Evidence map›Paper›PMID 41068314›Full record

ArticlePediatric research2026

Prediction of motor developmental outcomes based on MRI radiomics in premature infants.

Han Meng, Fang He, Fei Li, Haiping Zu, Feng Wang, Hao Xie, Ying Liu, Mengyi Wang, Qiaozhi Ma, Siqing Dong and 3 more

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Article in Pediatric research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
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1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Han MengPostgraduate Training Base of the Third Medical Center of Chinese PLA General Hospital, Jinzhou Medical University, Beijing, China.
Fang HeDepartment of Child Growth and Development Clinic, The Seventh Medical Center of Chinese PLA General Hospital, Beijing, China.
Fei LiDepartment of Radiology, The Seventh Medical Center of Chinese PLA General Hospital, Beijing, China.
Haiping ZuDepartment of Radiology, Characteristic Medical Center of Rocket Army, Beijing, China.
Feng WangDepartment of Newborn Care Center, Senior Department of Pediatrics, The Seventh Medical Center of PLA General Hospital, Beijing, China.
Hao XieDepartment of Radiology, The Jintang First People's Hospital, Chengdu, China.
Ying LiuDepartment of Radiology & Tianjin Key Lab of Functional Imaging & Tianjin Institute of Radiology & State Key Laboratory of Experimental Hematology, Tianjin Medical University General Hospital, Tianjin, China.
Mengyi WangPostgraduate Training Base of the Third Medical Center of Chinese PLA General Hospital, Jinzhou Medical University, Beijing, China.
Qiaozhi MaDepartment of Radiology, The Third Medical Center of Chinese PLA General Hospital, Beijing, China.
Siqing DongThe First Affiliated Hospital of Jinzhou Medical University, Jinzhou, China.
Junnan DaiDepartment of Radiology, The Third Medical Center of Chinese PLA General Hospital, Beijing, China.
Bing WuDepartment of Radiology, The Seventh Medical Center of Chinese PLA General Hospital, Beijing, China. 13910720619@163.com.
Xuetao MuDepartment of Radiology, The Third Medical Center of Chinese PLA General Hospital, Beijing, China. muxuetao091@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study aimed to combine radiomics and clinical variables to predict motor developmental outcomes in preterm infants.

methodsBrain MRI images at term-equivalent age (TEA), perinatal clinical variables, and Bayley Scales of Infant and Toddler Development assessment results at 12-24 months corrected age were retrospectively collected for each preterm infant. Radiomic analysis was conducted on conventional MRI sequences, and a binary classification model for predicting motor neurodevelopmental outcomes was developed. A clinical prediction model was established on the basis of perinatal data, and a combined prediction model was created by integrating selected radiomic features. The predictive performance of each model was evaluated via the AUC.

resultsPreterm infants (n = 218) were included in the study, with 90 (41.3%) diagnosed with motor developmental delays. The AUCs of the prediction models were 0.75 (sensitivity 0.69, specificity 0.69) for multisequence radiomics, 0.87 (sensitivity 0.83, specificity 0.77) for clinical variables, and 0.94 (sensitivity 0.91, specificity 0.87) for the combined multisequence radiomics and clinical variables model.

conclusionA prediction model combining MRI-based radiomic biomarkers with clinical variables increases the accuracy of predicting motor developmental outcomes in preterm infants. IMPACT: Our results showed that birth weight and maternal hypertensive disorders are important risk factors for motor nerve development abnormalities in preterm infants with no significant abnormalities on magnetic resonance imaging. The combination of multisequence radiomic Rad-scores and clinical variable models can improve the prediction efficiency of adverse prognoses. These findings contribute to the early detection of motor nerve abnormalities in related preterm infants and timely interventions for the benefit of families with preterm infants.

Indexed as

BrainChild DevelopmentDevelopmental DisabilitiesInfant, PrematureMagnetic Resonance ImagingChild, PreschoolFemaleGestational AgeHumansInfantInfant, NewbornMaleNeurodevelopmentPredictive Value of TestsRadiomicsRetrospective Studies

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.