Human performance in predicting enhancement quality of gliomas using gadolinium-free MRI sequences
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11130%2F24%3A10484996" target="_blank" >RIV/00216208:11130/24:10484996 - isvavai.cz</a>
Result on the web
<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=jADh4UJisY" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=jADh4UJisY</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1111/jon.13233" target="_blank" >10.1111/jon.13233</a>
Alternative languages
Result language
angličtina
Original language name
Human performance in predicting enhancement quality of gliomas using gadolinium-free MRI sequences
Original language description
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.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
30103 - Neurosciences (including psychophysiology)
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Journal of Neuroimaging
ISSN
1051-2284
e-ISSN
1552-6569
Volume of the periodical
34
Issue of the periodical within the volume
6
Country of publishing house
US - UNITED STATES
Number of pages
21
Pages from-to
673-693
UT code for WoS article
001316506300001
EID of the result in the Scopus database
2-s2.0-85204445726