A series of 17 point sources with an activity of 185.3 kBq ± 5% and aligned in a geometry of a cross shape with a separate distance of 40.0 mm apart were utilized to measure the image resolution of reconstructed images. An International Electrotechnical Commission (IEC) 61675-1 emission phantom (NEMA phantom) consist of the shape of an upper human body and 6 hollow glass spheres (inner diameters 37, 28, 22, 17, 13, and 10 mm) was employed to measure the image contrast and uniformity of reconstructed images. The background volume of the NEMA phantom and the 6 spheres were filled with 18F-FDG mixed with pure water using a roughly 10:1 sphere-to-background activity concentration ratio. The initial tracer activity concentration was specifically calibrated to the start of the measurement: 15.1 kBq/mL ± 1% in the phantom background and 168.6 kBq/mL ± 5% in the 6 small spheres.
The prospective patient study consisted of 61 tumor lesions from 15 patients [13 males and 2 females; aged 46–79 years old, with a mean age of (62.5±8.8) years] whose thoracic carcinomas were histologically confirmed between July 2014 and August 2015 (10 lung cancers, 2 lung cancers accompanied with gastric cancer, 1 thymic carcinoma, 1 pleural mesothelioma, 1 esophagus cancer). Patient characteristic and pathological diagnosis of tumor lesions are listed in Table 1. All patients underwent both thoracic 18F-FDG Co-SPECT/CT and 18F-FDG PET/CT scans. This study adopted the standard protocol to require patient fasting and resting for at least 6 hours that ensured <8.3 mmol/L blood sugar level prior to the intravenous administration of FDG. For each patient, FDG dose was determined by a weight formula (3.7 MBq/kg body weight). Forty minutes post the FDG injection, the Co-SPECT/CT scan was started, and upon the completion of scan, the PET/CT scan was intermediately followed. Each patient signed the informed consent form approved by the medical ethics committee of China-Japan Friendship Hospital.
Patients Gender Age (year) Height (cm) Weight (kg) No. of tumor lesions Pathological diagnosis 1 Male 57 175 65 1 Esophagus cancer 2 Male 60 160 61 4 Thymic carcinoma 3 Male 71 171 67 1 Lung adenosquamous carcinoma 4 Male 68 168 85 3 Lung squamous carcinoma 5 Male 79 176 72 8 Lung adenocarcinoma 6 Male 58 164 75 3 Lung adenocarcinoma 7 Male 69 170 71 6 Lung adenocarcinoma 8 Female 51 165 55 3 Lung adenocarcinoma 9 Male 65 171 65 2 Lung adenocarcinoma 10 Male 61 170 55 8 Lung adenocarcinoma and gastric cancer 11 Male 63 160 53 6 Gastric cancer 12 Male 69 178 55 1 Lung squamous carcinoma 13 Male 46 168 78 10 Pleural mesothelioma 14 Female 69 160 69 3 Lung adenocarcinoma 15 Male 52 180 90 2 Lung adenocarcinoma
Table 1. Patient characteristics and pathological diagnosis of tumor lesions
18F-FDG Co-SPECT/CT scan was performed on a GE Hawkeye Infinia SPECT/CT scanner (GE Healthcare, USA) equipped with two 2.54 cm NaI (Tl) crystals, ultra-fast coincidence detection system (CoDe8 VARICAM circuitry) and lead-tin-copper septa for 2D 511-keV coincidence data acquisition. An integrated low-dose CT system was integrated for patient positioning and attenuation correction. Prior to the Co-SPECT acquisition, a topogram was acquired for patient positioning. The coincidence emission data was acquired with the setting of 12-degree axial acceptance, 128×128 matrix, 4.0 mm pixel size, 460–562 keV energy window, 64 projections within 360-degree continuous and repetitive rotations for total 30 minutes scan time. The CT transmission data was acquired with 140 kVp and 2.5 mA for 10 minutes. Conventional Co-SPECT images with CT attenuation correction were reconstructed by the vendor provided system implementing ordered subsets expectation maximization (OSEM) (20 iterations and 2 subsets) and intermediate Gauss filter every 4 iterations. Quantitative Co-SPECT images were reconstructed by a separated software AllSUVQ (China) utilizing OSEM (5 iterations and 8 subsets) with CT attenuation correction, resolution recovery with specially-dependent point spread functions (PSF), scatter correction with the model-based method and reconstruction-based nose filter to correct for physical interference in images[10–14]. For quantitative Co-SPECT images, pixel intensity was converted to a physical unit (Bq/mL) using a conversion factor obtained from a separated study with a uniform phantom.
18F-FDG PET/CT scan was performed on a GE Discovery Elite (690) PET/CT scanner (GE Healthcare). Prior to PET imaging, a low-dose CT scan was acquired craniocaudally during shallow breathing. Effective tube current was 80 mA, tube voltage of 140 kV and care dose switched on. Slice thickness was 3.75 mm, and bed speed was 39.37 mm/s with pitch of 0.984. PET imaging was performed in 3D mode with time of flight (TOF) as 2.5 minutes per bed position at an axial sampling thickness of 3.25 mm per slice and 15.7 cm field of view. The vendor provided PET image reconstruction utilizes coincidence events from a delayed coincidence window for random correction and a model-based approach for scatter correction. 3D TOF PET images were reconstructed with OSEM (24 subsets and 2 iterations), filter cut-off 6.4 mm and the PSF with enhanced image resolution.
For the study of point sources aligned in a cross shape, image resolution was assessed by the full width at half maximum (FWHM) of each point in in-plane and axial directions. For the study of NEMA phantom, image contrast was defined as (the intensity of largest sphere-background activity) background activity. Image uniformity was calculated by (SD/mean) in background area using a region of interest (ROI) with 25 mL. To evaluate the quantitative accuracy for measurement of F-18 activity concentrations in 6 spheres, measured values were compared to the corresponded true values in quantitative Co-SPECT and PET images. Accuracy curves as functions of diameters were plotted to depict the impact of partial volume effect (PVE) for decreased diameters. Additionally, mean activity concentration in background area was also measured to assess the accuracy without PVE. For the patient study, analysis of metabolic uptake in 18F-FDG-avid tumor lesions for quantitative Co-SPECT and PET images was accomplished in a dedicated reporting workstation (MedEx, China) to measure the maximum and mean standardized uptake values (SUVmax and SUVmean), peak lean body mass SUV (SULpeak) and metabolic tumor volume (MTV) in the lesions of interest. By definition, SUVmax is the highest value of SUV within a ROI. The SUVmean is the average value of SUV within the region of interest with the default threshold as 40% SUVmax. The SULpeak is the averaged SUV in a spherical ROI with 1.0 mL centering around the hottest point in the tumor foci corrected for lean body mass. MTV is the volume of the tumor lesion with the default threshold above 2.5 SUV. Further analysis for SUVmean and MTV obtained from quantitative Co-SPECT against PET was also performed to verify the stability of measurement under various levels of threshold values as 30%–50% SUVmax for SUVmean and 2.8–40 SUV for MTV.
For the patient study, difference of functional parameters (SUVmax, SUVmean, SULpeak and MTV) from quantitative Co-SPECT and PET were verified by paired t-test. A P<0.05 was considered significant. Using functional parameters from PET images as the reference standard, linear regression was performed to obtain the correlation of functional parameters form quantitative Co-SPECT with PET images. All the statistical data analysis was performed with a commercialized software (GraphPad Prism V5.0, USA).
Performance of conventional Co-SPECT, quantitative Co-SPECT and PET for a series of line sources and NEMA phantom were listed in Table 2 with corresponded images shown in Fig. 1 and Fig. 2. With full physical corrections, mean image resolution of Co-SPECT was improved from (13.1±1.2) mm to (9.5±0.8) mm in the in-plane direction and from (13.5±1.1) mm to (9.8±0.7) mm in the axial direction. The image contrast was enhanced from 1.79 to 6.32. As a tradeoff, the image uniformity in background area were slightly degraded from 3.1% to 6.7%. For PET images, the in-plane image resolution was (7.4±0.4) mm and (7.6±0.5) mm for the axial direction. The image uniformity was 5.6%. Fig. 3 demonstrates the accuracy curves of quantitative Co-SPECT and PET images to measure the activity concentration as functions of sphere diameters. Among spheres with diameters ≥28 mm, the accuracy to measure F-18 activity concentration for quantitative Co-SPECT was >97.1% and gradually declined when smaller diameters decreased due to increased PVE. For PET, the >98.5% accuracy was observed for spheres with diameters ≥17 mm. In the background area of NEMA phantom without PVE, both quantitative SPECT and PET demonstrated >99% accuracy.
Image parameters Conventional Co-SPECT Quantitative Co-SPECT PET In-plane image resolution (mm) *, +13.1±1.2 &9.5±0.8 7.4±0.4 Axial image resolution (mm) *, +13.5±1.1 &9.8±0.7 7.6±0.5 Image contrast *, +1.79 6.32 6.69 Image uniformity *, +3.1% 6.7% 5.6% *significant difference between conventional Co-SPECT and quantitative Co-SPECT (P<0.05); +significant difference between conventional Co-SPECT and PET; &significant difference between quantitative Co-SPECT and PET (P<0.05).
Table 2. Parametric performance of Co-SPECT and PET images for NEMA phantom
Fig. 4 represents conventional Co-SPECT, quantitative Co-SPECT and PET images of a patient with histologically confirmed lung adenocarcinoma. From visual assessment, quantitative Co-SPECT outperformed conventional Co-SPECT mainly with higher image resolution and contrast moving closer to PET. Among 15 patients and 61 tumor lesions, functional parameters of quantitative Co-SPECT were significantly different from those of PET. Mean difference of SUVmax as (Co-SPECT-PET) was –1.822 g/mL, and (–1.250 g/mL, –1.808 g/mL, 34.97 mL) for SUVmean, SULpeak and MTV (all P<0.0025). Nonetheless, linear regression of SUVmax revealed strong correlation and close to unity slope for quantitative Co-SPECT and PET as r=0.8218 (95% CI, 0.7186–0.8895) and y=1.0804x−2.7765 (Fig. 5). Linear regression for SUVmean and SULpeak demonstrated similar findings as r=0.8390 (95% CI, 0.7444–0.9005) and y=1.0601x−1.679, and r=0.8171 (95% CI, 0.7116–0.8865) and y=0.9736x−1.5318, respectively. For the MTV measurement, the correlation between quantitative Co-SPECT and PET remained strong as r=0.8791 (95% CI, 0.8056–0.9260), but relatively increased slope and offset as y=1.2021x+20.037. In the verification of measurement tendency for SUVmean by testing the threshold of 30%~50% SUVmax, correlations with PET stayed similar (r=0.8315–0.8413) (Fig. 6). The range of slope and offset in linear regression were (0.893–1.2197) and (−1.3276–−2.0431) (g/mL). In the verification of measurement tendency for MTV by testing the threshold of 2.8–4.0 SUV, the threshold of 2.8 SUV showed the highest correlation (r=0.8779) (Fig. 7). The slope and offset in linear regression were 1.0198 and 16.746 (mL).
Figure 4. Representative images from a patient with histologically confirmed lung adenocarcinoma in maximum intensity projection and coronal view.
Figure 5. Linear regression for SUVmax, SUVmean, SULpeak and MTV obtained from quantitative Co-SPECT and compared to those of PET.
Figure 6. Linear regression for SUVmean obtained from quantitative Co-SPECT with different thresholds of % SUVmax (30%–50%) compared to those of PET.
Improved image resolution on thoracic carcinomas by quantitative 18F-FDG coincidence SPECT/CT in comparison to 18F-FDG PET/CT
- Received Date: 2019-01-04
- Accepted Date: 2019-06-04
- Rev Recd Date: 2019-05-21
- Available Online: 2019-08-16
- Publish Date: 2020-07-01
- 18F-FDG /
- coincidence SPECT/CT /
- full physical corrections /
- thoracic carcinomas /
- image quantitation
Abstract: Currently, 18F-FDG coincidence SPECT (Co-SPECT)/CT scan still serves as an important tool for diagnosis, staging, and evaluation of cancer treatment in developing countries. We implemented full physical corrections (FPC) to Co-SPECT (quantitative Co-SPECT) to improve the image resolution and contrast along with the capability for image quantitation. FPC included attenuation, scatter, resolution recovery, and noise reduction. A standard NEMA phantom filled with 10:1 F-18 activity concentration ratio in spheres and background was utilized to evaluate image performance. Subsequently, 15 patients with histologically confirmed thoracic carcinomas were included to undergo a 18F-FDG Co-SPECT/CT scan followed by a 18F-FDG PET/CT scan. Functional parameters as SUVmax, SUVmean, SULpeak, and MTV from both quantitative Co-SPECT and PET were analyzed. Image resolution of Co-SPECT for NEMA phantom was improved to reveal the smallest sphere from a diameter of 28 mm to 22 mm (17 mm for PET). The image contrast was enhanced from 1.7 to 6.32 (6.69 for PET) with slightly degraded uniformity in background (3.1% vs. 6.7%) (5.6% for PET). Patients' SUVmax, SUVmean, SULpeak, and MTV measured from quantitative Co-SPECT were overall highly correlated with those from PET (r=0.82–0.88). Adjustment of the threshold of SUVmax and SUV to determine SUVmean and MTV did not further change the correlations with PET (r=0.81–0.88). Adding full physical corrections to Co-SPECT images can significantly improve image resolution and contrast to reveal smaller tumor lesions along with the capability to quantify functional parameters like PET/CT.
|Citation:||Yuming Zheng, Chaoling Jin, Huijuan Cui, Haojie Dai, Jue Yan, Pingping Han, Bailing Hsu. Improved image resolution on thoracic carcinomas by quantitative 18F-FDG coincidence SPECT/CT in comparison to 18F-FDG PET/CT[J]. The Journal of Biomedical Research, 2020, 34(4): 309-317. doi: 10.7555/JBR.33.20190004|