Preoperative assessment of tumor consistency and gross total resection in pituitary adenoma: Radiomic analysis of T2-weighted MRI and interpretation of contributing radiomic features

IF 1.9 Q3 CLINICAL NEUROLOGY

Brain & spine Pub Date : 2025-01-01 DOI:10.1016/j.bas.2025.104237

Martin Černý , Vojtěch Sedlák , Martin Májovský , Petr Vacek , Kateřina Sajfrídová , Kíra R. Patai , Alexia-Ştefana Mârza , David Netuka

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Abstract

Background

Preoperative knowledge of tumor consistency and the likelihood of gross total resection (GTR) would greatly benefit planning of pituitary adenoma surgery, however, no reliable methods currently exist.

Objectives

To evaluate the utility of radiomic analysis of MRI for predicting tumor consistency and GTR. To explore the interpretability of contributing radiomic features.

Methods

Patients undergoing first endoscopic surgery for pituitary macroadenomas were included. Tumor consistency was assessed intraoperatively, GTR was assessed based on postoperative MRI. Radiomic features were extracted from axial T2-weighted MRI. Low-variability and highly intercorrelated features were removed. Random Forest Classifiers were optimized using 70 % of patient data and evaluated on the remaining 30 %. Relative feature importance was assessed using the Gini–Simpson index.

Results

542 patients were included. GTR was achieved in 325 (60.0 %) cases, firm tumors were encountered in 122 (22.5 %) cases. There was a significant correlation between GTR and tumor consistency (67.1 % vs. 35.2 %, p < 0.001). 1688 radiomic variables were extracted, 442 were removed due to low variance and 699 due to high intercorrelation. The consistency prediction model achieved an accuracy of 81.6 % and utilized 32 features, GTR prediction model achieved 79.1 % accuracy using 73 features.

Conclusions

Radiomic analysis demonstrated significant potential for preoperative evaluation of pituitary adenomas. Texture and intensity-based features were the primary contributors to consistency prediction. However, the explanation of these features was insufficient. GTR prediction was predominantly driven by shape-related features. Our findings highlight the challenges of linking radiomic features to underlying tissue properties and emphasize the need for cautious interpretation.

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垂体腺瘤肿瘤一致性和大体全切除的术前评估：t2加权MRI放射学分析及相关放射学特征的解释

术前了解肿瘤一致性和大体全切除（GTR）的可能性将极大地有利于垂体腺瘤手术的规划，然而，目前还没有可靠的方法。目的评价MRI放射组学分析在预测肿瘤一致性和GTR中的应用价值。探讨贡献放射学特征的可解释性。方法选取首次行内窥镜手术的垂体大腺瘤患者。术中评估肿瘤一致性，术后MRI评估GTR。从轴向t2加权MRI提取放射学特征。低变异性和高度相互关联的特征被去除。随机森林分类器使用70%的患者数据进行优化，并对剩余的30%进行评估。使用基尼-辛普森指数评估相对特征重要性。结果共纳入542例患者。325例（60.0%）患者实现GTR， 122例（22.5%）患者出现硬瘤。GTR与肿瘤一致性有显著相关性(67.1% vs. 35.2%, p <；0.001)。共提取了1688个放射组学变量，其中442个因方差小而被剔除，699个因相关性高而被剔除。一致性预测模型使用32个特征，准确率达到81.6%，GTR预测模型使用73个特征，准确率达到79.1%。结论放射组学分析对垂体腺瘤的术前评估具有重要意义。纹理和基于强度的特征是一致性预测的主要贡献者。然而，对这些特征的解释是不够的。GTR预测主要由形状相关特征驱动。我们的发现强调了将放射学特征与潜在组织特性联系起来的挑战，并强调了谨慎解释的必要性。

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