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Quantification of chemotherapy-induced changes in body composition in pediatric, adolescent, and young adult lymphoma using standard of care CT imaging

  • Oncology
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Objectives

The objective of this study was to use computed tomography (CT) imaging to quantify chemotherapy-induced changes in body composition (BC) in pediatric, adolescent, and young adult (AYA) patients with lymphoma and to compare image-derived changes in BC measures to changes in traditional body mass index (BMI) measures.

Methods

Skeletal muscle (SkM), subcutaneous adipose tissue (SAT), and visceral adipose tissue (VAT) volumes were manually segmented using low-dose CT images acquired from a 10-year retrospective, single-site cohort of 110 patients with lymphoma. CT images and BMI percentiles (BMI%) were acquired from baseline and first therapeutic follow-up. CT image segmentation was performed at vertebral level L3 using 5 consecutive axial CT images.

Results

CT imaging detected significant treatment-induced changes in BC measures from baseline to first follow-up time points, with SAT and VAT significantly increasing and SkM significantly decreasing. BMI% measures did not change from baseline to first follow-up and were not significantly correlated with changes in image-derived BC measures. Patients who were male, younger than 12 years old, diagnosed with non-Hodgkin’s lymphoma, and presented with stage 3 or 4 disease gained more adipose tissue and lost more SkM in response to the first cycle of treatment compared to their clinical counterparts.

Conclusions

Standard of care CT imaging can quantify treatment-induced changes in BC that are not reflected by traditional BMI assessment. Image-based monitoring of BC parameters may offer personalized approaches to lymphoma treatment for pediatric and AYA patients by guiding cancer treatment recommendations and subsequently enhance clinical outcomes.

Key Points

• Standard of care low-dose CT imaging quantifies chemotherapy-induced changes in body composition in pediatric, adolescent, and young adults with lymphoma.

• Body mass index could not detect changes in body composition during treatment that were quantified by CT imaging.

• Pediatric and AYA patients who were male, younger than 12 years old, and diagnosed with non-Hodgkin’s lymphoma, and presented with stage 3 or 4 disease gained more adipose tissue and lost more skeletal muscle tissue in response to the first cycle of treatment compared to their clinical counterparts.

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Abbreviations

ALL:

Acute lymphoblastic leukemia

AYA:

Adolescent and young adult

BC:

Body composition

BMI:

Body mass index

CT :

Computed tomography

DXA:

Dual-energy X-ray absorptiometry

MR:

Magnetic resonance

SAT:

Subcutaneous adipose tissue

SkM:

Skeletal muscle

VAT :

Visceral adipose tissue

References

  1. Caan BJ, Cespedes Feliciano EM, Prado CM et al (2018) Association of muscle and adiposity measured by computed tomography with survival in patients with nonmetastatic breast cancer. JAMA Oncol 4:798–804

    Article  PubMed  PubMed Central  Google Scholar 

  2. Ryan AM, Prado CM, Sullivan ES, Power DG, Daly LE (2019) Effects of weight loss and sarcopenia on response to chemotherapy, quality of life, and survival. Nutrition 67-68:110539

    Article  PubMed  Google Scholar 

  3. Daly LE, Ni Bhuachalla EB, Power DG, Cushen SJ, James K, Ryan AM (2018) Loss of skeletal muscle during systemic chemotherapy is prognostic of poor survival in patients with foregut cancer. J Cachexia Sarcopenia Muscle 9:315–325

    Article  PubMed  PubMed Central  Google Scholar 

  4. Cespedes Feliciano EM, Chen WY, Lee V et al (2020) Body composition, adherence to anthracycline and taxane-based chemotherapy, and survival after nonmetastatic breast cancer. JAMA Oncol 6:264–270

    Article  PubMed  Google Scholar 

  5. Thompson PA, Rosner GL, Matthay KK et al (2009) Impact of body composition on pharmacokinetics of doxorubicin in children: a Glaser Pediatric Research Network study. Cancer Chemother Pharmacol 64:243–251

    Article  CAS  PubMed  Google Scholar 

  6. Prado CM, Maia YL, Ormsbee M, Sawyer MB, Baracos VE (2013) Assessment of nutritional status in cancer--the relationship between body composition and pharmacokinetics. Anticancer Agents Med Chem 13:1197–1203

    Article  CAS  PubMed  Google Scholar 

  7. Prado CM, Lima IS, Baracos VE et al (2011) An exploratory study of body composition as a determinant of epirubicin pharmacokinetics and toxicity. Cancer Chemother Pharmacol 67:93–101

    Article  CAS  PubMed  Google Scholar 

  8. Prado CM, Baracos VE, McCargar LJ et al (2007) Body composition as an independent determinant of 5-fluorouracil-based chemotherapy toxicity. Clin Cancer Res 13:3264–3268

    Article  CAS  PubMed  Google Scholar 

  9. Joffe L, Schadler KL, Shen W, Ladas EJ (2019) Body composition in pediatric solid tumors: state of the science and future directions. J Natl Cancer Inst Monogr 2019:144–148

    Article  PubMed  PubMed Central  Google Scholar 

  10. Kaestner SA, Sewell GJ (2007) Chemotherapy dosing part I: scientific basis for current practice and use of body surface area. Clin Oncol (R Coll Radiol) 19:23–37

    Article  CAS  Google Scholar 

  11. Orgel E, Mueske NM, Sposto R, Gilsanz V, Freyer DR, Mittelman SD (2018) Limitations of body mass index to assess body composition due to sarcopenic obesity during leukemia therapy. Leuk Lymphoma 59:138–145

    Article  PubMed  Google Scholar 

  12. Murphy AJ, White M, Davies PS (2010) Body composition of children with cancer. Am J Clin Nutr 92:55–60

    Article  CAS  PubMed  Google Scholar 

  13. Collins L, Beaumont L, Cranston A, Savoie S, Nayiager T, Barr R (2017) Anthropometry in long-term survivors of acute lymphoblastic leukemia in childhood and adolescence. J Adolesc Young Adult Oncol 6:294–298

    Article  PubMed  Google Scholar 

  14. Prado CM, Lieffers JR, McCargar LJ et al (2008) Prevalence and clinical implications of sarcopenic obesity in patients with solid tumours of the respiratory and gastrointestinal tracts: a population-based study. Lancet Oncol 9:629–635

    Article  PubMed  Google Scholar 

  15. Prado CM, Baracos VE, McCargar LJ et al (2009) Sarcopenia as a determinant of chemotherapy toxicity and time to tumor progression in metastatic breast cancer patients receiving capecitabine treatment. Clin Cancer Res 15:2920–2926

    Article  CAS  PubMed  Google Scholar 

  16. Mei KL, Batsis JA, Mills JB, Holubar SD (2016) Sarcopenia and sarcopenic obesity: do they predict inferior oncologic outcomes after gastrointestinal cancer surgery? Perioper Med (Lond) 5:30

    Article  Google Scholar 

  17. Yip C, Dinkel C, Mahajan A, Siddique M, Cook GJ, Goh V (2015) Imaging body composition in cancer patients: visceral obesity, sarcopenia and sarcopenic obesity may impact on clinical outcome. Insights Imaging 6:489–497

    Article  PubMed  PubMed Central  Google Scholar 

  18. Martin L, Birdsell L, Macdonald N et al (2013) Cancer cachexia in the age of obesity: skeletal muscle depletion is a powerful prognostic factor, independent of body mass index. J Clin Oncol 31:1539–1547

    Article  PubMed  Google Scholar 

  19. Murphy AJ, White M, Elliott SA, Lockwood L, Hallahan A, Davies PS (2015) Body composition of children with cancer during treatment and in survivorship. Am J Clin Nutr 102:891–896

    Article  CAS  PubMed  Google Scholar 

  20. den Hoed MA, Pluijm SM, de Groot-Kruseman HA et al (2015) The negative impact of being underweight and weight loss on survival of children with acute lymphoblastic leukemia. Haematologica 100:62–69

    Article  Google Scholar 

  21. Brinksma A, Sanderman R, Roodbol PF et al (2015) Malnutrition is associated with worse health-related quality of life in children with cancer. Support Care Cancer 23:3043–3052

    Article  PubMed  PubMed Central  Google Scholar 

  22. Santoro A, Guidarelli G, Ostan R et al (2019) Gender-specific association of body composition with inflammatory and adipose-related markers in healthy elderly Europeans from the NU-AGE study. Eur Radiol 29:4968–4979

    Article  PubMed  PubMed Central  Google Scholar 

  23. Lee SY, Gallagher D (2008) Assessment methods in human body composition. Curr Opin Clin Nutr Metab Care 11:566–572

    Article  PubMed  PubMed Central  Google Scholar 

  24. Williams JE, Wells JC, Wilson CM, Haroun D, Lucas A, Fewtrell MS (2006) Evaluation of Lunar Prodigy dual-energy X-ray absorptiometry for assessing body composition in healthy persons and patients by comparison with the criterion 4-component model. Am J Clin Nutr 83:1047–1054

    Article  CAS  PubMed  Google Scholar 

  25. Salinas-Miranda E, Deniffel D, Dong X et al (2021) Prognostic value of early changes in CT-measured body composition in patients receiving chemotherapy for unresectable pancreatic cancer. Eur Radiol 31:8662–8670

    Article  PubMed  Google Scholar 

  26. Peng YC, Wu CH, Tien YW, Lu TP, Wang YH, Chen BB (2021) Preoperative sarcopenia is associated with poor overall survival in pancreatic cancer patients following pancreaticoduodenectomy. Eur Radiol 31:2472–2481

    Article  PubMed  Google Scholar 

  27. Joffe L, Dwyer S, Glade Bender JL, Frazier AL, Ladas EJ (2019) Nutritional status and clinical outcomes in pediatric patients with solid tumors : a systematic review of the literature. Semin Oncol 46:48–56

    Article  PubMed  Google Scholar 

  28. Shen W, Punyanitya M, Wang Z et al (2004) Total body skeletal muscle and adipose tissue volumes: estimation from a single abdominal cross-sectional image. J Appl Physiol (1985) 97:2333–2338

    Article  Google Scholar 

  29. Yang HR, Choi HS (2019) A prospective study on changes in body composition and fat percentage during the first year of cancer treatment in children. Nutr Res Pract 13:214–221

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Suzuki D, Kobayashi R, Sano H, Hori D, Kobayashi K (2018) Sarcopenia after induction therapy in childhood acute lymphoblastic leukemia: its clinical significance. Int J Hematol 107:486–489

    Article  PubMed  Google Scholar 

  31. Murphy AJ, Wells JC, Williams JE, Fewtrell MS, Davies PS, Webb DK (2006) Body composition in children in remission from acute lymphoblastic leukemia. Am J Clin Nutr 83:70–74

    Article  CAS  PubMed  Google Scholar 

  32. Rayar M, Webber CE, Nayiager T, Sala A, Barr RD (2013) Sarcopenia in children with acute lymphoblastic leukemia. J Pediatr Hematol Oncol 35:98–102

    Article  PubMed  Google Scholar 

  33. Mueske NM, Mittelman SD, Wren TAL, Gilsanz V, Orgel E (2019) Myosteatosis in adolescents and young adults treated for acute lymphoblastic leukemia. Leuk Lymphoma 60:3146–3153

    Article  PubMed  PubMed Central  Google Scholar 

  34. Armenian SH, Iukuridze A, Teh JB et al (2020) Abnormal body composition is a predictor of adverse outcomes after autologous haematopoietic cell transplantation. J Cachexia Sarcopenia Muscle 11:962–972

    Article  PubMed  PubMed Central  Google Scholar 

  35. Marriott CJC, Beaumont LF, Farncombe TH et al (2018) Body composition in long-term survivors of acute lymphoblastic leukemia diagnosed in childhood and adolescence: a focus on sarcopenic obesity. Cancer 124:1225–1231

    Article  CAS  PubMed  Google Scholar 

  36. Ooi PH, Thompson-Hodgetts S, Pritchard-Wiart L, Gilmour SM, Mager DR (2020) Pediatric sarcopenia: a paradigm in the overall definition of malnutrition in children? JPEN J Parenter Enteral Nutr 44:407–418

    Article  PubMed  Google Scholar 

  37. Liu J, Yan Y, Xi B et al (2019) Skeletal muscle reference for Chinese children and adolescents. J Cachexia Sarcopenia Muscle 10:155–164

    Article  PubMed  Google Scholar 

  38. Joffe L, Shen W, Shadid G, Jin Z, Ladas EJ (2021) Skeletal muscle and adipose tissue changes in the first phase of treatment of pediatric solid tumors. Cancer Med 10:15–22

    Article  CAS  PubMed  Google Scholar 

  39. Mourtzakis M, Prado CM, Lieffers JR, Reiman T, McCargar LJ, Baracos VE (2008) A practical and precise approach to quantification of body composition in cancer patients using computed tomography images acquired during routine care. Appl Physiol Nutr Metab 33:997–1006

    Article  PubMed  Google Scholar 

  40. Papademetris X, Jackowski MP, Rajeevan N et al (2006) BioImage Suite: An integrated medical image analysis suite: an update. Insight J 2006:209

    PubMed  PubMed Central  Google Scholar 

  41. van Vugt JL, Levolger S, Gharbharan A et al (2017) A comparative study of software programmes for cross-sectional skeletal muscle and adipose tissue measurements on abdominal computed tomography scans of rectal cancer patients. J Cachexia Sarcopenia Muscle 8:285–297

    Article  PubMed  Google Scholar 

  42. Centers for Disease Control and Prevention. Healthy weight, about child and teen BMI. Available via https://www.cdc.gov/healthyweight/assessing/bmi/childrens_bmi/about_childrens_bmi.html. Accessed 09/13/2021

  43. Lee SJ, Liu J, Yao J, Kanarek A, Summers RM, Pickhardt PJ (2018) Fully automated segmentation and quantification of visceral and subcutaneous fat at abdominal CT: application to a longitudinal adult screening cohort. Br J Radiol 91:20170968

    Article  PubMed  PubMed Central  Google Scholar 

  44. Xiao DY, Luo S, O'Brian K et al (2016) Longitudinal body composition changes in diffuse large B-cell lymphoma survivors: a retrospective cohort study of United States Veterans. J Natl Cancer Inst 108:djw145

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Acknowledgements

We would like to acknowledge Dariya Hardisky for her help with collecting the patient images.

Funding

The authors state that this work has not received any funding.

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Authors and Affiliations

  1. Center for Regenerative Medicine, The Research Institute at Nationwide Children’s Hospital, 575 Children’s Crossroad, WB4131, Columbus, OH, 43215, USA

    Nguyen K. Tram, Ting-Heng Chou, Laila N. Ettefagh, Kyra Deep & Mitchel R. Stacy

  2. Department of Radiology, Nationwide Children’s Hospital, Columbus, OH, USA

    Adam J. Bobbey

  3. Division of Hematology/Oncology/BMT, Department of Pediatrics, The Ohio State University College of Medicine, Columbus, OH, USA

    Anthony N. Audino

  4. Division of Vascular Surgery and Diseases, Department of Surgery, The Ohio State University College of Medicine, Columbus, OH, USA

    Mitchel R. Stacy

  5. Interdisciplinary Biophysics Graduate Program, The Ohio State University, Columbus, OH, USA

    Mitchel R. Stacy

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  1. Nguyen K. Tram
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Correspondence to Mitchel R. Stacy.

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Tram, N.K., Chou, TH., Ettefagh, L.N. et al. Quantification of chemotherapy-induced changes in body composition in pediatric, adolescent, and young adult lymphoma using standard of care CT imaging. Eur Radiol 32, 7270–7277 (2022). https://doi.org/10.1007/s00330-022-09048-z

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