Dataset Information

Determining optimal clinical target volume margins in high-grade glioma based on microscopic tumor extension and magnetic resonance imaging.

ABSTRACT:

Introduction

In this study, we performed a consecutive macropathologic analysis to assess microscopic extension (ME) in high-grade glioma (HGG) to determine appropriate clinical target volume (CTV) margins for radiotherapy.

Materials and methods

The study included HGG patients with tumors located in non-functional areas, and supratotal resection was performed. The ME distance from the edge of the tumor to the microscopic tumor cells surrounding brain tissue was measured. Associations between the extent of ME and clinicopathological characteristics were evaluated by multivariate linear regression (MVLR) analysis. An ME predictive model was developed based on the MVLR model.

Results

Between June 2017 and July 2019, 652 pathologic slides obtained from 30 HGG patients were analyzed. The mean ME distance was 1.70 cm (range, 0.63 to 2.87 cm). The MVLR analysis identified that pathologic grade, subventricular zone (SVZ) contact and O⁶-methylguanine-DNA methyltransferase (MGMT) methylation, isocitrate dehydrogenase (IDH) mutation and 1p/19q co-deletion status were independent variables predicting ME (all P < 0.05). A multivariable prediction model was developed as follows: Y_ME = 0.672 + 0.513X_Grade + 0.380X_SVZ + 0.439X_MGMT + 0.320X_IDH + 0.333X_1p/19q. The R-square value of goodness of fit was 0.780. The receiver operating characteristic curve proved that the area under the curve was 0.964 (P < 0.001).

Conclusion

ME was heterogeneously distributed across different grades of gliomas according to the tumor location and molecular marker status, which indicated that CTV delineation should be individualized. The model could predict the ME of HGG, which may help clinicians determine the CTV for individual patients. Trial registration The trial was registered with Chinese Clinical Trial Registry (ChiCTR2100046106). Registered 4 May 2021-Retrospectively registered.

SUBMITTER: Nie S

PROVIDER: S-EPMC8186169 | biostudies-literature |

REPOSITORIES: biostudies-literature

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