Yang Zhang1, Liming Shi2, Xiaonan Sun2, Tianye Niu2, Ning Yue3, Jeon-Hor Chen1, Tiffany Kwong1,3, Min-Ying Su1, and Ke Nie3
1Department of Radiological Sciences, University of California, Irvine, CA, United States, 2Department of Radiation Oncology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China, 3Department of Radiation Oncology, Rutgers-The State University of New Jersey, New Brunswick, NJ, United States
Synopsis
This
study evaluates the difference in defining the target volume of rectal cancer with
MRI-guided radiation treatment planning. Tumors show different appearances on
different MR sequences, and also the motion of patients during the scan may
affect defining planning
target volume. A quantitative radial distance method was developed to evaluate
variations coming from image contrast and patient motion. A total of 45
patients with pre- and post-radiation treatment MRI were analyzed. The mean
difference in the radial distance between ROI’s drawn on different post-contrast
images was 2-3 mm, and the difference in the 90th percentile tumor
pixel was 6-8 mm.
Introduction:
Chemoradiation
therapy (CRT), followed by total mesorectal excision (TME), is the
standard-of-care treatment for locally-advanced colorectal cancer. Currently,
the tumor delineation in radiation therapy is mostly relied on CT images. With
the advancement of fast acquisition of MRI scans and the possibility to obtain
reliable electron density, MRI-guided treatment planning and MRI-Linac are
gradually gaining its popularity in radiotherapy. Although MRI shows much
better soft tissue contrast which could lead to better lesion delineation, the
appearance of the tumor can vary greatly depending on the type of imaging
sequence or images acquired at different times after injection of contrast
agent. Furthermore, patient motion can be another source of variation that can
add to the uncertainty when determining the target volume for treatment
planning. In this study, we developed a quantitative method using the radial
distance, defined as the distance from the center of rectum to the boundary of
the tumor region, to evaluate variations of the tumor ROI. All patients had a
follow-up MRI, and variations in both pre-
and post- treatment MRI were studied.
Methods:
A
total of 45 patients (mean age 60) with stage T3 and T4 rectal cancer were
studied. The MRI was done on a 3.0 Tesla scanner (GE Signa HDxt) using a
phased-array body coil. In this study only the three post-contrast frames
(termed as L2, L3, and L4) acquired at 15, 60, and 120 seconds after injection
of Gd (0.1 mmol/kg) in the LAVA sequence were analyzed. On each set of DCE images,
the tumor region of interest (ROI) was carefully drawn by a radiation
oncologist (Figure 1). Using the
rectum contour drawn on one slice as reference, an intensity based non-rigid
Demons algorithm was applied to automatically segment the rectum in both
cranial and caudal directions (Figure 2).
Then the centroid of the rectum on each slice was used as the reference point
to calculate the radial distance (Figure
3). A histogram was generated for the difference of the measured radial
distance between L2 vs. L3, and another for L2 vs. L4. The values of the 25th,
50th, 75th, and 90th percentile pixel, and the
mean value averaged over the entire tumor were obtained. In order to evaluate
the difference coming from intra-fractionation patient motion, Affine
registration was used to co-register two sets of images to determine the
deformation matrix, e.g. L2 and L3 (Figure
4), and then the manual ROI drawn on L2 was mapped to L3. For these two
ROI’s the difference was coming from the motion. Results:
Figure
4
demonstrates the difference between the manually drawn ROI on L2 and L3, the
mapped ROI from L2 to L3, as well as the histogram of the difference in the
radial distance in these two comparisons. Table
1
summarizes the difference in radial distance (absolute value) of the 25th,
50th, 75th, and 90th percentile pixel. The
intra-fractionation patient motion was found to be within 1-2 mm. Although
no-special bowel preparation was given, the patients were able to stay still
during the whole scan. On the other hand, when lesions were defined using
different image sequences, over 25% pixels showed over 3-5 mm differences, and
over 10% pixels showed 6-8 mm differences.Conclusions:
The
mean value from the entire tumor showed that the difference between L2 and L4
was higher than between L2 and L3, which was reasonable due to the longer time
difference. The motion difference was higher in the post-treatment
compared to pre-treatment. This was also reasonable as patients might be weaker
after treatment and had more difficulty holding still during the scan. In the
current CRT planning, 1 cm margin expansion is typically used to create
planning target volume (PTV) from clinical target volume (CTV) which counts for
both intra- and inter-fractionation motion and setup error. Previous studies
assessed the inter-fractionation motion of rectal cancer patients was by
average of 8 mm using daily CBCT, and concluded the 1 cm expansion should be
adequate for radiotherapy planning [1-2]. However, none of previous work tried
to identify the intra-fractionation motion or the variation of CTV delineation
from image sequences. This is understandable as in CT based planning, different
image sequences as helical mode or cine mode etc., theoretically do not cause
large variations in the image contrast. But in MRI-based planning, difference
in image contrast as demonstrated in this work, can lead to variations in
identifying CTV. With MRI-guided radiotherapy gradually becoming available, the
method developed in this work may be used to evaluate the variations in delineating
tumor ROI, so a more precise treatment planning field with reasonable margin
can be used to avoid side effect without compromising the tumor treatment
efficacy.Acknowledgements
This
study is supported in part by NIH R01 CA127927, and Rutgers-RBHS precision
medicine pilot grant, The Rutgers-Cancer Institute of New Jersey P30 CA072720.References
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