The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.
Diagnostic Imaging of Colorectal Liver Metastases with CT, MR Imaging, FDG PET, and/or FDG PET/CT: A Meta-Analysis of Prospective Studies Including Patients Who Have Not Previously Undergone Treatment
Abstract
PURPOSE: To obtain diagnostic performance values of computed tomography (CT), magnetic resonance (MR) imaging, fluorine 18 fluorodeoxyglucose (FDG) positron emission tomography (PET), and FDG PET/CT in the detection of colorectal liver metastases in patients who have not previously undergone therapy. MATERIALS AND METHODS: A comprehensive search was performed for articles published from January 1990 to January 2010 that fulfilled the following criteria: a prospective study design was used; the study population included at least 10 patients; patients had histopathologically proved colorectal cancer; CT, MR imaging, FDG PET, or FDG PET/CT was performed for the detection of liver metastases; intraoperative findings or those from histopathologic examination or follow-up were used as the reference standard; and data for calculating sensitivity and specificity were included. Study design characteristics, patient characteristics, imaging features, reference tests, and 2 × 2 tables were recorded. RESULTS: Thirty-nine articles (3391 patients) were included. Variation existed in study design characteristics, patient descriptions, imaging features, and reference tests. The sensitivity estimates of CT, MR imaging, and FDG PET on a per-lesion basis were 74.4%, 80.3%, and 81.4%, respectively. On a per-patient basis, the sensitivities of CT, MR imaging, and FDG PET were 83.6%, 88.2%, and 94.1%, respectively. The per-patient sensitivity of CT was lower than that of FDG PET (P = .025). Specificity estimates were comparable. For lesions smaller than 10 mm, the sensitivity estimates for MR imaging were higher than those for CT. No differences were seen for lesions measuring at least 10 mm. The sensitivity of MR imaging increased significantly after January 2004. The use of liver-specific contrast material and multisection CT scanners did not provide improved results. Data about FDG PET/CT were too limited for comparisons with other modalities. CONCLUSION: MR imaging is the preferred first-line modality for evaluating colorectal liver metastases in patients who have not previously undergone therapy. FDG PET can be used as the second-line modality. The role of FDG PET/CT is not yet clear owing to the small number of studies. SUPPLEMENTAL MATERIAL: http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.10100729/-/DC1.
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Bias in meta-analysis detected by a simple, graphical test
Egger, M., Smith, G. D., Schneider, M., & Minder, C. (1997) · BMJ · doi:10.1136/bmj.315.7109.629 · Cited by 56,722
Whiting, P., Rutjes, A. W., Reitsma, J. B., Bossuyt, P. M., & Kleijnen, J. (2003) · BMC Medical Research Methodology · doi:10.1186/1471-2288-3-25 · Cited by 3,592
Reitsma, J. B., Glas, A. S., Rutjes, A. W. S., Scholten, R. J. P. M., Bossuyt, P. M., & Zwinderman, A. H. (2005) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2005.02.022 · Cited by 3,369
(2012) · Hepatogastroenterology · doi:10.5754/hge12458 · Cited by 1,977
Epidemiology and Management of Liver Metastases From Colorectal Cancer
Manfredi, S., Lepage, C., Hatem, C., Coatmeur, O., Faivre, J., & Bouvier, A.-M. (2006) · Annals of Surgery · doi:10.1097/01.sla.0000217629.94941.cf · Cited by 1,394
Chu, H., & Cole, S. R. (2006) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2006.06.011 · Cited by 708
Colorectal Liver Metastases: CT, MR Imaging, and PET for Diagnosis—Meta-analysis
Bipat, S., van Leeuwen, M. S., Comans, E. F. I., Pijl, M. E. J., Bossuyt, P. M. M., Zwinderman, A. H., & Stoker, J. (2005) · Radiology · doi:10.1148/radiol.2371042060 · Cited by 544
Self-citationDoes blinding of readers affect the results of meta-analyses?
Berlin, J. A. (1997) · The Lancet · doi:10.1016/s0140-6736(05)62352-5 · Cited by 478
Selzner, M., Hany, T. F., Wildbrett, P., McCormack, L., Kadry, Z., & Clavien, P.-A. (2004) · Annals of Surgery · doi:10.1097/01.sla.0000146145.69835.c5 · Cited by 348
Bivariate Random Effects Meta-Analysis of ROC Curves
Arends, L. R., Hamza, T. H., van Houwelingen, J. C., Heijenbrok-Kal, M. H., Hunink, M. G. M., & Stijnen, T. (2008) · Medical Decision Making · doi:10.1177/0272989x08319957 · Cited by 325
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ESMO consensus guidelines for the management of patients with metastatic colorectal cancer
Van Cutsem, E., Cervantes, A., Adam, R., Sobrero, A., Van Krieken, J. H., Aderka, D., Aranda Aguilar, E., Bardelli, A., Benson, A., Bodoky, G., et al. (2016) · Annals of Oncology · doi:10.1093/annonc/mdw235 · Cited by 3,421
Brenner, H., Kloor, M., & Pox, C. P. (2014) · The Lancet · doi:10.1016/s0140-6736(13)61649-9 · Cited by 2,762
Japanese Society for Cancer of the Colon and Rectum, Watanabe, T., Muro, K., Ajioka, Y., Hashiguchi, Y., Ito, Y., Saito, Y., Hamaguchi, T., Ishida, H., Ishiguro, M., et al. (2018) · International Journal of Clinical Oncology · doi:10.1007/s10147-017-1101-6 · Cited by 2,467
Hashiguchi, Y., Muro, K., Saito, Y., Ito, Y., Ajioka, Y., Hamaguchi, T., Hasegawa, K., Hotta, K., Ishida, H., Ishiguro, M., et al. (2020) · International Journal of Clinical Oncology · doi:10.1007/s10147-019-01485-z · Cited by 1,922
Cervantes, A., Adam, R., Roselló, S., Arnold, D., Normanno, N., Taïeb, J., Seligmann, J., De Baere, T., Osterlund, P., Yoshino, T., et al. (2023) · Annals of Oncology · doi:10.1016/j.annonc.2022.10.003 · Cited by 1,796
Metadata
- Authors
- Niekel, M. C., Bipat, S., & Stoker, J.
- Venue
- Radiology
- Published
- 2010-12
- Volume
- 257
- Issue
- 3
- Pages
- 674-684
- ISSN
- 0033-8419 (ISSN-L)
- 1527-1315
- OpenAlex
- W2134333066
- Cited by
- 584
- References
- 28
- FWCI
- 3.30
- Type
- journal article
- Language
- en
- Open access
- closed
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- Niekel, M. C., Bipat, S., & Stoker, J. (2010). Diagnostic Imaging of Colorectal Liver Metastases with CT, MR Imaging, FDG PET, and/or FDG PET/CT: A Meta-Analysis of Prospective Studies Including Patients Who Have Not Previously Undergone Treatment. Radiology. https://doi.org/10.1148/radiol.10100729
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