A Visually Apparent and Quantifiable CT Imaging Feature Identifies Biophysical Subtypes of Pancreatic Ductal Adenocarcinoma.
A Visually Apparent and Quantifiable CT Imaging Feature Identifies Biophysical Subtypes of Pancreatic Ductal Adenocarcinoma.
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DOI：
10.1158/1078-0432.ccr-17-3668
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发表时间：
2018-12-01
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影响因子：
--
通讯作者：
Fleming JB
中科院分区：
文献类型：
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作者：
Koay EJ;Lee Y;Cristini V;Lowengrub JS;Kang Y;Lucas FAS;Hobbs BP;Ye R;Elganainy D;Almahariq M;Amer AM;Chatterjee D;Yan H;Park PC;Rios Perez MV;Li D;Garg N;Reiss KA;Yu S;Chauhan A;Zaid M;Nikzad N;Wolff RA;Javle M;Varadhachary GR;Shroff RT;Das P;Lee JE;Ferrari M;Maitra A;Taniguchi CM;Kim MP;Crane CH;Katz MH;Wang H;Bhosale P;Tamm EP;Fleming JB
胰腺导管腺癌（PDAC）是一种异质性疾病，具有不同的表现和疾病自然史。我们假设诊断性计算机断层扫描 (CT) 扫描中 PDAC 肿瘤的不同形态特征将反映其潜在的生物学特征。我们开发了一种定量方法，对来自可切除和转移性疾病患者的多个数据集的治疗前 CT 扫描的 PDAC 形态进行分类，并将这些模式与临床/病理测量相关联。我们通过计算模拟宏观病变生长，以测试基质对形态模式的影响，假设癌细胞的增殖和局部迁移率的平衡将决定肿瘤形态。在局部和转移性 PDAC 中，量化肿瘤和实质 (delta) 之间界面处 CT 扫描的增强变化表明，与不明显 (低 delta) 肿瘤患者相比，明显 (高 delta) 肿瘤患者的间质显着减少，多种常见途径突变的可能性更高，间质特征更多，早期远处转移的可能性更高，生存时间更短。肿瘤的间质和间质特征的病理学测量支持了数学模型的 PDAC 生长的基本理论。在基线诊断时，视觉上引人注目且可量化的 CT 成像特征反映了 PDAC 的分子和病理异质性，可用于将患者分为不同的亚型。此外，PDAC 的生长模式可以使用物理原理来描述，从而为这种致命疾病的诊断和治疗提供新的见解。
Pancreatic ductal adenocarcinoma (PDAC) is a heterogeneous disease with variable presentations and natural histories of disease. We hypothesized that different morphologic characteristics of PDAC tumors on diagnostic computed tomography (CT) scans would reflect their underlying biology. We developed a quantitative method to categorize the PDAC morphology on pre-therapy CT scans from multiple datasets of patients with resectable and metastatic disease, and correlated these patterns with clinical/pathologic measurements. We modeled macroscopic lesion growth computationally to test the effects of stroma on morphological patterns, hypothesizing that the balance of proliferation and local migration rates of the cancer cells would determine tumor morphology. In localized and metastatic PDAC, quantifying the change in enhancement on CT scans at the interface between tumor and parenchyma (delta) demonstrated that patients with conspicuous (high delta) tumors had significantly less stroma, higher likelihood of multiple common pathway mutations, more mesenchymal features, higher likelihood of early distant metastasis, and shorter survival times compared with those with inconspicuous (low delta) tumors. Pathological measurements of stromal and mesenchymal features of the tumors supported the mathematical model’s underlying theory for PDAC growth. At baseline diagnosis, a visually striking and quantifiable CT imaging feature reflects the molecular and pathological heterogeneity of PDAC, and may be used to stratify patients into distinct subtypes. Moreover, growth patterns of PDAC may be described using physical principles, enabling new insights into diagnosis and treatment of this deadly disease.