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Background <p>Body composition (BC) analysis is performed to quantify the relative amounts of different body tissues as a measure of physical fitness and tumor cachexia. We hypothesized that relative changes in body composition (BC) parameters, assessed by an artificial intelligence–based, PACS-integrated software, between baseline imaging before the start of radioligand therapy (RLT) and interim staging after two RLT cycles could predict overall survival (OS) in patients with metastatic castration-resistant prostate cancer.</p> Methods <p>We conducted a single-center, retrospective analysis of 92 patients with mCRPC undergoing [<sup>177</sup>Lu]Lu-PSMA RLT between September 2015 and December 2023. All patients had [<sup>68</sup>&#xa0;Ga]Ga-PSMA-11 PET/CT at baseline (≤ 6&#xa0;weeks before the first RLT cycle) and at interim staging (6–8&#xa0;weeks after the second RLT cycle) allowing for longitudinal BC assessment.</p> Results <p>During follow-up, 78 patients (85%) died. Median OS was 16.3&#xa0;months. Median follow-up time in survivors was 25.6&#xa0;months. The 1&#xa0;year mortality rate was 32.6% (95%CI 23.0–42.2%) and the 5&#xa0;year mortality rate was 92.9% (95%CI 85.8–100.0%). In multivariable regression, relative change in visceral adipose tissue (VAT) (HR: 0.26; <i>p</i> = 0.006), previous chemotherapy of any type (HR: 2.4; <i>p</i> = 0.003), the presence of liver metastases (HR: 2.4; <i>p</i> = 0.018) and a higher baseline De Ritis ratio (HR: 1.4; <i>p</i> &lt; 0.001) remained independent predictors of OS. Patients with a higher decrease in VAT (&lt; −20%) had a median OS of 10.2&#xa0;months versus 18.5&#xa0;months in patients with a lower VAT decrease or VAT increase (≥ −20%) (log-rank test: <i>p</i> = 0.008). In a separate Cox model, the change in VAT predicted OS (<i>p</i> = 0.005) independent of the best PSA response after 1–2 RLT cycles (<i>p</i> = 0.09), and there was no interaction between the two (<i>p</i> = 0.09).</p> Conclusions <p>PACS-Integrated, AI-based BC monitoring detects relative changes in the VAT, Which was an independent predictor of shorter OS in our population of patients undergoing RLT</p>

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AI-driven body composition monitoring and its prognostic role in mCRPC undergoing lutetium-177 PSMA radioligand therapy: insights from a retrospective single-center analysis

  • 期刊论文

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  • 发表日期：

    2025年8月28日

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  • Tristan Ruhwedel,
  • Julian Rogasch,
  • Markus Galler,
  • Imke Schatka,
  • Christoph Wetz,
  • Christian Furth,
  • Nadine Biernath,
  • Maria De Santis,
  • Seyd Shnayien,
  • Johannes Kolck,
  • Dominik Geisel,
  • Holger Amthauer,
  • Nick Lasse Beetz

摘要

Background

Body composition (BC) analysis is performed to quantify the relative amounts of different body tissues as a measure of physical fitness and tumor cachexia. We hypothesized that relative changes in body composition (BC) parameters, assessed by an artificial intelligence–based, PACS-integrated software, between baseline imaging before the start of radioligand therapy (RLT) and interim staging after two RLT cycles could predict overall survival (OS) in patients with metastatic castration-resistant prostate cancer.

Methods

We conducted a single-center, retrospective analysis of 92 patients with mCRPC undergoing [177Lu]Lu-PSMA RLT between September 2015 and December 2023. All patients had [68 Ga]Ga-PSMA-11 PET/CT at baseline (≤ 6 weeks before the first RLT cycle) and at interim staging (6–8 weeks after the second RLT cycle) allowing for longitudinal BC assessment.

Results

During follow-up, 78 patients (85%) died. Median OS was 16.3 months. Median follow-up time in survivors was 25.6 months. The 1 year mortality rate was 32.6% (95%CI 23.0–42.2%) and the 5 year mortality rate was 92.9% (95%CI 85.8–100.0%). In multivariable regression, relative change in visceral adipose tissue (VAT) (HR: 0.26; p = 0.006), previous chemotherapy of any type (HR: 2.4; p = 0.003), the presence of liver metastases (HR: 2.4; p = 0.018) and a higher baseline De Ritis ratio (HR: 1.4; p < 0.001) remained independent predictors of OS. Patients with a higher decrease in VAT (< −20%) had a median OS of 10.2 months versus 18.5 months in patients with a lower VAT decrease or VAT increase (≥ −20%) (log-rank test: p = 0.008). In a separate Cox model, the change in VAT predicted OS (p = 0.005) independent of the best PSA response after 1–2 RLT cycles (p = 0.09), and there was no interaction between the two (p = 0.09).

Conclusions

PACS-Integrated, AI-based BC monitoring detects relative changes in the VAT, Which was an independent predictor of shorter OS in our population of patients undergoing RLT