Predictive Value of the Diffusion Magnetic Resonance Imaging Technique for the Postoperative Outcome of Cervical Spondylotic Myelopathy.

BACKGROUND: Diffusion magnetic resonsance imaging (dMRI) can potentially predict the postoperative outcome of cervical spondylotic myelopathy (CSM). PURPOSE: To explore preoperative dMRI parameters to predict the postoperative outcome of CSM through multifactor correlation analysis. STUDY TYPE: Prospective. POPULATION: Post-surgery CSM patients; 102 total, 73 male (52.42 ± 10.60 years old) and 29 female (52.0 ± 11.45 years old). FIELD STRENGTH/SEQUENCE: 3.0 T/Turbo spin echo T1/T2-weighted, T2*-weighted multiecho gradient echo and dMRI. ASSESSMENT: Spinal cord function was evaluated using modified Japanese Orthopedic Association (mJOA) scoring at different time points: preoperative and 3, 6, and 12 months postoperative. Single-factor correlation and t test analyses were conducted based on fractional anisotropy (FA), mean diffusivity, intracellular volume fraction, isotropic volume fraction, orientation division index, increased signal intensity, compression ratio, age, sex, symptom duration and operation method, and multicollinearity was calculated. The linear quantile mixed model (LQMM) and the linear mixed-effects regression model (LMER) were used for multifactor correlation analysis using the combinations of the above variables. STATISTICAL TESTS: Distance correlation, Pearson's correlation, multiscale graph correlation and t tests were used for the single-factor correlation analyses. The variance inflation factor (VIF) was used to calculate multicollinearity. LQMM and LMER were used for multifactor correlation analyses. P < 0.05 was considered statistically significant. RESULTS: The single-factor correlation between all variables and the postoperative mJOA score was weak (all r < 0.3). The linear relationship was stronger than the nonlinear relationship, and there was no significant multicollinearity (VIF = 1.10-1.94). FA values in the LQMM and LMER models had a significant positive correlation with the mJOA score (r = 5.27-6.04), which was stronger than the other variables. DATA CONCLUSION: The FA value based on dMRI significantly positively correlated with CSM patient postoperative outcomes, helping to predict the surgical outcome and formulate a treatment plan before surgery. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 2.

Application research of AI-assisted compressed sensing technology in MRI scanning of the knee joint: 3D-MRI perspective.

OBJECTIVE: To investigate the potential applicability of AI-assisted compressed sensing (ACS) in knee MRI to enhance and optimize the scanning process. METHODS: Volunteers and patients with sports-related injuries underwent prospective MRI scans with a range of acceleration techniques. The volunteers were subjected to varied ACS acceleration levels to ascertain the most effective level. Patients underwent scans at the determined optimal 3D-ACS acceleration level, and 3D compressed sensing (CS) and 2D parallel acquisition technology (PAT) scans were performed. The resultant 3D-ACS images underwent 3.5 mm/2.0 mm multiplanar reconstruction (MPR). Experienced radiologists evaluated and compared the quality of images obtained by 3D-ACS-MRI and 3D-CS-MRI, 3.5 mm/2.0 mm MPR and 2D-PAT-MRI, diagnosed diseases, and compared the results with the arthroscopic findings. The diagnostic agreement was evaluated using Cohen's kappa correlation coefficient, and both absolute and relative evaluation methods were utilized for objective assessment. RESULTS: The study involved 15 volunteers and 53 patients. An acceleration factor of 10.69 × was identified as optimal. The quality evaluation showed that 3D-ACS provided poorer bone structure visualization, and improved cartilage visualization and less satisfactory axial images with 3.5 mm/2.0 mm MPR than 2D-PAT. In terms of objective evaluation, the relative evaluation yielded satisfactory results across different groups, while the absolute evaluation revealed significant variances in most features. Nevertheless, high levels of diagnostic agreement (κ: 0.81-0.94) and accuracy (0.83-0.98) were observed across all diagnoses. CONCLUSION: ACS technology presents significant potential as a replacement for traditional CS in 3D-MRI knee scans, allowing thinner MPRs and markedly faster scans without sacrificing diagnostic accuracy. CLINICAL RELEVANCE STATEMENT: 3D-ACS-MRI of the knee can be completed in the 160 s with good diagnostic consistency and image quality. 3D-MRI-MPR can replace 2D-MRI and reconstruct images with thinner slices, which helps to optimize the current MRI examination process and shorten scanning time. KEY POINTS: • AI-assisted compressed sensing technology can reduce knee MRI scan time by over 50%. • 3D AI-assisted compressed sensing MRI and related multiplanar reconstruction can replace traditional accelerated MRI and yield thinner 2D multiplanar reconstructions. • Successful application of 3D AI-assisted compressed sensing MRI can help optimize the current knee MRI process.

A Deep Learning Approach for MRI in the Diagnosis of Labral Injuries of the Hip Joint.

BACKGROUND: The diagnosis of labral injury on MRI is time-consuming and potential for incorrect diagnoses. PURPOSE: To explore the feasibility of applying deep learning to diagnose and classify labral injuries with MRI. STUDY TYPE: Retrospective. POPULATION: A total of 1016 patients were divided into normal (n = 168, class 0) and abnormal labrum (n = 848) groups. The abnormal group consisted of n = 111 with class 1 (degeneration), n = 437 with class 2 (partial or complete tear), and n = 300 with unclassified injury. Patients were randomly divided into training, validation, and test cohort according to the ratio of 55%:15%:30%. FIELD STRENGTH/SEQUENCE: Fat-saturation proton density-weighted fast spin-echo sequence at 3.0 T. ASSESSMENT: Convolutional neural network-6 (CNN-6) was used to extract, discriminate, and detect oblique coronal (OCOR) and oblique sagittal (OSAG) images. Mask R-CNN was used for segmentation. LeNet-5 was used to diagnose and classify labral injuries. The weighting method combined the models of OCOR and OSAG. The output-input connection was used to correlate the whole diagnosis/classification system. Four radiologists performed subjective diagnoses to obtain the diagnosis results. STATISTICAL TESTS: CNN-6 and LeNet-5 were evaluated by area under the receiver operating characteristic (ROC) curve and related parameters. The mean average precision (MAP) evaluated the Mask R-CNN. McNemar's test was used to compare the radiologists and models. A P value < 0.05 was considered statistically significant. RESULTS: The area under the curve (AUC) of CNN-6 was 0.99 for extraction, discrimination, and detection. MAP values of Mask R-CNN for OCOR and OSAG image segmentation were 0.96 and 0.99. The accuracies of LeNet-5 in the diagnosis and classification were 0.94/0.94 (OCOR) and 0.92/0.91 (OSAG), respectively. The accuracy of the weighted models in the diagnosis and classification were 0.94 and 0.97, respectively. The accuracies of radiologists in the diagnosis and classification of labrum injuries ranged from 0.85 to 0.92 and 0.78 to 0.94, respectively. DATA CONCLUSION: Deep learning can assist radiologists in diagnosing and classifying labrum injuries. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

An LC-ESI-MS/MS assay for the therapeutic drug monitoring of 15 antiseizure medications in plasma of children with epilepsy.

Oral antiseizure medications are the preferred option for the clinical treatment of epilepsy. Therapeutic drug monitoring has become an important means of achieving individualized treatment of epilepsy. A sensitive, accurate and rapid LC-ESI-MS/MS method was developed and validated for the simultaneous determination of 15 antiseizure medications in human plasma (carbamazepine, gabapentin, pregabalin, phenytoin, zonisamide, oxcarbazepine, tiagabine, lamotrigine, topiramate, phenobarbital, lacosamide, primidone, 10,11-Dihydro-10-hydroxy carbamazepine, ethosuximide, and levetiracetam). The sample preparation procedure was an one-step protein precipitation with methanol. Mass detection was performed in ionization polarity switching mode (positive-negative-positive) using multiple reaction monitoring mode. A "boot-shaped" gradient elution program was applied to separate and concentrate those target analytes, resulting in symmetrical peak shapes within 10 min, without endogenous interference. The method showed great linearity over the concentration ranges with acceptable correlation coefficients (0.9966-0.9996). The precision and accuracy values for intra- and inter-assays were within ±15%. Consequently, the method was successfully implemented on pediatric patients undergoing mono- or polytherapy for epilepsy and provided timely concentration results to ordering clinicians.

Radiomics Approaches for Predicting Liver Fibrosis With Nonenhanced T1 -Weighted Imaging: Comparison of Different Radiomics Models.

BACKGROUND: Liver fibrosis is a common process resulting from various etiologies. Sustained progression of liver fibrosis leads to cirrhosis, even hepatocellular carcinoma. Thus, noninvasive staging of liver fibrosis is of clinical importance. Radiomics is an emerging approach for staging liver fibrosis. However, the feature selection methods and classifier models are complicated, and may result in a discrepancy of diagnostic performance owing to different radiomics models. PURPOSE: To identify the optimal feature selection and classifier methods for predicting liver fibrosis by using nonenhanced T1 -weighted imaging. STUDY TYPE: Prospective. ANIMAL MODEL: Wistar rats, total 97. FIELD STRENGTH/SEQUENCE: 3T, 3D T1 -weighted images with fast-spoiled gradient echo (FSPGR). ASSESSMENT: Liver fibrosis rats were induced via subcutaneous injection of a mixture of carbon tetrachloride. Rats in the control group were injected with saline. Segmentation and feature extraction were performed by 3D slicer and the image biomarker explorer (IBEX) software package. Data preprocessing, feature selection, model building, and model comparative evaluation were conducted with Python. The liver fibrosis stage was determined by pathological examination. STATISTICAL TESTS: Receiver operating characteristic curve, fuzzy comprehensive evaluation. RESULTS: For discriminating between F0 and F1-2, F0 and F3-4, F0 and F1-4, F0-1 and F2-4, F0-2 and F3-4, and F0-3 and F4, the accuracies of 12 radiomics models were 77.27-90.91%, 73.33-86.67%, 80.56-91.67%, 74.07-88.89%, 76.47-88.24%, and 79.49-92.31%, respectively. The AUCs of the radiomics models were 0.86-0.97, 0.85-0.95, 0.89-0.97, 0.81-0.96, 0.82-0.93, and 0.85-0.96, respectively. The least absolute shrinkage and selection operator / support vector machine (LASSO-SVM) model had high AUCs of 0.93-0.97. For discriminating between F0 and F1-2, F0 and F3-4, F0 and F1-4, F0-1 and F2-4, and F0-2 and F3-4, the fuzzy comprehensive evaluation showed that the LASSO-SVM model had a high fuzzy score/order of 0.087-0.091/1. DATA CONCLUSION: LASSO-SVM appears to be the optimal model for predicting liver fibrosis by using nonenhanced T1 -weighted imaging in a rodent model of liver fibrosis. LEVEL OF EVIDENCE: 2. TECHNICAL EFFICACY STAGE: 2.

Increased expression of long noncoding RNA GAS6-AS2 promotes proliferation and inhibits apoptosis of melanoma cells via upregulating GAS6 expression.

Long noncoding RNAs (lncRNAs) are frequently aberrantly expressed and involved in many cancers, including melanoma. GAS6-AS2 was a recently identified cancer-related lncRNA. However, the expression, roles, and functional mechanisms of GAS6-AS2 in melanoma remain unknown. In this study, we found that lncRNA GAS6-AS2 is significantly elevated in melanoma tissues and cells. Elevated expression of GAS6-AS2 is positively correlated with advanced stages and poor prognosis in melanoma. Functional assays demonstrated that ectopic expression of GAS6-AS2 promotes proliferation and inhibits apoptosis of melanoma cells. In contrast, knockdown of GAS6-AS2 inhibits proliferation and promotes apoptosis of melanoma cells. Furthermore, in vivo functional assays showed that GAS6-AS2 promotes melanoma xenograft growth. Mechanistically, we found that GAS6-AS2 upregulates GAS6 expression, promotes GAS6 secretion, and activates AXL/AKT/ERK signals. The expression of GAS6 was positively correlated with that of GAS6-AS2 in melanoma tissues. In addition, deficiency of GAS6 reverses the biological roles of GAS6-AS2 overexpression in melanoma cell proliferation and apoptosis. Collectively, our data identified GAS6-AS2 as an oncogenic lncRNA in melanoma via activation of GAS6/AXL/AKT/ERK signals. Our data suggested that GAS6-AS2 may be a novel potential prognostic biomarker and therapeutic target for melanoma.

A matched case-control study of early cervical spondylotic myelopathy based on diffusion magnetic resonance imaging.

BACKGROUND: Early cervical spondylotic myelopathy (CSM) is challenging to diagnose and easily missed. Diffusion MRI (dMRI) has the potential to identify early CSM. METHODS: Using diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), and neurite orientation dispersion and density imaging (NODDI), a 1:1 matched case-control study was conducted to evaluate the potential of dMRI in identifying early CSM and assessing uncompressed segments of CSM patients. CSM patients and volunteers were matched by age and spinal location. The differences in dMRI parameters between groups were assessed by the paired t-test, the multicollinearity of the dMRI parameters was evaluated by the variance inflation factor (VIF), and the value of dMRI parameters in distinguishing controls from CSM patients was determined by logistic regression. The univariate t-test was used to analyse differences between CSM patients and volunteers in adjacent uncompressed areas. RESULTS: In total, 56 CSM patients and 56 control volunteers were included. Paired t-tests revealed significant differences in nine dMRI parameters between groups. Multicollinearity calculated through VIF and combined with logistic regression showed that the orientation division index (ODI) was significantly positively correlated (r = 2.12, p = 0.035), and the anisotropic water fraction (AWF) was significantly negatively correlated (r = -0.98, p = 0.015). The fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), isotropic volume fraction (ISOVF), ODI, and AWF were significantly different in the upper and lower uncompressed areas at all ages. CONCLUSION: dMRI can noninvasively identify early CSM patients and potentially identify the extent of CSM lesions involving the cervical spinal cord. CRITICAL RELEVANCE STATEMENT: Diffusion MRI (dMRI) can identify early cervical spondylotic myelopathy (CSM) and has the potential to help determine the extent of CSM involvement. The application of dMRI can help screen for early CSM and develop clinical surgical and rehabilitation treatment plans. KEY POINTS: • Diffusion MRI can differentiate between normal and early-stage cervical spondylotic myelopathy patients. • Diffusion MRI has the ability to identify the extent of spinal cord involvement in cervical spondylotic myelopathy. • Diffusion MRI enables the early screening of cervical spondylotic myelopathy and helps guide clinical treatment.

Deep learning-assisted classification of calcaneofibular ligament injuries in the ankle joint.

Background: The classification of calcaneofibular ligament (CFL) injuries on magnetic resonance imaging (MRI) is time-consuming and subject to substantial interreader variability. This study explores the feasibility of classifying CFL injuries using deep learning methods by comparing them with the classifications of musculoskeletal (MSK) radiologists and further examines image cropping screening and calibration methods. Methods: The imaging data of 1,074 patients who underwent ankle arthroscopy and MRI examinations in our hospital were retrospectively analyzed. According to the arthroscopic findings, patients were divided into normal (class 0, n=475); degeneration, strain, and partial tear (class 1, n=217); and complete tear (class 2, n=382) groups. All patients were divided into training, validation, and test sets at a ratio of 8:1:1. After preprocessing, the images were cropped using Mask region-based convolutional neural network (R-CNN), followed by the application of an attention algorithm for image screening and calibration and the implementation of LeNet-5 for CFL injury classification. The diagnostic effects of the axial, coronal, and combined models were compared, and the best method was selected for outgroup validation. The diagnostic results of the models in the intragroup and outgroup test sets were compared with those results of 4 MSK radiologists of different seniorities. Results: The mean average precision (mAP) of the Mask R-CNN using the attention algorithm for the left and right image cropping of axial and coronal sequences was 0.90-0.96. The accuracy of LeNet-5 for classifying classes 0-2 was 0.92, 0.93, and 0.92, respectively, for the axial sequences and 0.89, 0.92, and 0.90, respectively, for the coronal sequences. After sequence combination, the classification accuracy for classes 0-2 was 0.95, 0.97, and 0.96, respectively. The mean accuracies of the 4 MSK radiologists in classifying the intragroup test set as classes 0-2 were 0.94, 0.91, 0.86, and 0.85, all of which were significantly different from the model. The mean accuracies of the MSK radiologists in classifying the outgroup test set as classes 0-2 were 0.92, 0.91, 0.87, and 0.85, with the 2 senior MSK radiologists demonstrating similar diagnostic performance to the model and the junior MSK radiologists demonstrating worse accuracy. Conclusions: Deep learning can be used to classify CFL injuries at similar levels to those of MSK radiologists. Adding an attention algorithm after cropping is helpful for accurately cropping CFL images.

Part IV: Design, synthesis and antitumor activity of fluoroquinolone C-3 heterocycles: bis-oxadiazole methylsulfide derivatives derived from ciprofloxacin.

To explore an efficient strategy for further development of anticancer fluoroquinolone candidates derived from ciprofloxacin, a heterocyclic ring as the bioisosteric replacement of C3 carboxyl group led to a key intermediate, oxadiazole thiol (5), which was further modified to the bis-oxadiazole methylsulfides (7a-7h) and the corresponding dimethylpiperazinium iodides (8a-8h), respectively. Structures were characterized by elemental analysis and spectra data, and their anticancer activities in vitro against CHO, HL60 and L1210 cancer cells were also evaluated by MTT assay. The preliminary results show that piperazinium compounds (8) possess more potent activity than that of corresponding free bases (7).

[Part IV. Synthesis and antitumor evaluation of s-triazolothiadiazines and pyrazolo s-triazoles derived from ciproxacin].

An efficient modified route based on the targeting mechanism of antibacterial fluoroquinolones for the shift from the antibacterial activity to the antitumor one was further developed. Using a fused heterocyclic ring, s-triazolothiadiazine as a carboxyl bioisostere of ciprofloxacin, the title compounds, 1-cyclopropyl-6-fluoro-7-piperazin-1-yl-3-(6-substituted-phenyl-7H-[1, 2, 4]triazolo[3, 4-b][1, 3, 4]thiadiazin-3-yl)-quinolin-4(1H)-ones (5a-5e) and their corresponding N-acetyl products (6a-6e), were designed and synthesized, separately. Meaningfully, a ring-contraction of fused six-membered thiadiazine occurred by a sulfur extrusion reaction gave new tri-acetylated fused heterocycles related to pyrazolo[5, 1-c][1, 2, 4] triazoles (7a-7e). The in vitro antitumor activity against L1210, CHO and HL60 cell lines was also evaluated for the synthesized fifteen heterocycles compared to parent ciprofloxacin by methylthiazole trazolium (MTT) assay. Interestingly, the results displayed that fifteen fused heterocyclic compounds showed more significant growth inhibitory activity (IC50 < 25.0 micromo x L(-1)) than that of parent ciprofloxacin (IC50 > 150.0 micromol x L(-1)), and the active order decreased from 7a-7e to 5a-5e to 6a-6e, respective.

Application of O-RADS Ultrasound Lexicon-Based Logistic Regression Analysis Model in the Diagnosis of Solid Component-Containing Ovarian Malignancies.

Objective: To use the logistic regression model to evaluate the value of ultrasound characteristics in the Ovarian-Adnexal Reporting and Data System ultrasound lexicon in determining ovarian solid component-containing mass benignancy/malignancy. Methods: We retrospectively analyzed the data of 172 patients with adnexal masses discovered by ultrasound, and diagnosis was confirmed by postoperative pathological tests from January 2019 to December 2021. Thirteen ovarian tumor-related parameters in the benign and malignant ovarian tumor groups were selected for univariate analyses. Statistically significant parameters were included in multivariate logistic regression analyses to construct a logistic regression diagnosis model, and the diagnostic performance of the model in predicting ovarian malignancies was calculated. Results: Of the 172 adnexal tumors, 104 were benign, and 68 were malignant. There were differences in cancer antigen 125, maximum mass diameter, maximum solid component diameter, multilocular cyst with solid component, external contour, whether acoustic shadows were present in the solid component, number of papillae, vascularity, presence/absence of ascites, and presence/absence of peritoneal thickening or nodules between the benign ovarian tumor and malignancy groups (p < 0.05). Logistic regression analyses showed that maximum solid component diameter, whether acoustic shadows were present in the solid component, number of papillae, and presence/absence of ascites were included in the logistic regression model, and the area under the receiver operating characteristic curve for this regression model in predicting ovarian malignancy was 0.962 (95% confidence interval: 0.933~0.990; p < 0.001). Logit (p) ≥ -0.02 was used as the cutoff value, and the prediction accuracy, sensitivity, specificity, positive predictive value, and negative predictive values were 93.6%, 86.8%, 98.1%, 96.7%, and 91.9%, respectively. Conclusion: The logistic regression model containing the maximum solid component diameter, whether acoustic shadows were present in the solid component, number of papillae, and presence/absence of ascites can help in determining the benignancy/malignancy of solid component-containing masses.

Imaging Features and Pathological Analysis of 43 Parotid Basal Cell Adenomas.

PURPOSE: To investigate the correlation between sonographic and computed tomography and pathological features of basal cell adenomas (BCAs) of the parotid gland. METHODS: This retrospective study included 41 patients (43 tumors) with BCAs. The tumors were divided into three types based on their location in the parotid gland and their imaging features. The features of the tumors were analyzed. RESULTS: Imaging manifestations and corresponding pathological results of most BCAs of the parotid glands resembled those of benign parotid gland tumors. Malignant transformation occurred in membranous BCAs and in those with extensive cribriform structures. Type-II and type-III tumors accounted for 82.93% of the total proportion. Thirteen tumors showed cystic degeneration with 30.23%, among which type-III tumors could easily develop cystic degeneration. These cystic areas might correspond to cystic degeneration or focal necrosis. Cystic change was not dependent on the tumor size. The pathological features of the tumors were correlated to their imaging manifestations. CONCLUSION: Most BCAs of the parotid glands have imaging manifestations similar to those of benign parotid gland tumors. BCAs with extensive cribriform structures and of the membranous type can show malignant transformation and should be treated with caution in clinical practice.

Valproic acid therapy decreases serum 25-hydroxyvitamin D level in female infants and toddlers with epilepsy- a pilot longitudinal study.

To evaluate if valproic acid (VPA) therapy is associated with vitamin D deficiency among infants and toddlers with epilepsy, a cross-sectional clinical study was conducted in 25 children with epilepsy taking VPA. Blood levels of calcium, phosphorus, alkaline phosphatase, and 25-hydroxy vitamin D [25(OH)D] and plasma VPA level were measured at 1- to 3-month intervals. At the initial and final measurements, vitamin D deficiency or insufficiency was recognized in 8 (32%) and 12 (42%), respectively. In girls, a decreasing trend in serum 25(OH)D levels ( P<0.05) was observed. Polytherapy had a significant negative effect on the longitudinal change of 25(OH)D ( P<0.05) in girls. In conclusion, our study indicates that a high proportion of girls after VPA therapy had hypovitaminosis D.

Valproate decreases vitamin D levels in pediatric patients with epilepsy.

PURPOSE: To compare Vitamin D (Vit D) levels in children with epilepsy on valproate monotherapy with healthy controls. METHODS: A meta-analysis performed on articles identified from PubMed and Web of Science online databases evaluated using National Institute of Health National Heart, Lung, and Blood Institute Study Quality Assessment Tools. Subgroup analyses and publication bias assessments were also performed. RESULTS: Eleven publications were eligible based on inclusion/exclusion criteria for the meta-analysis. Results noted a decrease in the mean Vit D level in children with epilepsy on valproate monotherapy compared with healthy children with a Standard Mean Difference = -0.313 [-0.457, -0.169]. Cumulative meta-analysis showed progressive negative effect of valproate therapy on Vit D levels across time. Other antiepileptic medications caused a similar effect on Vit D status. There was no evidence of publication bias in the analyses. Type of study design and country of origin introduced heterogeneities into the meta-analyses. CONCLUSION: This meta-analysis provides evidence that long-term therapy with valproate causes a decrease in Vit D levels in children. Therefore, in children with a seizure disorder on long-term valproate therapy, 25-OH-Vit D levels should be monitored and appropriate supplementation implemented if levels are deficient.

Relationship between acne and psychological burden evaluated by ASLEC and HADS surveys in high school and college students from central China.

Previously, acne and its effects on psychological well-being have mostly been studied unilaterally in the western population. This study was aimed to investigate bidirectional relationship between acne and stress using Adolescent Self-Rating Life Events Check (ASLEC) and Hospital Anxiety and Depression Scale (HADS) surveys from inhabitants of central China. An on-line survey of 2,284 high school and college students from central China was conducted using three questionnaires posted on Chinese professional survey website, the Questionnaire Web. The prevalence and severity of acne were determined using the Pillsbury grading, whereas, the role of stress in acne formation was ascertained by the ASLEC scale. The HADS was employed to assess the psychological well-being. A total of 50.61 % of high school and college students in central China were found to be suffering from acne for more than 6 months, and 19.72 % of them were graded as having severe acne. Negative life events were found to accelerate the occurrence and exacerbation of the condition. Acne-affected groups showed significantly higher HADS-A (HADS-anxiety) and HADS-D (HADS-depression) scores than the controls (7.31 and 7.28 vs. 4.37 and 3.85, respectively; p < 0.01). Despite the apparent neglect of acne in Chinese high school and college students, a close bidirectional relationship was found to exist between stress and acne. It is incumbent on the healthcare professional to introduce school-based educational programs to help students with knowledge and management of acne and prevent the consequent psychological disorders.