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CT-derived body composition measurements as predictors for neoadjuvant treatment tolerance and survival in gastroesophageal adenocarcinoma

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Abstract

Purpose

Treatment for gastroesophageal adenocarcinomas can result in significant morbidity and mortality. The purpose of this study is to supplement methods for choosing treatment strategy by assessing the relationship between CT-derived body composition, patient, and tumor features, and clinical outcomes in this population.

Methods

Patients with neoadjuvant treatment, biopsy-proven gastroesophageal adenocarcinoma, and initial staging CTs were retrospectively identified from institutional clinic encounters between 2000 and 2019. Details about patient, disease, treatment, and outcomes (including therapy tolerance and survival) were extracted from electronic medical records. A deep learning semantic segmentation algorithm was utilized to measure cross-sectional areas of skeletal muscle (SM), visceral fat (VF), and subcutaneous fat (SF) at the L3 vertebra level on staging CTs. Univariate and multivariate analyses were performed to assess the relationships between predictors and outcomes.

Results

142 patients were evaluated. Median survival was 52 months. Univariate and multivariate analysis showed significant associations between treatment tolerance and SM and VF area, SM to fat and VF to SF ratios, and skeletal muscle index (SMI) (p = 0.004–0.04). Increased survival was associated with increased body mass index (BMI) (p = 0.01) and increased SMI (p = 0.004). A multivariate Cox model consisting of BMI, SMI, age, gender, and stage demonstrated that patients in the high-risk group had significantly lower survival (HR = 1.77, 95% CI = 1.13–2.78, p = 0.008).

Conclusion

CT-based measures of body composition in patients with gastroesophageal adenocarcinoma may be independent predictors of treatment complications and survival and can supplement methods for assessing functional status during treatment planning.

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Author information

Author notes

  1. Kyle J. Lafata and Mustafa R. Bashir are co-last authors.

Authors and Affiliations

  1. Department of Radiology, Duke University Medical Center, 2301 Erwin Road, Box 3808, Durham, NC, 27710, USA

    Mariana R. DeFreitas, Amadu Toronka, Marybeth A. Nedrud, Sarah Cubberley, Islam H. Zaki, Brandon Konkel, Kyle J. Lafata & Mustafa R. Bashir

  2. Department of Medicine, Medical Oncology Division, Duke University School of Medicine, Durham, NC, USA

    Hope E. Uronis & Mustafa R. Bashir

  3. Department of Radiation Oncology, Duke University School of Medicine, Durham, NC, USA

    Manisha Palta & Kyle J. Lafata

  4. Department of Surgery, Duke University School of Medicine, Durham, NC, USA

    Dan G. Blazer

  5. Electrical and Computer Engineering, Duke University, Durham, NC, USA

    Kyle J. Lafata

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  1. Mariana R. DeFreitas
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DeFreitas, M.R., Toronka, A., Nedrud, M.A. et al. CT-derived body composition measurements as predictors for neoadjuvant treatment tolerance and survival in gastroesophageal adenocarcinoma. Abdom Radiol 48, 211–219 (2023). https://doi.org/10.1007/s00261-022-03695-y

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