Incoherent Motion Research Articles

Whole tumor based texture analysis of magnetic resonance diffusion imaging for colorectal liver metastases: A prospective study for diffusion model comparison and early response biomarker

PurposeTo evaluate and compare the diagnostic value of diffusion-related texture analysis parameters obtained from various magnetic resonance diffusion models as early predictors of the clinical response to chemotherapy in patients with colorectal liver metastases (CRLM). MethodsPatients (n = 145) with CRLM were prospectively and consecutively enrolled and scanned using diffusion-weighted imaging (DWI)-magnetic resonance imaging (MRI)/intravoxel incoherent motion (IVIM)/diffusion kurtosis imaging (DKI) before (baseline) and two–three weeks after (follow-up) commencing chemotherapy. Therapy response was evaluated based on the Response Evaluation Criteria in Solid Tumors (RECIST, version 1.1). The histogram and texture parameters of each diffusion-related parametric map were analysed between the responding and non-responding groups, screened using LASSO, and fitted with binary logistic regression models. The diagnostic efficacy of each model in the early prediction of CRLM was analysed, and the corresponding receiver operating characteristic (ROC) curve was drawn. The area under the curve (AUC) and 95% confidence intervals (CI) were calculated. ResultsOf the 145 analysed patients, 69 were in the responding group and 76 were in the non-responding group. Among all models, the difference value based on the histogram and texture features of the DKI-derived parameters performed best for the early prediction of CRLM treatment efficacy. The AUC of the DKI model in the validation set reached 0.795 (95% CI 0.652–0.938). Among the IVIM-derived parameters, the difference model based on D and D* performed best, and the AUC in the validation set reached 0.737 (95% CI 0.586–0.889). Finally, in the DWI sequence, the model comprising baseline features performed the best, with an AUC of 0.699 (95% CI 0.537–0.86) in the validation set. ConclusionsBaseline DWI parameters and follow-up changes in IVIM and DKI parameters predicted the chemotherapeutic response in patients with CRLM. In addition, as very early predictors, DKI-derived parameters were more effective than DWI- and IVIM-related parameters, in which changes in D-parameters performed best.

Characterization of parotid gland tumors: Whole-tumor histogram analysis of diffusion weighted imaging, diffusion kurtosis imaging, and intravoxel incoherent motion – A pilot study

PurposeTo investigate the diagnostic performance of histogram features of diffusion parameters in characterizating parotid gland tumors. MethodFrom December 2018 to January 2023, patients who underwent diffusion weighted imaging (DWI), diffusion kurtosis imaging (DKI), and intravoxel incoherent motion (IVIM) were consecutively enrolled in this retrospective study. The histogram features of diffusion parameters, including apparent diffusion coefficient (ADC), diffusion coefficient (Dk), diffusion kurtosis (K), pure diffusion coefficient (D), pseudo-diffusion coefficient (DP), and perfusion fraction (FP) were analyzed. The Mann-Whitney U test was used for comparison between benign parotid gland tumors (BPGTs) and malignant parotid gland tumors (MPGTs). Receiver operating characteristic curve and logistic regression analysis were used to identify the differential diagnostic performance. The Spearman’s correlation coefficient was used to analyze the correlation between diffusion parameters and Ki-67 labeling index. ResultsFor diffusion MRI, twenty-three histogram features of diffusion parameters showed significant differences between BPGTs and MPGTs (all P < 0.05). Compared with the DWI model, the IVIM model and combined model had better diagnostic specificity (58 %, 94 %, and 88 %, respectively; both corrected P < 0.001) and accuracy (64 %, 89 %, and 86 %, respectively; both corrected P = 0.006). The combined model was superior to the single DWI model with improved IDI (IDI improvement 0.25). Significant correlations were found between Ki-67 and ADCmean, Dkmean, Kmean, and Dmean (r = -0.57 to 0.53; all P < 0.05). ConclusionsWhole-tumor histogram analysis of IVIM and combined diffusion model could further improve the diagnostic performance for differentiating BPGTs from MPGTs.

Preoperative Grading of Rectal Cancer with Multiple DWI Models, DWI-Derived Biological Markers, and Machine Learning Classifiers.

Background: this study aimed to utilize various diffusion-weighted imaging (DWI) techniques, including mono-exponential DWI, intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI), for the preoperative grading of rectal cancer. Methods: 85 patients with rectal cancer were enrolled in this study. Mann-Whitney U tests or independent Student's t-tests were conducted to identify DWI-derived parameters that exhibited significant differences. Spearman or Pearson correlation tests were performed to assess the relationships among different DWI-derived biological markers. Subsequently, four machine learning classifier-based models were trained using various DWI-derived parameters as input features. Finally, diagnostic performance was evaluated using ROC analysis with 5-fold cross-validation. Results: With the exception of the pseudo-diffusion coefficient (Dp), IVIM-derived and DKI-derived parameters all demonstrated significant differences between low-grade and high-grade rectal cancer. The logistic regression-based machine learning classifier yielded the most favorable diagnostic efficacy (AUC: 0.902, 95% Confidence Interval: 0.754-1.000; Specificity: 0.856; Sensitivity: 0.925; Youden Index: 0.781). Conclusions: utilizing multiple DWI-derived biological markers in conjunction with a strategy employing multiple machine learning classifiers proves valuable for the noninvasive grading of rectal cancer.

Preoperative detection of lymphovascular invasion in rectal cancer using intravoxel incoherent motion imaging based on radiomics.

Lymphovascular invasion (LVI) status plays an important role in treatment decision-making in rectal cancer (RC). Intravoxel incoherent motion (IVIM) imaging has been shown to detect LVI; however, making better use of IVIM data remains an important issue that needs to be discussed. We proposed to explore the best way to use IVIM quantitative parameters and images to construct radiomics models for the noninvasive detection of LVI in RC. A total of 83 patients (LVI negative (LVI-): LVI positive (LVI+)=51:32) with postoperative pathology-confirmed LVI status in RC were divided into a training group (n=58) and a validation group (n=25). Images were acquired from a 3.0 Tesla machine, including oblique axial T2 weighted imaging (T2WI) and IVIM with 11 b values. The ADC, D, D* and f values were measured on IVIM maps. The ROIs of tumors were delineated on T2WI, DWI, ADCmap , and Dmap images, and three mapping methods were used: ROIs_mapping from DWI, ROIs_mapping from ADCmap , and ROIs_mapping from Dmap . Three-dimensional radiomics features were extracted from the delineated ROIs. Multivariate logistic regression was used for radiomics feature selection. Radiomics models based on different mapping methods were developed. Receiver operating characteristic (ROC) curves, calibration, and decision curve analyses (DCA) were used to evaluate the performance of the models. Model B, which was constructed with radiomics features from ADCmap , Dmap and fmap by "ROIs_mapping from DWI" and T2WI (AUC 0.894), performed better than other models based on single sequence (AUC 0.600-0.806) and even better than Model A, which was based on "ROIs_mapping from ADC" and T2WI (AUC 0.838). Furthermore, an integrated model was constructed with Model B and the IVIM parameter (f value) with an AUC of 0.920 (95% CI: 0.820-1.000), which was higher than that of Model B, in the validation group. The integrated model incorporating the radiomics features and IVIM parameters accurately detected LVI of RC. The "ROIs_mapping from DWI" method provided the best results.

Application of Intravoxel Incoherent Motion in Clinical Liver Imaging: A Literature Review.

Intravoxel incoherent motion (IVIM) modeling is a widely used double-exponential model for describing diffusion-weighted imaging (DWI) signal, with a slow component related to pure molecular diffusion and a fast component associated with microcirculatory perfusion, which compensates for the limitations of traditional DWI. IVIM is a noninvasive technique for obtaining liver pathological information and characterizing liver lesions, and has potential applications in the initial diagnosis and treatment monitoring of liver diseases. Recent studies have demonstrated that IVIM-derived parameters are useful for evaluating liver lesions, including nonalcoholic fatty liver disease (NAFLD), liver fibrosis and liver tumors. However, the results are not stable. Therefore, it is necessary to summarize the current applications of IVIM in liver disease research, identify existing shortcomings, and point out the future development direction. In this review, we searched for studies related to hepatic IVIM-DWI applications over the past two decades in the PubMed database. We first introduce the fundamental principles and influential factors of IVIM, and then discuss its application in NAFLD, liver fibrosis, and focal hepatic lesions. It has been found that IVIM is still unstable in ensuring the robustness and reproducibility of measurements in the assessment of liver fibrosis grade and liver tumors differentiation, due to inconsistent and substantial overlap in the range of IVIM-derived parameters for different fibrotic stages. In the end, the future direction of IVIM-DWI in the assessment of liver diseases is discussed, emphasizing the need for further research on the stability of IVIM-derived parameters, particularly perfusion-related parameters, in order to promote the clinical practice of IVIM-DWI. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 3.

Comparison of image quality and quantitative parameters in intravoxel incoherent motion imaging at 3-T based on turbo spin-echo and echo-planar imaging in patients with oral cancer.

To compare the image quality, apparent diffusion coefficient (ADC), and intravoxel incoherent motion- (IVIM) derived parameters of IVIM imaging based on turbo spin-echo (TSE) and echo-planar imaging (EPI) of patients with oral cancer and to assess the equivalence of the ADC and IVIM-derived parameters. Thirty patients with oral cancer underwent TSE-IVIM and EPI-IVIM imaging using a 3.0-T system. The distortion ratio (DR), signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), qualitative evaluations of image quality, ADC, pure diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) were compared between the two sequences. The consistency of the quantitative parameters in oral cancer between the TSE and EPI sequences was evaluated using a Bland-Altman analysis. TSE-IVIM had a significantly smaller DR than EPI-IVIM (P < 0.001). The CNR of EPI-IVIM on most of the anatomical sites was significantly higher than that of TSE-IVIM (P < 0.05), while the SNR was not significantly different (P > 0.05). TSE-IVIM had significantly higher image quality, less distortion and artifacts, and lower image contrast compared with EPI-IVIM (P < 0.05). The lesion-edge sharpness and diagnostic confidence of EPI-IVIM were lower than that of TSE-IVIM, although no significant differences existed (P > 0.05). The ADC and D of TSE-IVIM had better reproducibility (intraclass correlation coefficient > 0.9). Although no significant difference existed for the ADC and IVIM-derived parameters of lesions between the two sequences (P > 0.05), wide limits of agreement were found in the Bland-Altman plots. TSE-IVIM could be used as an alternative technique to EPI-IVIM for patients with oral cancer because of its better image quality. Furthermore, TSE-IVIM can provide more accurate quantitative parameters. However, the quantitative parameters derived from the two IVIM techniques cannot be used as equivalent parameters for patients with oral cancer.

Relationships between intravoxel incoherent motion parameters and expressions of programmed cell death-1 (PD-1) and programmed cell death ligand-1 (PD-L1) in patients with cervical cancer

To determine the associations of intravoxel incoherent motion (IVIM) parameters with expression of programmed cell death-1 (PD-1) and programmed cell death ligand-1 (PD-L1), and evaluate the performance of the combined model established based on IVIM and clinicopathological parameters in predicting PD-L1and PD-1 status of cervical cancer (CC) patients. Seventy-eight consecutive CC patients were enrolled prospectively and underwent magnetic resonance imaging (MRI) including IVIM. IVIM quantitative parameters were measured, compared, and correlated with PD-L1 and PD-1 expression. Independent factors related to PD-L1 and PD-1 positivity were identified and were used to establish the combined model. The combined model's diagnostic performance was evaluated using the receiver operating characteristic (ROC) analysis. The Shapley additive explanation (SHAP) algorithm was used to explain the contribution of each parameter in the combined model. The real diffusion coefficient (D) value was significantly lower in the PD-L1-positive group than in the PD-L1-negative group (0.64±0.12 versus 0.72±0.11, p=0.021). The PD-1-positive and PD-1-negative groups showed similar trends (0.63±0.13 versus 0.73±0.09, p=0.003). Parametrial invasion, lymph node status, pathological grade, FIGO (International Federation of Gynecology and Obstetrics) staging, and D values were independently associated with PD-L1 and PD-1expression. A combined model incorporating these parameters showed good discrimination with the sensitivity, specificity of 90.9%, 82.6% for PD-L1, and 93.5%, 72% for PD-1. According to the SHAP value, FIGO staging and pathological grade were the most influential features of the prediction model. IVIM parameters were found to correlate with PD-L1 and PD-1 expression. The combined model, incorporating parametrial invasion, lymph node status, pathological grade, FIGO staging, and D values, showed good discrimination in predicting PD-L1 and PD-1 status, providing the basis for CC immunotherapy.

Predicting histopathological types and molecular subtype of breast tumors: A comparative study using amide proton transfer-weighted imaging, intravoxel incoherent motion and diffusion kurtosis imaging

PurposeTo evaluate the predictive performance of multiparameter and histogram features derived from amide proton transfer-weighted imaging (APTWI), intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) for histopathological types of breast tumors. MethodsRegion of interest (ROI) was delineated by outlining the largest slice of the tumor on the false-color images of the DKI, IVIM and APTWI parameters, and extracted the histogram features. Receiver operating characteristic (ROC) curve was used to evaluate the performance of parameters in predicting benign and malignant breast lesions, molecular prognostic biomarkers, lymph node status, and subtypes of breast lesions. The Spearman correlation coefficient was used to determine the correlations between each parameter and clinical-pathological factors. ResultsAll 52 breast lesions were enrolled in this prospective study, including 8 benign lesions and 44 breast cancers. To diagnose malignant and benign breast lesions, the value of APT (min) performed best, with the AUC reaching 0.983. According to the different imaging methods, the APTWI performed best. To predict the positive status of ER, PR, Ki67, the value of Dapp (uniformity), Dapp (uniformity), f (entropy) performed best, with the AUC values reaching 0.743, 0.770, 0.848, respectively. For the identification of Luminal B, HER2-enriched, and TNBC breast cancers, Kapp (max), f (kurtosis), and Dapp (uniformity) performed best, with AUC values reaching 0.679, 0.826, 0.771, respectively. ConclusionThis study found the APTWI, IVIM and DKI parameters could diagnose breast cancer. The histogram features of DKI and IVIM, based on tumor heterogeneity, may help to predict breast cancer subtypes.

Predicting Preoperative Pathologic Grades of Bladder Cancer Using Intravoxel Incoherent Motion and Amide Proton Transfer-Weighted Imaging

To investigate the predictive value of intravoxel incoherent motion (IVIM) combined with amide proton transfer-weighted (APTw) imaging for the preoperative grading of bladder cancer (BC). A total of 69 patients with histopathologically confirmed BC underwent diffusion-weighted imaging (DWI), IVIM, and APTw imaging at 3.0T MRI. Two radiologists independently measured the mean apparent diffusion coefficient (ADC) in DWI, true diffusion coefficient (D), perfusion-related pseudo-diffusion coefficient (D*), and perfusion fraction (f) in IVIM, and APTw values, respectively. The areas under the receiver operating characteristic curves (AUCs) were utilized to compare the diagnostic efficacy of these single and combined quantitative parameters. ADC and D values of low-grade BC were significantly higher than those of high-grade BC ([1.42±0.20×10-3 mm2/s] vs. [1.09±0.25×10-3 mm2/s] and [1.24±0.24×10-3 mm2/s] vs. [0.89±0.18×10-3 mm2/s], respectively; all P<0.001). Opposite patterns were found for APTw ( [1.53±0.42]% vs. [2.38±0.71]%, P<0.001). The ROC curves indicated that the combination of D and APTw values could distinguish low- from high-grades of BC with the highest predictive efficacy (AUC = 0.96), as well as a significant difference compared to those by ADC, D, and APTw values separately(AUC = 0.84, 0.88, 0.85, respectively; all P<0.05). IVIM combined with APTw imaging significantly improved the predictive efficacy of assessing low-and high-grade BC compared to the individual parameters on their own, providing an effective non-invasive method for clinical preoperative prediction of BC grading.

Application of DKI and IVIM imaging in evaluating histologic grades and clinical stages of clear cell renal cell carcinoma.

To evaluate the value of quantitative parameters derived from diffusion kurtosis imaging (DKI) and intravoxel incoherent motion (IVIM) in differentiating histologic grades and clinical stages of clear cell renal cell carcinoma (ccRCC). A total of 65 patients who were surgically and pathologically diagnosed as ccRCC were recruited in this study. In addition to routine renal magnetic resonance imaging examination, all patients underwent preoperative IVIM and DKI. The corresponding diffusion coefficient (D), pseudo-diffusion coefficient (D*), perfusion fraction (f), mean diffusivity (MD), kurtosis anisotropy (KA), and mean kurtosis (MK) values were obtained. Independent-samples t-test or Mann-Whitney U test was used for comparing the differences in IVIM and DKI parameters among different histologic grades and clinical stages. The diagnostic efficacy of IVIM and DKI parameters was evaluated using the receiver operating characteristic (ROC) curve. Spearman's correlation analysis was used to separately analyze the correlation of each parameter with histologic grades and stages of ccRCC. The D and MD values were significantly higher in low-grade ccRCC than high-grade ccRCC (all p < 0.001) and in low-stage than high-stage ccRCC (all p < 0.05), and the f value of high-stage ccRCC was lower than that of low-stage ccRCC (p = 0.007). The KA and MK values were significantly higher in low-grade than high-grade ccRCC (p = 0.000 and 0.000, respectively) and in low-stage than high-stage ccRCC (p = 0.000 and 0.000, respectively). The area under the curve (AUC) values of D, D*, f, MD, KA, MK, DKI, and IVIM+DKI values were 0.825, 0.598, 0.626, 0.792, 0.750, 0.754, 0.803, and 0.857, respectively, in grading ccRCC and 0.837, 0.719, 0.710, 0.787, 0.796, 0.784, 0.864, 0.823, and 0.916, respectively, in staging ccRCC. The AUC of IVIM was 0.913 in staging ccRCC. The D, D*, and MD values were negatively correlated with the histologic grades and clinical stages (all p < 0.05), and the KA and MK values showed a positive correlation with histologic grades and clinical stages (all p < 0.05). The f value was also negatively correlated with the ccRCC clinical stage (p = 0.008). Both the IVIM and DKI values can be used preoperatively to predict the degree of histologic grades and stages in ccRCC, and the D and MD values have better diagnostic performance in the grading and staging. Also, further slightly enhanced diagnostic efficacy was observed in the model with combined IVIM and DKI parameters.

Machine Learning-Based Models for Assessing Postoperative Risk Factors in Patients with Cervical Cancer

To investigate the value of machine learning-based radiomics, intravoxel incoherent motion (IVIM) diffusion-weighted imaging and its combined model in predicting the postoperative risk factors of parametrial infiltration (PI), lymph node metastasis (LNM), deep muscle invasion (DMI), lymph-vascular space invasion (LVSI), pathological type (PT), differentiation degree (DD), and Ki-67 expression level in patients with cervical cancer. The data of 180 patients with cervical cancer were retrospectively analyzed and randomized 2:1 into a training and validation group. The IVIM-DWI and radiomics parameters of primary lesions were measured in all patients. Seven machine learning methods were used to calculate the optimal radiomics score (Rad-score), which was combined with IVIM-DWI and clinical parameters to construct nomograms for predicting the risk factors of cervical cancer, with internal and external validation. The diagnostic efficacy of the nomograms based on clinical and imaging parameters wassignificantly better than MRI assessment alone. The area under the curve (AUC) of nomograms and MRI for the assessment of PI, LNM, and DMI were 0.981 vs 0.868, 0.848 vs 0.639, and 0.896 vs 0.780, respectively. Nomograms also performed well in the assessment of LVSI, PT, DD, and Ki-67 expression levels, with AUC of 0.796, 0.854, 0.806, 0.839 and 0.840, 0.856, 0.810, 0.832 in the training and validation groups. Machine learning-based nomograms can serve as a useful tool for assessing postoperative risk factors in patients with cervical cancer.

Highly accelerated multi-shot intravoxel incoherent motion diffusion-weighted imaging in brain enabled by parametric POCS-based multiplexed sensitivity encoding.

Recently, intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) has also been demonstrated as an imaging tool for applications in neurological and neurovascular diseases. However, the use of single-shot diffusion-weighted echo-planar imaging for IVIM DWI acquisition leads to suboptimal data quality: for instance, geometric distortion and deteriorated image quality at high spatial resolution. Although the recently commercialized multi-shot acquisition methods, such as multiplexed sensitivity encoding (MUSE), can attain high-resolution and high-quality DWI with signal-to-noise ratio (SNR) performance superior to that of the conventional parallel imaging method, the prolonged scan time associated with multi-shot acquisition is impractical for routine IVIM DWI. This study proposes an acquisition and reconstruction framework based on parametric-POCSMUSE to accelerate the four-shot IVIM DWI with 70% reduction of total scan time (13 min 8 s versus 4 min 8 s). First, the four-shot IVIM DWI scan with 17 b values was accelerated by acquiring only one segment per b value except for b values of 0 and 600 s/mm2 . Second, an IVIM-estimation scheme was integrated into the parametric-POCSMUSE to enable joint reconstruction of multi-b images from under-sampled four-shot IVIM DWI data. In vivo experiments on both healthy subjects and patients show that the proposed framework successfully produced multi-b DW images with significantly higher SNRs and lower reconstruction errors than did the conventional acceleration method based on parallel imaging. In addition, the IVIM quantitative maps estimated from the data produced by the proposed framework showed quality comparable to that of fully sampled MUSE-reconstructed images, suggesting that the proposed framework can enable highly accelerated multi-shot IVIM DWI without sacrificing data quality. In summary, the proposed framework can make multi-shot IVIM DWI feasible in a routine MRI examination, with reasonable scan time and improved geometric fidelity.

Amide Proton Transfer-Weighted Imaging and Multiple Models Intravoxel Incoherent Motion-Based 18F-FDG PET/MRI for Predicting Progression-Free Survival in Non-Small Cell Lung Cancer.

Amide proton transfer-weighted imaging (APTWI) and multiple models intravoxel incoherent motion (IVIM) based 18F-FDG PET/MR could reflect the microscopic information of the tumor from multiple perspectives. However, its value in the prognostic assessment of non-small cell lung cancer (NSCLC) still needs to be further explored. To determine whether pretreatment APTWI, mono-, bi-, and stretched-exponential model IVIM, and 18F-FDG PET-derived parameters of the primary lesion may be associated with progression-free survival (PFS) in NSCLC. Prospective. Seventy-seven patients (mean age, 62 years, range, 20-81 years) with 37 men and 40 women were included. 3.0 T 18F-FDG PET/MRI, single shot echo planar imaging sequences for IVIM and fast spin-echo sequences with magnetization transfer pulses for APTWI. Patient clinical characteristics (age, sex, smoke, subtype, TNM stage, and surgery), PFS (chest CT every 3 months, median follow-up was 18 months, range, 4-27 months), and APTWI (MTRasym(3.5 ppm)), IVIM (ADCstand, D, D*, f, DDC, and α), and 18F-FDG PET (SUVmax, MTV, and TLG) parameters were recorded. Proportional hazards model, concordance index, calibration curve, decision curve analysis (DCA), and Log-rank test. A P value <0.05 was considered statistically significant. Histological subtype, TNM stage, MTV, D*, and MTRasym(3.5 ppm) were all independent predictors of PFS. A prediction model based on these predictors was developed with a C-index of 0.895 (95% CI: 0.839-0.951), which was significantly superior to each of the above predictors alone (C-index = 0.629, 0.707, 0.692, 0.678, and 0.558, respectively). The calibration curve and DCA indicated good consistency and clinical utility of the prediction model, respectively. Log-rank test results showed a significant difference in PFS between the high- and low-risk groups. APTWI and multiple models IVIM based 18F-FDG PET/MRI can be used for PFS assessment in NSCLC. 3 TECHNICAL EFFICACY: Stage 2.

Intravoxel incoherent motion imaging to assess the acute effects of moderate-intensity continuous training and high-intensity interval training on thigh muscles.

This study investigated the use of intravoxel incoherent motion imaging (IVIM) to compare skeletal muscle perfusion during and after high-intensity interval training (HIIT) and moderate-intensity continuous training (MICT) to determine the impact on fat oxidation outcomes. Twenty overweight volunteers were recruited for the study. Each participant received one HIIT intervention and one MICT intervention using a cycling ergometer. Participants underwent a magnetic resonance imaging scan before, immediately after, and 1 and 2 h after each intervention. The IVIM parameters (D, fD*) of the rectus femoris, vastus lateralis, and biceps femoris long head were obtained. Changes in IVIM parameters of these muscles after both exercise interventions were compared using a two-factor repeated measures analysis of variance. In the rectus femoris, the fD* increased immediately after exercise intervention (d = 0.69 × 10-3 mm2 /s, p < 0.0083) and 2h after exercise intervention (d = 0.64 × 10-3 mm2 /s, p < 0.0083) compared with before exercise. The increase in the fD* in the HIIT group was greater than that in the MICT group (d = 0.32, p = 0.023). In the vastus lateralis, the fD* increased immediately after the exercise intervention (d = 0.53 × 10-3 mm2 /s, p < 0.001) and returned to the pre-exercise level 1h after exercising. The increase in the fD* in the HIIT group was lower than that in the MICT group (d = -0.21, p = 0.015). For the biceps femoris long head, the fD* was not significantly different between the two exercise interventions before and after exercise. Furthermore, the fD* 60min after the HIIT intervention correlated with maximal oxygen consumption (VO2max), whereas fD* immediately after the MICT intervention correlated with VO2max. In summary, IVIM parameters can be used to evaluate differences in muscle perfusion between HIIT and MICT, and show a correlation with VO2max.

Using the non-distortion IVIM to reduce the need for contrast agents in nasopharyngeal MRI

BackgroundPatients with nasopharyngeal carcinoma (NPC) who undergo longitudinal follow-up contrast-enhanced MRI are at risk of developing gadolinium deposition in their neural tissue, which may potentially harm them. Therefore, for these patients, a non-contrast-enhanced method is potentially beneficial as an alternative approach to predict enhancement in T1-weighted imaging (CE-T1WI). The traditional intravoxel incoherent motion (IVIM) is one of the non-contrast-enhanced methods; however, the severe distortion and signal loss limit its application in patients with NPC. The present study aimed to investigate whether non-distortion IVIM could reduce the need of CE-T1WI in the follow-up of patients with NPC. MethodsThe patients with NPC underwent Turbo Spin-echo MVXD diffusion-weighted imaging-based IVIM (non-distortion IVIM) from November 2021 to May 2022. Firstly, thirty patients with NPC were underwent both non-distortion IVIM and traditional IVIM. The distortion rate (DR) of the non-distortion IVIM was compared with the traditional IVIM. Then, twenty-one NPC patients with tumors (areas >50mm2) were included and correlation coefficient analysis was used to assess the relationship between their non-distortion IVIM and CE-T1WI. Linear regression analysis was performed to determine whether non-distortion IVIM predictors could predict CE-T1WI. ResultsThe correlation was observed between the parameter f of the non-distortion IVIM and the enhancement ratio of CE-T1WI (r = 0.543, P = 0.011). Moreover, the linear regression analysis revealed that f was an independent IVIM predictor of CE-T1WI in patients with NPC (P = 0.011). The DR of the non-distortion IVIM was significantly smaller than that of the traditional IVIM (0.12 ± 0.05 vs 0.48 ± 0.16, P < 0.001). ConclusionsIn patients with NPC, non-distortion IVIM showed potential clinical benefits to reduce the need for contrast agents, and it can independently predict the enhancement ratio.

The dependence of cerebral interstitial fluid on diffusion-sensitizing directions: A multi-b-value diffusion MRI study in a memory clinic sample

Three-component intravoxel incoherent motion (3C-IVIM) imaging with spectral analysis provides a proxy for interstitial fluid (ISF) (e.g., in perivascular spaces (PVS), granting a potential marker for altered cerebral clearance. When 3C-IVIM images are acquired with three orthogonal diffusion-sensitizing directions, these are often averaged into the Trace image. This may result in loss of valuable direction-specific information, particularly in PVS-rich regions (basal ganglia (BG) and centrum semiovale (CSO)).This study assessed the dependence of individual diffusion-sensitizing directions to the ISF fraction in PVS-rich regions. Additionally, we explored the value of diffusion direction-specific information on ISF characteristics in distinguishing thirty-one patients with cognitive impairment (CI) (Alzheimer's disease (n = 15) or Mild Cognitive Impairment (n = 16)) from thirty cognitively healthy elderly controls (CON). Multi-b-value diffusion-weighted images were acquired in three orthogonal directions (L-R (left-right), A-P (anterior-posterior) and S-I (superior-inferior)) at 3 T. Voxel-based spectral analysis using non-negative least squares was conducted to independently analyze the L-R, A-P, S-I, and Trace images. 3C-IVIM measures were first compared between diffusion-sensitizing directions and the Trace within the BG using repeated measures ANOVA. Subsequently, the 3C-IVIM measures were compared per direction between the CI and CSO group in the BG and CSO with multivariable linear regression.Our results show that the ISF fraction significantly differs between all diffusion-sensitizing directions and Trace in the BG, with the highest ISF fraction detected using S-I. Solely using S-I, a higher ISF fraction was identified in CI compared to CON in the BG (p = .020) and CSO (p = .046).Thereby, this study found that the measured ISF fraction depends on the acquired diffusion-sensitizing direction, where S-I is most sensitive to detect ISF and differences between CI and CON. The Trace approach is not always sensitive enough to ISF characteristics. Solely acquiring S-I may offer an alternative to reduce scanning time.

Comparison between Intravoxel Incoherent Motion and Splenic Volumetry to Predict Hepatic Fibrosis Staging in Preoperative Patients.

Intravoxel incoherent motion (IVIM) and splenic volumetry (SV) for hepatic fibrosis (HF) prediction have been reported to be effective. Our purpose is to compare the HF prediction of IVIM and SV in 67 patients with pathologically staged HF. SV was divided by body surface area (BSA). IVIM indices, such as slow diffusion-coefficient related to molecular diffusion (D), fast diffusion-coefficient related to perfusion in microvessels (D*), apparent diffusion-coefficient (ADC), and perfusion related diffusion-fraction (f), were calculated by two observers (R1/R2). D (p = 0.718 for R1, p = 0.087 for R2) and D* (p = 0.513, p = 0.708, respectively) showed a poor correlation with HF. ADC (p = 0.034, p = 0.528, respectively) and f (p < 0.001, p = 0.007, respectively) decreased as HF progressed, whereas SV/BSA increased (p = 0.015 for R1). The AUCs of SV/BSA (0.649-0.698 for R1) were higher than those of f (0.575-0.683 for R1 + R2) for severe HF (≥F3-4 and ≥F4), although AUCs of f (0.705-0.790 for R1 + R2) were higher than those of SV/BSA (0.628 for R1) for mild or no HF (≤F0-1). No significant differences to identify HF were observed between IVIM and SV/BSA. SV/BSA allows a higher estimation for evaluating severe HF than IVIM. IVIM is more suitable than SV/BSA for the assessment of mild or no HF.

Non-contrast based approach for liver function quantification using Bayesian-based intravoxel incoherent motion diffusion weighted imaging: A pilot study.

Liver cirrhosis disrupts liver function and tissue perfusion, detectable by magnetic resonance imaging (MRI). Assessing liver function at the voxel level with 13-b value intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) could aid in radiation therapy liver-sparing treatment for patients with early impairment. This study aimed to evaluate the feasibility of IVIM-DWI for liver function assessment and correlate it with other multiparametric (mp) MRI methods at the voxel level. This study investigates the variability of apparent diffusion coefficient (ADC) derived from 13-b value IVIM-DWI and B1-corrected dual flip angle (DFA) T1 mapping. Experiments were conducted in-vitro with QIBA and NIST phantoms and in 10 healthy volunteers for IVIM-DWI. Additionally, 12 patients underwent an mp-MRI examination. The imaging protocol included a 13-b value IVIM-DWI sequence for generating IVIM parametric maps. B1-corrected DFA T1 pulse sequence was used for generating T1 maps, and Gadoxatate low temporal resolution dynamic contrast-enhanced (LTR-DCE) MRI was used for generating the Hepatic extraction fraction (HEF) map. The Mann-Whitney U test was employed to compare IVIM-DWI parameters (Pure Diffusion, Dslow ; Pseudo diffusion, Dfast ; and Perfusion Fraction, Fp ) between the healthy volunteer and patient groups. Furthermore, in the patient group, statistical correlations were assessed at a voxel level between LTR-DCE MRI-derived HEF, T1 post-Gadoxetate administration, ΔT1%, and various IVIM parameters using Pearson correlation. For-vitro measurements, the maximum coefficient of variation of the ADC and T1 parameters was 12.4% and 16.1%, respectively. The results also showed that Fp and Dfast were able to distinguish between healthy liver function and mild liver function impairment at the global level, with p=0.002 for Fp and p<0.001 for Dfast . Within the patient group, these parameters also exhibited a moderate correlation with HEF at the voxel level. Overall, the study highlighted the potential of Dfast and Fp for detecting liver function impairment at both global and pixel levels.

Value of Multimodal Diffusion-weighted Imaging in Preoperative Evaluation of Ki-67 Expression in Endometrial Carcinoma.

To investigate the value of multimodal diffusion weighted imaging (DWI) in preoperative evaluation of Ki-67 expression of endometrial carcinoma (EC). Patients who had undergone pelvic DWI, intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI) sequence MRI scan before surgery were retrospectively enrolled. Single index model, double index model, and DKI were used for post-processing of the DWI data, and the apparent diffusion coefficient (ADC), real diffusion coefficient (D), pseudo diffusion coefficient (D*), perfusion fraction (f), non-Gaussian mean diffusion kurtosis (MK), mean diffusion coefficient (MD) and anisotropy fraction (FA) were calculated and compared between the Ki-67 high (≥50%) and low (<50%) expression groups. Forty-two patients with a median age of 56 (range 37 - 75) years were enrolled, including 15 patients with a high Ki-67 (≥50%) expression and 27 with a low Ki-67 (<50%) expression. The MK (0.91 ± 0.12 vs. 0.76 ± 0.12) was significantly (P<0.05) higher while MD (0.99 ± 0.17 vs. 1.16 ± 0.22), D (0.55 ± 0.06 vs. 0.62 ± 0.08), and f (0.21 vs. 0.28) were significantly (P<0.05) lower in the high than in the low expression group. The combined model of MK, MD, D, and f-values had the largest area under the curve (AUC) value of 0.869 (95% CI: 0.764-0.974), sensitivity 0.733 and specificity 0.852, followed by the MK value with an AUC value 0.827 (95% CI: 0.700-0.954), sensitivity 0.733 and specificity 0.815. IVIM and DKI have certain diagnostic values for preoperative evaluation of the EC Ki-67 expression, and the combined model has the highest diagnostic efficiency.

The Relationship Between Conventionally Obtained Serum-Based Liver Function Indices and Intravoxel Incoherent Motion Diffusion-Weighted Imaging and Magnetic Resonance Elastography in Patients With Hepatocellular Carcinoma.

To investigate the relationship between conventionally obtained serum-based biochemical indices and intravoxel incoherent motion imaging (IVIM) parameters compared with magnetic resonance elastography (MRE). Patients with hepatocellular carcinoma who underwent ≥2 liver magnetic resonance imaging (MRI) scan, including IVIM and MRE, between 2017 and 2020 and biochemical testing within 1 week before or after MRI were included in this study. Biochemical tests were performed to determine the albumin-bilirubin (ALBI) score and modified ALBI (mALBI) grade, aspartate aminotransferase to platelet ratio index (APRI), and fibrosis-4 index (FIB-4). The diffusion coefficient ( D ), pseudo-diffusion coefficient ( D *), fractional volume occupied by flowing spins ( f ), and apparent diffusion coefficient were calculated for IVIM. The correlations between (1) the imaging parameters and biochemical indices and (2) the changes in mALBI grades and imaging parameters were evaluated. This study included 98 scans of 40 patients (31 men; mean age, 67.7 years). The correlation analysis between the biochemical and IVIM parameters showed that ALBI score and D* had the best correlation ( r = -0.3731, P < 0.001), and the correlation was higher than that with MRE ( r = 0.3289, P < 0.001). However, among FIB-4, APRI, and MRI parameters, MRE outperformed IVIM parameters (MRE and FIB-4, r = 0.3775, P < 0.001; MRE and APRI, r = 0.4687, P < 0.001). There were significant differences in the changes in MRE among the 3 groups (improved, deteriorated, and unchanged mALBI groups) in the analysis of covariance ( P = 0.0434). There were no significant changes in IVIM. Intravoxel incoherent motion imaging has the potential to develop into a more readily obtainable method of liver function assessment.