BACKGROUND: Osteoporosis (OP) is a common chronic metabolic bone disease characterized by decreased bone mineral content and microstructural damage, leading to increased fracture risk. Traditional methods for measuring bone density have limitations in accurately distinguishing vertebral bodies and are influenced by vertebral degeneration and surrounding tissues. Therefore, novel methods are needed to quantitatively assess changes in bone density and improve the accurate diagnosis of OP.
METHODS: This study aimed to explore the applicative value of the iterative decomposition of water and fat with echo asymmetry and least-squares estimation-iron (IDEAL-IQ) sequence combined with intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) for the diagnosis of osteoporosis. Data from 135 patients undergoing dual-energy X-ray absorptiometry (DXA), IDEAL-IQ, and IVIM-DWI were prospectively collected and analyzed. Various parameters obtained from IVIM-DWI and IDEAL-IQ sequences were compared, and their diagnostic efficacy was evaluated.
RESULTS: Statistically significant differences were observed among the three groups for FF, R2*, f, D, DDC values, and BMD values. FF and f values exhibited negative correlations with BMD values, with r=-0.313 and - 0.274, respectively, while R2*, D, and DDC values showed positive correlations with BMD values, with r = 0.327, 0.532, and 0.390, respectively. Among these parameters, D demonstrated the highest diagnostic efficacy for osteoporosis (AUC = 0.826), followed by FF (AUC = 0.713). D* exhibited the lowest diagnostic performance for distinguishing the osteoporosis group from the other two groups. Only D showed a significant difference between genders. The AUCs for IDEAL-IQ, IVIM-DWI, and their combination were 0.74, 0.89, and 0.90, respectively.
CONCLUSIONS: IDEAL-IQ combined with IVIM-DWI provides valuable information for the diagnosis of osteoporosis and offers evidence for clinical decisions. The superior diagnostic performance of IVIM-DWI, particularly the D value, suggests its potential as a more sensitive and accurate method for diagnosing osteoporosis compared to IDEAL-IQ. These findings underscore the importance of integrating advanced imaging techniques into clinical practice for improved osteoporosis management and highlight the need for further research to explore the full clinical implications of these imaging modalities.

Intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) is considered a potential marker of hepatic fibrosis (HF).
To explore the influencing factors of repeatability and reliability in IVIM-DWI parameters of ROI-based liver segments in participants with HF and healthy volunteers (HV) and to assess the diagnostic efficiency of these parameters in HF.
Participants with early HF (EHF, n=59) or advanced HF (AHF, n=38) and HV (n=48) were recruited. Two examiners measured IVIM data using mono-, bi-exponential and stretched exponential models. The results and influencing factors of repeatability and reliability of IVIM-DWI, and the diagnostic efficiency were analyzed.
The repeatability of D* (CV: 26.62-41.47%) and DDC (CV: 18.01-34.40%) was poor, the repeatability of ADC (CV: 4.95-9.76%), D (CV: 7.09-15.52%), f (CV: 9.35-17.15%), and α (CV: 7.48-13.81%) was better; ordered logistic regression showed statistically significant results of IVIM-derived parameters; the reliability showed no obvious trend, and ordered logistic regression showed statistically significant results of IVIMderived parameters, groups, and partial hepatic segments (all p<0.001). IVIM-derived parameters with relatively good repeatability (CV<20%) and reliability (ICC>0.4) were used to establish regression models for differential diagnosis. The AUC of regression models was 0.744-0.783 (EHF vs. AHF), but no statistically significant parameters were found in the HV vs EHF comparison.
IVIM-derived parameters were the most important factors affecting the repeatability and reliability, while staging of HF and hepatic segments may be the influencing factors of reliability. IVIM-derived parameters showed medium diagnostic efficiency in distinguishing between EHF and AHF.

Angiogenesis inhibitors have been identified to improve the efficacy of immunotherapy in recent studies. However, the delayed therapeutic effect of immunotherapy poses challenges in treatment planning. Therefore, this study aims to explore the potential of non-invasive imaging techniques, specifically intravoxel-incoherent-motion diffusion-weighted imaging (IVIM-DWI) and blood oxygenation level-dependent magnetic resonance imaging (BOLD-MRI), in detecting the anti-tumor response to the combination therapy involving immune checkpoint blockade therapy and anti-angiogenesis therapy in a tumor-bearing animal model.
The C57BL/6 mice were implanted with murine MC-38 cells to establish colon cancer xenograft model, and randomly divided into the control group, anti-PD-1 therapy group, and combination therapy group (VEGFR-2 inhibitor combined with anti-PD-1 antibody treatment). All mice were imaged before and, on the 3rd, 6th, 9th, and 12th day after administration, and pathological examinations were conducted at the same time points.
The combination therapy group effectively suppressed tumor growth, exhibiting a significantly higher tumor inhibition rate of 69.96% compared to the anti-PD-1 group (56.71%). The f value and D* value of IVIM-DWI exhibit advantages in reflecting tumor angiogenesis. The D* value showed the highest correlation with CD31 (r = 0.702, P = 0.001), and the f value demonstrated the closest correlation with vessel maturity (r = 0.693, P = 0.001). While the BOLD-MRI parameter, R2* value, shows the highest correlation with Hif-1α(r = 0.778, P < 0.001), indicating the capability of BOLD-MRI to evaluate tumor hypoxia. In addition, the D value of IVIM-DWI is closely related to tumor cell proliferation, apoptosis, and infiltration of lymphocytes. The D value was highly correlated with Ki-67 (r = - 0.792, P < 0.001), TUNEL (r = 0.910, P < 0.001) and CD8a (r = 0.918, P < 0.001).
The combination of VEGFR-2 inhibitors with PD-1 immunotherapy shows a synergistic anti-tumor effect on the mouse colon cancer model. IVIM-DWI and BOLD-MRI are expected to be used as non-invasive approaches to provide imaging-based evidence for tumor response detection and efficacy evaluation.

This study aimed to construct an imaging genomics nomogram based on intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) to predict the status of the alpha thalassemia/mental retardation syndrome X-linked (ATRX) gene in patients with brain gliomas. We retrospectively analyzed routine MR and IVIM-DWI data from 85 patients with pathologically confirmed brain gliomas from January 2017 to May 2023. The data were divided into a training set (N=61) and a test set (N=24) in a 7:3 ratio. Regions of interest (ROIs) of brain gliomas, including the solid tumor region (rCET), edema region (rE), and necrotic region (rNec), were delineated using 3D-Slicer software and projected onto the D, D*, and f sequences. A total of 1037 features were extracted from each ROI, resulting in 3111 features per patient. Age was incorporated in the calculation of the Radscore, and a clinical-imaging genomics combined model was constructed, from which a nomogram graph was generated. Separate models were built for the D, D*, and f parameters. The AUC value of the D parameter model was 0.97 (95% CI: 0.93-1.00) in the training set and 0.91 (95% CI: 0.79-1.00) in the validation set, which was significantly higher than that of the D* parameter model (0.90, 0.82) and the f parameter model (0.89, 0.91). The imaging genomics nomogram based on IVIM-DWI can effectively predict the ATRX gene status of patients with brain gliomas, with the D parameter showing the highest efficacy.

OBJECTIVE: Trastuzumab is an important targeted drug for HER2-positive gastric cancer. The treatment efficacy of a more cost-effective and accessible trastuzumab biosimilar, HLX02, was not well investigated, especially when combined with antiangiogenic treatment. In addition, the tumour microenvironment detected by functional MRI was still unclear during treatment. This study attempts to evaluate the therapeutic effect of antiangiogenic agents combined with HLX02 in a HER2-positive gastric cancer xenograft model and to detect microenvironmental changes using intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI).
METHODS: We subcutaneously injected MKN-45 human gastric cancer cells into BALB/C nude mice to establish a tumour model. Twenty-eight mice were divided into four groups and treated with saline (Group 1), Endostar (Group 2), trastuzumab biosimilar HLX02 (Group 3), or the combination of Endostar and HLX02 (Group 4). We then performed IVIM-DWI before and at different time points after treatment. HE, HER2, TUNEL, E-cadherin staining, and α-SMA and CD31 double-staining were used to confirm the pathological changes.
RESULTS: Group 4 demonstrated the smallest tumour volume at the end of treatment. The D value in Group 4 increased more dramatically, with the highest value on Day 20, compared with the other groups. Perfusion-related parameters (D* and f values) in Groups 2 and 4 increased initially and reversed after Day 10. Group 4 showed the lowest CD31 and HER2 and the highest TUNEL- and E-cadherin-positive staining rates. The D value was positively correlated with TUNEL but negatively correlated with HER2 staining. The D* and f values had positive correlations with CD31 and E-cadherin expression and the vessel maturity index.
CONCLUSIONS: The trastuzumab biosimilar drug HLX02 exhibited good treatment efficacy in HER2-positive gastric cancer, especially when combined with Endostar. IVIM-DWI can noninvasively monitor the process of vascular normalization and reflect the treatment effect early at the molecular level.

UNASSIGNED: This study aims to evaluate the accuracy of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) in distinguishing malignant and benign solitary pulmonary nodules and masses.
UNASSIGNED: Studies investigating the diagnostic accuracy of IVIM-DWI in lung lesions published through December 2020 were searched. The standardized mean differences (SMDs) of the apparent diffusion coefficient (ADC), tissue diffusivity (D), pseudo-diffusivity (D*), and perfusion fraction (f) were calculated. The sensitivity, specificity, area under the curve (AUC), publication bias, and heterogeneity were then summarized, and the source of heterogeneity and the reliability of combined results were explored by meta-regression and sensitivity analysis.
UNASSIGNED: A total of 16 studies including 714 malignant and 355 benign lesions were included. Significantly lower ADC, D, and f values were found in malignant pulmonary lesions compared to those in benign lesions. The D value showed the best diagnostic performance (sensitivity = 0.90, specificity = 0.71, AUC = 0.91), followed by ADC (sensitivity = 0.84, specificity = 0.75, AUC = 0.88), f (sensitivity = 0.70, specificity = 0.62, AUC = 0.71), and D * (sensitivity = 0.67, specificity = 0.61, AUC = 0.67). There was an inconspicuous publication bias in ADC, D, D* and f values, moderate heterogeneity in ADC, and high heterogeneity in D, D*, and f values. Subgroup analysis suggested that both ADC and D values had a significant higher sensitivity in \"nodules or masses\" than that in \"nodules.\"
UNASSIGNED: The parameters derived from IVIM-DWI, especially the D value, could further improve the differential diagnosis between malignant and benign solitary pulmonary nodules and masses.Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO/#myprospero, identifier: CRD42021226664.

To explore the imaging changes of the liver and kidneys in COVID-19 survivors using variable flip angle (VFA) T1 mapping and intravoxel incoherent motion-diffusion weighted imaging (IVIM-DWI).
This prospective study included 37 discharged COVID-19 participants and 24 age-matched non-COVID-19 volunteers who underwent abdominal MRI with VFA T1 mapping and IVIM-DWI sequencing as a COVID-19 group and control group, respectively. Among those discharged COVID-19 participants, 23 patients underwent two follow-up MRI scans, and were enrolled as the 3-month follow-up group and 1-year follow-up group, respectively. The demographics, clinical characteristics, and laboratory tests were collected. Imaging parameters of the liver and kidneys were measured. All collected values were compared among different groups.
The 3-month follow-up group had the lowest hepatic T1 value, which was significantly lower than the value in the control group (P < 0.001). Additionally, the 3-month follow-up group had the highest hepatic ADC and D values, cortical ADC and f values, which were significantly higher than those in the control group (for all, P < 0.05). The hepatic D value in the 1-year follow-up group decreased significantly in comparison with that in the 3-month follow-up group (P = 0.001). Compared to non-severe patients, severe cases had significantly higher hepatic D* and f*D* values (P = 0.031, P = 0.015, respectively).
The dynamic alterations of hepatic and renal imaging parameters detected with T1 mapping and IVIM-DWI suggested that COVID-19 survivors might develop mild, non-symptomatic liver and kidney impairments, of which liver impairment could probably relieve over time and kidney impairment might be long-existing.

Lymph node (LN) staging plays an important role in treatment decision-making. Current problem is that preoperative detection of LN involvement is always highly challenging for radiologists.
To explore the value of the nomogram model combining intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and radiomics features from the primary lesion of rectal adenocarcinoma in assessing the non-enlarged lymph node metastasis (N-LNM) preoperatively.
Retrospective.
A total of 126 patients (43% female) comprising a training group (n = 87) and a validation group (n = 39) with pathologically confirmed rectal adenocarcinoma.
A 3.0 Tesla (T); T2 -weighted imaging (T2 WI) with fast spin-echo (FSE) sequence; IVIM-DWI spin-echo echo-planar imaging sequence.
Based on pathological analysis of the surgical specimen, patients were classified into negative LN (LN-) and positive LN (LN+) groups. Apparent diffusion coefficient (ADC), diffusion coefficient (D), pseudo diffusion coefficient (D*) and microvascular volume fraction (f) values of primary lesion of rectal adenocarcinoma were measured. Three-dimensional (3D) radiomics features were measured on T2 WI and IVIM-DWI. A nomogram model including IVIM-DWI and radiomics features was developed.
General_univariate_analysis and multivariate logistic regression were used for radiomics features selection. The performance of the nomogram was assessed by the receiver operating characteristic (ROC) curve, calibration, and decision curve analysis (DCA).
The LN+ group had a significantly lower D* value ([13.20 ± 13.66 vs. 23.25 ± 18.71] × 10-3  mm2 /sec) and a higher f value (0.43 ± 0.12 vs. 0.34 ± 0.10) than the LN- group in the training cohort. The nomogram model combined D*, f, and radiomics features had a better evaluated performance (AUC = 0.864) than any other model in the training cohort.
The nomogram model including IVIM-DWI and MRI radiomics features in the primary lesion of rectal adenocarcinoma was associated with the N-LNM.
4 TECHNICAL EFFICACY: Stage 2.

The intra-voxel incoherent motion model of diffusion-weighted magnetic resonance imaging (IVIM-DWI) with a series of images with differentb-values has great potential as a tool for detecting, diagnosing, staging, and monitoring disease progression or the response to treatment. The current clinical tumour characterisation using IVIM-DWI is based on the parameter values derived from the IVIM model. On the one hand, the calculation accuracy of such parameter values is susceptible to deviations due to noise and motion; on the other hand, the performance of the parameter values is rather limited with respect to tumour characterisation. In this article, we propose a deep learning approach to directly extract spatiotemporal features from a series ofb-value images of IVIM-DWI using a deep learning network for lesion characterisation. Specifically, we introduce an attention mechanism to select dominant features from specificb-values, channels, and spatial areas of the multipleb-value images for better lesion characterisation. The experimental results for clinical hepatocellular carcinoma (HCC) when using IVIM-DWI demonstrate the superiority of the proposed deep learning model for predicting the microvascular invasion (MVI) of HCC. In addition, the ablation study reflects the effectiveness of the attention mechanism for improving MVI prediction. We believe that the proposed model may be a useful tool for the lesion characterisation of IVIM-DWI in clinical practice.

UNASSIGNED: This study aimed to investigate the effectiveness of intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) and blood oxygen level-dependent (BOLD) magnetic resonance imaging (MRI) in monitoring tumor responses to antiangiogenic therapy combined with hypoxia-activated prodrugs (HAPs).
UNASSIGNED: Establishing colon cancer xenograft model by subcutaneously injecting the HCT116 cell line into BALB/C nude mice. Twenty-four tumor-bearing mice were randomly divided into four groups and injected with bevacizumab combined with TH-302 (A), bevacizumab (B), TH-302 (C), or saline (D) on days 1, 4, 7, 10 and 13. Functional MRI was performed before and at 3, 6, 9, 12 and 15 days after treatment. Pathologic examinations, including HE staining, HIF-1α and CD31 immunohistochemical staining, and TUNEL and Ki-67 immunofluorescent staining, were performed after the last scan.
UNASSIGNED: At the end of the study, Group A showed the lowest tumor volume, followed by Groups B, C, and D (F=120.652, P<0.001). For pathologic examinations, Group A showed the lowest percentage of CD31 staining (F=73.211, P<0.001) and Ki-67 staining (F=231.170, P<0.001), as well as the highest percentage of TUNEL staining (F=74.012, P<0.001). Moreover, the D* and f values exhibited positive correlations with CD31 (r=0.868, P<0.001, and r=0.698, P=0.012, respectively). R2* values was positively correlated with HIF-1α (r=0.776, P=0.003). D values were positively correlated with TUNEL (r=0.737, P=0.006) and negatively correlated with Ki-67 (r=0.912, P<0.001). The standard ADC values were positive correlated with TUNEL (r=0.672, P=0.017) and negative correlated with Ki-67 (r=0.873, P<0.001).
UNASSIGNED: Anti-angiogenic agents combined with HAP can inhibit tumor growth effectively. In addition, IVIM-DWI and BOLD-MRI can be used to monitor the tumor microenvironment, including perfusion, hypoxia, cell apoptosis and proliferation, in a noninvasive manner.