Diffusion Kurtosis Imaging: Correlation Analysis of Quantitative Model Parameters with Molecular Features in Advanced Lung Adenocarcinoma

Diffusion Kurtosis Imaging: Correlation Analysis of Quantitative Model Parameters with Molecular Features in Advanced Lung Adenocarcinoma

Lung cancer remains the leading cause of cancer-related mortality worldwide, with a 5-year overall survival rate of only 15% to 20% regardless of tumor stage and treatment. The recognition of specific molecular alterations in certain lung cancer subtypes has facilitated tailored therapy and ushered in the era of personalized oncologic practice. Among lung carcinomas, lung adenocarcinoma is the most well-understood in terms of its molecular foundation, with approximately 60% of cases harboring an oncogenic driver mutation that often predicts treatment response and correlates with clinicopathologic features.

Computed tomography (CT) is typically the first imaging modality used for evaluating and staging lung adenocarcinoma. However, functional imaging techniques such as positron emission tomography-CT (PET-CT) and thoracic magnetic resonance imaging (MRI) have emerged as important supplementary tools. Diffusion-weighted imaging (DWI), a widely applied functional MRI technique, has shown potential for improved cancer detection, prediction of aggressiveness, and evaluation of pathologic subtypes. However, DWI assumes that water diffusion follows a Gaussian distribution, which is unlikely in micro-structurally complex tissues. Diffusion kurtosis imaging (DKI), a non-Gaussian technique, better reflects water diffusivity in tissues with ultrahigh b values. DKI is sensitive to deviations from Gaussian diffusion patterns and provides more accurate assessments of micro-structural complexity than conventional DWI.

This study aimed to evaluate the correlation between DKI parameters and the expression of molecular markers—epidermal growth factor receptor (EGFR), anaplastic lymphoma kinase (ALK), and Ki-67 protein—in patients with advanced lung adenocarcinoma. The study also compared DKI with routine DWI as the reference standard.

The study retrospectively analyzed data from 96 patients with primary lung adenocarcinoma diagnosed at the Cancer Hospital, Chinese Academy of Medical Sciences, between 2016 and 2019. Inclusion criteria included histopathologically confirmed primary lung adenocarcinoma, no prior therapy or surgery, and MRI examinations including DWI and DKI sequences. Exclusion criteria included lesions with ground-glass opacity (GGO) on MRI and lesions smaller than 2 cm. The study evaluated DKI-derived parameters (Kapp and Dapp), apparent diffusion coefficient (ADC) values from DWI, and molecular markers (EGFR, ALK, and Ki-67) detected by immunohistochemistry and molecular biology techniques.

MRI scans were performed on a 3.0-T scanner with a 32-channel coil. The imaging protocol included axial propeller T2-weighted imaging with fat suppression (T2WI/FS), axial fast spin echo T1-weighted imaging, DWI, and DKI. DWI used respiratory-gated, single-shot, spin-echo, echo-planar technology with b values of 0 and 800 s/mm². DKI was performed in the axial plane with b values of 0, 500, 1000, 1500, and 2000 s/mm². Parametric maps of ADC, Dapp, and Kapp were calculated using an offline workstation. Regions of interest were placed on T2WI/FS images and transferred to corresponding ADC, Dapp, and Kapp maps for quantitative analysis.

Histologic analysis was performed according to the 2015 World Health Organization Classification of Tumors of the Lung and Pleura. EGFR mutations were detected by nested polymerase chain reaction (PCR), ALK rearrangements by fluorescence in situ hybridization or reverse transcription-PCR, and Ki-67 expression by immunohistochemistry. Ki-67 proliferative index (PI) was categorized as high (≥25%) or low (<25%).

Statistical analysis included normality and variance homogeneity tests for quantitative variables, independent-samples t-tests for subgroup comparisons, and Spearman correlation tests for assessing relationships between imaging parameters and molecular markers. Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic accuracy of ADC, Dapp, and Kapp in differentiating lesions with different molecular marker expressions.

The study included 96 lung adenocarcinoma lesions from 96 patients (42 males, 54 females) with a mean age of 66 years. Lesion sizes ranged from 2.1 to 7.3 cm. EGFR mutations were positive in 53 cases (55.2%), ALK rearrangements in 12 cases (12.5%), and high Ki-67 expression in 83 cases (86.5%). Patients with ALK rearrangements tended to be younger than those without.

Kapp values were significantly higher in EGFR mutation-positive cases (0.81 ± 0.12 vs. 0.66 ± 0.10, t = 6.41, P < 0.001), ALK rearrangement-negative cases (0.76 ± 0.12 vs. 0.60 ± 0.15, t = 4.09, P < 0.001), and high Ki-67 expression cases (0.76 ± 0.12 vs. 0.58 ± 0.13, t = 4.88, P < 0.001). Dapp values were significantly lower in high Ki-67 expression cases (3.19 ± 0.69 mm²/ms vs. 4.20 ± 0.83 mm²/ms, t = 4.80, P < 0.001) and EGFR mutation-positive cases (3.11 ± 0.73 mm²/ms vs. 3.59 ± 0.77 mm²/ms, t = 3.12, P = 0.002). ADC values were significantly lower in EGFR mutation-positive cases ([1.19 ± 0.37] × 10⁻³ mm²/s vs. [1.50 ± 0.53] × 10⁻³ mm²/s, t = 3.38, P = 0.001) and high Ki-67 expression cases ([1.28 ± 0.39] × 10⁻³ mm²/s vs. [1.67 ± 0.77] × 10⁻³ mm²/s, t = 2.88, P = 0.005).

Spearman correlation analysis revealed strong positive correlations between Kapp and EGFR mutations (r = 0.844, P = 0.008) and Ki-67 PI (r = 0.882, P = 0.001), and a strong negative correlation with ALK rearrangements (r = -0.772, P = 0.001). Dapp showed moderate negative correlations with EGFR mutations (r = -0.650, P = 0.024) and Ki-67 PI (r = -0.734, P = 0.012). ADC showed a moderate negative correlation with Ki-67 PI (r = -0.679, P = 0.033). No significant correlations were found between Dapp and ALK rearrangements or ADC and EGFR mutations or ALK rearrangements.

ROC analysis showed that Kapp had higher AUC values for predicting adverse pathologic findings (AUC: 0.79–0.88) compared to ADC (AUC: 0.49–0.73) and Dapp (AUC: 0.60–0.86). However, the differences in performance between the metrics were not statistically significant.

The study demonstrated that DKI-derived parameters, particularly Kapp, are strongly correlated with the expression of molecular markers in advanced lung adenocarcinoma. Kapp values were significantly higher in EGFR mutation-positive, ALK rearrangement-negative, and high Ki-67 expression cases, reflecting greater micro-structural complexity. Dapp and ADC values were lower in high Ki-67 expression and EGFR mutation-positive cases, indicating restricted water diffusion. While DKI provided slightly better diagnostic accuracy than conventional DWI, the differences were not statistically significant.

The findings suggest that DKI can serve as a non-invasive imaging tool to assess the status of molecular markers in lung adenocarcinoma, potentially improving detection, staging, and treatment monitoring. However, the study’s limitations include the exclusion of small lesions and GGO lesions due to imaging challenges. Further prospective studies are needed to validate these findings and explore the clinical utility of DKI in lung cancer management.

doi.org/10.1097/CM9.0000000000001074

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