An enhancement to Dixon's technique is described which can provide error-free decomposition of water and fat proton images even in the presence of off-resonance conditions which result from susceptibility differences, demagnetization, or shim errors. The method uses three measurements with phase shifts of 0, pi, and -pi between the fat and water resonances. The additional information provided by the third measurement is used to calculate an image of the field inhomogeneity in addition to true water and fat images. The signal-to-noise ratio (SNR) in the decomposed images is equivalent to that of a 2.7 NEX acquisition (instead of 3 NEX), yielding an SNR imaging efficiency of 95%. In addition, the B0 image which is provided may have diagnostic value in its own right. Examples of head and body scans often portray surprisingly large B0 shifts near interfaces between air or bone and soft tissue.

Summary Objectives To report on the process and criteria for selecting acquisition protocols to include in the osteoarthritis initiative (OAI) magnetic resonance imaging (MRI) study protocol for the knee. Methods Candidate knee MR acquisition protocols identified from the literature were first optimized at 3 Tesla (T). Twelve knees from 10 subjects were scanned one time with each of 16 acquisitions considered most likely to achieve the study goals and having the best optimization results. The resultant images and multi-planar reformats were evaluated for artifacts and structural discrimination of articular cartilage at the cartilage–fluid, cartilage–fat, cartilage–capsule, cartilage–meniscus and cartilage–cartilage interfaces. Results The five acquisitions comprising the final OAI MRI protocol were assembled based on the study goals for the imaging protocol, the image evaluation results and the need to image both knees within a 75 min time slot, including positioning. For quantitative cartilage morphometry, fat-suppressed, 3D dual-echo in steady state (DESS) acquisitions appear to provide the best universal cartilage discrimination. Conclusions The OAI knee MRI protocol provides imaging data on multiple articular structures and features relevant to knee OA that will support a broad range of existing and anticipated measurement methods while balancing requirements for high image quality and consistency against the practical considerations of a large multi-center cohort study. Strengths of the final knee MRI protocol include cartilage quantification capabilities in three planes due to multi-planar reconstruction of a thin slice, high spatial resolution 3D DESS acquisition and the multiple, non-fat-suppressed image contrasts measured during the T2 relaxation time mapping acquisition.

DESSwe permits accurate and precise analysis of cartilage morphology in the femorotibial joint at 3 T. Further studies are needed to examine the accuracy of DESSwe in the femoropatellar joint and its ability to characterise sensitivity to longitudinal changes in cartilage morphology.

A rapid and completely automated method of adjusting the magnetic field (B0) homogeneity for in vivo proton spectroscopy and imaging is described. B0 inhomogeneity maps are generated by a gradient-recalled echo pulse sequence in which the frequency dispersion is chosen to eliminate the effects of the fat/water chemical shift. Low-order shim values are derived by magnitude-weighted least-squares fits to the B0 maps and automatically applied as DC offsets to the X, Y, and Z gradient amplifiers. Imaging with chemical shift selective saturation is used as a measure of the efficacy of the technique. Results indicate that AUTOSHIM improves the overall homogeneity: however, local high-order field distortions which cannot be corrected by linear gradients are generated by certain air/tissue and bone/tissue morphology. In such cases a "Zoom SHIM" may be applied over a limited region of interest for local homogeneity improvement at the expense of other regions. It is suggested that such scans are a necessity for recording the homogeneity during clinical MR spectroscopy.

This paper presents a fully automated method for segmenting articular knee cartilage and bone from in vivo 3-D dual echo steady state images. The magnetic resonance imaging (MRI) datasets were obtained from the Osteoarthritis Initiative (OAI) pilot study and include longitudinal images from controls and subjects with knee osteoarthritis (OA) scanned twice at each visit (baseline, 24 month). Initially, human experts segmented six MRI series. Five of the six resultant sets served as reference atlases for a multiatlas segmentation algorithm. The methodology created precise knee segmentations that were used to extract articular cartilage volume, surface area, and thickness as well as subchondral bone plate curvature. Comparison to manual segmentation showed Dice similarity coefficient (DSC) of 0.88 and 0.84 for the femoral and tibial cartilage. In OA subjects, thickness measurements showed test-retest precision ranging from 0.014 mm (0.6%) at the femur to 0.038 mm (1.6%) at the femoral trochlea. In the same population, the curvature test-retest precision ranged from 0.0005 mm(-1) (3.6%) at the femur to 0.0026 mm(-1) (11.7%) at the medial tibia. Thickness longitudinal changes showed OA Pearson correlation coefficient of 0.94 for the femur. In conclusion, the fully automated segmentation methodology produces reproducible cartilage volume, thickness, and shape measurements valuable for the study of OA progression.