Aibar-Durán Juan Ángel, Mirapeix Rosa M, Gallardo Alcañiz Alberto, Salgado-López Laura, Freixer-Palau Berta, Casitas Hernando Vicente, Hernández Fernando Muñoz, de Quintana-Schmidt Cristian
1Department of Neurosurgery, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain.
5Institut de Recerca de Sant Pau (IR Sant Pau), Barcelona, Spain; and.
J Neurosurg. 2025 Apr 18;143(2):323-331. doi: 10.3171/2024.12.JNS242496. Print 2025 Aug 1.
The primary goal in neuro-oncology is the maximally safe resection of high-grade glioma (HGG). A more extensive resection improves both overall and disease-free survival, while a complication-free surgery enables better tolerance to adjuvant therapies such as chemotherapy and radiotherapy. Techniques such as 5-aminolevulinic acid (5-ALA) fluorescence and intraoperative ultrasound (ioUS) are valuable for safe resection and cost-effective. However, the benefits of combining these techniques remain undocumented. The aim of this study was to investigate outcomes when combining 5-ALA and ioUS.
From January 2019 to January 2024, 72 patients (mean age 62.2 years, 62.5% male) underwent HGG resection at a single hospital. Tumor histology included glioblastoma (90.3%), grade IV astrocytoma (4.1%), grade III astrocytoma (2.8%), and grade III oligodendroglioma (2.8%). Tumor resection was performed under natural light, followed by using 5-ALA and ioUS to detect residual tumor. Biopsies from the surgical bed were analyzed for tumor presence and categorized based on 5-ALA and ioUS results. Results of 5-ALA and ioUS were classified into positive, weak/doubtful, or negative. Histological findings of the biopsies were categorized into solid tumor, infiltration, or no tumor. Sensitivity, specificity, and predictive values for both techniques, separately and combined, were calculated. A machine learning algorithm (HGGPredictor) was developed to predict tumor presence in biopsies.
The overall sensitivities of 5-ALA and ioUS were 84.9% and 76%, with specificities of 57.8% and 84.5%, respectively. The combination of both methods in a positive/positive scenario yielded the highest performance, achieving a sensitivity of 91% and specificity of 86%. The positive/doubtful combination followed, with sensitivity of 67.9% and specificity of 95.2%. Area under the curve analysis indicated superior performance when both techniques were combined, in comparison to each method used individually. Additionally, the HGGPredictor tool effectively estimated the quantity of tumor cells in surgical margins.
Combining 5-ALA and ioUS enhanced diagnostic accuracy for HGG resection, suggesting a new surgical standard. An intraoperative predictive algorithm could further automate decision-making.
神经肿瘤学的主要目标是最大程度安全地切除高级别胶质瘤（HGG）。更广泛的切除可提高总生存期和无病生存期，而无并发症的手术能使患者对化疗和放疗等辅助治疗有更好的耐受性。5-氨基乙酰丙酸（5-ALA）荧光和术中超声（ioUS）等技术对于安全切除很有价值且具有成本效益。然而，联合使用这些技术的益处尚无文献记载。本研究的目的是调查联合使用5-ALA和ioUS的效果。
2019年1月至2024年1月，72例患者（平均年龄62.2岁，62.5%为男性）在一家医院接受了HGG切除术。肿瘤组织学类型包括胶质母细胞瘤（90.3%）、IV级星形细胞瘤（4.1%）、III级星形细胞瘤（2.8%）和III级少突胶质细胞瘤（2.8%）。在自然光下进行肿瘤切除，随后使用5-ALA和ioUS检测残留肿瘤。对手术床的活检组织进行肿瘤存在情况分析，并根据5-ALA和ioUS结果进行分类。5-ALA和ioUS的结果分为阳性、弱阳性/可疑或阴性。活检组织的组织学结果分为实体瘤、浸润或无肿瘤。分别计算两种技术单独及联合使用时的敏感性、特异性和预测值。开发了一种机器学习算法（HGGPredictor）来预测活检组织中肿瘤的存在情况。
5-ALA和ioUS的总体敏感性分别为84.9%和76%，特异性分别为57.8%和84.5%。两种方法在阳性/阳性情况下联合使用时性能最佳，敏感性达到91%，特异性为86%。其次是阳性/可疑联合，敏感性为67.9%，特异性为95.2%。曲线下面积分析表明，与单独使用每种方法相比，两种技术联合使用时性能更优。此外，HGGPredictor工具有效地估计了手术切缘的肿瘤细胞数量。
联合使用5-ALA和ioUS可提高HGG切除的诊断准确性，提示一种新的手术标准。术中预测算法可进一步实现决策自动化。
