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Diagnostic ability of intraoperative ultrasound for identifying tumor residual in glioma surgery operation.

ABSTRACT: Achieving total glioma resection represents a major challenge to neurosurgeons with no distinct margin between tumor and surrounding brain tissue. Many imaging methods are employed in surgery visualization and resection control. We performed this meta-analysis to assess the diagnosis value of intraoperative ultrasound and judged whether ultrasound is a suitable tool in detecting glioma residual. The databases including PubMed, Embase, Web of Science, China National Knowledge Infrastructure (CNKI), Wanfang and Weipu were systematically searched to find out relevant studies and published up to May 5, 2017. A total of 14 studies involving 542 participants met the selection criteria and bivariate mixed effects models were used for analysis. The parameters and their corresponding 95% confidence interval (CI) were computed on Stata 12.0 software. The pooled sensitivity was 0.75 (95%CI: 0.62-0.84), specificity was 0.88 (95%CI: 0.79-0.94), positive likelihood ratios was 6.27 (95%CI: 3.76-10.47), negative likelihood ratios was 0.29 (95%CI: 0.20-0.42), diagnostic odds ratios was 21.83 (95%CI: 14.20-33.55) and area under the curve of summary receiver operator characteristic was 0.89. Stratified meta-analysis showed sensitivity and area under the curve in low-grade glioma were both higher than high-grade glioma. The Deek's plot showed no significant publication bias (t = -1.03, P = 0.33). Intraoperative ultrasound has high overall diagnostic value to identify glioma remnants, especially in low-grade glioma, which shows a benefit for prognosis and life quality of patients. In general, Intraoperative ultrasound is an effective tool for maximizing the extent of glioma resection.

SUBMITTER: Zhang G

PROVIDER: S-EPMC5641196 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature

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Diagnostic ability of intraoperative ultrasound for identifying tumor residual in glioma surgery operation.

Zhang Guangying G Li Zhanzhan Z Si Daolin D Shen Liangfang L

Oncotarget 20170822 42

Achieving total glioma resection represents a major challenge to neurosurgeons with no distinct margin between tumor and surrounding brain tissue. Many imaging methods are employed in surgery visualization and resection control. We performed this meta-analysis to assess the diagnosis value of intraoperative ultrasound and judged whether ultrasound is a suitable tool in detecting glioma residual. The databases including PubMed, Embase, Web of Science, China National Knowledge Infrastructure (CNKI ...[more]

PMID: 29069853

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Project description:BackgroundMolecular diagnosis is crucial for biomarker-assisted glioma resection and management. However, some limitations of current molecular diagnostic techniques prevent their widespread use intraoperatively. With the unique advantages of ultrasound, this study developed a rapid intraoperative molecular diagnostic method based on ultrasound radio-frequency signals.MethodsWe built a brain tumor ultrasound bank with 169 cases enrolled since July 2020, of which 43483 RF signal patches from 67 cases with a pathological diagnosis of glioma were a retrospective cohort for model training and validation. IDH1 and TERT promoter (TERTp) mutations and 1p/19q co-deletion were detected by next-generation sequencing. We designed a spatial-temporal integration model (STIM) to diagnose the three molecular biomarkers, thus establishing a rapid intraoperative molecular diagnostic system for glioma, and further analysed its consistency with the fifth edition of the WHO Classification of Tumors of the Central Nervous System (WHO CNS5). We tested STIM in 16-case prospective cohorts, which contained a total of 10384 RF signal patches. Two other RF-based classical models were used for comparison. Further, we included 20 cases additional prospective data for robustness test (ClinicalTrials.govNCT05656053).FindingsIn the retrospective cohort, STIM achieved a mean accuracy and AUC of 0.9190 and 0.9650 (95% CI, 0.94-0.99) respectively for the three molecular biomarkers, with a total time of 3 s and a 96% match to WHO CNS5. In the prospective cohort, the diagnostic accuracy of STIM is 0.85 ± 0.04 (mean ± SD) for IDH1, 0.84 ± 0.05 for TERTp, and 0.88 ± 0.04 for 1p/19q. The AUC is 0.89 ± 0.02 (95% CI, 0.84-0.94) for IDH1, 0.80 ± 0.04 (95% CI, 0.71-0.89) for TERTp, and 0.85 ± 0.06 (95% CI, 0.73-0.98) for 1p/19q. Compared to the second best available method based on RF signal, the diagnostic accuracy of STIM is improved by 16.70% and the AUC is improved by 19.23% on average.InterpretationSTIM is a rapid, cost-effective, and easy-to-manipulate AI method to perform real-time intraoperative molecular diagnosis. In the future, it may help neurosurgeons designate personalized surgical plans and predict survival outcomes.FundingA full list of funding bodies that contributed to this study can be found in the Acknowledgements section.

Dataset Information

Diagnostic ability of intraoperative ultrasound for identifying tumor residual in glioma surgery operation.

Publications

Diagnostic ability of intraoperative ultrasound for identifying tumor residual in glioma surgery operation.

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