What Is the Best Way to Identify Malignant Transformation Within Pancreatic IPMN: A Systematic Review and Meta-Analyses View Full Text


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Article Info

DATE

2015-12-10

AUTHORS

Asma Sultana, Richard Jackson, Gilbert Tim, Emma Bostock, Eftychia E Psarelli, Trevor F Cox, Robert Sutton, Paula Ghaneh, Michael G T Raraty, John P Neoptolemos, Christopher M Halloran

ABSTRACT

OBJECTIVES: Pancreatic intraductal papillary mucinous neoplasias (IPMNs) represent 25% of all cystic neoplasms and are precursor lesions for pancreatic ductal adenocarcinoma. This study aims to identify the best imaging modality for detecting malignant transformation in IPMN, the sensitivity and specificity of risk features on imaging, and the usefulness of tumor markers in serum and cyst fluid to predict malignancy in IPMN. METHODS: Databases were searched from November 2006 to March 2014. Pooled sensitivity and specificity of diagnostic techniques/imaging features of suspected malignancy in IPMN using a hierarchical summary receiver operator characteristic (HSROC) approach were performed. RESULTS: A total of 467 eligible studies were identified, of which 51 studies met the inclusion criteria and 37 of these were incorporated into meta-analyses. The pooled sensitivity and specificity for risk features predictive of malignancy on computed tomography/magnetic resonance imaging were 0.809 and 0.762 respectively, and on positron emission tomography were 0.968 and 0.911. Mural nodule, cyst size, and main pancreatic duct dilation found on imaging had pooled sensitivity for prediction of malignancy of 0.690, 0.682, and 0.614, respectively, and specificity of 0.798, 0.574, and 0.687. Raised serum carbohydrate antigen 19-9 (CA19-9) levels yielded sensitivity of 0.380 and specificity of 0903. Combining parameters yielded a sensitivity of 0.743 and specificity of 0.906. CONCLUSIONS: PET holds the most promise in identifying malignant transformation within an IPMN. Combining parameters increases sensitivity and specificity; the presence of mural nodule on imaging was the most sensitive whereas raised serum CA19-9 (>37 KU/l) was the most specific feature predictive of malignancy in IPMNs. More... »

PAGES

e130

References to SciGraph publications

  • 2007-08-07. Intraductal papillary mucinous neoplasms of the pancreas: correlation of helical CT and dynamic MR imaging features with pathologic findings in ABDOMINAL RADIOLOGY
  • 2009-09-24. Invasive carcinomas originating from intraductal papillary mucinous neoplasms of the pancreas: conspicuity and primary sites of the solid masses on triple-phase dynamic CT imaging in ABDOMINAL RADIOLOGY
  • 2010-04-10. Prediction of invasive carcinoma in branch type intraductal papillary mucinous neoplasms of the pancreas in JOURNAL OF GASTROENTEROLOGY
  • 2011-03-17. Predictive Value of Serum Carbohydrate Antigen 19-9 in Malignant Intraductal Papillary Mucinous Neoplasms in WORLD JOURNAL OF SURGERY
  • 2009-02-17. Fluid CEA in IPMNs: A Useful Test or the Flip of a Coin? in THE AMERICAN JOURNAL OF GASTROENTEROLOGY
  • 2013-09-18. Predicting Dysplasia and Invasive Carcinoma in Intraductal Papillary Mucinous Neoplasms of the Pancreas: Development of a Preoperative Nomogram in ANNALS OF SURGICAL ONCOLOGY
  • 2008-04. MR imaging and MR cholangiopancreatography of multifocal intraductal papillary mucinous neoplasms of the side branches: MR pattern and its evolution in LA RADIOLOGIA MEDICA
  • 2007-10-02. Treatment Guidelines for Branch Duct Type Intraductal Papillary Mucinous Neoplasms of the Pancreas: When Can We Operate or Observe? in ANNALS OF SURGICAL ONCOLOGY
  • 2010-11-18. Size of mural nodule as an indicator of surgery for branch duct intraductal papillary mucinous neoplasm of the pancreas during follow-up in JOURNAL OF GASTROENTEROLOGY
  • 2000-10. WinBUGS - A Bayesian modelling framework: Concepts, structure, and extensibility in STATISTICS AND COMPUTING
  • 2007-10-05. CT vs MRCP: Optimal Classification of IPMN Type and Extent in JOURNAL OF GASTROINTESTINAL SURGERY
  • 2011-01-06. Controversies in the management of pancreatic IPMN in NATURE REVIEWS GASTROENTEROLOGY & HEPATOLOGY
  • 2009-03-12. Single-institution validation of the international consensus guidelines for treatment of branch duct intraductal papillary mucinous neoplasms of the pancreas in JOURNAL OF HEPATO-BILIARY-PANCREATIC SCIENCES
  • 2008-09-04. Intraductal Papillary Mucinous Neoplasms of the Pancreas: Performance of Pancreatic Fluid Analysis for Positive Diagnosis and the Prediction of Malignancy in THE AMERICAN JOURNAL OF GASTROENTEROLOGY
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    PUBMED

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    20 schema:description OBJECTIVES: Pancreatic intraductal papillary mucinous neoplasias (IPMNs) represent 25% of all cystic neoplasms and are precursor lesions for pancreatic ductal adenocarcinoma. This study aims to identify the best imaging modality for detecting malignant transformation in IPMN, the sensitivity and specificity of risk features on imaging, and the usefulness of tumor markers in serum and cyst fluid to predict malignancy in IPMN. METHODS: Databases were searched from November 2006 to March 2014. Pooled sensitivity and specificity of diagnostic techniques/imaging features of suspected malignancy in IPMN using a hierarchical summary receiver operator characteristic (HSROC) approach were performed. RESULTS: A total of 467 eligible studies were identified, of which 51 studies met the inclusion criteria and 37 of these were incorporated into meta-analyses. The pooled sensitivity and specificity for risk features predictive of malignancy on computed tomography/magnetic resonance imaging were 0.809 and 0.762 respectively, and on positron emission tomography were 0.968 and 0.911. Mural nodule, cyst size, and main pancreatic duct dilation found on imaging had pooled sensitivity for prediction of malignancy of 0.690, 0.682, and 0.614, respectively, and specificity of 0.798, 0.574, and 0.687. Raised serum carbohydrate antigen 19-9 (CA19-9) levels yielded sensitivity of 0.380 and specificity of 0903. Combining parameters yielded a sensitivity of 0.743 and specificity of 0.906. CONCLUSIONS: PET holds the most promise in identifying malignant transformation within an IPMN. Combining parameters increases sensitivity and specificity; the presence of mural nodule on imaging was the most sensitive whereas raised serum CA19-9 (>37‚ÄČKU/l) was the most specific feature predictive of malignancy in IPMNs.
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    26 schema:keywords CA19-9
    27 Meta-Analysis
    28 PET
    29 adenocarcinoma
    30 antigen 19
    31 approach
    32 best imaging modality
    33 best way
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    35 characteristics approach
    36 criteria
    37 cyst fluid
    38 cyst size
    39 cystic neoplasms
    40 database
    41 dilation
    42 duct dilation
    43 ductal adenocarcinoma
    44 eligible studies
    45 emission tomography
    46 features
    47 fluid
    48 imaging
    49 imaging modalities
    50 inclusion criteria
    51 intraductal papillary mucinous neoplasia
    52 lesions
    53 levels
    54 magnetic resonance imaging
    55 main pancreatic duct dilation
    56 malignancy
    57 malignant transformation
    58 markers
    59 modalities
    60 most promise
    61 mucinous neoplasia
    62 mural nodules
    63 neoplasia
    64 neoplasms
    65 nodules
    66 pancreatic duct dilation
    67 pancreatic ductal adenocarcinoma
    68 parameters
    69 pooled sensitivity
    70 positron emission tomography
    71 precursor lesions
    72 prediction
    73 prediction of malignancy
    74 presence
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    76 receiver operator characteristic approach
    77 resonance imaging
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