Huiyan Li1, Yingjie Mei2, Queenie Chan3, and Yikai Xu1
1Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, China, People's Republic of, 2Philips Healthcare, Guangzhou, China, People's Republic of, 3Philips Healthcare, HongKong, China, People's Republic of
Synopsis
Kurtosis model based on
Gaussian distribution may be an appropriate condition in prostate. T1rho can
detect slow molecular motions of tissue water or proton chemical exchange
selectively, which may alter in prostate cancer (PCa). Parameters Dapp, Kapp
and T1 relaxation time obtained from T1rho sequence and kurtosis model for DWI
underwent statistic analysis between PCa and benign prostate hyperplasia（BPH）patients.
Our study showed that Kapp and Dapp could be an effective parameter on PCa
detection, while T1rho failed to differentiate PCa and BPH.Introduction
Prostate cancer（PCa）is the most common malignancy among males worldwide, and
is the second leading cause of cancer death among men in United States.[1] Multiparametric MRI (mpMRI), usually consisting of T2-weighted
imaging (T2WI), diffusion weighted imaging (DWI) and dynamic
contrast enhanced MRI (DCE-MRI), had been widely used for the detection of PCa.
Novel quantitative parameters, such as apparent diffusion for Gaussian
distribution (Dapp), apparent kurtosis coefficient (Kapp) or T1rho relaxation
time need more studies for verification. Our study is to assess kurtosis model
for DWI and T1 relaxation time in the rotating frame (T1rho) of PCa and BPH (benign
prostate hyperplasia), and investigate the effect of three parameters (Dapp,
Kapp and T1rho) on the differentiation of PCa and BPH.
Materials
and Methods
This retrospective study was approved by the local ethics
committee, and written informed consent was obtained from each participant. 30 cases
of PCa (Mean age 65.1 yrs.; age range 45-86 yrs.；TPSA range 3.0-409.6 ng/mL) and 30 cases of BPH (Mean age
63.0 yrs.; age range 52-84 yrs.；TPSA range 2.7-36.85 ng/mL) verified by TRUS-guided
biopsy or histopathology following radical prostatectomy were included in this
study. In PCa group, 8, 16, and 6 patients had Gleason score of 3＋3, 3＋4, >3＋4, respectively. The
MR experiment was conducted on a Philips 3.0T clinical scanner (Achieva TX,
Best, Netherlands). A16-channel SENSE Torso XL coil was used for signal
reception. T1rho was performed using turbo field echo (TFE) sequence, scanning
parameters were as follows: TR/TE= 3.3 ms/1.5ms, FOV= 240mm × 240 mm; flip
angle= 40°, matrix= 118×192; slice thickness= 3.5 mm; NSA=1; number of slices= 20;
spinlock frequency= 500 Hz; spin lock time= 0, 10, 20, 40, 60 ms, respectively.
T1rho relaxation map was generated by fitting different spin lock data with a
monoexponential decaying function. DWI was performed using single-shot
echo-planar imaging, scanning parameters were as follows: TR/TE= 2000ms/67ms, FOV=
240mm ×240 mm; flip angle= 90°, matrix= 120×160; slice thickness= 3.5 mm; NSA=4;
number of slices=20. Diffusion in 3 directions was measured by using b values
of 0, 500, 1000, 1500 s/mm2. Data were postprocessed by kurtosis
model for quantitation of Dapp and Kapp. Regions of interest (ROIs) were drawn
on tumor foci, central gland (CG) or peripheral zone (PZ) of BPH, using T2WI,
DWI and histopathology result as references. Independent samples t-test was
used to compare Dapp, Kapp and T1rho relaxation time between PCa and BPH group.
The diagnostic performance of DKI and T1rho sequences was evaluated with
receiver operating characteristics (ROC).
Results
and Dissuasion
ROIs
positions, T1rho, Dapp and Kapp maps are
shown in Figure 1. Independent samples t-test results of Dapp, Kapp and T1rho
relaxation time between PCa and BPH group are shown in Figure 2. T1rho values
(mean ± SD) of PCa and CG-BPH are 65.3 ± 7.7ms and 68.6 ± 9.5ms respectively. In
Figure 1,tumors with slightly low signal intensity (SI) in picture D look similarly to hyperplastic
nodules in picture G. There is no significantly statistical difference between
PCa and BPH in CG. In PZs of BPH cases, T1rho relaxation map shows very low SI and
T1rho value was 0ms(Figure 1:C&G). This performance is usually found in mild
or moderate hyperplasia cases with uniform high signal in T2WI, which
included a majority of BPH cases. Bilateral PZs in severe hyperplasia cases
uaually be very thin and hard to draw ROIs for being squeezed by huge
hyperplasia in CG. According to our findings in T1tho imaging, we deduce that :(1)
in CG, T1rho relaxation time fails to distinguish tumors from hyperplastic
tissues;(2) in PZ, cause SI of hyperplastic tissues are much lower than tumors,
we can easily to detect tumors aroused in hyperplasia PZ. The diagnostic
performance of DKI is shown in Table 1.Both Dapp and Kapp have satisfactory performances
in differentiating two types of prostate diseases. In the study by Toivonen, J[2], similar behaviors in Kurtosis Model for DWI can be
found in PCa and normal prostate.
Conclusions
Kurtosis model for DWI is feasible for prostate MRI
examination and owns good clinical utility to detect PCa from BPH. Kurtosis model
for DWI can be a new sequence used to fulfill mpMRI. T1 Relaxation Time in
the rotating frame failed to differentiate PCa from hyperplastic nodules in CG
and its mechanism in prostate diseases need further research.
Acknowledgements
No acknowledgement found.References
1. Bashir, M.N., Epidemiology of Prostate Cancer. Asian Pac J Cancer Prev, 2015. 16(13): p. 5137-41.
2. Toivonen, J., et al., Magn Reson Med,
2015. 74(4): p. 1116-24.