Arimbrakkunnan Mufeed, Garg Pawan K, Khera Pushpinder S, Sureka Binit, Elhence Poonam, Pareek Puneet, Chauhan Nishant Kumar, Yadav Taruna
Department of Diagnostic and Interventional Radiology, All India Institute of Medical Sciences, Jodhpur, Rajasthan, India.
Department of Pathology and Lab Medicine, All India Institute of Medical Sciences, Jodhpur, Rajasthan, India.
Lung India. 2022 May-Jun;39(3):220-229. doi: 10.4103/lungindia.lungindia_365_21.
Lung cancer is the leading cause of cancer-related deaths in the world. Computed tomography perfusion (CTP) parameters can be used to evaluate the vascular flow dynamics of lung tumours. We set out to evaluate the CTP parameters in lung cancer and correlate them with histopathological subtype and other characteristics of patients with Lung Cancer.
This prospective study was conducted at a tertiary care referral hospital in western India.
Between January 2019 and July 2020, CTP was performed in 46 patients of lung cancer with histopathological confirmation. The CTP parameters were evaluated in detail and correlated with histopathological subtypes, staging and immunohistochemistry (IHC) markers. Analysis of variance (ANOVA) test, receiver operator characteristic (ROC) curve, Box and whiskers plot graph and Pearson correlation tests were used for statistical analysis.
The most common subtype was adenocarcinoma (AC) in 21 patients, followed by squamous cell carcinoma (SCC) in 15 patients and others in 10 patients. Statistically significant difference in blood flow (BF) (f = 5.563, P = 0.007), blood volume (BV) (f = 3.548, P = 0.038) and permeability/flow extraction (FE) (f = 3.617, P = 0.036) were seen in different histopathological subtypes of lung cancer. BF is the main perfusion parameter for differentiation of AC from SCC. P63 positive lesions showed statistically significant lower BF, BV and FE parameters compared to P63 negative lesions (P = 0.013, 0.016 and 0.014, respectively). Different T stages showed statistically significant differences in BF (f = 3.573, P = 0.037), BV (f = 5.145, P = 0.010) and in FE (f = 4.849, P = 0.013).
CTP is a non-invasive imaging method to assess the vascular flow dynamics of the tumours that may predict the histopathological subtypes in lung cancer. It can be used to target large-sized lesions during biopsy and to predict the chemotherapy response.
肺癌是全球癌症相关死亡的主要原因。计算机断层扫描灌注（CTP）参数可用于评估肺肿瘤的血管血流动力学。我们旨在评估肺癌中的CTP参数，并将其与组织病理学亚型及肺癌患者的其他特征相关联。
这项前瞻性研究在印度西部的一家三级医疗转诊医院进行。
在2019年1月至2020年7月期间，对46例经组织病理学确诊的肺癌患者进行了CTP检查。详细评估了CTP参数，并将其与组织病理学亚型、分期和免疫组织化学（IHC）标志物相关联。采用方差分析（ANOVA）检验、受试者操作特征（ROC）曲线、箱线图和Pearson相关性检验进行统计分析。
最常见的亚型是21例腺癌（AC），其次是15例鳞状细胞癌（SCC）和10例其他类型。在肺癌的不同组织病理学亚型中，血流（BF）（f = 5.563，P = 0.007）、血容量（BV）（f = 3.548，P = 0.038）和通透性/血流提取率（FE）（f = 3.617，P = 0.036）存在统计学显著差异。BF是区分AC和SCC的主要灌注参数。与P63阴性病变相比，P63阳性病变的BF、BV和FE参数在统计学上显著更低（分别为P = 0.013、0.016和0.014）。不同的T分期在BF（f = 3.573，P = 0.037）、BV（f = 5.145，P = 0.010）和FE（f = 4.849，P = 0.013）方面存在统计学显著差异。
CTP是一种评估肿瘤血管血流动力学的非侵入性成像方法，可预测肺癌的组织病理学亚型。它可用于在活检期间针对大尺寸病变，并预测化疗反应。
