Imaging the WHO 2021 Brain Tumor Classification: Fully Automated Analysis of Imaging Features of Newly Diagnosed Gliomas.
Imaging the WHO 2021 Brain Tumor Classification: Fully Automated Analysis of Imaging Features of Newly Diagnosed Gliomas.
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随着2021年WHO第五次CNS肿瘤分类的发布，基于生物学的肿瘤分类将进一步推进，并将分子特征加入诊断中。这既为长期以来基于影像学特征和组织学标准的对应性的放射学诊断带来了挑战，也开辟了新的机会。在这项工作中，使用先进的成像和基于AI的图像处理新诊断的成人胶质瘤患者（n = 226）具有广泛的分子特征，在分子定义的胶质瘤亚组之间的生物MR成像指标的显着差异被证明。特别是，与“经典”胶质母细胞瘤（IDH野生型）（WHO CNS 4级）和星形细胞瘤（IDH突变体，1 p/19 q非共缺失）（WHO CNS 4级）相比，具有胶质母细胞瘤（现在被认为是胶质母细胞瘤，WHO CNS 4级）分子特征的弥漫性胶质瘤（IDH野生型）显示出更高的灌注以及增加的细胞密度。我们的研究结果增加了相关的新兴图片，精细的肿瘤分级是可能的部分可视化肿瘤生物学与先进的MRI。 背景资料：2021年世界卫生组织（WHO）第五版中枢神经系统（CNS）肿瘤分类带来实质性变化。在分子表征的增强实施的驱动下，一些诊断被调整，而另一些则是新引入的。这些变化如何反映在影像学特征仍然很少调查。材料与方法：我们回顾性分析了来自我们机构的226例未经治疗的原发性脑肿瘤患者，这些患者通过表观基因组甲基化微阵列进行了广泛的分子表征，并根据2021年WHO脑肿瘤分类进行了诊断。从多模态术前3 T MRI扫描中，我们通过全自动的基于AI的图像分割和处理管道提取成像指标。随后，我们研究了三种主要胶质瘤实体（胶质母细胞瘤，星形细胞瘤和少突胶质细胞瘤）之间的影像学特征差异，并特别研究了新的实体，如星形细胞瘤，WHO 4级。结果如下：我们的研究结果证实了先前的研究，发现胶质母细胞瘤的对比增强区域的中位CBV（p = 0.00003，ANOVA）显著高于星形细胞瘤和少突胶质细胞瘤（p = 0.41333，ANOVA）。有趣的是，分子定义的胶质母细胞瘤，通常不包含对比增强区域，也显示出显着更高的CBV值在非增强肿瘤比常见的胶质母细胞瘤和星形细胞瘤4级（p = 0.01309，ANOVA）。结论：根据2021年新的WHO CNS肿瘤分类，这项工作为胶质瘤的影像学特征提供了广泛的见解。先进的成像技术在可视化肿瘤生物学和改善脑肿瘤患者的诊断方面显示出了希望。
With the release of the fifth WHO classification for CNS tumors in 2021, biology-based tumor classification is further advanced with the addition of molecular characteristics into diagnosis. This both poses challenges as well as opens up new opportunities for radiological diagnosis, which was long based on the correspondence of imaging features and histological criteria. In this work, using advanced imaging and AI-based image processing on newly-diagnosed adult glioma patients (n = 226) with extensive molecular characterization, significant differences in biological MR imaging metrics among molecularly defined glioma subgroups were demonstrated. In particular, diffuse glioma (IDH wild type) with molecular characteristics of glioblastoma (now recognized as glioblastoma, WHO CNS grade 4) showed higher perfusion as well as increased cell density compared to “classical” glioblastoma (IDH wild type), WHO CNS grade 4, and astrocytoma (IDH mutant, 1p/19q non-codeleted), WHO CNS grade 4. Our results add relevantly to the emerging picture that fine tumor grading is possible in part by visualization of tumor biology with advanced MRI. Background: The fifth version of the World Health Organization (WHO) classification of tumors of the central nervous system (CNS) in 2021 brought substantial changes. Driven by the enhanced implementation of molecular characterization, some diagnoses were adapted while others were newly introduced. How these changes are reflected in imaging features remains scarcely investigated. Materials and Methods: We retrospectively analyzed 226 treatment-naive primary brain tumor patients from our institution who received extensive molecular characterization by epigenome-wide methylation microarray and were diagnosed according to the 2021 WHO brain tumor classification. From multimodal preoperative 3T MRI scans, we extracted imaging metrics via a fully automated, AI-based image segmentation and processing pipeline. Subsequently, we examined differences in imaging features between the three main glioma entities (glioblastoma, astrocytoma, and oligodendroglioma) and particularly investigated new entities such as astrocytoma, WHO grade 4. Results: Our results confirm prior studies that found significantly higher median CBV (p = 0.00003, ANOVA) and lower median ADC in contrast-enhancing areas of glioblastomas, compared to astrocytomas and oligodendrogliomas (p = 0.41333, ANOVA). Interestingly, molecularly defined glioblastoma, which usually does not contain contrast-enhancing areas, also shows significantly higher CBV values in the non-enhancing tumor than common glioblastoma and astrocytoma grade 4 (p = 0.01309, ANOVA). Conclusions: This work provides extensive insights into the imaging features of gliomas in light of the new 2021 WHO CNS tumor classification. Advanced imaging shows promise in visualizing tumor biology and improving the diagnosis of brain tumor patients.
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影响因子：
64.8
作者：
Capper D;Jones DTW;Sill M;Hovestadt V;Schrimpf D;Sturm D;Koelsche C;Sahm F;Chavez L;Reuss DE;Kratz A;Wefers AK;Huang K;Pajtler KW;Schweizer L;Stichel D;Olar A;Engel NW;Lindenberg K;Harter PN;Braczynski AK;Plate KH;Dohmen H;Garvalov BK;Coras R;Hölsken A;Hewer E;Bewerunge-Hudler M;Schick M;Fischer R;Beschorner R;Schittenhelm J;Staszewski O;Wani K;Varlet P;Pages M;Temming P;Lohmann D;Selt F;Witt H;Milde T;Witt O;Aronica E;Giangaspero F;Rushing E;Scheurlen W;Geisenberger C;Rodriguez FJ;Becker A;Preusser M;Haberler C;Bjerkvig R;Cryan J;Farrell M;Deckert M;Hench J;Frank S;Serrano J;Kannan K;Tsirigos A;Brück W;Hofer S;Brehmer S;Seiz-Rosenhagen M;Hänggi D;Hans V;Rozsnoki S;Hansford JR;Kohlhof P;Kristensen BW;Lechner M;Lopes B;Mawrin C;Ketter R;Kulozik A;Khatib Z;Heppner F;Koch A;Jouvet A;Keohane C;Mühleisen H;Mueller W;Pohl U;Prinz M;Benner A;Zapatka M;Gottardo NG;Driever PH;Kramm CM;Müller HL;Rutkowski S;von Hoff K;Frühwald MC;Gnekow A;Fleischhack G;Tippelt S;Calaminus G;Monoranu CM;Perry A;Jones C;Jacques TS;Radlwimmer B;Gessi M;Pietsch T;Schramm J;Schackert G;Westphal M;Reifenberger G;Wesseling P;Weller M;Collins VP;Blümcke I;Bendszus M;Debus J;Huang A;Jabado N;Northcott PA;Paulus W;Gajjar A;Robinson GW;Taylor MD;Jaunmuktane Z;Ryzhova M;Platten M;Unterberg A;Wick W;Karajannis MA;Mittelbronn M;Acker T;Hartmann C;Aldape K;Schüller U;Buslei R;Lichter P;Kool M;Herold-Mende C;Ellison DW;Hasselblatt M;Snuderl M;Brandner S;Korshunov A;von Deimling A;Pfister SM
通讯作者：
Pfister SM
影响因子：
3.5
作者：
Garyfallidis E;Brett M;Amirbekian B;Rokem A;van der Walt S;Descoteaux M;Nimmo-Smith I;Dipy Contributors
通讯作者：
Dipy Contributors
影响因子：
4.7
作者：
Arzanforoosh F;Croal PL;van Garderen KA;Smits M;Chappell MA;Warnert EAH
通讯作者：
Warnert EAH
影响因子：
4.8
作者：
Rohlfing, Torsten;Zahr, Natalie M.;Sullivan, Edith V.;Pfefferbaum, Adolf
通讯作者：
Pfefferbaum, Adolf
影响因子：
2.7
作者：
Yang, Xiefeng;Xing, Zhen;She, Dejun;Lin, Yu;Zhang, Hua;Su, Yan;Cao, Dairong
通讯作者：
Cao, Dairong