Comparison of Diatrizoate and Iohexol for Patient Acceptance and Fecal-Tagging Performance in Noncathartic CT Colonography.

OBJECTIVE: The aim of this study was to compare diatrizoate and iohexol regarding patient acceptance and fecal-tagging performance in noncathartic computed tomography colonography. METHODS: This study enrolled 284 volunteers with fecal tagging by either diatrizoate or iohexol at an iodine concentration of 13.33 mg/mL and an iodine load of 24 g. Patient acceptance was rated on a 4-point scale of gastrointestinal discomfort. Two gastrointestinal radiologists jointly analyzed image quality, fecal-tagging density and homogeneity, and residual contrast agent in the small intestine. The results were compared by the generalized estimating equation method. RESULTS: Patient acceptance was comparable between the 2 groups (3.95 ± 0.22 vs 3.96 ± 0.20, P = 0.777). The diatrizoate group had less residual fluid and stool than the iohexol group ( P = 0.019, P = 0.004, respectively). There was no significant difference in colorectal distention, residual fluid, and stool tagging quality between the 2 groups (all P 's > 0.05). The mean 2-dimensional image quality score was 4.59 ± 0.68 with diatrizoate and 3.60 ± 1.14 with iohexol ( P < 0.001). The attenuation of tagged feces was 581 ± 66 HU with diatrizoate and 1038 ± 117 HU with iohexol ( P < 0.001). Residual contrast agent in the small intestine was assessed at 55.3% and 62.3% for the diatrizoate group and iohexol group, respectively ( P = 0.003). CONCLUSIONS: Compared with iohexol, diatrizoate had better image quality, proper fecal-tagging density, and more homogeneous tagging along with comparable excellent patient acceptance, and might be more suitable for fecal tagging in noncathartic computed tomography colonography.

Automatic Image Segmentation and Grading Diagnosis of Sacroiliitis Associated with AS Using a Deep Convolutional Neural Network on CT Images.

Ankylosing spondylitis (AS) is a chronic inflammatory disease that causes inflammatory low back pain and may even limit activity. The grading diagnosis of sacroiliitis on imaging plays a central role in diagnosing AS. However, the grading diagnosis of sacroiliitis on computed tomography (CT) images is viewer-dependent and may vary between radiologists and medical institutions. In this study, we aimed to develop a fully automatic method to segment sacroiliac joint (SIJ) and further grading diagnose sacroiliitis associated with AS on CT. We studied 435 CT examinations from patients with AS and control at two hospitals. No-new-UNet (nnU-Net) was used to segment the SIJ, and a 3D convolutional neural network (CNN) was used to grade sacroiliitis with a three-class method, using the grading results of three veteran musculoskeletal radiologists as the ground truth. We defined grades 0-I as class 0, grade II as class 1, and grades III-IV as class 2 according to modified New York criteria. nnU-Net segmentation of SIJ achieved Dice, Jaccard, and relative volume difference (RVD) coefficients of 0.915, 0.851, and 0.040 with the validation set, respectively, and 0.889, 0.812, and 0.098 with the test set, respectively. The areas under the curves (AUCs) of classes 0, 1, and 2 using the 3D CNN were 0.91, 0.80, and 0.96 with the validation set, respectively, and 0.94, 0.82, and 0.93 with the test set, respectively. 3D CNN was superior to the junior and senior radiologists in the grading of class 1 for the validation set and inferior to expert for the test set (P < 0.05). The fully automatic method constructed in this study based on a convolutional neural network could be used for SIJ segmentation and then accurately grading and diagnosis of sacroiliitis associated with AS on CT images, especially for class 0 and class 2. The method for class 1 was less effective but still more accurate than that of the senior radiologist.

[CT and MRI fusion based on generative adversarial network and convolutional neural networks under image enhancement].

Aiming at the problems of missing important features, inconspicuous details and unclear textures in the fusion of multimodal medical images, this paper proposes a method of computed tomography (CT) image and magnetic resonance imaging (MRI) image fusion using generative adversarial network (GAN) and convolutional neural network (CNN) under image enhancement. The generator aimed at high-frequency feature images and used double discriminators to target the fusion images after inverse transform; Then high-frequency feature images were fused by trained GAN model, and low-frequency feature images were fused by CNN pre-training model based on transfer learning. Experimental results showed that, compared with the current advanced fusion algorithm, the proposed method had more abundant texture details and clearer contour edge information in subjective representation. In the evaluation of objective indicators, Q AB/F, information entropy (IE), spatial frequency (SF), structural similarity (SSIM), mutual information (MI) and visual information fidelity for fusion (VIFF) were 2.0%, 6.3%, 7.0%, 5.5%, 9.0% and 3.3% higher than the best test results, respectively. The fused image can be effectively applied to medical diagnosis to further improve the diagnostic efficiency.

Change in humeral anchor position significantly affects isometry in ulnar collateral ligament repair: a 3-dimensional computer modeling study.

BACKGROUND: Medial ulnar collateral ligament (UCL) repair utilization is increasing in recent years, bolstered by shorter rehabilitation and satisfactory clinical outcomes. Although previous literature has illustrated the importance of tunnel position on restoring graft isometry in reconstruction, there remains a paucity of literature guiding anchor placement in UCL repair. The purpose of this study is to design a 3-dimensional (3D) elbow model to understand the effect of anchor location on UCL repair isometry. METHODS: A 3D computer model of an elbow joint was created using computed tomographic and magnetic resonance imaging MRI scans from a single patient. The humeral and ulnar attachments of the UCL were plotted using 3 methodologies: (1) geometric cloud mapping and (2) quantitative measurements from the anatomic studies by Camp et al and (3) Frangiamore et al. A 3.5-mm-diameter clockface was placed on each attachment site, which allowed for simulation of 12 distinct 1.75-mm deviations in anchor position. The 3 models were ranged through 0°-120° at 10° increments, and the 3D distances were measured between the ligament centroids. The humeral and ulnar anchors were sequentially repositioned around the clockfaces, and construct lengths were again measured to evaluate changes in isometry. A paired Student t test was performed to determine if there was a significant difference in isometry between the humeral and ulnar anchor deviations. RESULTS: Using method 1, the UCL repair length at 90° of elbow flexion was 26.8 mm. This construct underwent 13.6 mm of total excursion for a 46.4% change in length throughout its arc of motion. Method 2 produced a 19.3-mm construct that underwent 0.8 mm of excursion for a 3.9% length change throughout the arc. Method 3 produced a 24.5-mm construct that underwent 2.3 mm of excursion for a 9.4% length change. Identifying ligament footprints using the quantitative anatomic measurements from Camp et al and Frangiamore et al improved construct isometry through 120° of flexion (length changes of 3.9% and 9.4%, respectively) when compared to using the geometric cloud technique alone (46.4% length change). Humeral anchor deviations produced a significant increase in repair construct excursion compared with ulnar anchor deviations (P < .001). CONCLUSION: When performing UCL repair, small deviations in humeral anchor position may significantly influence ligament repair isometry. Using quantitative anatomic data may help identify anchor positions with improved repair isometry. Particularly when addressing detachments of the humeral footprint, surgeons should be critical of the humeral anchor position in order to restore native anatomy and optimal biomechanics.

Risk stratification of thymic epithelial tumors by using a nomogram combined with radiomic features and TNM staging.

OBJECTIVES: To construct and validate a nomogram model that integrated the CT radiomic features and the TNM staging for risk stratification of thymic epithelial tumors (TETs). METHODS: A total of 136 patients with pathology-confirmed TETs who underwent CT examination were collected from two institutions. According to the WHO pathological classification criteria, patients were classified into low-risk and high-risk groups. The TNM staging was determined in terms of the 8th edition AJCC/UICC staging criteria. LASSO regression was performed to extract the optimal features correlated to risk stratification among the 704 radiomic features calculated. A nomogram model was constructed by combining the Radscore and the TNM staging. The clinical performance was evaluated by ROC analysis, calibration curve, and decision curve analysis (DCA). The Kaplan-Meier (KM) analysis was employed for survival analysis. RESULTS: Five optimal features identified by LASSO regression were employed to calculate the Radscore correlated to risk stratification. The nomogram model showed a better performance in both training cohort (AUC = 0.84, 95%CI 0.75-0.91) and external validation cohort (AUC = 0.79, 95%CI 0.69-0.88). The calibration curve and DCA analysis indicated a better accuracy of the nomogram model for risk stratification than either Radscore or the TNM staging alone. The KM analysis showed a significant difference between the two groups stratified by the nomogram model (p = 0.02). CONCLUSIONS: A nomogram model that integrated the radiomic signatures and the TNM staging could serve as a reliable model of risk stratification in predicting the prognosis of patients with TETs. KEY POINTS: • The radiomic features could be associated with the TET pathophysiology. • TNM staging and Radscore could independently stratify the risk of TETs. • The nomogram model is more objective and more comprehensive than previous methods.

Predicting the response to neoadjuvant chemotherapy for breast cancer: wavelet transforming radiomics in MRI.

BACKGROUND: The purpose of this study was to investigate the value of wavelet-transformed radiomic MRI in predicting the pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) for patients with locally advanced breast cancer (LABC). METHODS: Fifty-five female patients with LABC who underwent contrast-enhanced MRI (CE-MRI) examination prior to NAC were collected for the retrospective study. According to the pathological assessment after NAC, patient responses to NAC were categorized into pCR and non-pCR. Three groups of radiomic textures were calculated in the segmented lesions, including (1) volumetric textures, (2) peripheral textures, and (3) wavelet-transformed textures. Six models for the prediction of pCR were Model I: group (1), Model II: group (1) + (2), Model III: group (3), Model IV: group (1) + (3), Model V: group (2) + (3), and Model VI: group (1) + (2) + (3). The performance of predicting models was compared using the area under the receiver operating characteristic (ROC) curves (AUC). RESULTS: The AUCs of the six models for the prediction of pCR were 0.816 ± 0.033 (Model I), 0.823 ± 0.020 (Model II), 0.888 ± 0.025 (Model III), 0.876 ± 0.015 (Model IV), 0.885 ± 0.030 (Model V), and 0.874 ± 0.019 (Model VI). The performance of four models with wavelet-transformed textures (Models III, IV, V, and VI) was significantly better than those without wavelet-transformed textures (Model I and II). In addition, the inclusion of volumetric textures or peripheral textures or both did not result in any improvements in performance. CONCLUSIONS: Wavelet-transformed textures outperformed volumetric and/or peripheral textures in the radiomic MRI prediction of pCR to NAC for patients with LABC, which can potentially serve as a surrogate biomarker for the prediction of the response of LABC to NAC.

The influencing factors and functions of DNA G-quadruplexes.

G-quadruplexes form folded structures because of tandem repeats of guanine sequences in DNA or RNA. They adopt a variety of conformations, depending on many factors, including the type of loops and cations, the nucleotide strand number, and the main strand polarity of the G-quadruplex. Meanwhile, the different conformations of G-quadruplexes have certain influences on their biological functions, such as the inhibition of transcription, translation, and DNA replication. In addition, G-quadruplex binding proteins also affect the structure and function of G-quadruplexes. Some chemically synthesized G-quadruplex sequences have been shown to have biological activities. For example, bimolecular G-quadruplexes of AS1411 act as targets of exogenous drugs that inhibit the proliferation of malignant tumours. G-quadruplexes are also used as vehicles to deliver nanoparticles. Thus, it is important to identify the factors that influence G-quadruplex structures and maintain the stability of G-quadruplexes. Herein, we mainly discuss the factors influencing G-quadruplexes and the synthetic G-quadruplex, AS1411. SIGNIFICANCE OF THE STUDY: This review summarizes the factors that influence G-quadruplexes and the functions of the synthetic G-quadruplex, AS1411. It also discusses the use of G-quadruplexes for drug delivery in tumour therapy.

Preliminary Study of MR and Fluorescence Dual-mode Imaging: Combined Macrophage-Targeted and Superparamagnetic Polymeric Micelles.

Purpose: To establish small-sized superparamagnetic polymeric micelles for magnetic resonance and fluorescent dual-modal imaging, we investigated the feasibility of MR imaging (MRI) and macrophage-targeted in vitro. Methods: A new class of superparamagnetic iron oxide nanoparticles (SPIONs) and Nile red-co-loaded mPEG-Lys3-CA4-NR/SPION polymeric micelles was synthesized to label Raw264.7 cells. The physical characteristics of the polymeric micelles were assessed, the T2 relaxation rate was calculated, and the effect of labeling on the cell viability and cytotoxicity was also determined in vitro. In addition, further evaluation of the application potential of the micelles was conducted via in vitro MRI. Results: The diameter of the mPEG-Lys3-CA4-NR/SPION polymeric micelles was 33.8 ± 5.8 nm on average. Compared with the hydrophilic SPIO, mPEG-Lys3-CA4-NR/SPION micelles increased transversely (r2), leading to a notably high r2 from 1.908 µg/mL-1S-1 up to 5.032 µg/mL-1S-1, making the mPEG-Lys3-CA4-NR/SPION micelles a highly sensitive MRI T2 contrast agent, as further demonstrated by in vitro MRI. The results of Confocal Laser Scanning Microscopy (CLSM) and Prussian blue staining of Raw264.7 after incubation with micelle-containing medium indicated that the cellular uptake efficiency is high. Conclusion: We successfully synthesized dual-modal MR and fluorescence imaging mPEG-Lys3-CA4-NR/SPION polymeric micelles with an ultra-small size and high MRI sensitivity, which were effectively and quickly uptaken into Raw 264.7 cells. mPEG-Lys3-CA4-NR/SPION polymeric micelles might become a new MR lymphography contrast agent, with high effectiveness and high MRI sensitivity.

Measurement of Glenoid Bone Loss With 3-Dimensional Magnetic Resonance Imaging: A Matched Computed Tomography Analysis.

PURPOSE: To compare the measurement of glenoid bone surface area (GBSA) and glenoid bone loss (GBL) between 3-dimensional computed tomography (3D CT) and an autosegmentation approach for 3D magnetic resonance imaging (MRI) of patients with recurrent shoulder instability. METHODS: Eight subjects (2 women and 6 men; age range, 15-72 years [mean, 44 ± 19 years]) were consecutively enrolled who had both CT and MRI of the shoulder for clinical shoulder instability. Inclusion criteria were patients with shoulder instability or other shoulder injury who had both a CT scan and MRI performed of the same shoulder. All patients underwent a 3D CT scan and a 3-Tesla 3D MRI with additional volumetric and autosegmented sequences. En face views of the glenoid for both CT and MRI were auto- and manually measured for overall GBSA and GBL using best-fit circle technique; the amount of GBL was compared with loss of GBSA and was expressed as a percentage of bone loss. RESULTS: There were no differences in GBL measured by 3D CT (41 mm2, 6.6%) vs 3D MRI (40 mm2, 6.5%, P = .852). The mean GBSA was not different among the manual- and autocalculated 3D CT (644 mm2 vs 640 mm2, P = .482). In addition, the manual MRI scan glenoid area was similar to the autocalculated 3D MRI (622 mm2 vs 618 mm2, respectively; P = .482). Overall regression analysis demonstrated excellent correlation between CT and MRI for both GBSA and GBL calculations (R2 = 0.84-0.90). CONCLUSIONS: 3D MRI of the glenoid is nearly identical to 3D CT scans for measurement of GBSA and GBL, making 3D MRI a reliable alternative to a CT scan for a preoperative shoulder evaluation of the glenoid pathology. This study shows that a 3D MRI could be a radiation-free and reliable alternative to a preoperative CT shoulder scan. LEVEL OF EVIDENCE: Level III, case-control study.

Genetic variation in the invasive weed Mikania micrantha (Asteraceae) suggests highways as corridors for its dispersal in southern China.

BACKGROUND AND AIMS: Roads as corridors of seed or fruit spatial dispersal have major impacts on the establishment and spread of invasive species, but their precise role in population genetic variation remains poorly understood. The South American weed Mikania micrantha has spread rapidly across southern China since its introduction to the Shenzhen area in 1984. This study investigated how its genetic diversity is distributed along highways, and whether highways have acted as corridors for the rapid expansion of M. micrantha METHODS: Twenty-seven roadside populations were sampled along four highways in southern China, and 787 samples were examined using 12 microsatellite markers. Variation in genetic diversity among populations was quantified and patterns of genetic differentiation were analysed. KEY RESULTS: A high level of genetic diversity was found at both the species and the population levels in this self-incompatible plant (expected heterozygosity = 0·497 and 0·477, respectively; allelic richness = 2·580 and 2·521, respectively). The Wright F-statistic value among populations (0·044, P < 0·01) and the analysis of molecular variance (91 % of genetic variation residing within populations, 9 % among populations within highways and 0 % among the four highways) showed a relatively low level of genetic differentiation among populations, while the principal coordinate and cluster analyses also indicated a lack of clear geographical genetic structure among populations. The calculated Nm value of 5·5 signifies strong gene flow. CONCLUSIONS: The pattern of genetic variation is consistent with facilitated dispersal along highways. The genetic admixtures among the roadside populations imply the occurrence of multiple population introductions during colonization. The long-distance dispersal of seeds associated with vehicular transportation on highways may have played important roles in shaping the genetic variation. This finding highlights the importance of highways as corridors for the spread of M. micrantha in southern China.

Diagnostic Value of Gadoxetic Acid-Enhanced MR Imaging to Distinguish HCA and Its Subtype from FNH: A Systematic Review.

Objective: The purpose of this study was to systematically review the diagnostic performance of gadoxetic acid-enhanced magnetic resonance imaging (Gd-EOB-DTPA-MRI) for differentiation of hepatocellular adenoma (HCA) and focal nodular hyperplasia (FNH), as well as HCA classification by using the low signal intensity (SI) in the hepatobiliary phase (HBP). Methods: A systematic process was used to review all published data in MEDLINE database about Gd-EOB-DTPA-MRI applied to differentiation of HCA and FNH, and classification of HCA by using low SI in the HBP. The pooled sensitivity and specificity were calculated to assess the diagnostic value of low SI in the HBP. Results: A review of 45 articles identified 10 eligible studies with a total of 288 HCA lesions. The pooled proportion of low SI in the HBP of HCA were 91% (95% CI: 0.81-0.97). In specific, the subtypes of HCA were 75% (95% CI: 0.64-0.85) for I-HCA, 100% (95% CI: 0.95-1.00) for H-HCA, 92% (95% CI: 0.70-1.00) for U-HCA, and 59% (95% CI: 0.00-1.00) for b-HCA, respectively. The pooled specificity and sensitivity of low SI in the HBP for distinguishing FNH from HCA were 95% (95% CI: 0.92-0.98) and 92% (95% CI: 0.87-0.96), respectively. Conclusion: Low SI in the HBP of Gd-EOB-DTPA-MRI is associated with higher accuracy for distinguishing HCA from FNH. However, the diagnostic accuracy may be overvalued, especially for the diagnosis of subtypes of b-HCA and I-HCA. Therefore, the risk factors and conventional imaging findings should be take into account simultaneously.

[Efficacy and mechanism of hemoperfusion plus hemodialysis for peripheral neuropathy of uremic patients on maintenance hemodialysis].

OBJECTIVE: To explore the efficacy and mechanism of hemoperfusion (HP) plus hemodialysis (HD) for peripheral neuropathy of uremic patients on maintenance hemodialysis. METHODS: A total of 66 uremic patients on hemodialysis during January 2014 and April 2011 were assigned randomly into HP+HD, low-flux HD and high-flux HD groups (n=22 each). The serum levels of leptin, endothelin-1 (ET-1), parathyroid hormone (PTH) and ß-2 microglobulin were observed pre and post-treatment. And sensory conduction velocity (SCV) was detected simultaneously. RESULTS: After 12-week treatment, the clinical symptoms of group HP+HD improved significantly with an effective rate of 90.91% while improvement was not obvious in groups high-flux and low-flux HD with effective rates of 31.82% and 13.64%. In HP+HD group, the levels of leptin, ET-1, PTH and ß-2MG decreased, sensory conduction velocity increased (P<0.05) and clinical symptoms improved apparently. While in low-flux HD and high-flux HD groups, leptin, ET-1, PTH and ß-2MG had no decrease and SCV showed no improvement (P>0.05). Correlation analysis showed that the levels of leptin, ET-1 and ß-2MG were negatively correlated with SCV (r=-0.57, r=-0.47, r=-0.56). Yet PTH had no correlation with SCV (r=-0.23). CONCLUSION: Hemoperfusion plus hemodialysis may improve the clinical symptoms of peripheral neuropathy of uremic patients on maintenance hemodialysis. And it is probably due to the fact that HP+HD effectively removes such plasma middle and macromolecular toxins as leptin, ET-1, PTH and ß-2MG.

Relationship between whole-body tumor burden, clinical phenotype, and quality of life in patients with neurofibromatosis.

Patients with neurofibromatosis 1 (NF1), NF2, and schwannomatosis share a predisposition to develop multiple nerve sheath tumors. Previous studies have demonstrated that patients with NF1 and NF2 have reduced quality of life (QOL), but no studies have examined the relationship between whole-body tumor burden and QOL in these patients. We administered a QOL questionnaire (the SF-36) and a visual analog pain scale (VAS) to a previously described cohort of adult neurofibromatosis patients undergoing whole-body MRI. One-sample t-tests were used to compare norm-based SF-36 scores to weighted population means. Spearman correlation coefficients and multiple linear regression analyses controlling for demographic and disease-specific clinical variable were used to relate whole-body tumor volume to QOL scales. Two hundred forty-five patients (142 NF1, 53 NF2, 50 schwannomatosis) completed the study. Subjects showed deficits in selected subscales of the SF-36 compared to adjusted general population means. In bivariate analysis, increased tumor volume was significantly associated with pain in schwannomatosis patients, as measured by the SF-36 bodily pain subscale (rho = -0.287, P = 0.04) and VAS (rho = 0.34, P = 0.02). Regression models for NF2 patients showed a positive relationship between tumor burden and increased pain, as measured by the SF-36 (P = 0.008). Patients with NF1, NF2, and schwannomatosis suffer from reduced QOL, although only pain shows a clear relationship to patient's overall tumor burden. These findings suggest that internal tumor volume is not a primary contributor to QOL and emphasize the need for comprehensive treatment approaches that go beyond tumor-focused therapies such as surgery by including psychosocial interventions.

Benign whole body tumor volume is a risk factor for malignant peripheral nerve sheath tumors in neurofibromatosis type 1.

The purpose of this study is to determine whether benign whole body tumor volume of plexiform neurofibromas (PNs) is a risk factor for malignant peripheral nerve sheath tumors (MPNST) in individuals with neurofibromatosis type 1 (NF1). Thirty-one NF1 patients with MPNSTs and 62 age- and sex-matched NF1 patients without MPNSTs, who had undergone whole body magnetic resonance imaging (MRI) were analyzed for benign whole body tumor volume. Mann-Whitney U test, Wilcoxon signed ranks test, Fisher's exact test (two-tailed), and logistic regression analysis were used for statistical analysis. Sixteen percent of all patients with MPNST did not have internal PN. The median whole body benign tumor volume in patients with PN was 352.0 mL among the MPNST group and 3.8 mL in the comparison group (p < 0.001). When the patients were stratified by age as younger or older than 30 years (median age of MPNST diagnosis), the median benign whole body tumor volume was 693.0 mL in MPNST patients and 0.0 mL in control patients younger than 30 years (p < 0.001). The mean number of PNs in MPNST patients was 2.8 (range 0-13, median 2.0) and 1.4 (range 0-13, median 1.0) in patients without MPNST (p = 0.001). The risk of MPNST development increased 0.2 % with each additional mL of benign PN volume (adjusted odds ratio [OR] = 1.002, 95 % confidence interval [CI] 1.001-1.003, p = 0.005) and was higher in patients younger than 30 years (adjusted OR = 1.007, 95 % CI 1.002-1.012, p = 0.003). Higher numbers of PNs, larger whole body benign tumor volume, and younger age are important risk factors for MPNST. We identified a subgroup of patients with MPNST without internal PN on MRI and the lack of correlation of MPNST development with tumor burden in older patients. These findings may alter our belief that all MPNSTs arise from pre-existing PNs and suggest that surveillance MRI based on clinical suspicion may be warranted in older patients, respectively.

Horsetail mixture on rheumatoid arthritis and its regulation on TNF-α and IL-10.

Taking autoimmune inflammation of rheumatoid arthritis as entry point, this paper discussed the clinical effect of horsetail mixture on rheumatoid arthritis (RA) and its mechanism. A total of 60 cases of patients with RA were randomly divided into experimental group and control group using randomized controlled trial. We observed its biochemistry, TNF-α and IL-10 before and after treatment, and then systematically assessed the clinical effect of horsetail on RA. Results showed that the total effective rate of experimental group was 80%, while that of control group was 16.67%. After statistical treatment, the differences between two groups were significant (p<0.01). Comparison of the difference value of TNF-α (p<0.05) and IL-0.05 in serum between groups before and after treatment, there were significant differences. Comparison of CRP within group before and after treatment was significantly different (p<0.05), while comparison of CRP between groups was not significantly different (p>0.05). Comparison of ESR and RF within group before and after treatment was significantly different (p<0.01), and comparison of them between groups was also significantly different (p<0.05). Comparison of difference values within group before and after treatment were also significantly different (p<0.01). It was concluded that horsetail mixture has remarkable curative effect on rheumatoid arthritis, and its clinical application is safe and reliable. It has obvious down regulatory effect on cell factor TNF-α related to RA, that is, it can down regulate the level of pre-inflammatory factor TNF-α as well as the level of anti-inflammatory factor IL-10. Therefore, it is considered that the regulating effect of horsetail mixture on TNF-α and IL-10 is one of the mechanisms of its treatment on RA.

New Model and Public Online Prediction Platform for Risk Stratification of Vocal Cord Leukoplakia.

OBJECTIVE: To extract texture features from vocal cord leukoplakia (VCL) images and establish a VCL risk stratification prediction model using machine learning (ML) techniques. METHODS: A total of 462 patients with pathologically confirmed VCL were retrospectively collected and divided into low-risk and high-risk groups. We use a 5-fold cross validation method to ensure the generalization ability of the model built using the included dataset and avoid overfitting. Totally 504 texture features were extracted from each laryngoscope image. After feature selection, 10 ML classifiers were utilized to construct the model. The SHapley Additive exPlanations (SHAP) was employed for feature analysis. To evaluate the model, accuracy, sensitivity, specificity, and the area under the receiver operating characteristic (ROC) curve (AUC) were utilized. In addition, the model was transformed into an online application for public use and further tested in an independent dataset with 52 cases of VCL. RESULTS: A total of 12 features were finally selected, random forest (RF) achieved the best model performance, the mean accuracy, sensitivity, specificity, and AUC of the 5-fold cross validation were 92.2 ± 4.1%, 95.6 ± 4.0%, 85.8 ± 5.8%, and 90.7 ± 4.9%, respectively. The result is much higher than the clinicians (AUC between 63.1% and 75.2%). The SHAP algorithm ranks the importance of 12 texture features to the model. The test results of the additional independent datasets were 92.3%, 95.7%, 90.0%, and 93.3%, respectively. CONCLUSION: The proposed VCL risk stratification prediction model, which has been developed into a public online prediction platform, may be applied in practical clinical work. LEVEL OF EVIDENCE: 3 Laryngoscope, 134:4329-4337, 2024.

An External Validation Study for Automated Segmentation of Vestibular Schwannoma.

OBJECTIVE: To validate how an automated model for vestibular schwannoma (VS) segmentation developed on an external homogeneous dataset performs when applied to internal heterogeneous data. PATIENTS: The external dataset comprised 242 patients with previously untreated, sporadic unilateral VS undergoing Gamma Knife radiosurgery, with homogeneous magnetic resonance imaging (MRI) scans. The internal dataset comprised 10 patients from our institution, with heterogeneous MRI scans. INTERVENTIONS: An automated VS segmentation model was developed on the external dataset. The model was tested on the internal dataset. MAIN OUTCOME MEASURE: Dice score, which measures agreement between ground truth and predicted segmentations. RESULTS: When applied to the internal patient scans, the automated model achieved a mean Dice score of 61% across all 10 images. There were three tumors that were not detected. These tumors were 0.01 ml on average (SD = 0.00 ml). The mean Dice score for the seven tumors that were detected was 87% (SD = 14%). There was one outlier with Dice of 55%-on further review of this scan, it was discovered that hyperintense petrous bone had been included in the tumor segmentation. CONCLUSIONS: We show that an automated segmentation model developed using a restrictive set of siloed institutional data can be successfully adapted for data from different imaging systems and patient populations. This is an important step toward the validation of automated VS segmentation. However, there are significant shortcomings that likely reflect limitations of the data used to train the model. Further validation is needed to make automated segmentation for VS generalizable.

Use of multidetector computed tomography to guide management of pneumothorax.

PURPOSE OF REVIEW: Pneumothorax, a potentially life-threatening condition, is present in about one-third of chest trauma patients. Traditionally, pneumothorax has been diagnosed and managed by use of chest radiography, which has been found inaccurate and inconsistent. With the ubiquitous application of multidetector computed tomography (MDCT) in emergency care, MDCT quantification of pneumothoraces becomes an emerging technique for accurate determination of the size of pneumothoraces. The use of MDCT quantification provides a promising means to improve pneumothorax management. RECENT FINDINGS: Recent studies have demonstrated that MDCT is the gold standard for detecting pneumothorax and MDCT provides an effective imaging modality for the accurate measurement of the volume of pneumothoraces. The use of MDCT volumetric quantification of pneumothoraces has been evidenced in the improvement of performance in pneumothorax management for clinically stable chest trauma patients. SUMMARY: The MDCT volumetric quantification of pneumothoraces is a new concept in the care of chest trauma patients and has the potential to improve pneumothorax management. Further clinical studies are needed to establish a MDCT-based clinical guideline for pneumothorax management.