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This study aimed to assess the relationship between pancreatic fibrosis measured by the extracellular volume fraction (ECV) using contrast-enhanced computed tomography (CT) and the histologic pancreatic fibrosis fraction and investigate the relationship between pancreatic fibrosis and pancreatic cancer.The study included 88 consecutive patients (48 males, 40 females; median age, 69 years; range, 17-89 years); 47 had pancreatic cancer, and 41 had other diseases. Fifty-two cases were evaluated pathologically for pancreatic fibrosis. The histologic pancreatic fibrosis fraction was quantified using image analysis software in nontumorous pancreatic tissue at the resection stump using 2-µm-thick Azan-stained slides. Two board-certified radiologists measured ECV in the pancreatic parenchyma at an estimated transection line. The correlation between histologic pancreatic fibrosis fraction and ECV was investigated, and whether the ECV value could be used as a biomarker for pancreatic cancer was investigated.The histologic pancreatic fibrosis fraction was significantly correlated with the ECV (r = 0.64, P 0.01). Pancreatic fibrosis evaluated by ECV was higher in pancreatic cancer patients than in other patients (P 0.01). On receiver-operating characteristic curve analysis, the ECV had good diagnostic accuracy for the development of pancreatic cancer (cut-off value 32.8%; sensitivity 61.0%, specificity 85.1%). ECV was identified on multivariate analysis as an independent risk factor for pancreatic cancer (odds ratio 1.16; P 0.01).Extracellular volume fraction was strongly related to the histologic pancreatic fibrosis fraction, which was independently associated with pancreatic cancer. Thus, extracellular volume fraction is an imaging biomarker that reflects the progression of pancreatic fibrosis and may potentially help predict the development of pancreatic cancer, although further investigation will be needed.

Purpose: To compare the accuracy of liver fibrosis staging with MR elastography and of staging with extracellular volume fraction (fECV) analysis using contrast-enhanced CT. Methods: This retrospective study included 60 patients who underwent both MR elastography and contrast-enhanced CT before liver surgery between October 2013 and July 2020. Two radiologists independently measured liver stiffness of MR elastography and fECV of CT images. Accuracy for liver fibrosis staging was assessed using receiver operating characteristic (ROC) analysis. Correlations between liver stiffness or fECV and liver fibrosis were also evaluated by means of the Spearman rank correlation coefficient. Results: The areas under the ROC curves for MR elastography for each stage differentiation of ≥F1 (0.85, 0.82 for the two radiologists), ≥F2 (0.88, 0.89), ≥F3 (0.87, 0.86), and F4 (0.84, 0.83) were greater than those for fECV analysis with CT (0.64, p = 0.06, 0.69, p = 0.2; 0.62, p < 0.005, 0.63, p < 0.005; 0.62, p < 0.005, 0.62, p < 0.01; and 0.70, p = 0.08, 0.71, p = 0.2, respectively). The correlation coefficients between liver stiffness and liver fibrosis in A0 (0.67, 0.69 for the two radiologists), A1 (0.64, 0.66) and A2 group (0.58, 0.51) were significantly higher than those between fECV and liver fibrosis (0.28, 0.30; 0.27, 0.31; and 0.23, 0.07; p < 0.05 for all comparisons). Conclusion: MR elastography allows for more accurate liver fibrosis staging compared with fECV analysis with CT. In addition, MR elastography may be less affected than fECV analysis by the inflammatory condition.

A newly developed Adaptive Image Receive (AIR) coil is designed to be more flexible to conform to the human body habitus, and may improve image quality by reducing the distance between the coil element and the imaging subject. This study evaluated the AIR coil's usefulness for liver MR imaging at 3.0 T in comparison with that of a conventional coil retrospectively.The study population comprised 50 consecutive patients, who underwent follow-up liver MR examinations with a 3.0-T MR system using both an AIR coil and a conventional coil to evaluate hepatocellular carcinoma. Three-dimensional fat-suppressed T1-weighted gradient-echo images before and after injection of an MRI contrast agent, T2-weighted single-shot fast spin-echo (SSFSE) images, and diffusion-weighted (DW) images obtained with the AIR coil were compared with corresponding images obtained with the conventional coil. One radiologist measured signal-to-noise ratios (SNRs), while two other radiologists used a 3-point scale to independently assess subjective image noise, artifacts, signal uniformity, and overall image quality.SNRs for the AIR coil were significantly higher than those for the conventional coil (P .05). Subjective image noise for the AIR coil on pre- and postcontrast T1-weighted and DW images was lower than for the conventional coil for both readers (P .05). Overall image quality on pre- and postcontrast T1-weighted and DW images for the AIR coil was better than that for the conventional coil for at least one reader (P .05).In comparison with the conventional coil, AIR coil improved SNR and image quality of liver MR imaging.

To evaluate the image quality of CT urography (CTU) obtained with ultra-high-resolution CT (U-HRCT) reconstructed with hybrid iterative reconstruction (IR) and model-based IR algorithms.Forty-eight patients who underwent CTU using the U-HRCT system were enrolled in this retrospective study. Excretory phase images were reconstructed with three protocols: Protocol A: 1024-matrix, 0.25 mm-thickness, and model-based IR; Protocol B: 1024-matrix, 0.25 mm-thickness, and hybrid IR; Protocol C: 512-matrix, 0.5 mm-thickness, and model-based IR. Objective image noise and contrast-to-noise ratio (CNR) of the renal pelvis were compared among the protocols. Three-dimensional maximum intensity projection CTU images were generated from each image data set, and image quality was evaluated by two radiologists.Protocol C yielded the lowest objective image noise and highest CNR, whereas Protocol A had highest image noise and lowest CNR (P 0.01). Regarding the detailed delineation of urinary tract structures on the images, the mean visual score was significantly higher for Protocol A than for Protocols B and C (P 0.001), and the mean score for subjective image noise was significantly lower for Protocol A than for Protocols B and C (P 0.001).CTU with a 1024-matrix and model-based IR depicted the structures of the urinary system in the most detail.