Use of monoexponential diffusion-weighted imaging and diffusion kurtosis imaging and dynamic contrast-enhanced-MRI for the differentiation of spinal tumors

Pitfalls of Diffusion-Weighted Imaging: Clinical Utility of T2 Shine-through and T2 Black-out for Musculoskeletal Diseases

Diffusion-weighted imaging (DWI) with an apparent diffusion coefficient (ADC) value is a relatively new magnetic resonance imaging (MRI) sequence that provides functional information on the lesion by measuring the microscopic movement of water molecules. While numerous studies have evaluated the promising role of DWI in musculoskeletal radiology, most have focused on tumorous diseases related to cellularity. This review article aims to summarize DWI-acquisition techniques, considering pitfalls such as T2 shine-through and T2 black-out, and their usefulness in interpreting musculoskeletal diseases with imaging. DWI is based on the Brownian motion of water molecules within the tissue, achieved by applying diffusion-sensitizing gradients. Regardless of the cellularity of the lesion, several pitfalls must be considered when interpreting DWI with ADC values in musculoskeletal radiology. This review discusses the application of DWI in musculoskeletal diseases, including tumor and tumor mimickers, as well as non-tumorous diseases, with a focus on lesions demonstrating T2 shine-through and T2 black-out effects. Understanding these pitfalls of DWI can provide clinically useful information, increase diagnostic accuracy, and improve patient management when added to conventional MRI in musculoskeletal diseases.

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.

Preliminary study of monoexponential, biexponential, and stretched-exponential models of diffusion-weighted MRI and diffusion kurtosis imaging on differential diagnosis of spinal metastases and chordoma

PURPOSE

Quantitative comparison of diffusion parameters from various models of diffusion-weighted (DWI) and diffusion kurtosis (DKI) imaging for distinguishing spinal metastases and chordomas.

METHODS

DWI and DKI examinations were performed in 31 and 13 cases of spinal metastases and chordomas, respectively. DWI derived apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudo diffusion coefficient (D*), perfusion fraction (f), water molecular distributed diffusion coefficient (DDC), and intravoxel water diffusion heterogeneity (α). DKI derived mean diffusivity (MD) and mean kurtosis (MK). Independent sample t-testing compared statistical differences among parameters. Sensitivity, specificity, and area under the receiver operating characteristic (ROC) curve were determined. Pearson correlation analysis evaluated the parameters' correlations.

RESULTS

ADC, D, f, DDC, α, and MD were significantly lower in spinal metastases than chordomas (all P < 0.05). MK was significantly higher in spinal metastases than chordomas (P < 0.05). D had the highest area under the ROC curve (AUC) of 0.886, greater than MD (AUC = 0.706) or DDC (AUC = 0.742) in differentiating the two tumors (both P < 0.05). Combining D with f and α statistically significantly increased the AUC for diagnosis (to 0.995) relative to D alone (P < 0.05). There was a certain correlation among DDC, ADC, and D (all P < 0.05).

CONCLUSIONS

Monoexponential, biexponential, and stretched-exponential models of DWI and DKI can potentially differentiate spinal metastases and chordomas. D combined with f and α performed best.

Diffusion kurtosis imaging assessment of the response to radiotherapy in a VX2 bone tumor model: an animal study

BACKGROUND

Neoadjuvant radiotherapy plays a vital role in the treatment of malignant bone tumors, and non-invasive imaging methods are needed to evaluate the response to treatment.

PURPOSE

To assess the value of diffusion kurtosis imaging (DKI) for monitoring early response to radiotherapy in malignant bone tumors.

MATERIAL AND METHODS

Treatment response was evaluated in a rabbit VX2 bone tumor model (n = 35) using magnetic resonance imaging (MRI), DKI, and histopathologic examinations. Subjects were divided into three groups: pre-treatment, post-treatment, and control groups. The post-treatment group was subclassified into good response and poor response groups according to the results of histopathologic examination. Apparent diffusion coefficient (ADC) and DKI parameters (mean diffusion coefficient [MD] and mean kurtosis [MK]) were recorded. The relationship between ADC, DKI parameters, and histopathologic changes after radiotherapy was determined using Pearson's correlation coefficient. The diagnostic performance of these parameters was assessed using receiver operating characteristic analysis.

RESULTS

MD in the good response group was higher after treatment than before treatment (P < 0.001) and higher than that in the poor response group (P = 0.009). MD was highly correlated with tumor cell density and apoptosis rate (r = -0.771, P < 0.001 and r = 0.625, P < 0.001, respectively). MD was superior to other parameters for determining the curative effect of radiotherapy, with a sensitivity of 75.0%, specificity of 100.0%, and area under the curve of 0.917 (P < 0.001).

CONCLUSION

The correlations between MD, tumor cell density, and apoptosis suggest that MD could be useful for assessing the early response to radiotherapy in rabbit VX2 malignant bone tumors.

Different Attenuation Models of Diffusion-Weighted MR Imaging for the Differentiation of Benign and Malignant Musculoskeletal Tumors

BACKGROUND

Several functional imaging techniques, including monoexponential diffusion-weighted imaging (m-DWI), intravoxel incoherent motion (IVIM), and diffusion kurtosis (DK) imaging, have been used in differentiating benign and malignant musculoskeletal tumors. Combining all three techniques in the same study population may improve differentiation.

PURPOSE

To compare the diagnostic performance of m-DWI, IVIM, and DK models and their combinations in differentiating benign and malignant musculoskeletal tumors.

STUDY TYPE

Prospective.

POPULATION

Fifty patients with benign and malignant musculoskeletal tumors divided into nonmyxoid and nonchondroid and myxoid and/or chondroid subgroups.

FIELD STRENGTH/SEQUENCE

A 1.5 T/m-DWI, IVIM, and DK single-shot spin-echo echo-planar sequences.

ASSESSMENT

Minimum and volumetric values of apparent diffusion coefficient (ADC), pure molecular diffusion (D_ivim ), pseudodiffusion (D*), perfusion fraction (f), diffusion coefficient for kurtosis model (D_K ), and Kurtosis (K) were compared between all benign and malignant tumors. Subgroup analysis was also performed for nonmyxoid and nonchondroid and myxoid and/or chondroid tumors.

STATISTICAL TESTS

Independent samples t-test, Mann-Whitney U test, intraclass correlation coefficient, ROC analysis, and logistic regression analysis. A P value < 0.05 was considered statistically significant.

RESULTS

ADC_min , D_ivim-min , D*_vol , D_K-min, K_vol, and K_min values showed statistically significant differences between all benign and malignant tumors and nonmyxoid and nonchondroid tumor subgroup. K_min showed the highest diagnostic performance in differentiating benign and malignant tumors with AUCs of 0.760 for "all tumors" and 0.825 for the nonmyxoid and nonchondroid tumor subgroup. No significant differences were detected in m-DWI-, IVIM-, and DK-derived parameters for differentiating benign and malignant myxoid and/or chondroid tumors. Only three of 63 combinations of prediction models demonstrated a higher diagnostic performance than K_min ; however, improvements were not significantly different.

DATA CONCLUSION

ADC_min , D_ivim-min , D*_vol , D_K-min , K_vol , and K_min values can be used to differentiate benign and malignant musculoskeletal tumors. Our findings suggest that the added value of multiparametric approach in such differentiation is not significant.

EVIDENCE LEVEL

1 TECHNICAL EFFICACY: Stage 2.