Diagnostic precision of CT in local staging of colon cancers: a meta-analysis

Dighe, Shwetal; Purkayastha, Sanjay; Swift, Ian; Tekkis, Paris; Darzi, Ara; A’Hern, Roger; Brown, Gina

doi:10.1016/j.crad.2010.01.024

Cited by 159 publications

(116 citation statements)

References 55 publications

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“…This end point was assessed in a meta-analysis by Dighe et al 30 in 2010, which included 19 studies from 1986 to 2008, 17 studies of which had sufficient data to be included in a meta-analysis. The overall sensitivity was 86% (95% CI 78-92%), with a specificity of 78% (95% CI 71-84%) and diagnostic odds ratio (DOR) of 22.4 (95% CI 11.9-42.4).…”

Section: Discussionmentioning

confidence: 99%

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Local staging and assessment of colon cancer with 1.5-T magnetic resonance imaging

Hunter¹,

Blake²,

Jeyadevan³

et al. 2016

BJR

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Objective: The aim of this study was to assess the accuracy of 1.5-T MRI in the pre-operative local T and N staging of colon cancer and identification of extramural vascular invasion (EMVI). Methods: Between 2010 and 2012, 60 patients with adenocarcinoma of the colon were prospectively recruited at 2 centres. 55 patients were included for final analysis. Patients received pre-operative 1.5-T MRI with high-resolution T 2 weighted, gadolinium-enhanced T 1 weighted and diffusion-weighted images. These were blindly assessed by two expert radiologists. Accuracy of the T-stage, N-stage and EMVI assessment was evaluated using post-operative histology as the gold standard. Results: Results are reported for two readers. Identification of T3 disease demonstrated an accuracy of 71% and 51%, sensitivity of 74% and 42% and specificity of 74% and 83%. Identification of N1 disease demonstrated an accuracy of 57% for both readers, sensitivity of 26% and 35% and specificity of 81% and 74%. Identification of EMVI demonstrated an accuracy of 74% and 69%, sensitivity 63% and 26% and specificity 80% and 91%. Conclusion: 1.5-T MRI achieved a moderate accuracy in the local evaluation of colon cancer, but cannot be recommended to replace CT on the basis of this study. Advances in knowledge: This study confirms that MRI is a viable alternative to CT for the local assessment of colon cancer, but this study does not reproduce the very high accuracy reported in the only other study to assess the accuracy of MRI in colon cancer staging.

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Section: Discussionmentioning

confidence: 99%

“…This end point was also assessed by Dighe et al 30 in his meta-analysis and 15 studies were included for this end point. The overall sensitivity for nodal detection in this meta-analysis was 70% (95% CI 59-80%), specificity was 78% (95% CI 66-86%) and DOR was 8.1 (95% CI 4.7-14.1).…”

Section: Discussionmentioning

confidence: 99%

Local staging and assessment of colon cancer with 1.5-T magnetic resonance imaging

Hunter¹,

Blake²,

Jeyadevan³

et al. 2016

BJR

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“…Extramural invasion (EMI) is an important factor affecting the prognosis in patients with colon cancer (3). Preoperative CT can detect EMI in colon cancers with high sensitivity (4). In addition, CTbased T staging can be used to stratify patients into good and poor prognosis (4,5).…”

mentioning

confidence: 99%

“…Preoperative CT can detect EMI in colon cancers with high sensitivity (4). In addition, CTbased T staging can be used to stratify patients into good and poor prognosis (4,5).…”

mentioning

confidence: 99%

The role of multidetector CT in local staging and evaluation of retroperitoneal surgical margin involvement in colon cancer

Elibol¹,

Obuz²,

Sökmen³

et al. 2015

Diagn Interv Radiol

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“…Significant discrepancy exists between the reported sensitivities and specificities of computed tomography (CT) in identifying lymph node positivity. [9][10][11] In particular, poor specificity and a high false-positive rate preclude CT evaluation in preoperative nodal classification in colon cancer. Magnetic resonance imaging and endoanal ultrasonography, though useful in assessing local tumor burden, are limited in discriminating between malignant and benign lymph nodes.…”

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confidence: 99%

Introducing a Novel and Robust Technique for Determining Lymph Node Status in Colorectal Cancer

et al. 2014

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Objective: This study aims to harness the potential of public gene expression repositories, to develop gene expression profiles that could accurately determine nodal status in colorectal cancer. Background: Currently, techniques that determine lymph node positivity (before resection) have poor sensitivity and specificity. The ability to determine lymph node status, based on preoperative biopsies, would greatly assist in planning treatment in colorectal cancer. This is particularly relevant in polypdetected cancers. Methods: Public gene expression repositories were screened for experiments comparing metastatic and nonmetastatic colorectal cancer. A customized graphic user interface was developed to extract genes dysregulated across most identified studies (ie, consensus profiles). The utility of consensus profiles was tested by determining whether classifiers could be derived that determined nodal positivity or negativity. Consensus profiles-derived classifiers were tested on separate Affymetrix-and Illumina-based experiments, and collated outputs were compiled in summary receiver operator curve characteristic format, with area under the curve (AUC) reflecting accuracy. The association between classification and oncologic outcome was determined using an additional, independent data set. Final validation was conducted using the Ingenuity network-linkage environment. Results: Four consensus profiles were generated from which classifiers were derived that accurately determined node positive and negative status (pooled AUC were 0.79 ± 0.04 and 0.8 ± 0.03 for nodal positivity and negativity, respectively). Overall AUC ranged from 0.73 to 0.86, demonstrating high accuracy across consensus profile type, classification technique, and array platform used. As consensus profile enabled classification of nodal status, survival outcomes could be compared for those predicted node negative or positive. Patterns of disease-free and overall survival were identical to those observed for standard histopathologic nodal status. Genes contained within consensus profiles were strongly linked to the metastatic process and included (among others) FYN, WNT5A, COL8A1, BMP, and SMAD family members. Conclusions: Microarray expression data available in public gene expression repositories can be harnessed to generate consensus profiles. The latter are a source of classifiers that have prognostic and predictive properties.

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Diagnostic precision of CT in local staging of colon cancers: a meta-analysis

Cited by 159 publications

References 55 publications

Local staging and assessment of colon cancer with 1.5-T magnetic resonance imaging

Local staging and assessment of colon cancer with 1.5-T magnetic resonance imaging

The role of multidetector CT in local staging and evaluation of retroperitoneal surgical margin involvement in colon cancer

Introducing a Novel and Robust Technique for Determining Lymph Node Status in Colorectal Cancer

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