Literature DB >> 32332147

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

Robert Seifert1,2,3,4, Ken Herrmann2,3,4, Jens Kleesiek3,5, Michael Schäfers1,4, Vijay Shah6, Zhoubing Xu7, Guillaume Chabin7, Sasa Grbic7, Bruce Spottiswoode6, Kambiz Rahbar8,4.   

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: R 2 = 1.000, P < 0.001; SUVmax: R 2 = 0.988, P < 0.001). The interobserver agreement of the semiautomated workflow was also high (PSMATV50: R 2 = 1.000, P < 0.001, interclass correlation coefficient = 1.000; SUVmax: R 2 = 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.
© 2020 by the Society of Nuclear Medicine and Molecular Imaging.

Entities:  

Keywords:  PSMA-PET/CT; image biomarker; prostate cancer; tumor volume

Mesh:

Substances:

Year:  2020        PMID: 32332147     DOI: 10.2967/jnumed.120.242057

Source DB:  PubMed          Journal:  J Nucl Med        ISSN: 0161-5505            Impact factor:   10.057


  18 in total

1.  Machine learning-based radiomics for multiple primary prostate cancer biological characteristics prediction with 18F-PSMA-1007 PET: comparison among different volume segmentation thresholds.

Authors:  Kun Tang; Yunjun Yang; Fei Yao; Shuying Bian; Dongqin Zhu; Yaping Yuan; Kehua Pan; Zhifang Pan; Xianghao Feng
Journal:  Radiol Med       Date:  2022-08-26       Impact factor: 6.313

2.  First results on kinetic modelling and parametric imaging of dynamic 18F-FDG datasets from a long axial FOV PET scanner in oncological patients.

Authors:  Hasan Sari; Clemens Mingels; Ian Alberts; Jicun Hu; Dorothee Buesser; Vijay Shah; Robin Schepers; Patrik Caluori; Vladimir Panin; Maurizio Conti; Ali Afshar-Oromieh; Kuangyu Shi; Lars Eriksson; Axel Rominger; Paul Cumming
Journal:  Eur J Nucl Med Mol Imaging       Date:  2022-01-04       Impact factor: 10.057

3.  Semiautomatic Tumor Delineation for Evaluation of 64Cu-DOTATATE PET/CT in Patients with Neuroendocrine Neoplasms: Prognostication Based on Lowest Lesion Uptake and Total Tumor Volume.

Authors:  Esben Andreas Carlsen; Camilla Bardram Johnbeck; Mathias Loft; Andreas Pfeifer; Peter Oturai; Seppo W Langer; Ulrich Knigge; Claes Nøhr Ladefoged; Andreas Kjaer
Journal:  J Nucl Med       Date:  2021-02-26       Impact factor: 11.082

4.  Assessing Response to [177Lu]PSMA Radioligand Therapy using modified PSMA PET Progression Criteria.

Authors:  Kerstin Michalski; Claudius Klein; Tonio Brueggemann; Philipp T Meyer; Cordula Annette Jilg; Juri Ruf
Journal:  J Nucl Med       Date:  2021-03-31       Impact factor: 11.082

5.  Analysis of PSMA expression and outcome in patients with advanced Prostate Cancer receiving 177Lu-PSMA-617 Radioligand Therapy.

Authors:  Robert Seifert; Konstantin Seitzer; Ken Herrmann; Katharina Kessel; Michael Schäfers; Jens Kleesiek; Matthias Weckesser; Martin Boegemann; Kambiz Rahbar
Journal:  Theranostics       Date:  2020-06-19       Impact factor: 11.556

6.  Prostate-Specific Membrane Antigen Uptake and Survival in Metastatic Castration-Resistant Prostate Cancer.

Authors:  Panagiotis J Vlachostergios; Muhammad Junaid Niaz; Michael Sun; Seyed Ali Mosallaie; Charlene Thomas; Paul J Christos; Joseph R Osborne; Ana M Molina; David M Nanus; Neil H Bander; Scott T Tagawa
Journal:  Front Oncol       Date:  2021-02-18       Impact factor: 6.244

7.  Early PSA Change after [177Lu]PSMA-617 Radioligand Therapy as a Predicator of Biochemical Response and Overall Survival.

Authors:  Felix Kind; Thomas F Fassbender; Geoffroy Andrieux; Melanie Boerries; Philipp T Meyer; Juri Ruf
Journal:  Cancers (Basel)       Date:  2021-12-29       Impact factor: 6.639

Review 8.  Imaging and liquid biopsy in the prediction and evaluation of response to PRRT in neuroendocrine tumors: implications for patient management.

Authors:  Wolfgang Roll; Matthias Weckesser; Robert Seifert; Lisa Bodei; Kambiz Rahbar
Journal:  Eur J Nucl Med Mol Imaging       Date:  2021-04-26       Impact factor: 10.057

9.  Feasibility of Different Tumor Delineation Approaches for 18F-PSMA-1007 PET/CT Imaging in Prostate Cancer Patients.

Authors:  Lena M Mittlmeier; Matthias Brendel; Leonie Beyer; Nathalie L Albert; Andrei Todica; Mathias J Zacherl; Vera Wenter; Annika Herlemann; Alexander Kretschmer; Stephan T Ledderose; Nina-Sophie Schmidt-Hegemann; Wolfgang G Kunz; Jens Ricke; Peter Bartenstein; Harun Ilhan; Marcus Unterrainer
Journal:  Front Oncol       Date:  2021-05-21       Impact factor: 6.244

10.  Total tumor volume reduction and low PSMA expression in patients receiving Lu-PSMA therapy.

Authors:  Robert Seifert; Katharina Kessel; Katrin Schlack; Matthias Weckesser; David Kersting; Konstantin E Seitzer; Manuel Weber; Martin Bögemann; Kambiz Rahbar
Journal:  Theranostics       Date:  2021-07-13       Impact factor: 11.556

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