Validation of a fast method for quantification of intra-abdominal and subcutaneous adipose tissue for large-scale human studies

Central obesity is the hallmark of a number of non-inheritable disorders. The advent of imaging techniques such asMRI has allowed for a fast and accurate assessment of body fat content and distribution. However, image analysis continues to be one of the major obstacles to the use of MRI in large-scale studies. In this study we assess the validity of the recently proposed fat–muscle quantitation system (AMRATM Profiler) for the quantification of intra-abdominal adipose tissue (IAAT) and abdominal subcutaneous adipose tissue (ASAT) from abdominal MR images. Abdominal MR images were acquired from 23 volunteers with a broad range of BMIs and analysed using sliceOmatic, the current gold-standard, and the AMRATM Profiler based on a non-rigid image registration of a library of segmented atlases. The results show that there was a highly significant correlation between the fat volumes generated by the two analysis methods, (Pearson correlation r = 0.97, p < 0.001), with the AMRATM Profiler analysis being significantly faster (~3 min) than the conventional sliceOmatic approach (~40 min). There was also excellent agreement between the methods for the quantification of IAAT (AMRA 4.73 ± 1.99 versus sliceOmatic 4.73 ± 1.75 l, p = 0.97). For the AMRATM Profiler analysis, the intra-observer coefficient of variation was 1.6% for IAAT and 1.1% for ASAT, the inter-observer coefficient of variationwas 1.4%for IAAT and 1.2%for ASAT, the intra-observer correlationwas 0.998 for IAAT and 0.999 for ASAT, and the inter-observer correlation was 0.999 for both IAAT and ASAT. These results indicate that precise and accurate measures of body fat content and distribution can be obtained in a fast and reliable form by the AMRATM Profiler, opening up the possibility of large-scale human phenotypic studies

Quantitative PET image reconstruction employing nested expectation-maximization deconvolution for motion compensation

Bulk body motion may randomly occur during PET acquisitions introducing blurring, attenuation-emission mismatches and, in dynamic PET, discontinuities in the measured time activity curves between consecutive frames. Meanwhile, dynamic PET scans are longer, thus increasing the probability of bulk motion. In this study, we propose a streamlined 3D PET motion-compensated image reconstruction (3D-MCIR) framework, capable of robustly deconvolving intra-frame motion from a static or dynamic 3D sinogram. The presented 3D-MCIR methods need not partition the data into multiple gates, such as 4D MCIR algorithms, or access list-mode (LM) data, such as LM MCIR methods, both associated with increased computation or memory resources. The proposed algorithms can support compensation for any periodic and non-periodic motion, such as cardio-respiratory or bulk motion, the latter including rolling, twisting or drifting. Inspired from the widely adopted point-spread function (PSF) deconvolution 3D PET reconstruction techniques, here we introduce an image-based 3D generalized motion deconvolution method within the standard 3D maximum-likelihood expectation-maximization (ML-EM) reconstruction framework. In particular, we initially integrate a motion blurring kernel, accounting for every tracked motion within a frame, as an additional MLEM modeling component in the image space (integrated 3D-MCIR). Subsequently, we replaced the integrated model component with a nested iterative Richardson-Lucy (RL) image-based deconvolution method to accelerate the MLEM algorithm convergence rate (RL-3D-MCIR). The final method was evaluated with realistic simulations of whole-body dynamic PET data employing the XCAT phantom and real human bulk motion profiles, the latter estimated from volunteer dynamic MRI scans. In addition, metabolic uptake rate Ki parametric images were generated with the standard Patlak method. Our results demonstrate significant improvement in contrast-to-noise ratio (CNR) and noise-bias performance in both dynamic and parametric images. The proposed nested RL-3D-MCIR method is implemented on the Software for Tomographic Image Reconstruction (STIR) open-source platform and is scheduled for public release

International cooperation framework and its effect on research stuff skills

The article outlines experience of collaboration between the National Mining University (Dnepropetrovsk, Ukraine) and the Esslingen University of Applied Sciences (Germany). The framework of this cooperation is described and the benefits are highlighted.В статті описаний досвід співробітництва Національного гірничого університету (Дніпропетровськ, Україна) та Есслінгенського університету прикладних наук (ФРН). Наведена модель та форми співробітництва, описані вигоди для сторін-учасників

Respiratory Motion Correction in Oncologic PET Using T1-Weighted MR Imaging on a Simultaneous Whole-Body PET/MR System

Hybrid PET/MR combines the exceptional molecular sensitivity of PET with the high resolution and versatility of MR imaging. Simultaneous data acquisition additionally promises the use of MR to enhance the quality of PET images, for example, by respiratory motion correction. This advantage is especially relevant in thoracic and abdominal areas to improve the visibility of small lesions with low radiotracer uptake and to enhance uptake quantification. In this work, the applicability and performance of an MR-based method of respiratory motion correction for PET tumor imaging was evaluated in phantom and patient studies. METHODS: PET list-mode data from a motion phantom with (22)Na point sources and 5 patients with tumor manifestations in the thorax and upper abdomen were acquired on a simultaneous hybrid PET/MR system. During the first 3 min of a 5-min PET scan, the respiration-induced tissue deformation in the PET field of view was recorded using a sagittal 2-dimensional multislice gradient echo MR sequence. MR navigator data to measure the location of the diaphragm were acquired throughout the PET scan. Respiration-gated PET data were coregistered using the MR-derived motion fields to obtain a single motion-corrected PET dataset. The effect of motion correction on tumor visibility, delineation, and radiotracer uptake quantification was analyzed with respect to uncorrected and gated images. RESULTS: Image quality in terms of lesion delineation and uptake quantification was significantly improved compared with uncorrected images for both phantom and patient data. In patients, in head-feet line profiles of 14 manifestations, the slope became steeper by 66.7% (P = 0.001) and full width at half maximum was reduced by 20.6% (P = 0.001). The mean increase in maximum standardized uptake value, lesion-to-background ratio (contrast), and signal-to-noise ratio was 28.1% (P = 0.001), 24.7% (P = 0.001), and 27.3% (P = 0.003), respectively. Lesion volume was reduced by an average of 26.5% (P = 0.002). As opposed to the gated images, no increase in background noise was observed. However, motion correction performed worse than gating in terms of contrast (-11.3%, P = 0.002), maximum standardized uptake value (-10.7%, P = 0.003), and slope steepness (-19.3%, P = 0.001). CONCLUSION: The proposed method for MR-based respiratory motion correction of PET data proved feasible and effective. The short examination time and convenience (no additional equipment required) of the method allow for easy integration into clinical routine imaging. Performance compared with gating procedures can be further improved using list-mode-based motion correction

Relaxometry of tendons, ligaments and menisci in the knee joint at 3 T

Within the last years a variety of pulse sequences have been published which visualize musculoskeletal tissues such as menisci, tendons, or ligaments with positive contrast despite their relatively short T2-values. For optimization of sequence parameters by numerical simulations based on Bloch’s equations, knowledge of tissue relaxation times is essential. So far there has been no comprehensive MRI study regarding the systematic measurement of their inherent relaxation properties. Therefore, the purpose of this study was to exemplarily quantify the T1lower case Greek rho, T1, T2, and T2* relaxation times of rapidly relaxing tissues in the human knee joint at 3T in an acceptable examination time

The use of a generalized reconstruction by inversion of coupled systems (GRICS) approach for generic respiratory motion correction in PET/MR imaging

International audienceRespiratory motion is a source of artifacts in multimodality imaging such as PET/MR. Solutions include retrospective or prospective gating. They have however found limited use in clinical practice, since their increased overall acquisition duration to maintain overall image quality. More elaborate methods consist of using 4D MR datasets to extract spatial deformations in order to correct for the respiratory motion in PET. The main drawbacks of such approaches is the relatively long acquisition times associated with 4D MR imaging which is often incompatible with clinical PET/MR protocols. The objective of this work was to overcome these limitations by exploiting a generalized reconstruction by inversion of coupled systems (GRICS) approach. The methodology is based on a joint estimation of motion during the MR image reconstruction process, providing internal structure motion and associated deformation matrices for retrospective use in PET respiratory motion correction. This method was first validated on four MR volunteers and two PET/MR patient datasets by comparing GRICS generated MR images to 4D MR series obtained by retrospective gating. In a second step 4D PET datasets corresponding to acquired 4D MR images were simulated using the GATE Monte Carlo simulation platform. GRICS generated deformation matrices were subsequently used to correct respiratory motion in comparison to the 4D MR image based deformations both for the simulated and the two 4D PET/MR patient datasets. Results confirm that GRICS synchronized MR images correlate well with the acquired 4D MR series. Similarly, the use of GRICS for respiratory motion correction allows an equivalent percentage improvement on lesion contrast, position and size, considering the PET simulated tumors as well as PET real tumors. This work demonstrates the potential interest of using GRICS for PET respiratory motion correction in combined PET/MR using shorter duration acquisitions without the need for 4D MRI and associated specific MR sequences

Characteristics, changes and influence of body composition during a 4486 km transcontinental ultramarathon: Results from the Transeurope Footrace mobile whole body MRI-project.

Background: Almost nothing is known about the medical aspects of runners doing a transcontinental ultramarathon over several weeks. The results of differentiated measurements of changes in body composition during the Transeurope Footrace 2009 using a mobile whole body magnetic resonance (MR) imager are presented and the proposed influence of visceral and somatic adipose and lean tissue distribution on performance tested. Methods: 22 participants were randomly selected for the repeated MR measurements (intervals: 800 km) with a 1.5 Tesla MR scanner mounted on a mobile unit during the 64-stage 4,486 km ultramarathon. A standardized and validated MRI protocol was used: T1 weighted turbo spin echo sequence, echo time 12 ms, repetition time 490 ms, slice thickness 10 mm, slice distance 10mm (breath holding examinations). For topographic tissue segmentation and mapping a modified fuzzy c-means algorithm was used. A semi-automatic post-processing of whole body MRI data sets allows reliable analysis of the following body tissue compartments: Total body volume (TV), total somatic (TSV) and total visceral volume (TVV), total adipose (TAT) and total lean tissue (TLT), somatic (SLT) and visceral lean tissue (VLT), somatic (SAT) and visceral adipose tissue (VAT) and somatic adipose soft tissue (SAST). Specific volume changes were tested on significance. Tests on difference and relationship regarding prerace and race performance and non-finishing were done using statistical software SPSS. Results: Total, somatic and visceral volumes showed a significant decrease throughout the race. Adipose tissue showed a significant decrease compared to the start at all measurement times for TAT, SAST and VAT. Lean adipose tissues decreased until the end of the race, but not significantly. The mean relative volume changes of the different tissue compartments at the last measurement compared to the start were: TV -9.5% (SE 1.5%), TSV -9.4% (SE 1.5%), TVV -10.0% (SE 1.4%), TAT -41.3% (SE 2.3%), SAST -48.7% (SE 2.8%), VAT -64.5% (SE 4.6%), intraabdominal adipose tissue (IAAT) -67.3% (SE 4.3%), mediastinal adopose tissue (MAT) -41.5% (SE 7.1%), TLT -1.2% (SE 1.0%), SLT -1.4% (SE 1.1%). Before the start and during the early phase of the Transeurope Footrace 2009, the non-finisher group had a significantly higher percentage volume of TVV, TAT, SAST and VAT compared to the finisher group. VAT correlates significantly with prerace training volume and intensity one year before the race and with 50 km-and 24 hour-race records. Neither prerace body composition nor specific tissue compartment volume changes showed a significant relationship to performance in the last two thirds of the Transeurope Footrace 2009. Conclusions: With this mobile MRI field study the complex changes in body composition during a multistage ultramarathon could be demonstrated in detail in a new and differentiated way. Participants lost more than half of their adipose tissue. Even lean tissue volume (mainly skeletal muscle tissue) decreased due to the unpreventable chronic negative energy balance during the race. VAT has the fastest and highest decrease compared to SAST and lean tissue compartments during the race. It seems to be the most sensitive morphometric parameter regarding the risk of non-finishing a transcontinental footrace and shows a direct relationship to prerace-performance. However, body volume or body mass and, therefore, fat volume has no correlation with total race performances of ultra-athletes finishing a 4,500 km multistage race