Utility of Multi-Parametric Quantitative Magnetic Resonance Imaging for Characterization and Radiotherapy Response Assessment in Soft-Tissue Sarcomas and Correlation With Histopathology

Abstract

Purpose: To evaluate repeatability of quantitative multi-parametric MRI in retroperitoneal sarcomas, assess parameter changes with radiotherapy, and correlate pre-operative values with histopathological findings in the surgical specimens. Materials and Methods: Thirty patients with retroperitoneal sarcoma were imaged at baseline, of whom 27 also underwent a second baseline examination for repeatability assessment. 14/30 patients were treated with pre-operative radiotherapy and were imaged again after completing radiotherapy (50.4 Gy in 28 daily fractions, over 5.5 weeks). The following parameter estimates were assessed in the whole tumor volume at baseline and following radiotherapy: apparent diffusion coefficient (ADC), parameters of the intra-voxel incoherent motion model of diffusion-weighted MRI (D, f, D*), transverse relaxation rate, fat fraction, and enhancing fraction after gadolinium-based contrast injection. Correlation was evaluated between pre-operative quantitative parameters and histopathological assessments of cellularity and fat fraction in post-surgical specimens (ClinicalTrials.gov, registration number NCT01902667). Results: Upper and lower 95% limits of agreement were 7.1 and -6.6%, respectively for median ADC at baseline. Median ADC increased significantly post-radiotherapy. Pre-operative ADC and D were negatively correlated with cellularity (r = -0.42, p = 0.01, 95% confidence interval (CI) -0.22 to -0.59 for ADC; r = -0.45, p = 0.005, 95% CI -0.25 to -0.62 for D), and fat fraction from Dixon MRI showed strong correlation with histopathological assessment of fat fraction (r = 0.79, p = 10-7, 95% CI 0.69-0.86). Conclusion: Fat fraction on MRI corresponded to fat content on histology and therefore contributes to lesion characterization. Measurement repeatability was excellent for ADC; this parameter increased significantly post-radiotherapy even in disease categorized as stable by size criteria, and corresponded to cellularity on histology. ADC can be utilized for characterizing and assessing response in heterogeneous retroperitoneal sarcomas.

Keywords: apparent diffusion coefficient (ADC); diffusion weighted MRI; magnetic resonance imaging; neoplasm; radiation therapy; soft tissue sarcoma.

Figures

Figure 1

Study organization. Flow chart showing numbers of patients and tumor sub-types included in each part of the study. Well-differentiated liposarcomas refer to fatty neoplasms corresponding histologically with differentiated adipocytic tumors closely resembling mature fat, and dedifferentiated liposarcomas as more solid to myxoid tumors corresponding histologically with non-lipogenic, usually pleomorphic, tumors. In this study, closely intermingled tumors refer to intermingled well- and dedifferentiated components, which can be seen histologically.

Figure 2

Example showing positioning of ROI for histopathological and radiological analysis. (A) Slice cut by histopathologist. (B) fitted b = 0 s mm−2 image from matching slice in DW-MRI series. ROI shown by green square and dashed arrows. Solid arrow in (B) shows kidney (not removed in surgery). ROIs were chosen jointly by the histopathologist and radiologist using pre-surgical imaging, markers inserted by the surgeon, and anatomical landmarks within tumor. Note ROI lies in a nodule in the posterior part of the tumor.

Figure 3

Acquired images and fitted/calculated parameters from the same slice as Figure 2. Left-hand image: T2-weighted image showing ROI. Right-hand panels: fitted/calculated values in ROI (color) overlaid on acquired images (gray scale). Top row: ADC overlaid on b = 50 s mm−2 image; D, f, and D* overlaid on b = 50 s mm−2 images. Bottom row: R2* overlaid on TE = 5 ms gradient-echo image; FF overlaid on in-phase image; εF overlaid on pre-contrast image.

Figure 4

Bland-Altman plots showing percentage change between two baseline estimates of median parameter vs. their geometric mean. (A) median ADC, (B) median D, (C) median f, (D) median D*, (E) median R2*. Solid lines show the mean difference between two baseline examinations (mean differences were 1.9, 1.4, 5.5, −5.0, and 9.7% for ADC, D, f, D*, and R2*, respectively). Dashed lines show 95% limits of agreement.

Figure 5

Median ADC estimates pre- and post-radiotherapy. Ladder plot showing median ADC estimates for 13 patients pre- and post-radiotherapy (solid lines). In patients undergoing two baseline examinations, the mean of two estimates was used. Dashed line shows mean values for the cohort. Asterisks show four patients exhibiting post-treatment increases in median ADC outside baseline 95% LoA (One patient who underwent radiotherapy was excluded from ADC analysis as the tumor [well-differentiated liposarcoma] was composed of more than 80% fat and was therefore not evaluable using fat-suppressed diffusion-weighted imaging).

Figure 6

(A) Example of tumor exhibiting high cellularity, with patternless distributions of markedly pleomorphic cells dispersed in moderate amounts of collagenous stroma (200× magnification). (B) Example of tumor exhibiting low cellularity, comprising loose fascicles of relatively bland spindle cells, dispersed in abundant collagenous stroma (200× magnification).

Figure 7

(A) Example of high-fat fraction tumor showing prominent lobules and sheets of adipocytes, intersected by sparsely cellular fibrous septa. Occasional atypical hyperchromatic nuclei are apparent within the fibrous stroma (400× magnification). (B) Example of low-fat fraction tumor largely composed of prominent spindle cells arising in loose fascicles within delicately collagenous stroma. Only small numbers of adipocytes are scattered within the neoplasm (100× magnification).

Figure 8

Histopathological assessment of cellularity. Natural logarithm of nuclear-to-stromal ratio (estimated from histopathological analysis) vs. (A) apparent diffusion coefficient (ADC, estimated from DW-MRI) and (B) diffusion coefficient (D, from IVIM model of DW-MRI). Each point represents one ROI. Solid black line shows line of best fit. Points are labeled by histopathological assessment of stroma type (myxoid, fibromyxoid, or fibrous), with fibrous stroma types labeled by stroma grade (lower grades 1–2, and higher grades 3–5). ROIs that consisted of more than 80% fat were excluded from analysis of ADC and D.

Figure 9

Histopathological assessment of fat fraction. (A) Fat fraction estimated from Dixon MRI vs. fat fraction estimated from histopathological assessment. Solid black line shows line of best fit. Gray line shows line of identity. (B) Difference between fat fraction estimated from Dixon MRI and fat fraction estimated from histopathological assessment, plotted against the mean of the two measurements. Gray line shows line of no difference between two measurements.

Figure 10

Graph showing ADC data from the literature (described in Table 2), alongside data from the present study. References are shown on the x-axis. Double-headed arrows show multiple data points from the same reference. Red lines show ADC estimates from soft-tissue sarcomas at baseline. Black and gray lines show ADC estimates from osteosarcomas [and Ewing sarcomas in Hayashida et al. (21)] at baseline and post-treatment, respectively. Studies reporting mean ± standard deviation are shown as markers (×) with error bars representing standard deviation. Studies reporting only an average value are shown as markers (×) without error bars. Studies reporting a range are shown as error bars (upper and lower ends of range) without markers.