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Research ArticleTheranostics

Semiautomatically Quantified Tumor Volume Using 68Ga-PSMA-11 PET as a Biomarker for Survival in Patients with Advanced Prostate Cancer

Robert Seifert, Ken Herrmann, Jens Kleesiek, Michael Schäfers, Vijay Shah, Zhoubing Xu, Guillaume Chabin, Sasa Grbic, Bruce Spottiswoode and Kambiz Rahbar
Journal of Nuclear Medicine December 2020, 61 (12) 1786-1792; DOI: https://doi.org/10.2967/jnumed.120.242057
Robert Seifert
1Department of Nuclear Medicine, University Hospital Münster, Münster, Germany
2Department of Nuclear Medicine, University Hospital Essen, Essen, Germany
3German Cancer Consortium (DKTK), Essen, Germany
4West German Cancer Center, Muenster and Essen, Germany
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Ken Herrmann
2Department of Nuclear Medicine, University Hospital Essen, Essen, Germany
3German Cancer Consortium (DKTK), Essen, Germany
4West German Cancer Center, Muenster and Essen, Germany
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Jens Kleesiek
3German Cancer Consortium (DKTK), Essen, Germany
5Division of Radiology, German Cancer Research Center, Heidelberg, Germany
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Michael Schäfers
1Department of Nuclear Medicine, University Hospital Münster, Münster, Germany
4West German Cancer Center, Muenster and Essen, Germany
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Vijay Shah
6Siemens Medical Solutions USA, Inc., Knoxville, Tennessee; and
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Zhoubing Xu
7Siemens Medical Solutions USA, Inc., Princeton, New Jersey
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Guillaume Chabin
7Siemens Medical Solutions USA, Inc., Princeton, New Jersey
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Sasa Grbic
7Siemens Medical Solutions USA, Inc., Princeton, New Jersey
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Bruce Spottiswoode
6Siemens Medical Solutions USA, Inc., Knoxville, Tennessee; and
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Kambiz Rahbar
1Department of Nuclear Medicine, University Hospital Münster, Münster, Germany
4West German Cancer Center, Muenster and Essen, Germany
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Abstract

Prostate-specific membrane antigen (PSMA)–targeting PET imaging is becoming the reference standard for prostate cancer staging, especially in advanced disease. Yet, the implications of PSMA PET–derived whole-body tumor volume for overall survival are poorly elucidated to date. This might be because semiautomated quantification of whole-body tumor volume as a PSMA PET biomarker is an unmet clinical challenge. Therefore, in the present study we propose and evaluate a software that enables the semiautomated quantification of PSMA PET biomarkers such as whole-body tumor volume. Methods: The proposed quantification is implemented as a research prototype. PSMA-accumulating foci were automatically segmented by a percental threshold (50% of local SUVmax). Neural networks were trained to segment organs in PET/CT acquisitions (training CTs: 8,632, validation CTs: 53). Thereby, PSMA foci within organs of physiologic PSMA uptake were semiautomatically excluded from the analysis. Pretherapeutic PSMA PET/CTs of 40 consecutive patients treated with 177Lu-PSMA-617 were evaluated in this analysis. The whole-body tumor volume (PSMATV50), SUVmax, SUVmean, and other whole-body imaging biomarkers were calculated for each patient. Semiautomatically derived results were compared with manual readings in a subcohort (by 1 nuclear medicine physician). Additionally, an interobserver evaluation of the semiautomated approach was performed in a subcohort (by 2 nuclear medicine physicians). Results: Manually and semiautomatically derived PSMA metrics were highly correlated (PSMATV50: R2 = 1.000, P < 0.001; SUVmax: R2 = 0.988, P < 0.001). The interobserver agreement of the semiautomated workflow was also high (PSMATV50: R2 = 1.000, P < 0.001, interclass correlation coefficient = 1.000; SUVmax: R2 = 0.988, P < 0.001, interclass correlation coefficient = 0.997). PSMATV50 (ml) was a significant predictor of overall survival (hazard ratio: 1.004; 95% confidence interval: 1.001–1.006, P = 0.002) and remained so in a multivariate regression including other biomarkers (hazard ratio: 1.004; 95% confidence interval: 1.001–1.006 P = 0.004). Conclusion: PSMATV50 is a promising PSMA PET biomarker that is reproducible and easily quantified by the proposed semiautomated software. Moreover, PSMATV50 is a significant predictor of overall survival in patients with advanced prostate cancer who receive 177Lu-PSMA-617 therapy.

  • PSMA-PET/CT
  • prostate cancer
  • image biomarker
  • tumor volume

Footnotes

  • Published online Apr. 24, 2020.

  • © 2020 by the Society of Nuclear Medicine and Molecular Imaging.
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Journal of Nuclear Medicine: 61 (12)
Journal of Nuclear Medicine
Vol. 61, Issue 12
December 1, 2020
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Semiautomatically Quantified Tumor Volume Using 68Ga-PSMA-11 PET as a Biomarker for Survival in Patients with Advanced Prostate Cancer
Robert Seifert, Ken Herrmann, Jens Kleesiek, Michael Schäfers, Vijay Shah, Zhoubing Xu, Guillaume Chabin, Sasa Grbic, Bruce Spottiswoode, Kambiz Rahbar
Journal of Nuclear Medicine Dec 2020, 61 (12) 1786-1792; DOI: 10.2967/jnumed.120.242057

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Semiautomatically Quantified Tumor Volume Using 68Ga-PSMA-11 PET as a Biomarker for Survival in Patients with Advanced Prostate Cancer
Robert Seifert, Ken Herrmann, Jens Kleesiek, Michael Schäfers, Vijay Shah, Zhoubing Xu, Guillaume Chabin, Sasa Grbic, Bruce Spottiswoode, Kambiz Rahbar
Journal of Nuclear Medicine Dec 2020, 61 (12) 1786-1792; DOI: 10.2967/jnumed.120.242057
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Keywords

  • PSMA-PET/CT
  • prostate cancer
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  • tumor volume
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