growth kinetics and treatment response of the intracerebral...

Vol. 1, 643-650, June 1995 Clinical Cancer Research 643

Growth Kinetics and Treatment Response of the Intracerebral Rat

9L Brain Tumor Model: A Quantitative in Vivo Study Using

Magnetic Resonance Imaging’

Boklye Kim, Thomas L. Chenevert,

and Brian D. Ross2

Departments of Radiology [B. K., T. L. C., B. D. R.] and Biological

Chemistry [B. D. R.], University of Michigan, School of Medicine,

Ann Arbor, Michigan 48109-0648

ABSTRACT

We report the use of magnetic resonance imaging

(MRI) for in situtumor growth rate studies of experimental

intracranial 9L tumors. T2-weighted spin-echo coronal mag-netic resonance images of rat brains with 9L tumors were

obtained every 2 days beginning at 8-11 days postimplan-

tation using a 7 tesla Mifi system. Tumors were clearly

delineated in the images as a hyperintense region with a

relatively well-demarcated border and minimal peritumoral

edema. Tumor volumes from individual slices were summed

together to yield the total tumor volume. The accuracy of

this methodology for volumetric determination was verified

by MRI phantom studies. Tumor growth rates determinedfrom sequential MIII measurements of tumor volumes werequantitated in terms of volumetric doubling time. Tumor

doubling times were found to range from 50 to 81 h, with an

average of 66 ± 8 h (n = 10). Intracranial 9L tumors werefound to grow exponentially over the entire life span of theanimal, allowing treated animals to serve as their own con-trols since the volumetric doubling time could be determined

from three to four MRI scans before treatment administra-

tion. The intracerebral tumor growth delay following a sin-

gle injection of 1,3-bis(2-chloroethyl)-1-nitrosourea (13.3

mg/kg i.p.) allowed for noninvasive determination of in vivo

log cell kill. A 2.0 ± 0.2 (n 3) log cell kill from 1,3-bis(2-

chloroethyl)-1-nitrosourea treatment was found from post-

treatment MRI volume measurements. These results dem-

onstrate that MRI provides a powerful and sensitive method

for assessing the growth and treatment response of intra-

cranial 9L tumors in the rat.

INTRODUCTION

Malignant gliomas constitute a major therapeutic problem

because of their frequency of occurrence and extremely poor

prognosis. Rodent brain tumor models play an important role in

the in vivo evaluation of novel therapeutic approaches (1). The

therapeutic response of orthotopic brain tumors has traditionally

been quantitated using animal survival, tumor weights following

excision, or colony-forming assays of cells cultured from the in

situ tumor as biological end points (2-12). These methods have

proved valuable for in vivo testing of new therapeutic ap-

proaches but suffer the disadvantage that large numbers of

animals are typically required due to the variable growth rate

and therapeutic response. A method that would allow the intra-

cranial tumor volume to be noninvasively and repeatedly mon-

itored over the life span of individual animals would be bene-

ficial for the evaluation of new therapeutic approaches. In this

study, we evaluated the use of MRI3 as a noninvasive tool to

serially monitor the growth and therapeutic response of the

intracranial rat 9L brain tumor model (2, 5). Tumor volumetric

measurements by MRI were validated using phantoms of known

volumes. We report that T,,,s of intracranial 9L tumors could be

accurately obtained in individual rats from serial MR images.

Significant animal to animal variation in tumor growth rates

using this approach was observed; however, all untreated 9L

tumors were found to grow exponentially over the entire life

span of the animal. The exponential growth characteristic al-

lowed for treated animals to serve as their own control if the Td

was determined from several MRI scans before administration

of treatment. A marked decrease in growth rate was observed

following BCNU administration, and cell kill was determined

for individual animals from tumor volume growth delay mea-

surements. Furthermore, changes in tumor morphology follow-

ing BCNU treatment could be detected as regional changes in

image signal intensity. This study shows the usefulness of MRI

as a powerful noninvasive tool for evaluating treatment of in

vivo intracranial brain tumor models.

MATERIALS AND METHODS

Cell Culture Conditions. 9L tumor cells were grown as

monolayers in 75-cm2 sterile plastic flasks in modified Eagle’s

MEM with 10% FCS. Cells were cultured in an incubator at

37#{176}Cin an atmosphere containing 95% air and 5% CO2 until

confluent. Cells were harvested by trypsinization, counted, and

resuspended in serum-free media for intracerebral injection.

Induction of Brain Tumors. 9L tumor cells were im-

planted in anesthetized (ketamine, 87 mg/kg, + xylazine, 13

Received 10/6/94; accepted 1/20/95.

C This research was supported in part by Grant BE-149 from the Amer-

ican Cancer Society and NIH Grants R29 CA59009 and P20 N531 114-

01.

2 To whom requests for reprints should be addressed, at Department of

Radiology, University of Michigan Medical School, 1150 West Medical

Center Drive, MSRB III, Room 9303, Box 0648, Ann Arbor, MI

48109-0648.

3 The abbreviations used are: MRI, magnetic resonance imaging;

BCNU, 1 ,3-bis(2-chloroethyl)-1-nitrosourea; MR, magnetic resonance;

LD10, lethal dose for 10% of animals; MRS, magnetic resonance spec-

troscopy; SISCO, Spectroscopy Imaging Systems Corporation; �

potential doubling time; Td, doubling time; TR, repetition time; TE,

echo time; FOV, field of view.

on April 9, 2019. © 1995 American Association for Cancer Research.clincancerres.aacrjournals.org Downloaded from

http://clincancerres.aacrjournals.org/

644 MRI of Experimental Intracranial Tumors

V�(t) = [(1 - 1k) V(tT) e�’�’ � tT)] + 1k V(tT) (B)

mg/kg body weight i.p.) adult male Fischer 344 rats weighing

between 125 and 150 g. A small skin incision over the right

hemisphere was made. A high-speed drill was used to create a

1-mm diameter burr hole through the skull. Inoculation of i05

9L tumor cells in S p.1 in the right forebrain at a depth of 3 mm

was accomplished. The burr hole was filled with bone wax to

minimize the potential for extracerebral extension of the tumor

tissue. The skin was sutured together and the rats were allowed

to recover.

MRI. All in vivo MRI experiments were performed on a

SISCO system equipped with a 7.0 tesla, 18.3-cm horizontal

bore magnet (300-MHz proton frequency). For MRI examina-

tion, rats were anesthetized with either sodium pentobarbital (65

mg/kg i.p.) or a ketamine/xylazine (87 mg/kg/13 mg/kg i.p.)

mixture and maintained at 37#{176}Cinside the magnet using a

heated circulating water blanket. MRI of rat brains was initiated

between 8 and 1 1 days following cell implantation and repeated

every other day. The rat head was positioned inside a 4-cm

diameter birdcage rf coil which was designed and constructed

with ear bars to secure the position of the head during the

acquisition. For each MRI session, a single-slice gradient-

recalled-echo image was acquired with 1-mm ‘ ‘saturation cross-

hairs’ ‘ imprinted on the axial and coronal images to facilitate

rapid and reproducible positioning of the animal. Multislice

axial images were acquired using a standard spin echo sequence.

T2-weighted images through the rat brain were produced using

the following parameters: TR/TE = 3500/60, FOV = 30 X 30

mm using a 128 x 128 matrix, slice thickness = 0.5 mm and

slice separation 0.8 mm. Twenty-five slices were acquired

followed by acquisition of a second set of 25 slices with a slice

offset of 0.4 mm providing contiguous image data set of the rat

brain.

Tumor Treatment. BCNU was obtained from the Uni-

versity of Michigan Hospital pharmacy and dissolved in abso-

lute ethanol and diluted in saline (0.9% NaC1) to a final con-

centration of 3.3 mg/ml in 10% ethanol. Each treated animal

(n 3) received a single LD10 injection of BCNU (13.3 mg/kg

i.p.) after three or four pretreatment tumor MRI volumetric

measurements. This procedure allowed each animal to serve as

its own control because the Td could be accurately determined

from as few as three pretreated volumetric measurements.

Certain anesthetics have been reported to induce changes in

liver enzymes accelerating the clearance of BCNU. For exam-

ple, chronic p.o. administration of phenobarbital has been shown

to completely eliminate the antitumor activity of BCNU against

the rat intracranial 9L tumor model (13). Because the use of

anesthetics was necessary to keep the animals motionless during

MRI examination, their effects on induction of liver enzymes

was minimized in two ways: (a) only the ketamine mixture was

used (rather than pentobarbital) for treatment studies since it has

been shown to have limited potential for long term induction of

liver enzymes (14), and (b) following acquisition of the first two

or three MRI scans 2 days apart, 3 days were allowed to pass

between the last time the animal was anesthetized and BCNU

administration. This was done to allow for clearance of the

anesthetic and reversal of the potential changes in liver enzyme

levels. On the third day following the last MRI scan, BCNU was

administered to unanesthetized rats. Within 1-2 h following

BCNU administration, MRI scanning was resumed and contin-

ued every 2-3 days until death. Pretreatment Td was determined

from the initial three or four MRI scans which allowed for

sufficient time to follow treatment response before death.

Calibration of MIII Volume Measurements. Calibra-tion of MRI volume measurements was achieved by measuring

the volume of four different sphere phantoms using the same

MRI acquisition protocol used for scanning rats. The phantoms

consisted of spherical glass bulbs (Wilmad Glass Co., Buena,

NJ). The ‘ ‘actual volumes’ ‘ of the phantoms, calibrated using a

Hamilton syringe, were 22.5, 31.2, 113.5, and 297.7 mm3.

Phantom volumes were quantitated from MRI data sets using a

region of interest program provided with the SISCO software

and were compared with the actual volume of each phantom to

determine the accuracy of the MRI method. For all MRI phan-

tom validation experiments, phantoms were filled with cupric

sulfate (20 mM) and submerged in a bottle filled with distilled

water.

Partial volume effects, assuming square slice profiles and

ideal spherical volumes, were modeled to define the precision of

this methodology. MRI volumes were determined by summing

all of the cylindroids that spanned the object. Errors arising from

partial volume effects result in maximum overestimation of

experimental volume if voxels are included in the volume when

any fraction of a voxel is within the sphere. Conversely, if only

voxels entirely within the sphere are included, then an underes-

timated volume results. An intermediary condition is where the

center of each slice profile circumscribes the projected area of

the sphere for that slice. Modeled volumes and associated partial

volume errors were estimated using four idealized spheres hay-

ing the same volume as the phantoms.

Quantitation of Intracranial Tumor Volumes. For vol-

ume measurements at each time point, the area (volume) of

tumor visualized in each slice was manually outlined using a

region of interest program provided with the SISCO MRI soft-

ware. The outlined tumor area in each cross-sectional image was

multiplied by the slice separation (0.4 mm) to calculate the

tumor volume in each slice. The tumor volumes of individual

slices were summed to yield the total volume of the tumor.

Although tumors as small as 2 mm3 (about 2 mm in diameter)

were measured using MRI, tumors with a minimal volume of

8-10 mm3 were used for the initial volumetric time point since

there was less uncertainty in the accuracy of the initial tumor

volume measurement.

Determination of Tumor T,, and Log Cell Kill. Tumorvolumes measured by MRI were plotted against hours postim-

plantation to determine the growth rate of the intracranial 9L

tumors. By using the definition of exponential growth,

V(t) = V0 10kz (A)

where V(t) is tumor volume at time t, V0 is the initial tumor

volume, and the volumetric Td was calculated from the expres-

sion, Td (log 2)/k. The tumor growth rate constant (k) was

obtained from an exponential curve fit of the volume data points

using a least-squares algorithm.

In principle, cell kill for each treated animal can be deter-

mined by using the expression for posttreatment tumor volume

(Vp),



Clinical Cancer Research 645

4 R. F. Keep, personal communication.

r�;;

E‘-.

t�

E.�

;;a.

.��I

b��-

��

300

250

200

150

100

50

0/

0 50 100 150 200 250 300

Actual Phantom Volume (mm3)

Fig. 1 A plot of the actual phantom volumes (mm3) determined usinga Hamilton syringe versus MRI determined volumes (mm3).

where V(t�) is tumor volume at the time of treatment (tv), fk

is the fraction of cells killed by the treatment, and k is the

posttreatment growth rate constant. The first term in Equation

B describes the growing fraction following treatment while

the second term describes the dead cell fraction following

treatment. In this study, Equation B was used to model the

effect of increasing cell kill on the posttreatment tumor

growth rate.

Given the empirical growth delay, (T, - 1’,) which is

defined as the difference in time for untreated (T�) and treated

(Ti) tumors to grow to the same size (15), cell kill can be

estimated by

log(cell kill) = (1’, - T,.)k

The values of T�, T�, and k can all be accurately determined from

the serial MR images of the intracranial tumor, thus Equation B

was used to determine the cell kill for animals treated with

BCNU in this study.

RESULTS

Accuracy of Mill Volume Measurements. Shown inFig. 1 are the ‘ ‘actual’ ‘ phantom volumes (obtained by mea-

surements using a Hamilton syringe) plotted against volumes

determined by MRI. All discrepancies from the unity line

were within 10%. Modeled extrema of partial volume errors

ranged from ±21% (smallest phantom) to ±9% (largest

phantom). Close agreement between MRI and actual phantom

volumes suggests that the MRI methodology is accurate and

well within predicted precision limits set by partial volume

models.

Quantitation of Td from MR Images of Rat IntracranialTumors. Intracranial 9L tumor volumes could be measured by

MRI approximately 10 days postimplantation. Shown in Fig. 2

is a representative series of T2-weighted coronal MR images

revealing the growth of an untreated intracranial tumor from 12

to 22 days postimplantation. During this time period, the tumor

volume increased from 23 to 263 mm3. In Fig. 2, the series of

MR images are shown from the same region of the rat brain

located at approximately the largest diameter of the tumor. The

tumor is clearly evident in the right hemisphere as a hyperin-

tense region which is easily distinguished from the normal brain

parenchyma. An increasing mass effect with time, due to the

presence of the expanding tumor, is evident (e.g., midline shift).

The characteristic features of untreated 9L tumors imaged in this

study were a well-demarcated tumor mass with a relatively

uniform hyperintense tumor signal and minimal peritumoral

edema. The small and disseminated hypointense regions appar-

ent in the tumors in Fig. 2 are believed to arise from paramag-

netic susceptibility differences within the tumor mass, which are

accentuated at the relatively high magnetic field (7 tesla) used in

this study, and were included in tumor volume calculations.

Recent studies of excised tissue samples have revealed that the

brain adjacent to the 9L tumor in the ipsilateral hemisphere had

no significant change in water content (edema) relative to the

contralateral hemisphere.4

Shown in Fig. 3 is a semi-log plot of the volume versus

hours after intracerebral implantation of i0� 9L tumor cells

from the rat shown in Fig. 2. The individual points are shown

along with the line representing the least-squares fit. The Td

of the 9L tumor shown in Fig. 3 was determined to be 68 h.

This plot reveals the typical exponential growth pattern seen

for all untreated intracerebral 9L tumors. Untreated intracra-

nial tumor Tds are listed in Table 1 along with survival times

and the final tumor volumes. The mean tumor Td of intracra-

nial 9L tumors determined from sequential MRI measure-

ments was 66 ± 8 h (n = 10, ±SD). All untreated intrace-

rebral 9L tumors imaged in this study were found to grow

exponentially over the entire life span of the animal, with an

average correlation cofficient of 0.986 ± 0.14 (n = 10,

±SD). The final average tumor volume obtained at or near

death was 223 ± 53 mm3 (n = 7, ± SD).

(C) Quantitation of Therapeutic Efficacy from MIII Tumor

Volumetric Measurements. Assuming an intracranial tumor

with a Td of 50 h, a theoretical growth curve was generated

using Equation A as shown in Fig. 4. Log kill values of 0.2, 0.4,

0.7, 1, 2, and 3 were used in Equation B to model the effect on

the initial tumor growth as shown in Fig. 4, b-g, respectively.

This model assumes that on the day of treatment, the growth rate

constant (k) for the surviving cells remains the same average

rate as that of untreated cells, cells rendered nonviable by the

treatment do not undergo further division, and the volume of the

displaced brain does not shrink, even following significant cell

killing (e.g., 3 X log kill), but rather is replaced with reactive

astrocytosis, necrosis, etc. The growth delays for 0.2, 0.4, 0.7, 1,

2, and 3 log kill, given a Td of 50 h, were calculated to be 33,

66, 116, 166, 332, and 498 h, respectively, as shown in Fig. 4,

b-g.

In order to determine the sensitivity at which the MRI

volumetric measurements could detect a change in Td (or cell

kill), all of the untreated rats were analyzed as if they were

treated in the following manner. The first four volumetric

measurements of each untreated 9L tumor were used to

determine the value of k for that particular tumor. The fourth




(D)

a b c

,. p

&

d e f

#{149}r

\� //

dl”

:� -,

Fig. 2 A series of coronal T2-weighted MR images of a rat brain (Rat 2, Table 1) with time after implantation of 10� 9L tumor cells. Each displayedimage is from approximately the same region of the brain. Clearly evident in the right hemisphere is a hyperintense region corresponding to the 9L

tumor mass. Untreated tumor volumes for each time point are as follows [day postimplantation/tumor volume (mm3)]: a, 12/23; b, 14/40; c, 16/64;d, 18/97; e, 20/171; andf, 22/263.

volumetric data point (the volume at the supposed time of

treatment) was used with the subsequent volume measure-

ments along with k (determined from pretreatment volumetric

data) to calculate the cell kill (Jk) using an iterative fitting

algorithm for Equation B. Analyzing the data in this manner

revealed that for all untreated rats, cell kill values ranged

from -0.1 to +0.1 log cell kill. Thus, evaluation of MRI

tumor growth data from untreated rats indicated that this MRI

approach was sensitive enough to detect changes in tumor

growth rates when the treatment resulted in >0.1 log kill.

Therapeutic Efficacy of BCNU on Intracranial 9L Tu-

mors. Fig. 5 shows a semi-log plot of the volume versus time

postimplantation of an intracranial 9L tumor. At approximately

1-2 h before the third volume measurement, the rat was treated

with a LD10 of BCNU. The time course of posttreatment tumor

volumes shows a deviation from the well-defined pretreatment

exponential growth curve. The volume of the tumor appears to

increase (although the rate of growth is attenuated) for 5 to 6

days after treatment followed by a decrease in tumor volume

during 6-14 days posttreatment. The first and last three data

points in Fig. 5 were used to determine the pretreatment and

post-treatment tumor T,�s, respectively. After approximately 14

days posttreatment (672 h postimplantation in Fig. 5), the Td of

the intracranial 9L tumor was 49 h, nearly identical to the

pretreatment rate of 5 1 h. A growth delay of 356 h (“�‘ 15 days)

was calculated from the MRI data and when combined with the

pretreatment growth rate constant (k) of 50 h, a log kill of 2.1

was calculated using Equation C. This calculation compares

favorably with the modeled cell kill plot shown in Fig. 4 which

used a pretreatment Td of 50 h, comparable to the rat shown in

Fig. 5. Log kills of 2.1 and 1.8 were found for the other two rats

treated with BCNU. An average survival time of 38 ± 5 days

(n 3, ±SD) for BCNU-treated rats was found compared to the

average survival time of 22 ± 2 days (Table 1) for untreated

animals yielding a 73% increased life span for BCNU-treated

animals.

The use of MRI also allowed for monitoring, noninva-

sively, the changes in tumor morphology following treatment.

Fig. 6A-F displays the coronal T2-weighted MR images of the

same 9L tumor shown in Fig. S at Days 14, 17, 20, 24, 26, and

28 postimplantation, respectively. Two h prior to acquiring the

14-day image (Fig. 6a), the rat was treated with a single dose of

BCNU (13.3 mg/kg i.p.). The tumor continued to expand until

Day 20 postimplantation (Fig. 6c) and a heterogeneous reduc-

tion in tumor image intensity was noted at later times following

treatment (Fig. 6, d-f).

Calculation of the Cell Loss Factor. In a previous study

of intracranial 9L tumors, the � the time required for a tumor

to double its size in the absence of cell loss, was determined to

be 64.2 h using double labeling with iododeoxyuridine and

bromodeoxyuridine (16). This value of � combined with our

average value of Td for untreated 9L tumors (66 h), allowed the

cell loss factor (J) to be determined using Equation D below as

described previously (17).

1= 1 - T�,c,t/Td



“C

EE

EE4�

EC

0

1..

0

E0

Hours Post Implantation of 9L Cells

240 360 480 600 720 840 960

EE

�/�ai#{216}- growth delay �

...,

BCNU�/ #{149}.

$.....o. #{149} 0’

,.L;1:

.“a

.�

�. . .,,

DISCUSSION

Quantitation of the in vivo antitumor activity of an exper-

imental treatment is an essential component of assessing new

therapeutic approaches. Traditional survival studies using ani-

mal brain tumor models, although invaluable, require a greater

than one log kill to discern a statistically significant increase in

life span (3). MRI of intracranial rodent brain tumor models

offers a more sensitive indicator of therapeutic effectiveness

since a >0.1 log kill can be detected in a single animal from

serial MR images and should facilitate an earlier interpretation

of brain tumor responsiveness relative to survival studies. Fur-

thermore, studies of intracranial tumor models using MRI

should help to improve our understanding of the biochemical or

physiological basis of nonresponsiveness due to such variable

factors as growth rate, size, location, and vascularity. This


approach should also help to increase the throughput of evalu-

Fig. 3 A semi-log plot of the tumor volumes obtained from serial MRimages versus time after cell implantation for the intracranial 9L tumorshown in Fig. 2. The individual volume measurements are shown alongwith the line corresponding to the least-squares fit (y = 1.4 * 100��;

correlation coefficient, 0.9986). This representative plot reveals the cx-ponential growth characteristic of the intracerebral 9L tumor over the

entire growth period. Using this data, the Td for this rat was determinedto be 68 h.

Table 1 Summary of tumor volumetric Td, final volumes, and

survival of individual rats with untreated intracranial9L gliosarcomas

Final SurvivalRat Td (h)” volume (mm3) (days)

1 74 284 22

2 68 263 22

3 61 210 22

4 69 242 19

5 68 189 19b

6 81 1467 63 245 20

8 50 191 26

9 62 16010 63 304 21

Average ± SD 66 ± 8 223 ± 53C 22 ± 2C

a All intracranial tumors exhibited exponential growth over the

entire life span of the animal.b Animals that died from anesthesia during MRI examination.C Includes only animals (n 7) that did not die prematurely due to

anesthesia.

Calculation of f reveals a value of 2.7%, indicating that pro-

cesses of cell loss competing with the process of cell production

are minimal for untreated 9L tumors.

Hours Post Implantation of Cells

Fig. 4 Theoretical tumor growth curves were generated using Equa-

tion B, assuming a Td of 50 h showing log cell kill values of 0 (a), 0.2

(b), 0.4 (c), 0.7 (d), 1 (e), 2 (f), and 3 (g) corresponding to tumor growth

delays of 0, 33, 66, 1 16, 166, 332, and 498 h, respectively. Note that 0.2,

0.4, 0.7, 1, 2, and 3 log kill represent a cell kill of 16%, 25%, 50%, 90%,99%, and 99.9%, respectively.

240 360 480 600 � �

Hours Post Implantation of 9L Cells

Fig. 5 A semi-log plot of the tumor volumes obtained from serial MR

images versus time after cell implantation for an intracranial 9L tumor

treated with a LD10 of BCNU at 350 h after cell implantation. The firstthree volumetric measurements were used to determine the pretreatmentTd. Curves a and b, least-squares fit of the pretreatment and posttreat-ment regrowth, respectively. The pretreatment and posttreatment T,,swere 51 and 49 h, respectively. The tumor growth delay, 15 days, wasdetermined from the difference in time for untreated and treated tumorto grow to the same size.



a

‘I.

, - .‘

�: ‘( � ‘ I

d

., ‘I,


b

e

Fig. 6 Coronal T2-weighted MR images of a rat brain (same rat as in Fig. 5) with time after implantation of 9L tumor cells. Each displayed imageis from approximately the same region of the brain. a-f, 9L tumor brain at Days 14, 17, 20, 24, 26, and 28 postimplantation, respectively. Two h prior

to acquiring the 14-day image (a), the rat was treated with a single dose of BCNU (13.3 mg/kg i.p.). The tumor continued to expand until Day 20

postimplantation and a heterogeneous reduction in tumor image intensity was noted at later times following treatment (d-f).

ating novel therapeutic approaches for treating brain tumors,

since an individual animal can serve as its own control due to

the exponential growth characteristic of this tumor model.

The exponential growth of the intracranial 9L tumor is

consistent with a model in which the cell cycle time, growth

fraction, and rate of cell loss are all constant with time (17). The

nearly zero cell loss factor (2.7%) also agrees well with our

histopathological observation of minimal necrosis within un-

treated intracerebral 9L tumors. It should be noted, however,

that the biological characteristics ofthe 9L tumor may vary from

institution to institution and � obtained from the literature

(16) may not exactly represent T�1 for the 9L tumors studied in

our laboratory. In the present study, we used a single dose of

BCNU to demonstrate the feasibility of monitoring therapeutic-

induced tumor growth inhibition using MRI. This approach

should provide a unique opportunity to evaluate various thera-

peutic interventions such as systemically or intratumorally ad-

ministered chemotherapeutic agents, radiation, interstitial im-

plants of drugs encapsulated in biodegradable polymers, and

after transfer of a therapeutic gene construct. Application of this

latter approach to MRI is appealing since the vector or virus is

typically delivered by a direct injection into the tumor mass.

Prior knowledge of the size, location, and pretreatment growth

rate of an individual intracerebral tumor would allow individu-

alization of the dose, provide coordinates for stereotaxic deliv-

ery, and monitoring of the therapeutic response. It should also

be possible to use MRI to study other brain tumor models such

as heterologous transplantation of human brain tumors in athy-

mid nude mice and nude rats, although for each model, the

untreated growth characteristics must be established.

The range in Td of intracerebral 9L tumors (from 50 to

81 h) found in this present study (Table 1) provides a direct

observation of the heterogeneity of tumor growth rates in this

brain tumor model system. We found that the variation in tumor

growth rates is inherent to the biological system since it is

present in a group of animals implanted on the same day with

the same cell suspension. This observation helps to elucidate the

reason for the marked variability in tumor sizes reported in

studies using excision and weighing of the tumor (see Fig. 2 in

Ref. 5).

Although the Td dramatically decreased following treat-

ment with BCNU, the tumor volume still increased for 4 to 5

days posttreatment before the tumor volume began to shrink

(Fig. 5). This phenomenon is most likely due to BCNU render-

ing many cells nonviable immediately following treatment.

However, some of these cells probably divide several times

before death. The cells remaining viable following treatment

grow at the same average rate as untreated cells, resulting in the

regrowth observed at Day 14 posttreatment in Fig. 5. This time

course is nearly identical to that previously reported for changes

in tumor weight following a LD10 of BCNU (5) and for the

removal of dead tumor tissue from the brain of a rat (18). The

theoretical growth delay curves shown in Fig. 4 serve to provide

an approximation of the growth delay expected from a given log

kill. We did not attempt to model the more complex tumor

volume time course observed following BCNU treatment since

log kill can be estimated from the tumor growth delay (5). A

more complete model would require additional functions de-

scribing such phenomenon as the swelling of cells following

death (18), the ability of treated cells to divide a few times after

treatment (19), and the removal of dead cells from the brain

( 18). However, Equation B can be used to model the changes in

tumor growth for lower cell kills (0.2-1.0 log kill) in which the

swelling of cells and cell removal would not produce the pro-

found changes seen with log kill in the range of 2.0-3.0.

The mean 2.1 ± 0.2 log kill observed in the present study

using MRI was lower than the mean log kill of 3.23 ± 0.57 (SD,

n 57) previously reported for a LD10 of BCNU, measured




using the colony-forming efficiency assay (5). Our lower cell

kill could be due to several factors such as a residual anesthetic-

induced increase in liver enzymes involved in BCNU removal

or differences in the time between preparation of the BCNU

solution and administration since BCNU in aqueous solution is

unstable (20). Many other biological factors could also be re-

sponsible for the difference between the cell kill value calcu-

lated from the MRI data and the value determined by colony

formation assays. For example, the host cell composition of the

tumor will vary significantly after treatment, thereby influencing

cell kill estimates made from volume measurements (21). The

cell loss factor will increase dramatically after treatment and

will be variable during the posttreatment period and intratu-

moral edema and necrosis may also be complicating features.

Furthermore, results obtained from excision assays have been

reported to not always correlate with studies using in situ assays

in which the tumor is allowed to remain intact in the animal (22,

23). Finally, the large variability in cell kill measured by the

colony-forming assay (1-1.5 logs) and the biological factors

which contribute to volume but not to tumor cell colony forma-

tion indicate that the MRI measurements of BCNU-treated

animals are consistent with the expected cell kill from a single

dose of BCNU.

The validity of MRI volume measurements has been es-

tablished by direct comparison with either histological volume

measurements (24) or volumes of excised tumors (25). MRI

volume measurements have also been reported to estimate in-

tracranial tumor progression (26) and assess the average treat-

ment response of hepatic metastases of colon cancer in rats (27).

For most MR images, partial volume effects from limited res-

olution blur even high-contrast tumor borders. Consequently,

tracing the shape of interest may result in errors in accurate

volume measurements. This potential source of error, as well as

geometric accuracy of the imaging system, was evaluated by the

use of phantoms of predetermined volumes. With a 0.5-mm

slice sampling, the partial volume effect was determined to be

minimal, thus verifying the accuracy of the tumor volume mea-

surements by the present method. Furthermore, we also evalu-

ated the effects of administration of contrast agent (gadolinium

diethylenetriamine pentaacetic acid) on the delineation of 9L

tumor boundaries using T1-weighted images. Tumor volumes

calculated from T2- and T1-weighted contrast enhanced images

were found to be nearly identical to the T1-weighted image data

set yielding tumor volumes of approximately 10% larger. This

larger volume was presumably due to ‘ ‘leakage ‘ ‘ of the contrast

agent from the tumor into the adjacent normal brain paren-

chyma. Contrast enhancement for delineation of the 9L tumor

border resulted in an overestimation of tumor volume and is

therefore not advised for determining tumor volumes from MR

images since this tumor model characteristically has well-de-

marcated tumor boundaries with minimal peritumoral edema.

Finally, because MRS provides a method for in vivo mon-

itoring of various tumor metabolites and pH (28), there has been

great interest in determining whether specific changes in me-

tabolite levels following treatment are predictive of therapeutic

outcome. Studies of experimental intracerebral brain tumors

using 31P, ‘3C, and ‘H MRS have been reported (29-32). Since

MRI can now be used to quantitate treatment effectiveness in an

individual animal, correlative studies between MRS and MRI

using animal brain tumor models should provide an exciting

opportunity to evaluate MRS as a predictor of therapeutic effi-

cacy. This type of correlative study would serve to more clearly

define the use of MRS for evaluating brain tumor treatment in

the clinical setting.

ACKNOWLEDGMENTS

The 9L gliosarcoma cell line was kindly provided by the Brain

Tumor Research Center at the University of California, San Franscisco.We thank Christina Hurlbert for excellent technical assistance and

Reviewer 2 for helpful comments.

REFERENCES

1. Peterson, D. L., Sheridan, P. J., and Brown, W. E., Jr. Animal models

for brain tumors: historical perspectives and future directions. J. Neu-

rosurg., 80: 865-876, 1994.

2. Barker, M., Hoshino, T., Gurcay, 0., Wilson, C. B., Nielsen, S. L.,Downie, R., and Eliason, J. Development of an animal brain tumor

model and its response to therapy with 1,3-bis(2-chloroethyl)-1-nitro-

sourea. Cancer Res., 33: 976-986, 1973.

3. Rosenblum, M. L, Wheeler, K. T., Wilson, C. B., Barker, M., and

Knebel, K. D. In vitro evaluation of in vivo brain tumor chemotherapy with

1,3-bis(2-cMoroethyl)-1-nitrosourea. Cancer Res., 35: 1387-1391, 1975.

4. Rosenblum, M. L., Knebel, K. D., Vasquez, D. A., and Wilson, C. B.

In vivo clonogenic tumor cell kinetics following 1,3-bis(2-chloroethyl)-

1-nitrosourea brain tumor therapy. Cancer Res., 36: 3718-3725, 1976.

5. Rosenblum, M. L., Knebel, K. D., Vasquez, D. A., and Wilson, C. B.

Brain-tumor therapy. Quantitative analysis using a model system. J.

Neurosurg., 46: 145-154, 1977.

6. Rosenblum, M. L., Deen, D. F., Hoshino, T., Dougherty, D. A.,Williams, M. E., and Wilson, C. B. Comparison of clonogenic cellassays after in vivo and in vitro treatment of 9L gliosarcoma. Br. J.

Cancer, 41 (Suppl. IV): 307-308, 1980.

7. Wheeler, K. T., and Wallen, C. A. Is cell survival a determinant ofthe in situ response of 9L tumours? Br. J. Cancer, 41 (Suppl. IV):299-303, 1980.

8. Rosenblum, M. L., Dougherty, D. A., Brown, J. M., Barker, M.,

Deen, D. F., and Hoshino, T. Improved methods for disaggregatingsingle cells from solid tumors. Cell Tissue Kinet., 13: 667, 1980.

9. Weizsaecker, M., Deen, D. F., Rosenblum, M. L., Hoshino, T.,Gutin, P. H., and Barker, M. The 9L rat brain tumor: description and

application of an animal model. J. Neurol., 224: 183-192, 1981.

10. Nomura, K., Hoshino, T., and Pentecost, S. M. Post-treatmentkinetics of BCNU in a 9L rat brain tumor model. Neurol. Med. Chir.(Tokyo), 21: 19-25, 1981.

1 1 . Wheeler, K. T., and Kaufman, K. Efficacy of continuous treatmentwith radiation in a rat brain-tumor model. J. Neurosurg., 55: 52-54, 1981.

12. Vats, T. S., Kimler, B. F., Henderson, S. D., and Morantz, R. A.Combination chemotherapy for the 9L rat brain tumor model system.

Cancer Treat. Rep., 66: 575-579, 1982.

13. Levin, V. A., Sterns, J., Byrd, A., Finn, A., and Weinkam, R. J. The

effect of phenobarbital pretreatment on the antitumor activity of 1,3-

bis(2-chloroethyl)-1-nitrosourea (BCNU), 1-(2-chloroethyl)-3-cydlo-

hexyl-1-nitrosourea (CCNU) and 1-(2-chloroethyl)-3-(2, 6-dioxo-3-pi-peridyl-1-nitrosourea (PCNU), and on the plasma pharmacokinetics and

biotransformation of BCNU. J. Pharmacol. Exp. Ther., 208: 1-6, 1979.

14. Marietta, M. P., Vore, M. E., Way, W. L., and Trevor, A. J.

Characterization of ketamine induction of hepatic microsomal drug

metabolism. Biochem. Pharmacol., 26: 2451-2453, 1977.

15. Hill, R. P. Experimental Radiotherapy. In: I. F. Tannock and R. P.Hill (eds.), The Basic Science of Oncology, pp. 276-301. New York:McGraw-Hill, Inc., 1992.

16. Asai, A., Shibui, S., Barker, M., Vanderlaan, M., Gray, J. W., and

Hoshino, T. Cell kinetics of rat 9L brain tumors determined by double




labeling with iodo- and bromodeoxyuridine. J. Neurosurg., 73: 254-

258, 1990.

17. Steel, G. G. Cell loss from experimental tumours. Cell Tissue

Kinet., 1: 193-207, 1968.

18. Kumar, A. R. V., Hoshino, T., Wheeler, K. T., Barker, M., and

Wilson, C. B. Comparative rates of dead tumor cell removal from brain,

muscle, subcutaneous tissue, and peritoneal cavity. J. Natl. Cancer Inst.,

52: 1751-1755, 1974.

19. Wilcox, W. S., Griswold, D. P., Laster, W. R., Jr., Schabel, F. M.,Jr., and Skipper, H. E. Experimental evaluation of potential anticancer

agents. XVII. Kinetics of growth and regression after treatment of

certain solid tumors. Cancer Chemother. Rep., 47: 27-39, 1965.

20. Tepe, P., Hassenbusch, S. J., Benoit, R., and Anderson, J. H. BCNU

stability as a function of ethanol concentration and temperature. J.

Neuro-Oncol., 10: 121-127, 1991.

21. Siemann, D. W., Lord, E. M., Keng, P. C., and Wheeler, K. T. Cell

subpopulations dispersed from solid tumours and separated by centrif-

ugal elutriation. Br. J. Cancer, 44: 100-108, 1981.

22. Twentyman, P. R. Experimantal chemotherapy studies: intercom-

parison of assays. Br. J. Cancer 41 (Suppl. IV): 279-287, 1980.

23. Stephens, T. C., and Peacock, J. H. Tumour volume response, initial

cell kill and cellular repopulation in B16 melanoma treated with cyclo-

phosphamide and 1-(2-choloroethyl)-3-cyclohexyl-1-nitrosourea. Br. J.

Cancer, 36: 313-321, 1977.

24. Mahmood, U., Devitt, M. L., Kocheril, P. G., Sutanto-Ward, E.,

Ballon, D., Sigurdson, E. R., and Koutcher, J. A. Quantitation of totalmetastatic tumor volume in rat liver: correlation of MR and histologicmeasurements. J. Magn. Reson. Imaging, 2: 335-340, 1992.

25. Quin, Y., Cauteren, M. V., Osteaux, M., and Willems, G. Quan-titative study of the growth of experimental hepatic tumors in rats by

using magnetic resonance imaging. Int. J. Cancer, 51: 665-670,

1992.

26. Rajan, S. S., Rosa, L., Francisco, J., Muraki, A., Carvlin, M., and

Tuturea, E. MRI characterization of 9L-glioma in rat brain at 4.7 tesla.

Magn. Reson. Imaging, 8: 185-190, 1990.

27. Quin, Y., Cauteren, M. V., Osteaux, M., Schally, A. V., andWillems, G. Inhibitory effect of somatostatin analogue RC-160 on the

growth of hepatic metastases of colon cancer in rats: a study with

magnetic resonance imaging. Cancer Res., 52: 6025-6030, 1992.

28. Certaines, J. D. D., Larsen, V. A., Podo, F., Carpinelli, G., Briot, 0.,

and Henriksen, 0. In vivo 31P MRS of experimental tumours. NMRBiomed., 6: 345-365, 1993.

29. Ross, B. D., Higgins, R. J., Boggan, J. E., Knittel, B., and Garwood,

M. 31P NMR spectroscopy of the in vivo metabolism of an intracerebral

glioma in the rat. Magn. Reson. Med., 6: 403-417, 1988.

30. Ross, B. D., Higgins, R. J., Boggan, J. E., Willis, J. A., Knittel, B.,

and Unger, S. W. Investigation of the carbohydrate metabolism of the

C6 glioma: an in vivo ‘3C and in vitro ‘H magnetic resonance spectros-

copy study. NMR Biomed., 1: 20-26, 1988.

31. Ross, B. D., Mitchell, S. L., Merkle, H., and Garwood, M. In vivo

3’P and 2H NMR studies of rat brain tumor pH and blood flow duringacute hyperglycemia: differential effects between subcutaneous andintracerebral locations. Magn. Reson. Med., 12: 219-234, 1989.

32. Ross, B. D., Merkle, H., Hendrich, K., Staewen, R. S., and Gar-wood, M. Spatially localized ‘H spectroscopy of a rat intracerebral

glioma. Magn. Reson. Med., 23: 96-108, 1992.



1995;1:643-650. Clin Cancer Res B Kim, T L Chenevert and B D Ross magnetic resonance imaging.9L brain tumor model: a quantitative in vivo study using Growth kinetics and treatment response of the intracerebral rat

Updated version

http://clincancerres.aacrjournals.org/content/1/6/643

Access the most recent version of this article at:

E-mail alerts related to this article or journal.Sign up to receive free email-alerts

Subscriptions

Reprints and

[email protected] at

To order reprints of this article or to subscribe to the journal, contact the AACR Publications

Permissions

Rightslink site. Click on "Request Permissions" which will take you to the Copyright Clearance Center's (CCC)

.http://clincancerres.aacrjournals.org/content/1/6/643To request permission to re-use all or part of this article, use this link



http://clincancerres.aacrjournals.org/cgi/alerts

mailto:[email protected]



growth kinetics and treatment response of the intracerebral...

Documents