Diffusion kurtosis imaging: correlation analysis of quantitative model parameters with molecular features in advanced lung adenocarcinoma

Whole-volume diffusion kurtosis magnetic resonance (MR) imaging histogram analysis of non-small cell lung cancer: correlation with histopathology and degree of tumor differentiation

AIMS

To evaluate the role of diffusion kurtosis imaging (DKI) histogram analysis in the characterization of non-small cell lung cancer (NSCLC) and to correlate DKI parameters with tumor cellularity.

MATERIALS AND METHODS

Sixty-four patients with pathologically diagnosed NSCLCs were evaluated by DKI on a 3-T scanner. Regions of interest (ROIs) were drawn on the map of b1000 manually. All NSCLCs were histologically graded according to the degree of tumor differentiation. Tumor cellularity was measured by the nuclear-to-cytoplasm (N/C) ratio and the number of tumor cell nuclei (NTCN), the expression of Ki-67 was detected using the streptavidin-peroxidase method. Histogram analysis was performed using voxel-based on raw data from each ROI.

RESULTS

NSCLCs were classified as grades 1, 2, and 3 according to differentiation degree. Histogram parameters of apparent diffusion coefficient (ADC) and DKI could discriminate between different grades of tumors (p<0.001). Receiver operating characteristic (ROC) curve analysis showed that Kapp 75th exhibited the best performance with an AUC of 0.936 and sensitivity/specificity of 95.74%/80% (p<0.001) in distinguishing grade 1 from grade 2, ADC mean exhibited the best performance with an AUC of 0.923 and sensitivity/specificity of 92.33%/86.67% (p<0.001) in distinguishing grade 2 from 3. N/C ratio and Ki-67 changed significantly with grade (p<0.01). Negative correlations were found between the ADC mean and the N/C ratio, Ki-67, Dapp mean and N/C ratio, whereas Kapp mean and N/C ratio, Ki-67 were positively correlated.

CONCLUSIONS

DKI histogram analysis could quantitatively characterize NSCLC with different grades by probing non-Gaussian diffusion properties related to changes in the tumor microenvironment or tissue complexities in the tumor.

Integrated pretreatment diffusion kurtosis imaging and serum squamous cell carcinoma antigen levels: a biomarker strategy for early assessment of radiotherapy outcomes in cervical cancer

OBJECTIVE

This study aims to explore the utility of pretreatment DKI parameters and serum SCC-Ag in evaluating the early therapeutic response of cervical cancer to radiotherapy.

MATERIALS AND METHODS

A total of 33 patients diagnosed with cervical cancer, including 31 cases of cervical squamous cell carcinoma and two cases of adenosquamous carcinoma, participated in the study. All patients underwent conventional MRI and DKI scans on a 3T magnetic resonance scanner before radiotherapy and after ten sessions of radiotherapy. The therapeutic response was evaluated based on the Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1. Patients were categorized into a response group (RG), comprising Complete Remission (CR) and Partial Remission (PR), and a non-response group (NRG), comprising Stable Disease (SD) and Progressive Disease (PD). LASSO was employed to select pretreatment DKI parameters, and ROC curves were generated for the selected parameters and serum SCC-Ag.

RESULTS

Significant differences were observed in pretreatment MD, Da, Dr, MK, Ka, Kr, and SCC-Ag between the RG and NRG groups (P < 0.01). However, no significant differences were noted for FA and FAK (P = 0.441&0.928). The two selected parameters (MD and MK) demonstrated area under the curve (AUC), sensitivity, and specificity of 0.810, 0.769, 0.850 and 0.827, 0.846, 0.750, respectively. The combination of MD and MK exhibited an improved AUC of 0.901, sensitivity of 0.692, and specificity of 1.000, with a higher Youden index compared to the individual parameters. Conversely, the AUC, sensitivity, and specificity of the combination of MD, MK, and SCC-Ag were 0.852, 0.615, and 1.000, with a Youden index of 0.615.

CONCLUSION

Pretreatment MD, MK, and SCC-Ag demonstrate potential clinical utility, with the combined application of MD and MK showing enhanced efficacy in assessing the early therapeutic response of cervical cancer to radiotherapy. The addition of SCC-Ag did not contribute further to the assessment efficacy.

Differential value of diffusion kurtosis imaging and intravoxel incoherent motion in benign and malignant solitary pulmonary lesions

Objective

To investigate the diagnostic value of diffusion kurtosis imaging (DKI) and intravoxel incoherent motion (IVIM) whole-lesion histogram parameters in differentiating benign and malignant solitary pulmonary lesions (SPLs).

Materials and Methods

Patients with SPLs detected by chest CT examination and with further routine MRI, DKI and IVIM-DWI functional sequence scanning data were recruited. According to the pathological results, SPLs were divided into a benign group and a malignant group. Independent samples t tests (normal distribution) or Mann‒Whitney U tests (nonnormal distribution) were used to compare the differences in DKI (Dk, K), IVIM (D, D*, f) and ADC whole-lesion histogram parameters between the benign and malignant SPL groups. The receiver operating characteristic (ROC) curve was used to evaluate the diagnostic efficiency of the histogram parameters and determine the optimal threshold. The area under the curve (AUC) of each histogram parameter was compared by the DeLong method. Spearman rank correlation was used to analyze the correlation between histogram parameters and malignant SPLs.

Results

Most of the histogram parameters for diffusion-related values (Dk, D, ADC) of malignant SPLs were significantly lower than those of benign SPLs, while most of the histogram parameters for the K value of malignant SPLs were significantly higher than those of benign SPLs. DKI (Dk, K), IVIM (D) and ADC were effective in differentiating benign and malignant SPLs and combined with multiple parameters of the whole-lesion histogram for the D value, had the highest diagnostic efficiency, with an AUC of 0.967, a sensitivity of 90.00% and a specificity of 94.03%. Most of the histogram parameters for the Dk, D and ADC values were negatively correlated with malignant SPLs, while most of the histogram parameters for the K value were positively correlated with malignant SPLs.

Conclusions

DKI (Dk, K) and IVIM (D) whole-lesion histogram parameters can noninvasively distinguish benign and malignant SPLs, and the diagnostic performance is better than that of DWI. Moreover, they can provide additional information on SPL microstructure, which has important significance for guiding clinical individualized precision diagnosis and treatment and has potential clinical application value.

Application of diffusion kurtosis imaging and 18F-FDG PET in evaluating the subtype, stage and proliferation status of non-small cell lung cancer

Background

Lung cancer has become one of the deadliest tumors in the world. Non-small cell lung cancer (NSCLC) is the most common type of lung cancer, accounting for approximately 80%-85% of all lung cancer cases. This study aimed to investigate the value of diffusion kurtosis imaging (DKI), diffusion-weighted imaging (DWI) and 2-[¹⁸F]-fluoro-2-deoxy-D-glucose positron emission tomography (¹⁸F-FDG PET) in differentiating squamous cell carcinoma (SCC) and adenocarcinoma (AC) and to evaluate the correlation of each parameter with stage and proliferative status Ki-67.

Methods

Seventy-seven patients with lung lesions were prospectively scanned by hybrid 3.0-T chest ¹⁸F-FDG PET/MR. Mean kurtosis (MK), mean diffusivity (MD), apparent diffusion coefficient (ADC), maximum standard uptake value (SUVmax), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were measured. The independent samples t test or Mann–Whitney U test was used to compare and analyze the differences in each parameter of SCC and AC. The diagnostic efficacy was evaluated by receiver operating characteristic (ROC) curve analysis and compared with the DeLong test. A logistic regression analysis was used for the evaluation of independent predictors. Bootstrapping (1000 samples) was performed to establish a control model, and calibration curves and ROC curves were used to validate its performance. Pearson’s correlation coefficient and Spearman’s correlation coefficient were calculated for correlation analysis.

Results

The MK and ADC values of the AC group were significantly higher than those of the SCC group (all P< 0.05), and the SUVmax, MTV, and TLG values of the SCC group were significantly higher than those of the AC group (all P<0.05). There was no significant difference in the MD value between the two groups. Moreover, MK, SUVmax, TLG and MTV were independent predictors of the NSCLC subtype, and the combination of these parameters had an optimal diagnostic efficacy (AUC, 0.876; sensitivity, 86.27%; specificity, 80.77%), which was significantly better than that of MK (AUC = 0.758, z = 2.554, P = 0.011), ADC (AUC = 0.679, z = 2.322, P = 0.020), SUVmax (AUC = 0.740, z = 2.584, P = 0.010), MTV (AUC = 0.715, z = 2.530, P = 0.011) or TLG (AUC = 0.716, z = 2.799, P = 0.005). The ROC curve showed that the validation model had high accuracy in identifying AC and SCC (AUC, 0.844; 95% CI, 0.785-0.885);. The SUVmax value was weakly positively correlated with the Ki-67 index (r = 0.340, P< 0.05), the ADC and MD values were weakly negatively correlated with the Ki-67 index (r = -0.256, -0.282, P< 0.05), and the MTV and TLG values were weakly positively correlated with NSCLC stage (r = 0.342, 0.337, P< 0.05).

Conclusion

DKI, DWI and ¹⁸F-FDG PET are all effective methods for assessing the NSCLC subtype, and some parameters are correlated with stage and proliferation status.