The DOI matches its Crossref record; 54 of the 54 references it cites were found in a registry or an index.
Ultrasonography, Computed Tomography and Magnetic Resonance Imaging for Diagnosis and Determining Resectability of Pancreatic Adenocarcinoma: A Meta-Analysis
Abstract
OBJECTIVE: To compare ultrasonography (US), computed tomography (CT), and magnetic resonance imaging (MRI) in the diagnosis and determination of resectability of pancreatic adenocarcinoma. METHODS: Articles reporting US, CT, or MRI data of patients with known or suspected pancreatic adenocarcinoma and at least 20 patients verified with histopathology, surgical findings, or follow-up were included. A bivariate random effects approach was used to calculate sensitivity and specificity for diagnosis and resectability of pancreatic adenocarcinoma. RESULTS: Sixty-eight articles fulfilled all inclusion criteria. For diagnosis, sensitivities of helical CT, conventional CT, MRI, and US were 91%, 86%, 84%, and 76% and specificities were 85%, 79%, 82%, and 75% respectively. Sensitivities for MRI and US were significantly lower compared with helical CT (P = 0.04 and P = 0.0001). For determining resectability, sensitivities of helical CT, conventional CT, MRI, and US were 81%, 82%, 82, and 83% and specificities were 82%, 76%, 78%, and 63% respectively. Specificity of US was significantly lower compared with helical CT (P = 0.011). CONCLUSIONS: Helical CT is preferable as an imaging modality for the diagnosis and determination of resectability of pancreatic adenocarcinoma.
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Estimating the world cancer burden: Globocan 2000
Parkin, D. M., Bray, F., Ferlay, J., & Pisani, P. (2001) · International Journal of Cancer · doi:10.1002/ijc.1440 · Cited by 3,721
Towards complete and accurate reporting of studies of diagnostic accuracy: The STARD Initiative.
Bossuyt, P. M., Reitsma, J. B., Bruns, D. E., Gatsonis, C. A., Glasziou, P. P., Irwig, L. M., Lijmer, J. G., Moher, D., Rennie, D., de Vet, H. C. W., et al. (2003) · Annals of Internal Medicine · doi:10.7326/0003-4819-138-1-200301070-00010 · Cited by 3,219
Self-citationTowards complete and accurate reporting of studies of diagnostic accuracy: the STARD initiative
Bossuyt, P. M., Reitsma, J. B., Bruns, D. E., Gatsonis, C. A., Glasziou, P. P., Irwig, L. M., Lijmer, J. G., Moher, D., Rennie, D., & de Vet, H. C. W. (2003) · BMJ · doi:10.1136/bmj.326.7379.41 · Cited by 3,215
Self-citationTowards Complete and Accurate Reporting of Studies of Diagnostic Accuracy: The STARD Initiative
Bossuyt, P. M., Reitsma, J. B., Bruns, D. E., Gatsonis, C. A., Glasziou, P. P., Irwig, L. M., Lijmer, J. G., Moher, D., Rennie, D., & de Vet, H. C. W. (2003) · Radiology · doi:10.1148/radiol.2261021292 · Cited by 3,215
Self-citationEmpirical evidence of design-related bias in studies of diagnostic tests.
Lijmer, J. G. (1999) · JAMA · doi:10.1001/jama.282.11.1061 · Cited by 1,861
Advanced methods in meta‐analysis: multivariate approach and meta‐regression
van Houwelingen, H. C., Arends, L. R., & Stijnen, T. (2002) · Statistics in Medicine · doi:10.1002/sim.1040 · Cited by 1,580
A hierarchical regression approach to meta‐analysis of diagnostic test accuracy evaluations
Rutter, C. M., & Gatsonis, C. A. (2001) · Statistics in Medicine · doi:10.1002/sim.942 · Cited by 1,505
Regression Analysis for Correlated Data
Liang, K. Y., & Zeger, S. L. (1993) · Annual Review of Public Health · doi:10.1146/annurev.pu.14.050193.000355 · Cited by 764
Lu, D. S., Reber, H. A., Krasny, R. M., Kadell, B. M., & Sayre, J. (1997) · American Journal of Roentgenology · doi:10.2214/ajr.168.6.9168704 · Cited by 546
Pancreatic tumors: evaluation with endoscopic US, CT, and MR imaging.
Müller, M. F., Meyenberger, C., Bertschinger, P., Schaer, R., & Marincek, B. (1994) · Radiology · doi:10.1148/radiology.190.3.8115622 · Cited by 499
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Cancer of the pancreas: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up
Ducreux, M., Cuhna, A. S., Caramella, C., Hollebecque, A., Burtin, P., Goéré, D., Seufferlein, T., Haustermans, K., Van Laethem, J. L., Conroy, T., et al. (2015) · Annals of Oncology · doi:10.1093/annonc/mdv295 · Cited by 1,300
European experts consensus statement on cystic tumours of the pancreas
Del Chiaro, M., Verbeke, C., Salvia, R., Klöppel, G., Werner, J., McKay, C., Friess, H., Manfredi, R., Van Cutsem, E., Löhr, M., et al. (2013) · Digestive and Liver Disease · doi:10.1016/j.dld.2013.01.010 · Cited by 498
Advances in Diagnostic and Intraoperative Molecular Imaging of Pancreatic Cancer
Tummers, W. S., Willmann, J. K., Bonsing, B. A., Vahrmeijer, A. L., Gambhir, S. S., & Swijnenburg, R.-J. (2018) · Pancreas · doi:10.1097/mpa.0000000000001075 · Cited by 50
Surveillance for neoplasia in the pancreas
Overbeek, K. A., Cahen, D. L., Canto, M. I., & Bruno, M. J. (2016) · Best Practice & Research Clinical Gastroenterology · doi:10.1016/j.bpg.2016.10.013 · Cited by 28
Metadata
- Authors
- Bipat, S., Phoa, S. S. K. S., van Delden, O. M., Bossuyt, P. M. M., Gouma, D. J., Lam??ris, J. S., & Stoker, J.
- Venue
- Journal of Computer Assisted Tomography
- Published
- 2005-07
- Volume
- 29
- Issue
- 4
- Pages
- 438-445
- ISSN
- 0363-8715 (ISSN-L)
- OpenAlex
- W2001385756
- Cited by
- 272
- References
- 54
- FWCI
- 4.66
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Ultrasonography, Computed Tomography and Magnetic Resonance Imaging for Diagnosis and Determining Resectability of Pancreatic Adenocarcinoma: A Meta-Analysis. https://app.cochat.ai/papers/10.1097/01.rct.0000164513.23407.b3
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- Bipat, S., Phoa, S. S. K. S., van Delden, O. M., Bossuyt, P. M. M., Gouma, D. J., Lam??ris, J. S., & Stoker, J. (2005). Ultrasonography, Computed Tomography and Magnetic Resonance Imaging for Diagnosis and Determining Resectability of Pancreatic Adenocarcinoma: A Meta-Analysis. Journal of Computer Assisted Tomography. https://doi.org/10.1097/01.rct.0000164513.23407.b3
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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.
