The DOI matches its Crossref record; 58 of the 58 references it cites were found in a registry or an index.
Recent Issues on Body Composition Imaging for Sarcopenia Evaluation
Open accessAbstract
Recently, sarcopenia has garnered renewed interest. Sarcopenia is a disease characterized by decreased skeletal muscle mass and strength/function, which can impair the quality of life and increase physical disability, adverse metabolic effects, and mortality. Imaging tools for evaluating and diagnosing sarcopenia have developed rapidly. Radiologists should be aware of sarcopenia and its clinical implications. We review current knowledge about sarcopenia, its pathophysiological impact, and advantages and disadvantages of methods for evaluation of sarcopenia focusing on body composition imaging modalities such as whole-body dual-energy X-ray absorptiometry, CT, and MRI. Controversial issues are discussed, including the lack of consensus and standardization of the disease definition, imaging modality, measurement methods, and diagnostic cutoff points.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Sarcopenia: European consensus on definition and diagnosis
Cruz-Jentoft, A. J., Baeyens, J. P., Bauer, J. M., Boirie, Y., Cederholm, T., Landi, F., Martin, F. C., Michel, J.-P., Rolland, Y., Schneider, S. M., et al. (2010) · Age and Ageing · doi:10.1093/ageing/afq034 · Cited by 11,601
Epidemiology of Sarcopenia among the Elderly in New Mexico
Baumgartner, R. N., Koehler, K. M., Gallagher, D., Romero, L., Heymsfield, S. B., Ross, R. R., Garry, P. J., & Lindeman, R. D. (1998) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a009520 · Cited by 4,004
Prado, C. M., Lieffers, J. R., McCargar, L. J., Reiman, T., Sawyer, M. B., Martin, L., & Baracos, V. E. (2008) · The Lancet Oncology · doi:10.1016/s1470-2045(08)70153-0 · Cited by 3,238
Martin, L., Birdsell, L., MacDonald, N., Reiman, T., Clandinin, M. T., McCargar, L. J., Murphy, R., Ghosh, S., Sawyer, M. B., & Baracos, V. E. (2013) · Journal of Clinical Oncology · doi:10.1200/jco.2012.45.2722 · Cited by 2,680
The Frailty Syndrome: Definition and Natural History
Xue, Q.-L. (2011) · Clinics in Geriatric Medicine · doi:10.1016/j.cger.2010.08.009 · Cited by 2,061
Cruz-Jentoft, A. J., Landi, F., Schneider, S. M., Zuniga, C., Arai, H., Boirie, Y., Chen, L.-K., Fielding, R. A., Martin, F. C., Michel, J.-P., et al. (2014) · Age and Ageing · doi:10.1093/ageing/afu115 · Cited by 1,963
Health Outcomes of Sarcopenia: A Systematic Review and Meta-Analysis
Beaudart, C., Zaaria, M., Pasleau, F., Reginster, J.-Y., & Bruyère, O. (2017) · PLOS ONE · doi:10.1371/journal.pone.0169548 · Cited by 1,272
Leng, S., Chen, X., & Mao, G. (2014) · Clinical Interventions in Aging · doi:10.2147/cia.s45300 · Cited by 991
Dalakas, M. C. (2015) · New England Journal of Medicine · doi:10.1056/nejmra1402225 · Cited by 790
Sarcopenia and Mortality after Liver Transplantation
Englesbe, M. J., Patel, S. P., He, K., Lynch, R. J., Schaubel, D. E., Harbaugh, C., Holcombe, S. A., Wang, S. C., Segev, D. L., & Sonnenday, C. J. (2010) · Journal of the American College of Surgeons · doi:10.1016/j.jamcollsurg.2010.03.039 · Cited by 766
Cited by
Persson, H. L., Sioutas, A., Kentson, M., Jacobson, P., Lundberg, P., Dahlqvist Leinhard, O., & Forsgren, M. F. (2022) · Journal of Inflammation Research · doi:10.2147/jir.s366204 · Cited by 25
Food insecurity as a risk factor of sarcopenic obesity in older adults
Fonseca-Pérez, D., Arteaga-Pazmiño, C., Maza-Moscoso, C. P., Flores-Madrid, S., & Álvarez-Córdova, L. (2022) · Frontiers in Nutrition · doi:10.3389/fnut.2022.1040089 · Cited by 23
Láinez Ramos-Bossini, A. J., Gámez Martínez, A., Luengo Gómez, D., Valverde-López, F., Morillo Gil, A. J., González Flores, E., Salmerón Ruiz, Á., Jiménez Gutiérrez, P. M., Melguizo, C., & Prados, J. (2025) · Cancers · doi:10.3390/cancers17040607 · Cited by 15
Metadata
- Authors
- Lee, K., Shin, Y., Huh, J., Sung, Y. S., Lee, I.-S., Yoon, K.-H., & Kim, K. W.
- Venue
- Korean Journal of Radiology
- Publisher
- XMLink
- Published
- 2019
- Volume
- 20
- Issue
- 2
- Pages
- 205
- ISSN
- 1229-6929 (ISSN-L)
- 2005-8330
- OpenAlex
- W2908411629
- Cited by
- 336
- References
- 58
- FWCI
- 23.86
- Type
- journal article
- Language
- en
- Open access
- hybrid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Recent Issues on Body Composition Imaging for Sarcopenia Evaluation. https://app.cochat.ai/papers/10.3348/kjr.2018.0479
- The paper
- Lee, K., Shin, Y., Huh, J., Sung, Y. S., Lee, I.-S., Yoon, K.-H., & Kim, K. W. (2019). Recent Issues on Body Composition Imaging for Sarcopenia Evaluation. Korean Journal of Radiology. https://doi.org/10.3348/kjr.2018.0479
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
