Download Comparison of MRS and DWI in the diagnosis of prostate cancer

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JOURNAL OF MAGNETIC RESONANCE IMAGING 000:000–000 (2012)
Original Research
Comparison of MRS and DWI in the Diagnosis of
Prostate Cancer Based on Sextant Analysis
Bo Li, MS,1 Wenchao Cai, BS,2 Dongjiao Lv, PhD,1 Xuemei Guo, PhD,2
Xiaoying Wang, PhD,2,3* Jue Zhang, PhD,1,3* and Jing Fang, PhD1,3
PROSTATE CANCER IS the fifth most common cancer
in the world and the second most common in men (1).
Numerous studies indicated approximately 65%–75%
prostate cancer cases occur in the peripheral zone (2).
Magnetic resonance (MR) imaging as a noninvasive
tool plays an increasingly important role in the detection, localization and staging of prostate cancer (3).
T2-weighted endorectal MR image can depict the prostate zonal anatomy and periprostatic structures with
exquisite detail (4). MR spectroscopic (MRS) imaging
has ability to provide chemical information about
metabolites in normal and abnormal tissues. Elevation of choline (Cho) levels and reduction of citrate
(Cit) have been observed in cancerous tissue relative
to normal prostatic tissue (5). Diffusion-weighted
imaging (DWI) can offer valuable information about
the microstructure and pathophysiology of tissues
based on the diffusion properties of the water molecules. Results of several studies suggested the apparent diffusion coefficient (ADC) values of cancerous
peripheral zone (PZ) and transition zone tissues was
lower than those of normal prostate tissue (6).
Although both MRS and DWI can provide valuable
information about prostate cancer (PCa), each of them
plays a different role in detection. Kumar et al (7) studied both MRS and DWI and observed a positive correlation between metabolic ratio (Cit/(Cho þ Cr)) and ADC
with estimated prostate-specific antigen (PSA). It was
reported that the combination of MRS and DWI
improved the detection of malignancy. Reinsberg et al
(8) reported that specificity of the combination of DWI
(ADC) and MRS (Cho/Cit) was significantly improved
compared with DWI or MRS alone, without reduction
in sensitivity for voxels containing 70% or more tumor
tissue. Both studies used voxel-wise comparisons. In
contrast, Mazaheri et al (5) used a region of interest
(ROI)-based analysis and combined DWI and MRS with
generalized estimating equations using a logistic
regression model and reported that the combination of
DWI and MRS was significantly more accurate than
MRS alone and was also more accurate than DWI
alone, although the latter difference was not significant. However, the results in these studies depend
highly on the data registration between DWI and MRS;
besides, there is no comparison of the utility of MRS
and DWI in cancer diagnosis in the related studies.
Purpose: To evaluate apparent diffusion coefficient (ADC)
value, metabolic ratio ((Cho þ Cr)/Cit) and the combination of the two in identifying prostate malignant regions.
Materials and Methods: Fifty-six consecutive patients with
prostate biopsy results were retrospectively recruited in this
study. Transrectal ultrasound-guided (TRUS) systemic prostate biopsies were used as a standard of reference. Mean
ADC value and mean metabolic ratio (MMR) were calculated
within each benign sextant region or malignant region. The
efficiency of these two indices in prostate cancer (PCa) diagnosis is estimated in Fisher linear discriminant analysis
(FLDA). The area under the receiver operating characteristic
(ROC) curve was used to evaluate the distinguishing capacity
of mean ADC, MMR, and the combination of the two in differentiating between noncancerous and cancerous cases.
Results: There were significant differences for mean ADC
value and MMR between malignant and benign regions.
Weights of mean ADC value obtained by FLDA were much
higher than those of MMR. In differentiating malignant
regions, both ADC alone and combined ADC and metabolic ratio performed significantly better than MMR alone.
However, accuracy improvements were not significant by
using combined ADC and MMR than ADC alone.
Conclusion: DWI is more efficient than MR spectroscopic
(MRS) in the detection of PCa in this study. Combined
ADC and MMR performed significantly better than MMR
alone in distinguishing malignant from benign region in
prostate peripheral zone.
Key Words: prostate cancer; MR spectroscopic imaging; Diffusion weighted imaging; fisher linear discriminant analysis
J. Magn. Reson. Imaging 2012;000:000–000.
C 2012 Wiley Periodicals, Inc.
V
1
College of Engineering, Peking University, Beijing, China, People’s
Republic of China.
2
Department of Radiology, Peking University First Hospital, Beijing,
China, People’s Republic of China.
3
Academy for Advanced Interdisciplinary Studies, Peking University,
Beijing, China, People’s Republic of China.
Contract grant sponsor: Fundamental Research Funds for the
Central Universities.
*Address reprint requests to: Jue Zhang, College of Engineering,
Peking University, Yiheyuan Road No. 5, Beijing, 100871, China.
E-mail: [email protected]; Xiaoying Wang, Department of Radiology, Peking University First Hospital, Xishiku Street No. 8, Xicheng District, Beijing, 100034, China. E-mail: [email protected]
Received January 15, 2012; Accepted August 8, 2012.
DOI 10.1002/jmri.23809
View this article online at wileyonlinelibrary.com.
C 2012 Wiley Periodicals, Inc.
V
1
2
In this study, we aim to (a) compare the utility of
mean ADC and mean metabolic ratio ((Cho þ Cr)/Cit)
by analyzing the weights of them in the detection of
PCa using Fisher linear discriminant analysis (FLDA),
and then (b) evaluate ADC value, metabolic ratio
((Cho þ Cr)/Cit) and the combination of the two by
FLDA in identifying malignant regions.
MATERIALS AND METHODS
Database
After institutional review board approval and written
informed consent, fifty-six consecutive patients were
retrospectively evaluated in this study from 2007–
2009. Inclusion criteria are: (a) The image data and
clinical record of the patient were available; (b) Transrectal ultrasound-guided biopsy was performed within
6 months of MR examination, with pathological record
of the cancerous and noncancerous areas in the prostate gland; (c) The patients had not received any treatments such as endocrine therapy, brachytherapy,
radiotherapy, etc., before MRI.
The Gleason score varied from 6 to 10 and 30
patients (54%) had a Gleason score of 7 or lower.
The 23 patients (41%) (mean age, 66.2 6 9.3 years;
range, 54–78 years) with benign prostate were all histopathologically confirmed. The histological diagnosis
on the basis of tissue obtained by transrectal ultrasound-guided sextant biopsy was benign prostatic
hyperplasia with or without chronic prostatitis or no
histological abnormality, but no evidence of prostatic
intraepithelial neoplasia. The serum PSA level ranged
from 0.61 to 29.63 ng/mL with a mean value of 9.9
ng/mL. All 33 PCa patients (59%) (mean age, 68.2 6
9.8 years; range, 56–79 years) were also histopathologically diagnosed by ultrasound-guided sextant prostate
biopsy. The serum PSA level ranged from 4.15 to 38.00
ng/mL with a mean value of 13.99 ng/mL.
MR Imaging
Thin-section, high-spatial-resolution transverse T2-WI
MR images of the prostate and seminal vesicles were
obtained on a 1.5 Tesla (T) whole-body MR scanner
(SignaTM; GE Medical Systems, Milwaukee, WI). The
patients were examined in supine position using a
body coil for excitation and a pelvic phased-array coil
(GE Medical Systems) for signal reception in combination with an expandable endorectal coil (Medrad,
Pittsburgh, PA). A fast spin-echo sequence was
applied with the following parameters: repetition
time/echo time of 3800/139 ms; echo train length,
12–16; section thickness, 3 mm; intersection gap, 0
mm; field of view, 26 cm; matrix, 320 256; and four
signal averages were acquired.
Li et al.
troscopy (PRESS) sequence, with high-bandwidth
spectral-spatial 180 refocusing pulses, and with very
selective outer voxel suppression pulses (9). A PRESS
volume encompassing the prostate was graphically
selected using the T2-weighted transverse images.
This volume was selected to maximize coverage of
prostate while minimizing the inclusion of periprostatic fat and rectal air. Dual-band spectral-spatial radiofrequency 180 pulses (10) and highly selective
outer voxel saturation pulses (11) were combined to
achieve water and lipid suppression. Additional voxel
saturation bands were selectively placed around the
selected region of interest to confine the shape of the
rectangular PRESS volume to the shape of the prostate. Three-dimensional MR spectroscopic imaging
data were acquired from the prostate with the following parameters: repetition time / echo time 1000/130
ms, field of view 11 cm and 16 8 8 phase encoding to yield spectra with a nominal resolution of 345
mm3 in approximately 17 min. The total MR acquisition time was typically approximately 50 min.
All 3D MR spectroscopy data were transferred offline and processed on a workstation (Functool, GE
Medical Systems) using specific commercially available software developed for 3D MR spectroscopy studies. The 3D MR spectroscopy data sets were apodized
with a 2-Hz Lorentzian function, Fourier transformed
in the time domain and three spatial domains. After
frequency, phase, and baseline correction, the integral
areas for the choline, creatine, and citrate resonances
were calculated.
Diffusion-Weighted Imaging
Diffusion-weighted imaging (DWI) data were acquired
by using single-shot diffusion-weighted echo-planar
imaging with repetition time (TR) of 3500 ms, echo
time (TE) of 56.7 [b ¼ 500 s/mm2, b ¼ 0 s/mm2] or
76.7 [b ¼ 800 s/mm2, b ¼ 0 s/mm2] ms, field of view
26 26 cm, matrix size 128 128, section thickness
6 mm, no intersection gap and four signal averages.
Fisher Linear Discriminant Analysis (FLDA)
FLDA was used to evaluate the weights of mean ADC
value and mean metabolic ratio ((Cho þ Cre)/Cit) in
the detection of prostate cancer. FLDA is a linear discriminative method to analyze the efficiency of each
feature vector in a certain task by their weights in the
discriminant. The weights reflect the utility of these
two features in prostate cancer diagnosis.
Given two classes with mean vectors M1, and M2,
the goal of FLDA is to find the linear projection, x,
which maximizes the contrast criterion J(x), the ratio
of inter-cluster distance to intra-cluster variance represented as:
J ðxÞ ¼ ðx 0 Sb xÞ=ðx 0 Sw xÞ
Three-Dimensional 1H MR Spectroscopic Imaging
Three-dimensional (3D) MR spectroscopic imaging
was performed using the prostate spectroscopy and
imaging examination (PROSE) sequence (GE Medical
Systems), which is a water- and lipid-suppressed double-spin-echo point-resolved spatially localized spec-
½1
where
Sw ¼
2 X
X
k¼1 x2Ck
ðx Mk Þðx Mk Þ0
½2
MRS and DWI in the Diagnosis of Prostate Cancer
3
Figure 1. Box-and-whisker plots
of mean ADC (b ¼ 500 s/mm2)
(a), mean ADC (b ¼ 800 s/mm2)
(b), and mean (Choline þ Creatine)/Citrate (c) in prostate cancer
and
benign
prostate
peripheral zone regions.
and
Sb ¼ ðM1 M2 ÞðM1 M2 Þ0
½3
are intra-cluster variance and inter-cluster distance,
respectively.
When
1
x ¼ Sw
ðM1 M2 Þ
½4
is satisfied, J(x) is maximized. Next, a new feature is
obtained by combining individual features with the
direction vector x:
*
D ¼ xT F ;
½5
*
where F are feature vectors.
Data Analysis
The first criterion chosen for inclusion of an MRS
voxel was that the signal-to-noise ratio (SNR) of the
three main metabolites (Cho, Cit, and Cr) in each
spectrum was greater than 3. The second criterion
was that there was no lipid peak at 2.0 ppm influencing Cit peak. The third criterion was that at least 70%
of the voxel was covered by peripheral zone.
Tumor regions were defined as low-signal-intensity
areas within peripheral zone in a sextant that was biopsy-positive on T2-weighted images and identified by
a radiologist who had more than 5 years experience in
interpreting prostate MRI. On the contrary, benign
regions were defined as normal signal intensity areas
within peripheral zone in a sextant that was biopsynegative on T2-weighted images. The identified
regions on T2-weighted images were mapped on the
MRS imaging grid and ADC map for voxel and region
selection. For MRS, tumor region consisted of all voxels whose 60% were covered by tumor tissue on the
basis of comparison of the grid with T2-weighted
images within a sextant region. Corresponding regions
were selected from ADC maps on the basis of T2weighted (b ¼ 0) images to minimize the partial volume effect, because of the one to one correspondence
of the ADC voxels to the voxels of the T2-weighted
images.
Sextant regions containing tumor foci that were 0.1
cm3 or smaller or more than 50% invalid voxels were
excluded to avoid the bias resulted from partial volume. The corresponding sextant regions in DWI were
eliminated at the same time. Two hundred twentyeight (67%) sextant regions were involved in the analysis. Mean ADC value and mean metabolic ratio for
malignant regions and benign sextant regions were
calculated.
Statistical Analysis
T-tests were performed to evaluate the differences
between groups of benign and malignant regions
characterized by mean ADC, mean metabolic ratio
((Cho þ Cre)/Cit) and the combination of the two.
Classification performance was evaluated by receiver
operating characteristic (ROC) (12,13) analysis based
on biopsy results. The area under the ROC curve (Az)
was used as an index to evaluate the inherent distinguishing capacity of mean ADC, mean metabolic
ratio, and the combination of the two in differentiating
between noncancerous and cancerous cases. A
4
Li et al.
Figure 2. A 72-year-old man with a current PSA level of 27.5 mg/mL and biopsy-proved cancer (Gleason score of 5 þ 4) in
the right peripheral zone. a: The selected volume for spectroscopy (white box) is overlaid on the transverse T2-weighted
(3800/139) image. And two areas in the volume are chosen for both comparisons of ADC and metabolic ratio. An area locates
in the cancer right peripheral zone (1) and another one locates in the normal left peripheral zone (2). b: ADC color map
obtained using b value of 800. ADC value in the cancer right peripheral zone (0.96 103 mm2/s) is lower than that in benign tissue in the left peripheral zone (1.73 103 mm2/s). c: MR spectrums obtained from the cancer right peripheral area
(1 in a) shows elevated choline and reduced citrate, and its metabolic ratio ((Cho þ Cr)/Cit) is 4.14. d: MR spectrums
obtained from the normal left peripheral zone (2 in a) shows a normal spectral pattern with high citrate and the absence of
an elevated choline, and its metabolic ratio ((Cho þ Cr)/Cit) is 0.686.
P value less than 0.05 was selected as the criterion of
statistical significance.
RESULTS
In our study, according to the MRS inclusion criteria,
we obtained 336 sextant regions and 1305 voxels.
Among those voxels, (a) Eighty-seven voxels were
excluded because they had a low SNR for all the three
main metabolites (Cho, Cit, and Cr); (b) Two hundred
fifty-three voxels were excluded because there were
large lipid peaks interfered the interpretation of Cit
peak; (c) Another 135 voxels were excluded because
they contained too much urethra and periprostatic
fatty tissue. Totally 475 voxels were nondiagnostic,
then 830 voxels and 247 sextant regions were available for further analysis.
Furthermore, 19 tumor sextant regions were
excluded for data analysis because no voxels locating
in those tumor region contained more than 60% tumor tissue. Finally, there were 228 sextant regions
(146 benign and 82 malignant) included in the study.
The median number of benign regions per patient
was four (range, zero to six), and the median number
of malignant regions per patient was four (range, zero
to six). The mean ADC values with b values of 500
and 800 s/mm2 and mean (Cho þ Cre)/Cit are shown
in Figure 1. The ADC values when b ¼ 800 were significantly different from those when b ¼ 500 for malignant regions and benign sextant regions (P ¼
0.0028). Figure 2 shows a sample MR images with the
corresponding 3D MRS imaging results and ADC
maps obtained using b ¼ 800.
The weights of mean ADC and mean metabolic ratio
((Cho þ Cre)/Cit) in the detection of prostate cancer
MRS and DWI in the Diagnosis of Prostate Cancer
5
Table 1
FLDA Weights for Combining Diffusion-Weighted With Different b
Values and MR Spectroscopic Imaging
Measurements
FLDA weight
2
b ¼ 500 (s/mm )
Mean ADC value
Mean (ChoþCre)/Cit
b ¼ 800 (s/mm2)
Mean ADC value
Mean (ChoþCre)/Cit
0.9388
0.0612
0.9374
0.0626
with different b values are shown in Table 1. The
mean ADC value with b values of 500 s/mm2 for all
patients for malignant regions in the PZ (mean 6
standard deviation (SD): 1.1441 6 0.4136 (103
mm2/s)) was significantly lower than that for benign
regions in the PZ (1.8213 6 0.3365 (103 mm2/s)) (P
< 0.001) (Table 2). Similarly, the mean ADC value
with b values of 800s/mm2 for all patients for malignant regions in the PZ (1.0603 6 0.1362 (103
mm2/s)) was significantly lower than that for benign
regions in the PZ (1.7053 6 0.3225 (103 mm2/s)) (P
< 0.001) (Table 2). The mean (Cho þ Cre)/Cit ratios
for all patients for malignant regions in the PZ
(2.7062 6 2.1746) was significantly higher than that
for benign regions in the PZ (1.1197 6 0.8146) (P <
0.01) (Table 2). Performance in differentiating malignant from benign regions in the PZ was evaluated by
ROC analysis (Fig. 3). Mean metabolite ratio alone
yielded an Az value of 0.778 (Table 3). No cutoff value
of metabolite ratio could be chosen to achieve 70% for
both sensitivity and specificity. A cutoff value of 0.81
resulted in a sensitivity of 56.1% and specificity of
88.4% (Table 4).
In the case of b ¼ 500 s/mm2, mean ADC alone
yielded an Az value of 0.892 (Table 3) and using a cutoff value of 1.49 103 mm2/s, cancer was detected
with a sensitivity of 85.4% and specificity of 87%
(Table 4). Mean ADC alone performed significantly
more accurately than mean metabolite ratio alone
(P < 0.01). The combination of metabolite ratio and
ADC yielding an Az value of 0.895 was also more
accurate than metabolite alone (P < 0.001), but there
was no significant improvement compared with mean
ADC alone (Fig. 3a).
When b ¼ 800 s/mm2, mean ADC alone yielded an
Az value of 0.897 (Table 3) and using a cutoff value of
1.26 103 mm2/s, cancer was detected with a sensitivity of 81.7% and specificity of 93.2% (Table 4).
Mean ADC alone was significantly more accurate than
mean metabolite ratio alone (P < 0.01). The combination of metabolite ratio and ADC yielded an Az value
of 0.901, achieving significantly better discrimination
of malignant from benign regions than metabolite
alone (P<0.001) and was also slightly better than
ADC alone, but the latter difference was not significant (Fig. 3b).
In both cases, the sensitivity of the combination
was significantly improved compared with metabolite
ratio alone (P < 0.001) (Table 4). There was a slight
improvement in specificity when b ¼ 800 s/mm2
(Table 4).
DISCUSSION
In this study, mean ADC with different b values and
mean metabolic ratio ((Cho þ Cr)/Cit) for benign sextant regions and malignant regions within sextant
regions were retrospectively calculated. Mean ADC
values were lower and mean metabolic ratios ((Cho þ
Cre)/Cit) were higher for malignant than for benign
PZ regions. These changes were consistent with those
reported in previous studies (5,7,8,14).
All the patients in our study underwent the same MR
protocol. Multi b values of 500 and 800 s/mm2, which
are common selections in our usual scanning, were used
to investigate whether diagnosis performance changes
with different b-value. Although significant difference
was found between ADC values from b ¼ 800 and b ¼
500 for both malignant regions and benign sextant
regions, there is no significant difference in either weight
analysis or diagnosis performance between ADC values
of two groups. Kitajima et al (15) reported that measuring ADC using a high b-value has little diagnostic
advantage over using the standard b-value in discriminating malignant from normal prostate tissue. The clinical benefit of high-b-value DWI has also been discussed,
although sacrificing the signal-to-noise ratio (16). Therefore, extending the analysis to include more and higher b
values could better assess the effect of b-value in diagnosis and provide better MR protocol of DWI.
FLDA is a linear discriminative method to analyze
the efficiency of each feature vector in a certain task
by their weights in the discriminant. There is a positive relation between weight and utility. The weights
ranges from 0 to 1, larger weight suggesting more
important role the corresponding feature plays in the
task. A weight of 1 indicates that the corresponding
feature is absolutely primary; on the contrary, a
weight of 0 indicates a neglectable feature. To our
knowledge, ours is the first study to use FLDA to
analysis the weights of MRS and DWI in prostate cancer diagnosis. Mean ADC weights obtained by FLDA
(0.9388 (b ¼ 500 s/mm2) and 0.9374(b ¼ 800 s/
mm2)) are much higher than those of mean metabolic
ratios (0.0612 (b ¼ 500 s/mm2) and 0.0626 (b ¼ 800
s/mm2)), indicating that DWI is more efficient than
MRS in the detection of PCa in the current study.
More efficient functional MRI techniques are superior
in prostate cancer screening and diagnosis and scan
program could be optimized by the weights obtained
by FLDA based on a larger patient population.
Table 2
Statistical Results of ADC and Metabolite Ratio
Measurement*
3
ADC (10 mm /s)
b ¼ 500 (s/mm2)
b ¼ 800 (s/mm2)
(ChoþCre)/Cit
Cancer region
Benign region
1.144160.4136
(0.157–2.25)
1.060360.1362
(0.368–2.28)
2.706262.1746
(0.475–7.998)
1.821360.3365
(0.92–2.57)
1.705360.3225
(0.833–2.7)
1.119760.8146
(0.2010–4.385)
2
*Data are mean 6 SD (range).
6
Li et al.
Figure 3. Receiver operating characteristic curves show performance of mean ADC alone, mean [(Choline þ Creatine)/Citrate] alone, and combination of the two to differentiate between cancer and benign regions in the case of (a) b ¼ 500 s/mm2
and (b) b ¼ 800 s/mm2.
In our study, combined ADC and metabolic ratio
((Cho þ Cr)/Cit) by FLDA was evaluated in identifying
malignant regions with sextant biopsy findings, as well
as mean ADC alone and mean metabolic ratio ((Cho þ
Cr)/Cit) alone. To avoid the registration problem
between different scan techniques and better
correspond to biopsy findings, the ADC values and metabolic ratios of all malignant voxels within a sextant
region were averaged as new indicators. This is different from previous studies (5,8) where a voxel to voxel
correspondence of tumor regions on ADC maps and
MRS maps is needed, whereas the voxels on ADC maps
cannot correspond exactly to the voxels on the MRS
maps because of the discrepancy in voxel size and scan
protocol. Combined ADC and metabolic ratio performed
better than metabolic ratio and ADC alone. This result
was consistent with previous results (5,8). However, accuracy improvements were not significant by using
combined ADC and metabolic ratio than ADC alone.
And ADC alone performed better than metabolic ratio
alone for both b values. These results were consistent
with (5), but contrary to the results of (8) that reported
that MRS alone performed better than DWI alone.
The deficiency of MRS in weight analysis and ROC
analysis was presumably attributed to susceptible signal by lipid contamination and low spatial resolution.
The spatial resolution of MRS is nearly tenfold lower
than that of DWI. Additionally, MRS took much longer
Table 3
Area Under Curve (Az) of Metabolite Ratio Alone, ADC Alone, and Combination of the Two in ROC Analysis
b ¼ 500 (s/mm2)
b ¼ 800 (s/mm2)
Measurement
Az*
Az*
(ChoþCre)/Cit
ADC
Combineda
0.77860.032 (0.715–0.841)
0.89260.025 (0.844–0.941)
0.89560.024 (0.848–0.942)
0.77860.032 (0.715–0.841)
0.89760.025 (0.849–0.945)
0.90160.024 (0.854–0.948)
*Data are mean 6 SD (95% confidence interval).
a
For b ¼ 500 (s/mm2), combined ¼ 0.9388ADC-0.0612(ChoþCre)/Cit; For b ¼ 800 (s/mm2), combined ¼ 0.9374ADC0.0626(ChoþCre)/Cit.
Table 4
Sensitivities, Specificities and Accuracies of Metabolite Ratio Alone, ADC Alone, and Combination of the Two as Predictors of Prostate
Cancer
b ¼ 500 (s/mm2)
Criterion for positive (cancer)*
(ChoþCre)/Cit
ADC
Combined
b ¼ 800 (s/mm2)
Sensitivity (%)
Specificity (%)
Accuracy (%)
Sensitivity (%)
Specificity (%)
Accuracy (%)
56.1
85.4
86.6
88.4
87.0
83.6
76.8
86.4
84.7
56.1
81.7
82.9
88.4
93.2
89.7
76.8
88.7
87.2
*Optimum cutoff values for b ¼ 500 (s/mm2): (ChoþCre)/Cit ¼ 0.81. ADC ¼ 1.34 103 mm2/s, combined ¼ 0.9388 ADC 0.0612 (ChoþCre)/Cit. Optimum cutoff values for b ¼ 800 (s/mm2): (ChoþCre)/Cit ¼ 1.96, ADC ¼ 1.26 103 mm2/s, combined ¼ 0.9374 ADC 0.0626 (ChoþCre)/Cit.
MRS and DWI in the Diagnosis of Prostate Cancer
time when imaging which is MRS’s another limitation.
However, many studies have reported advantages of
MRS including sensitivity to prostate cancer and correlation with Gleason score (17). Moreover, the disadvantage of low spatial resolution would be improved by
increasing field strength and using more efficient acquisition sequences (7). Thus, the accuracy of combined DWI and MRS with better spatial resolution
should be much improved and higher than that of each
technique alone in cancer identification.
Tumor regions were defined as low-signal-intensity
areas within peripheral zone in a sextant that was biopsy-positive on T2-weighted images, as described in
Reinsberg et al (8), and identified by experienced radiologist. As a result, malignant regions isointense to
normal peripheral zone tissue on T2-weighted images
were not included and there is also a false-positive rate
of mimic cancer associated with other benign abnormalities also presenting low signal intensity on T2weighted images. It is not possible to identify those
regions in the analysis without histologic proof of their
inclusion and exclusion with tumor. Although using
whole-mount histopathologic examination can improve
the accuracy of the registration between MR images
and histopathology (5), the availability of detailed histological comparison at radical prostatectomy has
highly limited studies. Moreover, sextant analysis
plays an important role not only in diagnostic purpose,
but also in determining the prognosis, particularly
before radical prostatectomy (18,19). Thus, despite of
the defects of biopsy, the findings of our study still
processed significance and merit in clinic practice.
However, patients might harbor cancer that escaped
one-time biopsy detection for prostate cancer heterogeneity, and the evaluation of the Gleason concordance
between biopsy and prostatectomy specimens has
demonstrated mixed results (20–24). Because most of
the patients were suggested hormone therapy, there is
no available whole-mount histopathology of the
patients in the current study. Therefore, prostatectomy
specimens and clinical follow-up are still needed as the
reference standard to further confirm the accuracy of
the current study. In addition, there is a huge overlap
between normal and malignant tissues detections for
both ADC and MRS. Therefore, more functional MR
imaging techniques will be incorporated into our future
research for better performance in discriminating
between cancer and benign regions.
In conclusion, DWI is more efficient than MRS in
the diagnosis of prostate cancer; combined mean ADC
value and mean metabolic ratio by FLDA provides a
new and useful index as an indicator of prostate cancer and the combination of DWI and MRS is promising in the detection of prostate cancer.
ACKNOWLEDGMENT
This work was supported by the Fundamental
Research Funds for the Central Universities.
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