ORIGINAL ARTICLE
Radiosurgical Treatment Planning for Intracranial AVM
Based on Images Generated by Principal Component
Analysis - A Simulation Study
Osamu Kawaguchi,1 Yoshiyuki Nyui,2 Etsuo Kunieda,1 Satoshi Onozuka,1 Nobuhiro Tsukamoto,3
Junichi Fukada,1 Toshio Ohashi,1 Subaru Hashimoto,1 Koichi Ogawa4 and Atsushi Kubo1

Department of Radiology, Keio University, Tokyo, Japan
Department of Radiological science, Faculty of Health sciences, Tokyo Metropolitan University, Tokyo, Japan3
Department of Radiation Oncology, Saitama Medical University International Medical Center, Saitama, Japan
4
Department of Electronic Informatics, College of Engineering, Hosei University, Tokyo, Japan
1

2(Received for publication on October 10, 2008)(Revised for publication on November 5, 2008)(Accepted for publication on November 13, 2008)

Abstract
Background : One of the most important factors in stereotactic radiosurgery (SRS) for intracranial arteriovenous malformation (AVM) is to determine accurate target delineation of thenidus. However, since intracranial AVMs are complicated in structure, it is often difficult toclearly determine the target delineation.
Purpose : To investigate the usefulness of principal component analysis (PCA) on intra-arterial contrast enhanced dynamic CT (IADCT) images as a tool for delineating accurate target
volumes for stereotactic radiosurgery of AVMs.
Materials and Methods : IADCT and intravenous contrast-enhanced CT (IVCT) were used to
examine 4 randomly selected cases of AVM. PCA images were generated from the IADCT
data. The first component images were considered feeding artery predominant, the second
component images were considered draining vein predominant, and the third component
images were considered background. Target delineations were first carried out from IVCT,
and then again while referring to the first and second components of the PCA images. Dose
calculation simulations for radiosurgical treatment plans with IVCT and PCA images were
performed. Dose volume histograms of the vein areas as well as the target volumes werecompared.
Results : In all cases, the calculated target volumes based on IVCT images were larger thanthose based on PCA images, and the irradiation doses for the vein areas were reduced.
Conclusion : In this study, we simulated radiosurgical treatment planning for intracranial
AVM based on PCA images. By using PCA images, the irradiation doses for the vein areas
were substantially reduced. (Keio J Med 58 (1) : 41－ 49, March 2009)

Keywords: radiosurgery, target delineation, treatment planning, intracranial AVM, principal component analysis

Introduction

this abnormal nidus often break due to the high hydrodynamic pressure of the arterio-venous shunt. This leads tospasms and hemorrhage, and cerebral AVM is a condition that is considered to be fatal with sudden onset.
There have been many studies on the nature of AVMs,

An intracranial arteriovenous malformation (AVM) isa native deformed vessel in which the artery and vein directly connect without capillary vessels. The walls of

Reprint requests to: Osamu Kawaguchi, M.D, Department of Radiation Oncology, Keio University, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan,
Tel: +81-3-3353-1211 ex.62531, Fax: +81- 3-3359-7425, E-mail: kawaguti@rad.med.keio.ac.jp
41

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Kawaguchi O, et al: SRS Planning for AVM Based on Principal Component Analysis

and Pellettieri et al. hypothesized that the increase in sizeand debatable size-dependent risk of AVM hemorrhage
could be attributed to an anatomical entity.1
Recently, stereotactic radiosurgery (SRS) has been
useful as a treatment method for small AVMs when ordinary surgical methods are too difficult to apply due tothe location of the lesion or the patient’s status. With
SRS, the probability of a cure will increase and the riskof radiation injury will diminish if the target of the beam
concentration corresponds to the AVM nidus with minimal irradiation of the surrounding normal tissue.2, 3 In
particular, irradiation of draining veins may cause themto collapse before the nidus has been obliterated, leading
to higher blood pressure on the nidus wall and eventually
resulting in accidental hemorrhage.4, 5 Therefore, in orderto minimize such complications, draining veins should
be kept outside the irradiation area. To date, target delineation for AVM has been based on magnetic resonanceimaging (MRI) and intravenous contrast-enhanced computed tomography (IVCT) images with reference to angiograms. As for three-dimensional (3D) reconstructionof the brain’s blood vessels, various methods have been
proposed. Yeung et al. developed a technique for reconstructing the AVM from multi-directional stereotactic angiograms.6 This technique is precise, with sub-millimeter
accuracy, and is useful for radiosurgical treatment planning. Tanaka et al. demonstrated the value of helical CT
and CT angiography in evaluating the target for therapeutic planning of cerebral AVM, and compared thiswith time-of-flight MR angiography and digital subtraction angiography.7 In addition, Stancanello et al. reported
a method for registration of CT and 3D angiography for
AVM radiosurgery.8
Generally, in intracranial AVM feeding arteries, thenidi and draining veins are complicated in their structure,making it very difficult to accurately determine target
delineation with conventional methods for radiosurgicaltreatment planning. Our method used a sequence of dynamic CT images obtained by intra-arterial infusion ofcontrast medium. To identify the nature of the contrastenhanced vessels, we used information on blood flow
conditions (inflow and outflow) in these structures. Thatis, the acquired images were analyzed using the principal
component analysis (PCA) method. 9 PCA is a wellknown technique in the nuclear medicine field for image
reconstruction.1 0- 1 2 Knuttsson et al. applied PCA forwhole cerebral blood flow quantification,1 3 and Eida et
al. reported on MR factor analysis for two-dimensional
MR dynamic images of benign and malignant salivary
gland tumors.14
The purpose of this study was to examine the usefulness of the PCA method for delineating accurate target
volumes for stereotactic radiosurgery (SRS) of AVMs.
Using PCA images, we performed a simulation of SRS
treatment planning. In addition, we compared dose vol-ume histograms of the vein area as well as target volumes.
Materials and Methods
Four patients with cerebral AVMs were randomly selected from our radiosurgical database. Case 1 was a
12-year-old female with an intracranial AVM in the leftparietal lobe. Case 2 was a 39-year-old male with an intracranial AVM in the left frontal lobe. Case 3 was a54-year-old male with an intracranial AVM in the rightparietal lobe. Case 4 was a 39-year-old female with an
intracranial AVM in the right temporal lobe. Figure 1
shows Case 2 as a representative example using digital
subtraction angiography (DSA).
All of the patients were treated by SRS and had previously been studied using intravenous contrast-enhanced
helical CT (IVCT), intra-arterial contrast-enhanced dynamic CT (IADCT), and DSA. IVCT examinations were
performed using a helical CT scanner (XVision; Toshiba
Medical Systems Corp., Tokyo Japan), with contrast media infusion at 2 ml/sec and with a duration of 45 seconds. The slice thickness for IVCT was 2 mm, and reconstruction was performed with a 1-mm slice thickness
after scanning. In this way we obtained homogenous
contrast-enhanced images of the entire AVM, including
the feeding arteries, nidus, and draining veins. The
IADCT examinations were performed using another helical CT scanner (Advantx ACT; GE Medical Systems,
Milwaukee, WI) and nonionic contrast medium. We used

Fig. 1 Posterior-anterior (a) and left-right (b) digital subtraction
angiography (DSA) of Case 2.
Intra-arterial dynamic CT (IADCT) images near the center of thenidus in Case 2; (c)-(g) 0.2 sec intervals, (h)-(l) 0.4 sec intervals.

Keio J Med 2009; 58 (1):41－ 49

43

Fig. 2 Schematic representations of data acquisition.

a half concentration (150 mgI/ml) of contrast medium
for the IADCT. For each single-shot injection of 1-second duration, 1.5 ml of contrast medium was used. Scanning was continuously performed at a rate of 0.8 sec/
rotation for 10 seconds at the same table position using
120 kVp, 60–100mA, and a 3-mm slice thickness. The
scan position was then moved 3 mm cranially, and the
dynamic scans were repeated to encompass the nidus.
Figure 1 shows a sequence of acquired IADCT images
at a position near the center of the nidus in Case 2. A total of 55 images from start to end of contrast enhancement were obtained for each slice position. After the entire examination was completed, sequential images at 0.2
seconds intervals were reconstructed with an image sizeof 512×512 pixels, and a pixel size of 0.6×0.6 mm2.
The IADCT images were analyzed using the PCA
method and free software (Pixies Micro Edition, ver.
0.99.1; Apteryx, Issy-les-Moulineaux France). For PCA,an orthogonal analysis was first performed, and using theorthogonal analysis results, an oblique analysis was carried out, resulting in component images corresponding to
the artery and nidus-predominant component, vein-predominant component, and background component. Figure 2 provides a schematic illustration of our data acquisition and preprocessing method.
Generally, an increased estimated radiation dose involving DSA, IVCT, and IADCT would be a potential
drawback to our proposed method, and the risk-versusbenefit issue would need to be weighed. However, since
intracranial AVM is a lethal disease, reducing the risk ofhemorrhage is the most important issue. Moreover, secondary risks due to treatment dose are ultimately higher
than the risk of radiation exposure from the radiologicalexaminations.
Although our IADCT method for intracranial AVM
was approved by the ethical committee of our institute,
this study was performed for computational simulation
purposes only, using data obtained from IADCT fromeach patient’s clinical treatment.
Treatment Planning
For the purposes of experimentation, SRS treatment
planning was carried out virtually using PCA data as
well as IVCT data. Based on our standard protocol,
AVMs were irradiated with a total marginal dose of 20
Gy given in 1 fraction. The gross target volume (GTV)
was determined from the CT data. The clinical target
volume (CTV) was considered to be identical to GTV.
Margins of 1 mm were added to the CTV in order to create the planning target volume (PTV). Dose deliveries
with single isocenter and 10 non-coplanar static beams
were carried out. A 6-MV linear accelerator (ML15MV:
Mitsubishi Electric Corp., Tokyo, Japan) was used to
produce the x-ray beam. A computer-controlled MMLC
module (AccuLeaf: Alayna Enterprises Corp., Paris,
France) was mounted on the linac gantry-head, and 48
pairs of MMLC leaves, driven by individual motors,
were set up on 2 levels with the direction of the 2 levelsof leaves perpendicular to each other. The effective leaf
thickness of the inner 14 pairs was 2.6 mm, while thethickness of the outer pairs was 5.3 mm at the isocenter.15

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Kawaguchi O, et al: SRS Planning for AVM Based on Principal Component Analysis

Fig. 3 Intra-venous contrast-enhanced helical computed tomography (IVCT) and principal component analysis (PCA) images foreach slice in Case 2.
IVCT with GTV_IV, GTV_PCA, ‘vein’ ROI delineations and 3 PCA images of IADCT in Case 2. From left to right, IVCT, thefirst-component, second-component, and third-component images are indicated. From top to bottom, each axial image is indicated at 3mm intervals. A draining vein (white arrow) is indicated in the second component image. GTV_IV (blue), GTV_PCA (red), ‘vein’ ROI(sky blue and green) delineations are also indicated.
GTV: Gross target volume

Target delineation
The GTV outline was delineated using IVCT (Fig. 3:
GTV_IV, blue line) by an individual operator who had
not been involved in the study design and who had notseen the PCA images at that time. In order to be used as
support information for GTV delineation, DSA and MRI
images were allowed as references. Four weeks after thedelineation of GTV_IV, the same operator delineated the
GTV_PCA outline, referring to the first and second images from the PCA results (Fig. 3: red line). In order to
e v a l u a t e t h e d i ff e r e n c e b e t w e e n G T V _ I V a n d
GTV_PCA, an experienced radiation oncologist, who
had over 10 years experience with radiosurgery planning, very carefully delineated the area of ‘vein’ regionsof interest (ROI) (Fig. 3: sky blue and green lines) using
all the available data from PCA, IVCT, DSA, and MRI,
and considering the connection of the vessels in a 3D
manner.
Plan generation
Two SRS plans were generated from the GTV_IV and
GTV_PCA individually. Using the micro-multileaf collimator, 10 non-coplanar static beams were simulated witha prescribed dose level of 20 Gy. In generating theIV_plan and PCA_plan, we used the same beam parameters of gantry angles and couch angles as the template.
The details of the beam parameters are described in Table 1. The dose distributions of the IV_plan andKeio J Med 2009; 58 (1):41－ 49

45

Table 1 IV plan and PCA plan beam parameters in Case 2.
Case 2 Beam parameters
IV planCommon parameters
Beam

Couch

GantryWeightNo

Angle [deg]Angle [deg][of 1000]

1
2
3
4
5
6
7
8
9
10

320
330
338
340
0
0
0
18
53
85

29
340
299
80
46
18
304
54
59
95

90
90
98
114
118
86
94
114
110
86

PCA plan
MU

Weight[of 1000]

245
249
311
315
309
228
311
299
289
234

95
85
95
123
106
92
106
102
99
99

MU
257
236
305
335
279
245
351
268
260
270

Table 2 Radiosurgery treatment summary of Cases 1-4.
SRS treatment Results
Case

1

2

3

4

Plan nameIV plan

PCA planIV plan

PCA planIV plan

PCA planIV plan

PCA plan

Target Name
Target Volume [mm^3]
Min Dose [cGy]
Max Dose [cGy]
Mean Dose [cGy]Homogeneity Index
Conformity Index
Min Dose Index ( /PD ) [%]Max Dose Index ( /PD ) [%]GTV_IV
6701
1494
2492
2297
1.67
1.44
75
125

GTV_PCA
5859
1548
2490
2292
1.61
1.54
77
124

GTV_IV
5665
1269
2540
2315
2.00
1.61
63
127

GTV_PCA
4829
1458
2518
2298
1.73
1.53
73
126

GTV_IV
8367
1297
2477
2290
1.91
1.48
65
124

GTV_PCA
7042
1138
2498
2306
2.19
1.57
57
125

GTV_IV
3501
1454
2519
2324
1.73
1.6
73
126

GTV_PCA
2977
1472
2546
2343
1.73
1.65
74
127

PCA_plan were caliculated by treatment planning system (Accusoft; Alayna Enterprises Corp., Paris, France).
These plans were not used for actual treatment, but weremerely simulations for the purposes of this study.
Results
Figure 3 shows the IVCT images with GTV_IV,
GTV_PCA, ‘vein’ ROI delineations, and the principal
component images of IADCT for Case 2. From left toright, the first-, second-, and third-component IVCT images are shown. The ‘vein’ ROI was basically in the regions that were included in GTV_IV but were excluded
from GTV_PCA.
These principal component images can be considered
as follows: the first-component image shows predominantly the arterial and AVM region, the second shows
predominantly the venous and AVM region, and the thirdshows the background activity region. In the first set ofimages, the feeding artery was detectable as the area that
had strong intensity, and this finding was confirmed in
DSA and IADCT images that observed the anatomical
connection. In the second set of images, the draining
vein was similarly detected. In the third set of images,
bony structures and embolizing opacities were used for
confirmation.
Results of treatment planning and dose calculations
Table 2 summarizes the results of the treatment plans(IV_plan and PCA_plan). GTV_IV is larger than
GTV_PCA in all cases (Fig. 4). The radiation field for
the PCA_plan was smaller than that of the IV_plan. As
an example, the field shape of beam number 10 in Case
2 is indicated in Figure 5. The maximum dose average
for all 4 cases for the IV_plan was 25.07 Gy, and that for
the PCA_plan was 25.10 Gy. The dose distributions of
the IV_plan and PCA_plan are indicated in the same axi-

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Kawaguchi O, et al: SRS Planning for AVM Based on Principal Component Analysis

Fig. 4 Target volumes of GTV_IV and GTV_PCA in Cases 1-4.

Fig. 5 An example of field shape.
Beam’s-eye views of beam number 10 in Case 2 are shown: IV_plan (a), and PCA_plan (b). GTV_IV is shown as a blue, meshed area(a). GTV_PCA is shown as a red, meshed area (b). Organs at risk, ‘vein’ ROIs are shown as sky blue and green areas. In the PCA_plan,‘vein’ ROIs are reduced from the radiation field (b).

al, coronal, and sagittal plane (Fig. 6).The dose-volume
histograms for the target volumes and ‘vein’ ROI for
each plan in Case 2 are shown in Figure 7. The dosevolume histograms for ‘vein’ ROI are also indicated in
Figure 8. In the PCA_plan, the mean and minimum doseof ‘vein’ ROI appeared lower than those in the IV_plan.

Discussion
Many authors have reported that the main issue in radiosurgical treatment of AVMs is definition of the target,
and that the target should include the whole of the nidus.16 On the other hand, it is important to reduce the irradiation volume in order to minimize complications af-

Keio J Med 2009; 58 (1):41－ 49

47

Fig. 6 Dose distributions of the IV_plan and PCA_plan in Case 2.
The IV plan (upper images) and PCA_plan (lower images) are shown. Left to right; axial, sagittal, and coronal images. The
red-crossed line shows the position of the isocenter in each plan. The yellow-crossed line shows the position of the sagittal and coronalslices.

ter radiosurgery. In particular, the draining veins should
be excluded from the target volume. Conventionally, we
have excluded draining veins manually from the target
volume on planning CT images by referring to DSA images or MRI images. This operation is very time-consuming and complicated, even when the procedure is potentially feasible. In most cases, it is very difficult and infact, almost impossible, to identify which points on CT
images of each slice correspond to the marked draining
vein on DSA images, because the structures are presented two-dimensionally.
IADCT is a useful tool for separating veins from thenidus. However, as an example, in the left image of Figure 3, we can identify the shape of the vessels on thewhole, but cannot distinguish each vessel component using IVCT images alone. Because an AVM is composedof native deformed vessels where the artery and veinconnect directly without capillary vessels, most of the
AVM is labyrinthine in structure, with the feeding arteries, nidus, and draining veins. In these cases we cannot
remove the draining veins from the target volume because there are overlapping regions of the nidus and theveins. However, with our method, we found that there
are some cases in which the draining vein can be excluded from the target volume. In the left image of Figure 3,
the GTV_IV (blue line) is shown as the target delineation referring only to the IVCT image. Comparing thefirst-component image and second-component image,
we can easily identify the draining vein as part of thesecond-component image separated from the first-component image. As a result, we were able to delineate
GTV_PCA (red line) excluding the draining veins.
Graphically, the organ at risk ‘vein’ ROIs could be recognized as draining veins, and we confirmed the anatomical connection by referring to the DSA and IADCT
images. Irradiation doses of ‘vein’ ROI were evidently
reduced. Our method provides more accurate target delineation and reduction of wasteful operation time.
Moreover, when larger AVMs are treated, this proposed
method would be able to reduce the target volume dramatically, thereby allowing us to perform SRS moresafely.
Since there are many types of AVMs (e.g., high flow,
low flow, multiple feeders, etc.), we needed to analyze asufficient amount of clinical data regarding the kind ofcases that the PCA method could be adapted to clinically.
One limitation is the substantial amount of time andwork required for PCA data processing since this is currently performed virtually manually. In order to utilize
this method for actual clinical treatment, it would bevaluable to install the PCA method in a treatment planning workstation. In addition, in this study, a substantial
amount of time was needed to acquire IADCT data because we used a dynamic study for each 3 mm interposi-

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Kawaguchi O, et al: SRS Planning for AVM Based on Principal Component Analysis

Fig. 7 Dose-volume histograms of IV and PCA_plans in Case 2.
Dose-volume histograms as absolute dose for the IV_plan (solid line) and PCA_plan (dotted line) are shown.

Fig. 8 Dose-volume histograms of the ‘vein’ ROI in Cases 1-4 for the IV_plan (solid line) and PCA_plan (dotted line).

tion slice with a single-row-detector. AVMs could bestudied with IADCT in a very short time if 16- or 64-row
multidetector CT (MDCT) was used; a practice that has
become more widespread recently. The craniocaudal
special resolution of MDCT-based IADCT is less than
0.6 mm. Our proposed method would be more practicalusing MDCT.

Conclusions
We proposed a novel method of extracting intracranial
AVMs, and succeeded in accurately identifying the location of intracranial blood vessels by means of PCA. Furthermore, we were able to distinguish needless draining
veins for radiosurgical targeting by using the principal
component images. From these preliminary results, it
was determined that there are some cases in which it ispossible to make target delineation more accurate. In the

Keio J Med 2009; 58 (1):41－ 49

simulations, we were able to reduce the target volumeusing PCA images. The irradiation doses of these needless draining veins were also reduced. Further studies areneeded to investigate the effectiveness of this method forother types of AVMs.
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49

Appendix
Details and principle of factor analysis
for dynamic CT data set
We define the sequence of X-ray CT images as xij (k),where i and j are positions in the kth image (i = 1, … , n,
j = =1, … , n). The total number of images is n.
Let xij (k) be the count of each pixel defined by thevectorXij = [xij(1), xij(2), ... , xij(k), ... , xij(n)](1)

represents the temporal evolution of the content of pixel(i, j). This elemental time-activity curve is called a “dixel”(pixel for dynamic studies). The entire information iscontained in n×n dixels. Each pixel of an image corresponds to an underlying activity that is the summation of
the activities of a number of anatomical components andphysiological components. The kth image can be writtenasxij(k) = aijA(k) + vijV(k) + mijM(k) + bijB(k)(2)

where A(k), V(k), M(k), and B(k) represent the elementary activities corresponding to the arterial flow, the venous flow, the flow in nidus, and the background activity.
The time-independent coefficients aij, vij, mij, and bij
represent the contributions of each physiological component in the pixel (i, j). Bij(k) is the background component.
For each k the elementary activities A(k), V(k), M(k),and B(k) are non-negative, and coefficients aij, vij, mij,and bij are also non-negative.
The time evolution of a dixel (i, j) is
Xij = aijA + vijV + mijM + bijB
where each vector is(3)

A = [A(1), A(2), ..., A(k), ... , A(p)](4)
V = [V(1), V(2), ..., V(k), ... , V(p)](5)
M = [M(1), M(2), ..., M(k), ... , M(p)](6)
B = [B(1), B(2), ... , B(k), ..., B(p)](7)
These vectors represented as A, V, M, and B, are fundamental dynamic components, and vary with time. On theother hand, aij, vij, mij, and bij are coefficients that are
independent of time.
The associated images composed of coefficients arecalled functional images, and are as follows:
Ia = aij
Iv = vij
Im = mij
Ib = bij

(8)
(9)
(10)
(11)