Download Combined Use of Diffusion-Weighted MRI and H MR Spectroscopy

091.fm — 11/30/06
Reinsberg et al.
Prostate Cancer Detection
Using MRI and MR
Spectroscopy
Genitourinar y Imaging • Original Research
Combined Use of Diffusion-Weighted
MRI and 1H MR Spectroscopy to
Increase Accuracy in Prostate
Cancer Detection
Stefan A. Reinsberg1
Geoffrey S. Payne1
Sophie F. Riches1
Sue Ashley2
Jonathan M. Brewster3
Veronica A. Morgan1
Nandita M. deSouza1,3
Reinsberg SA, Payne GS, Riches SF, et al.
Keywords: diffusion-weighted MRI, genitourinary tract
imaging, MRI, MR spectroscopy, MR technique, oncologic
imaging, prostate cancer
DOI:10.2214/AJR.05.2198
Received December 21, 2005; accepted after revision
June 28, 2006.
Supported by Cancer Research UK (grant number
CUK C1060/A808). S. A. Reinsberg was supported by
Department of Health UK, New and Emerging Applications
of Technology, grant B132.
1Clinical Magnetic Resonance Group, Royal Marsden NHS
Foundation Trust, Royal Marsden Hospital, Downs Rd.,
Sutton, Surrey SM2 5PT, United Kingdom.
2Department of Statistics, Royal Marsden NHS Foundation
Trust, Sutton, Surrey, United Kingdom.
3Institute
of Cancer Research, Royal Marsden NHS
Foundation Trust, Sutton, Surrey, United Kingdom.
Address correspondence to N. M. deSouza
([email protected]).
AJR 2007; 188:91–98
0361–803X/07/1881–91
© American Roentgen Ray Society
AJR:188, January 2007
OBJECTIVE. The objective of our study was to establish the sensitivity and specificity
for prostate cancer detection using a combined 1H MR spectroscopy and diffusion-weighted
MRI approach.
SUBJECTS AND METHODS. Forty-two men (mean age ± SD, 69.3 ± 4.7 years) with
prostate cancer were studied using endorectal T2-weighted imaging, 2D chemical shift imaging (CSI), and isotropic apparent diffusion coefficient (ADC) maps. Regions of interest (ROIs)
were drawn around the entire gland, central gland, and peripheral zone tumor, diagnostically
defined as low signal intensity on T2-weighted images within a sextant that was biopsy-positive
for tumor. Lack of susceptibility artifact on a gradient-echo B0 map through the slice selected
for CSI and no high signal intensity on external array T1-weighted images confirmed the absence of significant hemorrhage after biopsy. CSI voxels were classified as nonmalignant or as
tumor (ROI included ≥ 30% or ≥ 70% tumor). Choline–citrate (Cho/Cit) ratios and average
ADCs were calculated for every voxel. A plot of Cho/Cit ratios versus ADCs yielded a line of
best separation of tumor voxels from nonmalignant voxels. Receiver operating characteristic
(ROC) curves were plotted for Cho/Cit ratios alone, ADCs alone, and a combination of the two.
RESULTS. The Cho/Cit ratios were significantly higher (p < 0.001) and the ADCs were
significantly lower (p < 0.006) in tumor-containing voxels than in non–tumor-containing voxels. When voxels containing 30% or more tumor were considered positive, the area under the
ROC curves using combined MR spectroscopy and ADC (0.81) was similar to that of Cho/Cit
alone (0.79) and better than ADC alone (0.66). When voxels containing 70% or more tumor
were considered positive and cutoffs to achieve a 90%-or-greater sensitivity chosen, a combination of Cho/Cit and ADC achieved a significant improvement in specificity compared with
Cho/Cit alone (p < 0.0001) or ADC alone (p < 0.0001).
CONCLUSION. When voxels containing ≥ 70% tumor are considered positive, the combined use of MR spectroscopy and diffusion-weighted MRI increases the specificity for prostate cancer detection while retaining the sensitivity compared with MR spectroscopy alone or
diffusion-weighted MRI alone.
n men with an elevated level of serum prostate-specific antigen
(PSA), the definitive diagnosis of
prostate cancer requires histology
of a sample that is obtained invasively at endorectal sonographically guided biopsy. Noninvasive imaging techniques, such as T2weighted MRI with an external pelvic array
coil, have a good specificity (90%) but a relatively low sensitivity (27.3%) for tumor detection [1]. With the higher spatial resolution
afforded by the use of endorectal receiver
coils, the sensitivity and positive predictive
value for the detection of tumor foci larger
than 1 cm in diameter on T2-weighted MRI
are relatively high (85.3% and 92.6%, respec-
I
tively), but these values fall dramatically to
26.2% and 75.9%, respectively, when tumors
less than 1 cm in diameter are considered [2].
Overall, sensitivity and specificity for tumor
localization are approximately 60% and 63%,
respectively [3]. Contrast mechanisms other
than T2-weighted imaging used in conjunction with high-spatial-resolution endorectal
techniques are therefore being sought.
MR spectroscopy offers some improvement in sensitivity and specificity for prostate
cancer detection [4–6]. Specifically, a significant reduction of citrate (Cit) and an elevation of choline (Cho) levels have been documented in prostatic adenocarcinomas as
compared with normal prostatic peripheral
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zone tissue and benign prostatic hypertrophy.
Recently, the use of 3D chemical shift imaging (CSI) has been shown to improve the sensitivity and specificity for tumor detection to
95% and 81%, respectively [7]. Another alternative to T2-weighted MRI is to develop image contrast through “apparent diffusivity,”
tissue water incoherent displacement over
distances of approximately 1–20 µm. Diffusion-weighted MRI is showing potential for
improving prostate cancer detection [8–10].
The purposes of this study therefore were to
determine the metabolic ratios on 2D chemical shift 1H MR spectroscopy and the apparent diffusion coefficient (ADC) in patients
with histologically proven prostate cancer
and to establish the sensitivity and specificity
of prostate cancer detection using a combined
MR spectroscopy and diffusion-weighted
MRI approach.
Subjects and Methods
Patient Population
This was a prospective, single-institution, crosssectional study with institutional approval from the
local research ethics committee and all patients
provided informed consent. The study population
consisted of 42 patients newly diagnosed with prostate cancer on the basis of an elevated PSA level
and positive findings for cancer on transrectal sonographically guided biopsy who were willing to undergo additional endorectal scanning. There was no
history of pelvic radiation therapy, thermal therapy
to the prostate, or chemotherapy. All patients had a
clinical stage less than or equal to T3 N0 M0 (23
were T1c, eight were T2a, two were T2b, and nine
were T3a).
A minimum of six cores had been obtained from
each patient. The number of positive cores varied
from one to four, and Gleason grade varied from 6
to 8. Patients ranged in age from 60 to 78 years
(mean ± SD, 69.3 ± 4.7 years) with PSA values
ranging from 0.45 to 45 ng/mL (median, 10.2
ng/mL; lower and upper quartiles, 6.0 and 16.2
ng/mL). Over a 13-month period, patients underwent diffusion-weighted MRI and 1H MR spectroscopy of the prostate during the same examination as
the routine staging MRI examination performed at
a median of 21 days (lower and upper quartiles, 12
and 49 days) after the most recent biopsy.
MRI and 1H MR Spectroscopy
MR studies were performed on a 1.5-T unit (Intera, Philips Medical Systems) using an endorectal
coil with a balloon inflated with 55 mL of air. Hyoscine butyl bromide (20 mg) was administered intramuscularly immediately before centering the patient in the scanner to reduce peristalsis: The use of
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hyoscine butyl bromide is routine at our institution
for abdominopelvic MRI, and hyoscine butyl bromide is preferred to glucagon because of its more
effective antiperistalsis capability. None of our patients had a history of urine retention. Although
hyoscine butyl bromide is contraindicated in patients with large prostates and urine retention, given
intramuscularly at this dose, we have seen no cases
of urine retention in the more than 500 prostate examinations we have performed.
Conventional T2-weighted turbo spin-echo
(TSE) images were obtained in three orthogonal
planes (TSE; TR/effective TE, 2,000/90; echo-train
length, 16; 2 signal averages) with a 256 × 512 matrix, 3-mm slice thickness, no gap, and a 14-cm
field of view; the total imaging time was 12 minutes. Echo-planar diffusion-weighted images
(TR/TE, 2,500/69) with b values of 0, 300, 500, and
800 s/mm2 were obtained transverse to the prostate
and parallel to the corresponding set of T2weighted images. The phase-encoding gradient
was from left to right to minimize motion artifacts
in the prostate. Twelve 4-mm-thick slices (no gap;
20-cm field of view; matrix, 128) provided coverage of the prostate with an image acquisition time
of 1 minute 24 seconds. ADC maps were generated
using the system software.
In addition, CSI was performed over a single
slice transverse to the prostate, using a thickness
of 15 mm and a 16 × 16 grid (voxel size,
8.75 × 8.75 × 15 mm3). The slice was selected by
identifying a focal low-signal-intensity abnormality on the axial T2-weighted scans within a sextant
that was biopsy-positive for tumor and centering
there. Signal collection was restricted to voxels
over the prostate using the point-resolved spectroscopy (PRESS) localization technique (TR/TE,
1,500/120). An automated shimming method over
the PRESS volume used scanner software to adjust
the x, y, and z axis gradients in small increments and
test for the best line shape. Lipid suppression, by
frequency-selective inversion before PRESS excitation, and water suppression, using band-selective
inversion with gradient dephasing (BASING [11]),
were included. Regional saturation was not required due to acceptably low levels of lipid contamination in both the central and peripheral voxels.
Data acquisition took 12 minutes. The spectroscopy data were voxel-shifted to align the CSI data
set with the PRESS box and were exported for analysis with LCModel fitting package (Stephen
Provencher, Inc.) [12] using a basis set containing
metabolite spectra from choline, creatine, and citrate. B0 maps (dual gradient-echo; TR/first-echo
TE, second-echo TE, 50/7.6, 17.6) were obtained
before MR spectroscopy in all cases to ensure that
there was no significant susceptibility artifact from
hemorrhage within the prostate.
After endorectal MRI and MR spectroscopy, an
external pelvic phased-array coil was used to acquire axial T1-weighted (TSE; TR/TE, 650/7) and
T2-weighted (TSE; TR/effective TE, 5,396/80) images through the pelvis as part of the routine clinical staging scan. The B0 maps and T1-weighted images confirmed the absence of any significant
postbiopsy hemorrhage in this patient cohort.
Data Analysis
The five consecutive T2-weighted slices that
corresponded to the thicker CSI slice were identified. On each of these, ROIs were drawn by a radiologist, who had 8 years’ experience in interpreting
prostate MRI at the time of the study, for the entire
prostate; central gland; and tumor, defined as lowsignal-intensity areas within the peripheral zone in
a sextant that was biopsy-positive for tumor. Isointense tumors were thus not included in this analysis.
The median tumor ROI size was 1.45 cm2, with
lower and upper quartiles of 0.69 and 2.1 cm2. The
absence of significant postbiopsy hemorrhage was
confirmed on the B0 maps and T1-weighted external array images.
The first criterion chosen for inclusion of a voxel
in the analysis was that the overall signal-to-noise
ratio (SNR) calculated by the LCModel fitting
package [12] in each spectrum should be greater
than 2. The SNR in the LCModel is defined as the
maximum signal within the frequency range of interest in the baseline-corrected spectrum divided by
twice the root-mean-square residuals. A possible
alternative criterion that both the choline and citrate
signals must satisfy a specific Cramer-Rao minimum variance bound would result in voxels containing significant tumor volume being rejected due
to an absence of citrate. The criterion chosen led to
the inclusion of spectra from a total of 511 voxels
in 42 patients. A second criterion was that the voxel
included should be formed of at least 70% prostate
gland as determined by the ROIs in the five corresponding T2-weighted slices. This process eliminated an additional 113 voxels, leaving a total of
398 voxels for inclusion in the analysis.
Tumor voxels were defined using two different
thresholds: ≥ 30% or ≥ 70% tumor based on proportion of tumor ROI identified on the T2-weighted
image within the voxel. Using the biopsy-supported ROIs outlined on the T2-weighted scans, the
398 CSI voxels were classified into nontumor
peripheral zone (0% tumor and ≥ 70% peripheral
zone, n = 24), nontumor central gland (0% tumor
and ≥ 70% central gland, n = 180), nontumor
mixed voxels (0% tumor, < 70% central gland,
< 70% peripheral zone, n = 68), and tumor (tumor
ROI occupying ≥ 30% [n = 47] or ≥ 70% [n = 15]
of the voxel). The small number of nontumor peripheral zone voxels is due to central gland enlarge-
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Prostate Cancer Detection Using MRI and MR Spectroscopy
A
B
Cit
15
Intensity (AU)
Intensity (AU)
10
Cho
5
10
5
0
0
4.0
Cit
Cho
15
3.5
3.0
ppm
2.5
2.0
4.0
C
3.5
3.0
ppm
2.5
2.0
D
Fig. 1—75-year-old man with prostate cancer.
A, Endorectal T2-weighted transverse image through mid prostate shows well-defined low-signal-intensity region in peripheral zone on left (arrows), within sextant that was
positive for tumor on biopsy.
B, Radiologist-determined region of interest around tumor and overlay of voxels for MR spectroscopy acquisition are seen.
C and D, Hydrogen-1 MR spectroscopy from a voxel of nonmalignant peripheral zone on right (signal-to-noise ratio [SNR] = 4) (C) is compared with a spectrum from malignant
peripheral zone nodule on left (SNR = 3) (D). Gray line shows data and black line represents fit using LCModel (Stephen Provencher, Inc.) (both smoothed for display using
5-point weighted average). Increase in choline (Cho) (3.2 ppm) and decrease in citrate (Cit) (2.6 ppm) are seen in D compared with C. In C, Cho/Cit ratio is 0.31; in D, 0.45.
AU = arbitrary units.
(Fig. 1 continues on next page)
ment in this age group, resulting in predominantly
central gland or mixed voxels. Thus, 319 and 287 of
the 398 voxels were included in the ≥ 30% tumor
and ≥ 70% tumor analyses, respectively; the remaining voxels contained smaller tumor volumes
and were not considered. ADC maps were coregistered with high-resolution T2-weighted images and
CSI spectroscopy. Metabolite levels and their ratios
and average ADCs were calculated for every voxel
classified on MR spectroscopy (Fig. 1). The
LCModel fitting package [12] calculated the
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Cramer-Rao minimum variance bounds (% SD) for
each peak; a peak was regarded as significant if this
value was less than 20%.
Statistical Analysis
Statistical analysis of the data was performed using SPSS software (version 11.0, SPSS) for Windows
(Microsoft) and in-house software developed using
Interactive Data Language (IDL, ITTVIS Ltd.). Because clear separation between choline and creatine
was obtained in our data, the ratios of Cho/Cit (rather
than needing to use [choline + creatine] / citrate) and
ADC from each voxel type (nontumor, ≥ 30% tumor,
and ≥ 70% tumor) were computed and compared.
Normality plots and the Shapiro and Francia test for
normality showed the data from the Cho/Cit ratios
were nonparametric, whereas the data from the ADC
maps were parametric. Therefore, the Cho/Cit data
were normalized by taking the log (to base 10) of values, and both sets of data were investigated using
parametric statistical tests. One-way analysis of variance tests were used to detect differences between
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E
F
Fig. 1 (continued)—75-year-old man with prostate cancer.
E and F, Apparent diffusion coefficient (ADC) map at native resolution (E) and ADC map resampled to match MR spectroscopy resolution (F) show restricted diffusion in left
peripheral zone (mean ADC: tumor-containing voxel, 0.8 × 10−3 mm2/s; non–tumor-containing voxel, 1.24 × 10−3 mm2/s).
from nontumor voxels was drawn (Fig. 2). The position of this line was determined by varying the angle to the horizontal in small incremental steps and
determining the angle that resulted in the ROC
curve with the highest area under the curve (AUC).
This optimal ROC curve was then used to select the
dividing line for the combination of Cho/Cit ratio
and ADC. For voxels containing ≥ 70% tumor, cutoffs were chosen to achieve at least 90% sensitivity.
One-sided significance tests were used to compare
differences in the sensitivity and specificity of the
combination of Cho/Cit ratio with ADC over either
technique alone, and a p value of less than 0.05 was
chosen as the criterion for statistical significance.
10.00-
Cho/Cit
1.000
0.100
0.010
0.001
0.8
1.0
1.2
1.4
1.6
1.8
2.0
ADC (10–3 mm2/s)
Fig. 2—Scatterplot of choline–citrate (Cho/Cit) ratio versus apparent diffusion coefficient (ADC) for MR
spectroscopy voxels with minimum signal-to-noise ratio of 2. Tumor voxels (…) were those that contained 70% or
more tumor, as outlined on T2-weighted images. Peripheral zone voxels (×) are non–tumor-containing voxels with
at least 70% peripheral zone, and central gland voxels (+) are non–tumor-containing voxels with 70% or more
central gland. Non–tumor-containing voxels, which do not reach either of these classification thresholds, are
labeled peripheral zone, central gland, or central gland–peripheral zone mixed („). Line optimally separating tumor
from nontumor voxels is shown.
nontumor and either ≥ 30% tumor or ≥ 70% tumor
voxels. The Student’s t test for independent samples
was used to compare peripheral zone or central gland
voxels with tumor voxels. Significance tests were
two-sided, and a p value of less than 0.05 was chosen
as the criterion for statistical significance.
Sensitivities and specificities for identifying tumor within a voxel using MR spectroscopy alone or
diffusion-weighted imaging alone were calculated.
94
Receiver operating characteristic (ROC) curves
were used to show the power of the Cho/Cit ratios
and ADCs as predictors of tumor at histology. ROC
curves considering voxels containing ≥ 30% tumor
and those considering voxels containing ≥ 70% tumor were plotted for Cho/Cit ratios alone, ADCs
alone, and a combination of the two. For the latter,
a 2D plot of the log10 Cho/Cit ratios versus ADCs
was obtained, and a line that best separated tumor
Results
Figure 1 shows a focal low-signal-intensity
lesion on T2-weighted imaging that was positive for tumor at biopsy with corresponding
spectra from CSI voxels and an ADC map.
The Cho/Cit ratio was higher in tumor-containing voxels than in non–tumor-containing
voxels (Table 1). Univariate analysis of variance for each tumor threshold showed that the
Cho/Cit ratios were significantly higher in
both classes of tumor-containing voxels than
in non–tumor-containing voxels (p < 0.001).
When ≥ 30% tumor within a voxel was considered positive, an ROC curve of the relation
between the log10 (Cho/Cit) and the diagnosis
of tumor showed the AUC to be 0.79 (95% CI,
0.71–0.88; Fig. 3A). For this 30% threshold,
the optimum discrimination suggested by the
ROC curve was at a cutoff Cho/Cit ratio
of > 0.07 (log10[Cho/Cit] = –1.15); voxels
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Prostate Cancer Detection Using MRI and MR Spectroscopy
TABLE 1: Metabolite Ratios and Apparent Diffusion Coefficients (ADCs) in the
Five Classes of Voxel
Choline/Citrate
(mean ± SD [range])
ADC × 10–3 mm2/s
(mean ± SD [range])
Peripheral zone
0.065 ± 0.052 (0–0.237)
1.51 ± 0.27 (1.05–2.05)
Central gland
0.077 ± 0.074 (0–0.721)
1.31 ± 0.20 (0.82–1.78)
Class of Voxel
0.11 ± 0.31 (0–2.44)
1.34 ± 0.24 (0.86–1.86)
Tumor ≥ 30% of voxel
0.814 ± 2.202 (0 to ∞)
1.19 ± 0.24 (0.71–1.93)
Tumor ≥ 70% of voxel
0.918 ± 1.276 (0.06 to ∞)
1.03 ± 0.18 (0.74–1.38)
1.0
1.0
0.8
0.8
Sensitivity
Sensitivity
Mixed voxels
0.6
0.4
0.2
0.0
0.0
0.6
0.4
0.2
0.2
0.4
0.6
0.8
0.0
0.0
1.0
1 – Specificity
0.2
0.4
0.6
0.8
1.0
1 – Specificity
A
B
Fig. 3—Receiver operating characteristic (ROC) curves.
A and B, ROC curves show power of choline–citrate (Cho/Cit) ratio alone (dashed line), apparent diffusion
coefficient (ADC) alone (dotted line), and combination of the two (solid line) as predictors of tumor at histology
when voxels containing ≥ 30% tumor as defined by tumor regions of interest on T2-weighted images are
considered positive (A) and when voxels containing ≥ 70% tumor are considered positive (B).
containing 30% tumor could be predicted
with a sensitivity of 80.9% and specificity of
64.3% (Table 2). When ≥ 70% tumor within a
voxel was considered positive, the optimum
discrimination was at a cutoff value of
Cho/Cit ratio of > 0.081 (log10[Cho/Cit] =
–1.089), resulting in a sensitivity of 93.3%
and specificity of 73.2% (AUC, 0.92; 95% CI,
0.85–0.99; Fig. 3B). This improvement was
statistically significant (p < 0.01).
Mean ADC values were obtained from voxels defined for 2D MR spectroscopy. Because
of the large voxel size, the average values obtained did not differentiate tumor voxels with
the sensitivity that is possible when using ADC
maps at their native resolution of 1.5 mm3
(Fig. 1). ADC values were lower in tumor-containing voxels than in non–tumor-containing
voxels (Table 1). Voxels in the central gland
tended to show smaller ADCs than peripheral
zone voxels and to partially overlap with voxels
comprising 30–70% tumor (Table 1).
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Univariate analysis of variance showed that
the ADCs were significantly lower in both
classes of tumor-containing voxels than in
the non–tumor-containing voxels (p < 0.006).
There were also significant differences between normal peripheral zone and central gland
voxels (p < 0.001) and between voxels containing ≥ 30% tumor and those containing ≥ 70%
tumor (p < 0.01). When ≥ 30% tumor within a
voxel was considered positive, an ROC curve of
the relation between the ADC and the diagnosis
of tumor showed the AUC to be 0.66 (95% CI,
0.58–0.75; Fig. 3A). No cutoff value of ADC
could be chosen to achieve at least 70% sensitivity and specificity. When voxels containing
≥ 70% tumor were considered, the AUC was
0.85 (95% CI, 0.76–0.95) and using a cutoff of
1.26 × 10−3 mm2/s, tumor could be predicted
with a sensitivity of 93.3% and specificity of
57.4% (Table 2). Sensitivity and specificity for
≥ 30% tumor voxels using this ADC cutoff
were 67.3% and 59.9%, respectively.
A combined analysis of Cho/Cit ratios and
ADCs was also done. When ≥ 30% tumor
within a voxel was considered positive, an ROC
curve of the relation between a combination of
log10(Cho/Cit) and ADC and the diagnosis of
tumor showed the AUC to be 0.81 (95% CI,
0.73–0.88), and there was no improvement
compared with the Cho/Cit curve alone
(Fig. 3A). When ≥ 70% tumor within a voxel
was considered positive, an ROC curve of
the relation between a combination of log10
(Cho/Cit) and ADC and the diagnosis of tumor
showed the AUC to be 0.98 (95% CI,
0.95–0.995) (Fig. 3B and Table 2), which
achieved a better separation of tumor-containing and non–tumor-containing voxels than
ADC alone or log10(Cho/Cit) alone (p < 0.05).
The optimal separation for the ≥ 70% tumorcontaining voxels is described by the relationship log10(Cho/Cit) = 1.946 × ADC – 3.088
(Fig. 2). Using this dividing line gives a sensitivity of 93.3% and a specificity of 90.9% for tumor diagnosis.
For comparison, a similar optimized separating line for the ≥ 30% tumor voxels given
by the relationship log10(Cho/Cit) = 0.910 ×
ADC – 2.102 resulted in a sensitivity of
70.2% and a specificity of 83.5%. Because
achieving > 90% sensitivity was used as the
criterion for comparison, it was not possible
to test for an improvement in sensitivity.
However, for ≥ 70% tumor-containing voxels,
specificity of the combination was significantly improved compared with either
Cho/Cit ratio alone (p < 0.0001) or ADC
alone (p < 0.0001). With a sensitivity of
100% for the combination of Cho/Cit and
ADC, a specificity of 90% could be achieved
(Table 2).
To assess the quality of the ROC curves
used for predicting the sensitivity and specificity tumor presence, the AUC was plotted
against tumor fraction in the voxel (Fig. 4).
The AUC values increased with increasing tumor fraction in the voxel, consistent with a reduced contamination of the data from nonmalignant tissue within the voxel.
Discussion
Our study shows that when voxels containing ≥ 70% tumor are considered positive for
tumor, the combination of MR spectroscopy
and diffusion-weighted MRI increases the
specificity of prostate cancer detection while
retaining sensitivity compared with MR spectroscopy alone or diffusion-weighted MRI
alone. The altered cellular metabolites from
tumor-containing voxels and changes in ADC
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TABLE 2: Sensitivities, Specificities, and Accuracies of Choline–Citrate (Cho/Cit) Ratio Alone, Apparent Diffusion
Coefficient (ADC) Alone, and a Combination of the Two for the Detection of Tumor in the Prostate
Tumor ≥ 30% of Voxel
Tumor ≥ 70% of Voxel
Sensitivity
(%)
Specificity
(%)
Accuracy
(%)
Log10Cho/Cit > optimum cutoff value
80.9
64.3
66.8
ADC > optimum cutoff value
67.3
59.9
61.1
0.666
93.3
57.4
59.2
0.851
Combined: log10Cho/Cit > optimum cutoff value
70.2
83.5
81.5
0.805
93.3
(100.0)a
90.9
(90.0)a
91.1
(92.7)a
0.978
Criterion to Test Positive for Cancer
AUC
Sensitivity
(%)
Specificity
(%)
Accuracy
(%)
AUC
0.791
93.3
73.2
74.2
0.919
Note—Optimum cutoff values for ≥ 30% voxels: log10Cho/Cit = –1.15, ADC = 1.26 × 10–3 mm2/s, combined log10Cho/Cit and ADC = (0.910 × ADC) –2.102. Optimum cutoff values
for ≥ 70% voxels: log10Cho/Cit = –1.089, ADC = 1.26 × 10–3 mm2/s, combined log10Cho/Cit and ADC = (1.946 × ADC) –3.088. AUC = area under the receiver operating
characteristic curve.
a Different choice of cutoff between nonmalignant and tumor voxels that achieve a sensitivity of 100%.
1.0
AUC
0.8
0.6
0.4
0.2
0.0
0
20
40
60
80
Tumor Fraction (%)
reflecting restricted extracellular water diffusion in hypercellular tumor regions were considered together to produce significant increases in specificity compared with either
technique alone. Although endorectal T2weighted MRI is well established as a local
staging technique for identifying extracapsular tumor extension [13, 14], newer treatment
strategies (e.g., imaging-guided brachytherapy [15, 16], photodynamic therapy [17], and
cryoablation [18]) demand more precise information about the presence of tumor and the
location of tumor in organ-confined disease in
order for treatment areas to be tailored to regions of the prostate gland where cancer is
present. Moreover, patient selection for and
maintenance in an active surveillance program are assisted by accurate information
about tumor localization, size, and growth
and may obviate repeat biopsies.
In patients with an elevated PSA level but
repeatedly negative findings at prostatic biopsy, identifying likely sites of tumor is vital
for guiding future biopsies. T2-weighted endorectal MRI alone has proved useful in reliably depicting large (> 1 cm) tumors [2], but
remains prohibitive for diagnosing small tumors. We have shown the potential of a combined MR spectroscopy and diffusion-
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100
Fig. 4—Quality of receiver operating characteristic curves as measured by area
under curve (AUC) as function of tumor fraction in voxel. As expected, there is
increase in AUC with increasing tumor fraction for all parameters measured due to
reduction of normal tissue in tumor voxel. Choline–citrate ratio alone (dashed line),
apparent diffusion coefficient alone (dotted line), and combination of the two (solid
line) are shown.
weighted imaging approach for prostate cancer detection. However, to define the best cutoff values for metabolite ratios and ADCs,
further work is needed to determine their reproducibility. Also, the voxels used in our
study were relatively large; future use of 3D
MR spectroscopy techniques with smaller
voxels would permit the detection of smaller
tumors. It would also make the addition of
diffusion-weighted imaging more valuable
because diffusion-weighted imaging would
have fewer partial volume effects from being
used at a large spectroscopic voxel resolution.
The use of MR spectroscopy as a diagnostic
tool for improving the accuracy of prostate
cancer detection has been extensively investigated [4, 7, 19]. Initial studies using multivoxel
MR spectroscopy with T2-weighted MRI
showed that the combination improved accuracy of cancer localization to 81% compared
with 71.4% for MRI alone [20]. Studies for
evaluating sensitivity and specificity have
largely been limited by the availability of detailed histologic comparison at radical prostatectomy. One study of 47 patients comparing
MRI and MR spectroscopy with sextant biopsy
against step section histology showed that MRI
and MR spectroscopy were more sensitive but
less specific than sextant biopsy at prostate
cancer detection [21] and that the combination
was better than MRI alone. With the use of various combinations of MRI and 3D MR spectroscopic imaging, a point on the ROC curve
can be chosen that provides either high sensitivity or high specificity depending on clinical
requirements. A positive result with combined
MRI and 3D MR spectroscopic imaging (> 3
SDs) indicates the presence of tumor with high
probability (positive predictive value, 89–92%),
whereas a negative result (> 2 SDs) excludes
the presence of cancer with high probability
(negative predictive value, 74–82%). The main
limitation of our study for clinical application
is the acquisition of only a single-slice 2D CSI.
However, this does not affect the validity of our
finding and is not a fundamental limitation;
both multislice 2D CSI and full 3D CSI can
also be implemented.
In our study, water suppression using BASING [11], together with the further reduction
of residual water within the LCModel, was
sufficient to produce spectra with negligible
interference from water. Some of the early
prostate MR spectroscopy measurements used
both CHESS (chemical shift selective) for
water suppression and inversion pulses for fat
suppression, a combination that inevitably led
to some compromises and imperfect suppres-
AJR:188, January 2007
091.fm — 11/30/06
Prostate Cancer Detection Using MRI and MR Spectroscopy
sion of water and lipid. Dual-band BASING
and spectral–spatial pulses have been recommended to solve this problem [22]. However,
we found that the combination of a simple frequency-selective inversion pulse followed by
a relaxation delay before the PRESS localization reduced signals from lipid to a satisfactory level. Also, although some authors have
found it helpful to use saturation bands to reduce lipid contamination from outside the
slice [22], visual inspection of our data showed
no sign of large lipid peaks. In addition, in
two patients scanned with and without saturation bands, a comparison of 40 voxels (with
sufficient SNR to give < 20% uncertainty in
peak areas) showed no significant difference
(p > 0.1) in mean metabolite values.
The sensitivity of MR spectroscopy, however, may be affected by cancer grade: A
study by Zakian et al. [23] suggests that small
low-grade tumors may be missed using 3D
MR spectroscopic imaging because the severity of metabolite alteration correlates with tumor aggressiveness. There was a trend toward
increasing the ([Cho + creatine] / Cit) value
with increasing Gleason score in lesions identified correctly with MR spectroscopic imaging. In our study, all but one of the tumors had
a Gleason grade > 6.
More recently, diffusion-weighted MRI has
also been evaluated for its ability to show the
prostate, primarily in animal models. An increase in the ADC has been noted in a subcutaneously implanted rat prostate tumor after
chemotherapy [24]. Using nuclear MR microscopy, Artemov et al. [25] showed different diffusion rates for two prostate cancer cell lines. A
study at 4.7 T showed improved prostate tumor
detection in transgenic mice using diffusion-weighted imaging compared with T2
mapping [26]. Preliminary work on diffusionweighted imaging of the prostate in vivo in humans has shown differences between tissue
types warranting clinical investigation [8, 9, 27,
28], and a recent study of 60 patients showed
that the addition of diffusion-weighted imaging
to conventional T2-weighted imaging significantly improved tumor detection [8].
In the present study, we were assessing diffusion-weighted imaging at a much lower resolution with a voxel size commonly used for
MR spectroscopy. Despite this, the addition of
the diffusion-weighted imaging data to the MR
spectroscopy data significantly improved specificity to 90%. Because it is easy to implement,
available on most standard MR scanners, and
incurs little time penalty (1.5 minutes), it is
worth incorporating diffusion-weighted imag-
AJR:188, January 2007
ing into the standard prostate MRI and MR
spectroscopy protocol. In this study, tumor foci
of 1 cm3 within a voxel could be identified with
a high degree of certainty.
The use of an air-filled balloon endorectal
coil potentially has several technical limitations.
The local field inhomogeneities cause difficulties in shimming and result in line broadening.
Further, our diffusion-weighted images were
acquired with an echo-planar readout, which
leads to some distortion in the neighborhood of
tissue boundaries where there is a discontinuity
in magnetic susceptibility. There is also sometimes a shift in the phase-encode direction owing to a slight offset of the water resonance frequency. We have previously quantified both
distortions compared with a standard spin-echo
readout, which yielded a bulk shift of 0.11–4.28
mm (median, 1.10 mm) and a residual disagreement between echo-planar and T2-weighted
prostate outlines of 1.2 ± 0.5 mm (mean ± SD)
[27]. These are small compared with the spectroscopic voxel size.
Although it would have been preferable to
perform MR spectroscopy 6–8 weeks after biopsy, the examination was done as an addition
to the staging MRI scan. This was required
within a shorter time frame to implement clinical management. A further limitation of this
study is that malignant lesions isointense to
normal peripheral zone on T2-weighted images
were not included in the analysis. It was not
possible to include those regions without histologic proof of their involvement with tumor.
Similarly, it was not possible to include tumor
within the central gland because differentiation
of benign from malignant low-signal-intensity
regions was not possible. The error inherent in
sampling on endorectal sonographically
guided biopsy would make it difficult to place
ROIs over a described location with any degree
of certainty. There is also a false-positive rate
associated with other benign abnormalities on
T2-weighted MRI—conditions including prostatitis, fibrosis, intraglandular dysplasia, and
glandular atrophy—that also are low in signal
intensity and may mimic cancer [29]. To further
establish the sensitivity and specificity of the
technique, therefore, correlation with prostatectomy specimens is warranted.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
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F O R YO U R I N F O R M AT I O N
The reader’s attention is directed to the article by Graser et al., “Per-Sextant
Localization and Staging of Prostate Cancer: Correlation of Imaging Findings with
Whole-Mount Step Section Histopathology,” which appears on page 84 of this issue.
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