Purpose

Accurate risk stratification and predicting tumor aggressiveness is critically important for the management of thyroid cancer¹. Diffusion-weighted (DW) and T₁ weighted dynamic contrast-enhanced (DCE) MRI have been used for the assessment of thyroid nodules, especially for the differentiation of benign and malignant tumors ^2,3. The apparent diffusion coefficient (ADC) has emerged as a surrogate marker to assess tumor aggressiveness in papillary thyroid cancer (PTC) ⁴. Measurements of non-Gaussian diffusion from the extended-intravoxel incoherent motion model (NG-IVIM) can provide additional information on tumor tissue microstructure in PTC^{5, 6}. NG-IVIM DWI and extended Tofts pharmacokinetic model (ETM) provide the surrogate biomarkers of tumor vascularity and cellularity, respectively, and have shown promise to assess the tumor aggressiveness in PTC ^6,7. The aim of the present study is to predict tumor aggressiveness based on histopathology in PTC using multiparametric quantitative metrics derived from the NG-IVIM and ETM models.

Materials and Methods

Patients: Our institutional review board approved this prospective study. Twelve patients (median age: 40 years, Male/Female: 5/7) with biopsy-proven PTC underwent pretreatment MRI studies before surgery on a GE 3T scanner with a 24-channel neurovascular phased-array coil. DWI and DCE-MRI followed the anatomical T₁/T₂-weighted acquisitions. The surgical tumor specimen obtained from patients who underwent surgery after the MRI was reviewed by an experienced pathologist to characterize the degree of tumor aggressiveness of the following histopathologic features: tall cell variant, necrosis, vascular and/or tumor capsular invasion, extrathyroidal extension (ETE), regional metastases, and distant metastases⁴.

DW-MRI data acquisition: Multi-b value DW-MRI acquisitions were performed using a SS-EPI sequence (TR = 4000 ms, TE = 80 ms [minimum], and 3 orthogonal directions) with b values of 0, 20, 50, 80, 200, 300, 500, 800, 1000, 1500 s/mm2, 4-8 slices of 5 mm thickness covering the whole tumor, FOV=20~24 cm, and acquisition matrix =128 × 128.

DCE-MRI data acquisition: DCE data were acquired using a 3D spoiled gradient recalled echo pulse sequence.The dynamic series was acquired before, during, and after administration of the contrast agent (CA) with the FA= 150 using the following MR parameters: matrix size = 256 x128, FOV = 18-22 cm, TR/TE = 5.7/1.7 ms, phases = 50, NEX=1, slices=4-8, slice thickness=5 mm, and flip angle (FA)= 150. A total of 50 dynamic volumes were acquired in ≤5 minutes with a temporal resolution of ≤5.8 seconds per image. The CA was injected by antecubital vein catheters with a bolus of 0.1 mmol/kg and rate of 2 cc/s followed by a saline flush. The pre-contrast T₁ (T₁₀) acquisition was performed using the above-mentioned MR parameters at multiple FA of 5°, 15°, and 30°.

ROI Analysis: The tumor regions of interest (ROIs) were contoured by an experienced neuroradiologist using ImageJ on b=0 s/mm2 and later phases of DWI and T₁w DCE images, respectively. For voxel-wise analysis, signal intensity vs. b-value data was fitted by the monoexponential model, to calculate ADC and for the NG-IVIM model, which provides estimates of true diffusion coefficient (D), pseudo-diffusion coefficient ( D^*), perfusion fraction (f), and kurtosis coefficient (K). An arterial input function was extracted from the carotid artery in an individual al patient. For the DCE data, the tissue CA- time course was fitted with the ETM, which estimates volume transfer constant of a CA (K^trans [min^-1]), volume fractions of the extravascular extracellular space [EES] (v_e) and blood plasma space (v_p)⁷. The image processing and parametric map generation were performed with in house software (MRI-QAMPER)⁸. All comparable metrics with and without features of tumor aggressiveness in PTC patients were compared using the Wilcoxon signed rank test. A Spearman correlation (ρ) was performed to examine the relationship between all comparable parameters obtained with the NG-IVIM DWI and ETM. A p-value of <0.05 was considered statistically significant.

Results

Table 1 exhibits DWI (ADC and NG-IVIM), and DCE-MRI pharmacokinetic model (ETM)- derived quantitative metrics mean values between with and without tumor aggressiveness for PTCs. The mean ADC, D, K^trans, and v_e values were significantly different between the tumors with vs.without aggressiveness feature in PTC patients (P<0.05). D^*, f, K, and v_p showed a trend towards the difference (P>0.05). Table 2 reports the Spearman correlation (ρ) results between the DWI and DCE derived metrics. There was a significant positive relationship between v_e and K (ρ=0.59, P=0.048). D and v_e showed a moderate positive correlation towards a significant (ρ=0.60, P=0.10). v_p and f showed a moderately significant correlation (r=0.60, P=0.04). K^trans and D were negatively correlated (ρ=-.67, P=0.02). Figures 1 and 2 are the representative scatter plots for quantitative metrics derived from the NG-IVIM and DCE MRI.Figure 3 shows the representative DWI and DCE-MRI derived parametric maps.

Discussion

PTCs with high K^trans and low D metric values relate to increased cell proliferation and cell density and decreased water diffusivity. Additionally, the increased mean value of K in aggressive tumors might reflect a higher degree of complexity in tissue microstructure. The volume fraction of the blood plasma space, v_p, and perfusion fraction, f were surrogate markers of tumor vascularity.

Conclusion

These findings suggest that multi-parametric MRI is a useful noninvasive test for the assessment of tumor aggressiveness in PTC.

Acknowledgements

Supported by NIH grants R21CA176660‐01A1

References

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