Background Development of successful weight loss interventions requires accurate assessment of body composition especially when measuring effects of dietary and exercise weight loss approaches. Because increasing proportions of the population are becoming obese, translation of measurement‐rich assessments from the clinical setting into the population setting are essential. Increasing visceral adipose tissue in the intra‐abdominal area during weight gain, independent of total adipose tissue, is associated with cardiovascular disease, metabolic syndrome, type‐2 diabetes, and cancer risk of several sites. The most accurate imaging of visceral fat (VF) is abdominal X‐ray computed tomography (CT) and Magnetic Resonance Imaging (MRI). Dual‐energy X‐Ray absorptiometry (iDXA) with the enCORE™ CoreScan software specifically designed to estimate visceral fat can measure body composition with low radiation exposure and potentially high precision. The iDXA could represent an accurate and less‐expensive option to CT and MRI, although only a few studies have validated iDXA abdominal visceral fat imaging against MRI or CT. Aims and Methods To more accurately estimate associations between metabolic parameters associated with adipose tissue, we conducted tandem measurements of abdominal visceral and subcutaneous fat using the MRI and iDXA to determine if iDXA was accurately estimating visceral fat. Results A total of 37 subjects, with average age of 28 years old who were mostly female (58%) and Caucasian (62%) had iDXA scans conducted at baseline. On average, they had class 1 obesity (BMI = 38 kg/m 2 ), with average weight of 253 pounds. Their visceral fat averaged 1633 ± 929 grams and total android fat mass was 5531 ± 2160 grams. Of the 37 subjects who had iDXA scans, 13 subjects also had MRI scans within one to two days of the iDXA scan. These 13 subjects had an average MRI assessment of 7918.38±1778.74 cm 3 visceral adipose tissue and 12180.08±3702.56 cm 3 subcutaneous. Correlations for visceral adipose tissue measurement by both the iDXA and MRI was r=0.59, p=0.04. Conclusions While MRI is the gold standard for assessing visceral abdominal fat, scanning with the iDXA is reasonably accurate. Precision could be improved with a larger sample size. Support or Funding Information NIH, R01 DK090406
The main objective of this work was to detect novel biomarkers in breast cancer by spreading the MR spectra over two dimensions in multiple spatial locations using an accelerated 5D EP-COSI technology.The 5D EP-COSI data were non-uniformly undersampled with an acceleration factor of 8 and reconstructed using group sparsity-based compressed sensing reconstruction. Different metabolite and lipid ratios were then quantified and statistically analyzed for significance. Linear discriminant models based on the quantified metabolite and lipid ratios were generated. Spectroscopic images of the quantified metabolite and lipid ratios were also reconstructed.The 2D COSY spectra generated using the 5D EP-COSI technique showed differences among healthy, benign, and malignant tissues in terms of their mean values of metabolite and lipid ratios, especially the ratios of potential novel biomarkers based on unsaturated fatty acids, myo-inositol, and glycine. It is further shown the potential of choline and unsaturated lipid ratio maps, generated from the quantified COSY signals across multiple locations in the breast, to serve as complementary markers of malignancy that can be added to the multiparametric MR protocol. Discriminant models using metabolite and lipid ratios were found to be statistically significant for classifying benign and malignant tumor from healthy tissues.Accelerated 5D EP-COSI technique demonstrates the potential to detect novel biomarkers such as glycine, myo-inositol, and unsaturated fatty acids in addition to commonly reported choline in breast cancer, and facilitates metabolite and lipid ratio maps which have the potential to play a significant role in breast cancer detection.This study presents the first evaluation of a multidimensional MR spectroscopic imaging technique for the detection of potentially novel biomarkers based on glycine, myo-inositol, and unsaturated fatty acids, in addition to commonly reported choline. Spatial mapping of choline and unsaturated fatty acid ratios with respect to water in malignant and benign breast masses are also shown. These metabolic characteristics may serve as additional biomarkers for improving the diagnostic and therapeutic evaluation of breast cancer.
In addition to detecting water and lipids in human tissues using magnetic resonance imaging (MRI), a number of metabolite resonances have been recorded noninvasively using one (chemical shift)-dimensional (1-D) proton (1H) magnetic resonance (MR) spectroscopy (MRS) on whole-body MRI scanners (1.5 and 3 T). However, severe overlap of resonances in 1-D MRS limits the unambiguous identification of many metabolites. Different versions of spectral editing sequences allow detection and quantification of selected metabolites. This approach, too, is limited in that it detects only one metabolite per acquisition, and many metabolites still cannot be detected owing to severe overlap. Adding another spectral dimension can overcome this limitation by providing resolution of metabolite resonances along the second dimension, thereby reducing the ambiguity, especially for quantifying J-coupled metabolites. In this article, we review progress with two-dimensional (2-D) MRS such as localized J-resolved spectroscopy (JPRESS) and localized correlated spectroscopy (L-COSY and their multidimensional versions, namely echo-planar-correlated spectroscopic imaging EP-COSI) and echo-planar J-resolved spectroscopic imaging (EP-JRESI), where 2-D spectral encoding is combined with two- or three-dimensional spatial encoding. These '4-D' or '5-D' spectroscopic imaging sequences can be extremely time consuming. However, acquisition using nonuniform undersampling (NUS) strategies and compressed sensing (CS) accelerates their acquisition times.
Despite the success of antiretroviral therapy (ART), perinatally infected HIV remains a major health problem worldwide. Although advance neuroimaging studies have investigated structural brain changes in HIV-infected adults, regional gray matter (GM) and white matter (WM) volume changes have not been reported in perinatally HIV-infected adolescents and young adults. In this cross-sectional study, we investigated regional GM and WM changes in 16 HIV-infected youths receiving ART (age 17.0 ± 2.9 years) compared with age-matched 14 healthy controls (age 16.3 ± 2.3 years) using magnetic resonance imaging (MRI)-based high-resolution T1-weighted images with voxel based morphometry (VBM) analyses. White matter atrophy appeared in perinatally HIV-infected youths in brain areas including the bilateral posterior corpus callosum (CC), bilateral external capsule, bilateral ventral temporal WM, mid cerebral peduncles, and basal pons over controls. Gray matter volume increase was observed in HIV-infected youths for several regions including the left superior frontal gyrus, inferior occipital gyrus, gyrus rectus, right mid cingulum, parahippocampal gyrus, bilateral inferior temporal gyrus, and middle temporal gyrus compared with controls. Global WM and GM volumes did not differ significantly between groups. These results indicate WM injury in perinatally HIV-infected youths, but the interpretation of the GM results, which appeared as increased regional volumes, is not clear. Further longitudinal studies are needed to clarify if our results represent active ongoing brain infection or toxicity from HIV treatment resulting in neuronal cell swelling and regional increased GM volume. Our findings suggest that assessment of regional GM and WM volume changes, based on VBM procedures, may be an additional measure to assess brain integrity in HIV-infected youths and to evaluate success of current ART therapy for efficacy in the brain.
Prospectively undersampled 5D echo-planar J-resolved spectroscopic imaging (EP-JRESI) data were acquired in 9 prostate cancer patients and 3 healthy controls. The 5D data was reconstructed using Dictionary learning (DL), Total Variation (TV), Perona-Malik (PM) and a hybrid DLTV method combining DL and TV. DLTV uses the gradient sparsity of TV and the learned dictionary-based sparsity of DL to further increase the transform sparsity of the data. The DLTV method unambiguously resolved 2D J-resolved peaks including myo-inositol, citrate, creatine, spermine and choline with an improved reconstruction that facilitates higher acceleration factors, leading to significant reduction in scan time.
'%3e%3ccircle r='20' fill='%23008'/%3e%3ccircle r='17.5' fill='%23fff'/%3e%3ccircle r='3.5' fill='%23008'/%3e%3cg id='d'%3e%3cg id='c'%3e%3cg id='b'%3e%3cg id='a' fill='%23008'%3e%3ccircle r='.875' transform='rotate(7.5 -8.75 133.5)'/%3e%3cpath d='M0 17.5.6 7 0 2l-.6 5L0 17.5z'/%3e%3c/g%3e%3cuse xlink:href='%23a' transform='rotate(15)'/%3e%3c/g%3e%3cuse xlink:href='%23b' transform='rotate(30)'/%3e%3c/g%3e%3cuse xlink:href='%23c' transform='rotate(60)'/%3e%3c/g%3e%3cuse xlink:href='%23d' transform='rotate(120)'/%3e%3cuse xlink:href='%23d' transform='rotate(-120)'/%3e%3c/g%3e%3c/svg%3e)