ArticleQuantitative imaging in medicine and surgery2024
Correlation between magnetic resonance imaging (MRI) features and lesion size in focal nodular hyperplasia of the liver.
Article in Quantitative imaging in medicine and surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Focal nodular hyperplasia (FNH) in the liver is a benign lesion and the relationship between lesion size and imaging features is yet to be established. We aimed to develop and validate a scoring system to assess the relationship between magnetic resonance imaging (MRI) features and lesion size in FNH. Methods: This cross-sectional study was conducted at Zhongshan Hospital, Fudan University in Shanghai, China, from August 2019 and March 2023. Three hundred and seven patients with 363 surgically confirmed FNHs were retrospectively enrolled (training set: 254 lesions, validation set: 109 lesions). Lesions were divided into large (>3 cm) and small (≤3 cm) groups according to the diameter. Multivariate logistic regression was used to assess imaging features associated with lesion size in the training set. A scoring system was constructed and verified. The discrimination and calibration performance of the scoring system were evaluated by the receiver operating characteristic and calibration curve. Results: In the training set, a round appearance (P<0.001) and hyperintense on arterial, portal and delayed phase (P=0.004) were more frequently observed in small FNHs, whereas a lobulated appearance [odds ratio (OR) =4.155, 95% confidence interval (CI): 2.023-8.536; P<0.001], feeding artery (OR =7.083, 95% CI: 2.970-16.892; P<0.001), radiating septa (OR =3.747, 95% CI: 1.682-8.347; P=0.001), central scar (OR =2.838, 95% CI: 1.284-6.273; P=0.010), hyperintense on arterial phase, hyper to isointense on portal phase, and isointense on delayed phase (OR =3.539, 95% CI: 1.650-7.595; P=0.001) were significantly associated with large FNHs. A scoring system derived from these variables showed an area under the curve of 0.888 (95% CI: 0.843-0.924) and 0.896 (95% CI: 0.821-0.945) in training and validation set respectively. Conclusions: Through scoring MRI features, it can be observed that these features contribute differently to the diagnosis of FNH depending on its size.
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