| Literature DB >> 27608045 |
Rie Ø Eriksen1,2, Louise S Strauch3,4, Michael Sandgaard5, Thomas S Kristensen6, Michael B Nielsen7, Carsten A Lauridsen8,9.
Abstract
The aim of this systematic review is to provide an overview of the use of Dynamic Contrast-enhanced Computed Tomography (DCE-CT) in patients with pancreatic cancer. This study was composed according to the PRISMA guidelines 2009. The literature search was conducted in PubMed, Cochrane Library, EMBASE, and Web of Science databases to identify all relevant publications. The QUADAS-2 tool was implemented to assess the risk of bias and applicability concerns of each included study. The initial literature search yielded 483 publications. Thirteen articles were included. Articles were categorized into three groups: nine articles concerning primary diagnosis or staging, one article about tumor response to treatment, and three articles regarding scan techniques. In exocrine pancreatic tumors, measurements of blood flow in eight studies and blood volume in seven studies were significantly lower in tumor tissue, compared with measurements in pancreatic tissue outside of tumor, or normal pancreatic tissue in control groups of healthy volunteers. The studies were heterogeneous in the number of patients enrolled and scan protocols. Perfusion parameters measured and analyzed by DCE-CT might be useful in the investigation of characteristic vascular patterns of exocrine pancreatic tumors. Further clinical studies are desired for investigating the potential of DCE-CT in pancreatic tumors.Entities:
Keywords: DCE-CT; diagnostics; pancreatic cancer; scan techniques; treatment response
Year: 2016 PMID: 27608045 PMCID: PMC5039568 DOI: 10.3390/diagnostics6030034
Source DB: PubMed Journal: Diagnostics (Basel) ISSN: 2075-4418
Figure 1Flowchart of the literature search and study selection.
Overview of included studies: Primary diagnosis and staging.
| Primary Diagnosis and Staging (All Studies were Prospective) | ||||||||||
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| Authors, Publication Year | No. of Patients | Diagnosis | Scan Parameters | Kinetic Model | Aim | Gold Standard | Results | Conclusion | ||
| Slice | Contrast | kV and mAs | ||||||||
| D’Assignies et al. 2008 [ | 28 | Pancreatic endocrine tumors | 64 | 40 mL | 100 kV, 100 mAs | Deconvolution/distributed parameter model | To correlate perfusion measurement with MVD and to determine whether perfusion parameters differ between tumor grades. | Histology, MVD, and WHO 2000 criteria † | DCE-CT is feasible in patients with pancreatic endocrine tumors and allows evaluation of tumor angiogenesis. | |
| Delrue et al. 2011 [ | 40 | Pancreatic adenocarcinoma ( | 128 Dual-source CT | 50 mL | 100 kV, 145 mAs | Maximum slope (single-compartment) | To assess perfusion characteristics in patients with pancreatic adenocarcinoma and to compare with values in normal healthy pancreatic tissue. | Histology | DCE-CT provides added value when investigating tumor vascularization in pancreatic adenocarcinoma, compared with image assessment based on tissue density measurements (HU), and can lead to more accurate diagnosis. | |
| Delrue et al. 2011 [ | 54 | Pancreatic adenocarcinoma ( | 128 Dual-source CT | 50 mL | 100 kV, 145 mAs | Maximum slope (single-compartment) | To evaluate whether perfusion parameters can distinguish general pathologies of the pancreas and possibly aid in early diagnosis. | Histology | Significant decreases in perfusion values in both adenocarcinomas and acute and chronic pancreatitis, and the opposite applies to values in neuroendocrine tumors, which were significantly increased, compared to the control group of healthy volunteers. Different perfusion values can be used as an additional parameter to differentiate pancreatic pathologies. | |
| D’Onofrio et al. 2012 [ | 32 | Pancreatic adenocarcinoma. | 64 | 50 mL | 120 kV, 150 mAs | Maximum slope (single-compartment) | To describe DCE-CT features and to assess whether these features correlate with the tumor grading. | Histology | Significantly lower median values of BV and PEI in high grade neoplasms compared with low grade neoplasms (BV: | DCE-CT can predict tumor grade of pancreatic adenocarcinoma. |
| Kandel et al. 2009 [ | 30 | Pancreatic adenocarcinoma | 320 | 60 mL | 100 kV, 22.5 mAs | Maximum slope (single-compartment) | To evaluate a whole-organ DCE-CT protocol and to analyze perfusion differences between tumor tissue and normal pancreatic tissue. | Histology | Significantly lower BF in tumor tissue compared with pancreatic tissue outside of tumor ( | DCE-CT carries the potential to improve detection of pancreatic cancers due to the perfusion differences. |
| Klauss et al. 2012 [ | 25 | Pancreatic adenocarcinoma | 64 Dual-source | 80 mL | 80 kV and 270 mAs 140 kV and 50 mAs | Patlak model (two-compartment) | To evaluate the feasibility of DCE-CT for assessing differences in perfusion values of tumor tissue and normal pancreatic tissue. | Histology | Significantly lower BF, BV, and PS in tumor tissue than in pancreatic tissue outside of tumor ( | DCE-CT using the Patlak analysis is feasible. Even isodense tumors could be delineated in the color-coded parameter maps. |
| Lu et al. 2011 [ | 112 | Pancreatic adenocarcinoma ( | 64 | 50 mL | 80 kV, 50 mAs | Maximum slope (single-compartment) | To investigate characteristics of pancreatic cancer, mass-forming chronic pancreatitis, and normal pancreas with DCE-CT. | Histology and AJCC 2002 classification system * | DCE-CT is feasible in providing quantitative hemodynamic information of pancreatic adenocarcinoma and mass-forming chronic pancreatitis. | |
| Nishikawa et al. 2014 [ | 17 | Pancreatic adenocarcinoma | 64 | 40 mL | 80 kV, 20 mAs | Maximum slope (single-compartment) | To investigate the relationship between patient prognosis and perfusion in tumor tissue and peritumoral tissue. | Histology, TNM * and Japanese classification (prognosis) | Patient prognosis may be related to perfusion in peritumoral tissue observed with DCE-CT. | |
| Xu et al. 2009 [ | 76 | Pancreatic adenocarcinoma ( | 64 | 50 mL | 120 kV, 150 mA (rotation time: N/A) | Deconvolution method | To explore the perfusion characteristics of pancreatic adenocarcinoma and normal pancreatic tissue in patients with non-pancreatic disease. | Histology | DCE-CT can differentiate pathological changes from normal tissue. Therefore, DCE-CT should be considered a potential modality to increase the accuracy of CT diagnosis for pancreatic adenocarcinoma. | |
Abbreviations: MVD (Microvessel Density); BF (Blood Flow); BV (Blood Volume); † WHO (World Health Organization) 2000 criteria-WHO 1: Well-differentiated endocrine tumors of benign behavior. WHO 2: Well-differentiated endocrine tumors of uncertain behavior. WHO 3: well-differentiated endocrine carcinomas. WHO 4: poorly differentiated endocrine carcinomas; PS (Permeability Surface); HU (Hounsfield Units); PEI (Peak Enhancement Intensity); * AJCC (American Joint Committee on Cancer); TNM (Tumor, Nodes, Metastasis); AUC (Area under Curve); N/A (Not Available).
Overview of included studies: Tumor response to treatment and scan techniques.
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| Park et al. 2009 [ | 30 | Pancreatic adenocarcinoma | 64 | 50 mL | 100 kV, 100 mAs | Patlak model (two-compartment) | To determine whether DCE-CT parameters, permeability and BV can be used to predict response to concurrent chemotherapy and radiation therapy (CCRT). | CCRT | Baseline. First follow-up: 4–6 weeks. Second follow-up: 10–12 weeks after first follow-up | WHO *, responders (complete or partial response: ≥50% decrease from baseline) and non-responders (progressive disease ≥25% increase in the size of lesion or the appearance of new lesions + those with no change) | Tumors with high pretreatment permeability values indicating higher intratumoral flow tended to respond better to the CCRT. DCE-CT may be used to predict the tumor response of CCRT in patients with pancreatic cancer. | |
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| Klauss et al. 2012 [ | 24 | Pancreatic adenocarcinoma | 64 Dual-energy CT | 80 mL | 80 kV and 270 mAs | Patlak model (two-compartment) | To evaluate the feasibility of dual-energy DCE-CT for assessing the differences in BF, PS, and BV between pancreatic adenocarcinoma and normal pancreatic tissue. | Histology | BF, BV, and PS was significantly lower in tumor tissue than in pancreatic tissue outside of tumor, for both 80 kV, 140 kV, and weighted average 120 kV (BF, BV, and PS: | The use of dual-energy DCE-CT improves the accuracy of DCE-CT of the pancreas by fully exploiting the advantages of enhanced iodine contrast at 80 kV in combination with the noise reduction at 140 kV. Using dual-energy perfusion data could improve the delineation of pancreatic carcinomas. | ||
| Li et al. 2013 [ | 33 | Pancreatic adenocarcinoma ( | N/A Dual-source CT | 50 mL | 70 kV and 120 mAs | Patlak model (two-compartment) | To investigate the feasibility of low-dose whole pancreas DCE-CT. | Histology | The low-dose whole-organ DCE-CT of the pancreas can effectively reduce the radiation dose. | |||
| Tan et al. 2015 [ | 67 | Pancreatic carcinoma ( | 640 | 40 mL | 100 kV, 50 mA (rotation time: N/A) | Maximum slope (single-compartment) | To evaluate the feasibility of low-dose scanning: Compare changes of tissue peak and BF in normal tissue, lesions, and surrounding areas. Compare the use of the whole sequence (group 1), odd number (group 2), and even number (group 3). | Histology | By using the method of low-dose whole pancreas perfusion, scan sequences, and radiation dose are halved, and the diagnosis capacity is not impaired. | |||
* WHO (World Health Organization) BV (Blood Volume); BF (Blood Flow); PS (Permeability Surface); N/A (Not Available); kg (kilogram).
Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2).
| Study | Risk of Bias | Applicability Concerns | |||||
|---|---|---|---|---|---|---|---|
| Patient Selection | Index Test | Reference Standard | Flow and Timing | Patient Selection | Index Test | Reference Standard | |
| D’Assignies et al. 2008 [ | |||||||
| Delrue et al. 2011 [ | |||||||
| Delrue et al. 2011 [ | |||||||
| D’Onofrio et al. 2012 [ | |||||||
| Kandel et al. 2009 [ | |||||||
| Klauss et al. 2012 [ | |||||||
| Lu et al. 2011 [ | |||||||
| Nishikawa et al. 2014 [ | |||||||
| Xu et al. 2009 [ | |||||||
| Park et al. 2009 [ | |||||||
| Klauss et al. 2012 [ | |||||||
| Li et al. 2013 [ | |||||||
| Tan et al. 2015 [ | |||||||
Risk of bias and concerns regarding applicability of the included studies: Low Risk; High Risk; Unclear Risk.