Evidence map›Paper›PMID 40116948›Full record

ArticleNeuroradiology2025

Radiomics based on preoperative magnetic resonance imaging predict the cell lineages of nonfunctioning pituitary neuroendocrine tumors.

Xuening Zhao, Xu Fu, Xiaochen Wang, Sihui Wang, Lingxu Chen, Mengyuan Yuan, Jiangang Liu, Shengjun Sun

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Article in Neuroradiology, 2025. 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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5 · Who and what money

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8 authors.

Xuening ZhaoBeijing Tian Tan Hospital, Beijing, China.
Xu FuBeihang University, Beijing, China.
Xiaochen WangBeijing Tian Tan Hospital, Beijing, China.
Sihui WangBeijing Tian Tan Hospital, Beijing, China.
Lingxu ChenBeijing Tian Tan Hospital, Beijing, China.
Mengyuan YuanBeijing Tian Tan Hospital, Beijing, China.
Jiangang LiuBeihang University, Beijing, China. jgliu@buaa.edu.cn.
Shengjun SunBeijing Tian Tan Hospital, Beijing, China. sunshengjun0212@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveAccurate preoperative predict the cell lineages of non-functioning pituitary neuroendocrine tumors (NFPitNETs) can help neurosurgeons develop treatment strategies. This study aimed to predict the three cell lineages of NFPitNETs using radiomics based on MRI.

methodsNFPitNETs patients from January 2019 and January 2023 were retrospectively enrolled, with adenoma lineages including SF-1 (n = 239), TPIT (n = 204), and PIT-1 (n = 100). Sagittal T1-weighted images (T1WI), contrast-enhanced (CE) sagittal T1WI, CE-coronal T1WI, and axial T2WI were obtained for tumor segmentation on ITK-SNAP. Pyradiomics was used for features extracted. Variance threshold method, t-test, and LASSO were used for feature selection. Support vector machine (SVM) and random forest (RF) were used to predict the three-lineages adenomas based on their radiomics and semantic features. Receiver operating characteristic curve-area under the curve (ROC-AUC) analysis was used to assess the model's performance.

resultsA total of 543 patients with NFPitNETs (mean age, 49.46 ± 12.39) were included. Patients with SF-1 adenomas had a higher mean age than those with TPIT and PIT-1 adenomas (52.84 ± 11.56 vs 49.94 ± 10.54 vs 40.42 ± 13.41, p < 0.001). Female patients are more common in TPIT and PIT-1 adenomas than SF-1 ones (96.57% vs 69% vs 41%, p < 0.001). The SVM model incorporating semantic and radiomics features based on CE-coronal T1WI performed the best, with a macro-average AUC of 0.899. CE-coronal T1WI were the best among all the MR sequences for predicting the cell lineages of NFPitNETs.

conclusionRadiomics based on preoperative MRI can help predict the cell lineages of NFPitNETs, which prove useful to neurosurgeons to develop treatment strategies.

Indexed as

Cell LineageMagnetic Resonance ImagingNeuroendocrine TumorsPituitary NeoplasmsAdultAgedContrast MediaFemaleHumansMaleMiddle AgedRadiomicsRetrospective StudiesContrast MediaCell lineageMagnetic resonance imagingNon-functioning pituitary neuroendocrine tumorsPituitary NeoplasmsRadiomics

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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.