The application value of support vector machine model based on multimodal MRI in predicting IDH-1mutation and Ki-67 expression in glioma.

PURPOSE: To investigate the application value of support vector machine (SVM) model based on diffusion-weighted imaging (DWI), dynamic contrast-enhanced (DCE) and amide proton transfer- weighted (APTW) imaging in predicting isocitrate dehydrogenase 1(IDH-1) mutation and Ki-67 expression in glioma. METHODS: The DWI, DCE and APTW images of 309 patients with glioma confirmed by pathology were retrospectively analyzed and divided into the IDH-1 group (IDH-1(+) group and IDH-1(-) group) and Ki-67 group (low expression group (Ki-67 ≤ 10%) and high expression group (Ki-67 > 10%)). All cases were divided into the training set, and validation set according to the ratio of 7:3. The training set was used to select features and establish machine learning models. The SVM model was established with the data after feature selection. Four single sequence models and one combined model were established in IDH-1 group and Ki-67 group. The receiver operator characteristic (ROC) curve was used to evaluate the diagnostic performance of the model. Validation set data was used for further validation. RESULTS: Both in the IDH-1 group and Ki-67 group, the combined model had better predictive efficiency than single sequence model, although the single sequence model had a better predictive efficiency. In the Ki-67 group, the combined model was built from six selected radiomics features, and the AUC were 0.965 and 0.931 in the training and validation sets, respectively. In the IDH-1 group, the combined model was built from four selected radiomics features, and the AUC were 0.997 and 0.967 in the training and validation sets, respectively. CONCLUSION: The radiomics model established by DWI, DCE and APTW images could be used to detect IDH-1 mutation and Ki-67 expression in glioma patients before surgery. The prediction performance of the radiomics model based on the combination sequence was better than that of the single sequence model.

Diffusion Kurtosis Imaging for Assessing the Therapeutic Response of Transcatheter Arterial Chemoembolization in Hepatocellular Carcinoma.

Objective: This study aimed to evaluate the therapeutic response of hepatocellular carcinoma (HCC) after transcatheter arterial chemoembolization (TACE) with diffusion kurtosis imaging (DKI). Methods: Forty-three patients with fifty-nine hepatic cancer nodules were recruited for this study. All patients were treated by TACE. Magnetic resonance imaging (MRI) and DKI (b=0, 800, 1,500, 2,000mm2/s) were performed before and one month after initiating TACE. Patients were classified as either progressing groups or non-progressing groups. Mean kurtosis (MK), mean diffusion (MD), and apparent diffusion coefficient (ADC) values of the tumor tissue were analyzed. Results: Twenty-three HCCs were classified as progressing groups, and thirty-six HCCs were non-progressing groups. After TACE, the values of MD and ADC in non-progressing groups (1.92±0.36×10-3mm2/s, 1.36±0.23×10-3mm2/s) were greater than progressing groups (1.44±0.32× 10-3mm2/s, 1.10±0.23×10-3mm2/s), however, the MK values in non-progressing groups (0.47±0.12) were lower than progressing groups (0.72±0.14). The MK values of tumor among non-progressing patients decreased one month after TACE (0.47±0.12) relative to the preoperative values (0.71±0.12) (P<0.05). In the non-progressing groups, the MD and ADC values of tumor after TACE (1.92±0.36×10-3mm2/s, 1.36±0.23×10-3mm2/s) became higher than their preoperative values (1.44±0.35×10-3mm2/s, 1.09±0.22×10-3mm2/s) (P<0.05). In the progressing groups, the MK, MD, and ADC values of tumor after TACE remained similar before TACE (P>0.05). The sensitivity, specificity, and AUC of the ROC curve for the assessment of HCC progress after TACE by MK (85.2%, 97.5%, and 0.95, respectively) were greater than by ADC (78.6%, 66.5%, and 0.75, respectively) and MD (76.2%, 64.3%, and 0.71, respectively). Conclusions: DKI for assessing the therapeutic response of TACE in HCC shows great promise. MK is more advantageous in the assessment of HCC progress after TACE.

Comparison of diffusion kurtosis imaging versus diffusion weighted imaging in predicting the recurrence of early stage single nodules of hepatocellular carcinoma treated by radiofrequency ablation.

OBJECTIVE: This study aimed to compare the diffusion kurtosis imaging (DKI) versus diffusion weighted imaging (DWI) in predicting the recurrence of early stage single nodules of hepatocellular carcinoma (HCC) treated by radiofrequency ablation (RFA). MATERIALS AND METHODS: A retrospective analysis of 107 patients with early stage single nodules of HCC was performed, all patients treated by RFA. Recurrence rate of HCC was recorded after a median follow-up of 36 months. During follow-up, the data of magnetic resonance imaging (MRI), DWI and DKI were obtained in multiple time points. The predictive values of DWI and DKI were analyzed using ROC curves. RESULTS: The overall recurrence rate was 66.3% (71/107). The sensitivity, specificity, and AUC for ADC, MD and MK after RFA (78.6, 73.3% and 0.842; 85.7, 83.3% and 0.839; 85.7, 96.7% and 0.956) were higher than before RFA (44.3, 53.3% and 0.560; 51.2, 56.7% and 0.543; 43.6, 67.3% and 0.489). The sensitivity, specificity, and AUC for MK after RFA were 85.7, 96.7%, and 0.956, respectively, which were significantly greater than those of ADC (78.6, 73.3% and 0.842; P < 0.05) and MD (85.7, 83.3% and 0.839). CONCLUSIONS: The prediction efficacy of DKI for the recurrence of early stage single nodules of HCC was better than that of DWI. And, MK was the most sensitive predictor among the DKI.