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  • Frontiers Media SA  (7)
  • Fang, Shengyu  (7)
  • 2020-2024  (7)
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  • Frontiers Media SA  (7)
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  • 2020-2024  (7)
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  • 1
    Online Resource
    Online Resource
    Table_3.docx
    Frontiers Media SA ; 2021
    In:  Frontiers in Oncology Vol. 10 ( 2021-2-11)
    Details
    In: Frontiers in Oncology, Frontiers Media SA, Vol. 10 ( 2021-2-11)
    Abstract: The detection of mutations in telomerase reverse transcriptase promoter (p TERT ) is important since preoperative diagnosis of p TERT status helps with evaluating prognosis and determining the surgical strategy. Here, we aimed to establish a radiomics-based machine-learning algorithm and evaluated its performance with regard to the prediction of mutations in p TERT in patients with World Health Organization (WHO) grade II gliomas. In total, 164 patients with WHO grade II gliomas were enrolled in this retrospective study. We extracted a total of 1,293 radiomics features from multi-parametric magnetic resonance imaging scans. Elastic net (used for feature selection) and support vector machine with linear kernel were applied in nested 10-fold cross-validation loops. The predictive model was evaluated by receiver operating characteristic and precision-recall analyses. We performed an unpaired t-test to compare the posterior predictive probabilities among patients with differing p TERT statuses. We selected 12 valuable radiomics features using nested 10-fold cross-validation loops. The area under the curve (AUC) was 0.8446 (95% confidence interval [CI], 0.7735–0.9065) with an optimal summed value of sensitivity of 0.9355 (95% CI, 0.8802–0.9788) and specificity of 0.6197 (95% CI, 0.5071–0.7371). The overall accuracy was 0.7988 (95% CI, 0.7378–0.8598). The F1-score was 0.8406 (95% CI, 0.7684–0.902) with an optimal precision of 0.7632 (95% CI, 0.6818–0.8364) and recall of 0.9355 (95% CI, 0.8802–0.9788). Posterior probabilities of p TERT mutations were significantly different between patients with wild-type and mutant TERT promoters. Our findings suggest that a radiomics analysis with a machine-learning algorithm can be useful for predicting p TERT status in patients with WHO grade II glioma and may aid in glioma management.
    Type of Medium: Online Resource
    ISSN: 2234-943X
    URL: Article
    URL: Article
    URL: Article
    URL: Article
    URL: Article
    DOI: 10.3389/fonc.2020.606741
    DOI: 10.3389/fonc.2020.606741.s001
    DOI: 10.3389/fonc.2020.606741.s002
    DOI: 10.3389/fonc.2020.606741.s003
    DOI: 10.3389/fonc.2020.606741.s004
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2021
    detail.hit.zdb_id: 2649216-7
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    Online Resource
  • 2
    Online Resource
    Online Resource
    Table_1.docx
    Frontiers Media SA ; 2021
    In:  Frontiers in Oncology Vol. 11 ( 2021-7-6)
    Details
    In: Frontiers in Oncology, Frontiers Media SA, Vol. 11 ( 2021-7-6)
    Abstract: The present study aimed to preoperatively predict the status of 1p/19q based on radiomics analysis in patients with World Health Organization (WHO) grade II gliomas. Methods This retrospective study enrolled 157 patients with WHO grade II gliomas (76 patients with astrocytomas with mutant IDH, 16 patients with astrocytomas with wild-type IDH, and 65 patients with oligodendrogliomas with mutant IDH and 1p/19q codeletion). Radiomic features were extracted from magnetic resonance images, including T1-weighted, T2-weighted, and contrast T1-weighted images. Elastic net and support vector machines with radial basis function kernel were applied in nested 10-fold cross-validation loops to predict the 1p/19q status. Receiver operating characteristic analysis and precision-recall analysis were used to evaluate the model performance. Student’s t -tests were then used to compare the posterior probabilities of 1p/19q co-deletion prediction in the group with different 1p/19q status. Results Six valuable radiomic features, along with age, were selected with the nested 10-fold cross-validation loops. Five features showed significant difference in patients with different 1p/19q status. The area under curve and accuracy of the predictive model were 0.8079 (95% confidence interval, 0.733–0.8755) and 0.758 (0.6879–0.8217), respectively, and the F1-score of the precision-recall curve achieved 0.6667 (0.5201–0.7705). The posterior probabilities in the 1p/19q co-deletion group were significantly different from the non-deletion group. Conclusion Combined radiomics analysis and machine learning showed potential clinical utility in the preoperative prediction of 1p/19q status, which can aid in making customized neurosurgery plans and glioma management strategies before postoperative pathology.
    Type of Medium: Online Resource
    ISSN: 2234-943X
    URL: Article
    URL: Article
    URL: Article
    DOI: 10.3389/fonc.2021.616740
    DOI: 10.3389/fonc.2021.616740.s001
    DOI: 10.3389/fonc.2021.616740.s002
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2021
    detail.hit.zdb_id: 2649216-7
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  • 3
    Online Resource
    Online Resource
    Data_Sheet_1.DOCX
    Frontiers Media SA ; 2021
    In:  Frontiers in Neurology Vol. 12 ( 2021-3-18)
    Details
    In: Frontiers in Neurology, Frontiers Media SA, Vol. 12 ( 2021-3-18)
    Abstract: Background: The use of electrocorticography (ECoG) to avoid intraoperative stimulation-induced seizure (ISS) during awake craniotomy is controversial. Although a standard direct cortical stimulating (DCS) protocol is used to identify the eloquent cortices and subcortical structures, ISS still occurs. Epilepsy is related to alterations in brain networks. In this study, we investigated specific alterations in brain networks in patients with ISS. Methods: Twenty-seven patients with glioma were enrolled and categorized into the ISS and non-ISS groups based on their history of ISS occurrence. A standard DCS protocol was used during awake craniotomy without ECoG supervision. Graph theoretical measurement was used to analyze resting-state functional magnetic resonance imaging data to quantitatively reveal alterations in the functional networks. Results: In the sensorimotor networks, the glioma significantly decreased the functional connectivity (FC) of four edges in the ISS group, which were conversely increased in the non-ISS group after multiple corrections ( p & lt; 0.001, threshold of p -value = 0.002). Regarding the topological properties, the sensorimotor network of all participants was classified as a small-world network. Glioma significantly increased global efficiency, nodal efficiency, and the sigma value, as well as decreased the shortest path length in the ISS group compared with the non-ISS group ( p & lt; 0.05). Conclusions: The specific alterations indicating patient susceptibility to ISS during DCS increased global and nodal efficiencies and decreased the shortest path length and FC induced by gliomas. If the patient has these specific alterations, ECoG is recommended to monitor after-discharge current during DCS to avoid ISS.
    Type of Medium: Online Resource
    ISSN: 1664-2295
    URL: Article
    URL: Article
    DOI: 10.3389/fneur.2021.602716
    DOI: 10.3389/fneur.2021.602716.s001
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2021
    detail.hit.zdb_id: 2564214-5
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  • 4
    Online Resource
    Online Resource
    DataSheet_1.pdf
    Frontiers Media SA ; 2022
    In:  Frontiers in Oncology Vol. 12 ( 2022-4-22)
    Details
    In: Frontiers in Oncology, Frontiers Media SA, Vol. 12 ( 2022-4-22)
    Abstract: Some gliomas in sensorimotor areas induce motor deficits, while some do not. Cortical destruction and reorganization contribute to this phenomenon, but detailed reasons remain unclear. This study investigated the differences of the functional connectivity and topological properties in the contralesional sensorimotor network (cSMN) between patients with motor deficit and those with normal motor function. Methods We retrospectively reviewed 65 patients (32 men) between 2017 and 2020. The patients were divided into four groups based on tumor laterality and preoperative motor status (deficit or non-deficit). Thirty-three healthy controls (18 men) were enrolled after matching for sex, age, and educational status. Graph theoretical measurement was applied to reveal alterations of the topological properties of the cSMN by analyzing resting-state functional MRI. Results The results for patients with different hemispheric gliomas were similar. The clustering coefficient, local efficiency, transitivity, and vulnerability of the cSMN significantly increased in the non-deficit group and decreased in the deficit group compared to the healthy group ( p & lt; 0.05). Moreover, the nodes of the motor-related thalamus showed a significantly increased nodal efficiency and nodal local efficiency in the non-deficit group and decreased in the deficit group compared with the healthy group ( p & lt; 0.05). Conclusions We posited the existence of two stages of alterations of the preoperative motor status. In the compensatory stage, the cSMN sacrificed stability to acquire high efficiency and to compensate for impaired motor function. With the glioma growing and the motor function being totally damaged, the cSMN returned to a stable state and maintained healthy hemispheric motor function, but with low efficiency.
    Type of Medium: Online Resource
    ISSN: 2234-943X
    URL: Article
    URL: Article
    DOI: 10.3389/fonc.2022.882313
    DOI: 10.3389/fonc.2022.882313.s001
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
    detail.hit.zdb_id: 2649216-7
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    Online Resource
  • 5
    Online Resource
    Online Resource
    DataSheet_1.pdf
    Frontiers Media SA ; 2022
    In:  Frontiers in Oncology Vol. 12 ( 2022-2-16)
    Details
    In: Frontiers in Oncology, Frontiers Media SA, Vol. 12 ( 2022-2-16)
    Abstract: Glioma-related epilepsy (GRE) is a common symptom in patients with prefrontal glioma. Epilepsy onset is associated with functional network alterations. This study investigated alterations of functional networks in patients with prefrontal glioma and GRE. Methods Sixty-five patients with prefrontal lobe gliomas were retrospectively assessed and classified into GRE and non-GRE groups. Additionally, 25 healthy participants were enrolled after matching for general information. Imaging data were acquired within 72 h in pre-operation. The sensorimotor network was used to delineate alterations in functional connectivity (FC) and topological properties. One-way analysis of variance and post-hoc analysis with Bonferroni correction were used to calculate differences of FC and topological properties. Results All significant alterations were solely found in the sensorimotor network. Irrespective of gliomas located in the left or right prefrontal lobes, the edge between medial Brodmann area 6 and caudal ventrolateral Brodmann area 6 decreased FC in the GRE group compared with the non-GRE group [ p & lt; 0.0001 (left glioma), p = 0.0002 (right glioma)]. Moreover, the shortest path length decrease was found in the GRE group compared with the non-GRE group [ p = 0.0292 (left glioma) and p = 0.0129 (right glioma)]. Conclusions The reduction of FC between the medial BA 6 (supplementary motor area) and caudal ventrolateral BA 6 in the ipsilateral hemisphere and the shortening of the path length of the sensorimotor network were characteristics alterations in patients with GRE onset. These findings fill in the gap which is the relationship between GRE onset and the alterations of functional networks in patients with prefrontal glioma. Significance Statement Glioma related epilepsy is the most common symptom of prefrontal glioma. It is important to identify characteristic alterations in functional networks in patients with GRE. We found that all significant alterations occurred in the sensorimotor network. Moreover, a decreased FC in the supplementary motor area and a shortening of the path’s length are additional characteristics of glioma-related epilepsy. We believe that our findings indicate new directions of research that will contribute to future investigations of glioma-related epilepsy onset.
    Type of Medium: Online Resource
    ISSN: 2234-943X
    URL: Article
    URL: Article
    DOI: 10.3389/fonc.2022.840871
    DOI: 10.3389/fonc.2022.840871.s001
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
    detail.hit.zdb_id: 2649216-7
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  • 6
    Online Resource
    Online Resource
    Table_1.docx
    Frontiers Media SA ; 2021
    In:  Frontiers in Neurology Vol. 12 ( 2021-6-18)
    Details
    In: Frontiers in Neurology, Frontiers Media SA, Vol. 12 ( 2021-6-18)
    Abstract: Background: Glioma-related epilepsy (GRE) is the most common presenting sign of patients with diffuse glioma. According to clinical experience, new-onset postoperative seizures can be observed even in patients without preoperative GRE. The current study mainly aimed to explore the risk factors of new-onset postoperative seizures in those patients. In addition, the prognostic value of new-onset postoperative seizures was also discussed. Methods: Data of 313 patients without GRE were retrospectively reviewed. Chi-square test or Fisher's exact test were first performed to compare categorical variables between patients with new-onset postoperative seizures and those without. Subsequently, binary logistic regression analysis was conduct to further assess risk factors of new-onset postoperative seizures. Kaplan-Meier and Cox analysis were used to investigate the prognostic value of new-onset postoperative seizures for progression-free survival (PFS) and overall survival (OS). Results: Patients with low-grade tumors ( p = 0.006), isocitrate dehydrogenase 1 (IDH1) mutation ( p = 0.040) or low Ki-67 expression ( p = 0.005) showed a higher incidence of new-onset postoperative seizures. IDH1 mutation was identified as the only independent predictor for new-onset postoperative seizures (OR, 2.075; 95% CI, 1.051–4.098; p = 0.035). Additionally, new-onset postoperative seizure occurrence was demonstrated as an independent predicter of prolonged OS (OR, 0.574; 95% CI, 0.335–0.983; p = 0.043), while younger age, gross total resection, low-grade and IDH1 mutation were independently correlated with prolonged OS and PFS. Conclusions: IDH1 mutation is an independent predictor for new-onset postoperative seizures in patients without preoperative GRE. Moreover, new-onset postoperative seizures can independently predict prolonged OS in those patients. The results of the current study can contribute to improving the individualized management of diffuse glioma.
    Type of Medium: Online Resource
    ISSN: 1664-2295
    URL: Article
    URL: Article
    DOI: 10.3389/fneur.2021.682535
    DOI: 10.3389/fneur.2021.682535.s001
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2021
    detail.hit.zdb_id: 2564214-5
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    Online Resource
  • 7
    Online Resource
    Online Resource
    Data_Sheet_1.DOCX
    Frontiers Media SA ; 2020
    In:  Frontiers in Neurology Vol. 11 ( 2020-7-17)
    Details
    In: Frontiers in Neurology, Frontiers Media SA, Vol. 11 ( 2020-7-17)
    Type of Medium: Online Resource
    ISSN: 1664-2295
    URL: Article
    URL: Article
    DOI: 10.3389/fneur.2020.00684
    DOI: 10.3389/fneur.2020.00684.s001
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2020
    detail.hit.zdb_id: 2564214-5
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