NEC Density and Liver ROI S/N Ratio for Image Quality Control of Whole-Body FDG-PET Scans: Comparison with Visual Assessment

Mizuta, Tetsuro; Senda, Michio; Okamura, Terue; Kitamura, Kazuhiro; Inaoka, Yuichi; Takahashi, Munehiro; Matsumoto, Keīichi; Abe, Makoto; Shimonishi, Yoshihiro; Shiomi, Susumu

doi:10.1007/s11307-009-0214-3

Cited by 27 publications

(32 citation statements)

References 8 publications

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“…This is consistent with the findings of McDermott et al [16]. Mizuta et al [17] concluded that noise equivalent count density NEC density was a better measure, but this was based on 15 scans and it is not clear whether the difference was significant.…”

Section: Discussionsupporting

confidence: 89%

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Patient-specific optimisation of administered activity and acquisition times for 18F-FDG PET imaging

et al. 2017

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BackgroundThe purpose of this study is to identify a method for optimising the administered activity and acquisition time for 18F-FDG PET imaging, yielding images of consistent quality for patients with varying body sizes and compositions, while limiting radiation doses to patients and staff. Patients referred for FDG scans had bioimpedance measurements. They were injected with 3 MBq/kg of 18F up to 370 MBq and scanned on a Siemens Biograph mCT at 3 or 4 min per bed position. Data were rebinned to simulate 2- and 1-min acquisitions. Subjective assessments of image quality made by an experienced physician were compared with objective measurements based on signal-to-noise ratio and noise equivalent counts (NEC). A target objective measure of image quality was identified. The activity and acquisition time required to achieve this were calculated for each subject. Multiple regression analysis was used to identify expressions for the activity and acquisition time required in terms of easily measurable patient characteristics.ResultsOne hundred and eleven patients were recruited, and subjective and objective assessments of image quality were compared for 321 full and reduced time scans. NEC-per-metre was identified as the objective measure which best correlated with the subjective assessment (Spearman rank correlation coefficient 0.77) and the best discriminator for images with a subjective assessment of “definitely adequate” (area under the ROC curve 0.94). A target of 37 Mcount/m was identified. Expressions were identified in terms of patient sex, height and weight for the activity and acquisition time required to achieve this target. Including measurements of body composition in these expressions was not useful. Using these expressions would reduce the mean activity administered to this patient group by 66 MBq compared to the current protocol.ConclusionsExpressions have been identified for the activity and acquisition times required to achieve consistent image quality in FDG imaging with reduced patient and staff doses. These expressions might need to be adapted for other systems and reconstruction protocols.Electronic supplementary materialThe online version of this article (doi:10.1186/s13550-016-0250-3) contains supplementary material, which is available to authorized users.

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Section: Discussionsupporting

confidence: 89%

“…Other studies have suggested that measures based on NEC may coincide better with physicians’ subjective assessment [9, 16, 17]. …”

Section: Introductionmentioning

confidence: 99%

Patient-specific optimisation of administered activity and acquisition times for 18F-FDG PET imaging

et al. 2017

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“…These three parameters are used in this guideline, because they are believed to be good indicators of image quality [2]. These reference values, however, may depend on the PET camera model and the subject body size to some extent.…”

Section: Human Image Quality Evaluationmentioning

confidence: 99%

“…These three indicators are known to be excellent indicators of image quality for whole-body FDG-PET/CT images acquired with a single PET camera model [2]. In the present study, in which image data by 10 PET camera models were merged, visual score presented a weak but significant correlation with NEC patient (r = 0.376, p \ 0.001) and with NEC density (r = 0.432, p \ 0.001).…”

Section: Human Image Quality Evaluationmentioning

confidence: 99%

Japanese guideline for the oncology FDG-PET/CT data acquisition protocol: synopsis of Version 1.0

Fukukita

Senda

Terauchi³

et al. 2010

Ann Nucl Med

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This synopsis outlines the Japanese guideline Version 2.0 for the data acquisition protocol of oncology FDG-PET/CT scans that was created by a joint task force of the Japanese Society of Nuclear Medicine Technology, the Japanese Society of Nuclear Medicine and the Japanese Council of PET Imaging, and was published in KakuigakuGijutsu 2013; 33:377-420 in Japanese. The guideline aims at standardizing the PET image quality among PET centers and different PET camera models by providing criteria for the IEC body phantom image quality as well as for the patient PET image quality based on the noise equivalent count (NEC), NEC density and liver signal-to-noise ratio, so that the appropriate scanning parameters can be determined for each PET camera. This Version 2.0 covers issues that were not focused on in Version 1.0, including the accuracy of the standardized uptake value (SUV), effect of body size together with adjustment of scanning duration, and time-of-flight (TOF) reconstruction technique. Version 2.0 also presents data acquired with new PET camera models that were not tested in Version 1.0. Reference values for physical indicators of phantom image quality have been updated as well.The objective of this guideline is to define the criteria for the data acquisition protocol for oncology FDG-PET (PET/ CT) scans in order to standardize the PET image quality among PET centers and different PET camera models. It describes the method for phantom experiments and human image quality evaluation and provides recommended values as a reference. The optimum imaging protocol for each camera model can be determined by using this guideline as a manual, and by comparing the results with the recommended values.The Version 1.0 (Kakuigaku-Gijutsu 2009; 29:195-235) and the English synopsis [1] did not deal with the accuracy of SUV values, and did not provide references for scanning patients with large body weight, which inevitably degrades image quality and requires longer scanning duration. Furthermore, new reconstruction techniques such as time-offlight (TOF) and point-spread-function (PSF) have become available, which affect image spatial resolution and noise in a way different from the conventional OSEM reconstruction technique. To address these issues, the joint task force again worked on the data of phantom and patient scans acquired with PET cameras currently used in Japan, including new PET camera models installed after Version

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“…To verify that the images obtained were available for response evaluation in terms of image quality, the liver signal-to-noise ratio (liver SNR) was calculated with the following formula [19]:…”

Section: Image Analysismentioning

confidence: 99%

Usefulness of standardized uptake value normalized by individual CT-based lean body mass in application of PET response criteria in solid tumors (PERCIST)

Narita

Shiomi

Katayama

et al. 2016

Radiol Phys Technol

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Our aim in this study was to verify the usefulness of the standardized uptake value (SUV) normalized by individual CT-based lean body mass (LBMCT) in application of PET response criteria in solid tumors (PERCIST).We retrospectively investigated 14 patients (4 male and 10 female) with malignant lymphoma who were undergoing chemotherapy. (18)F-FDG PET/CT examinations were performed before and after chemotherapy. The LBMCT was calculated by estimation of fat weight from CT data (from skull base to pelvis). The mean ± standard deviation (SD) and the Bland-Altman plot were used for comparison among body weight, LBMCT, and LBM derived from a predictive equation (LBMPE). Indices for FDG uptake in the liver were: SUV, SUV based on LBMPE (SULPE), and SUV based on LBMCT (SULCT). Overall differences between the uptake values were analyzed by one-way ANOVA. If the ANOVA showed significance, differences between uptake values were investigated further by use of the Tukey-Kramer test. The mean values of body weight, LBMPE, and LBMCT were: 55.4 ± 14.9 (39.0-112.0), 43.0 ± 10.5 (31.3-75.2), and 35.3 ± 9.8 (23.4-75.8) kg, respectively. There was a wide dispersion between LBMPE and LBMCT (differences, 7.6 ± 3.6 kg; 95 % CI, 6.42-8.85). LBMPE was higher than LBMCT in all the cases except in Case 11. The mean uptake values significantly differed among SUV, SULPE, and SULCT (F = 68.3, p < 0.05). Whereas SULPE deviated from PERCIST criteria in seven patients, SULCT satisfied the criteria except in one case. These results suggest that liver SULCT is useful for application of PERCIST.

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NEC Density and Liver ROI S/N Ratio for Image Quality Control of Whole-Body FDG-PET Scans: Comparison with Visual Assessment

Abstract: NEC density, representing count statistics per body volume, reflects the visual image quality assessment and may be utilized for quality control of whole-body FDG-PET images together with the liver ROI S/N ratio.

Cited by 27 publications

References 8 publications

Patient-specific optimisation of administered activity and acquisition times for 18F-FDG PET imaging

Patient-specific optimisation of administered activity and acquisition times for 18F-FDG PET imaging

Japanese guideline for the oncology FDG-PET/CT data acquisition protocol: synopsis of Version 1.0

Usefulness of standardized uptake value normalized by individual CT-based lean body mass in application of PET response criteria in solid tumors (PERCIST)

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