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Research ArticleImaging

Comparison of Measurement and Prognostic Power of SUV Between High-Definition and Standard PET Imaging in Non–Small Cell Lung Cancer Patients

Yonglin Pu, Bill C. Penney, Jingmian Zhang, Kevin Little, Cassie A. Simon, Nicholas Feinberg, Michael Hanzhe Zhang, Gloria Hwang and Daniel Eric Appelbaum
Journal of Nuclear Medicine Technology September 2024, 52 (3) 229-233; DOI: https://doi.org/10.2967/jnmt.124.267684
Yonglin Pu
1Department of Radiology, University of Chicago, Chicago, Illinois;
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Bill C. Penney
1Department of Radiology, University of Chicago, Chicago, Illinois;
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Jingmian Zhang
2Fourth Hospital of Hebei Medical University, Shijiazhuang, China; and
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Kevin Little
1Department of Radiology, University of Chicago, Chicago, Illinois;
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Cassie A. Simon
3Cancer Registry, University of Chicago, Chicago, Illinois
CTR
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Nicholas Feinberg
1Department of Radiology, University of Chicago, Chicago, Illinois;
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Michael Hanzhe Zhang
1Department of Radiology, University of Chicago, Chicago, Illinois;
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Gloria Hwang
1Department of Radiology, University of Chicago, Chicago, Illinois;
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Daniel Eric Appelbaum
1Department of Radiology, University of Chicago, Chicago, Illinois;
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Abstract

This study aimed to evaluate the measurement and prognostic ability of the SUVmax of whole-body tumors (SUVmaxwb) in non–small cell lung cancer (NSCLC) patients, comparing high-definition (HD) PET imaging with standard-definition (SD) PET imaging. Methods: The study included 242 consecutive NSCLC patients who underwent baseline 18F-FDG PET/CT from April 2018 to January 2021. Two imaging techniques were used: HD PET (using ordered-subsets expectation maximization with point-spread function modeling and time-of-flight techniques and smaller voxels) and SD PET (with ordered-subsets expectation maximization and time-of-flight techniques). SUVmaxwb was determined by measuring all the tumor lesions in the whole body, and tumor-to-background ratio (TBR) was calculated using the background SUVmean of various body parts. Results: The patient cohort had an average age of 68.3 y, with 59.1% being female. During a median follow-up of 29.6 mo, 83 deaths occurred. SUVmaxwb was significantly higher in HD PET than SD PET, with respective medians of 17.4 and 11.8. The TBR of 1,125 tumoral lesions was also higher in HD PET. Univariate Cox regression analysis showed that SUVmaxwb from both HD and SD PET were significantly associated with overall survival. However, after adjusting for TNM (tumor, node, metastasis) stage, only SUVmaxwb from SD PET remained significantly associated with survival. Conclusion: HD PET imaging in NSCLC patients yields higher SUVmaxwb and TBR, enhancing tumor visibility. Despite this, its prognostic value is less significant than SD PET after adjusting clinical TNM stage. Thus, consideration should be given to using HD PET reconstruction to increase tumor visibility, and SD PET is recommended for NSCLC patient prognostication and therapeutic evaluation, as well as for the classification of lung nodules.

  • non–small cell lung cancer
  • 18F-FDG
  • prognostication
  • SUV

Footnotes

  • Published online Jul. 17, 2024.

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Journal of Nuclear Medicine Technology: 52 (3)
Journal of Nuclear Medicine Technology
Vol. 52, Issue 3
September 1, 2024
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Comparison of Measurement and Prognostic Power of SUV Between High-Definition and Standard PET Imaging in Non–Small Cell Lung Cancer Patients
Yonglin Pu, Bill C. Penney, Jingmian Zhang, Kevin Little, Cassie A. Simon, Nicholas Feinberg, Michael Hanzhe Zhang, Gloria Hwang, Daniel Eric Appelbaum
Journal of Nuclear Medicine Technology Sep 2024, 52 (3) 229-233; DOI: 10.2967/jnmt.124.267684

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Comparison of Measurement and Prognostic Power of SUV Between High-Definition and Standard PET Imaging in Non–Small Cell Lung Cancer Patients
Yonglin Pu, Bill C. Penney, Jingmian Zhang, Kevin Little, Cassie A. Simon, Nicholas Feinberg, Michael Hanzhe Zhang, Gloria Hwang, Daniel Eric Appelbaum
Journal of Nuclear Medicine Technology Sep 2024, 52 (3) 229-233; DOI: 10.2967/jnmt.124.267684
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Keywords

  • non–small cell lung cancer
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