Differences in the distribution of peritoneal metastases in right- versus left-sided colon cancer on MRI.

PURPOSE: Right-sided colon tumors with peritoneal metastases (PM) are associated with a poorer prognosis than left-sided tumors. We hypothesized that a different pattern of spread could be characterized with abdominopelvic MRI. The objective of this study was to explore the spread of PM in relation to the primary tumor location on MRI. METHODS: This is a retrospective cohort study of patients with PM from colon cancer referred to be considered for CRS-HIPEC at a single tertiary referral center. Patients with colon cancer were eligible if they had undergone an abdominopelvic MRI scan following a clinical diagnosis of PM. The frequency of affected PCI regions on MRI (MRI-PCI) was assessed and compared between tumor sidedness. RESULTS: One hundred eighteen patients were included with a median age of 65 (IQR: 56-72). 46% percent were male. The median MRI-PCI was 10 (IQR: 5-16) and 8 (IQR: 4-11) for right- and left-sided tumors, respectively (p = 0.39), and the median number of affected regions was 4 (IQR: 2-7 for right-sided and IQR 2-5 for left-sided tumors). PM was most frequently found close to the primary tumor. The odds ratio of patients with PM of left sided to be affected with PM in the upper abdominal regions was 0.42 (95% CI: 0.20-0.90) and with PM on the small bowels or mesentery was 0.42 (95% CI: 0.19-0.92) over a patient with PM of right-sided colon cancer. CONCLUSION: MRI can help to assess the spread of PM in colonic cancer. In right-sided tumors, the small bowel and upper abdominal regions are more frequently affected.

The Apparent Diffusion Coefficient (ADC) is a useful biomarker in predicting metastatic colon cancer using the ADC-value of the primary tumor.

PURPOSE: To investigate the role of the apparent diffusion coefficient (ADC) as a potential imaging biomarker to predict metastasis (lymph node metastasis and distant metastasis) in colon cancer based on the ADC-value of the primary tumor. METHODS: Thirty patients (21M, 9F) were included retrospectively. All patients received a 1.5T MRI of the colon including T2 and DWI sequences. ADC maps were calculated for each patient. An expert reader manually delineated all colon tumors to measure mean ADC and histogram metrics (mean, min, max, median, standard deviation (SD), skewness, kurtosis, 5th-95th percentiles) were calculated. Advanced colon cancer was defined as lymph node mestastasis (N+) or distant metastasis (M+). The student Mann Whitney U-test was used to assess the differences between the ADC means of early and advanced colon cancer. To compare the accuracy of lymph node metastasis (N+) prediction based on morpholigical criteria versus ADC-value of the primary tumor, two blinded readers, determined the lymph node metastasis (N0 vs N+) based on morphological criteria. The sensitivity and specificity in predicting lymph node metastasis was calculated for both readers and for the ADC-value of the primary tumor, with histopathology results as the gold standard. RESULTS: There was a significant difference between the mean ADC-value of advanced versus early tumors (p = 0.002). The optimal cut off value was 1179 * 10-3 mm2/s with an area under the curve (AUC) of 0.83 and a sensitivity and specificity of 81% and 86% respectively to predict advanced tumors. Histogram analyses did not add any significant additional value. The sensitivity and specificity for the prediction of lymph node metastasis based on morphological criteria were 40% and 63% for reader 1 and 30% and 88% for reader 2 respectively. The primary tumor ADC-value using 1.179 * 10-3 mm2/s as threshold had a 100% sensitivity and specificity in predicting lymph node metastasis. CONCLUSION: The ADC-value of the primary tumor has the potential to predict advanced colon cancer, defined as lymph node metastasis or distant metastasis, with lower ADC values significantly associated with advanced tumors. Furthermore the ADC-value of the primary tumor increases the prediction accuracy of lymph node metastasis compared with morphological criteria.

MRI for Local Staging of Colon Cancer: Can MRI Become the Optimal Staging Modality for Patients With Colon Cancer?

BACKGROUND: Colon cancer is currently staged with CT. However, MRI is superior in the detection of colorectal liver metastasis, and MRI is standard in local staging of rectal cancer. Optimal (local) staging of colon cancer could become crucial in selecting patients for neoadjuvant treatment in the near future (Fluoropyrimidine Oxaliplatin and Targeted Receptor Preoperative Therapy trial). OBJECTIVE: The purpose of this study was to evaluate the diagnostic performance of MRI for local staging of colon cancer. DESIGN: This was a retrospective study. SETTINGS: The study was conducted at the Maastricht University Medical Centre. PATIENTS: In total, 55 patients with biopsy-proven colon carcinoma were included. MAIN OUTCOME MEASURES: All of the patients underwent an MRI (1.5-tesla; T2 and diffusion-weighted imaging) of the abdomen and were retrospectively analyzed by 2 blinded, independent readers. Histopathology after resection was the reference standard. Both readers evaluated tumor characteristics, including invasion through bowel wall (T3/T4 tumors), invasion beyond bowel wall of ≥5 mm and/or invasion of surrounding organs (T3cd/T4), serosal involvement, extramural vascular invasion, and malignant lymph nodes (N+). Interobserver agreement was compared using κ statistics. RESULTS: MRI had a high sensitivity (72%-91%) and specificity (84%-89%) in detecting T3/T4 tumors (35/55) and a low sensitivity (43%-67%) and high specificity (75%-88%) in detecting T3cd/T4 tumors (15/55). For detecting serosal involvement and extramural vascular invasion, MRI had a high sensitivity and moderate specificity, as well as a moderate sensitivity and specificity in the detection of nodal involvement. Interobserver agreements were predominantly good; the more experienced reader achieved better results in the majority of these categories. LIMITATIONS: The study was limited by its retrospective nature and moderate number of inclusions. CONCLUSIONS: MRI has a good sensitivity for tumor invasion through the bowel wall, extramural vascular invasion, and serosal involvement. In addition, together with its superior liver imaging, MRI might become the optimal staging modality for colon cancer. However, more research is needed to confirm this. See Video Abstract at http://links.lww.com/DCR/A309.

Diagnostic Accuracy of CT for Local Staging of Colon Cancer: A Systematic Review and Meta-Analysis.

OBJECTIVE: The purpose of this article is to determine the accuracy of CT in the detection of tumor invasion beyond the bowel wall and nodal involvement of colon carcinomas. A literature search was performed to identify studies describing the accuracy of CT in the staging of colon carcinomas. Studies including rectal carcinomas that were inseparable from colon carcinomas were excluded. Publication bias was explored by using a Deeks funnel plot asymmetry test. A hierarchic summary ROC model was used to construct a summary ROC curve and to calculate summary estimates of sensitivity, specificity, and diagnostic odds ratios (ORs). CONCLUSION: On the basis of a total of 13 studies, pooled sensitivity, specificity, and diagnostic ORs for detection of tumor invasion beyond the bowel wall (T3-T4) were 90% (95% CI, 83-95%), 69% (95% CI, 62-75%), and 20.6 (95% CI, 10.2-41.5), respectively. For detection of tumor invasion depth of 5 mm or greater (T3cd-T4), estimates from four studies were 77% (95% CI, 66-85%), 70% (95% CI, 53-83%), and 7.8 (95% CI, 4.2-14.2), respectively. For nodal involvement (N+), 16 studies were included with values of 71% (95% CI, 59-81%), 67% (95% CI, 46-83%), and 4.8 (95% CI, 2.5-9.4), respectively. Two studies using CT colonography were included with sensitivity and specificity of 97% (95% CI, 90-99%) and 81% (95% CI, 65-91%), respectively, for detecting T3-T4 tumors. CT has good sensitivity for the detection of T3-T4 tumors, and evidence suggests that CT colonography increases its accuracy. Discriminating between T1-T3ab and T3cd-T4 cancer is challenging, but data were limited. CT has a low accuracy in detecting nodal involvement.