New-onset atrial fibrillation in seropositive rheumatoid arthritis: association with disease-modifying anti-rheumatic drugs treatment.

OBJECTIVE: Atrial fibrillation (AF) is a potentially lethal complication that leads to increased hospitalization, disability and mortality. Furthermore, the risk of cardiovascular disease is increased in RA. We evaluated whether DMARD treatment is associated with incident AF in patients with seropositive RA (SPRA). METHODS: The South Korean Health Insurance Review and Assessment Service database was used to identify patients newly diagnosed with SPRA between 2010 and 2020. A nested case-control analysis was performed to match AF-affected patients to unaffected controls for age, sex, follow-up duration, and index year of SPRA diagnosis at a 1:4 ratio. Adjusted conditional logistic regression was used to identify the predictive factors for AF. RESULTS: Of the 108 085 patients with SPRA, 2,629 (2.4%) developed new-onset AF, and the proportion of females was ∼67%. In the matched population, pre-existing comorbidities of hypertension, chronic kidney disease, and heart failure were associated with increased risk of AF. Meanwhile, the use of methotrexate (MTX) decreased the risk of incident AF [adjusted odds ratio (aOR), 0.89], whereas the use of leflunomide (LEF) increased AF (aOR, 1.21). In a subgroup of patients aged ≥50 years, LEF and adalimumab increased the occurrence of AF, while MTX decreased AF in males and LEF increased this risk in females. CONCLUSION: Although the number of subjects developing new-onset AF was small, MTX decreased and LEF increased incident AF in patients with RA. Especially, a distinct pattern of AF risk with DMARDs usage was observed according to age and sex.

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.

Presence of periodontal disease and the incidence of inflammatory arthritides in the general population: data from the UK Biobank.

OBJECTIVES: To investigate the association between periodontal disease and the development of inflammatory arthritides in the general population. METHODS: In total, 489 125 participants from the UK Biobank without a previous history of RA, AS and PsA were enrolled. The primary outcome was the incidence of inflammatory arthritides, which was a composite of RA, AS and PsA according to the presence of periodontal disease based on self-reported oral health indicators. Multivariate Cox proportional hazard regression analyses using four different models were performed to assess the association between periodontal disease and inflammatory arthritides development. RESULTS: In all, 86 905 and 402 220 individuals were categorized as with and without periodontal disease, respectively. Cox hazard analysis indicated that the presence of periodontal disease was an independent predictor of the occurrence of composite outcomes of inflammatory arthritides, which was also consistent for RA and AS. Significant associations were found to be consistent in the four Cox models and were replicated even when different criteria were used to define periodontal disease. Subgroup analyses indicated that periodontal disease was associated with an increased RA risk in those aged <60 years, and this risk was persistent for both male and female patients and for patients with seropositive/seronegative RA. CONCLUSION: Self-reported periodontal disease is associated with inflammatory arthritides incidence in participants included in the UK Biobank, particularly for RA and AS. Higher clinical attention and optimal dental care in patients with signs of periodontal disease may be recommended for early disease detection and for reducing this risk.

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.

Rethinking extent of resection of contrast-enhancing and non-enhancing tumor: different survival impacts on adult-type diffuse gliomas in 2021 World Health Organization classification.

OBJECTIVES: Extent of resection (EOR) of contrast-enhancing (CE) and non-enhancing (NE) tumors may have different impacts on survival according to types of adult-type diffuse gliomas in the molecular era. This study aimed to evaluate the impact of EOR of CE and NE tumors in glioma according to the 2021 World Health Organization classification. METHODS: This retrospective study included 1193 adult-type diffuse glioma patients diagnosed between 2001 and 2021 (183 oligodendroglioma, 211 isocitrate dehydrogenase [IDH]-mutant astrocytoma, and 799 IDH-wildtype glioblastoma patients) from a single institution. Patients had complete information on IDH mutation, 1p/19q codeletion, and O6-methylguanine-methyltransferase (MGMT) status. Cox survival analyses were performed within each glioma type to assess predictors of overall survival, including clinical, imaging data, histological grade, MGMT status, adjuvant treatment, and EOR of CE and NE tumors. Subgroup analyses were performed in patients with CE tumor. RESULTS: Among 1193 patients, 935 (78.4%) patients had CE tumors. In entire oligodendrogliomas, gross total resection (GTR) of NE tumor was not associated with survival (HR = 0.56, p = 0.223). In 86 (47.0%) oligodendroglioma patients with CE tumor, GTR of CE tumor was the only independent predictor of survival (HR = 0.16, p = 0.004) in multivariable analysis. GTR of CE and NE tumors was independently associated with better survival in IDH-mutant astrocytoma and IDH-wildtype glioblastoma (all ps < 0.05). CONCLUSIONS: GTR of both CE and NE tumors may significantly improve survival within IDH-mutant astrocytomas and IDH-wildtype glioblastomas. In oligodendrogliomas, the EOR of CE tumor may be crucial in survival; aggressive GTR of NE tumor may be unnecessary, whereas GTR of the CE tumor is recommended. CLINICAL RELEVANCE STATEMENT: Surgical strategies on contrast-enhancing (CE) and non-enhancing (NE) tumors should be reassessed considering the different survival outcomes after gross total resection depending on CE and NE tumors in the 2021 World Health Organization classification of adult-type diffuse gliomas. KEY POINTS: The survival impact of extent of resection of contrast-enhancing (CE) and non-enhancing (NE) tumors was evaluated in adult-type diffuse gliomas. Gross total resection of both CE and NE tumors may improve survival in isocitrate dehydrogenase (IDH)-mutant astrocytomas and IDH-wildtype glioblastomas, while only gross total resection of the CE tumor improves survival in oligodendrogliomas. Surgical strategies should be reconsidered according to types in adult-type diffuse gliomas.

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.

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.

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.

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.

Incidence of septic arthritis in patients with ankylosing spondylitis and seropositive rheumatoid arthritis following TNF inhibitor therapy.

OBJECTIVES: Septic arthritis (SA) is a serious complication occurring in the joints, and its risk increases with immunosuppressive therapy. This study investigated whether TNF inhibitors increase the risk of SA in patients with AS and seropositive RA (SPRA). METHODS: We searched the South Korean Health Insurance Review and Assessment Service database for incident cases of AS and SPRA between 2010 and 2020. SA was defined using the diagnostic code M00 and hospital admission. Cox-proportional hazards analysis was conducted to compare the incidence of SA according to TNF inhibitor (infliximab, etanercept, adalimumab/golimumab) use during follow-up. RESULTS: Of the 145 129 patients analysed, 1170 (0.8%) developed SA during the follow-up period. Older age; male sex; SPRA diagnosis; comorbidities of hypertension (HTN), diabetes mellitus (DM) and chronic pulmonary disease (CPD); and infliximab and etanercept use increased the incidence of SA in the overall population. However, in patients with AS, only age and renal disease were predictors of SA, and TNF inhibitors did not increase the incidence of SA. Meanwhile, patients with SPRA treated with TNF inhibitors were prone to SA regardless of TNF inhibitor type, and age, HTN, DM and CPD were associated with SA. The incidence of SA was prominent after the first year of commencing TNF inhibitor therapy, for both AS and SPRA. CONCLUSION: TNF inhibitors increase the incidence of SA, specifically in patients with SPRA, but not AS. Importantly, age, comorbidities and the early time period after starting TNF inhibitors were associated with SA, which should be considered simultaneously when initiating TNF inhibitor therapy.

Reclassification of previously diagnosed GPA patients using the 2022 ACR/EULAR classification criteria.

OBJECTIVES: This study applied the 2022 criteria for granulomatosis with polyangiitis (GPA) proposed by the ACR and EULAR (the 2022 ACR/EULAR criteria) to Korean patients with previously diagnosed GPA to investigate the number of patients who could be reclassified as having GPA. METHODS: Sixty-five patients with GPA, who met the 2012 revised International Chapel Hill Consensus Conference Nomenclature of Vasculitides and the 2007 European Medicines Agency algorithm for GPA, were included in this study. They were reclassified based on the 2022 ACR/EULAR criteria. RESULTS: Of the 65 patients, 48 patients (73.8%) were reclassified as having GPA. A patient could not be reclassified as having GPA if the patient did not have a total score of 5 despite granulomas on biopsy or clear GPA surrogate markers. Among the 17 patients unclassified as having GPA, 16 patients were reclassified as having MPA and one as having unclassifiable vasculitis, and furthermore, 94.1% of them harboured MPO-ANCA (or perinuclear (P)-ANCA). CONCLUSION: The concordance rate between the 2022 ACR/EULAR criteria for GPA and the previous criteria in patients with previously diagnosed GPA was 73.8%. Although the 2022 ACR/EULAR criteria are the product of the most advanced methodologic process, it should be noted that there were some consequences of distorting the CHCC definition, and further discussion is required, especially with respect to the weightage of the items.

Applications of chemical exchange saturation transfer magnetic resonance imaging in identifying genetic markers in gliomas.

Chemical exchange saturation transfer (CEST) imaging is an important molecular magnetic resonance imaging technique that can image numerous low-concentration biomolecules with water-exchangeable protons (such as cellular proteins) and tissue pH. CEST, or more specially amide proton transfer-weighted imaging, has been widely used for the detection, diagnosis, and response assessment of brain tumors, and its feasibility in identifying molecular markers in gliomas has also been explored in recent years. In this paper, after briefing on the basic principles and quantification methods of CEST imaging, we review its early applications in identifying isocitrate dehydrogenase mutation status, MGMT methylation status, 1p/19q deletion status, and H3K27M mutation status in gliomas. Finally, we discuss the limitations or weaknesses in these studies.

Association of choroid plexus volume with motor symptoms and dopaminergic degeneration in Parkinson's disease.

BACKGROUND: The choroid plexus (CP) is involved in the clearance of harmful metabolites from the brain, as a part of the glymphatic system. This study aimed to investigate the association between CP volume (CPV), nigrostriatal dopaminergic degeneration and motor outcomes in Parkinson's disease (PD). METHODS: We retrospectively searched drug-naïve patients with early-stage PD who underwent dopamine transporter (DAT) scanning and MRI. Automatic CP segmentation was performed, and the CPV was calculated. The relationship between CPV, DAT availability and Unified PD Rating Scale Part III (UPDRS-III) scores was assessed using multivariate linear regression. We performed longitudinal analyses to assess motor outcomes according to CPV. RESULTS: CPV was negatively associated with DAT availability in each striatal subregion (anterior caudate, ß=-0.134, p=0.012; posterior caudate, ß=-0.162, p=0.002; anterior putamen, ß=-0.133, p=0.024; posterior putamen, ß=-0.125, p=0.039; ventral putamen, ß=-0.125, p=0.035), except for the ventral striatum. CPV was positively associated with the UPDRS-III score even after adjusting for DAT availability in the posterior putamen (ß=0.121; p=0.035). A larger CPV was associated with the future development of freezing of gait in the Cox regression model (HR 1.539, p=0.027) and a more rapid increase in dopaminergic medication in the linear mixed model (CPV×time, p=0.037), but was not associated with the risk of developing levodopa-induced dyskinesia or wearing off. CONCLUSION: These findings suggest that CPV has the potential to serve as a biomarker for baseline and longitudinal motor disabilities in PD.

The 2021 WHO Classification for Gliomas and Implications on Imaging Diagnosis: Part 2-Summary of Imaging Findings on Pediatric-Type Diffuse High-Grade Gliomas, Pediatric-Type Diffuse Low-Grade Gliomas, and Circumscribed Astrocytic Gliomas.

The fifth edition of the World Health Organization (WHO) classification of central nervous system tumors published in 2021 advances the role of molecular diagnostics in the classification of gliomas by emphasizing integrated diagnoses based on histopathology and molecular information and grouping tumors based on genetic alterations. This Part 2 review focuses on the molecular diagnostics and imaging findings of pediatric-type diffuse high-grade gliomas, pediatric-type diffuse low-grade gliomas, and circumscribed astrocytic gliomas. Each tumor type in pediatric-type diffuse high-grade glioma mostly harbors a distinct molecular marker. On the other hand, in pediatric-type diffuse low-grade gliomas and circumscribed astrocytic gliomas, molecular diagnostics may be extremely complicated at a glance in the 2021 WHO classification. It is crucial for radiologists to understand the molecular diagnostics and imaging findings and leverage the knowledge in clinical practice. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 3.

The 2021 WHO Classification for Gliomas and Implications on Imaging Diagnosis: Part 1-Key Points of the Fifth Edition and Summary of Imaging Findings on Adult-Type Diffuse Gliomas.

The fifth edition of the World Health Organization (WHO) classification of central nervous system tumors published in 2021 advances the role of molecular diagnostics in the classification of gliomas by emphasizing integrated diagnoses based on histopathology and molecular information and grouping tumors based on genetic alterations. Importantly, molecular biomarkers that provide important prognostic information are now a parameter for establishing tumor grades in gliomas. Understanding the 2021 WHO classification is crucial for radiologists for daily imaging interpretation as well as communication with clinicians. Although imaging features are not included in the 2021 WHO classification, imaging can serve as a powerful tool to impact the clinical practice not only prior to tissue confirmation but beyond. This review represents the first of a three-installment review series on the 2021 WHO classification for gliomas, glioneuronal tumors, and neuronal tumors and implications on imaging diagnosis. This Part 1 Review focuses on the major changes to the classification of gliomas and imaging findings on adult-type diffuse gliomas. EVIDENCE LEVEL: 3. TECHNICAL EFFICACY: Stage 3.

The 2021 WHO Classification for Gliomas and Implications on Imaging Diagnosis: Part 3-Summary of Imaging Findings on Glioneuronal and Neuronal Tumors.

The fifth edition of the World Health Organization classification of central nervous system tumors published in 2021 reflects the current transitional state between traditional classification system based on histopathology and the state-of-the-art molecular diagnostics. This Part 3 Review focuses on the molecular diagnostics and imaging findings of glioneuronal and neuronal tumors. Histological and molecular features in glioneuronal and neuronal tumors often overlap with pediatric-type diffuse low-grade gliomas and circumscribed astrocytic gliomas (discussed in the Part 2 Review). Due to this overlap, in several tumor types of glioneuronal and neuronal tumors the diagnosis may be inconclusive with histopathology and genetic alterations, and imaging features may be helpful to distinguish difficult cases. Thus, it is crucial for radiologists to understand the underlying molecular diagnostics as well as imaging findings for application on clinical practice. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 3.

Dynamic contrast-enhanced MRI radiomics model predicts epidermal growth factor receptor amplification in glioblastoma, IDH-wildtype.

PURPOSE: To develop and validate a dynamic contrast-enhanced (DCE) MRI-based radiomics model to predict epidermal growth factor receptor (EGFR) amplification in patients with glioblastoma, isocitrate dehydrogenase (IDH) wildtype. METHODS: Patients with pathologically confirmed glioblastoma, IDH wildtype, from January 2015 to December 2020, with an EGFR amplification status, were included. Patients who did not undergo DCE or conventional brain MRI were excluded. Patients were categorized into training and test sets by a ratio of 7:3. DCE MRI data were used to generate volume transfer constant (Ktrans) and extracellular volume fraction (Ve) maps. Ktrans, Ve, and conventional MRI were then used to extract the radiomics features, from which the prediction models for EGFR amplification status were developed and validated. RESULTS: A total of 190 patients (mean age, 59.9; male, 55.3%), divided into training (n = 133) and test (n = 57) sets, were enrolled. In the test set, the radiomics model using the Ktrans map exhibited the highest area under the receiver operating characteristic curve (AUROC), 0.80 (95% confidence interval [CI], 0.65-0.95). The AUROC for the Ve map-based and conventional MRI-based models were 0.74 (95% CI, 0.58-0.90) and 0.76 (95% CI, 0.61-0.91). CONCLUSION: The DCE MRI-based radiomics model that predicts EGFR amplification in glioblastoma, IDH wildtype, was developed and validated. The MRI-based radiomics model using the Ktrans map has higher AUROC than conventional MRI.

Revisiting prognostic factors in glioma with leptomeningeal metastases: a comprehensive analysis of clinical and molecular factors and treatment modalities.

PURPOSE: To comprehensively investigate prognostic factors, including clinical and molecular factors and treatment modalities, in adult glioma patients with leptomeningeal metastases (LM). METHODS: Total 226 patients with LM (from 2001 to 2021 among 1495 grade 2 to 4 glioma patients, 88.5% of LM patients being IDH-wildtype) with complete information on IDH mutation, 1p/19q codeletion, and MGMT promoter methylation status were enrolled. Predictors of overall survival (OS) of entire patients were determined by time-dependent Cox analysis, including clinical, molecular, and treatment data. Subgroup analyses were performed for patients with LM at initial diagnosis and LM diagnosed at recurrence (herein, initial and recurrent LM). Identical analyses were performed in IDH-wildtype glioblastoma patients. RESULTS: Median OS was 17.0 (IQR 9.7-67.1) months, with shorter median OS in initial LM than recurrent LM patients (12.2 vs 20.6 months, P < 0.001). In entire patients, chemotherapy and antiangiogenic therapy were predictors of longer OS, while male sex and initial LM were predictors of shorter OS. In initial LM, higher KPS, chemotherapy, and antiangiogenic therapy were predictors of longer OS, while male sex was a predictor of shorter OS. In recurrent LM, chemotherapy and longer interval between initial glioma and LM diagnoses were predictors of longer OS, while male sex was a predictor of shorter OS. A similar trend was observed in IDH-wildtype glioblastoma. CONCLUSION: Active chemotherapy and antiangiogenic therapy demonstrated survival benefit in glioma patients with LM. There is consistent female survival advantage, whereas longer interval between initial glioma diagnosis and LM development suggests longer OS in recurrent LM.

Intelligent noninvasive meningioma grading with a fully automatic segmentation using interpretable multiparametric deep learning.

OBJECTIVES: To establish a robust interpretable multiparametric deep learning (DL) model for automatic noninvasive grading of meningiomas along with segmentation. METHODS: In total, 257 patients with pathologically confirmed meningiomas (162 low-grade, 95 high-grade) who underwent a preoperative brain MRI, including T2-weighted (T2) and contrast-enhanced T1-weighted images (T1C), were included in the institutional training set. A two-stage DL grading model was constructed for segmentation and classification based on multiparametric three-dimensional U-net and ResNet. The models were validated in the external validation set consisting of 61 patients with meningiomas (46 low-grade, 15 high-grade). Relevance-weighted Class Activation Mapping (RCAM) method was used to interpret the DL features contributing to the prediction of the DL grading model. RESULTS: On external validation, the combined T1C and T2 model showed a Dice coefficient of 0.910 in segmentation and the highest performance for meningioma grading compared to the T2 or T1C only models, with an area under the curve (AUC) of 0.770 (95% confidence interval: 0.644-0.895) and accuracy, sensitivity, and specificity of 72.1%, 73.3%, and 71.7%, respectively. The AUC and accuracy of the combined DL grading model were higher than those of the human readers (AUCs of 0.675-0.690 and accuracies of 65.6-68.9%, respectively). The RCAM of the DL grading model showed activated maps at the surface regions of meningiomas indicating that the model recognized the features at the tumor margin for grading. CONCLUSIONS: An interpretable multiparametric DL model combining T1C and T2 can enable fully automatic grading of meningiomas along with segmentation. KEY POINTS: • The multiparametric DL model showed robustness in grading and segmentation on external validation. • The diagnostic performance of the combined DL grading model was higher than that of the human readers. • The RCAM interpreted that DL grading model recognized the meaningful features at the tumor margin for grading.

Natural language processing to predict isocitrate dehydrogenase genotype in diffuse glioma using MR radiology reports.

OBJECTIVES: To evaluate the performance of natural language processing (NLP) models to predict isocitrate dehydrogenase (IDH) mutation status in diffuse glioma using routine MR radiology reports. MATERIALS AND METHODS: This retrospective, multi-center study included consecutive patients with diffuse glioma with known IDH mutation status from May 2009 to November 2021 whose initial MR radiology report was available prior to pathologic diagnosis. Five NLP models (long short-term memory [LSTM], bidirectional LSTM, bidirectional encoder representations from transformers [BERT], BERT graph convolutional network [GCN], BioBERT) were trained, and area under the receiver operating characteristic curve (AUC) was assessed to validate prediction of IDH mutation status in the internal and external validation sets. The performance of the best performing NLP model was compared with that of the human readers. RESULTS: A total of 1427 patients (mean age ± standard deviation, 54 ± 15; 779 men, 54.6%) with 720 patients in the training set, 180 patients in the internal validation set, and 527 patients in the external validation set were included. In the external validation set, BERT GCN showed the highest performance (AUC 0.85, 95% CI 0.81-0.89) in predicting IDH mutation status, which was higher than LSTM (AUC 0.77, 95% CI 0.72-0.81; p = .003) and BioBERT (AUC 0.81, 95% CI 0.76-0.85; p = .03). This was higher than that of a neuroradiologist (AUC 0.80, 95% CI 0.76-0.84; p = .005) and a neurosurgeon (AUC 0.79, 95% CI 0.76-0.84; p = .04). CONCLUSION: BERT GCN was externally validated to predict IDH mutation status in patients with diffuse glioma using routine MR radiology reports with superior or at least comparable performance to human reader. CLINICAL RELEVANCE STATEMENT: Natural language processing may be used to extract relevant information from routine radiology reports to predict cancer genotype and provide prognostic information that may aid in guiding treatment strategy and enabling personalized medicine. KEY POINTS: • A transformer-based natural language processing (NLP) model predicted isocitrate dehydrogenase mutation status in diffuse glioma with an AUC of 0.85 in the external validation set. • The best NLP models were superior or at least comparable to human readers in both internal and external validation sets. • Transformer-based models showed higher performance than conventional NLP model such as long short-term memory.