Jungmann Friederike, Kaissis Georgios A, Ziegelmayer Sebastian, Harder Felix, Schilling Clara, Yen Hsi-Yu, Steiger Katja, Weichert Wilko, Schirren Rebekka, Demir Ishan Ekin, Friess Helmut, Makowski Markus R, Braren Rickmer F, Lohöfer Fabian K
Institute of Diagnostic and Interventional Radiology, School of Medicine, Technical University of Munich, 81675 Munich, Germany.
Department of Computing, Faculty of Engineering, Imperial College of Science, Technology and Medicine, London SW7 2AZ, UK.
Cancers (Basel). 2021 Apr 25;13(9):2069. doi: 10.3390/cancers13092069.
PDAC remains a tumor entity with poor prognosis and a 5-year survival rate below 10%. Recent research has revealed invasive biomarkers, such as distinct molecular subtypes, predictive for therapy response and patient survival. Non-invasive prediction of individual patient outcome however remains an unresolved task.
Discrete cellularity regions of PDAC resection specimen ( = 43) were analyzed by routine histopathological work up. Regional tumor cellularity and CT-derived Hounsfield Units (HU, = 66) as well as iodine concentrations were regionally matched. One-way ANOVA and pairwise t-tests were performed to assess the relationship between different cellularity level in conventional, virtual monoenergetic 40 keV (monoE 40 keV) and iodine map reconstructions.
A statistically significant negative correlation between regional tumor cellularity in histopathology and CT-derived HU from corresponding image regions was identified. Radiological differentiation was best possible in monoE 40 keV CT images. However, HU values differed significantly in conventional reconstructions as well, indicating the possibility of a broad clinical application of this finding.
In this study we establish a novel method for CT-based prediction of tumor cellularity for in-vivo tumor characterization in PDAC patients.
胰腺导管腺癌（PDAC）仍然是一种预后较差的肿瘤实体，5年生存率低于10%。最近的研究已经揭示了一些侵袭性生物标志物，如不同的分子亚型，可预测治疗反应和患者生存情况。然而，对个体患者预后进行无创预测仍然是一项未解决的任务。
通过常规组织病理学检查分析43例PDAC切除标本的离散细胞区域。将区域肿瘤细胞密度与CT衍生的亨氏单位（HU，n = 66）以及碘浓度进行区域匹配。进行单因素方差分析和两两t检验，以评估常规、虚拟单能40keV（单能E 40keV）和碘图重建中不同细胞密度水平之间的关系。
在组织病理学中区域肿瘤细胞密度与相应图像区域的CT衍生HU之间发现了具有统计学意义的负相关。在单能E 40keV CT图像中，放射学鉴别效果最佳。然而，在常规重建中HU值也存在显著差异，表明这一发现具有广泛临床应用可能性。
在本研究中，我们建立了一种基于CT的预测肿瘤细胞密度的新方法，用于PDAC患者体内肿瘤特征的表征。
