Defining the baseline functional imaging characteristics of retroperitoneal sarcomas
Jessica M Winfield1,2, Aisha Miah3, Dirk Strauss4, Khin Thway5, Andrew Hayes4, Daniel Henderson3, David J Collins1,2, Nandita M deSouza1,2, Martin O Leach1,2, Sharon L Giles1,2, Veronica A Morgan1,2, and Christina Messiou1,2

1MRI, Royal Marsden Hospital, Sutton, United Kingdom, 2Division of Radiotherapy and Imaging, Cancer Research UK Cancer Imaging Centre, Institute of Cancer Research, London, United Kingdom, 3Department of Radiotherapy, Royal Marsden Hospital, London, United Kingdom, 4Department of Surgery, Royal Marsden Hospital, London, United Kingdom, 5Department of Histopathology, Royal Marsden Hospital, London, United Kingdom

### Synopsis

Soft tissue sarcomas are often highly heterogeneous tumours and post-treatment changes cannot be described by standard size criteria. Functional imaging may provide a non-invasive method of assessing response to treatment. Knowledge of baseline functional imaging characteristics and the repeatability of estimated parameters is essential in development of future studies. In this study, 22 patients with retroperitoneal sarcoma were imaged before treatment. Whole-tumour assessments of apparent diffusion coefficient (ADC), parameters of the intra-voxel incoherent motion model (IVIM: diffusion coefficient D, fraction f, fast exponential component D*), transverse relaxation rate (R2*), fat fraction and enhancing fraction (EF) showed large ranges of median estimates, indicating wide inter-tumour heterogeneity. The large standard deviation of parameters within tumours reflects the intra-tumour heterogeneity. In 21 patients, a second examination was carried out to assess repeatability of ADC, D, f, D* and R2*. Excellent repeatability of fitted parameters, particularly ADC, indicates high sensitivity to treatment-induced changes.

### Background

Soft tissue sarcomas are often highly heterogeneous tumours with variable components which can include cellular tumour, fat, necrosis and cystic change. Post-treatment changes often cannot be described by standard size criteria e.g. RECIST 1.1, as responding tumours may not change size, or may grow, after radiotherapy.1,2 In non-resectable tumours, or trials of combined radiotherapy and systemic agents, non-invasive methods are required for assessment of response. Prior knowledge of functional imaging characteristics is required, however, to select appropriate MRI techniques and sequence parameters. Estimates of repeatability inform on sensitivity of imaging metrics to detect post-treatment changes.

### Purpose

To establish pre-treatment estimates of apparent diffusion coefficient (ADC), parameters of the intra-voxel incoherent motion model (IVIM:$\;$diffusion coefficient$\;$D,$\;$fraction$\;$f,$\;$fast exponential component$\;$D*), transverse relaxation rate (R2*), fat fraction and enhancing fraction (EF) in retroperitoneal sarcomas; assess repeatability of$\;$ADC,$\;$D,$\;$f,$\;$D*$\;$and$\;$R2*; and assess heterogeneity of these parameters within tumours and between patients, in order to inform protocol development for sarcoma clinical trials, where functional MRI has not been used extensively.

### Methods

22 patients with retroperitoneal sarcoma were imaged prior to treatment (21 imaged twice), with their written consent, as part of a prospective single-centre study. Tumours were 3 leiomyosarcomas, 17 well-differentiated/dedifferentiated liposarcomas, 1 lipoma and 1 spindle cell sarcoma. Scans were carried out using a 1.5T MR scanner (Aera, Siemens GmbH, Erlangen, Germany) (Figure$\;$1). Axial T2-w images, diffusion-weighted images (DWI), Dixon images and pre-contrast T1-weighted images were acquired from the whole tumour volume. T2*-w images for estimation of R2* and an additional DWI series for estimation of IVIM parameters were acquired from a smaller number of slices centred on the central slice of the tumour. Following administration of Gd-based contrast agent (Dotarem, 0.2ml/kg body weight, administered at 2ml/sec using a power-injector; images acquired 4 minutes after injection), post-contrast T1-w images were acquired for evaluation of EF. 1 patient did not have T2*-w imaging. 1 patient did not have post-contrast imaging. Dixon images were acquired in 12 patients. In 21 patients, DWI and T2*-w imaging were repeated after a short break during which the patient left the scanner room and was repositioned for the second scan.

Analysis was carried out using in-house software. Pixel values evaluated at all pixels in the regions of interest (ROIs, Figure 2) were combined to create a volume of interest (VOI) for each quantitative parameter. A threshold in signal intensity was applied to exclude suppressed fat from analysis of DW and T2*-w images since these sequences employed fat suppression; 2 tumours were excluded from analysis of DW and T2*-w images as >90% of pixels were excluded. For ADC,$\;$D,$\;$f,$\;$D*$\;$and$\;$R2*, the median, mean, standard deviation, 10th, 25th, 75th and 90th centiles, skew and kurtosis of pixel values in the VOI were evaluated. Fat fraction, calculated using Dixon fat and water images, was defined as the ratio of the pixel value in the fat image to the sum of the pixel values in fat and water images. EF was defined as the fraction of pixels in the VOI that increased in signal intensity by >5% between pre- and post-contrast T1-w images.

Bland-Altman plots of untransformed data showed a relationship between the differences in the repeated measurements and their means that was reduced by using the natural logarithm of the data. The Coefficient of Variation (CV) of the log-transformed data was used to describe the repeatability of fitted parameters$\;\mathrm{CV}=\sqrt{\mathrm{exp}\left(\Sigma_i d_i^2/2N\right)-1}$, where$\;d_i\;$is the difference between paired measurements for patient$\;i$ and$\;N\;$is the number of patients.

### Results

Repeatability of ADC summary statistics was excellent (Figure$\;$3). Repeatability of D was also good, with poorer repeatability of$\;$f,$\;$D*$\;$and$\;$R2*, particularly centile estimates. Median estimates of all parameters showed large ranges across the cohort (Figures$\;$3$\;$and$\;$4). The range of each estimated parameter within tumours was also wide, indicated by the large standard deviations (Figure$\;$3).

### Discussion

The large ranges of estimated parameters indicates wide inter-tumour heterogeneity, possibly reflecting the mixture of sarcoma sub-types included in the study, which is typical of sarcoma trials as this is a rare tumour type. The large standard deviation of parameters within tumours reflects the intra-tumour heterogeneity. The excellent repeatability of ADC statistics indicates high sensitivity to treatment-induced changes, including centile estimates, which may be sensitive to different components of heterogeneous tumours and furthermore have been shown to be earlier indicators of response than mean ADC in some tumours.3

### Conclusions

Good quality images can be obtained for estimation of$\;$ADC,$\;$D,$\;$f,$\;$D*,$\;$R2*,$\;$fat fraction and enhancing fraction in retroperitoneal sarcomas. Repeatability of ADC is excellent, with slightly poorer repeatability of D,$\;$f,$\;$D*$\;$and$\;$R2*. Knowledge of the ranges of these parameters within tumours and between subjects informs protocol development for clinical trials.

### Acknowledgements

We acknowledge funding from Cancer Research UK to the CRUK Cancer Imaging Centre in association with MRC and Department of Health and NHS funding to the NIHR Biomedical Research Centre and Clinical Research Facility in Imaging. MOL is an NIHR Senior Investigator.

### References

1. Canter R, Martinez S, Tamurian R, et al. Radiographic and histologic response to neoadjuvant radiotherapy in patients with soft tissue sarcoma. Ann Surg Oncol. 2010;17:2578-2584.

2. Roberge D, Skamene T, Nahal A, et al. Radiological and pathological response following pre-operative radiotherapy for soft tissue sarcoma. Radiother Oncol. 2010;97:404-407.

3. Kyriazi S, Collins D, Messiou C, et al. Metastatic ovarian and primary peritoneal cancer: Assessing chemotherapy response with diffusion-weighted MR imaging - value of histogram analysis of apparent diffusion coefficients. Radiology. 2011;261:182-192.

### Figures

Figure 1: Sequence parameters for diffusion-weighted imaging (DWI), Dixon, pre- and post-contrast T1-weighted imaging, T2*-weighted imaging and an additional diffusion-weighted imaging sequence for estimation of parameters of the intra-voxel incoherent motion (IVIM) model.

Figure 2: (a) ADC map, (b) R2* map, (c) Dixon fat image, (d) post-Gd T1-weighted image from the central slice of a dedifferentiated liposarcoma. ROIs (green lines) were drawn around the whole tumour on every slice of T2-weighted images by a consultant radiologist and transferred to each functional imaging series.

Figure 3: Median (range) and CV of summary statistics (median, mean, standard deviation (s.d.), 10th, 25th, 75th, 90th centiles, skew, kurtosis) of ADC, D, f, D* and R2*. For skew and kurtosis the s.d. of differences between two examinations is reported as these values may be zero or negative.

Figure 4: Median (range) of fat fraction and enhancing fraction.

Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)
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