Comparison of qualitative and quantitative measurements on unenhanced T1-weighted fat saturation MR images in predicting pancreatic pathology.

PURPOSE: To evaluate the accuracy of signal intensity (SI) analysis on unenhanced fat-suppressed T1-weighted MR images in the diagnosis of pancreatic disease and to compare subjective interpretation with different quantitative measurements. MATERIALS AND METHODS: The pancreas was evaluated in 159 patients (86 normal and 73 with pancreatic disease) with spoiled gradient echo (GRE) T1-weighted fat saturation MR images. The relative SI of the pancreas to liver and spleen was quantitatively measured using regions of interest (ROIs) and qualitatively assessed by two independent observers. RESULTS: The mean values between a normal and an abnormal pancreas with pancreas-liver ratios of 0.14 +/- 0.37 vs. -0.32 +/- 0.24, respectively, and pancreas-spleen ratios of 0.89 +/- 0.55 vs. 0.02 +/- 0.43, respectively, were significantly different (P < 0.001). The pancreas-liver SI ratio was significantly better than the pancreas-spleen ratio throughout the disease group (area under the receiver operating characteristic (ROC) curve +/- SD; 0.92 +/- 0.02 for pancreas-liver vs. 0.86 +/- 0.03 for pancreas-spleen, P < 0.01), and after excluding cases of acute pancreatitis (0.96 +/- 0.02 for pancreas-liver vs. 0.89 +/- 0.03 for pancreas-spleen, P < 0.01). There was no statistically significant difference between quantitative and qualitative analysis (area under the ROC curve +/- SD; 0.93 +/- 0.02 vs. 0.93 +/- 0.02 for the entire disease group; excluding acute pancreatitis 0.96 +/- 0.02 vs 0.97 +/- 0.02) for the diagnosis of pancreatic disease when using liver as internal standard. The interobserver concordance was very good (kappa > 0.71). The sensitivity of visual liver comparison was 80% in the entire disease group and 91% after the cases of acute pancreatitis were excluded, while specificity was 93%. CONCLUSION: The pancreas-liver ratio is the best quantitative means of distinguishing normal from abnormal pancreas. Visual observation by experienced observers (qualitative measurement) was just as accurate as quantitative measurement. Detection of pancreatic pathology can be made with high accuracy by visually comparing the SI of the pancreas with that of the normal liver.

Detection of nodules in liver cirrhosis: spiral computed tomography or magnetic resonance imaging? A prospective study of 88 nodules in 34 patients.

Detection and characterization of all focal lesions in the liver are critical for screening patients with chronic liver disease. The aim of this prospective study was to investigate the accuracy of magnetic resonance imaging (MRI) and spiral computed tomography for the diagnosis of hepatic nodules in cirrhotic patients when compared with pathological findings of the explanted liver. From February 1997 to July 1999, 34 cirrhotic patients waiting for orthotopic liver transplantation (OLT) (mean age, 53.5 +/- 9.3 years; 24 males) were included. All patients had MRI and spiral computed tomography examinations, and findings were matched with the histological findings. Data analyses were made using the McNemar chi-square test. Mean time between radiological examination (MRI or spiral computed tomography) and OLT was 43.8 +/- 39 days. A total of 88 nodules were found in the 34 patients: 54 hepatocellular carcinoma (HCC) (mean size, 18 +/- 10 mm) in 21 patients, 22 dysplastic nodules (mean size, 10.7 +/- 4.3 mm) in 11 patients, and 12 macroregenerative nodules in 13 patients. Lesion-by-lesion analyses showed that sensitivity of MRI and spiral computed tomography for nodule, HCC or dysplastic nodule diagnosis was 44.3 and 31.8% (P = 0.02), 61.1 and 51.9% (P = 0.2), and 27.3 and 0% (P = 0.04), respectively. Patient-by-patient analyses showed no statistical difference between spiral computed tomography and MRI for nodule diagnosis. In conclusion, in patients with liver cirrhosis, MRI is more accurate than spiral computed tomography for the detection of liver nodules and dysplastic nodules. However, tumour size is always a restricting factor for these two techniques, which are unable to detect small HCC in more than 60% of cases.