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PURPOSE: Compared with lower field strengths, DWI at 7 T faces the combined challenges of increased distortion and blurring due to B0 inhomogeneity, and increased signal dropouts due to B1 + inhomogeneity. This study addresses the B1 + limitations using slice-specific static parallel transmission (pTx) in a multi-shot, readout-segmented EPI diffusion imaging sequence. METHODS: DWI was performed in 7 healthy subjects using MRI at 7 T and readout-segmented EPI. Data were acquired with non-pTx circular-polarized (CP) pulses (CP-DWI) and static pTx pulses (pTx-DWI) using slice-specific B1 + shim coefficients. Each volunteer underwent two scan sessions on the same day, with two runs of each sequence in the first session and one run in the second. The sequences were evaluated by assessing image quality, flip-angle homogeneity, and intrasession and intersession repeatability in ADC estimates. RESULTS: pTx-DWI significantly reduced signal voids compared with CP-DWI, particularly in inferior brain regions. The use of pTx also improved RF uniformity and symmetry across the brain. These effects translated into improved intrasession and intersession repeatability for pTx-DWI. Additionally, re-optimizing the pTx pulse between repeat scans did not have a negative effect on ADC repeatability. CONCLUSION: The study demonstrates that pTx provides a reproducible image-quality increase in multishot DWI at 7 T. The benefits of pTx also extend to quantitative ADC estimation with regard to the improvement in intrasession and intersession repeatability. Overall, the combination of multishot imaging and pTx can support the development of reliable, high-resolution DWI for clinical studies at 7 T.
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BACKGROUND: The associations between deprivation and illness trajectory after hospitalisation for coronavirus disease-19 (COVID-19) are uncertain. METHODS: A prospective, multicentre cohort study was conducted on post-COVID-19 patients, enrolled either in-hospital or shortly post-discharge. Two evaluations were carried out: an initial assessment and a follow-up at 28-60 days post-discharge. The study encompassed research blood tests, patient-reported outcome measures, and multisystem imaging (including chest computed tomography (CT) with pulmonary and coronary angiography, cardiovascular and renal magnetic resonance imaging). Primary and secondary outcomes were analysed in relation to socioeconomic status, using the Scottish Index of Multiple Deprivation (SIMD). The EQ-5D-5L, Brief Illness Perception Questionnaire (BIPQ), Patient Health Questionnaire-4 (PHQ-4) for Anxiety and Depression, and the Duke Activity Status Index (DASI) were used to assess health status. RESULTS: Of the 252 enrolled patients (mean age 55.0 ± 12.0 years; 40% female; 23% with diabetes), deprivation status was linked with increased BMI and diabetes prevalence. 186 (74%) returned for the follow-up. Within this group, findings indicated associations between deprivation and lung abnormalities (p = 0.0085), coronary artery disease (p = 0.0128), and renal inflammation (p = 0.0421). Furthermore, patients with higher deprivation exhibited worse scores in health-related quality of life (EQ-5D-5L, p = 0.0084), illness perception (BIPQ, p = 0.0004), anxiety and depression levels (PHQ-4, p = 0.0038), and diminished physical activity (DASI, p = 0.002). At the 3-month mark, those with greater deprivation showed a higher frequency of referrals to secondary care due to ongoing COVID-19 symptoms (p = 0.0438). However, clinical outcomes were not influenced by deprivation. CONCLUSIONS: In a post-hospital COVID-19 population, socioeconomic deprivation was associated with impaired health status and secondary care episodes. Deprivation influences illness trajectory after COVID-19.
In our study, we aimed to understand how socioeconomic factors impact recovery from COVID-19 following hospitalisation. We followed 252 patients, collecting health data and utilising advanced imaging techniques. We discovered that individuals from deprived areas experienced more severe health complications, reported worse quality of life, and required more specialist care. However, their clinical outcomes were not significantly different. This underscores that socioeconomic deprivation affects health recovery, underlining the need for tailored care for these individuals. Our findings emphasise the importance of considering socioeconomic factors in recovery plans post-COVID-19, potentially improving healthcare for those in deprived areas.
