Home Intravoxel Incoherent Motion Diffusion-weighted MR Imaging for Early Evaluation of the Effect of Radiofrequency Ablation in Rabbit Liver VX2 Tumors
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Intravoxel Incoherent Motion Diffusion-weighted MR Imaging for Early Evaluation of the Effect of Radiofrequency Ablation in Rabbit Liver VX2 Tumors

Rationale and Objectives

This study aims to investigate the value of intravoxel incoherent motion (IVIM)-derived parameters for early evaluation of the efficiency of radiofrequency ablation (RFA) treatment for rabbit liver VX2 tumor.

Materials and Methods

Eighteen rabbit liver VX2 tumor models were constructed, and computed tomography–guided RFA was performed. One day before and 7 days after RFA, 18 models underwent magnetic resonance imaging, including contrast-enhanced imaging and IVIM diffusion-weighted imaging with 16 b -factors (0–1000 s/mm 2 ). Post-RFA liver tumors were segmented into viable tumor, inflammatory reaction, and ablation necrotic regions according to gross and histopathologic examinations. Parameters derived from IVIM were calculated. One-way analysis of variance and least significant difference test were used for comparisons among the three regions. The diagnostic performance of parameters was evaluated using receiver operating characteristic (ROC) analysis.

Results

ADC total , D , and f values were significantly lower in viable tumor than in inflammatory reaction regions (all P < .05), but D \* showed no significant difference between the two regions. ADC total values of viable tumor regions were significantly lower than that of ablation necrotic regions ( P = .007), but D \* values of necrotic regions were significantly lower than that of viable tumor regions ( P = .045). In ROC analysis, ADC showed the highest area under the ROC curve for differentiating inflammatory reaction from viable tumor region.

Conclusions

ADC total , D , and f were valuable discriminating markers for differentiation between regions of viable tumor and inflammatory reaction in post-RFA tumor, especially ADC total outperformed the other two parameters with higher diagnostic performance.

Introduction

As one of minimally invasive approaches, radiofrequency ablation (RFA) has been widely used in the treatment of malignant hepatic tumors, especially in patients with unresectable malignancies. Although RFA has achieved promising treatment effects, the incidence of local residual tumors or recurrence after RFA still remains high , which indicates treatment failure and the need for further therapy. Thus, it is of great importance for imaging assessment to detect viable tumor tissue accurately early after RFA. At an early stage after RFA, the inflammatory reaction to the thermal stress around the ablation zone is usually obvious and can last for up to 6 months after RFA . Some imaging features of inflammatory reaction regions may overlap with those of viable tumor regions, such as shape, density or signal intensity, and enhancement pattern . Conventional imaging examination methods (magnetic resonance imaging [MRI] or computed tomography [CT]) based on morphological characteristics cannot provide additional information, which makes it difficult to differentiate between regions of viable tumor and inflammatory reaction within liver tumors after RFA.

Magnetic resonance (MR) diffusion-weighted imaging (DWI) has shown its value in differential diagnosis and treatment follow-up for liver tumors. However, within living tissue, the signal intensity decay vs b -value (gradient intensity) is influenced simultaneously by microcirculation perfusion and pure molecular diffusion . The new intravoxel incoherent motion (IVIM) theory can distinguish perfusion effects from diffusion effects using multiple b -value imaging and biexponential fit analysis . In recent years, IVIM theory has been applied to many clinical studies in abdominal diseases . Therefore, we hypothesize that IVIM may help characterize tissue components in the liver tumor after RFA.

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Materials and Methods

Liver VX2 Tumor Model

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Radiofrequency Ablation of VX2 Tumors

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MR Protocol

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Table 1

Magnetic Resonance Imaging Parameters

Sequence Repetition Time (ms) Echo Time (ms) Flip Angle (degrees) Matrix Field of View (mm 2 ) Section Thickness (mm) T2-weighted single-shot fast spin echo 2830 65.9 90 288 × 288 140 × 140 2 DWI with 15 b -values 4000 73.9 90 128 × 128 140 × 140 2.6 LAVA-Flex 4 2 70 160 × 160 140 × 140 2

DWI, diffusion-weighted imaging.

Note. b -values of 0, 20, 30, 40, 50, 60, 70, 80, 100, 200, 300, 400, 600, 800, 1000 s/mm 2 were used for DWI.

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Histopathologic and Immunohistochemical Analysis

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DWI Parameter Acquisition

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Sb/S0=exp(−b×ADC). S

b

/

S

0

=

exp

(

b

×

A

D

C

)

.

In the equation, S b is the signal intensity at a given b -value and S 0 is the signal intensity in the absence of a diffusion gradient ( b = 0). On the basis of IVIM theory, the D , D *, and f values were calculated with a biexponential fit model using the following equation :

Sb/S0=(1−f)×exp(−b×D)+f×exp[−b(D+D*)]. S

b

/

S

0

=

(

1

f

)

×

exp

(

b

×

D

)

+

f

×

exp

[

b

(

D

+

D

*

)

]

.

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Statistical Analysis

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Results

Establishment of the Liver VX2 Tumor Model

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Histopathologic Findings

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Gross observation

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Microscopic observation

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Validation of Components Within Post-RFA Lesions on MRI

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IVIM Parameters

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Table 2

Mean Values of Measured Parameters for Three Regions of Post-RFA Tumor

Parameter Necrotic Inflammatory Viable_ADC_ total (×10 −3 mm 2 /s) 1.79 ± 0.36 2.04 ± 0.32 1.44 ± 0.44D (×10 −3 mm 2 /s) 1.63 ± 0.41 1.71 ± 0.52 1.37 ± 0.40D \* (×10 −3 mm 2 /s) 109.53 ± 123.64 153.44 ± 133.36 206.63 ± 164.10f (%) 7.71 ± 6.42 18.15 ± 11.12 9.97 ± 9.39

RFA, radiofrequency ablation.

Note. Data are expressed as mean ± standard deviation.

Table 3

Results of Multiple Comparisons Among the Three Regions of Post-RFA Liver Tumor

Parameter Necrotic vs Inflammatory Necrotic vs Viable Inflammatory vs Viable_ADC_ total 0.0560.007 \* ≤ 0.001 \* D 0.621 0.0800.026 \* D \* 0.3560.045 \* 0.264f0.001 \* 0.4640.010 \*

RFA, radiofrequency ablation.

Note. Data are P values.

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Figure 1, (a–d) Box plots of ADC total (a) , pure diffusion coefficient D (b) , perfusion-related diffusion coefficient D * (c) , and perfusion fraction f (d) values for ablation necrotic, inflammatory reaction, and viable tumor regions within postradiofrequency ablation liver tumor. The midline within the box is the median value. Cross lines above and below mark the minimum and maximum values, respectively. The ADC total , D , and f values of viable tumor regions were significantly lower than those of inflammatory regions.

Figure 2, Comparison of magnetic resonance images and pathologic specimen in postradiofrequency ablation (post-RFA) rabbit liver tumor. (a) Diffusion-weighted (DW) image shows three regions in post-RFA liver tumor. Viable tumor region (ROI1) with markedly hyperintense was localized to one side of slight hyperintense ablation necrotic region (ROI3). Inflammatory reaction region (ROI2) manifested as a hyperintense “rim” surrounding the central ablation necrotic region with the similar signal to viable tumor region (ROI1). (b) Corresponding pathologic specimen shows a good correlation with DW image. Corresponding parametric images are shown in ADC total (c) , D (d) , D * (e) , and perfusion fraction f (f) . ADC total , D , and f values are significantly lower in viable tumor regions than in inflammatory reaction regions, whereas D * shows no significant difference between the two regions.

Figure 3, Three graphs show the corresponding biexponential signal decay depending on the b -value of viable tumor region (a) , inflammatory reaction region (b) , and ablation necrotic region (c) in the same model as Figure 2 . Note the “steep” appearance of the signal attenuation curve at low b -values in inflammatory reaction region (b) compared to the “flattening” appearance in viable tumor region (a) , suggesting that viable tumor region has a lower perfusion than inflammatory reaction region.

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Table 4

ROC Analysis for ADC total , D , and f in Differentiating Between Viable and Inflammatory Regions

Parameter_A z_ Value \* (AUC) Best Cutoff Sensitivity (%) Specificity (%)P Value_ADC_ total (10 −3 mm 2 /s) 0.880 (0.750, 1.009) 1.465 77.78 100 ≤.001D (10 −3 mm 2 /s) 0.716 (0.547, 0.885) 1.310 66.67 72.22 .027f (%) 0.728 (0.560, 0.897) 0.166 88.89 55.56 .019

AUC, area under the curve; ROC, receiver operating characteristic.

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Figure 4, Receiver operating characteristic (ROC) curves of ADC total , D , and f for differentiating between viable tumor and inflammatory reaction regions within postradiofrequency ablation liver tumor. Areas under the ROC curves (AUC) and optimal cutoffs were 0.880 and 1.465 × 10 −3 mm 2s (sensitivity, 77.78%; specificity, 100%), 0.716 and 1.310 × 10 −3 mm 2s (sensitivity, 66.67%; specificity, 72.22%), 0.728 and 0.166 (sensitivity, 88.89%; specificity, 55.56%), respectively. The ROC curves demonstrated that ADC total had a higher AUC than D and f .

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Discussion

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