Schwannoma Clinical Trial
Official title:
Assessment of Volumetric Growth Rates of Spinal Intradural Extramedullary Schwannoma: A Longitudinal Study of Natural History
Spinal intradural schwannoma detected incidentally increased recently. Because there is
little knowledge about natural history of spinal schwannoma, there is no consensus of
treatment. Our hypothesis is as follows;
1. Some schwannomas keep growing, the others do not.
2. Foraminal schwannomas do not usually grow.
The investigators analyzed natural history and characteristics of 56 spinal schwannomas
observed initially with accurate and reliable methods. Here the investigators displayed
growing pattern and differential point of spinal schwannoma.
Study design and participants
The investigators included all patients who were diagnosed of spinal IDEM schwannoma by MR
imaging and checked follow-up MR imaging not undergoing surgical resection (including
radiosurgery). The patients usually checked follow-up MR imaging annually or biannually. The
patients who underwent surgical resection during the surveillance interval were also
enrolled.
Exclusion criteria of this study were as follows: 1) surgical resection at the diagnosis; 2)
von Recklinghausen' disease (neurofibromatosis); and 3) recurred or residual tumor. For
patients lost follow-up, the investigators checked whether the patients underwent a surgery
or not by telephone and obtained recent radiologic studies as possible.
Medical record and radiologic studies of enrolled patients were evaluated for patient
demographics, tumor level, main location (intracanal or foraminal), shape (globus, rugby
ball, or dumbbell), date at diagnosis, follow-up date at check follow-up MR imaging, and
length of follow-up. These serial studies were compared with tumor growth to evaluate for
any correlation.
Tumor volume measurement and growth
The investigators measured tumor volume by volume quantification method using the Leksell
Gamma Plan® system (version, 10.1.1. Elekta Instrument AB, Stockholm, Sweden) in Figure 1.
It calculates tumor volume by summation of cylindrical masses from each image and has an
advantage to measure with the best accuracy especially non-globus tumor.6 The process of
measuring tumor volume was rigorously designed to minimize observer subjectivity. Stack
images without gap were loaded to the program. The investigators draw the tumor outlining by
manually in select planes of each orthogonal view. The program measures tumor volume using
an algorithm based on scattered data interpolation with radial basis functions. All tumor
volumes were measured independently by two observers. Interobserver reliabilities were
assessed by the Brand-Altman plot. The plot was applied to look for trends in the data that
produce similar results and to evaluate the agreement between two observers.7 Under the
confidence of excellent interobserver agreement marks, the investigators finally estimated
the tumor volume as the mean value of two measured data.
Volumetric growth rate (VGR) of the tumor was calculated volume change to the baseline
volume and presented in percent. Overall VGR (%) was calculated using the following formula:
(Final volume-Baseline volume)x100/Baseline volume. Annual VGR (%) was calculated as
follows; Annual VGR (%)=(Final vol.-Baseline vol.)/(Baseline vol.)*FU
duration(days)*12/365*100 FU and vol. mean follow-up and volume, respectively. There is no
consensus about definition and amount of tumor growth. A prior study reported that the
cut-off value of growth rate of vestibular schwannoma extending into the cerebello-pontine
angle was 10.4%. The investigators set 10% increase of VGR as a cut-off value. The
investigators made two standards, 10% increase of overall and annual VGR, and evaluate
validity by the receiver operating characteristic (ROC) curve. Enrolled patients were
divided into two groups by the standard. The first group, growing tumor, was defined as mean
≥10% increase of tumor volume. The other group, stable tumor, was defined as mean <10%
increase, stationary, or decrease of tumor volume.
Statistical analysis
The investigators used the Brand-Altman plot for interobserver reliability. The
investigators used the ROC analysis to compare predictive validity of standards by overall
VGR and annual VGR, and to find out their optimal cut-off values of annual VGR in growing
schwannomas. Because the area under the curve is a measure of the diagnostic power of a
test, larger one is chosen as a standard dividing growing versus stable tumor. ROC curves
were plotted using measures of sensitivity and specificity based on various cut-off values.
Cut-off value was selected as the values closer to the upper left corner. For comparative
analyses between the growing and stable tumor group, independent t tests for continuous
variables, Fisher's exact test, and chi-square test were used. The significance level was
set at p < 0.05. The investigators used MedCalc Statistical Software version 12.7.2 (MedCalc
Software bvba, Ostend, Belgium) for the Bland-Altman plot and the SPSS statistical package
(Version 20.0; SPSS Inc, Chicago, IL, USA) for the other data analysis.
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Observational Model: Cohort, Time Perspective: Retrospective
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