Simplified perfusion fraction from diffusion-weighted imaging in preoperative prediction of IDH1 mutation in WHO grade II–III gliomas: comparison with dynamic contrast-enhanced and intravoxel incoherent motion MRI

Effect of isocitr ate dehydrogenase 1 (IDH1) mutation in neovascularization might be linked with tissue perfusion in gliomas. At present, the need of injection of contrast agent and the increasing scanning time limit the application of perfusion techniques. We used a simplified intravoxel incoherent motion (IVIM)-derived perfusion fraction (SPF) calculated from diffusion-weighted imaging (DWI) using only three b-values to quantitatively assess IDH1-linked tissue perfusion changes in WHO grade II-III gliomas (LGGs). Additionally, by comparing accuracy with dynamic contrast-enhanced (DCE) and full IVIM MRI, we tried to find the optimal imaging markers to predict IDH1 mutation status

Qualitative and Quantitative MRI Analysis in IDH1 Genotype Prediction of Lower-Grade Gliomas: A Machine Learning Approach

Purpose. Preoperative prediction of isocitrate dehydrogenase 1 (IDH1) mutation in lower-grade gliomas (LGGs) is crucial for clinical decision-making. This study aimed to examine the predictive value of a machine learning approach using qualitative and quantitative MRI features to identify the IDH1 mutation in LGGs. Materials and Methods. A total of 102 LGG patients were allocated to training (n=67) and validation (n=35) cohorts and were subject to Visually Accessible Rembrandt Images (VASARI) feature extraction (23 features) from conventional multimodal MRI and radiomics feature extraction (56 features) from apparent diffusion coefficient maps. Feature selection was conducted using the maximum Relevance Minimum Redundancy method and 0.632+ bootstrap method. A machine learning model to predict IDH1 mutation was then established using a random forest classifier. The predictive performance was evaluated using receiver operating characteristic (ROC) curves. Results. After feature selection, the top 5 VASARI features were enhancement quality, deep white matter invasion, tumor location, proportion of necrosis, and T1/FLAIR ratio, and the top 10 radiomics features included 3 histogram features, 3 gray-level run-length matrix features, and 3 gray-level size zone matrix features and one shape feature. Using the optimal VASARI or radiomics feature sets for IDH1 prediction, the trained model achieved an area under the ROC curve (AUC) of 0.779±0.001 or 0.849±0.008 on the validation cohort, respectively. The fusion model that integrated outputs of both optimal VASARI and radiomics models improved the AUC to 0.879. Conclusion. The proposed machine learning approach using VASARI and radiomics features can predict IDH1 mutation in LGGs

Application of a Simplified Method for Estimating Perfusion Derived from Diffusion-Weighted MR Imaging in Glioma Grading

Purpose: To evaluate the feasibility of a simplified method based on diffusion-weighted imaging (DWI) acquired with three b-values to measure tissue perfusion linked to microcirculation, to validate it against from perfusion-related parameters derived from intravoxel incoherent motion (IVIM) and dynamic contrast-enhanced (DCE) magnetic resonance (MR) imaging, and to investigate its utility to differentiate low- from high-grade gliomas.Materials and Methods: The prospective study was approved by the local institutional review board and written informed consent was obtained from all patients. From May 2016 and May 2017, 50 patients confirmed with glioma were assessed with multi-b-value DWI and DCE MR imaging at 3.0 T. Besides conventional apparent diffusion coefficient (ADC0,1000) map, perfusion-related parametric maps for IVIM-derived perfusion fraction (f) and pseudodiffusion coefficient (D*), DCE MR imaging-derived pharmacokinetic metrics, including Ktrans, ve and vp, as well as a metric named simplified perfusion fraction (SPF), were generated. Correlation between perfusion-related parameters was analyzed by using the Spearman rank correlation. All imaging parameters were compared between the low-grade (n = 19) and high-grade (n = 31) groups by using the Mann-Whitney U test. The diagnostic performance for tumor grading was evaluated with receiver operating characteristic (ROC) analysis.Results: SPF showed strong correlation with IVIM-derived f and D* (ρ = 0.732 and 0.716, respectively; both P < 0.001). Compared with f, SPF was more correlated with DCE MR imaging-derived Ktrans (ρ = 0.607; P < 0.001) and vp (ρ = 0.397; P = 0.004). Among all parameters, SPF achieved the highest accuracy for differentiating low- from high-grade gliomas, with an area under the ROC curve value of 0.942, which was significantly higher than that of ADC0,1000 (P = 0.004). By using SPF as a discriminative index, the diagnostic sensitivity and specificity were 87.1% and 94.7%, respectively, at the optimal cut-off value of 19.26%.Conclusion: The simplified method to measure tissue perfusion based on DWI by using three b-values may be helpful to differentiate low- from high-grade gliomas. SPF may serve as a valuable alternative to measure tumor perfusion in gliomas in a noninvasive, convenient and efficient way

Evaluation of skeletal muscle microvascular perfusion of lower extremities by cardiovascular magnetic resonance arterial spin labeling, blood oxygenation level-dependent, and intravoxel incoherent motion techniques

Abstract Background Noninvasive cardiovascular magnetic resonance (CMR) techniques including arterial spin labeling (ASL), blood oxygenation level-dependent (BOLD), and intravoxel incoherent motion (IVIM), are capable of measuring tissue perfusion-related parameters. We sought to evaluate and compare these three CMR techniques in characterizing skeletal muscle perfusion in lower extremities and to investigate their abilities to diagnose and assess the severity of peripheral arterial disease (PAD). Methods Fifteen healthy young subjects, 14 patients with PAD, and 10 age-matched healthy old subjects underwent ASL, BOLD, and IVIM CMR perfusion imaging. Healthy young and healthy old participants were subjected to a cuff-induced ischemia experiment with pressures of 20 mmHg and 40 mmHg above systolic pressure during imaging. Perfusion-related metrics, including blood flow, T2* relaxation time, perfusion fraction f, diffusion coefficient D, and pseudodiffusion coefficient D*, were measured in the anterior, lateral, soleus, and gastrocnemius muscle groups. Friedman, Mann-Whitney, Wilcoxon signed rank, and Spearman rank correlation tests were used for statistical analysis. Results In cases of significant differences determined by the Friedman test (P  0.05). Blood flow and T2* values showed significant positive correlations with transcutaneous oxygen pressure measurements (ρ = 0.465 and 0.522, respectively; both P ≤ 0.001), while f values showed a significant negative correlation in healthy young subjects (ρ = − 0.351; P = 0.018). T2* was independent of age in every muscle group. T2* values were significantly decreased in PAD patients compared with healthy old subjects and severe PAD patients compared with mild-to-moderate PAD patients (all P < 0.0125). Significant correlations were found between T2* and ankle–brachial index values in all muscle groups in PAD patients (ρ = 0.644–0.837; all P < 0.0125). Other imaging parameters failed to show benefits towards the diagnosis and disease severity evaluation of PAD. Conclusions ASL, BOLD, and IVIM provide complementary information regarding tissue perfusion. Compared with ASL and IVIM, BOLD may be a more reliable technique for assessing PAD in the resting state and could thus be applied together with angiography in clinical studies as a tool to comprehensively assess microvascular and macrovascular properties in PAD patients

Additional file 2: of Evaluation of skeletal muscle microvascular perfusion of lower extremities by cardiovascular magnetic resonance arterial spin labeling, blood oxygenation level-dependent, and intravoxel incoherent motion techniques

Figure S2. Graphs depicting serial measurements of imaging parameters from ASL, BOLD, and IVIM for the anterior, lateral, soleus, and gastrocnemius muscle groups in the control side in healthy young subjects. (PPTX 727 kb

Additional file 4: of Evaluation of skeletal muscle microvascular perfusion of lower extremities by cardiovascular magnetic resonance arterial spin labeling, blood oxygenation level-dependent, and intravoxel incoherent motion techniques

Table S1. Spearman rank correlation coefficients for ASL, BOLD, and IVIM imaging parameters. (DOCX 16 kb

Additional file 3: of Evaluation of skeletal muscle microvascular perfusion of lower extremities by cardiovascular magnetic resonance arterial spin labeling, blood oxygenation level-dependent, and intravoxel incoherent motion techniques

Figure S3. Graphs depicting serial measurements of imaging parameters from ASL, BOLD, and IVIM for the anterior, lateral, soleus, and gastrocnemius muscle groups in the control side in healthy old subjects. (PPTX 654 kb