Improved image resolution on thoracic carcinomas by quantitative <sup>18</sup>F-FDG coincidence SPECT/CT in comparison to <sup>18</sup>F-FDG PET/CT

Zheng Yuming; Jin Chaoling; Cui Huijuan; Dai Haojie; Yan Jue; Han Pingping; Hsu Bailing

doi:10.7555/JBR.33.20190004

Volume 34 Issue 4

Jul. 2020

Turn off MathJax

Article Contents

Abstract

References

The Journal of Biomedical Research > 2020 > 34(4): 309-317. > DOI: 10.7555/JBR.33.20190004

Zheng Yuming, Jin Chaoling, Cui Huijuan, Dai Haojie, Yan Jue, Han Pingping, Hsu Bailing. 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

Citation:

PDF (1389 KB)

Improved image resolution on thoracic carcinomas by quantitative ¹⁸F-FDG coincidence SPECT/CT in comparison to ¹⁸F-FDG PET/CT

1.
Nuclear Medicine Department
2.
Oncology of Integrative Medicine Department, China-Japan Friendship Hospital, Beijing 100029, China
3.
Nuclear Medicine Department, Danli Hospital, Beijing 100073, China
4.
Nuclear Science and Engineering Institute, University of Missouri-Columbia, Columbia, MO 65201, USA

More Information

Corresponding author:
Pingping Han, Nuclear Medicine Department, China-Japan Friendship Hospital, Beijing 100029, China. Tel: +86-010-84205508, E-mail: hanjiangpingping@163.com

Bailing Hsu, Nuclear Science and Engineering Institute, University of Missouri-Columbia, Columbia, MO 65201, USA. Tel: +1-573-882-8201, E-mail: bailinghsu@gmail.com
Received Date: January 03, 2019
Revised Date: May 20, 2019
Accepted Date: June 03, 2019
Available Online: August 15, 2019

Graphical Abstract

Abstract

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.
- ¹⁸F-FDG,
- coincidence SPECT/CT,
- full physical corrections,
- thoracic carcinomas,
- image quantitation

FullText(HTML)

References (20)

References

[1]	Facey K, Bradbury I, Laking G, et al. Overview of the clinical effectiveness of positron emission tomography imaging in selected cancers[J]. Health Technol Assess, 2007, 44(11): iii-iv, xi–267.
[2]	Gallamini A, Zwarthoed C, Borra A. Positron emission tomography (PET) in oncology[J]. Cancers, 2014, 6(4): 1821–1889. doi: 10.3390/cancers6041821
[3]	Ben-Haim S, Ell P. ¹⁸F-FDG PET and PET/CT in the evaluation of cancer treatment response[J]. J Nucl Med, 2009, 50(1): 88–99.
[4]	Martin WH, Delbeke D, Patton JA, et al. FDG-SPECT: correlation with FDG-PET[J]. J Nucl Med, 1995, 36(6): 988–995.
[5]	Martin WH, Delbeke D, Patton JA, et al. Detection of malignancies with SPECT versus PET, with 2-[fluorine-18] fluoro-2-deoxy-D-glucose[J]. Radiology, 1996, 198(1): 225–231. doi: 10.1148/radiology.198.1.8539384
[6]	Delbeke D, Patton JA, Martin WH, et al. FDG PET and dual-head gamma camera positron coincidence detection imaging of suspected malignancies and brain disorders[J]. J Nucl Med, 1999, 40(1): 110–117.
[7]	Qiao WL, Zhao JH, Wang C, et al. Comparison of ¹⁸F-FDG coincidence SPECT imaging and computed tomography in the initial staging and therapeutic evaluation of lymphomas[J]. Chin J Oncol (in Chinese), 2007, 29(7): 536–539.
[8]	Mao YS, He J, Zheng R, et al. The role of ¹⁸F-FDG DHC SPECT-CT in the diagnosis and staging for lung cancer[J]. Chin J Oncol (in Chinese), 2008, 30(12): 933–936.
[9]	Seo Y, Mari C, Hasegawa BH. Technological development and advances in single-photon emission computed tomography/computed tomography[J]. Semin Nucl Med, 2008, 38(3): 177–198. doi: 10.1053/j.semnuclmed.2008.01.001
[10]	Barret O, Carpenter TA, Clark JC, et al. Monte Carlo simulation and scatter correction of the GE Advance PET scanner with SimSET and Geant4[J]. Phys Med Biol, 2005, 50(20): 4823–4840. doi: 10.1088/0031-9155/50/20/006
[11]	Watson PG, Mainegra-Hing E, Tomic N, et al. Implementation of an efficient Monte Carlo calculation for CBCT scatter correction: phantom study[J]. J Appl Clin Med Phys, 2015, 16(4): 216–227. doi: 10.1120/jacmp.v16i4.5393
[12]	Sureau FC, Reader AJ, Comtat C, et al. Impact of image-space resolution modeling for studies with the high-resolution research tomograph[J]. J Nucl Med, 2008, 49(6): 1000–1008. doi: 10.2967/jnumed.107.045351
[13]	Rahmim A, Qi JY, Sossi V. Resolution modeling in PET imaging: theory, practice, benefits, and pitfalls[J]. Med Phys, 2013, 40(6): 064301.
[14]	Hsu B, Hu LH, Yang BH, et al. SPECT myocardial blood flow quantitation toward clinical use: a comparative study with ¹³N-Ammonia PET myocardial blood flow quantitation[J]. Eur J Nucl Med Mol Imaging, 2017, 44(1): 117–128. doi: 10.1007/s00259-016-3491-5
[15]	Gong K, Cherry SR, Qi JY. On the assessment of spatial resolution of PET systems with iterative image reconstruction[J]. Phys Med Biol, 2016, 61(5): N193–N202. doi: 10.1088/0031-9155/61/5/N193
[16]	Melcher CL. Scintillation crystals for PET[J]. J Nucl Med, 2000, 41(6): 1051–1055.
[17]	Bettinardi V, Mancosu P, Danna M, et al. Two-dimensional vs three-dimensional imaging in whole body oncologic PET/CT: a Discovery-STE phantom and patient study[J]. Q J Nucl Med Mol Imaging, 2007, 51(3): 214–223.
[18]	Tanaka E, Hasegawa T, Yamashita T, et al. A 2D/3D hybrid PET scanner with rotating partial slice-septa and its quantitative procedures[J]. Phys Med Biol, 2000, 45(10): 2821–2841. doi: 10.1088/0031-9155/45/10/307
[19]	Surti S. Update on time-of-flight PET imaging[J]. J Nucl Med, 2015, 56(1): 98–105. doi: 10.2967/jnumed.114.145029
[20]	El Fakhri G, Surti S, Trott CM, et al. Improvement in lesion detection with whole-body oncologic time-of-flight PET[J]. J Nucl Med, 2011, 52(3): 347–353. doi: 10.2967/jnumed.110.080382

[1]	Hamed Amini Amirkolaee, Hamid Amini Amirkolaee. Medical image translation using an edge-guided generative adversarial network with global-to-local feature fusion[J]. The Journal of Biomedical Research, 2022, 36(6): 409-422. DOI: 10.7555/JBR.36.20220037
[2]	Qian Sun, Yusi Hu, Saiyue Deng, Yanyu Xiong, Zhili Huang. A visualization pipeline for in vivo two-photon volumetric astrocytic calcium imaging[J]. The Journal of Biomedical Research, 2022, 36(5): 358-367. DOI: 10.7555/JBR.36.20220099
[3]	Ilakiyaselvan N., Nayeemulla Khan A., Shahina A.. Deep learning approach to detect seizure using reconstructed phase space images[J]. The Journal of Biomedical Research, 2020, 34(3): 240-250. DOI: 10.7555/JBR.34.20190043
[4]	Li Tiannv, Sun Jin, Hu Yao, Yang Min, Shi Haibin, Tang Lijun. Near-infrared fluorescent labeled CGRRAGGSC peptides for optical imaging of IL-11Rα in athymic mice bearing tumor xenografts[J]. The Journal of Biomedical Research, 2019, 33(6): 391-397. DOI: 10.7555/JBR.33.20180136
[5]	Xiaoquan Xu, Feiyun Wu, Yunxiang Chen, Hao Hu, Meiling Bao. CT and multimodal imaging findings of primary orbital Ewing's sarcoma involving the middle cranial fossa: a case report[J]. The Journal of Biomedical Research, 2017, 31(2): 170-174. DOI: 10.7555/JBR.30.20140132
[6]	Timothy McAlindon, Eckart Bartnik, Janina S. Ried, Lenore Teichert, Matthias Herrmann, Klaus Flechsenhar. Determination of serum biomarkers in osteoarthritis patients: a previous interventional imaging study revisited[J]. The Journal of Biomedical Research, 2017, 31(1): 25-30. DOI: 10.7555/JBR.31.20150167
[7]	Hongming Zhuang, Ion Codreanu. Growing applications of FDG PET-CT imaging in non-oncologic conditions[J]. The Journal of Biomedical Research, 2015, 29(3): 189-202. DOI: 10.7555/JBR.29.20140081
[8]	Marina Piccinelli, Ernest Garcia. Multimodality image fusion for diagnosing coronary artery disease[J]. The Journal of Biomedical Research, 2013, 27(6): 439-451. DOI: 10.7555/JBR.27.20130138
[9]	Yumin Zhang, Gerard B. Fox. PET imaging for receptor occupancy: meditations on calculation and simplification[J]. The Journal of Biomedical Research, 2012, 26(2): 69-76. DOI: 10.1016/S1674-8301(12)60014-1
[10]	Lihua Liu, Ming Zhang, Yuan Wang, Min Li. The relationship between the expression of tumor matrix-metalloproteinase and the characteristics of magnetic resonance imaging of human gliomas[J]. The Journal of Biomedical Research, 2010, 24(2): 124-131.