使用交互式深度学习和DTI生物标志物检测肿瘤周围水肿的胶质母细胞瘤浸润:通过立体定向活检进行检测。

IF 3.5 2区 医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Jiaqi Tu, Chuyun Shen, Jianpeng Liu, Bin Hu, Zecheng Chen, Yijiu Yan, Chao Li, Ji Xiong, Alex Michel Daoud, Xiangfeng Wang, Yuxin Li, Fengping Zhu
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引用次数: 0

摘要

背景:显微镜下肿瘤细胞浸润超出对比增强区影响胶质母细胞瘤的预后,但常规MRI无法检测到。目的:开发和评估胶质母细胞瘤浸润区交互检测框架(GIAIDF),这是一个集成扩散张量成像(DTI)生物标志物的交互式深度学习框架,用于识别肿瘤周围水肿的微观浸润。研究类型:回顾性。人群:来自中心1的73例训练患者(51.13±13.87岁;47 M/26F)和25例内部验证患者(52.82±10.76岁;14 M/11F);2中心外部验证患者25例(47.29±11.39岁;16 M/9F);1中心前瞻性活检患者13例(45.62±9.28岁;8 M/5F)。磁场强度/序列:3.0 T MRI包括三维超声造影t1布拉沃序列(重复时间= 7.8 ms,回波时间= 3.0毫秒,反转时间= 450毫秒,切片厚度= 1毫米),三维t2加权fluid-attenuated反转恢复(重复时间= 7000毫秒,回波时间= 120毫秒,反转时间= 2000毫秒,切片厚度= 1毫米),和扩散张量成像(重复时间= 8500毫秒,回波时间= 63毫秒,切片厚度= 2毫米)。评价:以25例立体定向活检标本的组织病理学作为参考标准。主要指标包括AUC、准确性、敏感性和特异性。使用Ratio-FAcpcic(0.16-0.22)作为交互先验,将GIAIDF热图与活检轨迹共同注册。统计检验:AUC采用DeLong法进行ROC分析;预测验证的召回率、精度和F1分数。结果:GIAIDF内部验证(n = 25)的召回率= 0.800±0.060,精密度= 0.915±0.057,F1 = 0.852±0.044;外部验证(n = 25)的召回率= 0.778±0.053,精密度= 0.890±0.051,F1 = 0.829±0.040。在13例行立体定向活检的患者中,分析了25例ed周围标本,其中18例无肿瘤细胞浸润,7例有浸润,AUC = 0.929 (95% CI: 0.804-1.000),敏感性= 0.714,特异性= 0.944,准确性= 0.880。浸润部位的风险评分明显高于非浸润部位(0.549±0.194 vs. 0.205±0.175),p数据结论:本研究为基于术前MR图像识别ed周围区域内GBM浸润区域提供了一种潜在的工具GIAIDF。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Detection of Microscopic Glioblastoma Infiltration in Peritumoral Edema Using Interactive Deep Learning With DTI Biomarkers: Testing via Stereotactic Biopsy.

Background: Microscopic tumor cell infiltration beyond contrast-enhancing regions influences glioblastoma prognosis but remains undetectable using conventional MRI.

Purpose: To develop and evaluate the glioblastoma infiltrating area interactive detection framework (GIAIDF), an interactive deep-learning framework that integrates diffusion tensor imaging (DTI) biomarkers for identifying microscopic infiltration within peritumoral edema.

Study type: Retrospective.

Population: A total of 73 training patients (51.13 ± 13.87 years; 47 M/26F) and 25 internal validation patients (52.82 ± 10.76 years; 14 M/11F) from Center 1; 25 external validation patients (47.29 ± 11.39 years; 16 M/9F) from Center 2; 13 prospective biopsy patients (45.62 ± 9.28 years; 8 M/5F) from Center 1.

Field strength/sequences: 3.0 T MRI including three-dimensional contrast-enhanced T1-weighted BRAVO sequence (repetition time = 7.8 ms, echo time = 3.0 ms, inversion time = 450 ms, slice thickness = 1 mm), three-dimensional T2-weighted fluid-attenuated inversion recovery (repetition time = 7000 ms, echo time = 120 ms, inversion time = 2000 ms, slice thickness = 1 mm), and diffusion tensor imaging (repetition time = 8500 ms, echo time = 63 ms, slice thickness = 2 mm).

Assessment: Histopathology of 25 stereotactic biopsy specimens served as the reference standard. Primary metrics included AUC, accuracy, sensitivity, and specificity. GIAIDF heatmaps were co-registered to biopsy trajectories using Ratio-FAcpcic (0.16-0.22) as interactive priors.

Statistical tests: ROC analysis (DeLong's method) for AUC; recall, precision, and F1 score for prediction validation.

Results: GIAIDF demonstrated recall = 0.800 ± 0.060, precision = 0.915 ± 0.057, F1 = 0.852 ± 0.044 in internal validation (n = 25) and recall = 0.778 ± 0.053, precision = 0.890 ± 0.051, F1 = 0.829 ± 0.040 in external validation (n = 25). Among 13 patients undergoing stereotactic biopsy, 25 peri-ED specimens were analyzed: 18 without tumor cell infiltration and seven with infiltration, achieving AUC = 0.929 (95% CI: 0.804-1.000), sensitivity = 0.714, specificity = 0.944, and accuracy = 0.880. Infiltrated sites showed significantly higher risk scores (0.549 ± 0.194 vs. 0.205 ± 0.175 in non-infiltrated sites, p < 0.001).

Data conclusion: This study has provided a potential tool, GIAIDF, to identify regions of GBM infiltration within areas of peri-ED based on preoperative MR images.

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来源期刊
CiteScore
9.70
自引率
6.80%
发文量
494
审稿时长
2 months
期刊介绍: The Journal of Magnetic Resonance Imaging (JMRI) is an international journal devoted to the timely publication of basic and clinical research, educational and review articles, and other information related to the diagnostic applications of magnetic resonance.
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