Soft tissue sarcomas: IVIM and DKI correlate with the expression of HIF-1α on direct comparison of MRI and pathological slices

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.

Neon ion (20 Ne10 + ) charged particle beams manipulate rapid tumor reoxygenation in syngeneic mouse models

Charged particle beams induce various biological effects by creating high-density ionization through the deposition of energy along the beam's trajectory. Charged particle beams composed of neon ions (20 Ne10+ ) hold great potential for biomedical applications, but their physiological effects on living organs remain uncertain. In this study, we demonstrate that neon-ion beams expedite the process of reoxygenation in tumor models. We simulated mouse SCCVII syngeneic tumors and exposed them to either X-ray or neon-ion beams. Through an in vivo radiobiological assay, we observed a reduction in the hypoxic fraction in tumors irradiated with 8.2 Gy of neon-ion beams 30 h after irradiation compared to 6 h post-irradiation. Conversely, no significant changes in hypoxia were observed in tumors irradiated with 8.2 Gy of X-rays. To directly quantify hypoxia in the irradiated living tumors, we utilized dynamic contrast-enhanced magnetic resonance imaging (MRI) and diffusion-weighted imaging. These combined MRI techniques revealed that the non-hypoxic fraction in neon-irradiated tumors was significantly higher than that in X-irradiated tumors (69.53% vs. 47.67%). Simultaneously, the hypoxic fraction in neon-ion-irradiated tumors (2.77%) was lower than that in X-irradiated tumors (4.27%) and non-irradiated tumors (32.44%). These results support the notion that accelerated reoxygenation occurs more effectively with neon-ion beam irradiation compared to X-rays. These findings shed light on the physiological effects of neon-ion beams on tumors and their microenvironment, emphasizing the therapeutic advantage of using neon-ion charged particle beams to manipulate tumor reoxygenation.

Correlation between IVIM parameters and microvessel architecture: direct comparison of MRI images and pathological slices in an orthotopic murine model of rhabdomyosarcoma

OBJECTIVE

This study aimed to explore the correlation between intravoxel incoherent motion (IVIM) parameters and microvessel architecture (microvessel density (MVD), vasculogenic mimicry (VM), and pericyte coverage index (PCI)) in an orthotopic murine model of rhabdomyosarcoma.

METHODS

The murine model was established by injecting rhabdomyosarcoma-derived (RD) cells into the muscle. Nude mice underwent routine magnetic resonance imaging (MRI) and IVIM examinations with ten b values (0, 50, 100, 150, 200, 400, 600, 800, 1000, and 2000 s/mm2). D, D*, and f values were calculated with the ADW4.7 workstation. MRI images and pathological slices were directly compared to ensure that radiology parameters accurately reflect pathology. MVD, VM, PCI, and cellularity were obtained by histological analysis. The correlations were assessed between IVIM parameters (D, D*, f, and fD* values) and pathological markers (MVD, VM, PCI, and cellularity).

RESULTS

The average of D, D*, f, and fD* values were 0.55 ± 0.07 × 10-3 mm2/s, 5.25 ± 0.73 × 10-3 mm2/s, 13.39 ± 7.68%, and 0.73 ± 0.49 × 10-3 mm2/s, respectively. The average of MVD, VM, PCI, and cellularity were 41.91 ± 10.98, 1.16 ± 0.83, 0.49 ± 0.18, and 39.15 ± 9.00%. D*, f, and fD* values showed a positive correlation with MVD separately, while the D value did not correlate with MVD. D value negatively correlated to VM moderately, and other parameters did not associate with VM. D* and fD* values were positively correlated with PCI, but no correlation was observed between other parameters and PCI.

CONCLUSIONS

IVIM may evaluate the tumor microvessel architecture. D*, f, and fD* may reflect the endothelial lining blood vessel; D could indirectly reflect the VM; D* and fD* could reflect PCI(the normal degree of the tumor blood vessel).

CLINICAL RELEVANCE STATEMENT

An intravoxel incoherent motion may be useful in assessing rhabdomyosarcoma microvessel structure to predict the target and effectiveness of anti-angiogenic therapy.

KEY POINTS

• IVIM may be used to evaluate the tumor microvessel architecture in the mouse rhabdomyosarcoma model. • The MRI-pathology control method achieves correspondence between MRI slices and pathology slices, which ensures the consistency of the ROI of MRI and the pathology observation region.

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

Purpose

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).

Materials and methods

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.

Results

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).

Conclusion

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.

Preoperative contrast-enhanced CT-based radiomics signature for predicting hypoxia-inducible factor 1α expression in retroperitoneal sarcoma

AIM

To develop and test a contrast-enhanced computed tomography (CECT)-based radiomics signature (RS) to preoperatively predict hypoxia-inducible factor 1α (HIF-1α) expression in retroperitoneal sarcoma (RPS).

MATERIALS AND METHODS

This study included 129 patients with RPS retrospectively who underwent CECT, including 64 male and 65 female patients (55 [2-84] years). Participants were divided into a training set comprising 85 patients and a test set comprising 44 patients. Clinical data and CECT findings of all patients were collected. RS construction was performed by the minimum redundancy maximum relevance method and least absolute shrinkage and selection operator algorithm. The clinical information was analysed by univariate and multivariate logistic regression analysis. The RS and risk factors were included to build a radiomics nomogram. The predictive efficacy of different models was evaluated by accuracy, area under the receiver operating characteristic curve (AUC), and decision curve analysis.

RESULTS

The RS combined signature was constructed on the basis of multi-phase CECT and had an accuracy of 0.795 and an AUC of 0.719 (95% confidence interval [CI], 0.552-0.886) in the test set, which were higher than that of the radiomics nomogram (accuracy: 0.636; AUC: 0.702 [95% CI, 0.547-0.857]) and the clinical model (accuracy: 0.682; AUC: 0.486 [95% CI, 0.324-0.647]). The decision curve analysis showed that the RS combined signature provided better clinical application than the clinical model and radiomics nomogram.

CONCLUSIONS

The multi-phase CECT-based RS constructed can be used as a powerful tool for predicting HIF-1α expression in patients with RPS.

Advances in The Application and Research of Magnetic Resonance Diffusion Kurtosis Imaging in The Musculoskeletal System

Magnetic resonance diffusion kurtosis imaging (DKI) is an emerging magnetic resonance imaging (MRI) technique that can reflect microstructural changes in tissue through non-Gaussian diffusion of water molecules. Compared to traditional diffusion weighted imaging (DWI), the DKI model has shown greater sensitivity for diagnosis of musculoskeletal diseases and can help formulate more reasonable treatment plans. Moreover, DKI is an important auxiliary examination for evaluation of the motor function of the musculoskeletal system. This article briefly introduces the basic principles of DKI and reviews the application and research of DKI in the evaluation of disorders of the musculoskeletal system (including bone tumors, soft tissue tumors, spinal lesions, chronic musculoskeletal diseases, musculoskeletal trauma, and developmental disorders) as well as the normal musculoskeletal tissues. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: 1.

Nomograms Combining Clinical and Imaging Parameters to Predict Recurrence and Disease-free Survival After Concurrent Chemoradiotherapy in Patients With Locally Advanced Cervical Cancer

PURPOSES

To investigate the value of nomograms based on clinical prognostic factors (CPF), intravoxel incoherent motion diffusion weighted imaging (IVIM-DWI) and MRI-derived radiomics in predicting recurrence and disease-free survival (DFS) after concurrent chemoradiotherapy (CCRT) for locally advanced cervical cancer (LACC).

METHODS

Retrospective analysis of data from 115 patients with ⅠB-ⅣA cervical cancer who underwent CCRT and had been followed up consistently. All patients were randomized 2:1 into training and validation groups. Pre-treatment IVIM-DWI parameters (ADC-value, D-value, D*-value and f-value) and pre- and post-treatment three-dimensional radiomics parameters (from axial T₂WI) of primary lesions were measured. The LASSO algorithm and Logistic regression analysis were used to filter texture features and calculate radiomics score (Rad-score). Multivariate Logistic and Cox regression analysis was used to construct nomograms to predict recurrence and DFS for patients with LACC after CCRT respectively, with internal and external validation.

RESULTS

External beam radiotherapy dose, f-value, pre-treatment and post-treatment Rad-score were independent prognostic factors for recurrence and DFS in patients with cervical cancer, forming Model1 and Model2, with OR values of 0.480, 1.318, 3.071, 3.200 and HR values of 0.322, 3.372, 5.138, 7.204. The area under the curve (AUC) of Model1 for predicting recurrence of cervical cancer was 0.977, with internal and external validation C-indexes of 0.977 and 0.962. The AUC for Model2 predicting disease-free survival (DFS) at 1, 3, and 5 years was 0.895, 0.888 and 0.916 respectively, with internal and external C-indexes of 0.860 and 0.892. The decision curves analysis and clinical impact curves further indicate the high predictive efficiency and stability of nomograms.

CONCLUSION

The nomograms based on clinical, IVIM-DWI and radiomics parameters have high clinical value in predicting recurrence and DFS of patients with LACC after CCRT and can provide a reference for prognostic assessment and individualized treatment of cervical cancer patients.

Whole-tumor histogram analysis of diffusion-weighted imaging and dynamic contrast-enhanced MRI for soft tissue sarcoma: correlation with HIF-1alpha expression

OBJECTIVE

To investigate the correlation of histogram metrics from diffusion-weighted imaging (DWI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters with HIF-1alpha expression in soft tissue sarcoma (STS).

METHODS

We enrolled 71 patients with STS who underwent 3.0-T MRI, including conventional MRI, DWI, and DCE-MRI sequences. Location, maximum tumor diameter, envelope, T2-weighted tumor heterogeneity, peritumoral edema, peritumoral enhancement, necrosis, tail-like pattern, bone invasion, and vessel/nerve invasion and/or encasement were determined using conventional MRI images. The whole-tumor histogram metrics were calculated on the apparent diffusion coefficient (ADC), K^trans, K_ep, and V_e maps. Independent-samples t test and one-way ANOVA were used for testing the differences between normally distributed categorical data with HIF-1alpha expression. Pearson and Spearman correlations and multiple linear regression analyses were performed to determine the correlations between histogram metrics and HIF-1alpha expression. Survival curves were plotted using the Kaplan-Meier method.

RESULTS

Regarding conventional MRI features, only highly heterogeneous on T2-weighted images (55.6 ± 19.9% vs. 45.4 ± 20.5%, p = 0.041) and more than 50% necrotic area (57.3 ± 20.4% vs. 43.9 ± 19.7%, p = 0.002) were prone to indicate STS with higher HIF-1alpha expression. Histogram metrics obtained from ADC (mean, median, 10th, and 25th percentile values), K^trans (mean, median, 75th, and 90th percentile values), and K_ep (90th percentile values) were significantly correlated with HIF-1alpha expression. Multiple linear regression analysis demonstrated that more than 50% necrosis, ADC_skewness, K^trans_90th, and grade III were independently associated with HIF-1alpha expression.

CONCLUSION

DWI and DCE-MRI histogram parameters were significantly correlated with HIF-1alpha expression in STS.

KEY POINTS

• DWI and DCE-MRI histogram parameters are correlated with HIF-1alpha expression in STS. • More than 50% necrosis, ADC_skewness, K^trans_90th, and grade III were independently associated with HIF-1alpha expression in STS.

Soft tissue sarcoma: intravoxel incoherent motion and diffusion kurtosis imaging parameters correlate with the histological grade and Ki-67 expression

BACKGROUND

Accurate prediction of the histological grade and Ki-67 expression of soft tissue sarcoma (STS) before surgery is essential for the subsequent diagnosis, treatment, and prognostic evaluation of patients.

PURPOSE

To evaluate intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) in predicting the histological grade and Ki-67 expression of STS.

MATERIAL AND METHODS

A total of 40 patients underwent 3-T MRI, including conventional sequences; IVIM and DKI parameters were obtained. All patients were divided into a low-grade (grade 1 and grade 2) group and a high-grade (grade 3) group through pathological analysis. Ki-67 expression of each lesion was calculated. Chi-square test, independent sample t-test, Mann-Whitney U test, Pearson, Spearman, and receiver operating characteristic curve analysis were performed.

RESULTS

There were 17 patients in the low-grade group and 23 in the high-grade group. Ki-67 expression was in the range of 10%-80%. D value was inversely correlated with Ki-67 expression. MK value showed a moderate positive correlation with Ki-67 expression. Regarding histological grading, only the peritumoral enhancement was statistically different between low- and high-grade STS on conventional MRI (P=0.024). The high-grade group had significantly higher MK value and lower D and MD value than the low-grade group. MK value showed the best diagnostic performance. The combination of MK and MD yielded the highest specificity (88.24%), and the combination of D, MK, and MD yielded the best area under the curve value (0.841) and sensitivity (95.65%).

CONCLUSION

IVIM and DKI parameters were correlated with Ki-67 expression and could help differentiate between low- and high-grade STS.

Correlations between DWI, IVIM, and HIF-1α expression based on MRI and pathology in a murine model of rhabdomyosarcoma

PURPOSE

To investigate the correlation between DWI, intravoxel incoherent motion (IVIM), and hypoxia-inducible factor 1-alpha (HIF-1α) expression in a nude mouse model of rhabdomyosarcoma based on imaging and pathological comparisons.

METHODS

Human rhabdomyosarcoma-derived (RD) cells were inoculated into the right thigh muscle of 20 BALB/c female nude mice. Mice were imaged using 3.0 Tesla MRI system. T₁ -weighted imaging, T₂ -weighted imaging, DWI, and IVIM images were obtained. ADW4.7 (GE Healthcare, ChicagoAQ34, IL, USA) was used for image processing of ADC, D_slow , D_fast , and f values. All parameter values were independently analyzed by 2 observers. Immunohistochemistry of HIF-1α was performed. We used a specific image-pathology comparison method to ensure correct overlap between the image plane and the pathological section. Mann-Whitney U test or independent sample t test, Pearson or Spearman correlation test, the intragroup correlation coefficient, Kolmogorov-Smirnov test, and receiver operating characteristic curve were used. The correlation between DWI and intravoxel incoherent motion parameter values and HIF-1α expression was determined.

RESULTS

There were 10 mice in the low-expression group and 7 in the high-expression group. The ADC and D_slow values were negatively correlated with HIF-1α with correlation coefficients of -0.491 and - 0.702 (P = 0.045 and 0.002). The f value positively correlated with HIF-1α expression (r = 0.485, P = 0.048). ADC, D_slow , and f were significantly different between the high-HIF-1α expression tumors and the low-HIF-1α expression tumors. ADC showed the best predictive performance among all parameters (area under the curve = 0.652, sensitivity = 83.3%, specificity = 63.6%).

CONCLUSION

The parameter values of DWI and intravoxel incoherent motion can be used to evaluate the expression of HIF-1α in rhabdomyosarcoma. ADC, D_slow , and f value showed correlation with the expression of HIF-1α.