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PURPOSE: Whether molecular glioblastomas (GBMs) identify with a similar dismal prognosis as a "classical" histological GBM is controversial. This study aimed to compare the clinical, molecular, imaging, surgical factors, and prognosis between molecular GBMs and histological GBMs. METHODS: Retrospective chart and imaging review was performed in 983 IDH-wildtype GBM patients (52 molecular GBMs and 931 histological GBMs) from a single institution between 2005 and 2023. Propensity score-matched analysis was additionally performed to adjust for differences in baseline variables between molecular GBMs and histological GBMs. RESULTS: Molecular GBM patients were substantially younger (58.1 vs. 62.4, P = 0.014) with higher rate of TERTp mutation (84.6% vs. 50.3%, P < 0.001) compared with histological GBM patients. Imaging showed higher incidence of gliomatosis cerebri pattern (32.7% vs. 9.2%, P < 0.001) in molecular GBM compared with histological GBM, which resulted in lesser extent of resection (P < 0.001) in these patients. The survival was significantly better in molecular GBM compared to histological GBM (median OS 30.2 vs. 18.4 months, P = 0.001). The superior outcome was confirmed in propensity score analyses by matching histological GBM to molecular GBM (P < 0.001). CONCLUSION: There are distinct clinical, molecular, and imaging differences between molecular GBMs and histological GBMs. Our results suggest that molecular GBMs have a more favorable prognosis than histological GBMs.
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Neoplasias Encefálicas , Glioblastoma , Mutação , Humanos , Glioblastoma/patologia , Glioblastoma/genética , Glioblastoma/diagnóstico por imagem , Masculino , Pessoa de Meia-Idade , Neoplasias Encefálicas/patologia , Neoplasias Encefálicas/genética , Neoplasias Encefálicas/diagnóstico por imagem , Neoplasias Encefálicas/mortalidade , Feminino , Prognóstico , Estudos Retrospectivos , Idoso , Adulto , Isocitrato Desidrogenase/genéticaRESUMO
PURPOSE: This study aimed to develop and validate a convolutional neural network (CNN) that automatically detects an aberrant right subclavian artery (ARSA) on preoperative computed tomography (CT) for thyroid cancer evaluation. MATERIALS AND METHODS: A total of 556 CT with ARSA and 312 CT with normal aortic arch from one institution were used as the training set for model development. A deep learning model for the classification of patch images for ARSA was developed using two-dimension CNN from EfficientNet. The diagnostic performance of our model was evaluated using external test sets (112 and 126 CT) from two institutions. The performance of the model was compared with that of radiologists for detecting ARSA using an independent dataset of 1683 consecutive neck CT. RESULTS: The performance of the model was achieved using two external datasets with an area under the curve of 0.97 and 0.99, and accuracy of 97% and 99%, respectively. In the temporal validation set, which included a total of 20 patients with ARSA and 1663 patients without ARSA, radiologists overlooked 13 ARSA cases. In contrast, the CNN model successfully detected all the 20 patients with ARSA. CONCLUSION: We developed a CNN-based deep learning model that detects ARSA using CT. Our model showed high performance in the multicenter validation.
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Redes Neurais de Computação , Artéria Subclávia , Tomografia Computadorizada por Raios X , Humanos , Artéria Subclávia/anormalidades , Artéria Subclávia/diagnóstico por imagem , Feminino , Masculino , Pessoa de Meia-Idade , Tomografia Computadorizada por Raios X/métodos , Adulto , Neoplasias da Glândula Tireoide/diagnóstico por imagem , Neoplasias da Glândula Tireoide/diagnóstico , Neoplasias da Glândula Tireoide/patologia , Anormalidades Cardiovasculares/diagnóstico por imagem , Idoso , Aneurisma/diagnóstico por imagem , Aprendizado ProfundoRESUMO
Although gliomatosis cerebri (GC) has been removed as an independent tumor type from the WHO classification, its extensive infiltrative pattern may harbor a unique biological behavior. However, the clinical implication of GC in the context of the 2021 WHO classification is yet to be unveiled. This study investigated the incidence, clinicopathologic and imaging correlations, and prognostic implications of GC in adult-type diffuse glioma patients. Retrospective chart and imaging review of 1,211 adult-type diffuse glioma patients from a single institution between 2005 and 2021 was performed. Among 1,211 adult-type diffuse glioma patients, there were 99 (8.2%) patients with GC. The proportion of molecular types significantly differed between patients with and without GC (P = 0.017); IDH-wildtype glioblastoma was more common (77.8% vs. 66.5%), while IDH-mutant astrocytoma (16.2% vs. 16.9%) and oligodendroglioma (6.1% vs. 16.5%) were less common in patients with GC than in those without GC. The presence of contrast enhancement, necrosis, cystic change, hemorrhage, and GC type 2 were independent risk factors for predicting IDH mutation status in GC patients. GC remained as an independent prognostic factor (HR = 1.25, P = 0.031) in IDH-wildtype glioblastoma patients on multivariable analysis, along with clinical, molecular, and surgical factors. Overall, our data suggests that although no longer included as a distinct pathological entity in the WHO classification, recognition of GC may be crucial considering its clinical significance. There is a relatively high incidence of GC in adult-type diffuse gliomas, with different proportion according to molecular types between patients with and without GC. Imaging may preoperatively predict the molecular type in GC patients and may assist clinical decision-making. The prognostic role of GC promotes its recognition in clinical settings.
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Neoplasias Encefálicas , Glioma , Isocitrato Desidrogenase , Neoplasias Neuroepiteliomatosas , Humanos , Masculino , Feminino , Pessoa de Meia-Idade , Adulto , Neoplasias Encefálicas/genética , Neoplasias Encefálicas/patologia , Neoplasias Encefálicas/diagnóstico por imagem , Neoplasias Neuroepiteliomatosas/genética , Neoplasias Neuroepiteliomatosas/patologia , Neoplasias Neuroepiteliomatosas/diagnóstico por imagem , Glioma/genética , Glioma/patologia , Glioma/diagnóstico por imagem , Estudos Retrospectivos , Idoso , Isocitrato Desidrogenase/genética , Mutação , Adulto Jovem , Imageamento por Ressonância Magnética , GenômicaRESUMO
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.
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Biomarcadores Tumorais , Neoplasias Encefálicas , Glioma , Humanos , Masculino , Feminino , Neoplasias Encefálicas/diagnóstico por imagem , Neoplasias Encefálicas/metabolismo , Adulto , Prognóstico , Estudos Retrospectivos , Pessoa de Meia-Idade , Glioma/diagnóstico por imagem , Glioma/patologia , Glioma/metabolismo , Idoso , Imageamento por Ressonância Magnética/métodos , Taxa de Sobrevida , Meios de ContrasteRESUMO
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.
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Neoplasias Encefálicas , Calcinose , Meios de Contraste , Imageamento por Ressonância Magnética , Gradação de Tumores , Oligodendroglioma , Carga Tumoral , Humanos , Oligodendroglioma/diagnóstico por imagem , Oligodendroglioma/patologia , Oligodendroglioma/genética , Feminino , Masculino , Adulto , Pessoa de Meia-Idade , Neoplasias Encefálicas/diagnóstico por imagem , Neoplasias Encefálicas/patologia , Neoplasias Encefálicas/genética , Idoso , Calcinose/diagnóstico por imagem , Calcinose/patologia , Estudos Retrospectivos , Imageamento por Ressonância Magnética/métodos , Organização Mundial da Saúde , Valor Preditivo dos TestesRESUMO
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.
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Cerebelo , Imageamento por Ressonância Magnética , Esquizofrenia , Esquizofrenia/diagnóstico por imagem , Esquizofrenia/patologia , Humanos , Cerebelo/diagnóstico por imagem , Cerebelo/patologia , Imageamento por Ressonância Magnética/normas , Masculino , Feminino , Adulto , Pessoa de Meia-Idade , Neuroimagem/normas , Neuroimagem/métodos , Adulto Jovem , Sensibilidade e Especificidade , RadiômicaRESUMO
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.
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Aim: To evaluate the performance of MRI-derived radiomic risk score (RRS) and PD-L1 expression to predict overall survival (OS) and progression-free survival (PFS) of patients with recurrent head and neck squamous cell carcinoma receiving nivolumab therapy. Materials & methods: Three hundred forty radiomic features from pretreatment MRI were used to construct the RRS. The integrated area under the receiver operating characteristic curve (iAUC) was calculated to evaluate the performance of the RRS and PD-L1. Results: The RRS showed iAUCs of 0.69 and 0.57 for OS and PFS, respectively. PD-L1 expression showed iAUCs of 0.61 and 0.62 for OS and PFS, respectively. Conclusion: RRS and PD-L1 potentially predict the OS and PFS of patients with recurrent head and neck squamous cell carcinoma receiving nivolumab therapy.
[Box: see text].
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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.
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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.
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Neoplasias Encefálicas , Glioblastoma , Humanos , Glioblastoma/diagnóstico por imagem , Glioblastoma/patologia , Neoplasias Encefálicas/diagnóstico por imagem , Neoplasias Encefálicas/secundário , Incerteza , Feminino , Pessoa de Meia-Idade , Masculino , Reprodutibilidade dos Testes , Adulto , Aprendizado Profundo , Idoso , Diagnóstico Diferencial , Imageamento por Ressonância Magnética/métodos , Sensibilidade e Especificidade , Área Sob a CurvaRESUMO
INTRODUCTION: Several cross-sectional studies have shown that long-term exposures to air pollutants are associated with smaller brain cortical volume or thickness. Here, we investigated longitudinal associations of long-term air pollution exposures with cortical thickness and subcortical volume. METHODS: In this longitudinal study, we included a prospective cohort of 361 adults residing in four cities in the Republic of Korea. Long-term concentrations of particulate matter with aerodynamic diameters of ≤10 µm (PM10) and ≤2.5 µm (PM2.5) and nitrogen dioxide (NO2) at residential addresses were estimated. Neuroimaging markers (cortical thickness and subcortical volume) were obtained from brain magnetic resonance images at baseline (August 2014 to March 2017) and at the 3-year follow-up (until September 2020). Linear mixed-effects models were used, adjusting for covariates. RESULTS: A 10-µg/m3 increase in PM10 was associated with reduced whole-brain mean (ß = -0.45, standard error [SE] = 0.10; p < 0.001), frontal (ß = -0.53, SE = 0.11; p < 0.001) and temporal thicknesses (ß = -0.37, SE = 0.12; p = 0.002). A 10-ppb increase in NO2 was associated with a decline in the whole-brain mean cortical thickness (ß = -0.23, SE = 0.05; p < 0.001), frontal (ß = -0.25, SE = 0.05; p < 0.001), parietal (ß = -0.12, SE = 0.05; p = 0.025), and temporal thicknesses (ß = -0.19, SE = 0.06; p = 0.001). Subcortical structures associated with air pollutants included the thalamus. CONCLUSIONS: Long-term exposures to PM10 and NO2 may lead to cortical thinning in adults.
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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.
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Neoplasias Encefálicas , Isocitrato Desidrogenase , Neoplasias Neuroepiteliomatosas , Humanos , Masculino , Feminino , Pessoa de Meia-Idade , Prognóstico , Neoplasias Neuroepiteliomatosas/patologia , Neoplasias Neuroepiteliomatosas/mortalidade , Neoplasias Neuroepiteliomatosas/genética , Estudos Retrospectivos , Neoplasias Encefálicas/patologia , Neoplasias Encefálicas/mortalidade , Neoplasias Encefálicas/genética , Neoplasias Encefálicas/cirurgia , Neoplasias Encefálicas/diagnóstico , Adulto , Idoso , Isocitrato Desidrogenase/genética , Glioma/patologia , Glioma/mortalidade , Glioma/genética , Glioma/cirurgia , Glioma/diagnóstico , Adulto Jovem , Taxa de Sobrevida , Mutação , SeguimentosRESUMO
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.
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Neoplasias Encefálicas , Imagem de Difusão por Ressonância Magnética , Glioma , Humanos , Glioma/diagnóstico por imagem , Glioma/mortalidade , Glioma/patologia , Feminino , Pessoa de Meia-Idade , Masculino , Adulto , Imagem de Difusão por Ressonância Magnética/métodos , Estudos Retrospectivos , Neoplasias Encefálicas/diagnóstico por imagem , Neoplasias Encefálicas/mortalidade , Neoplasias Encefálicas/patologia , Prognóstico , Curva ROC , Nomogramas , Modelos de Riscos Proporcionais , Gradação de Tumores , RadiômicaRESUMO
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.
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Neoplasias Encefálicas , Aprendizado Profundo , Neoplasias Pulmonares , Humanos , Neoplasias Pulmonares/diagnóstico por imagem , Estudos Retrospectivos , Reprodutibilidade dos Testes , Carga de Trabalho , Detecção Precoce de Câncer , Imageamento por Ressonância Magnética/métodos , Neoplasias Encefálicas/diagnóstico por imagem , Neoplasias Encefálicas/secundárioRESUMO
As a part of the glymphatic system, the choroid plexus (CP) is involved in the clearance of harmful metabolites from the brain. We investigated the association between CP volume (CPV), amyloid-ß (Aß) burden, and cognition in patients on the Alzheimer's disease (AD) continuum. We retrospectively reviewed the records of 203 patients on the AD continuum and 82 healthy controls who underwent brain magnetic resonance imaging and 18F-florbetaben positron emission tomography. Automatic segmentation was performed, and the CPV was calculated. Cognitive function was assessed using detailed neuropsychological tests, and patients on the AD continuum were categorized into the non-dementia and dementia groups. The relationships between CPV, Aß burden, and cognitive function were assessed using multivariate linear regression and linear mixed model. CPV was greater in the AD group than in the healthy control group (1.50 vs. 1.30, P < 0.001), but was comparable between the AD non-dementia and dementia groups (1.50 vs. 1.48, P = 0.585). After adjusting for age and sex, a larger CPV was significantly associated with greater global Aß deposition (ß = 0.20, P = 0.002). Larger CPV was also associated with worse general cognitive function assessed using the sum of boxes of the clinical dementia rating scale (ß = 0.85, P = 0.034) and lower composite scores for memory (ß = -0.68, P = 0.002) and frontal/executive function domains (ß = -0.65, P < 0.001). In addition, a larger CPV was associated with a more rapid decline in Mini-Mental State Examination scores in the AD dementia group (ß = -0.58, P = 0.004). The present study demonstrated that CP enlargement was associated with increased Aß deposition and impaired memory and frontal/executive function in patients on the AD continuum.
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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.
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Neoplasias Encefálicas , Glioblastoma , Glioma , Adulto , Humanos , Glioblastoma/patologia , Glioma/patologia , Neoplasias Encefálicas/patologia , Biomarcadores Tumorais/genética , Mutação , Necrose , OxigênioRESUMO
OBJECTIVES: This study explores whether textural features from initial non-contrast CT scans of infarcted brain tissue are linked to hemorrhagic transformation susceptibility. MATERIALS AND METHODS: Stroke patients undergoing thrombolysis or thrombectomy from Jan 2012 to Jan 2022 were analyzed retrospectively. Hemorrhagic transformation was defined using follow-up magnetic resonance imaging. A total of 94 radiomic features were extracted from the infarcted tissue on initial NCCT scans. Patients were divided into training and test sets (7:3 ratio). Two models were developed with fivefold cross-validation: one incorporating first-order and textural radiomic features, and another using only textural radiomic features. A clinical model was also constructed using logistic regression with clinical variables, and test set validation was performed. RESULTS: Among 362 patients, 218 had hemorrhagic transformations. The LightGBM model with all radiomics features had the best performance, with an area under the receiver operating characteristic curve (AUROC) of 0.986 (95% confidence interval [CI], 0.971-1.000) on the test dataset. The ExtraTrees model performed best when textural features were employed, with an AUROC of 0.845 (95% CI, 0.774-0.916). Minimum, maximum, and ten percentile values were significant predictors of hemorrhagic transformation. The clinical model showed an AUROC of 0.544 (95% CI, 0.431-0.658). The performance of the radiomics models was significantly better than that of the clinical model on the test dataset (p < 0.001). CONCLUSIONS: The radiomics model can predict hemorrhagic transformation using NCCT in stroke patients. Low Hounsfield unit was a strong predictor of hemorrhagic transformation, while textural features alone can predict hemorrhagic transformation. CLINICAL RELEVANCE STATEMENT: Using radiomic features extracted from initial non-contrast computed tomography, early prediction of hemorrhagic transformation has the potential to improve patient care and outcomes by aiding in personalized treatment decision-making and early identification of at-risk patients. KEY POINTS: ⢠Predicting hemorrhagic transformation following thrombolysis in stroke is challenging since multiple factors are associated. ⢠Radiomics features of infarcted tissue on initial non-contrast CT are associated with hemorrhagic transformation. ⢠Textural features on non-contrast CT are associated with the frailty of the infarcted tissue.
Assuntos
Acidente Vascular Cerebral , Tomografia Computadorizada por Raios X , Humanos , Masculino , Feminino , Tomografia Computadorizada por Raios X/métodos , Idoso , Estudos Retrospectivos , Acidente Vascular Cerebral/diagnóstico por imagem , Acidente Vascular Cerebral/etiologia , Pessoa de Meia-Idade , Hemorragia Cerebral/diagnóstico por imagem , Hemorragia Cerebral/etiologia , Imageamento por Ressonância Magnética/métodos , Trombectomia/métodos , Medição de Risco/métodos , RadiômicaRESUMO
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.
Assuntos
Astrocitoma , Neoplasias Encefálicas , Glioblastoma , Glioma , Oligodendroglioma , Humanos , Adulto , Neoplasias Encefálicas/diagnóstico por imagem , Neoplasias Encefálicas/genética , Neoplasias Encefálicas/cirurgia , Estudos Retrospectivos , Isocitrato Desidrogenase/genética , Glioma/diagnóstico por imagem , Glioma/genética , Glioma/cirurgia , Mutação , Organização Mundial da SaúdeRESUMO
PURPOSE: To investigate whether steep Trendelenburg in a major urologic surgery is associated with postoperative delirium, and to examine other potential clinical and radiologic factors predictive of postoperative delirium. METHODS: 182 patients who received a major urologic surgery and underwent a 3.0-T brain MRI scan within 1 year prior to the date of surgery were retrospectively enrolled. Preoperative brain MRIs were used to analyze features related to small vessel disease burden and mesial temporal atrophy. Presence of a significant mesial temporal atrophy was defined as Scheltens' scale ≥ 2. Patients' clinico-demographic data and MRI features were used to identify significant predictors of postoperative delirium using the logistic regression analysis. Independent predictors found significant in the univariate analysis were further evaluated in the multivariate analysis. RESULTS: Incidence of postoperative delirium was 6.0%. Patients with postoperative delirium had lower body mass index (21.3 vs. 25.0 kg/m2, P = 0.003), prolonged duration of anesthesia (362.7 vs. 224.7 min, P < 0.001) and surgery (302.2 vs. 174.5 min, P < 0.001), and had more significant mesial temporal atrophy (64% vs. 30%, P = 0.046). In the univariate analysis, female sex, type of surgery (radical prostatectomy over cystectomy), prolonged duration of anesthesia (≥ 6 h), and presence of a significant mesial temporal atrophy were significant predictors (all P-values < 0.050), but only the presence of significant mesial temporal atrophy was significant in the multivariate analysis [odds ratio (OR), 3.69; 95% CI 0.99-13.75; P = 0.046]. CONCLUSION: Steep Trendelenburg was not associated with postoperative delirium. Significant mesial temporal atrophy (Scheltens' scale ≥ 2) in preoperative brain MRI was predictive of postoperative delirium. TRIAL REGISTRATION: Not applicable.