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Journal of Medical Imaging and Radiation Oncology 58 (2014) 18–24
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RADIOLO GY —O R I G I N AL A R T I C L E
Head and neck squamous cell cancer (stages III and IV)
induction chemotherapy assessment: Value of FDG volumetric
imaging parameters
Jielin Yu,1 Timothy Cooley,2 Minh-Tam Truong,3 Gustavo Mercier1 and Rathan M. Subramaniam1,3*
1
Department of Radiology, 2Medical Oncology, 3Radiation Oncology, Boston University School of Medicine, Boston, Massachusetts, USA
J Yu; T Cooley MD; M-T Truong MD;
G Mercier MD, PhD; RM Subramaniam MD,
PhD, MPH.
Correspondence
A/Prof. Rathan Subramaniam, Division of
Nuclear Medicine, Russel H Morgan
Department of Radiology and Radiology
Science, Johns Hopkins Medical Institutions,
601 N. Caroline Street/JHOC 3235, Baltimore
MD 21287, USA.
Email: [email protected]
*Present address: Russel H Morgan
Department of Radiology and Radiological
Sciences, Johns Hopkins Medical Institutions,
Baltimore, MD, USA.
Submitted 4 February 2013; accepted 30 April
2013.
doi:10.1111/1754-9485.12081
Abstract
Introduction: To evaluate whether the change in the metabolic tumour volume
(MTV) or total lesion glycolysis (TLG) of the primary tumour, before and after
induction chemotherapy, predicts outcome for patients with advanced head
and neck squamous cell cancer (SCC).
Methods: Twenty-eight patients with advanced (American Joint Committee on
Cancer stage III and IV) head and neck SCC who underwent positron emission
tomography (PET)/CT were included in this retrospective study. Primary
tumour MTV and TLG were measured using gradient and fixed percentage
threshold segmentations. Outcome endpoint was disease progression or mortality. Pearson correlation, Bland–Altman and receiver operator characteristic
analysis were performed.
Results: The Pearson’s correlation coefficients between percentage changes
(pre- and post-induction chemotherapy) from gradient MTV (MTVG) and the
38% SUVmax threshold MTV (MTV38) was 0.96 and between MTVG and the 50%
threshold MTV (MTV50) was 0.95 (P < 0.0001). The corresponding Pearson r
between TLGG and TLG38 was 0.94 and between TLGG and TLG50 was 0.96
(P < 0.0001). The least bias was 1.89% (standard deviation = 25.30%)
between the percentage changes of MTVG and MTV50. The areas under the
curve for predicting progression or mortality were 0.76 (P = 0.03) for MTVG
and 0.82 for TLGG (P = 0.009). Optimum cut points of a 42% reduction in
MTVG and a 55% reduction in the TLGG predict event-free survival with a
sensitivity of 62.5% and a specificity of 90% and a hazards ratio of 6.25.
Conclusion: A reduction in primary tumour MTV of at least 42% or in TLG of at
least 55% after induction chemotherapy may predict event-free survival in
patients with advanced head and neck SCC.
Key words: head and neck; PET/CT.
Introduction
Induction chemotherapy is an emerging treatment paradigm for treating inoperable locally advanced squamous
cell carcinomas of the head and neck.1 Induction chemotherapy followed by chemoradiotherapy is a form of
treatment intensification and is evolving. This may contribute to a better survival rate compared with chemoradiotherapy alone.2 Monitoring the response to induction
chemotherapy provides critical information that allows
physicians to triage to the best post-induction treatment.
18
Fluorodeoxyglucose positron emission tomography/
computed tomography (FDG PET/CT) has proven to be
clinically useful as a diagnostic, staging and therapy
planning tool.3–7 The role of FDG PET/CT in determining
the outcome of induction chemotherapy has been
explored. Previous studies indicate that PET/CT shows
a significant correlation with pathological response following induction and concurrent chemoradiotherapy
(CCRT).8 It has been shown to have the same efficacy as
endoscopy with biopsy for determining the tumour
volume after induction therapy.9
© 2013 The Royal Australian and New Zealand College of Radiologists
PET volumetric parameters and HNSCC
The purpose of this exploratory study is to evaluate
whether the change in the metabolic tumour volume
(MTV) and total lesion glycolysis (TLG) of the primary
tumour, before and after induction chemotherapy, predicts outcome of patients with locally advanced head and
neck cancer.
Methodology
Patients and study design
This is a single-institution retrospective study and was
approved by the Institutional Review Board. Informed
consent requirements were waived for this study. All 28
patients, with biopsy-proven head and neck squamous
cell carcinoma who underwent a FDG PET/CT at baseline
and post-induction chemotherapy from January 2010
to April 2011 in our institution, were included in the
study. All the patients were treated with induction
chemotherapy followed by CCRT. The induction chemotherapy regimen consisted of three cycles of Taxotere
(docetaxol), cisplatin and 5-fluorouricil (TPF), with minor
adjustments for toxicity and other complications. Postinduction therapy consisted of 6 to 7 weeks of CCRT,
with 69.96 Gy over 33 fractions.
PET/CT
All PET/CT studies were performed on a GE Discovery
STE 16 (General Electric, Milwaukee, WI, USA) PET/CT
scanner according to the institutional standard clinical
protocol. For all patients, a dedicated head and neck
protocol was instituted. Patients were scanned from skull
base to aortic arch with the arms down and then clavicle
to mid thigh with the arms up. The average patient blood
glucose level was 103 mg/dl (standard deviation (SD)
21 mg/dL). Patients were injected with an average of
11.3 mCi (SD 0.6 mCi) or 418.1 Mbq (SD 22.2 Mbq) of
18F-FDG and incubated for an average period of 65 min
(SD 7 min).
The dedicated head and neck imaging protocol consisted of two-dimensional PET scans obtained from the
skull base to the arch of the aorta with a 30-cm field of
view and 128 ¥ 128 matrix.10 The emission scan lasted
for 5 min per bed position. The remainder of the body
(down to the mid thighs) was imaged using a weightbased emission scan time per bed position. PET slice
thickness was 3.27 mm. Helical (16 detector) CT images
were obtained with a matrix of 512 ¥ 512. Beam collimation was 10 mm with a pitch of 0.984. Table speed
was 9.84 mm/rotation, and the slice thickness was
0.625 mm. KV of 120 and mAs of 440 were used. CT
images were reconstructed using a slice thickness of
3.75 mm every 3.27 mm. In addition, CT images were
reconstructed using a slice thickness of 1.25 mm every
1.25 mm in soft tissue and a bone algorithm to generate
a diagnostic level CT of the neck for review. PET/CT
© 2013 The Royal Australian and New Zealand College of Radiologists
studies were performed at baseline before the start of
induction chemotherapy and 2 to 3 weeks after the
completion of induction chemotherapy.
Image analysis
All PET/CT studies were retrieved from the electronic
archival system and reviewed on a MIMvista workstation
(software version 4.1, MIM Software Inc., Cleveland, OH,
USA) by a board certified radiologist with nuclear radiology and neuroradiology faculty member with 3 years
experience as a faculty and head and neck and PET/CT
imaging. PET, CT and fused PET/CT images were
reviewed in axial, coronal and sagittal planes. For the
purposes of this study, the relevant imaging biomarker
measurements were MTV and TLG from PET. MTV was
defined as the tumour volume with FDG uptake segmented by a gradient-based method and fixed threshold
methods at 38% and 50% of SUVmax. The TLG was
defined as (MTV) x (SUVmean). The commercially available MIMvista software analysis suite (MIM Software
Inc.) includes a contouring suite for radiation therapy
planning and a PET/CT fusion suite. The edges of the
primary tumour were automatically calculated and outlined in both segmentation methods. Once the primary
tumour was segmented, MTV and TLG were semiautomatically calculated by the MIMvista software. Because
there is greater intrareader variability measuring the
FDG volumentric parameters (MTV and TLG) for smaller
volume tumour,11 we did not segment the nodal metastasis. In addition, previous studies have demonstrated
primary tumour volume than nodal volume as predictors
of outcome.12 For these reasons, we only segmented the
primary tumours.
Segmentation methods
(a) Gradient segmentation method
Gradient segmentation of tumour volume identifies the
tumour on the basis of a change in count level at the
tumour border. Complex segmentation methods have
been proposed including denoising, deblurring, gradient
estimation and watershed transformation. The gradient
segmentation method used in MIMvista (version 4.1) has
been previously described,13,14 and is simple and easy to
use. It calculates spatial derivatives along the tumour
radii and then defines the tumour edge on the basis of
derivative levels and continuity of the tumour edge. The
software relies on an operator-defined starting point
near the centre of the lesion. As the operator drags the
cursor from the centre of the lesion, six axes extend out,
providing visual feedback for the starting point of gradient segmentation. Spatial gradients are calculated along
each axis interactively, and the length of an axis is
restricted when a large spatial gradient is detected. The
six axes define an ellipsoid that is then used as an initial
19
J Yu et al.
bounding region for gradient detection. The reader can
add regions until visually satisfied that the entire primary
tumour is included in the contour.
Inc., Chicago, IL, USA) statistical packages for all analyses, and all hypothesis tests are two-sided with a significance level of 0.05.
(b) Fixed percent threshold
segmentation method
Results
The fixed SUVmax threshold contouring method relies
on including all voxels that are greater than a defined
percent of the maximum voxel within an operatordefined sphere (in this study 38% and 50% of SUVmax).
We used these fixed threshold as have been used in
previous studies.15 Cross-sectional circles are displayed
in all three projections (axial, sagittal and coronal) to
ensure three-dimensional coverage of the primary
tumour.13
Patients
The mean age of the patients was 59 years (range,
29–82 years). The primary tumour sites were oral cavity
and oropharynx (n = 14), larynx (n = 5), hypopharynx
(n = 5) and other (n = 4). The distribution of patients by
the American Joint Committee on Cancer (6th edition)
stage of the cancers included stages III (n = 3, 10.7%),
IVA (n = 20, 71.4%), IVB (n = 4, 14.3%) and IVC (n = 1,
3.6%). The mean follow-up period for the patients was
11 months (range, 2–26 months). Patient characteristics
and therapy details are summarized in Table 1.
Outcome endpoints
The primary outcome measure is to establish whether
the change in exploratory imaging markers, MTV and
TLG, before and after induction chemotherapy, predicts
overall survival and progression-free survival (PFS).
Overall survival is defined as the time from initiation
of therapy to death or to the most recent follow-up.
Progression-free survival is defined as the time from
initiation of therapy to the first documented progression
at the primary site, at regional nodes, or at distant
metastatic sites. Death from the primary cancer without
a documented site of recurrence or progression or death
from an unknown cause is considered death from local
regional disease. Electronic medical records, imaging
records and office visits at our institution were used to
establish the overall survival and PFS. Outcome measures of the study were PFS or disease progression/
mortality. The median follow-up time was 12.5 months.
The Pearson correlation coefficient between the percentage changes (before and after induction chemotherapy)
in gradient MTV (MTVG) and 38% SUVmax threshold MTV
(MTV38) was 0.96 (P < 0.0001). The Pearson r between
MTVG and 50% SUVmax threshold MTV (MTV50) was 0.95
(P < 0.0001). The corresponding Pearson r between
TLGG and TLG38 was 0.94 (P < 0.0001) and 0.96
(P < 0.0001) between TLGG and TLG50.
The Bland–Altman analysis showed a bias of 4.48%
(SD = 26.13%) between the percentage changes of
MTVG and MTV38. The corresponding bias was 1.89%
(SD = 25.30%) between the percentage changes of
MTVG and MTV50. The corresponding biases for TLG were
6.51% (SD = 28.96%) and 5.63% (SD = 32.92%).
Statistical methods
Table 1. Patient characteristics
We present our summary statistics as the mean ⫾SD or
range for continuous variables, or frequency and percentage for categorical variables. We used the Pearson
correlation coefficient to establish the relationship
between different segmentation methods, and we used
Bland–Altman analysis between the two best-correlated
segmentation methods to establish the reliability of the
methods for measuring changes in MTV and TLG. The
baseline MTV or TLG was used as the denominator for
the calculation of percentage reduction. Between group
analysis was performed using the Mann–Whitney U-test.
Receiver operating characteristic (ROC) analysis was
used to determine area under the curve (AUC) to estimate the accuracy and predictive ability of MTV and TLG.
The optimum cut points were established to predict
event-free survival. We used the Prism 5 (GraphPad
Software Inc., San Diego, CA, USA) and SPSS 19 (SPSS
20
Volumetric and metabolic changes and
segmentation methods
Characteristic
Age, mean (range)
Sex
Male
Female
Primary tumour site
Oral cavity/oropharynx
Larynx
Hypopharynx
Other sites
AJCC stage
III
IV
Completed three cycles of induction chemotherapy
Yes
No
Follow-up time, mean (range)
No. patients (%) n = 28
59 (29–82)
20 (71.43%)
8 (28.57%)
14 (50.0%)
5 (17.9%)
5 (17.9%)
4 (14.2%)
3 (10.7%)
25 (89.3%)
20 (71.43%)
8 (28.57%)
11 (2–26)
© 2013 The Royal Australian and New Zealand College of Radiologists
PET volumetric parameters and HNSCC
Fig. 1. Pre- and post-induction chemotherapy
change of metabolic tumour volume (MTV) (gradient segmentation) for patients who survived
without an event and for patients who progressed
or died.
SUVmax changes and outcomes
The median SUVmax changes for patients who had no
events and for patients who had progressed or died
were 100% (IQR 53.5% to 100%) and 51.88% (IQR
19.07% to 93.88%), respectively (Mann–Whitney U-test
P = 0.09). In the ROC analysis, the AUC for SUVmax was
0.70 (95% CI 0.47–0.92; P = 0.10).
were 0.84 (95% CI 0.66–1.00; P = 0.006) and 0.84
(95% CI 0.65–1.00; P = 0.006). An optimum cut point of
55% reduction in the TLGG predicts event-free survival
with a sensitivity of 62.5% and a specificity of 90% and
a HR of 6.25. The corresponding cut point for TLG50 was
59% reduction with the same sensitivity, specificity
and HR.
Discussion
MTV changes and outcomes
The median MTVG changes for patients who had no
events and for patients who had progressed or died were
100% (IQR 88.6% to 100%) and 36.75% (IQR -55.19%
to 89.13%), respectively (Mann–Whitney U-test P =
0.02) (Figs 1,2). The corresponding values using MTV38
were 100% (IQR 84.1% to 100%) and 19.05% (IQR
-44.1 to 81.62); and for MTV50 100% (IQR 84.85% to
100%) and 24.04% (IQR -17.25% to 77.78%). There
was a significant difference between the two groups for
both MTV38 (P = 0.02) and MTV50 (P = 0.02).
In the ROC analysis, the AUC for MTVG was 0.76 (95%
CI 0.55–0.97; P = 0.03) (Fig. 3). AUCs for MTV38 and
MTV50 were 0.77 (95% CI 0.56–0.98; P = 0.03) and 0.76
(95% CI 0.55–0.98; P = 0.03). An optimum cut point of
42% reduction in the MTVG predicts event-free survival
with a sensitivity of 67% and a specificity of 90% and an
hazards ratio (HR) of 6.3. The corresponding cut point
for MTV50 was a 53% reduction with the same sensitivity,
specificity and HR.
TLG changes and outcome
The median TLGG changes for patients who had no
events, and for patients who had progressed or died
were 100% (IQR 93.23% to 100%) and 43.16% (IQR
-55.47% to 88.96%), respectively (P = 0.007) (Fig. 4).
The corresponding values using TLG38 were 100% (IQR
94.34% to 100%) and 21.52% (IQR -23.66% to
85.31%) (P = 0.004); for TLG50 99.02% (IQR 40.41%
to 100%) and 41.96% (IQR -21.98% to 84.68%)
(P = 0.006).
In the ROC analysis, AUC for TLGG was 0.82 (95% CI
0.64–1.00; P = 0.009) (Fig. 3). AUCs for TLG38 and TLG50
© 2013 The Royal Australian and New Zealand College of Radiologists
The aim of this exploratory study was to determine
whether metabolic volumetric analysis of tumours before
and after induction chemotherapy can predict the eventfree survival of head and neck cancer patients. The
results suggest that there is a significant difference in
the changes of both MTV and TLG between patients who
had progressed or died and those who had an event-free
survival. Using ROC analysis, a 42% reduction in MTVG or
55% reduction in TLGG were determined to be optimal
for predicting event-free survival. The AUCs for MTV50,
TLGG, and TLG50 were also determined and found to be
similar to MTVG. In addition, the changes in percentage
of metabolic volume segmented by gradient and by
the fixed percentage threshold methods are highly
correlated.
Several parameters have been utilized for response
assessments. One conventional method is based on
changes in the longest measured diameter of the
tumour. The maximum diameter approach suffers from a
relatively small degree of interobserver reliability.16,17
Additionally, the tumour diameter is only a unidimensional anatomical parameter and provides no metabolic
or functional information about the tumour biology. A
more functional metabolic parameter is the maximum
SUV (SUVmax), the pixel with the highest intensity in the
tumour region. Compared with tumour diameter, SUVmax
has significantly less interobserver and intraobserver
variability.17,18 However, several factors can affect the
SUVmax and may under- or overestimate the degree to
which it depends on tumour size and the tumour-tobackground ratio.19 The utility of SUVmax as a prognostic
factor has been explored with mixed results. With nonsmall-cell lung cancers and head and neck nonsquamous cell carcinomas, using SUVmax values has been
21
J Yu et al.
Fig. 2. (a and d) Axial positron emission tomography (PET), (b and e) axial PET/CT and (c and f) coronal PET/CT of a 78-year-old woman with T3N2cM0 stage IVA
squamous cell cancer of the oropharynx. Pre-induction chemotherapy primary tumour MTV (gradient segmentation) is 8.3 mL. Induction therapy consisted of three
cycles of Taxotere (docetaxol), cisplatin and 5-fluorouracil. The post-induction primary tumour metabolic tumour volume is 6.6 mL (20% reduction). Patient had
progressed 4 months after the completion of treatment and died 21 months after treatment.
shown to have predictive value.20,21 Other studies,
however, have indicated that SUV measurements are not
significant or reliable prognostic factors.22,23
In light of the shortcomings of tumour diameter and
SUVmax, a new method of assessing prognosis based on
volumetric analysis has been drawing increased atten-
tion. In the case of small-cell lung cancers, the MTV has
been demonstrated to be a significant predictor of
patient outcome.24 MTV has also been shown to be an
important independent predictor of disease-free survival
in the case of oesophageal cancer as well as head and
neck cancers.25,26 It has been suggested to add value to
Fig. 3. Metabolic tumour volume (MTV) and total
lesion glycolysis (TLG) (gradient segmentation)
percentage change (pre- and post-therapy)
receiver operating characteristic analysis for
event-free survival. AUC, area under the curve.
22
© 2013 The Royal Australian and New Zealand College of Radiologists
PET volumetric parameters and HNSCC
Fig. 4. Pre- and post-induction chemotherapy
change of total lesion glycolysis (TLG) (gradient
segmentation) for patients who survived without
an event and for patients who progressed or died.
staging in predicting prognosis of patients with oral and
oral cavity squamous cell cancers.14 Our results further
demonstrate that MTV and TLG can potentially be used
for induction therapy assessment in head and neck squamous cell cancer. In contrary to a prior study,27 we used
the same threshold cut points, 38% and 50% of the
measured SUVmax in the baseline and then in the postinduction images, as the SUVmax of the primary tumour
are likely to change with induction chemotherapy. Our
study showed there is significant reduction in the threshold MTV and TLG, after induction chemotherapy, in those
who had an event and those who did not. This may be
due to lack of radiation inflammation in our study. We did
not use the baseline SUVmax for threshold cut point in the
post-induction images, as used by a prior study,28 as
SUVmax changes with induction therapy.
Our results need to be interpreted in the context of our
study design. This is an exploratory study with a small
number of patients, and the MTV and TLG were segmented using single vendor-provided, FDA-approved,
commercially available software. Segmentation of small
residual tumours may not be accurate, especially when
the tumour volume is less than 10 mL. We did not
perform the analysis for nodal disease, as small volume
disease have more variability in measurements but
acknowledge nodal disease is an important prognostic
factor. Though our study only included patients with
advanced head and neck cancer (stage III and stage IV)
patients, we did not perform Human Papilloma Virus
(HPV) status routinely in all head and neck patients at
the time of this study. Hence, HPV status is not included
in the analysis, which may influence the outcome of
some of the patients included in the study. Due to the
small sample size, we included both oral cavity and
oropharynx in the study. Our follow-up period is limited
with a range of 2–26 months with an actuarial median
follow-up of 11 months.
Conclusion
Our exploratory results suggest that a reduction in MTV
or TLG of 42% and 55%, respectively, before and after
induction chemotherapy, predicts short-term event-free
survival in patients with advanced head and neck squa© 2013 The Royal Australian and New Zealand College of Radiologists
mous cell cancer (stages III and IV). These exploratory
metabolic volumetric imaging parameters and cut points
for predicting short to intermediate term outcome need
validation in a larger and prospective study, which would
include other important clinical parameter such as HPV
status.
Acknowledgements
Rathan Subramaniam was supported by a GE-AUR
Research fellowship and received Siemens molecular
imaging and MJ Fox foundation research grants and
research support from MIM Software Inc.. He is a
speaker and consultant for Eli Lilly (Alzheimer’s disease).
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© 2013 The Royal Australian and New Zealand College of Radiologists