Human performance in predicting enhancement quality of gliomas using gadolinium-free MRI sequences

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

Human performance in predicting enhancement quality of gliomas using gadolinium-free MRI sequences

Popis výsledku v původním jazyce

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&apos;s/Fleiss&apos; kappa, and Kendall&apos;s W. Significance threshold was p &lt; .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 (&gt;=.68 [95% CI: .61-.75]). Interrater comparison showed at least moderate agreement (group: &gt;=.42 [95% CI: .36-.48], pairwise: &gt;=.61 [95% CI: .50-.72]). Among the imaging features in the EPDT, necrosis assessment displayed the highest intra- and interrater consistency (&gt;=.80 [95% CI: .73-.88]). CONCLUSION: The proposed EPDT has high accuracy in predicting enhancement patterns of gliomas irrespective of rater experience.

Název v anglickém jazyce

Human performance in predicting enhancement quality of gliomas using gadolinium-free MRI sequences

Popis výsledku anglicky

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&apos;s/Fleiss&apos; kappa, and Kendall&apos;s W. Significance threshold was p &lt; .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 (&gt;=.68 [95% CI: .61-.75]). Interrater comparison showed at least moderate agreement (group: &gt;=.42 [95% CI: .36-.48], pairwise: &gt;=.61 [95% CI: .50-.72]). Among the imaging features in the EPDT, necrosis assessment displayed the highest intra- and interrater consistency (&gt;=.80 [95% CI: .73-.88]). CONCLUSION: The proposed EPDT has high accuracy in predicting enhancement patterns of gliomas irrespective of rater experience.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

30103 - Neurosciences (including psychophysiology)

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Journal of Neuroimaging

ISSN

1051-2284

e-ISSN

1552-6569

Svazek periodika

34

Číslo periodika v rámci svazku

6

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

21

Strana od-do

673-693

Kód UT WoS článku

001316506300001

EID výsledku v databázi Scopus

2-s2.0-85204445726