Pomohaci Daniela, Marciuc Emilia Adriana, Dobrovăț Bogdan-Ionuț, Popescu Mihaela-Roxana, Ilinca Diana-Andreea, Chirica Costin, Oniciuc Onicescu Oriana-Maria, Haba Danisia
General and Dental Radiology, Faculty of Medicine, Grigore T Popa University of Medicine and Pharmacy, Iasi, Romania.
Radiology Department, Emergency Hospital Prof Dr Nicolae Oblu, Iasi, Romania.
J Med Life. 2025 Jun;18(6):563-574. doi: 10.25122/jml-2024-0411.
Brain metastases (BMs) from bronchopulmonary tumors are a major cause of morbidity and mortality and significantly reduce the quality of life in oncology patients. Their treatment depends on imaging features (size, number, location) and their genetic mutation subtype, small-cell lung cancer (SCLC) or non-small cell lung cancer (NSCLC). In patients with SCLC, prophylactic whole-brain radiotherapy (WBRT) with hippocampal sparing (HS) is recommended, whereas in patients with NSCLC, systemic targeted therapy is preferred. Multiple studies have analyzed the MRI morphology of BMs from both SCLC and NSCLC to identify specific imaging characteristics that can guide the selection of appropriate treatment. However, data on lung cancer (LC) brain metastases in patients from Romania are scarce or nonexistent. Our purpose was to investigate the imaging features of both NSCLC and SCLC BMs in our population using conventional MRI protocols. We selected patients from our hospital between 2019 and 2023 who had a histopathological diagnosis of LC BMs and underwent complete MRI exams prior to any radiotherapy or surgical treatment. For every MRI feature, we created both numerical and categorical variables, which were further studied using univariate, bivariate, and multivariate analyses, as well as a machine learning algorithm. We found 62 patients (49 men, 79.03% and 13 women, 20.96%) with confirmed LC BMs, of which 53 (85.49%) had NSCLC and 7 (11.29%) had SCLC. The sites affected were the cerebral hemisphere (56.46%), the cerebellum (40.32%), and the deep nuclei (6.45%), with the latter affecting relatively younger patients ( = 0.01), most notably in the case of thalamic situs ( = 0.0001). The SCLC subgroup showed a value of 0.025 for the number of lesions, indicating diffuse spread. The AI algorithm identified positive and negative imaging diagnostic prediction variables, including internal vascularization and the number of lesions, respectively, as well as cystic lesions and internal hemorrhage. Further multicentric studies are needed to unravel the MRI features of LC BMs.
支气管肺肿瘤的脑转移(BMs)是导致发病和死亡的主要原因,显著降低了肿瘤患者的生活质量。其治疗取决于影像学特征(大小、数量、位置)及其基因突变亚型,即小细胞肺癌(SCLC)或非小细胞肺癌(NSCLC)。对于SCLC患者,推荐采用海马体保护(HS)的预防性全脑放疗(WBRT),而对于NSCLC患者,则优先选择全身靶向治疗。多项研究分析了SCLC和NSCLC脑转移的MRI形态,以确定可指导选择合适治疗方法的特定影像学特征。然而,罗马尼亚患者肺癌(LC)脑转移的数据稀缺或不存在。我们的目的是使用传统MRI协议研究我们人群中NSCLC和SCLC脑转移的影像学特征。我们选取了2019年至2023年间我院经组织病理学诊断为LC脑转移且在任何放疗或手术治疗前接受了完整MRI检查的患者。对于每个MRI特征,我们创建了数值变量和分类变量,并使用单变量、双变量和多变量分析以及机器学习算法对其进行进一步研究。我们发现62例确诊为LC脑转移的患者(49例男性,占79.03%;13例女性,占20.96%),其中53例(85.49%)为NSCLC,7例(11.29%)为SCLC。受累部位为大脑半球(56.46%)、小脑(40.32%)和深部核团(6.45%),后者影响相对年轻的患者(P = 0.01),在丘脑部位尤为明显(P = 0.0001)。SCLC亚组的病灶数量P值为0.025,表明为弥漫性扩散。人工智能算法确定了阳性和阴性影像学诊断预测变量,分别包括内部血管形成和病灶数量,以及囊性病灶和内部出血。需要进一步开展多中心研究来阐明LC脑转移的MRI特征。