Abstract
Background and objectivesThe diagnostic performance of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) in the differential diagnosis of pulmonary tumors remained debatable among published studies. This study aimed to pool and summary the relevant results to provide more robust evidence in this issue using a meta-analysis method.Materials and methodsThe researches regarding the differential diagnosis of lung lesions using IVIM-DWI were systemically searched in Pubmed, Embase, Web of science and Wangfang database without time limitation. Review Manager 5.3 was used to calculate the standardized mean difference (SMD) and 95% confidence intervals of apparent diffusion coefficient (ADC), tissue diffusivity (D), pseudo-diffusivity (D*), and perfusion fraction (f). Stata 12.0 was used to pool the sensitivity, specificity, and area under the curve (AUC), as well as publication bias and heterogeneity. Fagan’s nomogram was used to predict the post-test probabilities.ResultsEleven studies with 481 malignant and 258 benign lung lesions were included. Most include studies showed a low to unclear risk of bias and low concerns regarding applicability. Lung cancer demonstrated a significant lower ADC (SMD = -1.17, P < 0.001), D (SMD = -1.02, P < 0.001) and f values (SMD = -0.43, P = 0.005) than benign lesions, except D* value (SMD = 0.01, P = 0.96). D value demonstrated the best diagnostic performance (sensitivity = 89%, specificity = 71%, AUC = 0.90) and highest post-test probability (57, 57, 43 and 43% for D, ADC, f and D* values) in the differential diagnosis of lung tumors, followed by ADC (sensitivity = 85%, specificity = 72%, AUC = 0.86), f (sensitivity = 71%, specificity = 61%, AUC = 0.71) and D* values (sensitivity = 70%, specificity = 60%, AUC = 0.66).ConclusionIVIM-DWI parameters show potentially strong diagnostic capabilities in the differential diagnosis of lung tumors based on the tumor cellularity and perfusion characteristics, and D value demonstrated better diagnostic performance compared to mono-exponential ADC.
Highlights
Lung cancer is the most commonly diagnosed cancer (11.6% of the total cases) and the leading cause of cancer death (18.4% of the total cancer deaths) in 2018 around the world [1]
Intravoxel incoherent motion (IVIM)-Diffusion-weighted imaging (DWI) parameters show potentially strong diagnostic capabilities in the differential diagnosis of lung tumors based on the tumor cellularity and perfusion characteristics, and D value demonstrated better diagnostic performance compared to mono-exponential apparent diffusion coefficient (ADC)
The mono-exponential model is expressed as SI / SI0 = exp(−b·ADC), where SI0 refers to the mean signal intensity (SI) of the region of interest for b = 0 s/mm2 while SI refers to the signal intensity for higher b values
Summary
Lung cancer is the most commonly diagnosed cancer (11.6% of the total cases) and the leading cause of cancer death (18.4% of the total cancer deaths) in 2018 around the world [1]. With the development of MRI hardwares and various rapid imaging technologies such as improved gradient performance, parallel imaging techniques and free-breathing acquisition, MRI has been increasingly used for identification of benign and malignant lung tumors and efficacy evaluation. Diffusion-weighted imaging (DWI) is a radiation-free and contrast-free functional imaging sequence, which allows measurement of water molecular movement using apparent diffusion coefficient (ADC) and demonstrates potential to differentiate malignant from benign lung lesions. A previous meta-analysis even reported a higher diagnostic performance with a pooled sensitivity, specificity and areas under the curve (AUC) of 83, 91% and 0.93 in DWI, compared to PET/CT whose sensitivity, specificity and AUC were 78, 81% and 0.86, respectively. The diagnostic performance of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) in the differential diagnosis of pulmonary tumors remained debatable among published studies. This study aimed to pool and summary the relevant results to provide more robust evidence in this issue using a meta-analysis method
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