The Netherlands protocol for standardisation and quantification of FDG whole body PET studies in multi-centre trials

Introduction  Several studies have shown the usefulness of positron emission tomography (PET) quantification using standardised uptake values (SUV) for diagnosis and staging, prognosis and response monitoring. Many factors affect SUV, such as patient preparation procedures, scan acquisition, image reconstruction and data analysis settings, and the variability in methodology across centres prohibits exchange of SUV data. Therefore, standardisation of 2-[¹⁸F] fluoro-2-deoxy-D-glucose (FDG) PET whole body procedures is required in multi-centre trials. Methods  A protocol for standardisation of quantitative FDG whole body PET studies in the Netherlands (NL) was defined. This protocol is based on standardisation of: (1) patient preparation; (2) matching of scan statistics by prescribing dosage as function of patient weight, scan time per bed position, percentage of bed overlap and image acquisition mode (2D or 3D); (3) matching of image resolution by prescribing reconstruction settings for each type of scanner; (4) matching of data analysis procedure by defining volume of interest methods and SUV calculations and; (5) finally, a multi-centre QC procedure is defined using a 20-cm diameter phantom for verification of scanner calibration and the NEMA NU 2 2001 Image Quality phantom for verification of activity concentration recoveries (i.e., verification of image resolution and reconstruction convergence). Discussion  This paper describes a protocol for standardization of quantitative FDG whole body multi-centre PET studies. Conclusion  The protocol was successfully implemented in the Netherlands and has been approved by the Netherlands Society of Nuclear Medicine. An erratum to this article can be found at     

符合线路显像与PET显像中SUV的比较研究

目的比较符合线路显像标准摄取值(SUV)与PET显像的SUV。方法用双探头符合显像仪及PET对模型显像，分别采用不同的重建算法重建，测定图像上热灶的SUV。结果对直径小于30mm热灶，相同大小时，PET、得到的SUV高于符合线路显像；无论对PET还是符合线路显像，随热灶大小增加SUV增加；SUV与重建算法有关；选取的感兴趣区(ROI)越大，获得的SUV越小；由PET图像获得的热灶SUV可见，当热灶大于2倍的系统分辨率时，SUCmax接近热灶的真实值(SUVmax)。结论符合线路显像的SUV低于PET显像；病灶大小、重建算法、ROI大小均影响SUV。     

Effects of noise, image resolution, and ROI definition on the accuracy of standard uptake values: a simulation study.

Semiquantitative standard uptake values (SUVs) are used for tumor diagnosis and response monitoring. However, the accuracy of the SUV and the accuracy of relative change during treatment are not well documented. Therefore, an experimental and simulation study was performed to determine the effects of noise, image resolution, and region-of-interest (ROI) definition on the accuracy of SUVs. METHODS: Experiments and simulations are based on thorax phantoms with tumors of 10-, 15-, 20-, and 30-mm diameter and background ratios (TBRs) of 2, 4, and 8. For the simulation study, sinograms were generated by forward projection of the phantoms. For each phantom, 50 sinograms were generated at 3 noise levels. All sinograms were reconstructed using ordered-subset expectation maximization (OSEM) with 2 iterations and 16 subsets, with or without a 6-mm gaussian filter. For each tumor, the maximum pixel value and the average of a 50%, a 70%, and an adaptive isocontour threshold ROI were derived as well as with an ROI of 15 x 15 mm. The accuracy of SUVs was assessed using the average of 50 ROI values. Treatment response was simulated by varying the tumor size or the TBR. RESULTS: For all situations, a strong correlation was found between maximum and isocontour-based ROI values resulting in similar dependencies on image resolution and noise of all studied SUV measures. A strong variation with tumor size of > or =50% was found for all SUV values. For nonsmoothed data with high noise levels this variation was primarily due to noise, whereas for smoothed data with low noise levels partial-volume effects were most important. In general, SUVs showed under- and overestimations of > or =50% and depended on all parameters studied. However, SUV ratios, used for response monitoring, were only slightly dependent of ROI definition but were still affected by noise and resolution. CONCLUSION: The poor accuracy of the SUV under various conditions may hamper its use for diagnosis, especially in multicenter trials. SUV ratios used to measure response to treatment, however, are less dependent on noise, image resolution, and ROI definition. Therefore, the SUV might be more suitable for response-monitoring purposes.     

FDG-PET standardized uptake values in normal anatomical structures using iterative reconstruction segmented attenuation correction and filtered back-projection

Filtered back-projection (FBP) is the most commonly used reconstruction method for PET images, which are usually noisy. The iterative reconstruction segmented attenuation correction (IRSAC) algorithm improves image quality without reducing image resolution. The standardized uptake value (SUV) is the most clinically utilized quantitative parameter of [fluorine-18]fluoro-2-deoxy-D-glucose (FDG) accumulation. The objective of this study was to obtain a table of SUVs for several normal anatomical structures from both routinely used FBP and IRSAC reconstructed images and to compare the data obtained with both methods. Twenty whole-body PET scans performed in consecutive patients with proven or suspected non-small cell lung cancer were retrospectively analyzed. Images were processed using both IRSAC and FBP algorithms. Nonquantitative or gaussian filters were used to smooth the transmission scan when using FBP or IRSAC algorithms, respectively. A phantom study was performed to evaluate the effect of different filters on SUV. Maximum and average SUVs (SUVmax and SUVavg) were calculated in 28 normal anatomical structures and in one pathological site. The phantom study showed that the use of a nonquantitative smoothing filter in the transmission scan results in a less accurate quantification and in a 20% underestimation of the actual measurement. Most anatomical structures were identified in all patients using the IRSAC images. On average, SUVavg and SUVmax measured on IRSAC images using a gaussian filter in the transmission scan were respectively 20% and 8% higher than the SUVs calculated from conventional FBP images. Scatterplots of the data values showed an overall strong relationship between IRSAC and FBP SUVs. Individual scatterplots of each site demonstrated a weaker relationship for lower SUVs and for SUVmax than for higher SUVs and SUVavg. A set of reference values was obtained for SUVmax and SUVavg of normal anatomical structures, calculated with both IRSAC and FBP image reconstruction algorithms. The use of IRSAC and a gaussian filter for the transmission scan seems to give more accurate SUVs than are obtained from conventional FBP images using a nonquantitative filter for the transmission scan.     

Evaluation of strategies towards harmonization of FDG PET/CT studies in multicentre trials: comparison of scanner validation phantoms and data analysis procedures

Purpose

PET quantification based on standardized uptake values (SUV) is hampered by several factors, in particular by variability in PET acquisition settings and data analysis methods. Quantitative PET/CT studies acquired during a multicentre trial require harmonization of imaging procedures to maximize study power. The aims of this study were to determine which phantoms are most suitable for detecting differences in image quality and quantification, and which methods for defining volumes of interest (VOI) are least sensitive to these differences.

Methods

The most common accreditation phantoms used in oncology FDG PET/CT trials were scanned on the same scanner. These phantoms were those used by the Society of Nuclear Medicine Clinical Trials Network (SNM-CTN), the European Association of Nuclear Medicine/National Electrical Manufacturers Association (EANM/NEMA) and the American College of Radiology (ACR). In addition, tumour SUVs were derived from ten oncology whole-body examinations performed on the same PET/CT system. Both phantom and clinical data were reconstructed using different numbers of iterations, subsets and time-of-flight kernel widths. Subsequently, different VOI methods (VOI_A50%, VOI_max, VOI_3Dpeak, VOI_2Dpeak) were applied to assess the impact of changes in image reconstruction settings on SUV and recovery coefficients (RC).

Results

All phantoms demonstrated sensitivity for detecting changes in SUV and RC measures in response to changes in image reconstruction settings and VOI analysis methods. The SNM-CTN and EANM/NEMA phantoms showed almost equal sensitivity in detecting RC differences with changes in image characteristics. Phantom and clinical data demonstrated that the VOI analysis methods VOI_A50% and VOI_max gave SUV and RC values with large variability in relation to image characteristics, whereas VOI_3Dpeak and VOI_2Dpeak were less sensitive to these differences.

Conclusion

All three phantoms may be used to harmonize parameters for data acquisition, processing and analysis. However, the SNM-CTN and EANM/NEMA phantoms are the most sensitive to parameter changes and are suitable for harmonizing SUV quantification based on 3D VOIs, such as VOI_A50% and VOI_3Dpeak, and VOI_max. Variability in SUV quantification after harmonization could be further minimized using VOI_3Dpeak analysis, which was least sensitive to residual variability in image quality and quantification.     

FDG-PET standardized uptake values in normal anatomical structures using iterative reconstruction segmented attenuation correction and filtered back-projection

Filtered back-projection (FBP) is the most commonly used reconstruction method for PET images, which are usually noisy. The iterative reconstruction segmented attenuation correction (IRSAC) algorithm improves image quality without reducing image resolution. The standardized uptake value (SUV) is the most clinically utilized quantitative parameter of [fluorine-18]fluoro-2-deoxy-D-glucose (FDG) accumulation. The objective of this study was to obtain a table of SUVs for several normal anatomical structures from both routinely used FBP and IRSAC reconstructed images and to compare the data obtained with both methods. Twenty whole-body PET scans performed in consecutive patients with proven or suspected non-small cell lung cancer were retrospectively analyzed. Images were processed using both IRSAC and FBP algorithms. Nonquantitative or gaussian filters were used to smooth the transmission scan when using FBP or IRSAC algorithms, respectively. A phantom study was performed to evaluate the effect of different filters on SUV. Maximum and average SUVs (SUV_max and SUV_avg) were calculated in 28 normal anatomical structures and in one pathological site. The phantom study showed that the use of a nonquantitative smoothing filter in the transmission scan results in a less accurate quantification and in a 20% underestimation of the actual measurement. Most anatomical structures were identified in all patients using the IRSAC images. On average, SUV_avg and SUV_max measured on IRSAC images using a gaussian filter in the transmission scan were respectively 20% and 8% higher than the SUVs calculated from conventional FBP images. Scatterplots of the data values showed an overall strong relationship between IRSAC and FBP SUVs. Individual scatterplots of each site demonstrated a weaker relationship for lower SUVs and for SUV_max than for higher SUVs and SUV_avg. A set of reference values was obtained for SUV_max and SUV_avg of normal anatomical structures, calculated with both IRSAC and FBP image reconstruction algorithms. The use of IRSAC and a gaussian filter for the transmission scan seems to give more accurate SUVs than are obtained from conventional FBP images using a nonquantitative filter for the transmission scan.     

Analysis of FDG uptake with hybrid PET using standardised uptake values

The standardised uptake value (SUV) has been used as an index of glucose metabolism to classify malignant tumours. To date, calculation of SUVs has been restricted to dedicated PET. The aim of this study was to investigate the feasibility of SUV calculation with attenuation-corrected hybrid PET, applying a singles count rate-related calibration method. Calibration factors for hybrid PET at different singles count rates were determined by phantom studies. SUVs were determined for hot spheres in a phantom study as well as for 68 malignant lesions in 56 patients. Recovery coefficients calculated for hot spheres were applied to SUVs of malignant lesions to correct for partial volume and recovery effects. At a sphere-to-background ratio of 10:1, SUVs of spheres with diameters from 34 to 16 mm varied from 5.0 to 1.5 for hybrid PET, and from 8.0 to 4.3 for dedicated PET. SUVs of malignant lesions calculated by hybrid and dedicated PET showed a strong correlation (r=0.95, P<0.001), with a mean percentage difference of 36%. SUVs calculated by hybrid PET were significantly lower than SUVs calculated by dedicated PET (6.2+/-4.3 vs 8.5+/-5.3, P<0.001). Application of recovery coefficients revealed an SUV of 12.2+/-7.3 for hybrid PET versus 10.8+/-6.3 for dedicated PET, with a significant reduction in the mean percentage difference (22%, P<0.01). In conclusion, singles count rate-related calibration factors allow calculation of SUVs with hybrid PET for lesions with a diameter larger than 15 mm. Correction for partial volume and recovery effects is needed to improve the agreement of SUVs of lesions determined by hybrid PET and dedicated PET.     

Influence of OSEM and segmented attenuation correction in the calculation of standardised uptake values for [18F]FDG PET

Standardised Uptake Values (SUVs) are widely used in positron emission tomography (PET) as a semi-quantitative index of fluorine-18 labelled fluorodeoxyglucose uptake. The objective of this study was to investigate any bias introduced in the calculation of SUVs as a result of employing ordered subsets-expectation maximisation (OSEM) image reconstruction and segmented attenuation correction (SAC). Variable emission and transmission time durations were investigated. Both a phantom and a clinical evaluation of the bias were carried out. The software implemented in the GE Advance PET scanner was used. Phantom studies simulating tumour imaging conditions were performed. Since a variable count rate may influence the results obtained using OSEM, similar acquisitions were performed at total count rates of 34 kcps and 12 kcps. Clinical data consisted of 100 patient studies. Emission datasets of 5 and 15 min duration were combined with 15-, 3-, 2- and 1-min transmission datasets for the reconstruction of both phantom and patient studies. Two SUVs were estimated using the average (SUVavg) and the maximum (SUVmax) count density from regions of interest placed well inside structures of interest. The percentage bias of these SUVs compared with the values obtained using a reference image was calculated. The reference image was considered to be the one produced by filtered back-projection (FBP) image reconstruction with measured attenuation correction using the 15-min emission and transmission datasets for each phantom and patient study. A bias of 5%-20% was found for the SUVavg and SUVmax in the case of FBP with SAC using variable transmission times. In the case of OSEM with SAC, the bias increased to 10%-30%. An overall increase of 5%-10% was observed with the use of SUVmax. The 5-min emission dataset led to an increase in the bias of 25%-100%, with the larger increase recorded for the SUVmax. The results suggest that OSEM and SAC with 3 and 2 min transmission may be reliably used to reduce the overall data acquisition time without compromising the accuracy of SUVs.     

Standardised uptake values from PET/CT images: comparison with conventional attenuation-corrected PET

Purpose In PET/CT, CT-derived attenuation factors may influence standardised uptake values (SUVs) in tumour lesions and organs when compared with stand-alone PET. Therefore, we compared PET/CT-derived SUVs intra-individually in various organs and tumour lesions with stand-alone PET-derived SUVs. Methods Thirty-five patients with known or suspected cancer were prospectively included. Sixteen patients underwent FDG PET using an ECAT HR+scanner, and subsequently a second scan using a Biograph Sensation 16PET/CT scanner. Nineteen patients were scanned in the reverse order. All images were reconstructed with an iterative algorithm (OSEM). Suspected lesions were grouped as paradiaphragmatic versus distant from the diaphragm. Mean and maximum SUVs were also calculated for brain, lung, liver, spleen and vertebral bone. The attenuation coefficients (μ values) used for correction of emission data (bone, soft tissue, lung) in the two data sets were determined. A body phantom containing six hot spheres and one cold cylinder was measured using the same protocol as in patients. Results Forty-six lesions were identified. There was a significant correlation of maximum and mean SUVs derived from PET and PET/CT for 14 paradiaphragmatic lesions (r=0.97 respectively; p<0.001 respectively) and for 32 lesions located distant from the diaphragm (r=0.87 and r=0.89 respectively; p<0.001 respectively). No significant differences were observed in the SUVs calculated with PET and PET/CT in the lesions or in the organs. In the phantom, radioactivity concentration in spheres calculated from PET and from PET/CT correlated significantly (r=0.99; p<0.001). Conclusion SUVs of cancer lesions and normal organs were comparable between PET and PET/CT, supporting the usefulness of PET/CT-derived SUVs for quantification of tumour metabolism.     

Analysis of FDG uptake with hybrid PET using standardised uptake values

The standardised uptake value (SUV) has been used as an index of glucose metabolism to classify malignant tumours. To date, calculation of SUVs has been restricted to dedicated PET. The aim of this study was to investigate the feasibility of SUV calculation with attenuation-corrected hybrid PET, applying a singles count rate-related calibration method. Calibration factors for hybrid PET at different singles count rates were determined by phantom studies. SUVs were determined for hot spheres in a phantom study as well as for 68 malignant lesions in 56 patients. Recovery coefficients calculated for hot spheres were applied to SUVs of malignant lesions to correct for partial volume and recovery effects. At a sphere-to-background ratio of 10:1, SUVs of spheres with diameters from 34 to 16 mm varied from 5.0 to 1.5 for hybrid PET, and from 8.0 to 4.3 for dedicated PET. SUVs of malignant lesions calculated by hybrid and dedicated PET showed a strong correlation (r=0.95, P<0.001), with a mean percentage difference of 36%. SUVs calculated by hybrid PET were significantly lower than SUVs calculated by dedicated PET (6.2dž.3 vs 8.5LJ.3, P<0.001). Application of recovery coefficients revealed an SUV of 12.2lj.3 for hybrid PET versus 10.8Lj.3 for dedicated PET, with a significant reduction in the mean percentage difference (22%, P<0.01). In conclusion, singles count rate-related calibration factors allow calculation of SUVs with hybrid PET for lesions with a diameter larger than 15 mm. Correction for partial volume and recovery effects is needed to improve the agreement of SUVs of lesions determined by hybrid PET and dedicated PET.