Human performance in predicting enhancement quality of gliomas using gadolinium-free MRI sequences - Azizova, Aynur; Wamelink, Ivar J H G; Prysiazhniuk, Yeva; Cakmak, Marcus; Kaya, Elif; Petr, Jan; Barkhof, Frederik; Keil, Vera C (Journal of neuroimaging, 2024)
BACKGROUND AND PURPOSE: To develop and test a decision tree for predicting contrast enhancement quality and shape using precontrast magnetic resonance imaging (MRI) sequences in a large adult-type diffuse glioma cohort. METHODS: Preoperative MRI scans (development/optimization/test sets: n = 31/38/303, male = 17/22/189, mean age = 52/59/56.7 years, high-grade glioma = 22/33/249) were retrospectively evaluated, including pre- and postcontrast T1-weighted, T2-weighted, fluid-attenuated inversion recovery, and diffusion-weighted imaging sequences. Enhancement prediction decision tree (EPDT) was developed using development and optimization sets, incorporating four imaging features: necrosis, diffusion restriction, T2 inhomogeneity, and nonenhancing tumor margins. EPDT accuracy was assessed on a test set by three raters of variable experience. True enhancement features (gold standard) were evaluated using pre- and postcontrast T1-weighted images. Statistical analysis used confusion matrices, Cohen's/Fleiss' kappa, and Kendall's W. Significance threshold was p < .05. RESULTS: Raters 1, 2, and 3 achieved overall accuracies of .86 (95% confidence interval [CI]: .81-.90), .89 (95% CI: .85-.92), and .92 (95% CI: .89-.95), respectively, in predicting enhancement quality (marked, mild, or no enhancement). Regarding shape, defined as the thickness of enhancing margin (solid, rim, or no enhancement), accuracies were .84 (95% CI: .79-.88), .88 (95% CI: .84-.92), and .89 (95% CI: .85-.92). Intrarater intergroup agreement comparing predicted and true enhancement features consistently reached substantial levels (≥.68 [95% CI: .61-.75]). Interrater comparison showed at least moderate agreement (group: ≥.42 [95% CI: .36-.48], pairwise: ≥.61 [95% CI: .50-.72]). Among the imaging features in the EPDT, necrosis assessment displayed the highest intra- and interrater consistency (≥.80 [95% CI: .73-.88]). CONCLUSION: The proposed EPDT has high accuracy in predicting enhancement patterns of gliomas irrespective of rater experience.
Keywords: lidé; magnetická rezonanční tomografie; vylepšení obrazu; Middle Aged; Adult; gliom; Decision Trees; Magnetic Resonance Imaging; senzitivita a specificita; Female; Contrast Media; Sensitivity and Specificity; Gadolinium; Brain Neoplasms; retrospektivní studie; Humans; Image Enhancement; gadolinium; lidé středního věku; mužské pohlaví; nádory mozku; ženské pohlaví; Male; Reproducibility of Results; Aged; rozhodovací stromy; reprodukovatelnost výsledků; kontrastní látky; Retrospective Studies; dospělí; Glioma; senioři