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• Clinical Articles •
Differentiating pulmonary inflammatory nodules from lung cancer based on whole-focus dynamic enhanced MRI intensity histogram
GAO Yeqi  LU Jie  XU Hai  YUAN Mei  YU Tongfu 

Cite this article as: GAO Y Q, LU J, XU H, et al. Differentiating pulmonary inflammatory nodules from lung cancer based on whole-focus dynamic enhanced MRI intensity histogram[J]. Chin J Magn Reson Imaging, 2023, 14(7): 42-48. DOI:10.12015/issn.1674-8034.2023.07.008.


[Abstract] Objective Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) intensity histogram analysis was used to analyze the whole focus of pulmonary inflammatory nodules and lung cancer which diameter 0.8-3.0 cm and to evaluate their value in differential diagnosis.Materials and Methods The DCE-MRI data of 123 patients with pulmonary inflammatory nodules and lung cancer confirmed by operation or puncture biopsy and clinical imaging follow-up from July 2019 to June 2022 were analyzed retrospectively, including 63 cases of pulmonary inflammatory nodules and 60 cases of lung cancer. Using FireVoxel software, the region of interest (ROI) of the whole lesion was manually delineated layer by layer on the peak enhancement image and its silhouette image, and the signal intensity histogram parameters of 3D ROI were obtained. Including minimum, maximum, average, median, standard deviation, skewness, kurtosis, entropy, coefficient of variation (CoV), 10th percentile (P10), 25th percentile (P25), 50th percentile (P50), 75th percentile (P75), 90th percentile (P90), etc. The diagnostic ability of intensity histogram parameters for both groups was determined by using thereceiver operating characteristic (ROC) curve. The joint variable (JV) was obtained by logistic regression analysis model, and the diagnostic ability was determined by ROC curve.Results In the histogram parameters of peak enhancement, the minimum, mean, median, P10 and P25 of lung cancer were higher than those of inflammatory nodules, while the CoV and skewness of lung cancer were lower than those of inflammatory nodules, and the difference was statistically significant. Among them, the AUC [0.668, 95% confidence interval (CI): 0.573-0.764] with the minimum value of 155.5 as the threshold is the largest, the diagnostic efficiency is the best, and the sensitivity and specificity are 35.0% and 93.7%. In the histogram parameters of peak enhancement, the minimum, P10 and P25 of lung cancer were higher than those of inflammatory nodules, while the values of CoV and entropy were lower than those of inflammatory nodules, and the difference was statistically significant. Among them, AUC (0.775, 95% CI: 0.692-0.858) with CoV 0.275 as the threshold was the largest, and the diagnostic efficiency was the best, with a sensitivity and specificity of 88.9% and 58.3%. The semi-quantitative parameters derived from time-signal intensity curve (TIC) included time to peak (TTP), contrast enhancement ratio and curve slope. The TTP of lung cancer was shorter than that of inflammatory nodules, but the slope of curve was larger than that of inflammatory nodules, and the difference was statistically significant. The AUC (0.737, 95% CI: 0.647-0.828) of TTP with a threshold of 204.2 seconds was the largest, with a sensitivity and specificity of 58.7% and 85.0%, and AUC (0.732, 95% CI: 0.641-0.822) with a slope of 1.76 was the largest, with a sensitivity and specificity of 61.7% and 82.5%. The combination of histogram parameters and semi-quantitative parameters of the silhouette showed that AUC (0.885, 95% CI: 0.823-0.947) with a threshold of JV of 0.43 was the highest, with a sensitivity and specificity of 88.3% and 79.4%.Conclusions DCE-MRI intensity histogram based on whole focus can provide information for differential diagnosis of lung cancer and inflammatory nodules, and the diagnostic efficiency of silhouette images is higher. The combined application of histogram parameters and semi-quantitative parameters derived from TIC can further improve the ability to distinguish between malignant nodules and inflammatory nodules, and provide reliable objective basis for differential diagnosis.
[Keywords] lung cancer；pulmonary inflammatory nodules；dynamic enhanced magnetic resonance imaging；intensity histogram；silhouette images；semi-quantitative parameters；magnetic resonance imaging

GAO Yeqi   LU Jie   XU Hai   YUAN Mei   YU Tongfu*  

Department of Radiology, the First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China

Corresponding author: Yu TF, E-mail: yu.tongfu@163.com

Conflicts of interest   None.

Received  2022-09-19
Accepted  2023-06-25
DOI: 10.12015/issn.1674-8034.2023.07.008
Cite this article as: GAO Y Q, LU J, XU H, et al. Differentiating pulmonary inflammatory nodules from lung cancer based on whole-focus dynamic enhanced MRI intensity histogram[J]. Chin J Magn Reson Imaging, 2023, 14(7): 42-48. DOI:10.12015/issn.1674-8034.2023.07.008.

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