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Predictive Value of CT Biomarkers in Lung Transplantation Survival: Preliminary Investigation in a Diverse, Underserved, Urban Population

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Abstract

Introduction

Survival following lung transplant is low. With limited donor lung availability, predicting post-transplant survival is key. We investigated the predictive value of pre-transplant CT biomarkers on survival.

Methods

In this single-center retrospective cohort study of adults in a diverse, underserved, urban lung transplant program (11/8/2017–5/20/2022), chest CTs were analyzed using TeraRecon to assess musculature, fat, and bone. Erector spinae and pectoralis muscle area and attenuation were analyzed. Sarcopenia thresholds were 34.3 (women) and 38.5 (men) Hounsfield Units (HU). Visceral and subcutaneous fat area and HU, and vertebral body HU were measured. Demographics and pre-transplant metrics were recorded. Survival analyses included Kaplan–Meier and Cox proportional hazard.

Results

The study cohort comprised 131 patients, 50 women, mean age 60.82 (SD 10.15) years, and mean follow-up 1.78 (SD 1.23) years. Twenty-nine percent were White. Mortality was 32.1%. Kaplan–Meier curves did not follow the proportional hazard assumption for sex, so analysis was stratified. Pre-transplant EMR metrics did not predict survival. Women without sarcopenia at erector spinae or pectoralis had 100% survival (p = 0.007). Sarcopenia did not predict survival in men and muscle area did not predict survival in either sex. Men with higher visceral fat area and HU had decreased survival (p = 0.02). Higher vertebral body density predicted improved survival in men (p = 0.026) and women (p = 0.045).

Conclusion

Pre-transplantation CT biomarkers had predictive value in lung transplant survival and varied by sex. The absence of sarcopenia in women, lower visceral fat attenuation and area in men, and higher vertebral body density in both sexes predicted survival in our diverse, urban population.

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References

  1. Valapour M, Lehr CJ, Skeans MA et al (2022) OPTN/SRTR 2020 annual data report: lung. Am J Transplant 22(S2):438–518. https://doi.org/10.1111/ajt.16991

    Article  PubMed  Google Scholar 

  2. Kobashigawa J, Dadhania D, Bhorade S et al (2019) Report from the American Society of Transplantation on frailty in solid organ transplantation. Am J Transplant 19(4):984–994. https://doi.org/10.1111/ajt.15198

    Article  PubMed  Google Scholar 

  3. Hook JL, Lederer DJ (2012) Selecting lung transplant candidates: where do current guidelines fall short? Expert Rev Respir Med 6(1):51. https://doi.org/10.1586/ers.11.83

    Article  PubMed  PubMed Central  Google Scholar 

  4. Kelm DJ, Bonnes SL, Jensen MD et al (2016) Pre-transplant wasting (as measured by muscle index) is a novel prognostic indicator in lung transplantation. Clin Transplant 30(3):247–255. https://doi.org/10.1111/ctr.12683

    Article  PubMed  Google Scholar 

  5. Hsu J, Krishnan A, Lin CT et al (2019) Sarcopenia of the psoas muscles is associated with poor outcomes following lung transplantation. Ann Thorac Surg 107(4):1082–1088. https://doi.org/10.1016/j.athoracsur.2018.10.006

    Article  PubMed  Google Scholar 

  6. Gani F, Cerullo M, Amini N et al (2017) Frailty as a risk predictor of morbidity and mortality following liver surgery. J Gastrointest Surg 21(5):822–830. https://doi.org/10.1007/s11605-017-3373-6

    Article  PubMed  Google Scholar 

  7. Awano N, Inomata M, Kuse N et al (2020) Quantitative computed tomography measures of skeletal muscle mass in patients with idiopathic pulmonary fibrosis according to a multidisciplinary discussion diagnosis: a retrospective nationwide study in Japan. Respir Investig 58(2):91–101. https://doi.org/10.1016/j.resinv.2019.11.002

    Article  PubMed  Google Scholar 

  8. Pienta MJ, Zhang P, Derstine BA et al (2018) Analytic morphomics predict outcomes after lung transplantation. Ann Thorac Surg 105(2):399–405. https://doi.org/10.1016/j.athoracsur.2017.08.049

    Article  PubMed  Google Scholar 

  9. Sella N, Boscolo A, Lovison D et al (2022) The impact of nutritional status and sarcopenia on the outcomes of lung transplantation. J Heart Lung Transplant 41(4):S165. https://doi.org/10.1016/j.healun.2022.01.388

    Article  Google Scholar 

  10. Kashani K, Sarvottam K, Pereira NL, Barreto EF, Kennedy CC (2018) The sarcopenia index: a novel measure of muscle mass in lung transplant candidates. Clin Transplant 32(3):e13182. https://doi.org/10.1111/ctr.13182

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Singer JP, Diamond JM, Anderson MR et al (2018) Frailty phenotypes and mortality after lung transplantation: a prospective cohort study. Am J Transplant 18(8):1995–2004. https://doi.org/10.1111/ajt.14873

    Article  PubMed  PubMed Central  Google Scholar 

  12. Hu A, Prosper A, Ruchaslski K et al (2021) Sarcopenia is distinct from physical frailty and significantly associated with length of stay after transplantation. J Heart Lung Transplant 40(4):S318–S319. https://doi.org/10.1016/j.healun.2021.01.902

    Article  Google Scholar 

  13. Clausen ES, Frankel C, Palmer SM, Snyder LD, Smith PJ (2018) Pre-transplant weight loss and clinical outcomes after lung transplantation. J Heart Lung Transplant 37(12):1443–1447. https://doi.org/10.1016/j.healun.2018.07.015

    Article  PubMed  Google Scholar 

  14. Singer JP, Peterson ER, Golden J et al (2014) Lung Transplant body composition. J Heart Lung Transplant 33(4):S79. https://doi.org/10.1016/j.healun.2014.01.246

    Article  Google Scholar 

  15. McClellan T, Allen BC, Kappus M et al (2017) Repeatability of computerized tomography-based anthropomorphic measurements of frailty in patients with pulmonary fibrosis undergoing lung transplantation. Curr Probl Diagn Radiol 46(4):300–304. https://doi.org/10.1067/j.cpradiol.2016.12.009

    Article  PubMed  Google Scholar 

  16. Tanimura K, Sato S, Fuseya Y et al (2016) Quantitative assessment of erector spinae muscles in patients with chronic obstructive pulmonary disease. Novel chest computed tomography–derived index for prognosis. Annals ATS 13(3):334–341. https://doi.org/10.1513/AnnalsATS.201507-446OC

    Article  Google Scholar 

  17. Heymsfield SB, Gonzalez MC, Lu J, Jia G, Zheng J (2015) Skeletal muscle mass and quality: evolution of modern measurement concepts in the context of sarcopenia. Proc Nutr Soc 74(4):355–366. https://doi.org/10.1017/S0029665115000129

    Article  PubMed  Google Scholar 

  18. Oshima Y, Sato S, Chen-Yoshikawa TF et al (2022) Erector spinae muscle radiographic density is associated with survival after lung transplantation. J Thorac Cardiovasc Surg 164(1):300-311.e3. https://doi.org/10.1016/j.jtcvs.2021.07.039

    Article  PubMed  Google Scholar 

  19. Weig T, Milger K, Langhans B et al (2016) Core muscle size predicts postoperative outcome in lung transplant candidates. Ann Thorac Surg 101(4):1318–1325. https://doi.org/10.1016/j.athoracsur.2015.10.041

    Article  PubMed  Google Scholar 

  20. Rozenberg D, Wickerson L, Singer LG, Mathur S (2014) Sarcopenia in lung transplantation: a systematic review. J Heart Lung Transplant 33(12):1203–1212. https://doi.org/10.1016/j.healun.2014.06.003

    Article  PubMed  Google Scholar 

  21. Rozenberg D, Orsso CE, Chohan K et al (2020) Clinical outcomes associated with computed tomography-based body composition measures in lung transplantation: a systematic review. Transpl Int 33(12):1610–1625. https://doi.org/10.1111/tri.13749

    Article  PubMed  Google Scholar 

  22. Anderson MR, Easthausen I, Gallagher G et al (2020) Skeletal muscle adiposity and outcomes in candidates for lung transplantation: a lung transplant body composition cohort study. Thorax 75(9):801–804. https://doi.org/10.1136/thoraxjnl-2019-214461

    Article  PubMed  Google Scholar 

  23. Hu A, Prosper A, Ruchalski K et al (2023) Sarcopenia predicts outcomes after lung transplantation in older lung transplant candidates. Ann Thorac Surg Short Rep 1(1):174–178. https://doi.org/10.1016/j.atssr.2022.11.005

    Article  Google Scholar 

  24. Derstine BA, Holcombe SA, Ross BE, Wang NC, Su GL, Wang SC (2018) Skeletal muscle cutoff values for sarcopenia diagnosis using T10 to L5 measurements in a healthy US population. Sci Rep 8(1):11369. https://doi.org/10.1038/s41598-018-29825-5

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. McNabb-Baltar J, Manickavasagan HR, Conwell DL et al (2022) A pilot study to assess opportunistic use of CT-scan for osteoporosis screening in chronic pancreatitis. Front Physiol 13:866945. https://doi.org/10.3389/fphys.2022.866945

    Article  PubMed  PubMed Central  Google Scholar 

  26. Parulekar AD, Wang T, Li GW, Hoang V, Kao CC (2020) Pectoralis muscle area is associated with bone mineral density and lung function in lung transplant candidates. Osteoporos Int 31(7):1361–1367. https://doi.org/10.1007/s00198-020-05373-5

    Article  CAS  PubMed  Google Scholar 

  27. Grambsch PM, Therneau TM (1994) Proportional hazards tests and diagnostics based on weighted residuals. Biometrika 81(3):515–526. https://doi.org/10.1093/biomet/81.3.515

    Article  Google Scholar 

  28. Alawi M, Begum A, Harraz M et al (2021) Dual-energy X-ray absorptiometry (DEXA) scan versus computed tomography for bone density assessment. Cureus 13(2):e13261. https://doi.org/10.7759/cureus.13261

    Article  PubMed  PubMed Central  Google Scholar 

  29. Buckens CF, Dijkhuis G, de Keizer B, Verhaar HJ, de Jong PA (2015) Opportunistic screening for osteoporosis on routine computed tomography? An external validation study Eur Radiol 25(7):2074–2079. https://doi.org/10.1007/s00330-014-3584-0

    Article  PubMed  Google Scholar 

  30. Hendrickson NR, Pickhardt PJ, del Rio AM, Rosas HG, Anderson PA (2018) Bone mineral density T-scores derived from CT attenuation numbers (Hounsfield Units): clinical utility and correlation with dual-energy X-ray absorptiometry. Iowa Orthop J 38:25–31

    PubMed  PubMed Central  Google Scholar 

  31. Lee SY, Kwon SS, Kim HS et al (2015) Reliability and validity of lower extremity computed tomography as a screening tool for osteoporosis. Osteoporos Int 26(4):1387–1394. https://doi.org/10.1007/s00198-014-3013-x

    Article  CAS  PubMed  Google Scholar 

  32. Pickhardt PJ, Pooler BD, Lauder T, del Rio AM, Bruce RJ, Binkley N (2013) Opportunistic screening for osteoporosis using abdominal computed tomography scans obtained for other indications. Ann Intern Med 158(8):588–595. https://doi.org/10.7326/0003-4819-158-8-201304160-00003

    Article  PubMed  PubMed Central  Google Scholar 

  33. Schreiber JJ, Anderson PA, Hsu WK (2014) Use of computed tomography for assessing bone mineral density. Neurosurg Focus 37(1):E4. https://doi.org/10.3171/2014.5.FOCUS1483

    Article  PubMed  Google Scholar 

  34. Zaidi Q, Danisa OA, Cheng W (2019) Measurement techniques and utility of Hounsfield unit values for assessment of bone quality prior to spinal instrumentation: a review of current literature. Spine 44(4):E239–E244. https://doi.org/10.1097/BRS.0000000000002813

    Article  PubMed  Google Scholar 

  35. Choi MK, Kim SM, Lim JK (2016) Diagnostic efficacy of Hounsfield units in spine CT for the assessment of real bone mineral density of degenerative spine: correlation study between T-scores determined by DEXA scan and Hounsfield units from CT. Acta Neurochir 158(7):1421–1427. https://doi.org/10.1007/s00701-016-2821-5

    Article  PubMed  Google Scholar 

  36. Gausden EB, Nwachukwu BU, Schreiber JJ, Lorich DG, Lane JM (2017) Opportunistic use of CT imaging for osteoporosis screening and bone density assessment: a qualitative systematic review. J Bone Joint Surg 99(18):1580–1590. https://doi.org/10.2106/JBJS.16.00749

    Article  PubMed  Google Scholar 

  37. Cho YH, Do KH, Chae EJ et al (2019) Association of chest CT-based quantitative measures of muscle and fat with post-lung transplant survival and morbidity: a single institutional retrospective cohort study in Korean population. Korean J Radiol 20(3):522–530. https://doi.org/10.3348/kjr.2018.0241

    Article  PubMed  PubMed Central  Google Scholar 

  38. Nachit M, Horsmans Y, Summers RM, Leclercq IA, Pickhardt PJ (2023) AI-based CT body composition identifies myosteatosis as key mortality predictor in asymptomatic adults. Radiology. https://doi.org/10.1148/radiol.222008

    Article  PubMed  Google Scholar 

  39. Halpern AL, Boshier PR, White AM et al (2020) A comparison of frailty measures at listing to predict outcomes after lung transplantation. Ann Thorac Surg 109(1):233–240. https://doi.org/10.1016/j.athoracsur.2019.07.040

    Article  PubMed  Google Scholar 

  40. Kuk JL, Katzmarzyk PT, Nichaman MZ, Church TS, Blair SN, Ross R (2006) Visceral fat is an independent predictor of all-cause mortality in men. Obesity 14(2):336–341. https://doi.org/10.1038/oby.2006.43

    Article  PubMed  Google Scholar 

  41. Ibrahim MM (2010) Subcutaneous and visceral adipose tissue: structural and functional differences. Obes Rev 11(1):11–18. https://doi.org/10.1111/j.1467-789X.2009.00623.x

    Article  PubMed  Google Scholar 

  42. Lee JH, Choi SH, Jung KJ, Goo JM, Yoon SH (2023) High visceral fat attenuation and long-term mortality in a health check-up population. J Cachexia Sarcopenia Muscle 14(3):1495–1507. https://doi.org/10.1002/jcsm.13226

    Article  PubMed  PubMed Central  Google Scholar 

  43. Loor G, Brown R, Kelly RF et al (2017) Gender differences in long-term survival posttransplant: a single-institution analysis in the lung allocation score (LAS) era. Clin Transplant. https://doi.org/10.1111/ctr.12889

    Article  PubMed  PubMed Central  Google Scholar 

  44. Roberts DH, Wain JC, Chang Y, Ginns LC (2004) Donor—recipient gender mismatch in lung transplantation: impact on obliterative bronchiolitis and survival. J Heart Lung Transplant 23(11):1252–1259. https://doi.org/10.1016/j.healun.2003.09.014

    Article  PubMed  Google Scholar 

  45. Suh JW, Paik HC, Yu WS et al (2019) Effect of sarcopenic overweight on lung transplant based in three-dimensional reconstructed psoas muscle mass. Ann Thorac Surg 107(6):1626–1631. https://doi.org/10.1016/j.athoracsur.2019.01.007

    Article  PubMed  Google Scholar 

  46. Nikkuni E, Hirama T, Hayasaka K et al (2021) Recovery of physical function in lung transplant recipients with sarcopenia. BMC Pulm Med 21(1):124. https://doi.org/10.1186/s12890-021-01442-5

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We would like to acknowledge the Einstein Office of Medical Student Research for its support with this project.

Funding

The authors did not receive external support for this submitted work.

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Author notes

  1. Linda B. Haramati

    Present address: Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA

Authors and Affiliations

  1. Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY, USA

    Renee S. Friedman, Anna Tarasova & Linda B. Haramati

  2. Department of Radiology, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY, USA

    Vineet R. Jain

  3. Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA

    Kenny Ye

  4. Department of Cardiothoracic and Vascular Surgery and Department of Medicine, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY, USA

    Ali Mansour

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Contributions

RSF: study design, data collection, data analysis, writing of manuscript, reviewing of manuscript. AT: study design, data collection, reviewing of manuscript. VRJ: study design, data analysis, reviewing of manuscript. KY: data analysis, reviewing of manuscript. AM: study design, reviewing of manuscript. LBH: study design, data analysis, reviewing of manuscript.

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Correspondence to Renee S. Friedman.

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Friedman, R.S., Tarasova, A., Jain, V.R. et al. Predictive Value of CT Biomarkers in Lung Transplantation Survival: Preliminary Investigation in a Diverse, Underserved, Urban Population. Lung 201, 581–590 (2023). https://doi.org/10.1007/s00408-023-00650-6

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