BACKGROUND:In addition to intracranial plaques, extracranial carotid plaques have also been linked to stroke recurrence. However, the association of combined intracranial and extracranial plaque characteristics with stroke recurrence remains unclear. PURPOSE:To evaluate the association between intracranial plaque features and extracranial carotid Plaque Reporting and Data System (Plaque-RADS) with stroke recurrence utilizing high-resolution vessel wall imaging (HR-VWI). STUDY TYPE:Retrospective. POPULATION:The 388 intracranial atherosclerotic ischemic stroke patients (mean age, 57.3 ± 11.5 years, 274 males). FIELD STRENGTH/SEQUENCE:3T, three-dimensional T1 weighted 3D fast spin echo. ASSESSMENT:HR-VWI was performed in all patients within 7 days of the stroke onset. The imaging features assessed included intracranial plaque characteristics (degree of stenosis, plaque burden, enhancement ratio, remodeling index, and intraplaque hemorrhage [IPH]) and extracranial carotid Plaque-RADS. Patients enrolled between May 2022 and July 2024 were included in the study. All patients were followed for a minimum of 12 months. STATISTICAL TESTS:Mann-Whitney U test or χ 2 test, univariate and multivariate Cox regression analyses, time-dependent ROC and AUC curves, and Kaplan-Meier survival curves. p-values less than 0.05 were regarded as statistically significant. RESULTS:During a median follow-up period of 24 months, 55 patients experienced recurrent stroke. Intracranial plaque enhancement ratio (HR, 1.62; 95% CI, 1.11-2.38), IPH (HR, 2.55; 95% CI, 1.47-4.40), and extracranial carotid Plaque-RADS (HR, 2.23; 95% CI, 1.29-3.86) were significantly associated with stroke recurrence. Time-dependent ROC indicated that the maximum AUCs for enhancement ratio, IPH, and Plaque-RADS were 0.75, 0.69, and 0.68, respectively, while the Cox model including all three reached a maximum AUC of 0.79. DATA CONCLUSION:The combination of intracranial plaque characteristics and extracranial carotid Plaque-RADS can be used to assess ischemic stroke recurrence. EVIDENCE LEVEL:3. TECHNICAL EFFICACY:Stage 2.

BACKGROUND:Different stroke mechanisms present with distinct imaging characteristics and prognosis. Multiparametric MRI can characterize these variations and may contribute to stroke secondary prevention. PURPOSE:To investigate the stroke mechanism subtypes and prognosis in patients with symptomatic intracranial atherosclerosis using multiparametric MRI. STUDY TYPE:Retrospective. POPULATION:Two hundred and seventeen ischemic stroke patients (147 males; age 55.5 ± 11.7 years) with intracranial atherosclerosis. FIELD STRENGTH/SEQUENCE:3-T, dynamic susceptibility contrast perfusion-weighted imaging (DSC-PWI); High-resolution vessel wall imaging (HR-VWI): three-dimensional (3D) T1-weighted Sampling Perfection with Application optimized Contrast using different flip angle Evolution (SPACE) and contrast-enhanced T1-SPACE. ASSESSMENT:All patients underwent multiparametric MRI within 7 days of stroke symptom onset. The stroke mechanisms included branch occlusive disease (BOD), artery-to-artery embolism, hypoperfusion, and mixed mechanisms. The following imaging characteristics were assessed by three radiologists independently. HR-VWI plaque characteristics included plaque area, lipid area, lipid ratio, occlusive thrombus, degree of stenosis, plaque burden, enhancement ratio, remodeling index, and intraplaque hemorrhage (IPH). The mean transit time-Alberta Stroke Program Early Computed Tomography score (MTT-ASPECTS) based on DSC-PWI was used to evaluate perfusion impairment. During a median follow-up period of 15 months, the correlation between different stroke mechanisms and prognosis was analyzed. STATISTICAL TESTS:Chi-squared or Fisher's exact, Kruskal-Wallis H-tests, multivariate logistic regression, and Kaplan-Meier curves. All p-values were corrected by Bonferroni correction, and p-values < 0.05 were considered statistically significant. RESULTS:Mixed mechanism was the most common subtype (32.7%). Significant differences were observed in perfusion impairment, degree of stenosis, plaque burden, enhancement ratio, IPH, and remodeling among stroke mechanisms. Of these characteristics, MTT-ASPECTS (odds ratio [OR] 0.70, 95% CI 0.562-0.863) and IPH (OR 2.30, 95% CI 1.042-5.051) were significantly associated with non-BOD mechanisms. Hypoperfusion mechanism was associated with a higher risk of stroke recurrence during a median follow-up of 15 months (hazard ratio 3.97, 95% CI 1.43-11.03). DATA CONCLUSION:Multiparametric MRI may reveal differences in imaging characteristics among stroke mechanisms. Hypoperfusion may be associated with an increased risk of stroke recurrence. EVIDENCE LEVEL:3. Technical Efficacy: Stage 3.

OBJECTIVES:To explore the value of middle cerebral artery (MCA) plaque characteristics in predicting the outcomes of subacute ischemic stroke and the incremental value of the previous diet on predictive performance. METHODS:One hundred and thirty-seven subacute ischemic stroke patients attributed to MCA plaques were included and analyzed in this prospective study. The National Institute of Health Stroke Scale (NIHSS) score, Mediterranean Diet Adherence Screener (MEDAS) score, and other clinical data were assessed. The plaque area, degree of stenosis, plaque burden, enhancement ratio, remodeling type, and intraplaque hemorrhage were measured using high-resolution MR vessel wall imaging (HR-VWI). Multivariable logistic regression analysis and receiver operating characteristic curve analysis were performed to assess the predictive performance of clinical and plaque characteristics for subacute ischemic stroke outcomes at 3 months. RESULTS:Patients with poor outcomes exhibited high NIHSS scores, and low MEDAS scores (P<0.001). Plaque burden, enhancement ratio, and degree of stenosis were significantly higher in patients with poor outcomes (P<0.001). Multivariate analyses further indicated that NIHSS score (P=0.001), MEDAS score (P=0.013), and enhancement ratio (P=0.011) were independent predictors of subacute ischemic stroke outcomes. The three models' area under the curve (AUC) values were 0.811, 0.844, and 0.794. Combining these three factors resulted in an AUC of 0.908 (P<0.001). CONCLUSIONS:The combination of NIHSS score, MEDAS score, and enhancement ratio showed significant superiority in the prognostic evaluation of subacute ischemic stroke. Clinical data combined with plaque characteristics improves the accuracy of 3-month outcome prediction on subacute ischemic stroke.

PURPOSE:The study aimed to construct a predictive model for clinically significant prostate cancer (csPCa) and investigate its clinical efficacy to reduce unnecessary prostate biopsies.METHODS:A total of 847 patients from institute 1 were included in cohort 1 for model development. Cohort 2 included a total of 208 patients from institute 2 for external validation of the model. The data obtained were used for retrospective analysis. The results of magnetic resonance imaging were obtained using Prostate Imaging Reporting and Data System version 2.1 (PI-RADS v2.1). Univariate and multivariate analyses were performed to determine significant predictors of csPCa. The diagnostic performances were compared using the receiver operating characteristic (ROC) curve and decision curve analyses.RESULTS:Age, prostate-specific antigen density (PSAD), and PI-RADS v2.1 scores were used as predictors of the model. In the development cohort, the areas under the ROC curve (AUC) for csPCa about age, PSAD, PI-RADS v2.1 scores, and the model were 0.675, 0.823, 0.875, and 0.938, respectively. In the external validation cohort, the AUC values predicted by the four were 0.619, 0.811, 0.863, and 0.914, respectively. Decision curve analysis revealed that the clear net benefit of the model was higher than PI-RADS v2.1 scores and PSAD. The model significantly reduced unnecessary prostate biopsies within the risk threshold of > 10%.CONCLUSIONS:In both internal and external validation, the model constructed by combining age, PSAD, and PI-RADS v2.1 scores exhibited excellent clinical efficacy and can be utilized to reduce unnecessary prostate biopsies.

As stated by Wang et al, 1 bladder cancer is the fourth most common tumor in men and the eighth most lethal. This kind of tumor can be subdivided into invasive or noninvasive of the muscle tissue surrounding the bladder. The difference in treatments between each kind of tumor, especially the 5-year survival rate, is considerable (90% for noninvasive vs. 50% for invasive). Even if tissue biopsy remains the golden standard to classify these tumors, differences in tissue obtention techniques as well as the limited number of samples acquired per patient make it a solution open to improvement. Developing a classification tool for these tumors is of high clinical interest, especially if this tool is noninvasive, nonpainful, covers the whole area of study, and shows a specificity over 90%. Plenty of work in this field has been performed to combine MR imaging techniques that are non-painful, noninvasive, and able to cover all the different tissues involved in diagnostics. The use of these techniques alone has allowed researchers and clinicians to develop diagnostic algorithms with a success rate between 64.7% and 87%. On top of them, radiomic analyses are a set of up-and-coming methodologies, able to obtain image features that can later be used to perform differential diagnostics. In fact, in the past, radiomics has been applied in this field to distinguish the two subtypes of cancer and to grade the tumor stage with different rates of success, usually under 80%. In this issue of JMRI, Wang et al obtained radiomic features of MR images, to assess the stage of bladder tumors and their muscle infiltration. The difference with previous works resides in the fact that here authors use a larger database of MR images obtained with different sequences and contrasts, leading to also to a larger body of radiomic features/variables. Also, and on top of this, they develop a nomogram that could further complement the diagnosis and staging of these illnesses, as it combined not just the radiomic features described before, but extra clinic-radiological variables. One of the strengths of this paper is the amount of data and statistical strength of its implementation. The authors use data from 234 patients, of which 103 are used to validate models and 239 to build them. Almost 7900 radiomic features were extracted from each one of the three volumes of interest used in this analysis, 23 different clinic-radiological features for each volunteer. Also, the authors use appropriately strong mathematical and statistical methodology to reduce the number of variables in their models (i.e., LASSO, multivariate logistic regression, recursive feature elimination, etc.). After all this statistical analysis, only nine radiomic features were used for the radiomic model and five for the clinicradiological counterpart. Wang et al produce, at the end of this project, three models to predict tumor muscle infiltration. The radiomic model is based on nine features, which are presented in Table 2 of the manuscript. This is a strong point of this work as it will allow readers to see the coefficients and replicate the findings. This is not usual in other publications in the field. The sensitivity of this model was 87.50%, and the specificity was 82.28%. The area under the curve (AUC) for the training data was 0.933 and 0.916 for the testing data. The clinical model on its own was based on five parameters, which are presented in Table 3. Training model specificity AUC scores were 0.876 and 0.840 for the testing data. When the radiomic-clinical nomogram was built, receiver operating characteristic curve was 0.955 for the training data and 0.924 for the testing data. This shows that both the radiomic and the radiomic-clinical models outperformed the clinical model. Secondary conclusions also derived from this work are that high-density protein content was negatively correlated with myometrial invasion in these kinds of tumors. Tumor volume and tumor stalk structure were also two variables of special interest and weight in the models developed. The authors present the built nomogram in the last figure of this paper. Finally, the authors explain the limitations of this study. They include as future improvements the use of multicenter data,

To develop an MRI radiomic nomogram capable of identifying muscle invasive bladder cancer (MIBC) patients with high-risk molecular characteristics related to poor 2-year disease-free survival (DFS). We performed a retrospective analysis of DNA sequencing data, prognostic information, and radiomics features from 91 MIBC patients at stages T2-T4aN0M0 without history of immunotherapy. To identify risk stratification, we employed Cox regression based on TP53 mutation status and tumor mutational burden (TMB) level. Radiomics signatures were selected using the least absolute shrinkage and selection operator (LASSO) to construct a nomogram based on logistic regression for predicting the stratification in the training cohort. The predictive performance of the nomogram was assessed in the testing cohort using receiver operator curve (ROC), Hosmer–Lemeshow (HL) test, clinical impact curve (CIC), and decision curve analysis (DCA). Among 91 participants, the mean TMB value was 3.3 mut/Mb, with 60 participants having TP53 mutations. Patients with TP53 mutations and a below-average TMB value were identified as high risk and had a significantly poor 2-year DFS (hazard ratio = 4.36, 95

Background The rate of inguinal lymph node metastasis is relatively low in cervical cancer patients.According to the NCCN (National Comprehensive Cancer Network) guidelines for cervical cancer,patients with cervical cancer invading the lower 1/3 of the vagina require bilateral inguinal lymphatic area preventive irradiation. But do they need preventive inguinal area irradiation? Methods A total of 184 patients with cervical cancer accompanied by the lower 1/3 of the vagina invasion were selected as the study subjects.In this study, a trial and control method was used to select 180 patients without inguinal lymph node metastasis.The patients were divided into preventive radiotherapy group (109 cases) and non-preventive radiotherapy group (71 cases). During and after treatment, the occurrence of inguinal skin damage, lower extremity edema and femoral head necrosis was observed. Results Thirteen cases (7.07%) of 184 patients were found with inguinal lymph node enlargement by imaging examination, and only 4 cases (2.17%) were further confirmed by pathology.In prophylaxis irradiation group, there were 26(23.85%) cases of side injury.In the follow-up of two groups after treatment there was no recurrence in the inguinal lymph nodes. Conclusion The inguinal lymph node metastasis rate in patients with cervical cancer invading the lower third of the vagina is 2.17%.In order to avoid such a low incidence, we carry out preventive irradiation, which will cause 23.85% of local secondary injuries .And even if we do not perform preventive inguinal lymph node irradiation, there is no difference in the recurrence rate of inguinal lymph nodes between the two groups. Preventive inguinal lymph node irradiation isn’t necessary for these patients.

Composite materials can achieve synergistic effect through complementarity components, which are important for improving electrode performance. The co-modification of vertically oriented TiO2 nanosheets (TiO2-NSs) and conductive polyaniline (PANI) are studied. PANI with different content is deposited onto TiO2-NSs/CP during electrochemical cyclic voltammetry (CV) with 5, 10, 15, 20 and 25 cycles. Bio-electrochemical experiments indicate that TiO2-20PANI/CP electrode with deposited PANI via 20 cycles of CV had the lowest charge transfer resistance (R-ct) and the largest transient charge storage capacity (TCSC), which exhibit the best performance. The maximum output power density of PV-4 at TiO2-20PANI/CP anode (813 mW.m(-2)) is increased 63.6% more than that at TiO2-NSs/CP anode. The results give a guideline for designing high performance bio-electrode. Moreover, the method is simply and efficient, and could be extended to other nano-semiconductor modified electrodes for superior MFC anodes.

BACKGROUND:Dural arteriovenous fistulas (DAVFs) at the craniocervical junction are rare. Clinical manifestations range from acute or chronic myelopathy to subarachnoid hemorrhage to brainstem dysfunction. We encountered 4 cases of DAVFs at the craniocervical junction with progressive brainstem dysfunction and investigated the typical magnetic resonance imaging (MRI) features using T2-weighting imaging, susceptibility-weighted imaging, diffusion-weighted imaging, and contrast-enhanced imaging. Literature review revealed 10 case reports of DAVFs at the craniocervical junction manifesting with brainstem dysfunction.CASE DESCRIPTION:Four patients presented with DAVFs at the craniocervical junction with progressive brainstem dysfunction. Two patients underwent midline suboccipital craniotomy and C1 laminectomy, and 1 patient underwent transarterial endovascular embolization with Onyx 18 under general anesthesia. All neurologic deficits gradually improved after the operation. In the fourth case, the patient received conservative treatment and did not undergo any surgical procedure. MRI showed high signal intensity on T2-weighted imaging, magnetic resonance angiography, and magnetic resonance venography. Abnormal dilated vessels and flow-void signs around the lesions were detected on susceptibility-weighted imaging and contrast-enhanced images. Two cases revealed no abnormalities and had improved neurological deficits than those showed on diffusion-weighted imaging.CONCLUSIONS:Susceptibility-weighted imaging, diffusion-weighted imaging, or contrast-enhanced scanning should be used during MRI examination of patients with progressive brainstem dysfunction to differentiate DAVFs at the craniocervical junction from other diseases, such as glioma or infection. Prompt diagnosis using MRI is of great significance in producing good functional outcomes of the patients.

OBJECTIVES:Oxygen 6-methylguanine-DNA methyltransferase (MGMT) promoter methylation is a significant prognostic biomarker in astrocytomas, especially for temozolomide (TMZ) chemotherapy. This study aimed to preoperatively predict MGMT methylation status based on magnetic resonance imaging (MRI) radiomics and validate its value for evaluation of TMZ chemotherapy effect.METHODS:We retrospectively reviewed a cohort of 105 patients with grade II-IV astrocytomas. Radiomic features were extracted from the tumour and peritumoral oedema habitats on contrast-enhanced T1-weighted images, T2-weighted fluid-attenuated inversion recovery images and apparent diffusion coefficient (ADC) maps. The following radiomics analysis was structured in three phases: feature reduction, signature construction and discrimination statistics. A fusion radiomics signature was finally developed using logistic regression modelling. Predictive performance was compared between the radiomics signature, previously reported clinical factors and ADC parameters. Validation was additionally performed on a time-independent cohort (n = 31). The prognostic value of the signature on overall survival for TMZ chemotherapy was explored using Kaplan Meier estimation.RESULTS:The fusion radiomics signature exhibited supreme power for predicting MGMT promoter methylation, with area under the curve values of 0.925 in the training cohort and 0.902 in the validation cohort. Performance of the radiomics signature surpassed that of clinical factors and ADC parameters. Moreover, the radiomics approach successfully divided patients into high-risk and low-risk groups for overall survival after TMZ chemotherapy (p = 0.03).CONCLUSIONS:The proposed radiomics signature accurately predicted MGMT promoter methylation in patients with astrocytomas, and achieved survival stratification for TMZ chemotherapy, thus providing a preoperative basis for individualised treatment planning.KEY POINTS:• Radiomics using magnetic resonance imaging can preoperatively perform satisfactory prediction of MGMT methylation in grade II-IV astrocytomas. • Habitat-based radiomics can improve efficacy in predicting MGMT methylation status. • Multi-sequence radiomics signature has the power to evaluate TMZ chemotherapy effect.

Background: Previous studies have demonstrated interhemispheric functional connectivity alterations in schizophrenia. However, the relationship between these alterations and the disease state of schizophrenia is largely unknown. Therefore, we aimed to investigate this relationship using voxel-mirrored homotopic connectivity (VMHC) method. Methods: This study enrolled 36 schizophrenia patients with complete remission, 58 schizophrenia patients with incomplete remission and 55 healthy controls. The VMHC was calculated based on resting-state functional magnetic resonance imaging data. Differences in VMHC among three groups were compared using one-way analysis of variance. A brain region with a significant difference in VMHC was defined as a region of interest (ROI), and the mean VMHC value in the ROI was extracted for the post hoc analysis, i.e., pair-wise comparisons across the three groups. Results: VMHC in the visual region (inferior occipital and fusiform gyri) and the sensorimotor region (paracentral lobule) showed significant differences among the three groups (P < 0.05, a false discovery rate method corrected). Pair-wise comparisons in the post hoc analysis showed that VMHC of the visual and sensorimotor regions in schizophrenia patients with complete remission and incomplete remission was lower than that in healthy controls (P < 0.05, Bonferroni corrected); however, there was no significant difference between the two patient subgroups. Conclusions: Interhemispheric functional connectivity in the sensorimotor and visual processing pathways was reduced in patients with schizophrenia, but this reduction was unrelated to the disease state; thus, this reduction may serve as a trait marker of schizophrenia.