Mean tumor volume for NDEA treated c-Myc transgenic mice separated by gender.

<p>Data were obtained by CT and histopathology and are defined as mean percentage tumor volume and standard error of the mean for NDEA treated animals. Data are broken down by gender. At the age of 5.5 months the tumor incidence was 100% for male and female animals. No gender specific difference in tumor volume was observed except for histopathology findings at the age of 7 months;</p><p>*P<0.05.</p

CT and histopathology of the lung of NDEA treated c-Myc transgenic mice.

<p>(A) Normal lung parenchyma of a vehicle treated control animal as shown by CT (A1) and by histopathology (A2). CT of NDEA treated animals at the age of 8.5 months. Depicted are lung nodules of different size (red arrows). Histopathology evidenced those lung nodules as metastasis of a poorly differentiated HCC (B2) and as well adenocarcinoma of the lung (C2).</p

Time dependent changes in tumor growth of NDEA-treated c-Myc transgenic mice.

<p>(A) The organ and tumor volume was assessed by CT and by histopathology. Depicted is the percentage tumor volume at different stages measured either by histopathology (light gray) or by contrast enhanced CT imaging (dark gray). The mean diameter of lesions (B) and the total number of lesions (C) are shown. *p<0.05. **p<0.01.</p

Study groups and imaging protocol.

<p>Histopathology was carried out for all groups and for all time points (4, 5.5, 7, 8.5 months).</p><p>*<b>No CT/PET imaging was done,</b></p><p>**<b>CT/PET was acquired at the age of 8.5 months only. m, months; w, weeks.</b></p

Fused μPET/μCT images of the liver of c-Myc transgenic mice treated with physiological saline, BHT or NDEA.

<p>Depicted are the liver morphology as determined by CT (A1, B1,C1), the glucose metabolism (A2, B2, C2) and fused PET and CT scans (A3, B3, C3) of transgenic animals treated with either physiological saline (A), with BHT (B) or with NDEA (C) at the age of 8.5 months. Note, after treatment with NDEA expansive tumor growth with large increase of liver weight and compression and displacement of adjacent organs was observed. Here, the lesions showed an increased 18F-FDG uptake. In contrast, in corresponding control animals treated with physiological saline no liver lesions were observed. After treatment with BHT small hypodens lesions are noticed, but PET did not show an increased 18F-FDG uptake. K = kidney, L = liver, S = spine, Sp = spleen, St = stomach, T = tumor.</p

Influence of Sinogram Affirmed Iterative Reconstruction of CT Data on Image Noise Characteristics and Low-Contrast Detectability: An Objective Approach

<div><h3>Objectives</h3><p>To utilize a novel objective approach combining a software phantom and an image quality metric to systematically evaluate the influence of sinogram affirmed iterative reconstruction (SAFIRE) of multidetector computed tomography (MDCT) data on image noise characteristics and low-contrast detectability (LCD).</p> <h3>Materials and Methods</h3><p>A low-contrast and a high-contrast phantom were examined on a 128-slice scanner at different dose levels. The datasets were reconstructed using filtered back projection (FBP) and SAFIRE and virtual low-contrast lesions (-20HU) were inserted. LCD was evaluated using the multiscale structural similarity index (MS-SIM*). Image noise texture and spatial resolution were objectively evaluated.</p> <h3>Results</h3><p>The use of SAFIRE led to an improvement of LCD for all dose levels and lesions sizes. The relative improvement of LCD was inversely related to the dose level, declining from 208%(±37%), 259%(±30%) and 309%(±35%) at 25mAs to 106%(±6%), 119%(±9%) and 123%(±8%) at 200mAs for SAFIRE filter strengths of 1, 3 and 5 (p<0.05). SAFIRE reached at least the LCD of FBP at a relative dose of 50%. There was no statistically significant difference in spatial resolution. The use of SAFIRE led to coarser image noise granularity.</p> <h3>Conclusion</h3><p>A novel objective approach combining a software phantom and the MS-SSIM* image quality metric was used to analyze the detectability of virtual low-contrast lesions against the background of image noise as created using SAFIRE in comparison to filtered back-projection. We found, that image noise characteristics using SAFIRE at 50% dose were comparable to the use of FBP at 100% dose with respect to lesion detectability. The unfamiliar imaging appearance of iteratively reconstructed datasets may in part be explained by a different, coarser noise characteristic as demonstrated by a granulometric analysis.</p> </div

Histopathology of the liver of c-Myc treated transgenic animals.

<p>(A) Diffuse liver cell dysplasia of physiological saline ( = vehicle) treated transgenic mice at (A1) 50- and (A2) 200-fold magnification. (B) Large cell dysplasia of various degrees in BHT treated animals at (B1) 50- and (B2) 200-fold magnification. (C) Hepatocellular carcinoma of a transgenic mouse treated with the genotoxic carcinogen NDEA at (C1) 50 and (C2) 200-fold magnification.</p

Contrast-enhanced CT, ¹⁸F-FDG-PET and fused images of c-Myc transgenic mice treated with NDEA at the age of 5.5 and 7 months.

<p>(A) CT image demonstrates a single tumor lesion (A1) in a 5.5 months old mouse without increased ¹⁸F-FDG uptake (A2). The fused CT and PET image is depicted in A3. (B) At the age of 7 months expansive tumor growth (B1) as well as an increased tracer uptake in hepatocellular carcinoma (B2) is observed. The fused CT and PET image is depicted in B3. G = gallbladder, K = kidney, L = liver, S = spine, St = stomach, T = tumor.</p

Relative improvement of lesion detectability using iterative reconstruction averaged over all dose levels as compared to the standard B30f reconstruction.

<p>Relative improvement of lesion detectability using iterative reconstruction averaged over all dose levels as compared to the standard B30f reconstruction.</p

Relative improvement of lesion visibility using iterative reconstruction relating to the filtered back projection algorithm.

<p>Relative improvement of lesion visibility using iterative reconstruction relating to the filtered back projection algorithm.</p