ArticleLung India : official organ of Indian Chest Society
Computed tomography perfusion (CTP) in primary lung cancer: Results from a tertiary care centre.
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Abstract
Context: 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. Settings and Design: This prospective study was conducted at a tertiary care referral hospital in western India. Methods: 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. Results: 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). Conclusion: 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.
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