Prediction of tumour necrosis fractions using metabolic and volumetric 18F-FDG PET/CT indices, after one course and at the completion of neoadjuvant chemotherapy, in children and young adults with osteosarcoma.
ABSTRACT The utility of combined metabolic and volumetric (18)F-FDG PET/CT indices for predicting tumour necrosis fractions following neoadjuvant chemotherapy has not been extensively studied in osteosarcoma. Furthermore, little is known of the early PET/CT responses after only one chemotherapy course.
Enrolled in the study were 20 children and young adults with resectable osteosarcoma who had undergone (18)F-FDG PET/CT scans before and after neoadjuvant chemotherapy. Maximum standardized uptake value (mSUV), metabolic tumour volume (MTV), and total lesion glycolysis (TLG) were measured. From among the 20 patients, 14 were prospectively recruited and underwent an additional PET/CT scan after one chemotherapy course. Histopathological necrosis fractions were compared with the above-mentioned PET/CT indices and their ratios.
MTV at the SUV threshold of 2 g/ml was closely correlated with the magnetic resonance image volumes before therapy (r = 0.91). In the prospective cohort, five patients were classified as good responders and nine as poor responders. All the metabolic indices (mSUV and its ratio) and combined metabolic/volumetric indices (MTV, TLG, and their ratios) except the mSUV ratio determined after therapy showed significant differences between good and poor responders (P <0.05). Differences were also noted for all of these indices determined after one chemotherapy course. Furthermore, most of these indices determined after therapy as well as after one chemotherapy course had good sensitivity, specificity, positive predictive value and negative predictive value with respect to predicting histological response to chemotherapy.
In our osteosarcoma patient population, (18)F-FDG PET/CT indices (either combined metabolic/volumetric or metabolic indices) determined after neoadjuvant chemotherapy were useful in predicting tumour responses. This held true after only one chemotherapy course.
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ABSTRACT: Osteosarcoma is the most common primary osseous malignancy excluding malignant neoplasms of marrow origin (myeloma, lymphoma and leukemia) and accounts for approximately 20% of bone cancers. It predominantly affects patients younger than 20 years and mainly occurs in the long bones of the extremities, the most common being the metaphyseal area around the knee. These are classified as primary (central or surface) and secondary osteosarcomas arising in preexisting conditions. The conventional plain radiograph is the best for probable diagnosis as it describes features like sun burst appearance, Codman's triangle, new bone formation in soft tissues along with permeative pattern of destruction of the bone and other characteristics for specific subtypes of osteosarcomas. X-ray chest can detect metastasis in the lungs, but computerized tomography (CT) scan of the thorax is more helpful. Magnetic resonance imaging (MRI) of the lesion delineates its extent into the soft tissues, the medullary canal, the joint, skip lesions and the proximity of the tumor to the neurovascular structures. Tc99 bone scan detects the osseous metastases. Positron Emission Tomography (PET) is used for metastatic workup and/or local recurrence after resection. The role of biochemical markers like alkaline phosphatase and lactate dehydrogenase is pertinent for prognosis and treatment response. The biopsy confirms the diagnosis and reveals the grade of the tumor. Enneking system for staging malignant musculoskeletal tumors and American Joint Committee on Cancer (AJCC) staging systems are most commonly used for extremity sarcomas.Indian Journal of Orthopaedics 05/2014; 48(3):238-46. · 0.62 Impact Factor
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ABSTRACT: Objective According to the current treatment protocol of the Cooperative Osteosarcoma Study, it is mandatory to determine the histological response to neoadjuvant chemotherapy treatment before surgical removal of the tumor, particularly if a limb salvage procedure is planned. The aim of this systematic, retrospective study was to evaluate the ability of 2-(18F) fluoro-2-deoxy-D-glucose positron-emission tomography/computed tomography to predict chemotherapy response of osteosarcoma and to identify a simple promising method for noninvasive evaluation of neoadjuvant chemotherapy response in osteosarcoma.Methods The PubMed database was searched to identify and analyze relevant published reports. In particular, correlations between tumor-to-background ratio (TBR), standard uptake value (SUV) and histological response to chemotherapy were assessed.ResultsIt was found that good responses are achieved in patients with TBR after chemotherapy (TBR2)/TBR before chemotherapy (TBR1) < 0.470 (positive predictive value [PPV] = 92.31%, negative predictive value [NPV] = 82.76%, sensitivity [S] = 87.80%, specificity [SP] = 88.89%), whereas poor responses occur in patients with SUV after chemotherapy/before chemotherapy (SUV2/SUV1) > 0.396 (PPV = 73.68%, NPV = 73.33%, S = 63.64%, SP = 81.48%).Conclusion Changes in TBR are better predictors of chemotherapy response than SUV in osteosarcoma patients. Therefore, we believe that choice of surgical strategy is optimally based on changes in TBR.Orthopaedic Surgery 05/2014; 6(2).
Article: FDG PET/CT of Primary Bone Tumors.[Show abstract] [Hide abstract]
ABSTRACT: OBJECTIVE. Numerous primary bone tumors are encountered on (18)F-FDG PET/CT, and many are FDG avid. The degree of FDG uptake in bone tumors does not necessarily reflect malignant potential. In conjunction with radiographs, evaluation of morphologic characteristics on the CT portion of PET/CT scans is important for characterization of the lesions. FDG PET/CT has been found to be useful for staging and has also been found to reflect prognosis in some primary bone malignancies. The purpose of this article is to familiarize the reader with topics regarding FDG PET/CT and both malignant and benign primary bone tumors. CONCLUSION. FDG uptake alone is not adequate for characterizing primary bone tumors, and morphologic evaluation is an important factor in the interpretation of PET/CT scans. After diagnosis, FDG avidity and morphologic features can play an important role in staging and determining response to therapy. On completion of this article, readers should have an improved ability to evaluate the FDG uptake and CT morphologic features of malignant and benign primary bone tumors. Readers should also have a better understanding of the potential role of FDG PET/CT in the management of patients with osteosarcoma and Ewing sarcoma.AJR. American journal of roentgenology. 06/2014; 202(6):W521-31.
Prediction of tumour necrosis fractions using metabolic
and volumetric18F-FDG PET/CT indices, after one course
and at the completion of neoadjuvant chemotherapy,
in children and young adults with osteosarcoma
Hyung Jun Im & Tae Sung Kim & Seog-Yun Park & Hye Sook Min & June Hyuk Kim &
Hyun Guy Kang & Seung Eun Park & Mi Mi Kwon & Jong Hyung Yoon &
Hyeon Jin Park & Seok-ki Kim & Byung-Kiu Park
Received: 23 April 2011 /Accepted: 2 September 2011 /Published online: 28 September 2011
# Springer-Verlag 2011
FDG PET/CT indices for predicting tumour necrosis fractions
following neoadjuvant chemotherapy has not been extensively
studied in osteosarcoma. Furthermore, little is known of the
early PET/CT responses after only one chemotherapy course.
Methods Enrolled in the study were 20 children and young
adults with resectable osteosarcoma who had undergone
18F-FDG PET/CT scans before and after neoadjuvant
chemotherapy. Maximum standardized uptake value
(mSUV), metabolic tumour volume (MTV), and total lesion
glycolysis (TLG) were measured. From among the 20
patients, 14 were prospectively recruited and underwent
an additional PET/CT scan after one chemotherapy
course. Histopathological necrosis fractions were com-
pared with the above-mentioned PET/CT indices and
Results MTV at the SUV threshold of 2 g/ml was closely
correlated with the magnetic resonance image volumes
before therapy (r=0.91). In the prospective cohort, five
patients were classified as good responders and nine as
poor responders. All the metabolic indices (mSUV and its
ratio) and combined metabolic/volumetric indices (MTV,
TLG, and their ratios) except the mSUV ratio determined
after therapy showed significant differences between good
and poor responders (P <0.05). Differences were also noted
for all of these indices determined after one chemotherapy
course. Furthermore, most of these indices determined after
therapy as well as after one chemotherapy course had good
sensitivity, specificity, positive predictive value and nega-
tive predictive value with respect to predicting histological
response to chemotherapy.
Conclusion In our osteosarcoma patient population,
FDG PET/CT indices (either combined metabolic/volumetric
or metabolic indices) determined after neoadjuvant chemo-
therapy were useful in predicting tumour responses. This
held true after only one chemotherapy course.
Keywords Osteosarcoma.18F-FDG PET/CT.Combined
metabolic/volumetric indices.Response to neoadjuvant
chemotherapy.Early PET/CT response
Seok-ki Kim and Byung-Kiu Park contributed equally to this work.
Electronic supplementary material The online version of this article
(doi:10.1007/s00259-011-1936-4) contains supplementary material,
which is available to authorized users.
H. J. Im:T. S. Kim:S.-k. Kim (*)
Department of Nuclear Medicine, National Cancer Center,
Goyang-si, Gyeonggi-do 410-769, Korea
S.-Y. Park:H. S. Min
Department of Pathology, National Cancer Center,
Goyang-si, Gyeonggi-do 410-769, Korea
J. H. Kim:H. G. Kang
Orthopedic Oncology Clinic, National Cancer Center,
Goyang-si, Gyeonggi-do 410-769, Korea
S. E. Park
Cancer Biostatistics Branch, National Cancer Center,
Goyang-si, Gyeonggi-do 410-769, Korea
M. M. Kwon:J. H. Yoon:H. J. Park:B.-K. Park (*)
Center for Pediatric Oncology, National Cancer Center,
323 Ilsan-ro, Ilsandong-gu,
Goyang-si, Gyeonggi-do 410-769, Korea
Eur J Nucl Med Mol Imaging (2012) 39:39–49
Osteosarcoma, the most common primary malignant bone
tumour, usually originates in the metaphyses of the long
bones of adolescents and young adults. The rate of systemic
spread is so high that cure is rarely achieved with surgical
treatment alone . Accordingly, adjuvant and neoadjuvant
chemotherapy were introduced, and since their introduction,
there has been a significant improvement in the long-term
survival rates of patients with high-grade osteosarcoma of the
extremities. Indeed, the 5-year disease-free survival has
improved from less than 20% to more than 60% over several
decades. Simultaneously, the frequency of limb salvage
surgery has increased from 10–20% to 80–90%, with a
corresponding decrease in the amputation rate .
Histopathological response to neoadjuvant chemotherapy
is an important prognostic indicator of disease-free survival
after multimodal treatment [3, 4]. An evaluation of the
Cooperative Osteosarcoma Study Group (COSS) database
revealed that patients with a good histological response
have an overall 5-year survival rate of 77.8%, whereas
those with a poor response have a survival rate of 55.5%
. In this work, histological response was assessed
according to the scale devised by Salzer-Kuntschik et al.
, and a good response was defined as a viable tumour
fraction of <10%.
Noninvasive means of predicting the effect of neo-
adjuvant chemotherapy, as reflected in histopathological
response, are important because they could be used to
determine whether to switch to a more intensified chemo-
therapy regimen or not, and to determine the most
appropriate surgical approach .
18F-FDG PET/CT has emerged as a promising tool for
predicting treatment response for many cancer types,
including oesophageal cancer, non-small-cell lung cancer,
head and neck cancer and breast cancer [8–11]. Only a
limited number of studies have evaluated the effect of
neoadjuvant chemotherapy on osteosarcoma, with most
having used maximum standardized uptake values (SUV),
post- to pretherapy SUV ratios, percentage change in
SUV, tumour to background ratios (TBR) and post- to
pretherapy TBR ratios as indices for predicting treatment
Maximum SUV represents only the most active parts of
the tumour, and may not represent the status of the entire
tumour. Alternatively, the combined metabolic/volume
index may be a good indicator of the status of the entire
tumour. In tumours such as osteosarcoma, which are
generally large and demonstrate high intratumoral hetero-
geneity with respect to FDG uptake, it appears to be
rational, at least theoretically, to measure tumour volume
and glycolytic activities simultaneously, rather than to
measure only the glycolytic activities of the most active
parts of the tumour . However, this suggestion has not
been thoroughly studied in osteosarcoma. Furthermore,
there have been no reports concerning the responses on
FDG PET/CT early during the course of neoadjuvant
chemotherapy, although such information might be useful
for determining changes in treatment strategy when the
histological response to chemotherapy is expected to be poor.
In the current study, we compared the utility of combined
metabolic/volume indices versus metabolic indices for
predicting treatment response in children and young adults
with high-grade osteosarcoma after one course and on
completion of neoadjuvant chemotherapy. We found that
both of these indices were useful for this purpose.
Materials and methods
Patients and study design
From August 2003 to July 2010, 20 children and young
adults with histologically confirmed and resectable high-
grade osteosarcoma were enrolled. Six patients were
enrolled retrospectively from 2003 to 2006, and 14
prospectively from 2007 to 2010. All patients underwent
a diagnostic biopsy and a pretherapy PET/CT scan before
neoadjuvant chemotherapy was initiated. Patients received
two to four courses of neoadjuvant chemotherapy, which
consisted of various combinations of doxorubicin, cisplatin,
high-dose methotrexate, ifosfamide and etoposide. They
then underwent a posttherapy PET/CT scan before defini-
tive surgery. The 14 prospectively recruited patients
received an additional (interim) PET/CT scan between the
first and second course (except one who underwent an
interim scan after two courses) of neoadjuvant chemotherapy.
The pretherapy PET/CT scans were performed within 0–
3 weeks before the initiation of neoadjuvant therapy, and the
posttherapy PET/CT scans within 0–3 weeks before tumour
resection. The removed tumour specimens were histopatho-
logically examined to determine necrosis fractions using a
conventional mapping method described previously [16, 17].
The National Cancer Center Institutional Review Board
(NCC IRB) approved the study. Informed consent was
obtained from the prospectively enrolled patients and/or
their parents and was waived for the retrospectively
enrolled patients by the IRB. The study was performed in
compliance with the ethical guidelines of the NCC IRB.
Whole-body FDG PET/CT was performed using a com-
bined PET/CT scanner (Biograph LSO; Siemens Medical
Solutions, Hoffman Estates, IL). After an 8-h fasting period
followed by blood sugar testing to confirm that the glucose
40Eur J Nucl Med Mol Imaging (2012) 39:39–49
value was <120 mg/dl, 166.5–666 MBq (4.5–18 mCi) of
18F-FDG was injected intravenously, and patients were
encouraged to rest during this period. PET/CT scanning
was performed from the middle of the skull to the upper
thigh 60 min after injection, and this was followed by an
additional PET/CT scan of the lower extremities.
During the PET/CT scans, spiral CT was performed
using the following parameters: a scout view at 30 mA and
130 kVp, followed by a spiral CTscan with effective mA of
50, 130 kVp, 5 mm section width, 4 mm collimation,
12 mm table feed per rotation, and 0.8 s per rotation with
arms raised. PET images were acquired after the CT scans
with 3 min per bed position (11.2-cm increments, three-
dimensional mode). CT images were reconstructed onto a
512 × 512 matrix, and were converted using equivalent
attenuation factors of 511 keV for attenuation correction.
PET images were reconstructed onto a matrix of 128 × 128
using the ordered-subsets expectation maximization algo-
rithm, and attenuation correction was also performed.
PET, PET/CT and CT images were reviewed using a
dedicated workstation and software (E.soft; Siemens
Medical Solutions), which allowed three-dimensional
displays (transaxial, coronal and sagittal) to be constructed
using CT, PET and PET/CT images and maximum intensity
projection displays of the PET data.
Magnetic resonance imaging
All patients underwent MR imaging before and after
neoadjuvant chemotherapy. All pretherapy MR images,
except those for two patients, were acquired within 3 weeks
of the PET/CT scans and therapy initiation. MR images
were obtained using a Signa 1.5-T unit (GE Medical
Systems, Milwaukee, WI) in different planes (axial, coronal
and sagittal/oblique along the axes of the long bones). T1-
weighted imaging was performed using a repetition time of
400 ms and an echo time of 10 ms, T2-weighted imaging
using a repetition time of 4,000 ms and an echo time of
73 ms, and contrast-enhanced T1-weighted imaging using a
repetition time of 500 ms and an echo time of 20 ms after
the administration of gadopentate dimeglumine (Gd-DTPA,
Magnevist; Schering, Berlin, Germany). Images were
obtained at the same 24 levels after contrast enhancement.
The section thickness was 4 mm with one data acquisition
and a 512 × 512 acquisition matrix.
Determination of standardized uptake values, metabolic
tumour volumes and total lesion glycolysis
SUVs were calculated as follows: SUV=(decay-corrected
activity in kilobecquerels per millilitre of tissue)/(injected
18F-FDG activity in kilobecquerels per body mass in
grams). The SUV of a lesion was obtained by placing
regions of interest (ROIs) manually around the lesion, and
the maximum SUV (mSUV) within an ROI was used to
minimize partial-volume effects. Volumes of interest
(VOIs) were drawn around tumours with a substantial
margin to include normal adjacent tissue. Metabolic tumour
volumes (MTVs) were calculated as described by Biehl
et al. . First, MTVs were calculated by summing the
volume of voxels that had an SUV higher than a certain
threshold SUV within a given VOI. MTV(1.5), MTV(2),
MTV(2.5) and MTV(3) were obtained using threshold
SUVs of 1.5, 2.0, 2.5 and 3.0 g/ml, respectively. MTVs
were automatically calculated using Osirix medical imaging
software (The Osirix Foundation, Geneva, Switzerland).
Total lesion glycolysis (TLG) values were calculated by
multiplying the MTVs by mean MTV SUVs . TLGs
corresponding to MTVs were calculated, i.e. TLG(1.5),
TLG(2), TLG(2.5) and TLG(3.0). mSUV, MTV and TLG
ratios (rSUV, rMTV, rTLG) were calculated by dividing
interim or postchemotherapy values by prechemotherapy
Determination of tumour volumes
Tumour volumes were defined as the sum of enhanced
areas on MR images, because the 3-D volume of irregularly
shaped tumours could not be measured reliably. MR
volumes (MRV) were obtained by manually drawing ROIs
around Gd-enhanced areas on axial T1-weighted sequence
images (Osirix medical imaging software). Only pretherapy
MR images obtained within 3 weeks before PET/CT
scanning were evaluated. MRVs were determined before
and after neoadjuvant chemotherapy.
MRVs and MTVs before neoadjuvant chemotherapy
were compared using Spearman’s correlation coefficients
and visual assessment. Pretherapy PET/CT, MR and PET/MR
physicians independently. PET/MR fusion was performed
using a three-point method (GE Medical Systems).
After surgery, excised specimens were cut longitudinally in
the plane deemed most likely to reveal residual viable
tumour, and tumour necrosis fractions were then defined
as the percentage of devitalized parts of the tumour in
the examined planes as determined histologically. Path-
ological good responders (GRs) and poor responders
(PRs) were differentiated using the grading system
proposed by Salzer-Kuntschik et al. : grades I–III
(necrosis fraction ≥90%) were considered GRs, and grades
IV–VI (necrosis fraction <90%) PRs.
Eur J Nucl Med Mol Imaging (2012) 39:39–4941
Immunohistochemical staining for glucose transporters
As increased expression of glucose transporters has been
reported in many human cancers , we investigated the
expression status of glucose transporters 1 and 3 (Glut1 and
Glut3) in the osteosarcoma tissues and its relationship to
PET/CT indices. Immunohistochemical staining was per-
formed using immunoperoxidase detection techniques, with
diaminobenzidine as the chromogen. Sections of 4 μm from
formalin-fixed, paraffin-embedded tissues obtained by
biopsy and surgical resection were placed in tissue arrays
and processed using a previously reported procedure .
The primary antibodies used were rabbit polyclonal anti-
human Glut1 (1:1,000 dilution; Chemicon International,
Temecula, CA) and Glut3 antibody (1:500 dilution;
Chemicon). Signals were detected using an EnVision kit
(Dako, Carpinteria, CA). Positive staining of the red
blood cells served as an internal positive control for
expression of Glut1. Human testes were used as positive
controls for Glut3. Parallel sections incubated with rabbit
IgG instead of the primary antibodies were used as
negative controls. Sections with tumour cells that demon-
strated membranous staining were considered positive for
Glut1 and Glut3.
The overall staining result was scored from 0 to 4 based
on the intensity and positive rate of staining . The
intensity of staining was categorized as negative, weak,
moderate or strong. The proportion of positively stained
cells was graded as: 0, 0%; 1, 1–10%; 2, 11–50%; 3, 51–
100%. All stained sections were reviewed by two experi-
enced pathologists who were blind to the PET/CT data.
Statistical analyses were performed using MedCalc for
Windows, version 188.8.131.52 (MedCalc Software, Mariakerke,
Belgium). Correlation analysis was performed to compare
histopathological necrosis fractions and posttherapy mSUV,
MTV and TLG, as well as post-to pretherapy rSUV, rMTV,
rTLG and rMRV. For these parameters, t-tests were
performed to determine their ability to discriminate patho-
logical GRs and PRs in the prospective cohort. Addition-
ally, a subanalysis was performed using prospectively
obtained information from pretherapy and interim PET/CT
imaging. Of the above parameters, those predicting histo-
logical response better (|r| >0.5, P <0.05) were chosen, and
receiver operating characteristic (ROC) curve analysis with
respect to histological response prediction was performed.
Area under the curve values (AUCs) were calculated to
determine the best predictor cut-off value for each
parameter. Then patients were grouped using these cut-off
values, and sensitivity, specificity, positive predictive value
(PPV) and negative predictive value (NPV) were calculated.
Correlations between various PET/CT indices and the
expression of glucose transporters were assessed using the
nonparametric Spearman’s rank test. All P values were
derived from the two-sided test, and values less than 0.05
were considered significant.
Patient age and sex, histological subtypes, primary tumour
sites, intervals between pretherapy and interim or post-
therapy PET scans, numbers of chemotherapy courses
during the various intervals, types of surgery and histolog-
ical responses are presented in Table 1. The median age of
the patients was 15 years (range 10–25 years), and there
were equal numbers of male and female patients. According
to the American Joint Committee on Cancer (AJCC)
staging system , seven patients had a stage IIA tumour,
six stage IIB tumour, three stage III tumour with skip
metastases, two stage IVA tumour with lung metastases,
and two stage IVB tumour with remote metastases in the
mandible and spine, respectively. All tumours included in
this study were high-grade with 95% of them being
osteoblastic. All patients had primary diseases except one
with osteosarcoma in the mandible, which was the only site
of relapse from the femoral primary tumour. A variety of
chemotherapeutic regimens were used; AOST 0331 (cis-
platin, doxorubicin, methotrexate) in eight patients, ISG/
SSG 1 (cisplatin, doxorubicin, methotrexate, ifosfamide) in
seven, CCG 7921 regimen B (ifosfamide, doxorubicin,
methotrexate) in two, and miscellaneous regimens in three.
Each course of AOST 0331 and CCG 7921 regimen B took
at least 5 weeks, and each course of ISG/SSG 1 at least
6 weeks. The median number of neoadjuvant chemotherapy
courses was two (two in 15 patients, three in 4, and four
in 1). As already mentioned, interim PET/CT scans were
additionally obtained in the 14 prospectively recruited
patients. The number of chemotherapy courses between
pretherapy and interim PET scanning was one in 13
patients and two in 1 patient, and that between interim
scanning and surgery was one in 11 patients and two in
3 patients. All patients underwent surgical resection of
their tumours after chemotherapy. Nine patients were
GRs and 11 were PRs.
Comparison between pretherapy MRVs and MTVs
MTV(1.5) and MTV(3) could not be obtained. The SUV
threshold of 1.5 g/ml could not clearly discriminate
between tumour and neighbouring normal tissue, and the
SUV threshold of 3 g/ml produced tumour areas that were
42 Eur J Nucl Med Mol Imaging (2012) 39:39–49
too small when compared to real tumour masses. MTV(2)
and MTV(2.5) could be calculated in all patients and
appeared to represent tumour areas well.
Pretherapy MTVs at various SUV thresholds were
compared with pretherapy MRVs to see if the former could
substitute for MRVs, and MTV(2) showed the best
correlation with tumour volume (r=0.91, P <0.05; Fig. 1).
MTV(2.5) also showed a significant correlation (r=0.86,
P<0.05). Images of MTV(2) and MR before treatment
(Fig. 2a, b) were visually well matched in all patients
Comparisons between mSUV, MTV, TLG and MRV values
before, during and after therapy vs. necrotic fractions
in the entire and prospective cohort
Various PET/CT parameters, MRV and necrosis fractions
for the entire cohort are presented in Table 2. Six patients
(patients 1–6) were retrospectively enrolled, and 14
(patients 7–20) were prospectively enrolled. Only one
patient (patient 4) had a posttherapy mSUV that was higher
than the pretherapy mSUV (Fig. 3a). Unexpectedly, the
necrosis fraction in the removed tumour specimen in this
patient was 99% (Fig. 3c). Unlike mSUV, posttherapy
MTV(2.5) and TLG(2.5) showed significant reductions
from their pretherapy values (690.3 ml to 113.5 ml;
3,043.7 g to 396 g) in this patient (Fig. 3b). Patient 7 was
the only one whose posttherapy MTVs and TLGs were
higher than the pretherapy values (Table 2). Only 3% of the
patient’s tumour specimen was necrotic. The mean (±SD)
rMRV was 0.93 (±0.28), and posttherapy MRVs were
greater than pretherapy values in 6 of 18 patients (two were
excluded from the tumour volume analysis because their
pretherapy MR images were acquired more than 3 weeks
before PET/CT scanning). MRVs were not different before
and after chemotherapy.
Fig. 1 MTV at SUV threshold of 2 g/ml (MTV(2)) and MR volume
before therapy are closely correlated (r=0.91, P <0.05)
Table 1 Patient characteristics, timing of PET, and histological
Sex, n (%)
Histological subtype, n (%)
Location, n (%)
Time from pretherapy to posttherapy PET (weeks)
Time from posttherapy PET to surgery (weeks)
Number of therapy courses from pretherapy to posttherapy PET
Time from pretherapy to interim PET (weeks)
Time from interim PET to surgery (weeks)
Number of therapy courses from pretherapy to interim PET
Number of therapy courses from interim PET to surgery
Type of surgery, n (%)
Tumour necrosis fraction (%)
Histological response, n (%)
aThe only patient who presented with recurrent lesion solely in the
mandible, and received two chemotherapy courses before interim PET
Eur J Nucl Med Mol Imaging (2012) 39:39–4943
Correlations between various PET/CT parameters and
the necrosis fraction are presented in Table 3. For the entire
cohort, posttherapy mSUV showed a weaker linear rela-
tionship with necrosis fraction (|r|<0.5, P <0.05), whereas
rMTV(2) and rTLG(2) showed a stronger relationship (|r|>
0.75, P <0.05). rMTV(2.5) and rTLG(2.5) also had a
stronger relationship (data not shown). However, rMRV did
not reflect tumour necrosis fraction.
All PET/CT parameters from the prospective cohort
were associated with necrotic fractions (|r| >0.5, P <0.05),
with correlations similar to those obtained for the entire
cohort, except posttherapy mSUV, rSUV, MTV(2) and TLG
(2). Of all prospective parameters, interim to pretherapy
rTLG(2) showed the best correlation with necrotic fractions
Prediction of histological response – ROC curve analysis
in the prospectively enrolled patients
Inthe prospective cohort, fivepatientswereclassifiedasGRs,
and nine as PRs. The five GRs were compared with the nine
PRs with respect to various PET/CT parameters and MRV.
Posttherapy mSUV, MTV(2) and TLG(2), as well as post- to
pretherapy rMTV(2) and rTLG(2), showed differences
between GRs and PRs (P <0.05), while rSUV showed a
trend towards a difference (P=0.09). However, posttherapy
MRVand rMRV were not different between the two groups.
Interim mSUV, MTV(2) and TLG(2), as well as interim
to pretherapy rSUV, rMTV(2) and rTLG(2), all showed
differences between GRs and PRs (P <0.05).
In the ROC curve analysis for all the parameters that had
shown moderate correlations (|r| >0.5, P <0.05) with
histological response in the prospective cohort (Table 3),
all parameters except post- to pretherapy rSUV nicely
predicted histological response (AUC 0.867–0.956;
P ≤0.0005; ROC curves not shown). rSUV showed a trend
towards prediction of response (AUC 0.756; P=0.081). In
the same analysis with parameters acquired before therapy
and in the interim, all parameters, including interim to
pretherapy rSUV, predicted histological response (AUC
0.867–0.956; P ≤0.0004).
Sensitivity, specificity, PPV, NPV and accuracy of these
parameters at each cut-off value determined in the ROC
curves were calculated. Of the parameters obtained before
and after therapy, posttherapy mSUV at a cut-off of 3 g/ml
showed the highest diagnostic index, with 100% sensitivity,
88.9% specificity, 83.3% PPV, 100% NPV and 92.9%
accuracy (Table 4). The specificity and PPVof post-therapy
MTV(2) were superior to those of mSUV, albeit its
sensitivity and NPV were lower.
Of the parameters obtained before therapy and in the
interim, diagnostic indices for interim mSUV, MTV(2) and
TLG(2) were equally high, with 100% sensitivity, 88.9%
specificity, 83.3% PPV, 100% NPV and 92.9% accuracy
Expression of Glut1 and Glut3 in the biopsy and surgical
specimens vs. PET/CT indices
Paired pretherapy and posttherapy tumour specimens were
available in eight patients. Five of the eight pretherapy
specimens (62.5%) showed positive Glut1 immunostaining,
while seven of eight (87.5%) were positive for Glut3 (see
the Table S1 in the Electronic supplementary material). The
c cb ba a
MRVMTV(2) over MRPET MTV(2)
Fig. 2 PET, MR and PET/MR fusion images in patient 1. a
Attenuation-corrected axial and coronal PET image of a tumour in
the right proximal femur. The green-coloured ROI represents a
collection of voxels with SUVs ≥2 g/ml automatically drawn by
Osirix. b Gadolinium-enhanced T1-weighted axial and coronal MR
images of the same slice as shown in a, which was registered to the
appropriate PET/CT image using a GE workstation. The pink ROI was
drawn manually around the gadolinium-enhanced area. c Fused
images of a and b. The tumour boundaries are well matched in the
axial and coronal views
44Eur J Nucl Med Mol Imaging (2012) 39:39–49
Table 2 PET/CT parameters, MRVs before and after chemotherapy, and histological response for the entire cohort
Necrosis fraction (%)
NA not assessed
Eur J Nucl Med Mol Imaging (2012) 39:39–49 45
extent of immunoreactivity varied from 5% to 70% for Glut1
and 70% to95% for Glut3.In contrast, Glut1immunostaining
was negative in all the posttherapy specimens, and Glut3
immunostaining was positive in only three of eight (37.5%).
When Glut1 or Glut3 expression (in terms of positive rate,
intensity or staining score) in the pretherapy specimens was
compared with pretherapy PET/CT indices, such as mSUV,
MTV(2) or TLG(2) values, no significant correlation was
found (Table 2 and supplementary Table S1). However,
posttherapy mSUV, MTV(2) and TLG(2) values in the three
Glut3-positive and five Glut3-negative cases showed a
difference: 5.4–9.4 g/ml vs. 1.2–4.95 g/ml, 122.5–182.1 ml
vs. 0–100.8 ml, 344.2–543.9 g vs. 0–260.1 g, respectively.
Of the many FDG PET/CT indices, mSUV and TBR have
been most commonly used to evaluate tumour response. A
few studies have suggested that TBR and SUV are good
parameters for predicting the response of osteosarcoma to
chemotherapy [12–14]. Ye et al.  compared mSUV and
TBR in this context, and concluded that TBR is superior to
mSUV for estimating histological necrosis in osteosarcoma.
However, TBR measures tend to be nonreproducible and
appear to be less practical, because interpreters have to
draw ROIs manually along tumour boundaries and in the
corresponding contralateral normal areas. Very recent
studies evaluating the usefulness of SUV in predicting
response to neoadjuvant chemotherapy have shown that
post- to pretherapy mSUV ratio (or percent change in
mSUV) and posttherapy mSUV are correlated with histo-
logical response [24–26]. Furthermore, progression-free
survival is associated with posttherapy mSUV [24, 27].
In 1999, Larson et al.  introduced TLG as a
semiquantitative index of tumour treatment response.
Nevertheless, previous studies have failed to demonstrate
that TLG is comparable or superior to mSUVor mean SUV
Post-theraphy MTV (2.5)
chemotherapy in patient 4. a Despite a profound decrease in overall
18F-FDG accumulation in the right upper arm lesion after chemotherapy,
the maximum SUV showed a slight increase. b Significant reduction in
18F-FDG PET scans acquired before and after neoadjuvant
MTV at a SUV threshold of 2.5 g/ml (MTV(2.5)) is evident after
chemotherapy. Pretherapy and posttherapy MTV(2.5) values were
690.3 ml and 113.5 ml, respectively. c The removed tumour specimen
of patient 4 was almost completely composed of necrotic tissue (99%)
Table 3 Correlation between
PET/CT parameters and
pathological necrosis fractions
NA not assessed
ParameterEntire cohort (n=20)Prospective cohort (n=14)
46Eur J Nucl Med Mol Imaging (2012) 39:39–49
in predicting treatment response in bone and soft-tissue
sarcomas, although it is a conceptually attractive parameter.
Recently, Benz et al.  compared various indices of
tumour response, including SUV and CT-based TLG, in
soft-tissue sarcomas, and concluded that maximum or mean
TLG is less predictive of tumour response than maximum
or mean SUV. However, the situation might be quite
different in osteosarcoma, a tumour that does not shrink
to a great extent after neoadjuvant chemotherapy [27, 28].
In a study evaluating the predictability of TLG for
histological response to chemotherapy in patients with
osteosarcoma, good responses were weakly associated with
low pretherapy and posttherapy TLG, but not with change
in TLG . In that study, a threshold of 45% mSUV in the
VOI was used to determine TLG, which is much higher
than thresholds used in the present study. Application of
45% mSUV to our series would have resulted in tumour
areas that were much smaller than the real tumour masses.
Instead, we tested several TLG thresholds to determine
suitable indices. Moreover, MTVs, which were concordant
with pretherapy MRV, were used to determine tumour
volume, as the measurement of tumour volume on CT and
MRI images after therapy probably overestimates remain-
ing viable tumour portions because appreciable size
changes may not be evident even in patients with
osteosarcoma with a good treatment response as demon-
strated also in the current study (Table 2).
In the present study, post- to pretherapy rMTV(2) and
rTLG(2) as well as posttherapy mSUV in the entire cohort
correlated with treatment-induced tumour necrosis frac-
tions, but rSUV did not (Table 3). Recent studies have
repeatedly shown that posttherapy mSUV and rSUV or
percent change in mSUVare indicators of good histological
response [24–27]. When data acquired from prospectively
recruited patients were analysed separately, rSUV gained
statistical significance, suggesting that bias was poten-
tially introduced into our retrospectively obtained data.
However, except for this, much of our prospective data
were similar to those from the entire cohort (Table 3).
Separate analysis using the prospective data revealed that
posttherapy mSUV, MTV(2) and TLG(2), and post- to
pretherapy rMTV(2) and rTLG(2) showed differences
between GRs and PRs. rSUV showed a trend towards a
difference between the two groups, whereas post-therapy
MRV and rMRV showed no difference. These findings
indicate that combined metabolic/volumetric indices,
like metabolic indices, could be useful predictors of
pathological response to chemotherapy in osteosarcoma.
The sensitivity, specificity, PPV and NPV for predicting
a good response were 100%, 88.9%, 83.3% and 100%,
using a posttherapy mSUV cut-off of 3 g/ml (Table 4).
The PPV and NPV were comparable to those reported
We additionally obtained interim PET/CT information
from prospectively recruited patients after only one che-
motherapy course (except one patient), at the median time
of 7.8 weeks after the initiation of neoadjuvant chemother-
apy (Table 1). Interim mSUV, MTV(2) and TLG(2), and
interim to pretherapy rSUV, rMTV(2) and rTLG(2) all
showed differences between GRs and PRs. The sensitivity,
specificity, PPVand NPV for predicting a good histological
response using interim mSUV, MTV(2) and TLG(2) with
certain cut-off values were equally high (100%, 88.9%,
83.3% and 100%, respectively). Thus, it can be stated that
as with posttherapy analysis, combined metabolic and
volumetric indices as well as metabolic indices might be
useful indicators of a good histological response in interim
analysis. To our knowledge, this is the first report
addressing the use of early PET/CT indices for predicting
Table 4 Diagnostic indices of various PET/CT parameters in the prospective cohort (n=14)
ParameterCut-off AUCSensitivity (%) Specificity (%)PPV (%)NPV (%)Accuracy (%)
Eur J Nucl Med Mol Imaging (2012) 39:39–4947
Although Glut1 and Glut3 were expressed in the
majority of eight pretherapy tumour specimens, their
expression was not correlated with pretherapy mSUV,
MTV(2) or TLG(2) values (Table 2 and supplementary
Taken together, these findings have several implications.
First, we demonstrated that posttherapy MTVs and TLGs,
and post- to pretherapy rMTVs and rTLGs with certain
thresholds were comparable to posttherapy mSUVand post-
to pretherapy rSUV in evaluating treatment response in our
osteosarcoma patient population. A recent large series study
has also documented the usefulness of a combined
metabolic and volume index, the metabolic volume change
ratio, with respect to predicting histopathological tumour
response . Second, we demonstrated that interim MTVs
and TLGs, and interim to pretherapy rMTVs and rTLGs, as
well as interim mSUV and interim to pretherapy rSUV,
acquired early after one course of neoadjuvant chemother-
apy could discriminate GRs from PRs, possibly facilitating
earlier modifications to treatment strategy. Third, MTV
seems to represent viable tumour volumes, especially in the
posttherapy state of osteosarcoma, better than CT or MRI.
MTV is based on tumour metabolism and thus provides
information on tumour viability. The current study also
showed that changes in MR-based tumour volumes failed
to discriminate between GRs and PRs. We conveniently
calculated tumour volumes using MTVs with certain
thresholds, which matched those on pretherapy MR images
within ROIs. In this way, acquisition of tumour volumes
from posttherapy MR images, which might be greater than
the remaining viable lesion, was avoided. This has another
advantage of overcoming the difficulty in determining the
volume of the lesion from PET images due to limited
resolution. In the current study, convenient calculation of
MTV(2), MTV(2.5), TLG(2) and TLG(2.5) on a worksta-
tion avoided the possible introduction of bias in delineating
viable tumour volumes on each PET and posttherapy MR
image. Fourth, in situations where target lesions show
heterogeneous responses to treatment with heterogeneous
FDG uptake, MTV and TLG appear to match the whole
tumour burden better than mSUV. Histopathological
tumour response (the gold standard) is measured two-
dimensionally, and reflects whole viable tumour burden
rather than the residual most active regions, which are
more likely to be reflected by mSUV. One of our
patients exemplified this situation. The patient had a
slight increment in mSUV after treatment (10.39 g/ml to
11.84 g/ml), although the necrosis rate of the tumour was
99% (Table 2, patient 4). In contrast, posttherapy MTV
(2.5) and TLG(2.5) were markedly reduced by 83.6% and
87.0%, respectively (Fig. 3b). Thus, MTV and TLG might
supplement mSUV in this particular situation.
The present study had several inherent limitations. First,
our results were based on data obtained retrospectively and
prospectively. We thus subanalysed the prospectively
recruited group separately, yielding similar results. Second,
diverse chemotherapeutic regimens were utilized preclud-
ing survival analysis. Although no uniform regimen was
utilized in a study analysing PET response and outcome
, uneven distribution of other prognostic factors, such
as tumour size, location, stage and presence of metastasis in
our series divided according to PET/CT indices, invalidated
survival analysis. Third, even though only children and
young adults were enrolled, our results based on a small
patient population require confirmation in a larger cohort.
Combined metabolic/volumetric indices, including MTV,
TLG, rMTV and rTLG, with thresholds within certain
ranges, as well as metabolic indices, including mSUV and
rSUV, could be useful predictors of histological response to
neoadjuvant chemotherapy in osteosarcoma. Moreover,
these PET/CT indices were able to discriminate GRs from
PRs even after one chemotherapy course with high
predictability in our osteosarcoma patient population.
National Cancer Center, Korea (grant nos. 0710090 and 0710072–
2, in part).
This work was financially supported by the
Conflicts of interest
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