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DOI 10.21037/qims-2025-1249

Медицинская библиотека · Quantitative imaging in medicine and surgery · 2026

Magnetic resonance imaging characteristics of brain metastases from lung cancer.

Sui Lian-Yu, Xing Li-Hong, Meng Huan, Zhang Yu, Liu Chong, Wang Qi, Wang Jia-Ning, Yin Xiao-Ping

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Аннотация

BACKGROUND

One of the most common primary tumor sources of brain metastases (BMs) is lung cancer. As certain magnetic resonance imaging (MRI) features overlap between the pathological and genetic subtypes of lung cancer BMs, directly determining the primary site based on these features remains a challenge. Thus, identifying the MRI features of different subtypes of lung cancer BMs is crucial in order to facilitate early diagnosis and treatment. This study aimed to characterize the MRI characteristics distinct to the various subtypes of lung cancer BMs in order to inform clinical decision-making.

METHODS

Data from 1,129 patients diagnosed with lung cancer BMs (a total of 8,312 lesions) from three institutions, including clinicopathological information and MRI features, were retrospectively analyzed. Among these cases of BMs, 369 (2,780 lesions) originated from small-cell lung cancer (SCLC) and 760 (5,532 lesions) from non-small cell lung cancer (NSCLC). Among the patients with NSCLC, there were 689 cases (5,243 lesions) of adenocarcinoma (AD) and 71 cases (289 lesions) of squamous cell carcinoma (SCC). Regarding epidermal growth factor receptor (EGFR) status, there were 188 wild-type cases (1,257 lesions) and 344 mutant-type cases (2,880 lesions). This study was divided into three parts. For Part I (comparison between SCLC and NSCLC), Part II (comparison between AD and SCC), and Part III (comparison between EGFR wild type and mutant type), a stepwise in-depth analysis was performed-from the level of pathological classification to the level of gene mutation status-of the clinical characteristics of patients with lung cancer BMs and of the quantity, size, location, and signal characteristics of BMs lesions based on brain MRI. According to different signal combinations of DWI and CE-T1WI, the BMs lesions were divided into seven patterns, namely Pattern I-VII: Pattern I: DWI-negative + CE-T1WI-positive; Pattern II: DWI-negative + CE-T1WI ring; Pattern III: DWI-positive + CE-T1WI-positive; Pattern IV: DWI ring + CE-T1WI-positive; Pattern V: DWI-positive + CE-T1WI ring; Pattern VI: DWI ring + CE-T1WI ring; Pattern VII: DWI-positive + CE-T1WI-negative. "Positive" indicates homogeneous hyperintensity on DWI or CE-T1WI, while "negative" indicates hypointensity or isointensity on DWI or CE-T1WI, and "ring" refers to ring enhancement.

RESULTS

In the Part I analysis, SCLC BMs tended to be multiple (>10 lesions; 0.5-1 cm in size), occur in the frontal/parietal lobes and periventricular regions, and have higher proportions of patterns consisting of diffusion-weighted imaging (DWI)-positive plus contrast-enhanced T1-weighted imaging (CE-T1WI) ring features, DWI ring plus CE-T1WI ring features, and DWI-positive plus C E-T1WI-negative features (all P values <0.05). NSCLC BMs had higher proportions of patterns consisting of DWI-negative plus CE-T1WI-positive features and DWI ring plus CE-T1WI-positive features (P<0.05). In the Part II analysis, as compared to AD BMs, SCC BMs have more peritumoral edema, and occur in the centrum semiovale, with higher proportions of patterns consisting of DWI ring plus CE-T1WI ring features and DWI-positive plus CE-T1WI-negative features (P<0.05). EGFR mutant-type BMs tended to be multiple (>10 lesions; <1 cm in size) and have less hemorrhage compared to wild-type BMs (P>0.05). DWI hyperintensity without CE-T1WI enhancement was more common in SCLC BMs than in NSCLC BMs (20.6% vs. 4.5%; P<0.001) and in SCC BMs than in AD BMs (33.9% vs. 2.8%; P<0.001).

CONCLUSIONS

MRI and clinical features may provide the ability to noninvasively distinguish between SCLC and NSCLC and between AD and SCC, as well as to partially indicate EGFR status. DWI hyperintensity without CE-T1WI enhancement might serve as a key subtype-specific feature that could aid in clinical decision-making.

Для цитирования: Sui Lian-Yu, Xing Li-Hong, Meng Huan, Zhang Yu, Liu Chong, Wang Qi, Wang Jia-Ning, Yin Xiao-Ping. Magnetic resonance imaging characteristics of brain metastases from lung cancer.. Quantitative imaging in medicine and surgery. 2026. DOI: 10.21037/qims-2025-1249.
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