Prognostic value of body composition out of PSMA-PET/CT in prostate cancer patients undergoing PSMA-therapy

Bray F, Laversanne M, Sung H, Ferlay J, Siegel RL, Soerjomataram I, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2024;74:229–63.

Article  PubMed  Google Scholar 

Sandhu S, Moore CM, Chiong E, Beltran H, Bristow RG, Williams SG. Prostate cancer. Lancet. 2021;398:1075–90.

Article  PubMed  CAS  Google Scholar 

Sartor O, de Bono J, Chi KN, Fizazi K, Herrmann K, Rahbar K, et al. Lutetium-177-PSMA-617 for Metastatic Castration-Resistant Prostate Cancer. N Engl J Med. 2021;385:1091–103.

Article  PubMed  PubMed Central  CAS  Google Scholar 

Kratochwil C, Fendler WP, Eiber M, Hofman MS, Emmett L, Calais J, et al. Joint EANM/SNMMI procedure guideline for the use of 177Lu-labeled PSMA-targeted radioligand-therapy (177Lu-PSMA-RLT). Eur J Nucl Med Mol Imaging. 2023;50:2830–45.

Article  PubMed  PubMed Central  CAS  Google Scholar 

Hartrampf PE, Hüttmann T, Seitz AK, Kübler H, Serfling SE, Schlötelburg W, et al. SUVmean on baseline [18F]PSMA-1007 PET and clinical parameters are associated with survival in prostate cancer patients scheduled for [177Lu]Lu-PSMA I&T. Eur J Nucl Med Mol Imaging. 2023;50:3465–74.

Article  PubMed  PubMed Central  CAS  Google Scholar 

Seifert R, Kessel K, Schlack K, Weber M, Herrmann K, Spanke M, et al. PSMA PET total tumor volume predicts outcome of patients with advanced prostate cancer receiving [177Lu]Lu-PSMA-617 radioligand therapy in a bicentric analysis. Eur J Nucl Med Mol Imaging. 2021;48:1200–10.

Article  PubMed  CAS  Google Scholar 

Rahbar Nikoukar L, Seifert R, Ventura D, Schindler P, Bögemann M, Rahbar K, et al. Prognostic value of pretherapeutic 68Ga-PSMA-11-PET based imaging parameters in mCRPC patients treated with PSMA radioligands. Nuklearmedizin. 2024.

Kuo P, Hesterman J, Rahbar K, Kendi AT, Wei XX, Fang B, et al. [68 Ga]Ga-PSMA-11 PET baseline imaging as a prognostic tool for clinical outcomes to [177 Lu]Lu-PSMA-617 in patients with mCRPC: A VISION substudy. J Clin Oncol. 2022;40:5002–5002.

Article  Google Scholar 

Ke ZB, You Q, Xue YT, Sun JB, Chen JY, Liu WQ, et al. Body composition parameters were associated with response to abiraterone acetate and prognosis in patients with metastatic castration-resistant prostate cancer. Cancer Med. 2023;12:8251–66.

Article  PubMed  PubMed Central  CAS  Google Scholar 

Bauckneht M, Lai R, D’Amico F, Miceli A, Donegani MI, Campi C, et al. Opportunistic skeletal muscle metrics as prognostic tools in metastatic castration-resistant prostate cancer patients candidates to receive Radium-223. Ann Nucl Med. 2022;36:373–83.

Article  PubMed  PubMed Central  CAS  Google Scholar 

Antoun S, Bayar A, Ileana E, Laplanche A, Fizazi K, Di Palma M, et al. High subcutaneous adipose tissue predicts the prognosis in metastatic castration-resistant prostate cancer patients in post chemotherapy setting. Eur J Cancer. 2015;51:2570–7.

Article  PubMed  Google Scholar 

Hartrampf PE, Mihatsch PW, Seitz AK, Solnes LB, Rowe SP, Pomper MG, et al. Elevated body mass index is associated with improved overall survival in castration-resistant prostate cancer patients undergoing prostate-specific membrane antigen-directed radioligand therapy. J Nucl Med. 2023;64:1272–8.

Article  PubMed  CAS  Google Scholar 

Keyl J, Bucher A, Jungmann F, Hosch R, Ziller A, Armbruster R, et al. Prognostic value of deep learning-derived body composition in advanced pancreatic cancer-a retrospective multicenter study. ESMO Open. 2024;9:102219.

Article  PubMed  PubMed Central  CAS  Google Scholar 

Keyl J, Hosch R, Berger A, Ester O, Greiner T, Bogner S, et al. Deep learning-based assessment of body composition and liver tumour burden for survival modelling in advanced colorectal cancer. J Cachexia Sarcopenia Muscle. 2023;14:545–52.

Article  PubMed  Google Scholar 

Ying T, Borrelli P, Edenbrandt L, Enqvist O, Kaboteh R, Trägårdh E, et al. AI-based fully automatic image analysis: Optimal abdominal and thoracic segmentation volumes for estimating total muscle volume on computed tomography scans. Osteoporos Sarcopenia. 2024;10:78–83.

Article  PubMed  PubMed Central  Google Scholar 

Isensee F, Jaeger PF, Kohl SAA, Petersen J, Maier-Hein KH. nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation. Nat Methods. 2021;18:203–11.

Article  PubMed  CAS  Google Scholar 

Wasserthal J, Breit HC, Meyer MT, Pradella M, Hinck D, Sauter AW, et al. TotalSegmentator: Robust segmentation of 104 Anatomic Structures in CT Images. Radiol Artif Intell. 2023;5:e230024.

Article  PubMed  PubMed Central  Google Scholar 

Haubold J, Baldini G, Parmar V, Schaarschmidt BM, Koitka S, Kroll L, et al. BOA: A CT-based body and organ analysis for radiologists at the point of care. Invest Radiol. 2024;59:433–41.

Article  PubMed  CAS  Google Scholar 

Davidson-Pilon C. Lifelines: survival analysis in Python. J Open Source Softw. 2019;4:1317.

Seabold S, Perktold J. Statsmodels: Econometric and statistical modeling with python. P SciPy. 2010;7:92–6.

Chiang PK, Tsai WK, Chiu AWH, Lin JB, Yang FY, Lee J. Muscle loss during androgen deprivation therapy is associated with higher risk of non-cancer mortality in high-risk prostate cancer. Front Oncol. 2021;11:722652.

Article  PubMed  PubMed Central  Google Scholar 

Chen PC, Chiang PK, Lin JB, Tsai WK, Lin WC, Jan YT, et al. Thresholds of body composition changes associated with survival during androgen deprivation therapy in prostate cancer. Eur Urol Open Sci. 2024;70:99–108.

Article  PubMed  PubMed Central  Google Scholar 

Cushen SJ, Power DG, Murphy KP, McDermott R, Griffin BT, Lim M, et al. Impact of body composition parameters on clinical outcomes in patients with metastatic castrate-resistant prostate cancer treated with docetaxel. Clin Nutr ESPEN. 2016;13:e39-45.

Article  PubMed  Google Scholar 

Schaudinn A, Linder N, Garnov N, Kerlikowsky F, Blüher M, Dietrich A, et al. Predictive accuracy of single-and multi-slice MRI for the estimation of total visceral adipose tissue in overweight to severely obese patients. NMR Biomed. 2015;28:583–90.

Article  PubMed  Google Scholar 

Jung M, Raghu VK, Reisert M, Rieder H, Rospleszcz S, Pischon T, et al. Deep learning-based body composition analysis from whole-body magnetic resonance imaging to predict all-cause mortality in a large western population. EBioMedicine. 2024;110:105467.

Article  PubMed  PubMed Central  Google Scholar 

Decazes P, Ammari S, De Prévia A, Mottay L, Lawrance L, Belkouchi Y, et al. Body composition to define prognosis of cancers treated by anti-angiogenic drugs. Diagnostics. 2023;13:205.

Article  PubMed  PubMed Central  CAS  Google Scholar 

Rämö JT, Kany S, Hou CR, Friedman SF, Roselli C, Nauffal V, et al. Cardiovascular significance and genetics of epicardial and pericardial adiposity. JAMA Cardiol. 2024;9:418–27.

Article  PubMed  PubMed Central  Google Scholar 

Lopez P, Newton RU, Taaffe DR, Singh F, Buffart LM, Spry N, et al. Associations of fat and muscle mass with overall survival in men with prostate cancer: a systematic review with meta-analysis. Prostate Cancer Prostat Dis. 2021;25:615–26.

Article  Google Scholar 

Lim JP, Chong MS, Tay L, Yang YX, Leung BP, Yeo A, et al. Inter-muscular adipose tissue is associated with adipose tissue inflammation and poorer functional performance in central adiposity. Arch Gerontol Geriatr. 2019;81:1–7.

Article  PubMed  CAS  Google Scholar 

Visser M, Study for the HA, Goodpaster BH, Study for the HA, Kritchevsky SB, Study for the HA, et al. Muscle mass, muscle strength, and muscle fat infiltration as predictors of incident mobility limitations in well-functioning older persons. J Gerontol Series A. 2005;60:324–33.

Seifert R, Herrmann K, Kleesiek J, Schäfers M, Shah V, Xu Z, et al. Semiautomatically quantified tumor volume using 68Ga-PSMA-11 PET as a biomarker for survival in patients with advanced prostate cancer. J Nucl Med. 2020;61:1786–92.

Article  PubMed  CAS  Google Scholar 

Kuo PH, Morris MJ, Hesterman J, Kendi AT, Rahbar K, Wei XX, et al. Quantitative 68Ga-PSMA-11 PET and clinical outcomes in metastatic castration-resistant prostate cancer following 177Lu-PSMA-617 (VISION trial). Radiology. 2024;312:e233460.

Article  PubMed  Google Scholar 

Herrmann K, Gafita A, de Bono JS, Sartor O, Chi KN, Krause BJ, et al. Multivariable models of outcomes with [177Lu] Lu-PSMA-617: analysis of the phase 3 VISION trial. EClinicalMedicine. 2024;77:102862.

Article  PubMed  PubMed Central 

Comments (0)

No login
gif