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Comparison of visual metric and planimetry methods for brain tumor measurement in dogs


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OBJECTIVE To compare the orthogonal diameter (visual metric) method against a manual perimeter tracing (planimetry) method to measure volume of brain tumors in dogs by use of MRI scans. SAMPLE 22 sets of MRI brain scans pertaining to 22 client-owned dogs with histologically confirmed glioma. PROCEDURES MRI scans were reviewed by 2 operators, and scans revealing tumors with a degree of gadolinium enhancement that allowed discrimination between tumor tissue and healthy parenchyma were used. Each operator calculated tumor volume for each set of scans twice by use of visual metric and planimetry methods. Inter- and intraoperator variability were assessed by calculation of an agreement index (AI). RESULTS Mean ± SD intraoperator AIs were 0.79 ± 0.24 for the visual metric method and 0.89 ± 0.17 for the planimetry method. Intraoperator variability for both operators was significantly less when the planimetry method was used than when the visual metric method was used. No significant differences were identified in mean interoperator AI between visual metric (0.68 ± 0.28) and planimetry (0.67 ± 0.31) methods. CONCLUSIONS AND CLINICAL RELEVANCE The lower intraoperator variability achieved with the planimetry versus visual metric method should result in more precise volume assessments when the same operator performs multiple volume measurements of brain tumors in dogs. Equivocal results for interoperator variability may have been due to method variance or inadequate preliminary training. Additional studies are needed to evaluate the suitability of planimetry for assessing response to treatment.
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AJVR • Vol 77 • No. 5 • May 2016 471
High-grade glial tumors are one of the most preva-
lent primary brain tumors in dogs for which the
prognosis is grave. In the United Kingdom, the inci-
dence of intracranial neoplasia in dogs is approxi-
mately 20 cases/10,000 dogs/y.1 Median survival times
for affected dogs range from 2 to 3 months, despite
the use of novel and aggressive treatments.2,3 In hu-
mans, a high correlation exists between the amount of
tumor that remains after resection and rate of tumor
recurrence, confirming that advanced imaging can be
a valuable prognostic tool.4 The incidence of primary
brain tumors is reportedly greater in dogs than in hu-
mans, so many subjects are potentially available for
preclinical and clinical trials to assess effects of novel
experimental treatments in dogs. Additionally, in terms
of disease-free interval, progression of neoplasms in
dogs occurs at a rate 4.6 times as fast as that in hu-
Comparison of visual metric and planimetry methods
for brain tumor measurement in dogs
Chris B. Thomson dvm
Kevin H. Haynes dvm
G. Elizabeth Pluhar dvm, phd
Received April 28, 2015.
Accepted July 17, 2015.
From the Department of Veterinary Clinical Sciences,
University of Minnesota, Saint Paul, MN 55108. Dr.
Thomson’s present address is School of Veterinary
Medicine, University of Wisconsin, Madison, WI 53706.
Dr. Haynes’ present address is VCA West Los Angeles
Animal Hospital, 1900 S Sepulveda Blvd, Los Angeles, CA
Address correspondence to Dr. Pluhar (pluha006@
To compare the orthogonal diameter (visual metric) method against a manual
perimeter tracing (planimetry) method to measure volume of brain tumors in
dogs by use of MRI scans.
22 sets of MRI brain scans pertaining to 22 client-owned dogs with histologi-
cally confirmed glioma.
MRI scans were reviewed by 2 operators, and scans revealing tumors with
a degree of gadolinium enhancement that allowed discrimination between
tumor tissue and healthy parenchyma were used. Each operator calculated tu-
mor volume for each set of scans twice by use of visual metric and planimetry
methods. Inter- and intraoperator variability were assessed by calculation of
an agreement index (AI).
Mean ± SD intraoperator AIs were 0.79 ± 0.24 for the visual metric method
and 0.89 ± 0.17 for the planimetry method. Intraoperator variability for both
operators was significantly less when the planimetry method was used than
when the visual metric method was used. No significant differences were
identified in mean interoperator AI between visual metric (0.68 ± 0.28) and
planimetry (0.67 ± 0.31) methods.
The lower intraoperator variability achieved with the planimetry versus visual
metric method should result in more precise volume assessments when the
same operator performs multiple volume measurements of brain tumors in
dogs. Equivocal results for interoperator variability may have been due to
method variance or inadequate preliminary training. Additional studies are
needed to evaluate the suitability of planimetry for assessing response to
treatment. (Am J Vet Res 2016;77:471–477)
mans, creating the potential to more rapidly advance
Antemortem quantification of lesion size via CT
or MRI is commonly performed to assess response
to treatment in experimental and clinical studies. Se-
rial gadolinium-enhanced MRI and clinical evaluation
are important methods used in human brain tumor
research to monitor therapeutic efficacy and progres-
sion-free survival times. Historically, the visual metric
method involving Macdonald criteria6 has been used,
by which the product of the 2 greatest orthogonal
diameters is calculated to estimate brain tumor size.
However, technological advances have resulted in
new software that allows more precise measurements.
Such advances include visual tracing of the tumor
perimeter (planimetry method)7,8; computer-assist-
ed, threshold-based methods8,9; and fully automated,
computer facilitated methods.10–12 Since the origi-
nal Macdonald criteria were developed, new criteria
have been proposed to assess therapeutic responses
in both human and veterinary neuro-oncology pa-
AI Agreement index
WHO World Health Organization
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472 AJVR • Vol 77 • No. 5 • May 2016
tients. For brain tumor evaluation in human medicine,
these include updated Macdonald criteria,13 response
evaluation criteria in solid tumors,14 and response as-
sessment in neuro-oncology.15 Recently, criteria were
proposed for assessment of veterinary neuro-oncol-
ogy patients, referred to as response assessment in
veterinary neuro-oncology.16 Criteria for human and
veterinary assessment are largely based on diameter
measurements in 2 or 3 dimensions.
The original Macdonald criteria, developed in
1990, involved use of the largest cross-sectional diam-
eter in a single plane on an MRI scan, multiplied by the
perpendicular diameter in the same plane to estimate
the size of brain tumors. These criteria were devel-
oped to assess response to various treatments on the
basis of MRI findings and clinical signs to designate
complete or partial response, stable disease, or pro-
gression, but they also provided a foundation for tu-
mor volume assessment. The Macdonald criteria were
largely developed in response to the WHO initiative
to standardize the reporting of patient responses to
various cancer treatments. Although tumor volumes
in dogs may be estimated from MRI scans through sim-
ilar methods, the authors are unaware of any studies
conducted to compare and validate different volumet-
ric quantification techniques for glioma in dogs. Veteri-
nary researchers and clinicians are now treating dogs
with glioma by surgical resection and other therapeu-
tic modalities and need an accurate and reproducible
method to measure response to treatment.
The purpose of the retrospective study reported
here was to assess accuracy and reproducibility of 2
protocols to measure tumor volume in dogs by use
of MRI data. The optimal method would involve com-
puter software that was user-friendly, widely available
to veterinarians, and relatively cost effective. It would
also allow an individual with the skill and knowledge
of a technologist to calculate tumor volume in a re-
peatable manner that was operator independent. Our
null hypothesis was that there would be no significant
differences in interoperator and intraoperator reliabil-
ity between the planimetry method and visual metric
method for estimation of brain tumor volume in dogs.
Materials and Methods
A total of 66 image series from 22 sets of brain
MRI scans were included in the study. Scans pertained
to 22 client-owned dogs with histologically confirmed
high-grade glioma. Images were acquired by several re-
ferral institutions that had MRI units of various magnet
strengths, ranging between 1.0 and 3.0 T. All dogs had
brain tumors that yielded some degree of contrast en-
hancement after gadolinium administration at a dose
of 1 mL/4.45 kg. All measurements were performed
on T1-weighted postgadolinium images in 3 anatomic
planes (axial, sagittal, and coronal). All dogs had un-
dergone surgical debulking of solitary primary brain
tumors, and tissue specimens from those tumors were
histologically evaluated at the University of Minneso-
ta Masonic Cancer Center by pathologists who were
board-certified by the American College of Veterinary
Volumetric measurements
Two operators, one experienced in reading
MRI scans (KHH) and another with no previous ex-
perience reading MRI scans (CBT), independently
evaluated each MRI scan 4 times, performing 2 mea-
surements for each of the 2 methods (Figure 1). To
decrease familiarity or recognition of specific tumors,
MRI studies in the different planes were randomized
between successive measurement events. The 2 opera-
tors were selected on the basis of their availability for
the time commitment involved in these evaluations
and their general lack of relevant diagnostic expertise,
which could be expected in intended future users. Pri-
or to performing volumetric calculations for the study,
operators participated in a brief instructional session
about the software used to perform the 2 volumetric
methods and practice sessions involving each method
and sample MRI scans. In addition, a veterinary sur-
geon that had 10 years of experience specializing in
the treatment of dogs with brain tumors made mea-
surements with both methods to serve as a reference
standard for comparisons. The imaging softwarea used
to obtain measurements was chosen on the basis of
affordability, technical simplicity, and availability.
The visual metric method consisted of identifying
and marking the longest diameter of the gadolinium-
enhanced portion of the tumor mass by use of digital
calipers within the designated software on each im-
age slice and subsequently identifying and marking
the orthogonal diameter of the mass (Figure 2).3 The
2 diameters were used to calculate an area for every
slice in which tumor could be identified by use of the
following formula:
Ellipsoid area = 0.5d1 X 0.5d2 X π
where d1 and d2 are orthogonal diameters. The sum of
the area measurements, multiplied by slice thickness
and intersection gap, was used to determine the vol-
ume of each tumor in each of the 3 anatomic planes.
The planimetry method consisted of manually
tracing and segmenting the gadolinium-enhanced
portion of the tumor mass on each individual slice by
use of the designated software. The software automati-
cally calculated the area from the traced perimeter.
Consistent with the visual metric method, area mea-
surements were summed and multiplied by the slice
thickness and intersection gap and the volume of
each tumor was determined in each of the 3 anatomic
planes. Volumes calculated on the basis of each meth-
od were used for statistical analysis.
Statistical analysis
Agreement indices were calculated to assess reli-
ability of each method within and between operators
by use of the following equation8:
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AJVR • Vol 77 • No. 5 • May 2016 473
AI = 1 – |xa – xb|/([ xa + xb]/2)
where xa and xb represent different sets of
As the AI approaches 1, the 2 compared vol-
ume measurements are more similar and therefore
more reliable. Intraoperator reliability was defined
as degree of agreement, or similarity, between 2
volume calculations made by the same operator for
the same tumor in an individual plane. For calcula-
tion of intraoperator AI, xa was the first calculated
volume and xb was the second calculated volume
by the same operator for the same method for each
tumor in 1 plane. Interoperator reliability was de-
fined as the agreement between operators in their
volume calculation for the same tumor in an individ-
ual plane. Because each operator calculated 2 vol-
umes for each and every tumor with both methods
in each plane, the mean of the 2 volumes was used
for interoperator comparisons. For the interopera-
tor AI, xa was the mean of the 2 calculated volumes
for the first operator and xb was the mean of the 2
calculated volumes for the second operator by use
of the same method for the same tumor.
Because of the wide range in tumor sizes, raw
data from the volume calculations were logarithmi-
cally (base 10) transformed in an attempt to normalize
the values. For intraoperator AI comparisons, a mixed
ANOVA model was fit by use of statistical software,b
with dog included as a block effect. For interoperator
AI, a similar mixed ANOVA model was fit but without
operator as a variable because the response was not
unique to each operator but to the AI between the
Figure 1—Representative T1-weighted axial MRI scans ob-
tained after gadolinium administration to a dog with glio-
blastoma multiforme showing contrast enhancement of the
tumor (A), tracing of the same scan by use of imaging soft-
ware for area calculation via the planimetry method (B), and
diameter markings made on the same scan via the visual
metric method (C). Tumor area calculated by means of the
visual metric method was 1.52 cm2, and that calculated by
means of the planimetry method was 1.15 cm2.
Figure 2—Axial MRI scan of a dog with a glioblastoma multi-
forme showing the longest orthogonal diameters (thick white
lines) and planimetric tracing (green line) of the tumor and
graphic representation of the inherent overestimation of tumor
volume associated with the diameter method (thin white lines).
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474 AJVR • Vol 77 • No. 5 • May 2016
For each model, terms were tested for significance
with type II tests; additionally, least squares means
were computed to estimate the mean value for each
level and compared via pairwise comparisons. The
Tukey honest significant difference test was used for
variables with > 2 categories, such as view and meth-
od. Values of P < 0.05 were considered significant.
All but 1 tumor was classified as grade III or IV
on the basis of WHO criteria and consisted of glioblas-
toma multiforme (n = 11), anaplastic astrocytoma (7),
anaplastic oligodendroglioma (3), and primitive neu-
roectodermal tumor (1). One tumor was classified as
a ganglioglioma, which in humans would be classified
as a WHO grade I tumor but in dogs has unknown bio-
logical behavior.
A total of 528 volume measurements were made
from the MRI scans (Figure 3). Tumor volumes ranged
from 6.61 to 252.21 mm3, with mean and median vol-
umes of 62.80 mm3 and 42.71 mm3, respectively. Esti-
mated least squares mean (SE) logarithmic values for tu-
mor volume were 1.61 (0.07) and 1.69 (0.07) for each
of the 2 inexperienced operators; 1.68 (0.07) and 1.61
(0.07) for the visual metric and planimetry methods, re-
spectively; and 1.66 (0.07), 1.63 (0.07), and 1.66 (0.07)
for the axial, coronal, and sagittal planes, respectively.
Mean difference in logarithmic volumes between the
2 operators was 0.08, representing a mean difference
in tumor size of 18% (P < 0.001). Volumes measured
by 1 inexperienced operator were on average smaller,
regardless of method or plane used, than those made
by the other inexperienced operator. Mean difference
in volumes between the 2 methods was 0.07, repre-
senting a mean difference in size of 16% (P < 0.001).
Volume calculations made with the planimetry method
were smaller than those made with the visual metric
method, regardless of operator or plane. No significant
differences were identified in volume measurements
among imaging planes.
Agreement indices used in assessments of intra-
operator agreement were graphically plotted (Figure
4). In these assessments, one inexperi-
enced operator had a median AI of 0.94,
whereas the other had a median AI of
0.89, indicating that the first operator’s
measurements were more precise (P <
0.001). The visual metric method had a
median AI of 0.89 (mean ± SD, 0.79 ±
0.24), and the planimetry method had a
median AI of 0.94 (0.89 ± 0.17), indicat-
ing significant (P < 0.001) differences
between the 2 methods, with the pla-
nimetry method having less variability.
There were no significant differences
among planes.
Agreement indices used in assess-
ments of interoperator agreement
were graphically plotted (Figure 5).
In these assessments, the visual metric
method had a median AI of 0.77 (mean
± SD, 0.68 ± 0.28) and the planimetry
method had a median AI of 0.74 (0.67 ±
0.31). These median values did not dif-
fer significantly. Mean and median inter-
operator AIs were lower than mean and
median intraoperator AIs. Median AIs
for each plane were 0.63 for axial, 0.73
for coronal, and 0.66 for sagittal. These
values differed significantly (P = 0.01)
in that greater variability was identified
between measurements made by use of
MRI scans obtained in the coronal and
axial planes.
Results of the present study indi-
cated that the planimetry method of
measuring brain tumor volume in dogs
by use of MRI scans was more reliable
Figure 3—Logarithmically (base 10) transformed volumetric data for gliomas in 22
dogs (patients A through V) as measured in axial (A and B), coronal (C and D), and
sagittal (E and F) planes by 2 inexperienced operators (squares and triangles) and
1 highly trained operator (circles) by use of the visual metric method (A, C, and E)
and planimetry method (B, D, and F). Clustering of data points represents similarity
among volume calculations; tighter clusters represent data with less variability. For
example, the data set for the visual metric method within the sagittal plane (panel
E) appears to have greater variability than that attained with the planimetry method.
On the other hand, minimal variability is evident among the data points for the pla-
nimetry method in the coronal plane (panel D). ID = Identification.
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AJVR • Vol 77 • No. 5 • May 2016 475
than the visual metric method for repeated measure-
ments, particularly when made by the same individ-
ual. Comparison of measurements between 2 fairly
inexperienced operators revealed that the methods
were equivalent in terms of reliability. Mean AIs were
consistent with calculations of operator variability in
another study.7 Differences in tumor volume calcula-
tion between operators that led to greater variability
were likely attributable to the inability
to precisely define tumor borders.
Both operators in the present study
reported that measurements were fast-
er and easier to perform when the pla-
nimetry method was used. When the
visual metric method was used, it took
more time to successfully find the lon-
gest diameter, the longest orthogonal
diameter, and the angle measurements
to ensure the 2 diameters were perpen-
dicular than it did to trace the gadolin-
ium-enhanced perimeter with the pla-
nimetry method. Theoretically, tracing
the tumor would provide a more reli-
able estimation of absolute tumor vol-
ume because delineating the orthogo-
nal diameter resulted in ellipse-shaped
area in each segment, whereas tracing
allowed more flexibility in perimeter
measurement (Figure 2). This inher-
ent limitation of the original method
described by Macdonald to accurately
measure irregularly shaped tumors has
been described in human medical lit-
erature.14 The planimetry method was
designed to mitigate this shortcoming
through a more adaptable determinant
of tumor area per slice. Data reported
here for dogs suggested that use of the
visual metric method resulted in a con-
siderable overestimation of tumor vol-
ume because of failure to account for
perimeter voids that did not occur with
the planimetry method.
The present study revealed no sig-
nificant differences in the volumetric
data acquired from 3 MRI planes by
the same operator. However, significant
differences were identified between
operators. Volume calculations made
from the images in the coronal plane
had the lowest variability. The mag-
nitude of variability was significantly
different between volumes measured
in the coronal versus axial planes. This
information would be beneficial when
a single plane is used for volume cal-
culations. The original Macdonald cri-
teria involved estimation of tumor size
by measuring area from the single MRI
slice with the greatest tumor diameter.
A study17 involving humans with malignant glioma re-
vealed that calculation of tumor volume rather than
area from a single image is more sensitive and specific
to changes in tumor size over time.
In the study reported here, all measurements
were made on T1-weighted, gadolinium-enhanced
images that revealed certain characteristics of high-
grade glioma, including a profound mass effect, peritu-
Figure 4—Intraoperator AIs for repeated (twice) calculations of glioma volume in
each of 22 dogs made by one operator (A and B) and another operator (C and D)
by means of the visual metric method (A and C) and the planimetry method (B and
D). Dashed line represents median AI, and solid line represents mean AI.
Figure 5—Interoperator AIs for single calculations of glioma volume in each of
22 dogs by 2 operators by means of the visual metric method (A) and planimetry
method (B). See Figure 4 for remainder of key.
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476 AJVR • Vol 77 • No. 5 • May 2016
moral edema, ring enhancement, and central necrotic
area.3,18,19 Although the visibility of many high-grade
gliomas is enhanced with contrast techniques, which
makes it easier to estimate tumor borders, this charac-
teristic is not universal.3 T2-weighted images may be
useful for measuring volume of tumors that lack en-
hancement when fluid-attenuated inversion recovery
sequence images are used to differentiate peritumoral
edema from tumor during segmentation. This is also
important because contrast enhancement can be af-
fected by treatment with antiangiogenic or corticoste-
roid drugs and with certain radiographic techniques
without true changes to the underlying tumor size.15
We used pretreatment MRI scans in the present study
to minimize the effects associated with tumor pseu-
doprogression or hyper- or hypoenhancement associ-
ated with other treatments or procedures.
Many factors need to be taken into account when
evaluating treatment efficacy in patients with brain
tumors. Neurocognitive function, resolution of clini-
cal signs, quality of life, and progression-free survival
time are variables currently used to assess response
to treatment. New methods need to be developed to
provide a more objective assessment than is currently
possible. In the present study, only pretreatment tu-
mor volumes were measured; however, serial evalua-
tions are needed to assess patient response to treat-
ment, tumor volume after resection, and progressive
changes in tumor volume. The Macdonald criteria and
new criteria to assess response to novel treatments
by veterinary neuro-oncology patients over time have
not been evaluated, and research is warranted into the
applicability of these criteria to gliomas in dogs.
A limitation of the present study was that, except
for the highly trained operator whose results were
used as the reference standard, only 2 inexperienced
operators calculated the tumor volumes. Use of more
operators with varied experience would minimize
study error attributable to interindividual variance.
However, use of a homogenous, highly-trained group
of operators does not necessarily lead to a decrease
in interoperator variance.20 This supposition was sup-
ported by the scatter plots in the present study in
which values calculated by the 2 inexperienced op-
erators were plotted along with those calculated by
the highly trained operator (Figure 3). More training
and practice trials may allow each operator to more
precisely define or recognize diseased regions on MRI
scans. We found that the lowest variation among vol-
ume calculations was achieved when the same indi-
vidual made the measurements, which is an important
factor to consider when assessing serially acquired
MRI scans.
Inherent limitations of visual metric and planim-
etry methods include the use of stacked slices for
volume determination. Volume calculated by sum-
mation of areas measured from stacked slices may
vary from the absolute tumor volume. Each slice as-
sumes a slab thickness that may not be consistent
throughout the given slice. Additionally, potential
exists for over- and underestimation of volume, de-
pending on the extent of inclusion or exclusion of
the end cap volumes.4 In the present study, images
had been acquired at several institutions with MRI
units of differing strength, ranging from 1.0 to 3.0 T.
This variability may have affected image evaluation
but in the authors’ opinion, appropriately reflected
how the technique would be used in clinical prac-
tice or research.
Accurate assessment of treatment response is im-
portant to tailor treatment to individual patients, facili-
tate communications about tumor size, perform clini-
cal trials, and allow reliable comparisons of treatment
results. The planimetry method used in the present
study offers an alternative method to the previously
described standard for measuring tumor volume. Con-
tinual assessment of and improvement in the reliabil-
ity of MRI measurements will allow this modality to be
used as end point verification for research and will aid
in prognosis determination and treatment planning
for dogs with brain tumors.
Supported in part by the American Humane Association.
The authors thank Dr. Aaron Rendahl for performing the sta-
tistical analyses.
a. OsiriX DICOM software, version 5.6, Pixmeo Sarl, Geneva,
b. R Core Team (2013), R: a language and environment for statisti-
cal computing, Foundation for Statistical Computing, Vienna,
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... [3][4][5] Several methods to quantify solid tumor size on diagnostic imaging studies are described including the Response Evaluation Criteria in Solid Tumors (RECIST), which utilizes a 1-dimensional (1D) linear measurement of the longest tumor diameter; the MacDonald and Response Assessment in Veterinary Neuro-oncology (RAVNO) criteria, both of which measure tumor size using orthogonal 2-dimensional (2D) linear measurements; and several manual, semiautomated, or fully computer automated volumetric methods. 1,2,6 Applying these methods in brain tumors, and particularly in gliomas, has been associated with numerous challenges associated with difficulties identifying distinct tumor borders, complex and irregular tumor geometries, and the requirement of conventional criteria to measure only the contrast-enhancing tumor burden. 1,2 There is greater interobserver variability associated with 2D linear compared to volumetric measurement methods in dogs with glioma, but the implications of this variability on the assessment of therapeutic response have yet to be investigated. ...
... 1,2 There is greater interobserver variability associated with 2D linear compared to volumetric measurement methods in dogs with glioma, but the implications of this variability on the assessment of therapeutic response have yet to be investigated. 6 As not all gliomas in dogs demonstrate contrastenhancement, there is a need to further define and evaluate tumor measurement criteria based on T2W sequences, as have been utilized in clinical studies in dogs. [3][4][5] The goals of this study were to: (a) evaluate inter-and intraobserver reliability and rater efficiency for 1D, 2D, and volumetric methods of gli- ...
... There are also relatively little data with respect to the reproducibility of measurement methods within and across observers. 6 Our results indicate that experienced raters can perform linear and volumetric methods of glioma quantification efficiently, each of these measurement methods are sufficiently reliable to be applied in the clinical setting, and that head-to-head correlations between the different linear (1D vs 2D) and volumetric measurement techniques (CEV vs TTV) were excellent and good, respectively. ...
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Background: Brain tumor therapeutic responses can be quantified from magnetic resonance images (MRI) using 1- (1D) and 2-dimensional (2D) linear and volumetric methods, but few studies in dogs compare these techniques. Hypotheses: Linear methods will be obtained faster, but have less agreement than volumetric measurements. Therapeutic response agreement will be highest with the total T2W tumor volumetric (TTV) method. Therapeutic response at 6-weeks will correlate with overall survival (OS). Animals: Forty-six dogs with intracranial gliomas. Methods: Prospective study. Three raters measured tumors using 1D and 2D linear, TTV, and contrast-enhancing volumetric (CEV) techniques on 143 brain MRI to determine agreement between methods, define therapeutic responses, and assess relations with OS. Results: Raters performed 1D the fastest (2.9 ± 0.57 minutes) and CEV slowest (17.8 ± 6.2 minutes). Inter- and intraobserver agreements were excellent (intraclass correlations ≥.91) across methods. Correlations between linear (1D vs 2D; ρ > .91) and volumetric (TTV vs CEV; ρ > .73) methods were stronger than linear to volumetric comparisons (ρ range, .26-.59). Incorporating clinical and imaging data resulted in fewer discordant therapeutic responses across methods. Dogs having partial tumor responses at 6 weeks had a lower death hazard than dogs with stable or progressive disease when assessed using 2D, CEV, and TTV (hazard ratio 2.1; 95% confidence interval, 1.22-3.63; P=.008). Conclusions and Clinical Importance: One-dimensional, 2D, CEV, and TTV are comparable for determining therapeutic response. Given the simplicity, universal applicability, and superior performance of the TTV, we recommend its use to standardize glioma therapeutic response criteria.
... These tumors are also categorized by grade on the basis of histologic assessment and biological characteristics. In a recent study, 3 high OBJECTIVE To assess the relationship between preoperative volume of primary intracranial gliomas in dogs as determined via MRI and survival time after surgical debulking and adjunctive immunotherapy. ...
... Values for tumor volume as a proportion of total calvarial volume were determined in both the axial and sagittal planes by the primary author, who used a previously described planimetry technique. 3 For each dog, tumor area was traced slice by slice in both axial and sagittal planes. The sum of area measures was multiplied by the sum of slice thickness and gap in each plane to yield tumor volume. ...
OBJECTIVE To assess the relationship between preoperative volume of primary intracranial gliomas in dogs as determined via MRI and survival time after surgical debulking and adjunctive immunotherapy. DESIGN Retrospective cohort study. ANIMALS 47 client-owned dogs enrolled in clinical trials regarding glioma treatments. PROCEDURES Medical records of all dogs undergoing craniotomy at the University of Minnesota Veterinary Medicine Center with histologically confirmed glioma between 2008 and 2015 were retrospectively reviewed, and outcome data were collected. Preoperative T2-weighted or post–gadolinium administration T1-weighted MRI scans, performed at several referral institutions with scanners of magnet strengths ranging from 0.5 to 3.0 T, were used to measure tumor volumes as a percentage of total calvarial volume. Data were analyzed to assess the effect of each 2% fraction of tumor volume on median survival time (MST) after surgery and adjuvant treatment. RESULTS Tumor volumes ranged from 0.5% to 12.2% of total intracranial volume. Overall MST was 185 days (range, 2 to 802 days). No association was identified between preoperative tumor volume and MST. Only 3 (6%) dogs had low-grade tumors that had relatively small volumes, measuring 1.4%, 2.1%, and 4.3% of total calvarial volume. The MST for these 3 dogs (727 days) was longer than that for high-grade tumors (174 days); however, owing to the low number of dogs with low-grade tumors, no statistical comparison was performed. CONCLUSIONS AND CLINICAL RELEVANCE Preoperative tumor volume determined via MRI was neither associated with nor predictive of outcome following surgery and adjunctive treatment for dogs with glioma. Tumor grade was predictive of outcome, but unlike tumor volume that was measured with MRI, invasive biopsy was necessary to definitively diagnose tumor grade.
... Peritumoral edema (PE) as evidenced by peritumoral hyperintensity in T2W/FLAIR images was evaluated (Fig. 4). MV was calculated by one of the authors (S.M.) using a previously described planimetric method [21]. The perimeter of the mass was traced manually in T1W images (all slices) acquired postcontrast in the transverse plane with a dedicated software (Osirix Dicom Viewer, Pixmeo SARL, Bernex, Switzerland) (Fig. 5). ...
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The incidence of brain herniation (BH) in association with intracranial meningioma (ICM) in dogs and cats is poorly described. The aim of this study was to evaluate the rate and type of brain herniations in client-owned dogs and cats with ICMs and to determine the meningioma volume (MV) relative to cranial cavity volume (CCV). A retrospective magnetic resonance imaging (MRI) analysis study of 24 cats and 45 dogs with ICMs was conducted to ascertain the presence and characteristics of BH. MV and CCV were measured and their ratio was calculated for each animal. Correlations of MV/CCV with independent variables were analyzed. BH was encountered in 24/24 cats (100%) and 30/45 dogs (66.7%) with ICMs. In cats, the most frequent presentation was foramenal herniation (FMH; 23/24, 95.8%), followed by caudotentorial (CTH; 21/24, 87.5%) and subfalcine (SH; 18/24, 75.0%) herniation. In dogs, the most frequent presentation was SH (28/45; 62.2%), followed by CTH (9/45; 20%) and FMH (2/45; 4.4%). Relative to dogs, cats with ICM had greater incidences of FMH (P<0.001) and CTH (P<0.001). Mean MV/CCV ratio was higher in cats (0.098) than in dogs (0.038; P<0.001). The most common clinical sign of ICM was altered behavior in cats (43%, P<0.01) and seizures in dogs (74.4%, P<0.001). In conclusion, cats were found to be more likely than dogs to present FMH and CTH, with a proportionally greater neoplasia volume.
... This effect occurs in human glioblastoma multiforme, suggesting 3D measurements to be preferred for accurate response assessment after radiotherapy. 30,31 Furthermore, 2 dogs with suspected glioma had to be excluded from comparison of 2D and 3D measurements, because of a lack of contrast uptake of the brain lesion. MacDonald's response criteria were published in 1990 for assessment of CT studies limiting their use in MRI, which has since progressed to be modality of choice in brain diagnostics. ...
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Background: Use of strongly hypofractionated radiation treatments in dogs with intracranial neoplasia did not improve outcomes and yielded increased rates of toxicosis. Objectives: To evaluate safety and efficacy of a new, moderately hypofractionated radiation protocol of 10 × 4 Gy compared to a standard protocol. Animals: Convenience sample of 56 client‐owned dogs with primary symptomatic brain tumors. Methods: Retrospective observational study. Twenty‐six dogs were assigned to the control standard protocol of 20 × 2.5 Gy (group A) and 30 dogs to the new protocol of 10 × 4 Gy (group B), assigned on owners' informed consent. Statistical analysis was conducted under the “as treated” regime, using Kaplan‐Meier and Cox‐regression analysis. Treatment was delivered with technically advanced image‐guided radiation therapy. The 2 treatment groups were compared in terms of outcome and signs of toxicosis. Results: Overall progression‐free interval (PFI) and overall survival (OS) time were favorable, with 663 (95%CI: 497;828) and 637 (95%CI: 403;870) days, respectively. We found no significant difference between the two groups: PFI for dogs in group A vs B was 608 (95%CI: 437;779) days and mean (median not reached) 863 (95%CI: 644;1083) days, respectively (P = .89), and OS for dogs in group A vs B 610 (95%CI: 404;816) and mean (median not reached) 796 (95%CI: 586;1007) days (P = .83). Conclusion and Clinical Importance: In conclusion, 10 × 4 Gy is a safe and efficient protocol for treatment of primary intracranial neoplasia and future dose escalation can be considered.
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Background: Intracranial neoplasia is relatively common in dogs and stereotactic radiotherapy, surgical debulking, or both, are the most successful treatment approaches. A key component of treatment planning involves delineating tumor margin on magnetic resonance imaging (MRI) examinations. How MRI signal intensity alterations relate to histological tumor margins is unknown. Objectives: Directly compare histological brain sections to MRI sequence images and determine which sequence alteration best correlates with tumor margins. Animals: Five dogs with glioma, 4 dogs with histiocytic sarcoma, and 3 dogs with meningioma. Methods: Retrospective cohort study. Histological brain sections were registered to in vivo MRI scan images obtained within 7 days of necropsy. Margins of signal intensity alterations (T2-weighted, fluid-attenuating inversion recovery [FLAIR], T1-weighted and contrast enhancement) were compared directly to solid tumor and surgical margins identified on histology. Jacquard similarity metrics (JSM) and cross-sectional areas were calculated. Results: In glioma cases, margins drawn around T2-weighted hyperintensity were most similar to surgical margins (JSM, 0.66 ± 0.17) when compared to other sequences. In both meningioma (JSM, 0.57 ± 0.21) and histiocytic sarcoma (JSM, 0.75 ± 0.11) margins of contrast enhancement were most similar to surgical margins. Conclusions and clinical importance: Signal intensities correspond to tumor margins for different tumor types and facilitate surgical and radiation therapy planning using MRI images.
Standardized veterinary neuroimaging response assessment methods for brain tumours are lacking. Consequently, a response assessment in veterinary neuro-oncology (RAVNO) system which uses the sum product of orthogonal lesion diameters on 1-image section with the largest tumour area, has recently been proposed. In this retrospective study, 22 pre-treatment magnetic resonance imaging (MRI) studies from 18 dogs and four cats with suspected intracranial neoplasia were compared by a single observer to 32 post-treatment MRIs using the RAVNO system and two volumetric methods based on tumour margin or area delineation with HOROS and 3D Slicer software, respectively. Intra-observer variability was low, with no statistically significant differences in agreement index between methods (mean AI ± SD, 0.91 ± 0.06 for RAVNO; 0.86 ± 0.08 for HOROS; and 0.91 ± 0.05 for 3D slicer), indicating good reproducibility. Response assessments consisting of complete or partial responses, and stable or progressive disease, agreed in 23 out of 32 (72%) MRI evaluations using the three methods. The RAVNO system failed to identify changes in mass burden detected with volumetric methods in 6 cases. 3D Slicer differed from the other two methods in 3 cases involving cysts or necrotic tissue as it allowed for more accurate exclusion of these structures. The volumetric response assessment methods were more precise in determining changes in absolute tumour burden than RAVNO but were more time-consuming to use. Based on observed agreement between methods, low intra-observer variability, and decreased time constraint, RAVNO might be a suitable response assessment method for the clinical setting.
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Object: Robust methodology that allows objective, automated, and observer-independent measurements of brain tumor volume, especially after resection, is lacking. Thus, determination of tumor response and progression in neurooncology is unreliable. The objective of this study was to determine if a semi-automated volumetric method for quantifying enhancing tissue would perform with high reproducibility and low interobserver variability. Methods: Fifty-seven MR images from 13 patients with glioblastoma were assessed using our method, by 2 neuroradiologists, 1 neurosurgeon, 1 neurosurgical resident, 1 nurse practitioner, and 1 medical student. The 2 neuroradiologists also performed traditional 1-dimensional (1D) and 2-dimensional (2D) measurements. Intraclass correlation coefficients (ICCs) assessed interobserver variability between measurements. Radiological response was determined using Response Evaluation Criteria In Solid Tumors (RECIST) guidelines and Macdonald criteria. Kappa statistics described interobserver variability of volumetric radiological response determinations. Results: There was strong agreement for 1D (RECIST) and 2D (Macdonald) measurements between neuroradiologists (ICC = 0.42 and 0.61, respectively), but the agreement using the authors' novel automated approach was significantly stronger (ICC = 0.97). The volumetric method had the strongest agreement with regard to radiological response (κ = 0.96) when compared with 2D (κ = 0.54) or 1D (κ = 0.46) methods. Despite diverse levels of experience of the users of the volumetric method, measurements using the volumetric program remained remarkably consistent in all users (0.94). Conclusions: Interobserver variability using this new semi-automated method is less than the variability with traditional methods of tumor measurement. This new method is objective, quick, and highly reproducible among operators with varying levels of expertise. This approach should be further evaluated as a potential standard for response assessment based on contrast enhancement in brain tumors.
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Early and accurate prediction of response to cancer treatment through imaging criteria is particularly important in rapidly progressive malignancies such as Glioblastoma Multiforme (GBM). We sought to assess the predictive value of structural imaging response criteria one month after concurrent chemotherapy and radiotherapy (RT) in patients with GBM. Thirty patients were enrolled from 2005 to 2007 (median follow-up 22 months). Tumor volumes were delineated at the boundary of abnormal contrast enhancement on T1-weighted images prior to and 1 month after RT. Clinical Progression [CP] occurred when clinical and/or radiological events led to a change in chemotherapy management. Early Radiologic Progression [ERP] was defined as the qualitative interpretation of radiological progression one month post-RT. Patients with ERP were determined pseudoprogressors if clinically stable for ≥6 months. Receiver-operator characteristics were calculated for RECIST and MacDonald criteria, along with alternative thresholds against 1 year CP-free survival and 2 year overall survival (OS). 13 patients (52%) were found to have ERP, of whom 5 (38.5%) were pseudoprogressors. Patients with ERP had a lower median OS (11.2 mo) than those without (not reached) (p < 0.001). True progressors fared worse than pseudoprogressors (median survival 7.2 mo vs. 19.0 mo, p < 0.001). Volume thresholds performed slightly better compared to area and diameter thresholds in ROC analysis. Responses of > 25% in volume or > 15% in area were most predictive of OS. We show that while a subjective interpretation of early radiological progression from baseline is generally associated with poor outcome, true progressors cannot be distinguished from pseudoprogressors. In contrast, the magnitude of early imaging volumetric response may be a predictive and quantitative metric of favorable outcome.
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Magnetic resonance imaging (MRI) was performed on 50 dogs with intracranial neoplasia. The following tumor features were assessed: axial origin, location, shape, growth pattern, MRI signal intensity, evidence for edema, and paramagnetic contrast enhancement. Histologic diagnosis included 5 intracranially invading nasal tumors, 7 pituitary tumors, 22 meningiomas, 6 choroid plexus tumors, 7 astrocytomas, 1 ependymoma, and 2 oligodendrogliomas. Axial origin, site, shape, and growth pattern were important diagnostic characteristics for tumor type. Signal intensity and contrast enhancement pattern allowed further differentiation. Characteristic MRI features that facilitate diagnosis and prognosis were identified. Accurate diagnosis of tumor type based on these features was not always possible because of similarities in MRI appearance for some tumors. Tissue biopsy remains necessary for definitive diagnosis of intracranial tumors.
The evaluation of therapeutic response using cross-sectional imaging techniques, particularly gadolinium-enhanced MRI, is an integral part of the clinical management of brain tumors in veterinary patients. Spontaneous canine brain tumors are increasingly recognized and utilized as a translational model for the study of human brain tumors. However, no standardized neuroimaging response assessment criteria have been formulated for use in veterinary clinical trials. Previous studies have found that the pathophysiologic features inherent to brain tumors and the surrounding brain complicate the use of the response evaluation criteria in solid tumors (RECIST) assessment system. Objectives of this review are to describe strengths and limitations of published imaging-based brain tumor response criteria and propose a system for use in veterinary patients. The widely used human Macdonald and response assessment in neuro-oncology (RANO) criteria are reviewed and described as to how they can be applied to veterinary brain tumors. Discussion points will include current challenges associated with the interpretation of brain tumor therapeutic responses such as imaging pseudophenomena and treatment-induced necrosis, and how advancements in perfusion imaging, positron emission tomography, and magnetic resonance spectroscopy have shown promise in differentiating tumor progression from therapy-induced changes. Finally, although objective endpoints such as MR imaging and survival estimates will likely continue to comprise the foundations for outcome measures in veterinary brain tumor clinical trials, we propose that in order to provide a more relevant therapeutic response metric for veterinary patients, composite response systems should be formulated and validated that combine imaging and clinical assessment criteria.
The Response Assessment in Neuro-Oncology (RANO) Working Group is an international, multidisciplinary effort to develop new standardized response criteria for clinical trials in brain tumors. The RANO group identified knowledge gaps relating to the definitions of tumor response and progression after the use of surgical or surgically based treatments. To outline a proposal for new response and progression criteria for the assessment of the effects of surgery and surgically delivered therapies for patients with gliomas. The Surgery Working Group of RANO identified surgically related end-point evaluation problems that were not addressed in the original Macdonald criteria, performed an extensive literature review, and used a consensus-building process to develop recommendations for how to address these issues in the setting of clinical trials. Recommendations were formulated for surgically related issues, including imaging changes associated with surgical resection or surgically mediated adjuvant local therapies, the determination of progression in the setting where all enhancing tumor has been removed, and how new enhancement should be interpreted in the setting where local therapies that are known to produce nonspecific enhancement have been used. Additionally, the terminology used to describe the completeness of surgical resections has been recognized to be inconsistently applied to enhancing vs nonenhancing tumors, and a new set of descriptors is proposed. The RANO process is intended to produce end-point criteria for clinical trials that take into account the effects of prior and ongoing therapies. The RANO criteria will continue to evolve as new therapies and technologies are introduced into clinical trial and/or practice.
Bidimensional tumor measurements indicating a greater than 25% increase in tumor size are generally accepted as indicating tumor progression. We hypothesized that use of digital images and a homogeneous reader population would have lower interobserver variability than in previous studies. Eight board-certified radiologists measured tumor diameters in three planes in two consecutive MRI examinations of 22 patients with contrast-enhancing high-grade brain tumors. Products of tumor measurements were calculated, and determinations were made about tumor progression (> 25% increase in area). A variance components model was run on diameter products and the ratios of consecutive maximal diameter products. The variance components included patient examination effect, reader effect, and residual effect. Complete agreement was found among readers in 10 cases (45%), all indicating stable disease. In the other 12 cases, at least one reader considered progressive disease present. The variance components model showed variance due to readers was small, indicating only modest bias among readers. The residual variance component was large (0.038), indicating that repeated measurements on the same image likely are variable even for the same reader. This variability in measurement implies that repeated measurements by the typical reader have an inherent 14% false-positive rate in the diagnosis of progression of tumors that are stable. Our hypothesis was disproved. We found substantial interreader disagreement and indications that the very nature of the measurement method produces a high rate of false-positive readings of stable tumors. These findings should be considered in interpretation of images with this widely accepted criterion for brain tumor progression.
The evaluation of tumor size by neurodiagnostic imaging is an important tool in determining disease progression or treatment efficacy. Apparent tumor size on any single slice image is sensitive to tumor shape and slice orientation. Volumetric measurements which use multiple, stacked images attenuate that sensitivity and can provide insights into tumor architecture. Volumetric measurements were made of induced canine gliomas using three common MR imaging protocols and with and without a contrast agent. Comparisons of the volumes described by each technique are made.
The prognostic importance of tumor size was studied in 510 patients with malignant glioma (80% with glioblastoma multiforme) in the Valid Study Group of Study 80-01 of the Brain Tumor Study Group (now the Brain Tumor Cooperative Group [BTCG]). The endpoint was length of survival from randomization, which occurred within 3 weeks of definitive surgery. Following randomization, patients were scheduled to receive radiotherapy (RT) (6,020 cGy) during a 7-week period, along with continuing courses of chemotherapy. Computed tomographic (CT) scan information was available for 124 patients preoperatively, 300 patients postoperatively (preradiation), and 218 patients 9 weeks post-RT (+/- 3 weeks). Tumor size was determined as area (length x width) on the contrast-enhanced scan and survival was compared by log rank statistics. Preoperative tumor area was unrelated to survival (P = .48), but postoperative area was significantly prognostic (P less than .0001); the smaller the residual tumor, the longer the patient lived. Patients with a 75% or greater resection, as determined by measuring the difference between the preoperative and the postoperative scans, tended to have better survival, but the difference was not significant (P = .16). The post-RT area was strongly related to survival (P less than .00001). The percent change in area between the pre- and post-RT scans was also prognostic. Tumor size was of prognostic importance independent of the other known prognostic variables: age, Karnofsky performance score, and whether the tumor was glioblastoma or anaplastic astrocytoma. We conclude that the amount of tumor remaining after surgery is an important baseline variable at the start of RT, and that the tumor size 9 weeks following RT is also prognostic. Surgical resection is most important when it leaves the least amount of residual tumor.
On the initiative of the World Health Organization, two meetings on the Standardization of Reporting Results of Cancer Treatment have been held with representatives and members of several organizations. Recommendations have been developed for standardized approaches to the recording of baseline data relating to the patient, the tumor, laboratory and radiologic data, the reporting of treatment, grading of acute and subacute toxicity, reporting of response, recurrence and disease-free interval, and reporting results of therapy. These recommendations, already endorsed by a number of organizations, are proposed for international acceptance and use to make it possible for investigators to compare validly their results with those of others.