1.陆军军医大学大坪医院放射科,重庆
2.重庆市影像学与核医学临床研究中心,重庆
3.陆军军医大学大坪医院病理科,重庆
WANG Shunan,E-mail: wangshunan@tmmu.edu.cn
Received:30 September 2025,
Revised:2025-12-25,
Published:30 December 2025
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李轩,王瀚苇,曾琳岚,等.基于磁共振DSC-PWI构建的肿瘤血管生境对胶质母细胞瘤和单发脑转移瘤鉴别诊断效能的研究[J].陆军军医大学学报,2025,47(24):3102-3111.DOI:,10.16016/j.2097-0927.202509101.
LI X,WANG H W,ZENG L L,,et al.Differential diagnostic efficacy of tumor vascular habitats based on DSC-PWI between glioblastoma and solitary metastatic brain tumors[J].J Army Med Univ,2025,47(24):3102-3111.DOI:,10.16016/j.2097-0927.202509101.
李轩,王瀚苇,曾琳岚,等.基于磁共振DSC-PWI构建的肿瘤血管生境对胶质母细胞瘤和单发脑转移瘤鉴别诊断效能的研究[J].陆军军医大学学报,2025,47(24):3102-3111.DOI:,10.16016/j.2097-0927.202509101. DOI:
LI X,WANG H W,ZENG L L,,et al.Differential diagnostic efficacy of tumor vascular habitats based on DSC-PWI between glioblastoma and solitary metastatic brain tumors[J].J Army Med Univ,2025,47(24):3102-3111.DOI:,10.16016/j.2097-0927.202509101. DOI:
目的
2
探讨基于磁共振动态磁敏感对比增强灌注加权成像(dynamic susceptibility contrast-enhanced perfusion weighted imaging,DSC-PWI)构建的肿瘤血管生境特征参数对初诊胶质母细胞瘤(Glioblastoma,GBM)和单发脑转移瘤(solitary brain metastasis,SBM)的鉴别诊断价值。
方法
2
采用病例对照研究方法,回顾性分析中国人民解放军陆军特色医学中心放射科2019年1月至2025年3月期间经术后病理证实或临床综合诊断的109例恶性脑肿瘤患者(其中胶质母细胞瘤57例,单发脑转移瘤52例)的影像学资料。基于DSC-PWI图像,采用血流动力学组织特征(hemodynamic tissue signature,HTS)法分割病灶并构建4种肿瘤血管生境,分别为增强区高血管生境(high angiogenic tumor,HAT)、增强区低血管生境(low angiogenic tumor,LAT)、肿瘤浸润性水肿(potentially infiltrated peripheral edema,IPE)和瘤周血管源性水肿区(vasogenic peripheral edema,VPE)。计算各生境区域体积参数和血流参数,包括各生境区域体积、肿瘤核心体积、瘤周水肿体积和相对脑血容量值(relative cerebral blood volume,rCBV),比较两组患者基线资料和生境特征参数,绘制受试者工作特征(receiver operating characteristic,ROC)曲线评估鉴别诊断效能。运用Pearson相关性分析判断各生境特征参数间的相关性以量化各生境间的空间相互作用。
结果
2
胶质母细胞瘤组HAT、LAT、IPE、VPE四种生境区域的rCBV中位值(rCBV
median
)分别为6.143±1.687(95%
CI
:5.695~6.591)、3.249±0.988(95%
CI
:2.987~3.511)、1.913(1.578,2.588)(95%
CI
:1.794~2.110)、0.836(0.676,1.110)(95%
CI
:0.710~0.949)。均高于单发脑转移瘤组的rCBV
median
值[4.634±1.647(95%
CI
:4.175~5.092)、2.255±0.807(95%
CI
:2.031~2.480)、1.291(1.022,1.767)(95%
CI
:1.125~1.677)、0.600(0.459,0.742)(95%
CI
:0.519~0.682)](
P
<
0.001)。经ROC曲线分析,LAT中rCBV
median
值具有良好的鉴别诊断效能,其AUC值为0.792(95%
CI
:0.704~0.864),最佳截断值为2.660(敏感性:75.44%,特异性:78.85%),(
P
<
0.001)。胶质母细胞瘤组IPE体积与瘤周体积比(
V
(IPE)
/
V
(P)
)为0.216(0.101,0.351)(95%
CI
:0.165~0.267),高于单发脑转移瘤组0.079(0.055,0.153)(95%
CI
:0.066~0.102)(
P
<
0.001)。经ROC曲线分析,
V
(IPE)
/
V
(P)
具有良好的鉴别诊断效能,AUC值为0.765(95%
CI
:0.674~0.840),最佳截断值为0.122(敏感性:71.93%,特异性:73.08%),(
P
<
0.001)。Pearson相关性分析显示,GBM组IPE-rCBV
median
和VPE-rCBV
median
与HAT-rCBV
median
间的相关系数分别为0.620(
P
<
0.01)、0.283(
P
=0.033),呈显著正相关。
结论
2
基于磁共振DSC-PWI构建的肿瘤血管生境特征参数在初诊GBM和SBM中差异明显,其体积特征参数
V
(IPE)
/
V
(P)
和血流特征参数LAT-rCBV
median
均具有较好的鉴别诊断效能,可作为两者鉴别诊断的影像学标记。
Objective
2
To investigate the value of tumor vascular habitat characteristic parameters constructed based on dynamic susceptibility contrast-enhanced perfusion-weighted imaging (DSC-PWI) in differentiating between newly diagnosed glioblastoma (GBM) and solitary brain metastasis (SBM).
Methods
2
A case-control study design was adopted to analyze the imaging data of 109 patients with malignant brain tumors (including 57 cases of GBM and 52 cases of SBM) confirmed by postoperative pathology or comprehensive clinical diagnosis retrospectively collected from Department of Radiology of Daping Hospital between January 2019 and March 2025. Based on DSC-PWI images
hemodynamic tissue signature (HTS) was used to segment the lesions and construct 4 tumor vascular habitats
that is
high angiogenic tumor (HAT)
low angiogenic tumor (LAT)
potentially infiltrated peripheral edema (IPE)
and vasogenic peripheral edema (VPE). Volume parameters and blood flow parameters for each habitat region were calculated
including volume of each habitat region
tumor core volume
peritumoral edema volume
and relative cerebral blood volume (rCBV). Baseline data and habitat characteristic parameters were compared between the 2 groups. Receiver operating characteristic (ROC) curves were drawn to evaluate the differential diagnostic efficacy. Pearson correlation analysis was performed to assess the correlations among habitat characteristic parameters to quantify the spatial interactions between habitats.
Results
2
In the GBM group
the median rCBV (rCBV
median
) at HAT
LAT
IPE
and VPE habitats were 6.143±1.687 (95%
CI
: 5.695~6.591)
3.249±0.988 (95%
CI
: 2.987~3.511)
1.913 (1.578
2.588) (95%
CI
: 1.794~2.110) and 0.836 (0.676
1.110) (95%
CI
: 0.710~0.949)
respectively. These values were all significantly higher than the rCBV
median
at above habitats in the SBM group [4.634±1.647 (95%
CI
: 4.175~5.092)
2.255±0.807 (95%
CI
: 2.031~2.480)
1.291 (1.022
1.767) (95%
CI
: 1.125~1.677)
0.600 (0.459
0.742) (95%
CI
: 0.519~0.682);
P
<
0.001
]
. ROC curve analysis showed that the rCBV
median
at LAT habitat had good diagnostic efficacy for differentiation
with an AUC value of 0.792 (95%
CI
: 0.704~0.864) (
P
<
0.001). The optimal cutoff value of rCBV
median
at LAT habitat was 2.660 (sensitivity: 75.44%
specificity: 78.85%). The ratio of IPE volume to peritumoral volume (
V
(IPE)
/
V
(P)
) in the GBM group was 0.216 (0.101
0.351) (95%
CI
: 0.165~0.267)
notably higher than that in the SBM group [0.079 (0.055
0.153) (95%
CI
: 0.066~0.102)
P
<
0.001
]
. ROC curve analy
sis indicated that
V
(IPE)
/
V
(P)
ratio had good diagnostic efficacy
with an AUC value of 0.765 (95%
CI
: 0.674~0.840). The optimal cutoff value of the ratio was 0.122 (sensitivity: 71.93%
specificity: 73.08%). Pearson correlation analysis suggested that in the GBM group
the correlation coefficients between IPE-rCBV
median
and HAT-rCBV
median
and between VPE-rCBV
median
and HAT-rCBV
median
were 0.620 (
P
<
0.01) and 0.283 (
P
=0.033)
respectively
indicating significant positive correlations.
Conclusion
2
DSC-PWI-based vascular habitat characteristic parameters show significant differences between newly diagnosed GBM and SBM. Both the volumetric parameter
V
(IPE)
/
V
(P)
ratio and the hemodynamic parameter LAT-rCBV
median
have good differential diagnostic efficacy
and can serve as imaging markers for distinguishing between GBM and SBM.
STUPP R , MASON W P , VAN DEN BENT M J , et al . Radiotherapy plus concomitant and adjuvant temozolomide for glioblastoma [J]. N Engl J Med , 2005 , 352 ( 10 ): 987 - 996 . DOI: 10.1056/NEJMoa043330 http://dx.doi.org/10.1056/NEJMoa043330 .
VOGELBAUM M A , BROWN P D , MESSERSMITH H , et al . Treatment for brain metastases: ASCO-SNO-ASTRO guideline [J]. J Clin Oncol , 2022 , 40 ( 5 ): 492 - 516 . DOI: 10.1200/JCO.21.02314 http://dx.doi.org/10.1200/JCO.21.02314 .
APARICI-ROBLES F , DAVIDHI A , CAROT-SIERRA J M , et al . Glioblastoma versus solitary brain metastasis: MRI differentiation using the edema perfusion gradient [J]. J Neuroimaging , 2022 , 32 ( 1 ): 127 - 133 . DOI: 10.1111/jon.12920 http://dx.doi.org/10.1111/jon.12920 .
李锐 , 吴冰 , 王玉林 , 等 . 氨基质子转移成像在鉴别脑内转移瘤和高级别胶质瘤中的应用价值 [J]. 第三军医大学学报 , 2016 , 38 ( 22 ): 2388 - 2392 . DOI: 10.16016/j.1000-5404.201606132 http://dx.doi.org/10.16016/j.1000-5404.201606132 .
LI R , WU B , WANG Y L , et al . Application value of amide proton transfer imaging in differential diagnosis of brain metastasis and high grade glioma [J]. J Third Mil Med Univ , 2016 , 38 ( 22 ): 2388 - 2392 . DOI: 10.16016/j.1000-5404.201606132 http://dx.doi.org/10.16016/j.1000-5404.201606132 .
PONS-ESCODA A , GARCIA-RUIZ A , NAVAL-BAUDIN P , et al . Voxel-level analysis of normalized DSC-PWI time-intensity curves: a potential generalizable approach and its proof of concept in discriminating glioblastoma and metastasis [J]. Eur Radiol . 2022 , 32 ( 6 ): 3705 - 3715 . DOI: 10.1007/s00330-021-08498-1 http://dx.doi.org/10.1007/s00330-021-08498-1 .
HEYNOLD E , ZIMMERMANN M , HORE N , Buchfelder M , et al . Physiological MRI Biomarkers in the Differentiation Between Glioblastomas and Solitary Brain Metastases [J]. Mol Imaging Biol . 2021 , 23 ( 5 ): 787 - 795 . DOI: 10.1007/s11307-021-01604-1 http://dx.doi.org/10.1007/s11307-021-01604-1 .
JUAN-ALBARRACÍN J , FUSTER-GARCIA E , PÉREZ-GIEBÉS A , et al . Glioblastoma: Vascular Habitats Detected at Preoperative Dynamic Susceptibility-weighted Contrast-enhanced Perfusion MR Imaging Predict Survival [J]. Radiology . 2018 Jun ; 287 ( 3 ): 944 - 954 . DOI: 10.1148/radiol.2017170845 http://dx.doi.org/10.1148/radiol.2017170845 .
NAPEL S , MU W , JARDIM-PERASSI B V , et al . Quantitative imaging of cancer in the postgenomic era: Radio(geno)mics, deep learning, and habitats [J]. Cancer , 2018 , 124 ( 24 ): 4633 - 4649 . DOI: 10.1002/cncr.31630 http://dx.doi.org/10.1002/cncr.31630 .
BLYSTAD I , MARCEL WARNTJES J B , SMEDBY Ö , et al . Quantitative MRI for analysis of peritumoral edema in malignant gliomas [J]. PLoS One , 2017 , 12 ( 5 ): e0177135 . DOI: 10.1371/journal.pone.0177135 http://dx.doi.org/10.1371/journal.pone.0177135 .
TRAN T T , MAHAJAN A , CHIANG V L , et al . Perilesional edema in brain metastases: potential causes and implications for treatment with immune therapy [J]. J Immunother Cancer , 2019 , 7 ( 1 ): 200 . DOI: 10.1186/s40425-019-0684-z http://dx.doi.org/10.1186/s40425-019-0684-z .
宋珍珍 , 孙小玲 , 李海鸥 , 等 . 120例胶质瘤及瘤周水肿MRI影像组学在评估肿瘤复发中的价值 [J]. 山东大学学报(医学版) , 2021 , 59 ( 11 ): 53 - 60 . DOI: 10.6040/j.issn.1671-7554.0.2021.0997 http://dx.doi.org/10.6040/j.issn.1671-7554.0.2021.0997 .
SONG Z Z , SUN X L , LI H O , et al . Value of MRI radiomics of glioma and peritumoral edema in evaluating tumor recurrence [J]. J Shandong Univ Health Sci , 2021 , 59 ( 11 ): 53 - 60 . DOI: 10.6040/j.issn.1671-7554.0.2021.0997 http://dx.doi.org/10.6040/j.issn.1671-7554.0.2021.0997 .
WANG H W , ZENG L L , WU H , et al . Preoperative vascular heterogeneity based on dynamic susceptibility contrast MRI in predicting spatial pattern of locally recurrent high-grade gliomas [J]. Eur Radiol , 2024 , 34 ( 3 ): 1982 - 1993 . DOI: 10.1007/s00330-023-10149-6 http://dx.doi.org/10.1007/s00330-023-10149-6 .
ASKANER K , RYDELIUS A , ENGELHOLM S , et al . Differentiation between glioblastomas and brain metastases and regarding their primary site of malignancy using dynamic susceptibility contrast MRI at 3T [J]. J Neuroradiol , 2019 , 46 ( 6 ): 367 - 372 . DOI: 10.1016/j.neurad. 2018. 09.006 http://dx.doi.org/10.1016/j.neurad.2018.09.006 .
ÁLVAREZ-TORRES M D M , FUSTER-GARCÍA E , JUAN-ALBARRACÍN J , et al . Local detection of microvessels in IDH-wildtype glioblastoma using relative cerebral blood volume: an imaging marker useful for astrocytoma grade 4 classification [J]. BMC Cancer , 2022 , 22 ( 1 ): 40 . DOI: 10.1186/s12885-021-09117-4 http://dx.doi.org/10.1186/s12885-021-09117-4 .
姜新雅 , 仇斌 , 王维 . 星形细胞瘤相对脑血容量与肿瘤血管生成的相关性研究 [J]. 中国医学影像技术 , 2006 , 22 ( 3 ): 401 - 404 . DOI: 10.13929/j.1003-3289.2006.03.028 http://dx.doi.org/10.13929/j.1003-3289.2006.03.028 .
JIANG X Y , QIU B , WANG W . Correlation of relative cerebral blood volume with tumor angiogenesis in astrocytomas [J]. Chin J Med Imag Technol , 2006 , 22 ( 3 ): 401 - 404 . DOI: 10.13929/j.1003-3289.2006.03.028 http://dx.doi.org/10.13929/j.1003-3289.2006.03.028 .
LEMÉE J M , CLAVREUL A , MENEI P . Intratumoral heterogeneity in glioblastoma: don’t forget the peritumoral brain zone [J]. Neuro Oncol , 2015 , 17 ( 10 ): 1322 - 1332 . DOI: 10.1093/neuonc/nov119 http://dx.doi.org/10.1093/neuonc/nov119 .
MAO J J , ZENG W K , ZHANG Q Y , et al . Differentiation between high-grade gliomas and solitary brain metastases: a comparison of five diffusion-weighted MRI models [J]. BMC Med Imaging , 2020 , 20 ( 1 ): 124 . DOI: 10.1186/s12880-020-00524-w http://dx.doi.org/10.1186/s12880-020-00524-w .
KADOTA Y , HIRAI T , AZUMA M , et al . Differentiation between glioblastoma and solitary brain metastasis using neurite orientation dispersion and density imaging [J]. J Neuroradiol , 2020 , 47 ( 3 ): 197 - 202 . DOI: 10.1016/j.neurad.2018.10.005 http://dx.doi.org/10.1016/j.neurad.2018.10.005 .
ZHU Y Y , WANG J , XUE C , et al . Deep learning and habitat radiomics for the prediction of glioma pathology using multiparametric MRI: a multicenter study [J]. Acad Radiol , 2025 , 32 ( 2 ): 963 - 975 . DOI: 10.1016/j.acra.2024.09.021 http://dx.doi.org/10.1016/j.acra.2024.09.021 .
EUN P , SUNG K , KIM N , et al . Spatiotemporal heterogeneity in multiparametric physiologic MRI is associated with patient outcomes in IDH-wildtype glioblastoma [J]. Clin Cancer Res , 2021 , 27 ( 1 ): 237 - 245 . DOI: 10.1158/1078-0432.CCR-20-2156 http://dx.doi.org/10.1158/1078-0432.CCR-20-2156 .
HYEON M , EUN P , KIM N , et al . Prospective longitudinal analysis of imaging-based spatiotemporal tumor habitats in glioblastoma, IDH-wild type: implication in patient outcome using multiparametric physiologic MRI [J]. BMC Cancer , 2024 , 24 ( 1 ): 1197 . DOI: 10.1186/s12885-024-12939-7 http://dx.doi.org/10.1186/s12885-024-12939-7 .
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