The monocyte-to-high-density lipoprotein-cholesterol ratio at diagnosis is associated with cerebrovascular accident during follow-up in patients with antineutrophil cytoplasmic antibody-associated vasculitis.

Objective: In this study, the association between the monocyte-to-high-density lipoprotein cholesterol ratio (MHR) at diagnosis and poor outcomes of atherosclerosis-related antineutrophil cytoplasmic antibody-associated vasculitis (AAV) during follow-up in patients with AAV was investigated. Methods: This retrospective study included 138 patients diagnosed with AAV. Their comprehensive medical records were meticulously reviewed. All-cause mortality, cerebrovascular accident (CVA), and acute coronary syndrome (ACS) were evaluated as atherosclerosis-related poor outcomes of AAV. MHR was obtained by dividing monocyte counts (/mm3) by high-density lipoprotein cholesterol (mg/dL) levels. Results: The median age of the 138 patients was 58.3 years with 44 being male (31.9%). Among the 138 patients, 11 (8.0%) died, and 11 (8.0%) and 9 (6.5%) had CVA, and ACS, respectively. MHR at diagnosis was significantly correlated with the Birmingham vasculitis activity score, erythrocyte sedimentation rate, and C-reactive protein at diagnosis. Among the three poor outcomes of AAV, only CVA during follow-up was significantly associated with MHR at diagnosis, and thus, only CVA was considered an atherosclerosis-related poor outcome of AAV. In the multivariable Cox hazards model analysis, MHR (hazard ratio [HR] 1.195) and serum albumin (HR 0.203) at diagnosis were independently associated with CVA during follow-up. Additionally, patients with MHR at diagnosis ≥3.0 exhibited a significantly higher risk for CVA and lower cumulative CVA-free survival rate than those with MHR at diagnosis <3.0. Conclusion: This study is the first to demonstrate clinical implications of MHR suggesting that MHR at diagnosis is significantly and independently associated with CVA during follow-up in patients with AAV.

Revisiting oligodendroglioma grading in the 2021 WHO classification: calcification and larger contrast-enhancing tumor volume may predict higher oligodendroglioma grade.

PURPOSE: To investigate whether qualitative and quantitative imaging phenotypes can predict the grade of oligodendroglioma. METHODS: Retrospective chart and imaging reviews were conducted on 180 adults with oligodendroglioma (IDH-mutant and 1p/19q codeleted) between 2005 and 2021. Qualitative imaging characteristics including tumor location, calcification, gliomatosis cerebri, cystic change, necrosis, and infiltrative pattern were analyzed. Quantitative imaging assessment was performed from the tumor mask via automatic segmentation to calculate total, contrast-enhancing (CE), non-enhancing (NE), and necrotic tumor volumes. Logistic analyses were conducted to determine predictors of oligodendroglioma grade. RESULTS: This study included 180 patients (84 [46.7%] with grade 2 and 96 [53.3%] with grade 3 oligodendrogliomas), with a median age of 42 years (range 23-76 years), comprising 91 females and 89 males. On univariable analysis, calcification (odds ratio [OR] = 6.00, P < 0.001), necrosis (OR = 21.84, P = 0.003), presence of CE tumor (OR = 7.86, P < 0.001), larger total (OR = 1.01, P < 0.001), larger CE (OR = 2.22, P = 0.010), and larger NE (OR = 1.01, P < 0.001) tumor volumes were predictors of grade 3 oligodendroglioma. On multivariable analysis, calcification (OR = 3.79, P < 0.001) and larger CE tumor volume (OR = 2.70, P = 0.043) remained as independent predictors of grade 3 oligodendroglioma. The multivariable model exhibited an AUC, accuracy, sensitivity, specificity of 0.78 (95% confidence interval 0.72-0.84), 72.8%, 79.2%, 69.1%, respectively. CONCLUSION: Presence of calcification and larger CE tumor volume may serve as useful imaging biomarkers for prediction of oligodendroglioma grade. CLINICAL RELEVANCE STATEMENT: Assessment of intratumoral calcification and CE tumor volume may facilitate accurate preoperative estimation of oligodendroglioma grade. Presence of intratumoral calcification and larger contrast-enhancing tumor volume were the significant predictors of higher grade oligodendroglioma based on the 2021 WHO classification.

Identification of prognostic imaging biomarkers in H3 K27-altered diffuse midline gliomas in adults: impact of tumor oxygenation imaging biomarkers on survival.

PURPOSE: To investigate prognostic markers for H3 K27-altered diffuse midline gliomas (DMGs) in adults with clinical, qualitative and quantitative imaging phenotypes, including tumor oxygenation characteristics. METHODS: Retrospective chart and imaging reviews were conducted on 32 adults with H3 K27-altered DMGs between 2017 and 2023. Clinical and qualitative imaging characteristics were analyzed. Quantitative imaging assessment was performed from the tumor mask via automatic segmentation to calculate normalized cerebral blood volume (nCBV), capillary transit time heterogeneity (CTH), oxygen extraction fraction (OEF), relative cerebral metabolic rate of oxygen (rCMRO2), and mean ADC values. Leptomeningeal metastases (LM) was diagnosed with imaging. Cox analyses were conducted to determine predictors of overall survival (OS) in entire patients and a subgroup of patients with contrast-enhancing (CE) tumor. RESULTS: The median patient age was 40.5 years (range 19.9-75.7), with an OS of 30.3 months (interquartile range 11.3-32.3). In entire patients, the presence of LM was the only independent predictor of OS (hazard ratio [HR] = 6.01, P = 0.009). In the subgroup of 23 (71.9%) patients with CE tumors, rCMRO2 of CE tumor (HR = 1.08, P = 0.019) and the presence of LM (HR = 5.92, P = 0.043) were independent predictors of OS. CONCLUSION: The presence of LM was independently associated with poor prognosis in adult patients with H3 K27-altered DMG. In patients with CE tumors, higher rCMRO2 of CE tumor, which may reflect higher metabolic activity in the tumor oxygenation microenvironment, may be a useful imaging biomarker to predict poor prognosis.

Identification of schizophrenia by applying interpretable radiomics modeling with structural magnetic resonance imaging of the cerebellum.

AIMS: The cerebellum is involved in higher-order mental processing as well as sensorimotor functions. Although structural abnormalities in the cerebellum have been demonstrated in schizophrenia, neuroimaging techniques are not yet applicable to identify them given the lack of biomarkers. We aimed to develop a robust diagnostic model for schizophrenia using radiomic features from T1-weighted magnetic resonance imaging (T1-MRI) of the cerebellum. METHODS: A total of 336 participants (174 schizophrenia; 162 healthy controls [HCs]) were allocated to training (122 schizophrenia; 115 HCs) and test (52 schizophrenia; 47 HCs) cohorts. We obtained 2568 radiomic features from T1-MRI of the cerebellar subregions. After feature selection, a light gradient boosting machine classifier was trained. The discrimination and calibration of the model were evaluated. SHapley Additive exPlanations (SHAP) was applied to determine model interpretability. RESULTS: We identified 17 radiomic features to differentiate participants with schizophrenia from HCs. In the test cohort, the radiomics model had an area under the curve, accuracy, sensitivity, and specificity of 0.89 (95% confidence interval: 0.82-0.95), 78.8%, 88.5%, and 75.4%, respectively. The model explanation by SHAP suggested that the second-order size zone non-uniformity feature from the right lobule IX and first-order energy feature from the right lobules V and VI were highly associated with the risk of schizophrenia. CONCLUSION: The radiomics model focused on the cerebellum demonstrates robustness in diagnosing schizophrenia. Our results suggest that microcircuit disruption in the posterior cerebellum is a disease-defining feature of schizophrenia, and radiomics modeling has potential for supporting biomarker-based decision-making in clinical practice.

Differentiation of glioblastoma from solitary brain metastasis using deep ensembles: Empirical estimation of uncertainty for clinical reliability.

BACKGROUND AND OBJECTIVES: To develop a clinically reliable deep learning model to differentiate glioblastoma (GBM) from solitary brain metastasis (SBM) by providing predictive uncertainty estimates and interpretability. METHODS: A total of 469 patients (300 GBM, 169 SBM) were enrolled in the institutional training set. Deep ensembles based on DenseNet121 were trained on multiparametric MRI. The model performance was validated in the external test set consisting of 143 patients (101 GBM, 42 SBM). Entropy values for each input were evaluated for uncertainty measurement; based on entropy values, the datasets were split to high- and low-uncertainty groups. In addition, entropy values of out-of-distribution (OOD) data from unknown class (257 patients with meningioma) were compared to assess uncertainty estimates of the model. The model interpretability was further evaluated by localization accuracy of the model. RESULTS: On external test set, the area under the curve (AUC), accuracy, sensitivity and specificity of the deep ensembles were 0.83 (95 % confidence interval [CI] 0.76-0.90), 76.2 %, 54.8 % and 85.2 %, respectively. The performance was higher in the low-uncertainty group than in the high-uncertainty group, with AUCs of 0.91 (95 % CI 0.83-0.98) and 0.58 (95 % CI 0.44-0.71), indicating that assessment of uncertainty with entropy values ascertained reliable prediction in the low-uncertainty group. Further, deep ensembles classified a high proportion (90.7 %) of predictions on OOD data to be uncertain, showing robustness in dataset shift. Interpretability evaluated by localization accuracy provided further reliability in the "low-uncertainty and high-localization accuracy" subgroup, with an AUC of 0.98 (95 % CI 0.95-1.00). CONCLUSIONS: Empirical assessment of uncertainty and interpretability in deep ensembles provides evidence for the robustness of prediction, offering a clinically reliable model in differentiating GBM from SBM.

Leptomeningeal Metastases in IDH-wildtype Glioblastomas Revisited: Comprehensive Analysis of Incidence, Risk Factors, and Prognosis Based on Post-contrast FLAIR.

BACKGROUND: The incidence of leptomeningeal metastases (LM) has been reported diversely. This study aimed to investigate the incidence, risk factors, and prognosis of LM in patients with IDH-wildtype glioblastoma. METHODS: A total of 828 patients with IDH-wildtype glioblastoma were enrolled between 2005 and 2022. Baseline preoperative MRI including post-contrast fluid-attenuated inversion recovery (FLAIR) was used for LM diagnosis. Qualitative and quantitative features, including distance between tumor and subventricular zone (SVZ) and tumor volume by automatic segmentation of the lateral ventricles and tumor, were assessed. Logistic analysis of LM development was performed using clinical, molecular, and imaging data. Survival analysis was performed. RESULTS: The incidence of LM was 11.4%. MGMTp unmethylation (odds ratio [OR] = 1.92, P = 0.014), shorter distance between tumor and SVZ (OR = 0.94, P = 0.010), and larger contrast-enhancing tumor volume (OR = 1.02, P < 0.001) were significantly associated with LM. The overall survival (OS) was significantly shorter in patients with LM than in those without (log-rank test; P < 0.001), with median OS of 12.2 and 18.5 months, respectively. Presence of LM remained an independent prognostic factor for OS in IDH-wildtype glioblastoma (hazard ratio = 1.42, P = 0.011), along with other clinical, molecular, imaging, and surgical prognostic factors. CONCLUSION: The incidence of LM is high in patients with IDH-wildtype glioblastoma, and aggressive molecular and imaging factors are correlated with LM development. The prognostic significance of LM based on post-contrast FLAIR imaging suggests acknowledgement of post-contrast FLAIR as a reliable diagnostic tool for clinicians.

Incorporating Supramaximal Resection into Survival Stratification of IDH-Wildtype Glioblastoma: A Refined Multi-institutional Recursive Partitioning Analysis.

PURPOSE: To propose a novel recursive partitioning analysis (RPA) classification model in patients with IDH-wildtype glioblastomas that incorporates the recently expanded conception of the extent of resection (EOR) in terms of both supramaximal and total resections. EXPERIMENTAL DESIGN: This multicenter cohort study included a developmental cohort of 622 patients with IDH-wildtype glioblastomas from a single institution (Severance Hospital) and validation cohorts of 536 patients from three institutions (Seoul National University Hospital, Asan Medical Center, and Heidelberg University Hospital). All patients completed standard treatment including concurrent chemoradiotherapy and underwent testing to determine their IDH mutation and MGMTp methylation status. EORs were categorized into either supramaximal, total, or non-total resections. A novel RPA model was then developed and compared to a previous RTOG RPA model. RESULTS: In the developmental cohort, the RPA model included age, MGMTp methylation status, KPS, and EOR. Younger patients with MGMTp methylation and supramaximal resections showed a more favorable prognosis (class I: median overall survival [OS] 57.3 months), while low-performing patients with non-total resections and without MGMTp methylation showed the worst prognosis (class IV: median OS 14.3 months). The prognostic significance of the RPA was subsequently confirmed in the validation cohorts, which revealed a greater separation between prognostic classes for all cohorts compared to the previous RTOG RPA model. CONCLUSIONS: The proposed RPA model highlights the impact of supramaximal versus total resections and incorporates clinical and molecular factors into survival stratification. The RPA model may improve the accuracy of assessing prognostic groups.

Association between Mycobacterium tuberculosis infection and the risk of inflammatory arthritides.

OBJECTIVES: Tuberculosis is a highly contagious disease that has a significant impact on global health. Emerging evidence suggests that tuberculosis can lead to an altered immune response. We investigated the association between tuberculosis and the onset of inflammatory arthritides (IA). METHODS: Patients with incident tuberculosis in the South Korean National Claims database from 2010 to 2021 were included, and those who had undergone appendectomy during 2010-2011 served as controls. The onset of IA (including seropositive rheumatoid arthritis [SPRA], ankylosing spondylitis [AS], and psoriatic arthritis [PsA]) after tuberculosis was compared between patients with tuberculosis and the control group. Sensitivity analysis was performed using stabilised inverse probability of treatment weighting (sIPTW). RESULTS: A total of 408,685 patients with tuberculosis and 159,675 controls were included. During the mean follow-up of 7.5 years, a total of 1,957 (0.3%) were diagnosed with IA (SPRA, 1,397; AS, 481; and PsA, 79). Multivariable Cox hazard analysis indicated that the overall risk of IA was elevated in the tuberculosis group (hazard ratio [HR], 1.71; 95% confidence interval [CI], 1.51-1.93) compared with controls. This increased incidence in patients with tuberculosis was identical among IA subgroups even after adjustment (SPRA [HR, 1.72; 95% CI, 1.49-2.00], AS [HR, 1.64; 95% CI, 1.30-2.06], and PsA [HR, 2.59; 95% CI, 1.32-5.07]) and was replicated in the sIPTW. CONCLUSIONS: The increased overall risk of developing IA after tuberculosis corroborates the hypothesis that tuberculosis can trigger dysregulated immunity. This necessitates an increased awareness of autoimmunity in this patient group.

Revisiting prognostic factors of gliomatosis cerebri in adult-type diffuse gliomas.

PURPOSE: There is lack of comprehensive analysis evaluating the impact of clinical, molecular, imaging, and surgical data on survival of patients with gliomatosis cerebri (GC). This study aimed to investigate prognostic factors of GC in adult-type diffuse glioma patients. METHODS: Retrospective chart and imaging review was performed in 99 GC patients from adult-type diffuse glioma (among 1,211 patients; 6 oligodendroglioma, 16 IDH-mutant astrocytoma, and 77 IDH-wildtype glioblastoma) from a single institution between 2005 and 2021. Predictors of overall survival (OS) of entire patients and IDH-wildtype glioblastoma patients were determined. RESULTS: The median OS was 16.7 months (95% confidence interval [CI] 14.2-22.2) in entire patients and 14.3 months (95% CI 12.2-61.9) in IDH-wildtype glioblastoma patients. In entire patients, KPS (hazard ratio [HR] = 0.98, P = 0.004), no 1p/19q codeletion (HR = 10.75, P = 0.019), MGMTp methylation (HR = 0.54, P = 0.028), and hemorrhage (HR = 3.45, P = 0.001) were independent prognostic factors on multivariable analysis. In IDH-wildtype glioblastoma patients, KPS (HR = 2.24, P = 0.075) was the only independent prognostic factor on multivariable analysis. In subgroup of IDH-wildtype glioblastoma with CE tumors, total resection of CE tumor did not remain as a significant prognostic factor (HR = 1.13, P = 0.685). CONCLUSIONS: The prognosis of GC patients is determined by its underlying molecular type and patient performance status. Compared with diffuse glioma without GC, aggressive surgery of CE tumor in GC patients does not improve survival.

Sex-specific Differences in IDH1-Wildtype Glioblastoma patients in the ReSPOND Consortium.

BACKGROUND: Understanding sex-based differences in glioblastoma patients is necessary for accurate personalized treatment planning to improve patient outcomes. PURPOSE: To investigate sex-specific differences in molecular, clinical and radiological tumor parameters, as well as survival outcomes in glioblastoma, isocitrate dehydrogenase-1 wildtype (IDH1-WT), grade 4 patients. METHODS: Retrospective data of 1832 glioblastoma, IDH1-WT patients with comprehensive information on tumor parameters was acquired from the Radiomics Signatures for Precision Oncology in Glioblastoma (ReSPOND) consortium. Data imputation was performed for missing values. Sex-based differences in tumor parameters, such as, age, molecular parameters, pre-operative KPS score, tumor volumes, epicenter and laterality were assessed through non-parametric tests. Spatial atlases were generated using pre-operative MRI maps to visualize tumor characteristics. Survival time analysis was performed through log-rank tests and Cox proportional hazard analyses. RESULTS: GBM was diagnosed at a median age of 64 years in females compared to 61.9 years in males (FDR = 0.003). Males had a higher Karnofsky Performance Score (above 80) as compared to females (60.4% females Vs 69.7% males, FDR = 0.044). Females had lower tumor volumes in enhancing (16.7 cm3 Vs. 20.6 cm3 in males, FDR = 0.001), necrotic core (6.18 cm3 Vs. 7.76 cm3 in males, FDR = 0.001) and edema regions (46.9 cm3 Vs. 59.2 cm3 in males, FDR = 0.0001). Right temporal region was the most common tumor epicenter in the overall population. Right as well as left temporal lobes were more frequently involved in males. There were no significant differences in survival outcomes and mortality ratios. Higher age, unmethylated O6-methylguanine-DNAmethyltransferase (MGMT) promoter and undergoing subtotal resection increased the mortality risk in both males and females. CONCLUSIONS: Our study demonstrates significant sex-based differences in clinical and radiological tumor parameters of glioblastoma, IDH1-WT, grade 4 patients. Sex is not an independent prognostic factor for survival outcomes and the tumor parameters influencing patient outcomes are identical for males and females. ABBREVIATIONS: IDH1-WT = isocitrate dehydrogenase-1 wildtype; MGMTp = O6-methylguanine-DNA-methyltransferase promoter; KPS = Karnofsky performance score; EOR = extent of resection; WHO = world health organization; FDR = false discovery rate.

Diffusion- and Perfusion-Weighted MRI Radiomics for Survival Prediction in Patients with Lower-Grade Gliomas.

PURPOSE: Lower-grade gliomas of histologic grades 2 and 3 follow heterogenous clinical outcomes, which necessitates risk stratification. This study aimed to evaluate whether diffusion-weighted and perfusion-weighted MRI radiomics allow overall survival (OS) prediction in patients with lower-grade gliomas and investigate its prognostic value. MATERIALS AND METHODS: In this retrospective study, radiomic features were extracted from apparent diffusion coefficient, relative cerebral blood volume map, and Ktrans map in patients with pathologically confirmed lower-grade gliomas (January 2012-February 2019). The radiomics risk score (RRS) calculated from selected features constituted a radiomics model. Multivariable Cox regression analysis, including clinical features and RRS, was performed. The models' integrated area under the receiver operating characteristic curves (iAUCs) were compared. The radiomics model combined with clinical features was presented as a nomogram. RESULTS: The study included 129 patients (median age, 44 years; interquartile range, 37-57 years; 63 female): 90 patients for training set and 39 patients for test set. The RRS was an independent risk factor for OS with a hazard ratio of 6.01. The combined clinical and radiomics model achieved superior performance for OS prediction compared to the clinical model in both training (iAUC, 0.82 vs. 0.72, p=0.002) and test sets (0.88 vs. 0.76, p=0.04). The radiomics nomogram combined with clinical features exhibited good agreement between the actual and predicted OS with C-index of 0.83 and 0.87 in the training and test sets, respectively. CONCLUSION: Adding diffusion- and perfusion-weighted MRI radiomics to clinical features improved survival prediction in lower-grade glioma.

Chemokine expression in sera of patients with microscopic polyangiitis and granulomatosis with polyangiitis.

We evaluated chemokine expression and its correlation with disease activity in patients with microscopic polyangiitis (MPA) and granulomatosis with polyangiitis (GPA) (MPA/GPA). Serum CCL2, CCL4, CCL19, CXCL1, CXCL2, and CX3CL1 level in 80 patients were analysed using multiple enzyme-linked immunosorbent assays. Correlations between variables were investigated using Pearson's correlation analysis, and receiver operator curve analysis was performed to identify optimal CX3CL1 values in determining active disease. Multivariate logistic regression analysis was done to evaluate predictors of active disease. CCL4 (r = 0.251, p = 0.025), CXCL1 (r = 0.270, p = 0.015), and CX3CL1 (r = 0.295, p = 0.008) significantly correlated with BVAS, while CX3CL1 was associated with five-factor score (r = - 0.290, p = 0.009). Correlations were revealed between CCL2 and CCL4 (r = 0.267, p = 0.017), CCL4 and CXCL1 (r = 0.368, p < 0.001), CCL4 and CXCL2 (r = 0.436, p < 0.001), and CXCL1 and CXCL2 (r = 0.518, p < 0.001). Multivariate analysis revealed serum CX3CL1 levels > 2408.92 pg/mL could predict active disease (odds ratio, 27.401, p < 0.001). Serum chemokine levels of CCL4, CXCL1, and CX3CL1 showed association with disease activity and especially, CX3CL1 > 2408.92 pg/mL showed potential in predicting active MPA/GPA.

Deep learning-based metastasis detection in patients with lung cancer to enhance reproducibility and reduce workload in brain metastasis screening with MRI: a multi-center study.

OBJECTIVES: To assess whether a deep learning-based system (DLS) with black-blood imaging for brain metastasis (BM) improves the diagnostic workflow in a multi-center setting. MATERIALS AND METHODS: In this retrospective study, a DLS was developed in 101 patients and validated on 264 consecutive patients (with lung cancer) having newly developed BM from two tertiary university hospitals, which performed black-blood imaging between January 2020 and April 2021. Four neuroradiologists independently evaluated BM either with segmented masks and BM counts provided (with DLS) or not provided (without DLS) on a clinical trial imaging management system (CTIMS). To assess reading reproducibility, BM count agreement between the readers and the reference standard were calculated using limits of agreement (LoA). Readers' workload was assessed with reading time, which was automatically measured on CTIMS, and were compared between with and without DLS using linear mixed models considering the imaging center. RESULTS: In the validation cohort, the detection sensitivity and positive predictive value of the DLS were 90.2% (95% confidence interval [CI]: 88.1-92.2) and 88.2% (95% CI: 85.7-90.4), respectively. The difference between the readers and the reference counts was larger without DLS (LoA: -0.281, 95% CI: -2.888, 2.325) than with DLS (LoA: -0.163, 95% CI: -2.692, 2.367). The reading time was reduced from mean 66.9 s (interquartile range: 43.2-90.6) to 57.3 s (interquartile range: 33.6-81.0) (P <.001) in the with DLS group, regardless of the imaging center. CONCLUSION: Deep learning-based BM detection and counting with black-blood imaging improved reproducibility and reduced reading time, on multi-center validation.

Incidence of systemic vasculitides after Mycobacterium tuberculosis infection: A population-based cohort study in Korea.

BACKGROUND: Tuberculosis (TB) is a highly prevalent disease associated with significant morbidity and mortality globally, and is reported to be associated with the onset of autoimmunity. This study investigated the association between TB and the incidence of systemic vasculitides (SV). METHODS: Data were obtained from the South Korean National Claims database to identify patients with TB and controls (who had undergone appendectomy). The overall occurrence of SV and disease subtypes during the observation period was compared between the two groups. Adjusted Cox proportional hazards regression and Kaplan-Meier analysis were performed to identify the relationship between TB and SV and to compare SV incidence. RESULTS: We identified 418 677 patients with TB and 160 289 controls. The overall SV incidence rate was 192/1,000 000 person-years during a mean follow-up of 7.5 years and was higher in patients with TB than controls. Cox regression revealed that the risk of SV was elevated in the TB group independently (adjusted hazard ratio [aHR]: 1.72, 95% confidence interval [CI]: 1.45-2.05). Furthermore, the risk of SV was significantly higher in extrapulmonary TB (aHR: 4.28, 95% CI: 3.52-5.21) when the TB group was categorized into pulmonary and extrapulmonary TB. The findings remained identical even after applying a stabilized inverse probability of treatment weighting analysis. CONCLUSIONS: Patients with TB have increased risk of SV, which is prominent in extrapulmonary TB. As well as confirming TB is associated with increased incidence of immune-related vasculitis, our findings highlight the need for clinical vigilance for early diagnosis and initiation of treatment.

Clinical, qualitative imaging biomarkers, and tumor oxygenation imaging biomarkers for differentiation of midline-located IDH wild-type glioblastomas and H3 K27-altered diffuse midline gliomas in adults.

PURPOSE: To compare the clinical, qualitative and quantitative imaging phenotypes, including tumor oxygenation characteristics of midline-located IDH-wildtype glioblastomas (GBMs) and H3 K27-altered diffuse midline gliomas (DMGs) in adults. METHODS: Preoperative MRI data of 55 adult patients with midline-located IDH-wildtype GBM or H3 K27-altered DMG (32 IDH-wildtype GBM and 23 H3 K27-altered DMG patients) were included. Qualitative imaging assessment was performed. Quantitative imaging assessment including the tumor volume, normalized cerebral blood volume, capillary transit time heterogeneity (CTH), oxygen extraction fraction (OEF), relative cerebral metabolic rate of oxygen values, and mean ADC value were performed from the tumor mask via automatic segmentation. Univariable and multivariable logistic analyses were performed. RESULTS: On multivariable analysis, age (odds ratio [OR] = 0.92, P = 0.015), thalamus or medulla location (OR = 10.48, P = 0.013), presence of necrosis (OR = 0.15, P = 0.038), and OEF (OR = 0.01, P = 0.042) were independent predictors to differentiate H3 K27-altered DMG from midline-located IDH-wildtype GBM. The area under the curve, accuracy, sensitivity, and specificity of the multivariable model were 0.88 (95 % confidence interval: 0.77-0.95), 81.8 %, 82.6 %, and 81.3 %, respectively. CONCLUSIONS: Along with younger age, tumor location, less frequent necrosis, and lower OEF may be useful imaging biomarkers to differentiate H3 K27-altered DMG from midline-located IDH-wildtype GBM. Tumor oxygenation imaging biomarkers may reflect the less hypoxic nature of H3 K27-altered DMG than IDH-wildtype GBM and may contribute to differentiation.

Earliest total vascular damage index scores independently predict all-cause mortality in patients with ANCA-associated vasculitis.

OBJECTIVES: This study investigated whether the earliest total Vasculitis Damage Index (VDI) score could significantly predict all-cause mortality during follow-up in patients with antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV). METHODS: This study included AAV patients who were first diagnosed at this hospital from 2001 to 2022. The earliest total VDI score was defined as the first VID assessed more than 3 months after AAV diagnosis in 93.5% of patients or after the first AAV presentation in 6.5% of patients. The optimal cut-off of the earliest total VDI score for all-cause mortality was obtained using the receiver operating characteristic curve. RESULTS: The median age and earliest VDI score were 60.0 years (35.5% men), and 3.0. The most common damaged system in the earliest VDI was the pulmonary (55.3%) system. Among the AAV patients, 39 (13.3%) died. When the optimal cut-off of the earliest total VDI score for all-cause mortality was set at 3.0 (sensitivity 64.1%, specificity 75.2%), AAV patients with the earliest total VDI score ≥3.0 exhibited a significantly higher risk for all-cause mortality than those without (relative risk 6.090). AAV patients with the earliest total VDI score ≥3.0 exhibited a significantly lower cumulative patients' survival rate than those without. In the multivariable Cox hazards model analyses, not only the earliest total VDI score but also the earliest total VDI score ≥3.0 were independently associated with all-cause mortality. CONCLUSIONS: This study was the first to demonstrate that the earliest total VDI score could predict all-cause mortality during follow-up in AAV patients.

Overlap syndrome of systemic sclerosis with antineutrophil cytoplasmic antibody-associated vasculitis according to 2022 ACR/EULAR criteria.

BACKGROUND/AIMS: This study applied the 2022 American College of Rheumatology (ACR)/European Alliance of Associations for Rheumatology (EULAR) criteria for antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) to patients with systemic sclerosis (SSc) and investigated the frequency of overlap syndrome of SSc and AAV (SSc-AAV-OS). METHODS: Among the 232 patients diagnosed with SSc, 105 with signs suggestive of small- or medium-vessel vasculitis, which were defined as the present of interstitial lung disease (ILD), peripheral neuropathy, or suspected renal vasculitis, were included in this study and analyzed. RESULTS: Among the 105 SSc patients, the detection rate of ANCA was 19.0%. When the 2022 ACR/EULAR criteria were applied, the frequency of SSc-AAV-OS was 20.0%, which was much higher than 1.7% reported with previous criteria for AAV. ANCA positivity contributed to the reclassification of SSc-AAV-OS more than ANCA negativity in SSc patients with signs suggestive of small- or medium-vessel vasculitis. CONCLUSION: The frequency of SSc-AAV-OS in SSc patients with signs suggestive of small- or medium-vessel vasculitis at diagnosis was 20.0%. Therefore, we suggest that physicians should perform ANCA tests in SSc patients exhibiting signs suggestive of small- or medium-vessel vasculitis and apply the new criteria for AAV.

Circulating cold-inducible RNA-binding protein levels in microscopic polyangiitis and granulomatosis with polyangiitis : Correlation with disease activity.

OBJECTIVE: This study investigated whether circulating cold-inducible RNA-binding protein (CIRP) could be a biomarker to reflect the current activity, function, and damage status in patients with microscopic polyangiitis (MPA) and granulomatosis with polyangiitis (GPA). METHODS: This study selected 39 MPA and 26 GPA patients. Antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV)-specific indices include the Birmingham Vasculitis Activity Index (BVAS), five-factor score (FFS), the Korean version of the Short-Form 36-Item Health Survey (SF-36) physical component summary (PCS) and mental component summary (MCS), and the vasculitis damage index (VDI). The highest tertile of BVAS was defined as high activity of AAV. RESULTS: The median age of the study subjects was 65.0 years and 53.8% were women. The median BVAS, FFS, SF-36 PCS, MCS, and VDI scores were 12.0, 2.0, 47.5, 50.3, and 3.0, respectively. The median circulating CIRP level was 6.4 ng/mL. Among the four AAV-specific indices, circulating CIRP was significantly correlated with BVAS (r = 0.256). Using the receiver operator characteristic curve, the cut-off of circulating CIRP for high activity of AAV was 6.16 ng/mL. High activity of AAV was identified more frequently in patients with circulating CIRP ≥ 6.16 ng/mL than in those with circulating CIRP < 6.16 ng/mL (48.6% vs. 21.4%). In addition, patients with circulating CIRP ≥ 6.16 ng/mL exhibited a significantly higher risk for high activity of AAV than those with circulating CIRP < 6.16 ng/mL (relative risk 3.474). CONCLUSION: This study suggests the clinical potential of circulating CIRP as a biomarker for reflecting the current BVAS and predicting high activity of AAV in patients with MPA and GPA.

Antineutrophil cytoplasmic antibody-associated vasculitis classification by cluster analysis based on clinical phenotypes: a single-center retrospective cohort study.

OBJECTIVE: Antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) refers to a group of small vessel inflammatory disorders. Overlapping clinical phenotypes of AAV subgroups continually provoke controversies over their diagnostic and classification criteria. METHODS: Using the agglomerative hierarchical clustering method, we classified 210 Korean patients diagnosed with AAV into mutually exclusive clusters according to Birmingham Vasculitis Activity Score items, ANCA specificity, sex, and age. We analyzed the resulting clusters' outcomes to investigate the clinical significance of the classification. We proposed a distance-based algorithm of patient assignment and explored its clinically relevant modification. RESULTS: In total, 116 patients (55%) had microscopic polyangiitis, 53 (25%) had granulomatosis with polyangiitis, and 42 (20%) had eosinophilic granulomatosis with polyangiitis. Our model grouped the patients into five clusters, namely, "limited proteinase 3 (PR3)-ANCA vasculitis," "generalized PR3-ANCA vasculitis," "ANCA-negative vasculitis," "renal-limited vasculitis," and "myeloperoxidase-ANCA vasculitis." Patients clustered under "generalized PR3-ANCA vasculitis" had a higher relapse rate (hazard ratio [HR] = 2.12, P = 0.067). The incidence of end-stage renal disease was higher in patients belonging to the "renal-limited vasculitis" cluster (HR=1.50, P=0.03), and those in the "ANCA-negative vasculitis" cluster experienced a relatively milder clinical course of AAV (mortality = 0). CONCLUSION: Because the clusters were naturally derived from their distinguished phenotypes and have different clinical courses, our clustering method may be a more clinically relevant classification system for AAV, revealing its phenotypic diversity. We also proposed a simple and intuitive distance-based assignment algorithm, which can be easily modified according to specific clinical needs. Key Points • In this study with a single-center AAV cohort, we showed that AAV can be divided into five distinct subclasses with different disease courses based on the clinical and laboratory features of the patients. • Our study revealed ethnic differences in AAV manifestation and suggests that physicians may need to analyze their own AAV patients to assess the disease status of AAV patients. • We proposed a distance-based cluster membership assignment method that can be clinically modified to fit the specific purpose of grouping patients.