Optimization of scan time in 18F FDG-PET/CT imaging for cardiac sarcoidosis

Optimization of scan time in 18F FDG-PET/CT imaging for cardiac sarcoidosis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Optimization of scan time in 18F FDG-PET/CT imaging for cardiac sarcoidosis Yoshiyuki Takahashi, Tatsuya Tsuchitani, Ryosuke Miki, Hotaka Nakagiri, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7221127/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective We determined an appropriate noise equivalent count per volume (NEC density ) for cardiac spot acquisition and optimized the scan time of cardiac spot acquisition by utilizing NEC density in 18 F-fluorodeoxyglucose positron emission tomography/computed tomography imaging for the diagnosis of cardiac sarcoidosis. Methods Seventy-two patients were enrolled. Using list mode data of cardiac spot acquisition, we evaluated the relationship between acquisition time and NEC density . Based on this result and the guideline recommendation of whole-body scan (NEC density >0.2), an appropriate NEC density for cardiac spot acquisition was determined. The correlation between the minimum acquisition time that satisfied the determined appropriate NEC density and the patient’s physical index (body weight, body mass index [BMI], and lean body mass) was evaluated. Results NEC density increased linearly with longer acquisition times. For all patients, NEC density of 10 min was 4.07 ± 0.15 times as high as that of 3 min, which was the acquisition time per one bed of whole-body scan. From the above and the guideline recommendation of whole-body scan (NEC density >0.2), we determined that NEC density of 0.9 was an appropriate NEC density for cardiac spot acquisition. The correlation coefficient value between the minimum acquisition time meeting the appropriate NEC density and body weight, BMI, or lean body mass was 0.79 (p < 0.0001), 0.83 (p < 0.0001), or 0.53 (p < 0.0001), respectively. Conclusions We defined a NEC density of 0.9 as an appropriate NEC density for cardiac spot acquisition. Our retrospective study using NEC density revealed that optimization of acquisition time according to BMI could help reduce examination time for patients with small body size and homogenization of image quality. Figures Figure 1 Figure 2 Introduction Sarcoidosis is a systemic granulomatous disease characterized by epithelioid cell granulomas without caseous necrosis. It frequently involves the lymph nodes, lungs, eyes, skin, liver, and heart. Cardiac involvement is also associated with life-threatening complications. Therefore, early detection and treatment of cardiac sarcoidosis (CS) are important. The guidelines suggest that the diagnosis of CS requires histopathological or clinical diagnosis of sarcoidosis in organs other than the heart ( 1 ). Additionally, these guidelines require histologically positive cases by myocardial biopsy or clinically observed cardiac abnormalities for the diagnosis of CS. Nuclear medicine imaging is considered useful in evaluating the activity of the CS, and Gallium-67 scintigraphy has been utilized. Recent studies have reported the usefulness of 18 F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) for the diagnosis and management of CS ( 2 , 3 ). The main advantage of FDG PET/CT is its ability to demonstrate metabolic activity, as opposed to anatomic imaging techniques such as radiography, CT, and magnetic resonance imaging, which are unable to differentiate an active focus from inactive or fibrotic changes. The Japanese Society of Nuclear Cardiology recommends cardiac spot acquisition of approximately 10 min in addition to whole-body scanning ( 4 ). However, the scan time has not been scientifically evaluated and is presented as a consideration ( 4 ). The Japanese Society of Nuclear Medicine suggested the liver signal-to-noise ratio, noise equivalent count per patient height (NEC patient ), and noise equivalent count per volume (NEC density ) as indicators of human PET image quality ( 5 ). Shimada et al. reported that NEC density showed the highest correlation coefficient with PET image quality (r = 0.743, p < 0.001) ( 6 ). The current study aimed to determine an appropriate NEC density for cardiac spot acquisition and optimize the scan time of cardiac spot acquisition by utilizing NEC density in FDG PET/CT imaging for the diagnosis of CS. Materials and Methods Patients We included 72 consecutive patients (38 men and 34 women; mean age, 68 ± 12 years; range, 34–87 years; mean body weight 61 ± 11 kg) who underwent 18 F-FDG PET/CT to evaluate suspected CS between January 2023 and August 2024 (Table 1 ). This study was approved by the institutional review board. Table 1 Characteristics of study participants Characteristic Value (n = 72) Age 67.7 ± 11.6 (34–87) Height (m) 1.63 ± 0.09 (143–178) Body weight (kg) 61.3 ± 11.3 (41–88) BMI (kg/m 2 ) 23.0 ± 3.9 (15.4–35.7) Lean body mass (kg) 40.2 ± 7.9 (27.0-55.8) Injection dose (MBq) 224.2 ± 42.3 (152–320) Dose/weight (MBq/kg) 3.67 ± 0.06 (3.56–3.81) Blood sugar level (mg/dl) 102.1 ± 38.6 (68–386) Uptake time (min) 45.8 ± 5.7 (34–65) Acquisition time (sec) 600 Protocol All patients were instructed to fast for at least 18 h to minimize physiological 18 F-FDG uptake in the heart. To further suppress background 18 F-FDG uptake, we intravenously injected low-dose unfractionated heparin before 18 F-FDG administration in patients without contraindications. Intravenous injection of 18 F-FDG (3.7 MBq/kg) was followed by an uptake phase of 45 min and a heart CT scan for attenuation correction. This was followed by cardiac 18 F-FDG PET to the same extent. Subsequently, a whole-body scan (3 min per bed) was obtained approximately 60 min after the 18 F-FDG injection. Discovery IQ combined PET/CT scanner (GE Healthcare) was used for all patients. The detector of this scanner comprised Bi 4 Ge 3 O 12 (BGO) crystals measuring 6.3 × 6.3 × 30 mm. The transaxial field of view (FOV) was 700 mm, the axial FOV was 260 mm, and 79 axial slices were obtained in the one-bed position. The energy window width was 435–650 keV, and the coincidence time window was 9.5 ns. A matrix size of 192 × 192 and slice thickness of 3.27 mm were acquired. The scattering coincidence correction was performed using a three-dimensional (3D) model-based scatter estimation method. The random coincidence method is a single method estimated from the count rate of each detector. Cardiac spot images were acquired at 10 min in 3D acquisition mode. From these list-mode data, 10 images acquired at acquisition times of 1, 2, 3, 4, 5, 6, 7, 8, 9, and 10 min were reconstructed using VUE Point HD and Q. Clear (GE Healthcare) ( 7 ). Calculation of noise equivalent count density (NEC density ) NEC density was calculated using the PETquactIE software (Nihon Medi-Physics Co., Ltd.). According to the cancer FDG PET/CT imaging method guidelines ( 5 ), the NEC at each bed position is given by NEC i = \(\:{(1-SF)}^{2}\:\frac{{({P}_{i}-{R}_{i})}^{2}}{\left({P}_{i}-{R}_{i}\right)+\left(1+\text{k}\right){R}_{i}}\) where NEC i is the NEC at bed position i, SF is the scatter fraction, P i is the number of prompt coincidences at bed position i, R i is the number of contingent coincidences at bed position i, and k is a coefficient based on the correction method for contingent coincidences (1 for delayed coincidence measurements and 0 otherwise). An SF of 0.362 was derived in a previous study ( 8 ). The number of coincidences was extracted using a DICOM tag. NEC density was given by NEC density = \(\:\frac{\sum\:_{i=1}^{n}{NEC}_{i}}{{V}_{patient}}\) where V patient is the body volume of the imaging area. For 10 cardiac spot acquisition data of all patients, NEC density was calculated. Data analysis For all patients, to evaluate linearity between NEC density and acquisition time, the coefficient of determination (r 2 ) was calculated. Given these results and the guideline recommendation of whole-body scan (NEC density >0.2) ( 5 ), an appropriate NEC density for cardiac spot acquisition was determined. For all patients, the correlation between the minimum acquisition time meeting the appropriate NEC density and body weight, body mass index (BMI), or lean body mass (LBM) was evaluated. LBM was calculated using the following formula ( 9 ). LBM (male) = 28.27×height (m) + 0.359×body weight (kg)–0.032×age − 21.83 LBM (female) = 26.12×height (m) + 0.253×body weight (kg)–0.022×age − 19.58 Statistical analysis JMP Pro (SAS Institute Inc.) was used for the statistical analysis. The relationship between NEC density and BMI and between the minimum acquisition time meeting the appropriate NEC density and BMI were evaluated using Pearson’s correlation coefficient. A p value < 0.05 was considered statistically significant. Results The mean NEC density of the 10 min acquisition data was 1.84 ± 0.62. Figure 1 shows the relationship between the NEC density of the 10 min acquisition data and body weight (a), BMI (b), or LBM (c), and the correlation coefficient values were − 0.75 (p < 0.0001), − 0.80 (p < 0.0001), and − 0.44 (p < 0.0001), respectively. The coefficient of determination (r 2 ) between NEC density and acquisition time for all patients was 0.9956 ± 0.0017. Therefore, it could be said that NEC density increased linearly with longer acquisition times. For all patients, NEC density of 10 min was 4.07 ± 0.15 times as high as that of 3 min, which was the acquisition time per one bed of whole-body scan, on average. From the above and the guideline recommendation of whole-body scan (NEC density >0.2), we determined that NEC density of 0.9 was an appropriate NEC density for cardiac spot acquisition. For all patients, the mean minimum acquisition time satisfying the appropriate NEC density was 6.36 ± 1.58 min. For two patients, NEC density of 10 min was < 0.9 (0.77 and 0.81, respectively). Figure 2 shows the relationship between the minimum acquisition time meeting the appropriate NEC density and body weight (a), BMI (b), or LBM (c). The correlation coefficient value was 0.79 (p < 0.0001), 0.83 (p < 0.0001), or 0.53 (p < 0.0001), respectively (Fig. 2 ). Discussion In FDG-PET imaging for the diagnosis of CS, the Japanese Society of Nuclear Cardiology recommends cardiac spot acquisition of approximately 10 min in addition to a whole-body scan ( 4 ). However, scan time has not been scientifically evaluated. In this study, we attempted to determine an appropriate NEC density for cardiac spot acquisition and optimize the scan time of cardiac spot acquisition by utilizing NEC density in FDG PET/CT imaging for the diagnosis of CS. We utilized NEC density as an index of image quality in FDG PET/CT for the diagnosis of CS. It has been reported that NEC density is highly correlated with visual scores and has become popular for evaluating the image quality of oncology FDG PET/CT scans ( 6 ). In FDG PET/CT imaging for the diagnosis of CS, the appearance of a positive case is similar to that for the diagnosis of cancer in terms of observed local FDG accumulation. Therefore, NEC density was available for the evaluation of image quality in FDG PET/CT for the diagnosis of CS. We suggested that NEC density increased linearly as acquisition time increased (r 2 = 0.99) and that the NEC density of the 10 min acquisition data was approximately four times as high as that of 3 min, which was the acquisition time per bed of the whole-body scan. Similar results were reported in a phantom study ( 10 ). According to the Japanese Nuclear Cardiology Society guidelines, if the injection dose is based on the guidelines of the Japanese Society of Nuclear Medicine, a scan time of 10 min is sufficient for cardiac spot acquisition ( 4 ). Considering our results and the guideline recommendation of whole-body scans (NEC density >0.2), we defined a NEC density of 0.9 as an appropriate NEC density for cardiac spot acquisition. The phantom study suggested that NEC differed more than twice depending on the PET/CT machines at the same acquisition time because sensitivity and count rate varied depending on the PET/CT machines ( 10 ). Therefore, the appropriate NEC density of 0.9 in this study might not apply to other PET/CT machines. For the 10 min acquisition data, NEC density and BMI had the highest statistically significant negative correlation (r = − 0.80, p < 0.0001) among body weight, BMI, and LBM (Fig. 1 ). Sagara et al. reported similar results using whole-body scan data ( 11 ). Moreover, 97% (70/72) of the patients satisfied the appropriate NEC density . For two patients whose BMI was 33.8 and 35.7, the NEC density in 10 min was < 0.9 (NEC density 0.77 and 0.81). With a longer acquisition time, the NEC density of the patient could satisfy the appropriate NEC density . However, the increased examination time can be a burden for patients. Additionally, the minimum acquisition time meeting the appropriate NEC density and BMI had the highest statistically significant correlation (r = 0.83, p < 0.0001) among body weight, BMI, and LBM (Fig. 2 ). Therefore, the adjustment of acquisition time according to patient body size could contribute to a reduction in examination time for patients with small body size and homogenization of image quality. In the acquisition of patients with large body size, the proportion of counts, which are attributed to increased noise, increases, and the proportion of effective counts, which contribute to improved image quality, decreases ( 12 ). This was mainly due to an increase in random coincidence counts and scatter fraction rates with increasing body size ( 13 ). Therefore, the true coincidence counts required to maintain the PET image quality cannot be obtained, and the scan time increases. The current study had some limitations. We did not examine the effects of scan-time optimization on the visual evaluation of the PET images. The interpretation of the images by physicians should be investigated in the future. Additionally, when NEC density was calculated, we used a fixed SF value obtained from the phantom study. In general, the scatter fraction measured using a scatter phantom based on the NEMA standard may provide a lower value than clinical scans because it increases as the body size of the patient increases ( 11 ). In addition, the scatter fraction is influenced by the radioactivity concentration if the data are acquired in the 3D mode ( 5 ). Therefore, the scatter fraction varies widely with the body size and activity inside or outside the direct field of view. However, because real-time measurement of the scatter fraction is impossible with clinical scans, the guidelines recommend using the scatter fraction values based on NEMA NU 2-2007 as an intrinsic value for each camera model ( 5 ). Therefore, there is the possibility of errors in the actual scatter fraction for each human scan. Conclusion In FDG PET imaging for the diagnosis of CS, we defined a NEC density of 0.9 as an appropriate NEC density for cardiac spot acquisition from the relationship between NEC density and scan time. Our retrospective study using NEC density revealed that optimization of acquisition time according to BMI could contribute to a reduction in examination time for patients with small body size and homogenization of image quality. Declarations Acknowledgement No potential conflicts of interest were disclosed. References Fumio Terasaki A, Azuma T, Anzai N, Ishizaka Y, Ishida M, Isobe, et al. Guidelines for Diagnosis and Treatment of Cardiac Sarcoidosis – Digest Version –. Circ J. 2019;83:2329–88. Youssef G, Leung E, Mylonas I, Nery P, Williams K, Wisenberg G, et al. The Use of 18F-FDG PET in the diagnosis of cardiac sarcoidosis: A systematic review and metaanalysis including the Ontario experience. J Nucl Med. 2012;53:241–8. Langah R, Spicer K, Gebregziabher M, Gordon L. Effectiveness of prolonged fasting 18f-FDG PET-CT in the detection of cardiac sarcoidosis. J Nucl Cardiol. 2009;16:801–10. Kumita S, Yoshinaga K, Miyagawa M, Momose M, Kiso K, Kasai T, et al. Committee for diagnosis of cardiac sarcoidosis using 18F-FDG PET, Japanese Society of Nuclear Cardiology. Recommendations for 18F-fluorodeoxyglucose positron emission tomography imaging for diagnosis of cardiac sarcoidosis-2018 update: Japanese Society of Nuclear Cardiology recommendations. J Nucl Cardiol. 2019;26:1414–33. Fukukita H, Suzuki K, Matsumoto K, Terauchi T, Daisaki H, Ikari Y, et al. Japanese guideline for the oncology FDG-PET/CT data acquisition protocol: synopsis of Version 2.0. Ann Nucl Med. 2014;28:693–705. Shimada N, Daisaki H, Murano T, Terauchi T, Shinohara H, Moriyama N. Optimization of the scan time is based on the physical index in FDG-PET/CT. Nihon Hoshasen Gijutsu Gakkai Zasshi. 2011;67:1259–66. Teoh EJ, McGowan DR, Macpherson RE, Bradley KM, Gleeson FV. Phantom and Clinical Evaluation of the Bayesian Penalized Likelihood Reconstruction Algorithm Q.Clear on an LYSO PET/CT System. J Nucl Med. 2015;56:1447–52. Reynés-Llompart G, Gámez-Cenzano C, Romero-Zayas I, Rodríguez-Bel L, Vercher-Conejero JL, Martí-Climent JM. Performance Characteristics of the Whole-Body Discovery IQ PET/CT System. J Nucl Med. 2017;58:1155–61. Ito H, Ohshima A, Ohto N, Ogasawara M, Tsuzuki M, Takao K, et al. Relation between body composition and age in healthy Japanese subjects. Eur J Clin Nutr. 2001;55:462–70. Fukukita H, Suzuki K, Matsumoto K, Terauchi T, Daisaki H, Ikari Y, et al. Japanese guideline Version 2.0 for the data acquisition protocol of oncology FDG-PET/CT scans. Kakuigaku-Gijutsu. 2013;33:377–420. Sagara H, Inoue K, Yaku H, Ohsawa A, Someya T, Yanagisawa K, et al. Optimization of injection dose in 18 F-FDG PET/CT based on the 2020 national diagnostic reference levels for nuclear medicine in Japan. Ann Nucl Med. 2021;35:1177–86. Badawi RD, Dahlbom M. NEC: some coincidences are more equivalent than others. J Nucl Med. 2005;46:1767–8. Bonutti F, Cattaruzzi E, Cragnolini E, Floreani M, Foti C, Malisan MR, et al. Count-rate analysis from clinical scans in PET with LSO detectors. Radiat Prot Dosimetry. 2008;129:288–90. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7221127","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":492254477,"identity":"ed9e4d8e-9427-4a44-aef3-733bfa73290c","order_by":0,"name":"Yoshiyuki Takahashi","email":"data:image/png;base64,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","orcid":"","institution":"Hyogo Medical University Hospital","correspondingAuthor":true,"prefix":"","firstName":"Yoshiyuki","middleName":"","lastName":"Takahashi","suffix":""},{"id":492254478,"identity":"77763ef7-422a-4f44-b5cc-ef5dda4a6a2b","order_by":1,"name":"Tatsuya Tsuchitani","email":"","orcid":"","institution":"Hyogo Medical University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Tatsuya","middleName":"","lastName":"Tsuchitani","suffix":""},{"id":492254479,"identity":"0bc2a17b-85af-4b13-a1bf-4d98708e5bfc","order_by":2,"name":"Ryosuke Miki","email":"","orcid":"","institution":"Hyogo Medical University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ryosuke","middleName":"","lastName":"Miki","suffix":""},{"id":492254480,"identity":"dbfc1319-34aa-424d-b1e0-4e12e312ce49","order_by":3,"name":"Hotaka Nakagiri","email":"","orcid":"","institution":"Hyogo Medical University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Hotaka","middleName":"","lastName":"Nakagiri","suffix":""},{"id":492254481,"identity":"1dfa7daa-66ed-4f04-9eec-60546b13aebc","order_by":4,"name":"Tomoyasu Sakuma","email":"","orcid":"","institution":"Hyogo Medical University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Tomoyasu","middleName":"","lastName":"Sakuma","suffix":""},{"id":492254482,"identity":"e936c352-174d-4cc9-b7bc-f44af1116b84","order_by":5,"name":"Ryoga Morotomi","email":"","orcid":"","institution":"Hyogo Medical University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ryoga","middleName":"","lastName":"Morotomi","suffix":""},{"id":492254483,"identity":"cd0b3c21-8f1b-44a9-935a-9dec932236a4","order_by":6,"name":"Kazuma Matsumoto","email":"","orcid":"","institution":"Hyogo Medical University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Kazuma","middleName":"","lastName":"Matsumoto","suffix":""},{"id":492254484,"identity":"bcf08f95-bb46-45da-bdf0-e9bbdf20f740","order_by":7,"name":"Kazuhiro Kitajima","email":"","orcid":"","institution":"Hyogo Medical University","correspondingAuthor":false,"prefix":"","firstName":"Kazuhiro","middleName":"","lastName":"Kitajima","suffix":""}],"badges":[],"createdAt":"2025-07-26 12:21:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7221127/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7221127/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88005306,"identity":"d4e6c824-3b3d-4ba0-b7e8-cc809c11e1d4","added_by":"auto","created_at":"2025-07-31 10:39:18","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":178634,"visible":true,"origin":"","legend":"\u003cp\u003eRelationship between noise equivalent count density of 10 min and body weight (a), body mass index (b), and lean body weight (c). The correlation efficient (r) values were −0.75 (p \u0026lt; 0.0001), −0.80 (p \u0026lt; 0.0001), and −0.44 (p \u0026lt; 0.0001), respectively.\u003c/p\u003e","description":"","filename":"Fig.1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7221127/v1/0fea33cbb39e241836f9f261.jpg"},{"id":88005740,"identity":"b84d3f9a-51f9-4e55-baf3-31eee0438e31","added_by":"auto","created_at":"2025-07-31 10:47:18","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":202196,"visible":true,"origin":"","legend":"\u003cp\u003eRelationship between minimum acquisition time meeting the appropriate noise equivalent count density and body weight (a), body mass index (b), and lean body weight (c). The correlation efficient (r) values were −0.79 (p \u0026lt; 0.0001), 0.83 (p \u0026lt; 0.0001), and 0.53 (p \u0026lt; 0.0001), respectively.\u003c/p\u003e","description":"","filename":"Fig.2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7221127/v1/adb19103686112b518841da4.jpg"},{"id":90772693,"identity":"ac805dbb-4c17-40b0-bfdd-5c99b36e8b0e","added_by":"auto","created_at":"2025-09-08 01:56:10","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":803659,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7221127/v1/bc124e4a-8620-40a2-966a-3d6a0b46d507.pdf"}],"financialInterests":"","formattedTitle":"Optimization of scan time in 18F FDG-PET/CT imaging for cardiac sarcoidosis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSarcoidosis is a systemic granulomatous disease characterized by epithelioid cell granulomas without caseous necrosis. It frequently involves the lymph nodes, lungs, eyes, skin, liver, and heart. Cardiac involvement is also associated with life-threatening complications. Therefore, early detection and treatment of cardiac sarcoidosis (CS) are important. The guidelines suggest that the diagnosis of CS requires histopathological or clinical diagnosis of sarcoidosis in organs other than the heart (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Additionally, these guidelines require histologically positive cases by myocardial biopsy or clinically observed cardiac abnormalities for the diagnosis of CS. Nuclear medicine imaging is considered useful in evaluating the activity of the CS, and Gallium-67 scintigraphy has been utilized.\u003c/p\u003e\u003cp\u003eRecent studies have reported the usefulness of \u003csup\u003e18\u003c/sup\u003eF-fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) for the diagnosis and management of CS (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). The main advantage of FDG PET/CT is its ability to demonstrate metabolic activity, as opposed to anatomic imaging techniques such as radiography, CT, and magnetic resonance imaging, which are unable to differentiate an active focus from inactive or fibrotic changes.\u003c/p\u003e\u003cp\u003eThe Japanese Society of Nuclear Cardiology recommends cardiac spot acquisition of approximately 10 min in addition to whole-body scanning (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). However, the scan time has not been scientifically evaluated and is presented as a consideration (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe Japanese Society of Nuclear Medicine suggested the liver signal-to-noise ratio, noise equivalent count per patient height (NEC\u003csub\u003epatient\u003c/sub\u003e), and noise equivalent count per volume (NEC\u003csub\u003edensity\u003c/sub\u003e) as indicators of human PET image quality (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Shimada et al. reported that NEC\u003csub\u003edensity\u003c/sub\u003e showed the highest correlation coefficient with PET image quality (r\u0026thinsp;=\u0026thinsp;0.743, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe current study aimed to determine an appropriate NEC\u003csub\u003edensity\u003c/sub\u003e for cardiac spot acquisition and optimize the scan time of cardiac spot acquisition by utilizing NEC\u003csub\u003edensity\u003c/sub\u003e in FDG PET/CT imaging for the diagnosis of CS.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003ePatients\u003c/p\u003e\u003cp\u003eWe included 72 consecutive patients (38 men and 34 women; mean age, 68\u0026thinsp;\u0026plusmn;\u0026thinsp;12 years; range, 34\u0026ndash;87 years; mean body weight 61\u0026thinsp;\u0026plusmn;\u0026thinsp;11 kg) who underwent \u003csup\u003e18\u003c/sup\u003eF-FDG PET/CT to evaluate suspected CS between January 2023 and August 2024 (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). This study was approved by the institutional review board.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCharacteristics of study participants\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eValue (n\u0026thinsp;=\u0026thinsp;72)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e67.7\u0026thinsp;\u0026plusmn;\u0026thinsp;11.6 (34\u0026ndash;87)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHeight (m)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.63\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09 (143\u0026ndash;178)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBody weight (kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e61.3\u0026thinsp;\u0026plusmn;\u0026thinsp;11.3 (41\u0026ndash;88)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e23.0\u0026thinsp;\u0026plusmn;\u0026thinsp;3.9 (15.4\u0026ndash;35.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLean body mass (kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e40.2\u0026thinsp;\u0026plusmn;\u0026thinsp;7.9 (27.0-55.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInjection dose (MBq)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e224.2\u0026thinsp;\u0026plusmn;\u0026thinsp;42.3 (152\u0026ndash;320)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDose/weight (MBq/kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.67\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06 (3.56\u0026ndash;3.81)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBlood sugar level (mg/dl)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e102.1\u0026thinsp;\u0026plusmn;\u0026thinsp;38.6 (68\u0026ndash;386)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUptake time (min)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e45.8\u0026thinsp;\u0026plusmn;\u0026thinsp;5.7 (34\u0026ndash;65)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAcquisition time (sec)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e600\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eProtocol\u003c/p\u003e\u003cp\u003eAll patients were instructed to fast for at least 18 h to minimize physiological \u003csup\u003e18\u003c/sup\u003eF-FDG uptake in the heart. To further suppress background \u003csup\u003e18\u003c/sup\u003eF-FDG uptake, we intravenously injected low-dose unfractionated heparin before \u003csup\u003e18\u003c/sup\u003eF-FDG administration in patients without contraindications.\u003c/p\u003e\u003cp\u003eIntravenous injection of \u003csup\u003e18\u003c/sup\u003eF-FDG (3.7 MBq/kg) was followed by an uptake phase of 45 min and a heart CT scan for attenuation correction. This was followed by cardiac \u003csup\u003e18\u003c/sup\u003eF-FDG PET to the same extent. Subsequently, a whole-body scan (3 min per bed) was obtained approximately 60 min after the \u003csup\u003e18\u003c/sup\u003eF-FDG injection. Discovery IQ combined PET/CT scanner (GE Healthcare) was used for all patients. The detector of this scanner comprised Bi\u003csub\u003e4\u003c/sub\u003eGe\u003csub\u003e3\u003c/sub\u003eO\u003csub\u003e12\u003c/sub\u003e (BGO) crystals measuring 6.3 \u0026times; 6.3 \u0026times; 30 mm. The transaxial field of view (FOV) was 700 mm, the axial FOV was 260 mm, and 79 axial slices were obtained in the one-bed position. The energy window width was 435\u0026ndash;650 keV, and the coincidence time window was 9.5 ns. A matrix size of 192 \u0026times; 192 and slice thickness of 3.27 mm were acquired. The scattering coincidence correction was performed using a three-dimensional (3D) model-based scatter estimation method. The random coincidence method is a single method estimated from the count rate of each detector.\u003c/p\u003e\u003cp\u003eCardiac spot images were acquired at 10 min in 3D acquisition mode. From these list-mode data, 10 images acquired at acquisition times of 1, 2, 3, 4, 5, 6, 7, 8, 9, and 10 min were reconstructed using VUE Point HD and Q. Clear (GE Healthcare) (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eCalculation of noise equivalent count density (NEC\u003csub\u003edensity\u003c/sub\u003e)\u003c/p\u003e\u003cp\u003eNEC\u003csub\u003edensity\u003c/sub\u003e was calculated using the PETquactIE software (Nihon Medi-Physics Co., Ltd.).\u003c/p\u003e\u003cp\u003eAccording to the cancer FDG PET/CT imaging method guidelines (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e), the NEC at each bed position is given by\u003c/p\u003e\u003cp\u003eNEC\u003csub\u003ei\u003c/sub\u003e = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{(1-SF)}^{2}\\:\\frac{{({P}_{i}-{R}_{i})}^{2}}{\\left({P}_{i}-{R}_{i}\\right)+\\left(1+\\text{k}\\right){R}_{i}}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003cp\u003ewhere NEC\u003csub\u003ei\u003c/sub\u003e is the NEC at bed position i, SF is the scatter fraction, P\u003csub\u003ei\u003c/sub\u003e is the number of prompt coincidences at bed position i, R\u003csub\u003ei\u003c/sub\u003e is the number of contingent coincidences at bed position i, and k is a coefficient based on the correction method for contingent coincidences (1 for delayed coincidence measurements and 0 otherwise).\u003c/p\u003e\u003cp\u003eAn SF of 0.362 was derived in a previous study (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). The number of coincidences was extracted using a DICOM tag.\u003c/p\u003e\u003cp\u003eNEC\u003csub\u003edensity\u003c/sub\u003e was given by\u003c/p\u003e\u003cp\u003eNEC\u003csub\u003edensity\u003c/sub\u003e = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{\\sum\\:_{i=1}^{n}{NEC}_{i}}{{V}_{patient}}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003cp\u003ewhere V\u003csub\u003epatient\u003c/sub\u003e is the body volume of the imaging area.\u003c/p\u003e\u003cp\u003eFor 10 cardiac spot acquisition data of all patients, NEC\u003csub\u003edensity\u003c/sub\u003e was calculated.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eData analysis\u003c/h2\u003e\u003cp\u003eFor all patients, to evaluate linearity between NEC\u003csub\u003edensity\u003c/sub\u003e and acquisition time, the coefficient of determination (r\u003csup\u003e2\u003c/sup\u003e) was calculated. Given these results and the guideline recommendation of whole-body scan (NEC\u003csub\u003edensity\u003c/sub\u003e \u0026gt;0.2) (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e), an appropriate NEC\u003csub\u003edensity\u003c/sub\u003e for cardiac spot acquisition was determined. For all patients, the correlation between the minimum acquisition time meeting the appropriate NEC\u003csub\u003edensity\u003c/sub\u003e and body weight, body mass index (BMI), or lean body mass (LBM) was evaluated. LBM was calculated using the following formula (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eLBM (male)\u0026thinsp;=\u0026thinsp;28.27\u0026times;height (m)\u0026thinsp;+\u0026thinsp;0.359\u0026times;body weight (kg)\u0026ndash;0.032\u0026times;age\u0026thinsp;\u0026minus;\u0026thinsp;21.83\u003c/p\u003e\u003cp\u003eLBM (female)\u0026thinsp;=\u0026thinsp;26.12\u0026times;height (m)\u0026thinsp;+\u0026thinsp;0.253\u0026times;body weight (kg)\u0026ndash;0.022\u0026times;age\u0026thinsp;\u0026minus;\u0026thinsp;19.58\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eJMP Pro (SAS Institute Inc.) was used for the statistical analysis. The relationship between NEC\u003csub\u003edensity\u003c/sub\u003e and BMI and between the minimum acquisition time meeting the appropriate NEC\u003csub\u003edensity\u003c/sub\u003e and BMI were evaluated using Pearson\u0026rsquo;s correlation coefficient. A \u003cem\u003ep\u003c/em\u003e value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eThe mean NEC\u003csub\u003edensity\u003c/sub\u003e of the 10 min acquisition data was 1.84\u0026thinsp;\u0026plusmn;\u0026thinsp;0.62. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the relationship between the NEC\u003csub\u003edensity\u003c/sub\u003e of the 10 min acquisition data and body weight (a), BMI (b), or LBM (c), and the correlation coefficient values were \u0026minus;\u0026thinsp;0.75 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), \u0026minus;\u0026thinsp;0.80 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), and \u0026minus;\u0026thinsp;0.44 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), respectively. The coefficient of determination (r\u003csup\u003e2\u003c/sup\u003e) between NEC\u003csub\u003edensity\u003c/sub\u003e and acquisition time for all patients was 0.9956\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0017. Therefore, it could be said that NEC\u003csub\u003edensity\u003c/sub\u003e increased linearly with longer acquisition times. For all patients, NEC\u003csub\u003edensity\u003c/sub\u003e of 10 min was 4.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15 times as high as that of 3 min, which was the acquisition time per one bed of whole-body scan, on average. From the above and the guideline recommendation of whole-body scan (NEC\u003csub\u003edensity\u003c/sub\u003e \u0026gt;0.2), we determined that NEC\u003csub\u003edensity\u003c/sub\u003e of 0.9 was an appropriate NEC\u003csub\u003edensity\u003c/sub\u003e for cardiac spot acquisition.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFor all patients, the mean minimum acquisition time satisfying the appropriate NEC\u003csub\u003edensity\u003c/sub\u003e was 6.36\u0026thinsp;\u0026plusmn;\u0026thinsp;1.58 min. For two patients, NEC\u003csub\u003edensity\u003c/sub\u003e of 10 min was \u0026lt;\u0026thinsp;0.9 (0.77 and 0.81, respectively). Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the relationship between the minimum acquisition time meeting the appropriate NEC\u003csub\u003edensity\u003c/sub\u003e and body weight (a), BMI (b), or LBM (c). The correlation coefficient value was 0.79 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), 0.83 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), or 0.53 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn FDG-PET imaging for the diagnosis of CS, the Japanese Society of Nuclear Cardiology recommends cardiac spot acquisition of approximately 10 min in addition to a whole-body scan (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). However, scan time has not been scientifically evaluated. In this study, we attempted to determine an appropriate NEC\u003csub\u003edensity\u003c/sub\u003e for cardiac spot acquisition and optimize the scan time of cardiac spot acquisition by utilizing NEC\u003csub\u003edensity\u003c/sub\u003e in FDG PET/CT imaging for the diagnosis of CS.\u003c/p\u003e\u003cp\u003eWe utilized NEC\u003csub\u003edensity\u003c/sub\u003e as an index of image quality in FDG PET/CT for the diagnosis of CS. It has been reported that NEC\u003csub\u003edensity\u003c/sub\u003e is highly correlated with visual scores and has become popular for evaluating the image quality of oncology FDG PET/CT scans (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). In FDG PET/CT imaging for the diagnosis of CS, the appearance of a positive case is similar to that for the diagnosis of cancer in terms of observed local FDG accumulation. Therefore, NEC\u003csub\u003edensity\u003c/sub\u003e was available for the evaluation of image quality in FDG PET/CT for the diagnosis of CS.\u003c/p\u003e\u003cp\u003eWe suggested that NEC\u003csub\u003edensity\u003c/sub\u003e increased linearly as acquisition time increased (r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.99) and that the NEC\u003csub\u003edensity\u003c/sub\u003e of the 10 min acquisition data was approximately four times as high as that of 3 min, which was the acquisition time per bed of the whole-body scan. Similar results were reported in a phantom study (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). According to the Japanese Nuclear Cardiology Society guidelines, if the injection dose is based on the guidelines of the Japanese Society of Nuclear Medicine, a scan time of 10 min is sufficient for cardiac spot acquisition (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Considering our results and the guideline recommendation of whole-body scans (NEC\u003csub\u003edensity\u003c/sub\u003e \u0026gt;0.2), we defined a NEC\u003csub\u003edensity\u003c/sub\u003e of 0.9 as an appropriate NEC\u003csub\u003edensity\u003c/sub\u003e for cardiac spot acquisition. The phantom study suggested that NEC differed more than twice depending on the PET/CT machines at the same acquisition time because sensitivity and count rate varied depending on the PET/CT machines (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Therefore, the appropriate NEC\u003csub\u003edensity\u003c/sub\u003e of 0.9 in this study might not apply to other PET/CT machines. For the 10 min acquisition data, NEC\u003csub\u003edensity\u003c/sub\u003e and BMI had the highest statistically significant negative correlation (r\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.80, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) among body weight, BMI, and LBM (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Sagara et al. reported similar results using whole-body scan data (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Moreover, 97% (70/72) of the patients satisfied the appropriate NEC\u003csub\u003edensity\u003c/sub\u003e. For two patients whose BMI was 33.8 and 35.7, the NEC\u003csub\u003edensity\u003c/sub\u003e in 10 min was \u0026lt;\u0026thinsp;0.9 (NEC\u003csub\u003edensity\u003c/sub\u003e 0.77 and 0.81). With a longer acquisition time, the NEC\u003csub\u003edensity\u003c/sub\u003e of the patient could satisfy the appropriate NEC\u003csub\u003edensity\u003c/sub\u003e. However, the increased examination time can be a burden for patients.\u003c/p\u003e\u003cp\u003eAdditionally, the minimum acquisition time meeting the appropriate NEC\u003csub\u003edensity\u003c/sub\u003e and BMI had the highest statistically significant correlation (r\u0026thinsp;=\u0026thinsp;0.83, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) among body weight, BMI, and LBM (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Therefore, the adjustment of acquisition time according to patient body size could contribute to a reduction in examination time for patients with small body size and homogenization of image quality. In the acquisition of patients with large body size, the proportion of counts, which are attributed to increased noise, increases, and the proportion of effective counts, which contribute to improved image quality, decreases (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). This was mainly due to an increase in random coincidence counts and scatter fraction rates with increasing body size (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Therefore, the true coincidence counts required to maintain the PET image quality cannot be obtained, and the scan time increases.\u003c/p\u003e\u003cp\u003eThe current study had some limitations. We did not examine the effects of scan-time optimization on the visual evaluation of the PET images. The interpretation of the images by physicians should be investigated in the future. Additionally, when NEC\u003csub\u003edensity\u003c/sub\u003e was calculated, we used a fixed SF value obtained from the phantom study. In general, the scatter fraction measured using a scatter phantom based on the NEMA standard may provide a lower value than clinical scans because it increases as the body size of the patient increases (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). In addition, the scatter fraction is influenced by the radioactivity concentration if the data are acquired in the 3D mode (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Therefore, the scatter fraction varies widely with the body size and activity inside or outside the direct field of view. However, because real-time measurement of the scatter fraction is impossible with clinical scans, the guidelines recommend using the scatter fraction values based on NEMA NU 2-2007 as an intrinsic value for each camera model (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Therefore, there is the possibility of errors in the actual scatter fraction for each human scan.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn FDG PET imaging for the diagnosis of CS, we defined a NEC\u003csub\u003edensity\u003c/sub\u003e of 0.9 as an appropriate NEC\u003csub\u003edensity\u003c/sub\u003e for cardiac spot acquisition from the relationship between NEC\u003csub\u003edensity\u003c/sub\u003e and scan time. Our retrospective study using NEC\u003csub\u003edensity\u003c/sub\u003e revealed that optimization of acquisition time according to BMI could contribute to a reduction in examination time for patients with small body size and homogenization of image quality.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eNo potential conflicts of interest were disclosed.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eFumio Terasaki A, Azuma T, Anzai N, Ishizaka Y, Ishida M, Isobe, et al. Guidelines for Diagnosis and Treatment of Cardiac Sarcoidosis \u0026ndash; Digest Version \u0026ndash;. Circ J. 2019;83:2329\u0026ndash;88.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYoussef G, Leung E, Mylonas I, Nery P, Williams K, Wisenberg G, et al. The Use of 18F-FDG PET in the diagnosis of cardiac sarcoidosis: A systematic review and metaanalysis including the Ontario experience. J Nucl Med. 2012;53:241\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLangah R, Spicer K, Gebregziabher M, Gordon L. Effectiveness of prolonged fasting 18f-FDG PET-CT in the detection of cardiac sarcoidosis. J Nucl Cardiol. 2009;16:801\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKumita S, Yoshinaga K, Miyagawa M, Momose M, Kiso K, Kasai T, et al. Committee for diagnosis of cardiac sarcoidosis using 18F-FDG PET, Japanese Society of Nuclear Cardiology. Recommendations for 18F-fluorodeoxyglucose positron emission tomography imaging for diagnosis of cardiac sarcoidosis-2018 update: Japanese Society of Nuclear Cardiology recommendations. J Nucl Cardiol. 2019;26:1414\u0026ndash;33.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFukukita H, Suzuki K, Matsumoto K, Terauchi T, Daisaki H, Ikari Y, et al. Japanese guideline for the oncology FDG-PET/CT data acquisition protocol: synopsis of Version 2.0. Ann Nucl Med. 2014;28:693\u0026ndash;705.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShimada N, Daisaki H, Murano T, Terauchi T, Shinohara H, Moriyama N. Optimization of the scan time is based on the physical index in FDG-PET/CT. Nihon Hoshasen Gijutsu Gakkai Zasshi. 2011;67:1259\u0026ndash;66.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTeoh EJ, McGowan DR, Macpherson RE, Bradley KM, Gleeson FV. Phantom and Clinical Evaluation of the Bayesian Penalized Likelihood Reconstruction Algorithm Q.Clear on an LYSO PET/CT System. J Nucl Med. 2015;56:1447\u0026ndash;52.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eReyn\u0026eacute;s-Llompart G, G\u0026aacute;mez-Cenzano C, Romero-Zayas I, Rodr\u0026iacute;guez-Bel L, Vercher-Conejero JL, Mart\u0026iacute;-Climent JM. Performance Characteristics of the Whole-Body Discovery IQ PET/CT System. J Nucl Med. 2017;58:1155\u0026ndash;61.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eIto H, Ohshima A, Ohto N, Ogasawara M, Tsuzuki M, Takao K, et al. Relation between body composition and age in healthy Japanese subjects. Eur J Clin Nutr. 2001;55:462\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFukukita H, Suzuki K, Matsumoto K, Terauchi T, Daisaki H, Ikari Y, et al. Japanese guideline Version 2.0 for the data acquisition protocol of oncology FDG-PET/CT scans. Kakuigaku-Gijutsu. 2013;33:377\u0026ndash;420.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSagara H, Inoue K, Yaku H, Ohsawa A, Someya T, Yanagisawa K, et al. Optimization of injection dose in \u003csup\u003e18\u003c/sup\u003eF-FDG PET/CT based on the 2020 national diagnostic reference levels for nuclear medicine in Japan. Ann Nucl Med. 2021;35:1177\u0026ndash;86.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBadawi RD, Dahlbom M. NEC: some coincidences are more equivalent than others. J Nucl Med. 2005;46:1767\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBonutti F, Cattaruzzi E, Cragnolini E, Floreani M, Foti C, Malisan MR, et al. Count-rate analysis from clinical scans in PET with LSO detectors. Radiat Prot Dosimetry. 2008;129:288\u0026ndash;90.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7221127/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7221127/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e\u003cp\u003eWe determined an appropriate noise equivalent count per volume (NEC\u003csub\u003edensity\u003c/sub\u003e) for cardiac spot acquisition and optimized the scan time of cardiac spot acquisition by utilizing NEC\u003csub\u003edensity\u003c/sub\u003e in \u003csup\u003e18\u003c/sup\u003eF-fluorodeoxyglucose positron emission tomography/computed tomography imaging for the diagnosis of cardiac sarcoidosis.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eSeventy-two patients were enrolled. Using list mode data of cardiac spot acquisition, we evaluated the relationship between acquisition time and NEC\u003csub\u003edensity\u003c/sub\u003e. Based on this result and the guideline recommendation of whole-body scan (NEC\u003csub\u003edensity\u003c/sub\u003e \u0026gt;0.2), an appropriate NEC\u003csub\u003edensity\u003c/sub\u003e for cardiac spot acquisition was determined. The correlation between the minimum acquisition time that satisfied the determined appropriate NEC\u003csub\u003edensity\u003c/sub\u003e and the patient\u0026rsquo;s physical index (body weight, body mass index [BMI], and lean body mass) was evaluated.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eNEC\u003csub\u003edensity\u003c/sub\u003e increased linearly with longer acquisition times. For all patients, NEC\u003csub\u003edensity\u003c/sub\u003e of 10 min was 4.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15 times as high as that of 3 min, which was the acquisition time per one bed of whole-body scan. From the above and the guideline recommendation of whole-body scan (NEC\u003csub\u003edensity\u003c/sub\u003e \u0026gt;0.2), we determined that NEC\u003csub\u003edensity\u003c/sub\u003e of 0.9 was an appropriate NEC\u003csub\u003edensity\u003c/sub\u003e for cardiac spot acquisition. The correlation coefficient value between the minimum acquisition time meeting the appropriate NEC\u003csub\u003edensity\u003c/sub\u003e and body weight, BMI, or lean body mass was 0.79 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), 0.83 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), or 0.53 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), respectively.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eWe defined a NEC\u003csub\u003edensity\u003c/sub\u003e of 0.9 as an appropriate NEC\u003csub\u003edensity\u003c/sub\u003e for cardiac spot acquisition. Our retrospective study using NEC\u003csub\u003edensity\u003c/sub\u003e revealed that optimization of acquisition time according to BMI could help reduce examination time for patients with small body size and homogenization of image quality.\u003c/p\u003e","manuscriptTitle":"Optimization of scan time in 18F FDG-PET/CT imaging for cardiac sarcoidosis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-31 10:31:14","doi":"10.21203/rs.3.rs-7221127/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"41ca516b-337e-426a-907a-a7881dfc9267","owner":[],"postedDate":"July 31st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-08T01:48:03+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-31 10:31:14","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7221127","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7221127","identity":"rs-7221127","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}