model achieved good clinical utility in predicting the treatment efficacy of TACE. CONCLUSION: CE-MRI radiomics analysis may serve as a promising and noninvasive tool to predict therapeutic response to TACE in HCC, which will facilitate the individualized follow-up and further therapeutic strategies guidance in HCC patients.

Radiomics Analysis Based on Multiparametric MRI for Predicting Early Recurrence in Hepatocellular Carcinoma After Partial Hepatectomy.

BACKGROUND: Preoperative prediction of early recurrence (ER) of hepatocellular carcinoma (HCC) plays a critical role in individualized risk stratification and further treatment guidance. PURPOSE: To investigate the role of radiomics analysis based on multiparametric MRI (mpMRI) for predicting ER in HCC after partial hepatectomy. STUDY TYPE: Retrospective. POPULATION: In all, 113 HCC patients (ER, n = 58 vs. non-ER, n = 55), divided into training (n = 78) and validation (n = 35) cohorts. FIELD STRENGTH/SEQUENCE: 1.5T or 3.0T, gradient-recalled-echo in-phase T1 -weighted imaging (I-T1 WI) and opposed-phase T1 WI (O-T1 WI), fast spin-echo T2 -weighted imaging (T2 WI), spin-echo planar diffusion-weighted imaging (DWI), and gradient-recalled-echo contrast-enhanced MRI (CE-MRI). ASSESSMENT: In all, 1146 radiomics features were extracted from each image sequence, and radiomics models based on each sequence and their combination were established via multivariate logistic regression analysis. The clinicopathologic-radiologic (CPR) model and the combined model integrating the radiomics score with the CPR risk factors were constructed. A nomogram based on the combined model was established. STATISTICAL TESTS: Receiver operating characteristic (ROC) curve analysis was used to evaluate the discriminative performance of each model. The potential clinical usefulness was evaluated by decision curve analysis (DCA). RESULTS: The radiomics model based on I-T1 WI, O-T1 WI, T2 WI, and CE-MRI sequences presented the best performance among all radiomics models with an area under the ROC curve (AUC) of 0.771 (95% confidence interval (CI): 0.598-0.894) in the validation cohort. The combined nomogram (AUC: 0.873; 95% CI: 0.756-0.989) outperformed the radiomics model and the CPR model (AUC: 0.742; 95% CI: 0.577-0.907). DCA demonstrated that the combined nomogram was clinically useful. DATA CONCLUSION: The mpMRI-based radiomics analysis has potential to predict ER of HCC patients after hepatectomy, which could enhance risk stratification and provide support for individualized treatment planning. EVIDENCE LEVEL: 4. TECHNICAL EFFICACY: Stage 4.

Quantification of Hepatic Fat Fraction in Patients With Nonalcoholic Fatty Liver Disease: Comparison of Multimaterial Decomposition Algorithm and Fat (Water)-Based Material Decomposition Algorithm Using Single-Source Dual-Energy Computed Tomography.

METHODS: Hepatic fat fractions were quantified by noncontrast (HFFnon-CE) and contrast-enhanced single-source dual-energy computed tomography in arterial phase (HFFAP), portal venous phase (HFFPVP) and equilibrium phase (HFFEP) using MMD in 19 nonalcoholic fatty liver disease patients. The fat concentration was measured on fat (water)-based images. As the standard of reference, magnetic resonance iterative decomposition of water and fat with echo asymmetry and least-squares estimation-iron quantification images were reconstructed to obtain HFF (HFFIDEAL-IQ). RESULTS: There was a strong correlation between HFFnon-CE, HFFAP, HFFPVP, HFFEP, fat concentration and HFFIDEAL-IQ (r = 0.943, 0.923, 0.942, 0.952, and 0.726) with HFFs having better correlation with HFFIDEAL-IQ. Hepatic fat fractions did not significantly differ across scanning phases. The HFFs of 3-phase contrast-enhanced computed tomography had a good consistency with HFFnon-CE. CONCLUSIONS: Hepatic fat fraction using MMD has excellent correlation with that of magnetic resonance imaging, is independent of the computed tomography scanning phases, and may be used as a routine technique for quantitative assessment of HFF.

Clinical flexible needle puncture path planning based on particle swarm optimization.

BACKGROUND AND OBJECTIVE: Percutaneous puncture with flexible needle has important value in clinical application for its low trauma and flexible path. However, it is difficult to guarantee accuracy and avoid obstacles in puncture process. Therefore, developing a viable path planning method is particularly important. In this research, the bending deformation law of flexible needles during puncture was studied and the puncture path was planned to provide a feasible method for clinical application of flexible needles. METHODS: According to the researchs that have been conducted, the path of the flexible needle in the tissue could be considered as a circular arc stitching. This research studied the calculation method of arc radius and obtained its actual value by the puncture experiments. Based on the arc model, the spatial transformation method of three-dimensional path planning was studied. In addition, a simplified particle swarm optimization (PSO) was applied into the process of path planning by changing the central angle of arc and the rotation angle of the needle body. RESULTS: The results of Experiment 1 showed that the path radius of the flexible needle pierced into gelatin prosthesis was influenced by four parameters, which were needle diameter, tip angle, puncture speed and the weight ratio of gelatin powder. As the needle diameter and tip angle increased, the radius of needle path tended to increase, but when the puncture speed and gelatin mass ratio increased, the radius of needle path decreased. The results of Experiment 2 showed that the distances of needle tip apart from target point were 3.2 mm (barrier-free experiments) and 1.8 mm (obstacle experiments). CONCLUSIONS: This research links the intelligent algorithm with the flexible needle puncture tissue process, which has high value in future clinical application. By setting the correct boundary conditions and parameters, the flexible needle can be planned to reach the target point accurately.

Study on the Discharge Characteristics of Single-Pulse Discharge in Micro-EDM.

To further study the discharge characteristics and machining mechanism of micro-electrical discharge machining (micro-EDM), the variation trends of the discharge energy and discharge crater size with actual discharge duration are discussed based on single-pulse experiments. The polarity effect of micro-EDM was analyzed according to the motion characteristics of electrons and ions in the discharge plasma channel. The results show that the discharge current and voltage of micro-EDM were independent of the discharge width and open-circuit voltage. The energy utilization rate of the short-pulse discharge was relatively high, and the energy utilization rate decreased gradually as the discharge duration increased. Even if the mass of the positive ion was much larger than that of the electron, the kinetic energy of the positive ion was still less than that of the electron when bombarding the surface of the electrode. The acceleration and speed of electrons were very high, and the number of times that electrons bombarded the surface of positive electrode was more than 600 times that of positive ions bombarding the surface of the negative electrode during the same time.