Apparent diffusion coefficient and fractional anisotropy of newly diagnosed grade II gliomas.
ABSTRACT Distinguishing between low-grade oligodendrogliomas (ODs) and astrocytomas (AC) is of interest for defining prognosis and stratifying patients to specific treatment regimens. The purpose of this study was to determine if the apparent diffusion coefficient (ADC) and fractional anisotropy (FA) from diffusion imaging can help to differentiate between newly diagnosed grade II OD and AC subtypes and to evaluate the ADC and FA values for the mixed population of oligoastrocytomas (OA). Fifty-three patients with newly diagnosed grade II gliomas were studied using a 1.5T whole body scanner (23 ODs, 16 ACs, and 14 OAs). The imaging protocol included post-gadolinium T1-weighted images, T2-weighted images, and either three and/or six directional diffusion imaging sequence with b = 1000 s/mm(2). Diffusion-weighted images were analyzed using in-house software to calculate maps of ADC and for six directional acquisitions, FA. The intensity values were normalized by values from normal appearing white matter (NAWM) to generate maps of normalized apparent diffusion coefficient (nADC) and normalized fractional anisotropy (nFA). The hyperintense region in the T2 weighted image was defined as the T2All region. A Mann-Whitney rank-sum test was performed on the 25th, median, and 75th nADC and nFA among the three subtypes. Logistic regression was performed to determine how well the nADC and nFA predict subtype. Lesions diagnosed as being OD had significantly lower nADC and significantly higher nFA, compared to AC. The nADC and nFA values individually classified the data with an accuracy of 87%. Combining the two did not enhance the classification. The patients with OA had nADC and nFA values between those of OD and AC. This suggests that ADC and FA may be helpful in directing tissue sampling to the most appropriate regions for taking biopsies in order to make a definitive diagnosis.
- SourceAvailable from: Wibeke Nordhøy[Show abstract] [Hide abstract]
ABSTRACT: To assess the diagnostic accuracy of axial diffusivity (AD), radial diffusivity (RD), apparent diffusion coefficient (ADC) and fractional anisotropy (FA) values derived from DTI for grading of glial tumors, and to estimate the correlation between DTI parameters and tumor grades. Seventy-eight patients with glial tumors underwent DTI. AD, RD, ADC and FA values of tumor, peritumoral edema and contralateral normal-appearing white matter (NAWM) and AD, RD, ADC and FA ratios: lowest average AD, RD, ADC and FA values in tumor or peritumoral edema to AD, RD, ADC and FA of NAWM were calculated. DTI parameters and tumor grades were analyzed statistically and with Pearson correlation. Receiver operating characteristic (ROC) curve analysis was also performed. The differences in ADC, AD and RD tumor values, and ADC and RD tumor ratios were statistically significant between grades II and III, grades II and IV, and between grades II and III-IV. The AD tumor ratio differed significantly among all tumor grades. Tumor ADC, AD, RD and glial tumor grades were strongly correlated. In the ROC curve analysis, the area under the curve (AUC) of the parameter tumor ADC was the largest for distinguishing grade II from grades III to IV (98.5%), grade II from grade IV (98.9%) and grade II from grade III (97.0%). ADC, RD and AD are useful DTI parameters for differentiation between low- and high-grade gliomas with a diagnostic accuracy of more than 90%. Our study revealed a good inverse correlation between ADC, RD, AD and WHO grades II-IV astrocytic tumors.European journal of radiology 01/2014; · 2.65 Impact Factor
Article: Molecular neuroimaging with PET/MRI[Show abstract] [Hide abstract]
ABSTRACT: Hybrid PET/MRI is a recently developed technique, which is attracting growing interest among the medical community owing to its potential clinical and research applications. PET/MRI is of special interest for neuroscience, given that PET and MRI are the neuroimaging methods of choice for many clinical and scientific applications. The first clinical studies conducted have tested the performance of PET/MRI in oncology indications, neurodegenerative disorders and epilepsy, using aminoacidic tracers and somatostatin-receptor imaging (68Ga-DOTATOC), 18F-fluorodeoxyglucose (18F-FDG), and 11C-flumazenil, respectively, and shown that the acquisition of both brain PET and MRI can be performed in a single session on a hybrid PET/MRI system achieving quality comparable to that of PET/CT and MRI acquired separately, but with some important advantages. Combined acquisition of PET and MRI maximizes the clinical information and optimizes the registration of both modalities, while minimizing patient discomfort. Sparing the patient the CT scan can reduce radiation exposure while the accurate coregistration due to the identical positioning opens new windows for better region-specific evaluation of PET data, particularly when acquired with tracers that provide little anatomical information. PET and MRI parameters can be systematically combined for diagnostic interpretation and new options concerning partial volume and motion correction can be exploited. There are still open issues, such as the selection of clinical indications, the influence of the combined design on the performance of each modality, and, in particular, the validation of quantitative PET measures with respect to attenuation correction. Overall, PET/MRI hybrid imaging is an exciting new modality and potentially the future modality of choice for neuroimaging investigations.Clinical and Translational Imaging. 02/2013; 1(1).
- [Show abstract] [Hide abstract]
ABSTRACT: Although classification of astrocytic tumors is standardized by the WHO grading system, which is mainly based on microscopy-derived, histomorphological features, there is great interobserver variability. The main causes are thought to be the complexity of morphological details varying from tumor to tumor and from patient to patient, variations in the technical histopathological procedures like staining protocols, and finally the individual experience of the diagnosing pathologist. Thus, to raise astrocytoma grading to a more objective standard, this paper proposes a methodology based on atomic force microscopy (AFM) derived images made from histopathological samples in combination with data mining techniques. By comparing AFM images with corresponding light microscopy images of the same area, the progressive formation of cavities due to cell necrosis was identified as a typical morphological marker for a computer-assisted analysis. Using genetic programming as a tool for feature analysis, a best model was created that achieved 94.74% classification accuracy in distinguishing grade II tumors from grade IV ones. While utilizing modern image analysis techniques, AFM may become an important tool in astrocytic tumor diagnosis. By this way patients suffering from grade II tumors are identified unambiguously, having a less risk for malignant transformation. They would benefit from early adjuvant therapies.BioMed research international. 01/2013; 2013:176519.
Received: 31 October 2008, Revised: 14 July 2008, Accepted: 4 November 2008, Published online in Wiley InterScience: 2008
Apparent diffusion coefficient and fractional
anisotropy of newly diagnosed grade II
Inas S. Khayala,b*, Tracy R. McKnighta,c, Colleen McGueb,
Scott Vandenbergd, Kathleen R. Lamborne, Susan M. Change,
Soonmee Chac,eand Sarah J. Nelsona,b,f
Distinguishing between low-grade oligodendrogliomas (ODs) and astrocytomas (AC) is of interest for defining
prognosis and stratifying patients to specific treatment regimens. The purpose of this study was to determine if
the apparent diffusion coefficient (ADC) and fractional anisotropy (FA) from diffusion imaging can help to differ-
entiate between newly diagnosed grade II OD and AC subtypes and to evaluate the ADC and FA values for the mixed
population of oligoastrocytomas (OA). Fifty-three patients with newly diagnosed grade II gliomas were studied using
a 1.5Twhole bodyscanner(23 ODs,16ACs,and 14OAs). Theimaging protocolincluded post-gadolinium T1-weighted
images, T2-weighted images,and either three and/or sixdirectional diffusion imaging sequencewith b¼1000s/mm2.
Diffusion-weighted images were analyzed using in-house software to calculate maps of ADC and for six directional
acquisitions, FA. The intensity values were normalized by values from normal appearing white matter (NAWM) to
generate maps of normalized apparent diffusion coefficient (nADC) and normalized fractional anisotropy (nFA). The
hyperintense region in the T2 weighted image was defined as the T2All region. A Mann–Whitney rank-sum test was
performed on the 25th, median, and 75th nADC and nFA among the three subtypes. Logistic regression was
lower nADC and significantly higher nFA, compared to AC. The nADC and nFAvalues individually classified the datawith
between those of OD and AC. This suggests that ADC and FA may be helpful in directing tissue sampling to the most
appropriateregionsfor takingbiopsiesinorder tomakeadefinitivediagnosis.Copyright? 2008JohnWiley&Sons,Ltd.
Keywords: grade 11 gliomas; oligodendroglioma; astrocytoma; oligoastrocytoma; diffusion imaging; apparent diffusion
coefficient; fractional anisotropy
The World Health Organization (WHO) categorizes low-grade
gliomas into grades I and II tumors. Grade II gliomas are
slow-growing malignant tumors that with time can progress to
grades III or IV tumors. The most common histologic subtypes are
the more homogeneous oligodendroglioma (OD) and astro-
cytoma (AC); and the more heterogeneous oligoastrocytoma
(OA) (1). OD and ACs have distinct biological characteristics that
have been shown to influence response to therapy and outcome.
OAs contain a mixture of both OD and AC and it is thought that
their biological behavior depends on the relative amounts of the
OD and AC components. The prognosis for patients with ODs is
significantly better than patients with ACs, averaging survival
times of 10 years or more as compared to 4 years. (2,3). ODs also
tend to be more responsive to chemotherapy (4–7). The current
gold standard for differentiation between the glioma subtypes is
surgical biopsy, which imparts substantial risk to the patient and
is prone to tissue sampling error (8,9). Knowing that gliomas are
heterogeneous tumors, the accuracy of glioma classification and
* Correspondence to: I. S. Khayal, University of California, San Francisco,
Department of Radiology and Biomedical Imaging, Byers Hall, Suite 303,
MC 2532, 17oo 4th Street, San Francisco, CA 94158-2330, USA.
a I. S. Khayal, T. R. McKnight, S. J. Nelson
UCSF/UCB Joint Graduate Group in Bioengineering, University of California,
San Francisco, CA, USA
b I. S. Khayal, C. McGue, S. J. Nelson
Surbeck Laboratory of Advanced Imaging, Department of Radiology,
University of California, San Francisco, CA, USA
c T. R. McKnight, S. Cha
Department of Radiology, University of California, San Francisco, CA, USA
d S. Vandenberg
Department of Pathology, University of California, San Francisco, CA, USA
e K. R. Lamborn, S. M. Chang, S. Cha
Department of Neurological Surgery, University of California, San Francisco,
f S. J. Nelson
Program in Bioengineering, University of California, San Francisco, CA, USA
yPresented in part at the 15th Annual Meeting of ISMRM, Berlin, Germany,
Abbreviations used DWI, diffusion-weighted imaging; ADC, apparent diffu-
anisotropy; nFA, normalized fractional anisotropy; OD, oligodendroglioma;
AC, astrocytoma; OA, oligoastrocytoma.
NMR Biomed. (2008) Copyright ? 2008 John Wiley & Sons, Ltd.
grading through biopsies is highly dependent on the extent of
sampling, especially since these tumors often do not enhance,
therefore there is no specific biopsy target. Therefore, finding
non-invasive imaging techniques capable of differentiating these
low-grade tumors is critical, especially for tumors that have
been diagnosed as such because the tissue samples used for
histological analysis were unable to represent the entire tumor.
Microscopic molecular movement of water in tumor tissue
reflects tissue properties that include varying levels of structural
alterations, tumor cellularity, and vasogenic edema. Diffusion-
to probe the structure of biologic tissues at a microscopic levelby
measuring the Brownian motion of water molecules, and has
therefore been used for in vivo tissue characterization (10).
Acquiring data with gradients in three directions allow the cal-
data with gradients in six or more directions allow the calculation
of the ADC and the fractional anisotropy (FA).
The ADC can be calculated from images with any number of
gradients applied (11). The directional restriction of water
diffusibility can be measured as the FA and has been shown
studies are discordant with regards to the use of ADC and FA in
distinguishing low-grade ODs and low-grade ACs. Bulakbasi et al.
(14) reported the ADC within the tumoral or peritumoral
regions cannot differentiate low-grade ACs from low-grade ODs
in 33 patients, while Tozer et al. (15) suggested an ADC histogram
analysis as a possible method for predicting low-grade glioma
subtypes in 27 patients.
The goal of this study was to determine if the ADC and FA from
DWI can help differentiate grade II OD and AC subtypes and to
examine the ADC and FA for the mixed OA subtype, in a larger
patient population that had been considered in previous studies.
MATERIALS AND METHODS
A total of 53 patients with newly diagnosed grade II glioma were
examination using criteria defined by the WHO. Twenty-three
patients had grade II ODs (9 females,14 males) and ranged in age
from 21 to 71 years,with a mean of 43 years. Sixteen patients had
grade II ACs (6 females, 10 males) and ranged in age from 22 to
(6 females, 8 males) and ranged in age from 18 to 62 with a mean
of 40 years. Patients provided informed consent as approved by
the Committee on Human Research at our institution.
(GE Healthcare Technologies Milwaukee, WI, USA), using a standard
quadrature head coil. The MRI examination included axial
T1-weighted pre- and post-gadolinium three-dimensional spoiled
gradient echo (SPGR) images (TR¼34ms, TE¼3ms, slice
thickness¼1.5mm, matrix¼ 256?192, FOV¼260?195mm2,
flip angle¼408) and axial T2-weighted 3D fast spin echo (FSE)
matrix¼256?192, FOV¼260? 195mm2). After each examin-
ation, the images were transferred to a SUN Ultra 10 workstation
(Sun Microsystems, CA, USA) for post-processing.
Patients were scanned with three directional DWI (TR¼10000ms,
TE¼110ms, matrix size¼256?256, slice thickness¼5mm,
b¼1000s/mm2, or six directional diffusion tensor imaging
(TR¼10000ms, TE¼108ms, matrix size¼256?256, slice
thickness¼ 3mm, b¼1000s/mm2), or both. Table 1 shows
the number of patients scanned with three, six and both three
and six directional data. DWI was performed before gadolinium
injection in all cases except for eight-patient scans. Some studies
report no difference in normal tissue or lesions (16) while others
report a very small decrease in ADC of 1–1.3% in normal tissue
(17,18) and 3% difference in lesions (17). This difference is
significantly smaller than the observed differences between the
subgroups. The ADC and FA were calculated on a pixel-by-pixel
basis using software developed in-house, based on published
algorithms (19). The ADC and FA maps were registered to
anatomical imaging by rigidly aligning the T2-weighted (b¼0)
diffusion image to the T2-weighted FSE and applying the
transformation to the ADC and FA maps (20), see Figure 1.
The FSE and pre-gadolinium SPGR images were aligned to the
post-gadolinium SPGR using software developed in our
laboratory (21). An in-house semi-automated segmentation
method was used to define the T2 hyperintense region
(T2ALL) on the T2-weighted FSE image (22). The T1-weighted
post-Gd SPGR image was checked forany contrast enhancement.
If small regions of contrast enhancement was present (6/53
NEL¼T2ALL?CEL. Normalized apparent diffusion coefficient
(nADC) maps were generated by dividing the ADC maps by the
median ADC value within the normal appearing white matter
(NAWM) mask, which was segmented using FAST (FMRIB’s
AutomatedSegmentation Tool) Software on the T2-weighted FSE
image (23). The same method was applied to the FA maps to
region wascontoured as
Table 1. Number of diffusion data sets per subtype, separated into only three directional diffusion-weighted imaging, only six
directional diffusion tensor imaging, patients scanned with both three and six directional diffusion imaging and total number of
diffusion imaging data sets per subtype
Low-grade subtypeOnly three direction DWI Only six direction DTIBoth three and six directions Total
22 11 20
Copyright ? 2008 John Wiley & Sons, Ltd. NMR Biomed. (2008)
I. S. KHAYAL ET AL.
generate the normalized fractional anisotropy (nFA) maps, see
The ADC values from three versus six directional data sets were
compared using a Wilcoxon signed-rank test and a correlation
coefficient for the median ADC values from the three and six
directional data sets was calculated. These analyses were
performed to verify that the three and six directional data sets
show the same results and therefore could be combined.
A Mann–Whitney rank-sum test was performed on OD, AC, and
Logistic regression analysis was used to estimate the accuracy of
Twenty patients were scanned with three directional DWI and six
directional DTI. The Wilcoxon signed-rank test for the three
directional and six directional median nADC values showed no
75th (p¼0.60) percentile nADC valueswithin the non-enhancing
region. There was also a very strong correlation between the
three and six directional median ADC (r¼0.97, p<0.001) and
nADC (r¼0.964, p<0.001) values. Therefore, the patients
scanned with three directional DWI and the patients scanned
with the six directional DTI were analyzed together.
The median, 25th, and 75th percentiles were calculated for the
nADC and nFA values, within the NEL. Normalization was
performedinorder tocombinethree andsixdirectionaldata.The
differences between the groups were maintained whether or not
the normalization was performed. The correlation coefficient
between the ADC and nADC values was r¼0.9725, p<0.0001.
Other studies have suggested ADC varies with age (24) and brain
or tumor volume (25). In this study, the correlation between ADC
and age showed a weak but significant correlation for all patient
data combined (r¼?0.315, p<0.022), but no significant
correlation for patients with ODs (r¼?0.352, p<0.099), patients
with ACs (r¼?0.192, p<0.477), or patients with OAs (r¼0.025,
p<0.932). The correlation between age and ADC values in
NAWM was also assessed for any of the subtypes separately and
gave OD (r¼0.0608, p<0.78), AC (r¼?0.337, p<0.20), OA
(r¼?0.154, p<0.60) or for all patients combined (r¼?0.099,
p<0.48) showing no correlation. The correlation was also
assessed for the FA values in NAWM with OD (r¼0.076, p<0.79),
AC (r¼?0.126, p<0.77), OA (r¼0.383, p<0.35) and all patients
combined (r¼0.119, p<0.53) showing no correlation. There was
no correlation between ADC and tumor volume for patients with
ODs (r¼?0.01, p<0.96), AC (r¼?0.30, p<0.23), OA (r¼0.29,
p<0.32) and all subtypes combined (r¼0.045, p<0.73). The
tumor volume mean?standard deviation (std) were 56.6?63.3,
49.7.?39.7, and 47.1?33.6cc for patients with OD, AC, and OAs.
A Wilcoxon rank-sum test shows no significant difference in
volume between the groups, OD versus AC (p¼0.7426), OD
versus OA (p¼0.9127), and AC versus OA (p¼0.9834).
Therewasalarger variationintheNAWMvaluesfor theFAthan
the ADC, with a variation of 25% in FA as compared to 13% in
ADC. The variation in FA likely arose from the difference in noise
from three to six directions and field strengths and the known
variation across patients. Therefore, normalization was more
important for FA values than for ADC values. Notably, although
there was a larger variation in the NAWM FA, there was no
significant difference between subtypes (see Table 2) within the
The median, 25th, and 75th percentiles for nADC and nFA for
the NEL regionare shownin Table2. Themedian nADCODvalues
were significantly lower (p<0.0001) than the median nADC AC
values, with the OAs falling in the middle range, as shown in
Figure 2a. This also held true for the 25th and 75th percentile
nADC values showing significant differences with p<0.0004 and
p<0.0001, respectively. The median nFA OD values were
significantly higher (p¼0.005) than the median nFA AC values,
with the OA nFA values falling in the middle range, as shown in
Figure 2b. This also held for the 25th and 75th percentile nFA
values with significant differences of p¼0.004 and p¼0.006,
In addition to the median, 25th, and 75th percentiles the
std and the coefficient of variability (cvb) defined here as the
(std/median).?100 were analyzed. The median stds and cvb for
the ADC within the NEL of grade II ODs, ACs, and OAs were 230,
283, 265?10?3mm2/s and 19, 20, 18%, respectively. The OD has
a significantly lower std than that of the AC (p¼0.015), but when
normalized by the median, there are no significant differences
between any of the subtypes.
and nFA histograms of each patient per subtype, shown in
Figure 3, along with the NAWM histograms which overlap for
nADC and nFA. The grade II OD nADC values were lower than the
grade II AC, with the grade II OA falling in between. The nFA
values in the grade II ODs were higher than those in the grade II
OAs and ACs. The overlap of the histograms between subtypes
was greater in the nFA than in the nADC.
Thedata werealso analyzedby examiningthe mediannFAand
the median nADC. There appears to be a significant correlation of
all subtypes (r¼?0.80, p<0.0001, n¼33), and separately for
p¼0.0011, n¼8) but no correlation for OA (r¼?0.2621,
p<0.530, n¼8). High FA values were found to correlate to
Figure 1. Example patient with an astrocytoma: (a) T1-weighted SPGR
(reference image) with T2ALL mask applied, (b) T1-weighted SPGR with
NAWM mask applied, (c) T2-FSE aligned to T1-weighted SPGR from which
the T2ALL mask is segmented, (d) T2 (b¼0) from diffusion imaging
aligned to the T2-weighted images through a transformation, (e) trans-
formation applied to ADC map, and (f) FA map with T2ALL mask applied.
NMR Biomed. (2008)Copyright ? 2008 John Wiley & Sons, Ltd.
ADC AND FA OF NEWLY DIAGNOSED LOW-GRADE GLIOMAS
low ADC values for all subtypes (r¼?0.791, p<00001), and
separately for patients with OD (r¼?0.585, p¼0.0172) and AC
(r¼?0.876, p¼0.002) but no correlation for OA (r¼?0.427,
p¼0.2912). Visual inspection of maps of the 25th, 50th, and 75th
percentiles revealed that the median values typically reflected
thecentraltumor whiletheedgeof thetumorcontainedthe25th
percentile nADC and 75th percentile nFA values. Although the
correlation across patients was strong, the correlation within
patients was not as strong. There was a large range of correlation
coefficient values, ranging from ?0.12 to ?0.81, with a median
correlation of ?0.43, ?0.49, ?0.45, and ?0.44 for patients with
ODs, ACs, OAs, and all subtypes, respectively. The within-patient
NAWM correlation coefficients were significantly lower than
those within the tumor, with a median correlation of ?0.17,
?0.18, ?0.23, and ?0.18 for patients with ODs, ACs, OAs, and all
Logistic regression analysis was used to examine the ability of
the nADC and nFA in subtyping patients with OD versus AC. The
most optimal cutoff value for the median nADC was 1.84,
misclassifying 2 of 23 ODs, 3 of 16 ACs with an overall accuracy of
87%. The most optimal cutoff value for the median nFA was 0.41,
misclassifying 1 of 14 ODs, 1 of 9 ACs, with an overall accuracy of
91%. The same two patients misclassified from the nFA analysis
alone were misclassified when both the nADC and nFAwere both
included in the analysis.
Non-invasive methods for distinguishing between patients who
have grade II AC and ODs are important because they have
shows a significant difference in the ADC and FA values between
newly diagnosed patients with grade II OD and AC lesions, while
patients with the heterogeneous grade II OA had values that fell
in between those of ODs and ACs.
The 23 patients with grade II OD and 16 patients with grade II
AC had a significant difference in the ADC and nADC values with
Figure 2. Boxplotsof themedian(a)nADCvaluesand(b)nFAvalueswithintheNELforpatientswithgradeIIoligodendroglioma(OD),astrocytoma(AC),
and oligoastrocytoma (OA).
Table 2. Descriptive statistics for the NAWM ADC values and non-enhancing lesion nADC values for patients with oligoden-
droglioma (OD), astrocytoma (AC), and oligoastrocytoma (OA) subtypes followed by the p-value from the Wilcoxon rank-sum test
NAWM ADCNon-enhancing lesion nADC
Median25th Median 75th
OD versus AC
OD versus OA
AC versus OA
Non-enhancing lesion nFA
OD versus AC
OD versus OA
AC versus OA
NAWM ADC, NAWM FA, non-enhancing lesion nADC and non-enhancing lesion nFA values.
Copyright ? 2008 John Wiley & Sons, Ltd.NMR Biomed. (2008)
I. S. KHAYAL ET AL.
mean?std ADC values of 1221?165 and 1562?204?
10?3mm2/s, respectively. Tozer et al. (15) was able to show a
significant difference between 9 patients with grade II OD and
15 patients with grade II AC with mean?std ADC values of
1360?150 and 1510?250?10?3mm2/s, respectively, using a
histogram analysis of ADC. Although the mean values obtained
were similar, Bulakbasi et al. (14) reported no significant
difference in the ADC peritumoral values between 10 patients
with grade II ODs and 23 patients with grade II ACs (mean?std
ADC values of 1360?220 vs. 1560?390?10?3mm2/s). In the
current study, the ADC values for patients with grade II ACs are
similar, whilethe ADC valuesfor ODwerelower. This mayreflecta
differenceinthe histopathologicclassification ofpatientsatUCSF
versus other institutions due to variations in practices, as well as
differences in pathologist training.
Although there was a significant difference in the nFA values
for patients with grade II ODand AC, the patients with grade IIOA
had values that fell between those of the ODs and ACs. To our
knowledge, this is the first paper to examine the FA values and
find a separation in values for patients with OD and AC. Patients
with ODshowed higher FAvaluesthan patientswith AC.This may
be explained by the more disruptive pattern of infiltration of ACs
as compared to perineuronal satelitosis in ODs.
Yamasaki et al. (26) presented the logistic regression to
discriminate between ADC values for OD and AC tumors for
separating 2 patients (one grade II OD and one grade II OA) from
17 patients with grade II AC with 94% accuracy. Tozer et al. (15)
with an accuracy of 83%. This study showed 87% accuracy in
separating 23 patients with grade II ODs from 16 patients with
grade II ACs. Patients with grade II OAs have tumor mixtures and
were then expected to have intermediate ADC and FA values
depending on how close they resembled oneor the other type of
the more homogeneous subtypes.
The use of FA values to discriminate between OD and AC
tumors has not previously been shown. This study was able to
distinguish between 14 grade II ODs and 8 grade II ACs with 91%
ADC misclassifies the same two patients as the FA. There is a
significant correlation between nFA and nADC, which would
explain why the same patients were misclassified and suggests
that combining the ADC and FA does not enhance the
Visual inspection indicated that the median ADC and median
FAvalues were within the center of the tumor, whereas the lower
25th percentile ADC and 75th percentile FA values were typically
at the edge of the tumor. The data shows a similar significant
between the median nADC and median nFA may reflect the
biology of the tumor, since no significant correlation was found
between values within individual patients. This distribution of
values,border andcentral, wasseeninbothpatientswithODand
AC and was not found to distinguish between them.
from biological differences and not from confounding factors.
There was no significant correlation between age and ADC in any
of the subgroups separately, but there was a weak significant
correlation when all of the patients were analyzed together.
Patients with OD tended to be older with lower ADC, while
patients with AC tended to be younger and have higher ADC
values. This weak correlation observed could be due to the diffe-
rence in age and ADC values between the groups. Interestingly,
there was no correlation between NAWM ADC values and age for
any of the group separately or when combined. This suggests
that age is not a confounding factor. Berger et al. (25) suggests
thatthe biologyoflarge low-gradegliomas isquitedifferentfrom
smaller tumors. These data suggest no correlation between
tumor volume and ADC values for any of the groups. There were
Figure 3. Sum of (a) nADC histograms and (b) nFA histograms within the NAWM of all patients and the NEL of all the patients with oligodendrogliomas
(OD), astrocytoma (AC), and oligoastrocytoma (OA).
NMR Biomed. (2008) Copyright ? 2008 John Wiley & Sons, Ltd.
ADC AND FA OF NEWLY DIAGNOSED LOW-GRADE GLIOMAS
no differences between the tumor volumes for patients with
different grade II subtypes. Therefore, as expected the significant
difference cannot be attributed to confounding factors and
therefore, it can be deduced that the variation is due to a
biological difference between the tumors, especially since the
mixed OAs had values in between those of OD and AC.
The pattern of infiltration varies in ACs and ODs. ODs tend to
infiltrate by perineuronal satelitosis (clustering of neoplastic
oligodendrocytes around neurons) (see Figure 4). ODs tend to
have more persistent neurons as seen in pathology, which may
explain the higher FA values. By sparing the neurons and less
volume of invasion, one would speculate that less edema is
expected, which may explain the lower ADC values in ODs.
Another biological effect that may enhance the separation
between OD and AC in ADC and FA is calcification. Calcification
has been reported in 20–91% of patients (27–29), while
micro-calcifications are seen in 90% of tumors (30). Patients
with calcification are expected to have lower ADC values due to
the expected lack of water movement in the calcified region. The
previous studies do not report the number of patients with
observedcalcification. In this study, calcification was present in at
least 40% of the patients with OD. The patients with calcification
tended to have the lower nADC values.
ADC has been suggested to correlate to cell density in a mixed
population of patients with gliomas (31,32), but it is not entirely
been shown to have a significant difference between OD and AC.
But, it is expected that the same cell density in these groups
would show a difference in FA and ADC because of the difference
in the infiltration patterns (see Figure 4).
Histopathology of the 23 patients with grade II OD and
in a systematic method to analyze the biological features of the
available tissue. Of the 23 patients with grade II OD, 4 patients
were determined to also have some features of AC; of the
16 patients with AC, 6 patients were determined to have some
component of OD and of the 14 patients with grade II OA,
1 patient was determined to be an AC. The original patient
classification based on nADC is shown in Figure 5 and the
adjusted classification is shown in Figure 5. Most of the patients
overlapping in the nADC values were re-classified to OAs. It is
important to mention that some of these patients with mixed
features had different focal areas exhibiting features of AC and
OD. This would lead us to believe that low-grade gliomas are
is an important aspect of accurate classification.
Diffusion parameters can be used to limit the sampling errors
of biopsies and therefore image-guided biopsies of the higher
and lower values of the tumor may help sample the more
definitive regions, especially when trying to determine a mixed
OA from the more homogeneous OD and AC.
In conclusion, this study suggests a significant difference in
ADC and FA values between patients with grade II OD and AC
could be utilized as a non-invasive biomarker for subtyping low
Figure 4. H&E staining for patient with (a) grade II oligodendroglioma, which tend to have an infiltration pattern of perineuronal satelitosis and more
the lower ADC and higher FA values in oligodendrogliomas and higher ADC and lower FA values in astrocytomas.
Figure 5. (a) The original patient classification based on nADC and
(b) the adjusted classification based on re-evaluation of histopathology
re-classified as patients with oligoastrocytomas. This figure is available in
color online at www.interscience.wiley.com/journal/nbm
Copyright ? 2008 John Wiley & Sons, Ltd.NMR Biomed. (2008)
I. S. KHAYAL ET AL.
The authors thank Niles Bruceand Bert Jimenez of the Department
of Radiology at UCSF for their assistance with data acquisition.
This work was supported by grants from the National Institutes of
Health (P50 CA97297), UC Discovery Grants (LSIT01-10107 and
ITL-Bio 04-10148) sponsored jointly with GE Healthcare and the
UCB Graduate Opportunity Program Fellowship.
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NMR Biomed. (2008) Copyright ? 2008 John Wiley & Sons, Ltd.
ADC AND FA OF NEWLY DIAGNOSED LOW-GRADE GLIOMAS