Caiqiang Xue1 and Junlin Zhou1
1Lanzhou University Second Hospital, Lanzhou, China
Synopsis
Keywords: Tumors (Pre-Treatment), Tumor, glioblastoma; magnetic resonance imaging; apparent diffusion coefficient; CD8+ T cells
Motivation: Tumor-infiltrating CD8+ T cells play a key role in glioblastoma development, malignant progression, and recurrence.
Goal(s): The aim of the study was to establish nomograms based on the VASARI features of multiparametric MRI to determine the expression levels of CD8+ T cells in patients with glioblastoma.
Approach: 140 patients with glioblastoma confirmed by surgery and pathology were retrospectively analyzed. Patients were divided into high and low CD8 expression groups. The MRI images of patients with glioblastoma were analyzed using the VASARI scoring system.
Results: The features with the greatest predictive power for CD8 expression levels were, cystic, hemorrhage, and ependymal extension.
Impact: The VASARI feature-based
nomogram model can shows promise to predict the level of infiltrative CD8
expression in GB tumors noninvasively for earlier tissue diagnosis and more
aggressive treatment.
Abstract
Abstract
Background: Tumor-infiltrating CD8+ T cells play a key role in glioblastoma
development, malignant progression, and recurrence. The aim of the study was
to establish nomograms based on the Visually AcceSAble Rembrandt Images
(VASARI) features of multiparametric magnetic resonance imaging (MRI) to
determine the expression levels of tumor-infiltrating CD8+ T cells in patients
with glioblastoma.
Materials and methods: Pathological and imaging data of 140 patients
with glioblastoma confirmed by surgery and pathology were retrospectively
analyzed. The levels of tumor-infiltrating CD8+ T cells in tumor tissue samples
obtained from patients were quantified using immunohistochemical staining.
Patients were divided into high and low CD8 expression groups. The MRI images
of patients with glioblastoma were analyzed by two radiologists using the
VASARI scoring system.
Results: A total of 25 MRI-based VASARI imaging features
were evaluated by two neuroradiologists. The features with the greatest
predictive power for CD8 expression levels were, cystic (OR, 3.063; 95% CI:
1.387, 6.766; P = 0.006), hemorrhage (OR, 2.980; 95% CI: 1.172, 7.575; P =
0.022), and ependymal extension (OR, 0.257; 95% CI: 0.114 0.581; P = 0.001). A
logistic regression model based on these three features showed better sample
predictive performance (AUC = 0.745; 95% CI: 0.665, 0.825; Sensitivity = 0.527;
Specificity = 0.857).
Conclusions: The VASARI feature-based nomogram model can shows promise to predict
the level of infiltrative CD8 expression in GB tumors noninvasively for earlier
tissue diagnosis and more aggressive treatment.Acknowledgements
Not applicable.References
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