Comparing nonrigid registration techniques for motion corrected MR prostate diffusion imaging.

PURPOSE: T2-weighted magnetic resonance imaging (MRI) is commonly used for anatomical visualization in the pelvis area, such as the prostate, with high soft-tissue contrast. MRI can also provide functional information such as diffusion-weighted imaging (DWI) which depicts the molecular diffusion processes in biological tissues. The combination of anatomical and functional imaging techniques is widely used in oncology, e.g., for prostate cancer diagnosis and staging. However, acquisition-specific distortions as well as physiological motion lead to misalignments between T2 and DWI and consequently to a reduced diagnostic value. Image registration algorithms are commonly employed to correct for such misalignment. METHODS: The authors compare the performance of five state-of-the-art nonrigid image registration techniques for accurate image fusion of DWI with T2. RESULTS: Image data of 20 prostate patients with cancerous lesions or cysts were acquired. All registration algorithms were validated using intensity-based as well as landmark-based techniques. CONCLUSIONS: The authors' results show that the "fast elastic image registration" provides most accurate results with a target registration error of 1.07 ± 0.41 mm at minimum execution times of 11 ± 1 s.

Automatic, three-segment, MR-based attenuation correction for whole-body PET/MR data.

PURPOSE: The combination of positron emission tomography (PET) and magnetic resonance (MR) tomography in a single device is anticipated to be the next step following PET/CT for future molecular imaging application. Compared to CT, the main advantages of MR are versatile soft tissue contrast and its capability to acquire functional information without ionizing radiation. However, MR is not capable of measuring a physical quantity that would allow a direct derivation of the attenuation values for high-energy photons. METHODS: To overcome this problem, we propose a fully automated approach that uses a dedicated T1-weighted MR sequence in combination with a customized image processing technique to derive attenuation maps for whole-body PET. The algorithm automatically identifies the outer contour of the body and the lungs using region-growing techniques in combination with an intensity analysis for automatic threshold estimation. No user interaction is required to generate the attenuation map. RESULTS: The accuracy of the proposed MR-based attenuation correction (AC) approach was evaluated in a clinical study using whole-body PET/CT and MR images of the same patients (n = 15). The segmentation of the body and lung contour (L-R directions) was evaluated via a four-point scale in comparison to the original MR image (mean values >3.8). PET images were reconstructed using elastically registered MR-based and CT-based (segmented and non-segmented) attenuation maps. The MR-based AC showed similar behaviour as CT-based AC and similar accuracy as offered by segmented CT-based AC. Standardized uptake value (SUV) comparisons with reference to CT-based AC using predefined attenuation coefficients showed the largest difference for bone lesions (mean value ± standard variation of SUV(max): -3.0% ± 3.9% for MR; -6.5% ± 4.1% for segmented CT). A blind comparison of PET images corrected with segmented MR-based, CT-based and segmented CT-based AC afforded identical lesion detectability, but slight differences in image quality were found. CONCLUSION: Our MR-based attenuation correction method offers similar correction accuracy as offered by segmented CT. According to the specialists involved in the blind study, these differences do not affect the diagnostic value of the PET images.

FDG PET/CT in cancer therapy monitoring: computer-assisted analysis of baseline together with up to two follow-ups.

OBJECTIVES: We developed and tested a software tool for computer-assisted analysis of FDG-PET/CT in cancer therapy monitoring. The tool provides automatic semi-quantitative analysis of a baseline scan together with up to two follow-up scans (standardized uptake values, glycolytic volume). The tool also supports visual analysis by local spatial registration which allows display of tumor lesions with the same orientation in all scans. The tool's stability and accuracy was tested at typical everyday image quality. PATIENTS, METHODS: Ten unselected cancer patients in whom three FDG PET/CT scans had been performed were included. A total of 18 lesions were analyzed. RESULTS: Automatic lesion tracking worked properly in all lesions but one. In this lesion local coregistration had to be adjusted manually which, however, is easily performed with the tool. Semi-automatic lesion segmentation and fully automatic semi-quantitative analysis worked properly in all cases. Computer-assisted analysis was significantly less time consuming than manual analysis. CONCLUSIONS: The novel software tool appears useful for analysis of FDG-PET/CT in cancer therapy monitoring in clinical routine patient care.