Prediction of abdominal CT body composition parameters by thoracic measurements as a new approach to detect sarcopenia in a COVID-19 cohort.

As most COVID-19 patients only receive thoracic CT scans, but body composition, which is relevant to detect sarcopenia, is determined in abdominal scans, this study aimed to investigate the relationship between thoracic and abdominal CT body composition parameters in a cohort of COVID-19 patients. This retrospective study included n = 46 SARS-CoV-2-positive patients who received CT scans of the thorax and abdomen due to severe disease progression. The subcutaneous fat area (SF), the skeletal muscle area (SMA), and the muscle radiodensity attenuation (MRA) were measured at the level of the twelfth thoracic (T12) and the third lumbar (L3) vertebra. Necessity of invasive mechanical ventilation (IMV), length of stay, or time to death (TTD) were noted. For statistics correlation, multivariable linear, logistic, and Cox regression analyses were employed. Correlation was excellent for the SF (r = 0.96) between T12 and L3, and good for the respective SMA (r = 0.80) and MRA (r = 0.82) values. With adjustment (adj.) for sex, age, and body-mass-index the variability of SF (adj. r2 = 0.93; adj. mean difference = 1.24 [95% confidence interval (95% CI) 1.02-1.45]), of the SMA (adj. r2 = 0.76; 2.59 [95% CI 1.92-3.26]), and of the MRA (adj. r2 = 0.67; 0.67 [95% CI 0.45-0.88]) at L3 was well explained by the respective values at T12. There was no relevant influence of the SF, MRA, or SMA on the clinical outcome. If only thoracic CT scans are available, CT body composition values at T12 can be used to predict abdominal fat and muscle parameters, by which sarcopenia and obesity can be assessed.

Skeletal muscle fat quantification by dual-energy computed tomography in comparison with 3T MR imaging.

OBJECTIVES: To quantify the proportion of fat within the skeletal muscle as a measure of muscle quality using dual-energy CT (DECT) and to validate this methodology with MRI. METHODS: Twenty-one patients with abdominal contrast-enhanced DECT scans (100 kV/Sn 150 kV) underwent abdominal 3-T MRI. The fat fraction (DECT-FF), determined by material decomposition, and HU values on virtual non-contrast-enhanced (VNC) DECT images were measured in 126 regions of interest (≥ 6 cm2) within the posterior paraspinal muscle. For validation, the MR-based fat fraction (MR-FF) was assessed by chemical shift relaxometry. Patients were categorized into groups of high or low skeletal muscle mean radiation attenuation (SMRA) and classified as either sarcopenic or non-sarcopenic, according to the skeletal muscle index (SMI) and cut-off values from non-contrast-enhanced single-energy CT. Spearman's and intraclass correlation, Bland-Altman analysis, and mixed linear models were employed. RESULTS: The correlation was excellent between DECT-FF and MR-FF (r = 0.91), DECT VNC HU and MR-FF (r = - 0.90), and DECT-FF and DECT VNC HU (r = - 0.98). Intraclass correlation between DECT-FF and MR-FF was good (r = 0.83 [95% CI 0.71-0.90]), with a mean difference of - 0.15% (SD 3.32 [95% CI 6.35 to - 6.66]). Categorization using the SMRA yielded an eightfold difference in DECT VNC HU values between both groups (5 HU [95% CI 23-11], 42 HU [95% CI 33-56], p = 0.05). No significant relationship between DECT-FF and SMI-based classifications was observed. CONCLUSIONS: Fat quantification within the skeletal muscle using DECT is both feasible and reliable. DECT muscle analysis offers a new approach to determine muscle quality, which is important for the diagnosis and therapeutic monitoring of sarcopenia, as a comorbidity associated with poor clinical outcome. KEY POINTS: • Dual-energy CT (DECT) material decomposition and virtual non-contrast-enhanced DECT HU values assess muscle fat reliably. • Virtual non-contrast-enhanced dual-energy CT HU values allow to differentiate between high and low native skeletal muscle mean radiation attenuation in contrast-enhanced DECT scans. • Measuring muscle fat by dual-energy computed tomography is a new approach for the determination of muscle quality, an important parameter for the diagnostic confirmation of sarcopenia as a comorbidity associated with poor clinical outcome.

First magnetic particle imaging angiography in human-sized organs by employing a multimodal ex vivo pig kidney perfusion system.

OBJECTIVE: Magnetic particle imaging (MPI) is a new, fast 3D imaging technique, which is considered promising for angiographies. As available MPI scanners suffer from restricted spatial resolution and are mostly constructed for small animal imaging, no vessels within one organ have been depicted by MPI, yet. The purpose of this study was to develop an ex vivo organ perfusion system to display vessels within one organ of human size by MPI and to compare the results to an established 3D imaging technique. APPROACH: An ex vivo porcine kidney perfusion system compatible with digital subtraction angiography (DSA), magnetic resonance tomography and MPI was developed. DSA was used to exemplarily prove intact vessel structures under ex vivo perfusion in two organs. Perfusion in nine organs was displayed by the 3D imaging techniques magnetic resonance angiography (MRA) and MPI angiography. All visible vessels in MRA and MPI were counted and their number compared between both techniques. MAIN RESULTS: The ex vivo organ perfusion system allowed us to perform angiographies by DSA, MRA and MPI. With it, organs of human size could be imaged in small animal scanners, which permitted us to depict vessels within one organ by MPI for the first time. In comparison to MRA, 33% of all vessels were visible in MPI, a difference probably caused by restricted spatial resolution in MPI. SIGNIFICANCE: The presented ex vivo organ perfusion system can serve to practically evaluate MPI's potential for angiography in human-sized organs. This is especially relevant as long as available, for angiography-suited MPI scanners still suffer from size and spatial resolution restrictions.