Abstract
PurposeInvestigating the diagnostic accuracy of histogram analyses of apparent diffusion coefficient (ADC) values for determining non-small cell lung cancer (NSCLC) tumor grades, lymphovascular invasion, and pleural invasion.Materials and methodsWe studied 60 surgically diagnosed NSCLC patients. Diffusion-weighted imaging (DWI) was performed in the axial plane using a navigator-triggered single-shot, echo-planar imaging sequence with prospective acquisition correction. The ADC maps were generated, and we placed a volume-of-interest on the tumor to construct the whole-lesion histogram. Using the histogram, we calculated the mean, 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles of ADC, skewness, and kurtosis. Histogram parameters were correlated with tumor grade, lymphovascular invasion, and pleural invasion. We performed a receiver operating characteristics (ROC) analysis to assess the diagnostic performance of histogram parameters for distinguishing different pathologic features.ResultsThe ADC mean, 10th, 25th, 50th, 75th, 90th, and 95th percentiles showed significant differences among the tumor grades. The ADC mean, 25th, 50th, 75th, 90th, and 95th percentiles were significant histogram parameters between high- and low-grade tumors. The ROC analysis between high- and low-grade tumors showed that the 95th percentile ADC achieved the highest area under curve (AUC) at 0.74. Lymphovascular invasion was associated with the ADC mean, 50th, 75th, 90th, and 95th percentiles, skewness, and kurtosis. Kurtosis achieved the highest AUC at 0.809. Pleural invasion was only associated with skewness, with the AUC of 0.648.ConclusionsADC histogram analyses on the basis of the entire tumor volume are able to stratify NSCLCs' tumor grade, lymphovascular invasion and pleural invasion.
Highlights
Lung cancer is the most common malignant tumor and has become the main cause of cancer mortality [1]
The receiver operating characteristics (ROC) analysis between high- and low-grade tumors showed that the 95th percentile apparent diffusion coefficient (ADC) achieved the highest area under curve (AUC) at 0.74
Lymphovascular invasion was associated with the ADC mean, 50th, 75th, 90th, and 95th percentiles, skewness, and kurtosis
Summary
Lung cancer is the most common malignant tumor and has become the main cause of cancer mortality [1]. Positron emission tomography using 18F-fluorodeoxyglucose (18F-FDG PET) has been used for evaluating the tumor aggressiveness of nonsmall cell lung cancer (NSCLC) [2,3], but 18F-FDG PET is not widely used because of its high cost. The use of lung magnetic resonance (MR) imaging is gradually increasing in clinical practice, because of its lower cost, and due to its easy applicability for various pathologic conditions. Some studies have suggested that the ADC could be used to demonstrate the histological characteristics of lung cancers, and that it may be useful for distinguishing the degree of cell differentiation [6,7,8,9,10,11]. The averaged mean ADC is calculated from the largest slice of a tumor, and the mean ADC may not represent the full spectrum of histology within a tumor
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
