First, a total of 296 patients who received whole-body 18F-FDG PET/CT examinations between December 2011 and March 2018 were retrospectively reviewed. All patients were successively assigned into equation (106 men and 93 women) and validation (54 men and 43 women) groups. Then, patients with solid tumours who underwent 18F-FDG PET/CT before and after treatment were retrospectively retrieved as the application group between the same periods. The inclusion criteria of this group were as follows: non-diabetic, still-existing 18F-FDG-avid lesions and no appearance of new 18F-FDG-avid lesions after treatment. Finally, a total of 241 patients (145 men and 96 women) were included in this study, including 72 with non–small cell lung cancer, 53 with hand and neck tumours, 46 with breast cancer, 22 with oesophageal cancer, and 48 with colorectal cancer. The study was approved by the institutional review board of the First Affiliated Hospital of Jinan University and complied with national legislation and the Declaration of Helsinki guidelines. All patients gave consent to use their 18F-FDG PET/CT results and relevant clinical data for this study.
All 18F-FDG PET/CT examinations were performed with the same protocol using a GE Discovery PET/CT 690 system. PET/CT images were acquired 50 to 70 min after intravenous injection of 18F-FDG at a dose of 0.08-0.10 mCi/kg body weight. The scanning range covered the whole-body for the equation and validation groups, and covered from the top of the skull to mid-thigh for the application group. CT data were acquired in breath-hold with 120 kV, 80-160 mA modulated using the GE AutomA technique with a slice thickness of 3.75 mm, slice interval of 3.27 mm, pitch of 1.375, matrix size of 512 ×512 and scan field-of-view of 50 cm. PET data were acquired in 3D time-of-flight (TOF) mode with a 2-min scan per bed position, slice thickness of 3.27 mm, slice interval of 3.75 mm, matrix size of 192×192 and scan field-of-view of 70 cm. The PET data were reconstructed in terms of the point spread function (PSF) together with TOF technology.
Estimated LBM from the LC images: Method development and validation
Fat tissues were defined as voxels identified and measured by CT as having CT numbers between −190 and −30 Hounsfield units. A built-in software package of the Advantage Workstation (GE Healthcare) was used to calculate fat volumes (FV). A fat-tissue average density of 0.923g/mL was applied to convert whole-body FV to whole-body fat mass (FMWB) . LC images were obtained by truncating whole-body images. The LC region was defined from top level of the thorax to distal point of the ischium. All image slices outside of this region were omitted. The volumes of LC fat tissues (FVLC) were measured using the same method.
Traditionally, LBM was equivalent to the fat free mass (FFM) . Because, in practice, the FMWB cannot be measured in conventional PET/CT examination, the relationships between FMWB and FVLC were analysed in the populations from the equation group, and an equation was developed using FMWB as the dependent variable and FVLC as independent variables. Subsequently, the LBM could be estimated from LC images (LBMLC) according to the following equation:
LBMLC (kg) = W (kg) - (α+β×FVLC) (kg) Eq.1
where α and β are the intercept and slope of the equation we developed, respectively.
To test the reliability of this method, LBM by LC images was compared with those derived by the James PE in an independent sample of 97 patients from the validation group. The reference standard was the measurement of LBM from whole-body CT. The James PE was defined as follows:
LBMPE (kg) =1.10×W-120× (W/H)2 (for male)
LBMPE (kg) = 1.07×W-148× (W/H)2 (for female) Eq.2
where W is weight in kg, and H is height in cm.
The therapeutic responses were analysed with PET volume computer-assisted reading (PET VCAR) of the Advantage Workstation (GE Healthcare). PET VCAR, using the James PE to estimate LBM and then measuring the SULpeak of target lesion (SULpeak-PE), is one program the clinician can use to assist in monitoring treatment response according to PERCIST 1.0. The detailed instructions for PET VCAR were described in our previous study . According to the LBMPE calculated by Equation 2 and the SULpeak-PE of target lesion measured by PET VCAR, the LC images-based SULpeak (SULpeak-LC) of the same target lesion could be calculated.
As defined in PERCIST 1.0 , we chose the hottest lesion as the target lesion on the baseline and subsequent follow-up scans. The hottest lesion on the follow-up scan could be a lesion different from the previously measured lesion, on the assumption that it had been present since baseline. On the basis of the variation of SULpeak-PE and SULpeak-LC between the baseline and follow-up scans, patients were classified as partial metabolic response (PMR), stable metabolic disease (SMD), and progressive metabolic disease (PMD) separately according to PERCIST 1.0.
The patients’ characteristics were presented as mean values and standard deviations. The unpaired t-test was used to analyse the differences in patients’ characteristics between the equation and validation groups. For the equation group, Pearson correlation coefficients (r) were used to evaluate the relationship between the FVLC and FMWB. Then, simple linear regression was applied to generate equation to estimate FMWB from FVLC. The populations from the validation group were used for cross-validation: paired t-test and Bland-Altman plots were used separately to examine the difference and agreement between the outcomes of LBMPE and LBMLC and the reference standard.
The paired t-test was used to evaluate the differences in the same parameters between before and after treatment for the application group. Concordance and differences among the PERCIST 1.0 results of these two methods were assessed using Cohen’s κ coefficient and Wilcoxon’s signed-ranks test. Furthermore, to evaluate the impact of the LBM algorithm on assessment of the therapeutic response, we first analysed the distribution of SULpeak-PE variation in patients with discordant response classifications. Subsequently, the variation of the LBMPE and LBMLC was evaluated in these patients. Graphs and analyses were performed using Prism GraphPad and the SPSS software.