Synthetic MRI is not yet ready for morphologic and functional assessment of patellar cartilage at 1.5 Tesla

PurposeThe purpose of this study was to compare morphologic assessment and relaxometry of patellar hyaline cartilage between conventional sequences (fast spin-echo [FSE] T2-weighted fat-saturated and T2-mapping) and synthetic T2 short-TI inversion recovery (STIR) and T2 maps at 1.5 T magnetic resonance imaging (MRI).MethodThe MRI examinations of the knee obtained at 1.5 T in 49 consecutive patients were retrospectively studied. There were 21 men and 28 women with a mean age of 45 ± 17.7 (SD) years (range: 18–88 years). Conventional and synthetic acquisitions were performed, including T2-weighted fat-saturated and T2-mapping sequences. Two radiologists independently compared patellar cartilage T2-relaxation time on conventional T2-mapping and synthetic T2-mapping images. A third radiologist evaluated the patellar cartilage morphology on conventional and synthetic T2-weighted images. The presence of artifacts was also assessed. Interobserver agreement for quantitative variables was assessed using intraclass correlation coefficient (ICC).ResultsIn vitro, conventional and synthetic T2 maps yielded similar mean T2 values 58.5 ± 2.3 (SD) ms and 58.8 ± 2.6 (SD) ms, respectively (P = 0.414) and 6% lower than the expected experimental values (P = 0.038). Synthetic images allowed for a 15% reduction in examination time compared to conventional images. On conventional sequences, patellar chondropathy was identified in 35 patients (35/49; 71%) with a mean chondropathy grade of 4.8 ± 4.8 (SD). On synthetic images, 28 patients (28/49; 57%) were diagnosed with patellar chondropathy, with a significant 14% difference (P = 0.009) and lower chondropathy scores (3.7 ± 4.9 [SD]) compared to conventional images. Motion artifacts were more frequently observed on synthetic images (18%) than on conventional ones (6%). The interobserver agreement was excellent for both conventional and synthetic T2 maps (ICC > 0.83). Mean cartilage T2 values were significantly greater on synthetic images (36.2 ± 3.8 [SD] ms; range: 29-46 ms) relative to conventional T2 maps (31.8 ± 4.1 [SD] ms; range: 26-49 ms) (P < 0.0001).ConclusionDespite a decrease in examination duration, synthetic images convey lower diagnostic performance for chondropathy, greater prevalence of motion artifacts, and an overestimation of T2 values compared to conventional MRI sequences.     

Impact of COVID-19 inequalities on children: An intersectional analysis

Societal concerns about the effects of the COVID-19 pandemic have largely focussed on the social groups most directly affected, such as the elderly and health workers. However, less focus has been placed on understanding the effects on other collectives, such as children. While children’s physical health appears to be less affected than the adult population, their mental health, learning and wellbeing is likely to have been significantly negatively affected during the pandemic due to the varying policy restrictions, such as withdrawal from face to face schooling, limited peer-to-peer interactions and mobility and increased exposure to the digital world amongst other things. Children from vulnerable social backgrounds, and especially girls, will be most negatively affected by the impact of COVID-19, given their different intersecting realities and the power structures already negatively affecting them. To strengthen the understanding of the social determinants of the COVID-19 crisis that unequally influence children’s health and wellbeing, this article presents a conceptual framework that considers the multiple axes of inequalities and power relations. This understanding can then be used to inform analyses and impact assessments, and in turn inform the development of effective and equitable mitigation strategies as well as assist to be better prepared for future pandemics.     

Magnetic resonance elastography with guided pressure waves

Magnetic resonance elastography aims to non-invasively and remotely characterize the mechanical properties of living tissues. To quantitatively and regionally map the shear viscoelastic moduli in vivo, the technique must achieve proper mechanical excitation throughout the targeted tissues. Although it is straightforward, ante manibus, in close organs such as the liver or the breast, which practitioners clinically palpate already, it is somewhat fortunately highly challenging to trick the natural protective barriers of remote organs such as the brain. So far, mechanical waves have been induced in the latter by shaking the surrounding cranial bones. Here, the skull was circumvented by guiding pressure waves inside the subject's buccal cavity so mechanical waves could propagate from within through the brainstem up to the brain. Repeatable, reproducible and robust displacement fields were recorded in phantoms and in vivo by magnetic resonance elastography with guided pressure waves such that quantitative mechanical outcomes were extracted in the human brain.     

Dose-response modeling of NLRP3 inflammasome-mediated diseases: asbestos,lung cancer,and malignant mesothelioma as examples

Abstract

Can a single fiber of amphibole asbestos increase the risk of lung cancer or malignant mesothelioma (MM)? Traditional linear no-threshold (LNT) risk assessment assumptions imply that the answer is yes: there is no safe exposure level. This paper draws on recent scientific progress in inflammation biology, especially elucidation of the activation thresholds for NLRP3 inflammasomes and resulting chronic inflammation, to model dose-response relationships for malignant mesothelioma and lung cancer risks caused by asbestos exposures. The modeling integrates a physiologically based pharmacokinetics (PBPK) front end with inflammation-driven two-stage clonal expansion (I-TSCE) models of carcinogenesis to describe how exposure leads to chronic inflammation, which in turn promotes carcinogenesis. Together, the combined PBPK and I-TSCE modeling predict that there are practical thresholds for exposure concentration below which asbestos exposure does not cause chronic inflammation in less than a lifetime, and therefore does not increase chronic inflammation-dependent cancer risks. Quantitative examples using model parameter estimates drawn from the literature suggest that practical thresholds may be within about a factor of 2 of some past exposure levels for some workers. The I-TSCE modeling framework explains previous puzzling aspects of asbestos epidemiology, such as why age at first exposure is a better predictor of lifetime MM risk than exposure duration. It may be a valuable tool for risk analysts when LNT assumptions are not justified due to inflammation response thresholds mediating dose-response relationships.     

MP2RAGEME: T1, T2*, and QSM mapping in one sequence at 7 tesla

Quantitative magnetic resonance imaging generates images of meaningful physical or chemical variables measured in physical units that allow quantitative comparisons between tissue regions and among subjects scanned at the same or different sites. Here, we show that we can acquire quantitative T₁, T₂^*, and quantitative susceptibility mapping (QSM) information in a single acquisition, using a multi‐echo (ME) extension of the second gradient‐echo image of the MP2RAGE sequence. This combination is called MP2RAGE ME, or MP2RAGEME. The simultaneous acquisition results in large time savings, perfectly coregistered data, and minimal image quality differences compared to separately acquired data. Following a correction for residual transmit B₁⁺‐sensitivity, quantitative T₁, T₂^*, and QSM values were in excellent agreement with those obtained from separately acquired, also B₁⁺‐corrected, MP2RAGE data and ME gradient echo data. The quantitative values from reference regions of interests were also in very good correspondence with literature values. From the MP2RAGEME data, we further derived a multiparametric cortical parcellation, as well as a combined arterial and venous map. In sum, our MP2RAGEME sequence has the benefit in large time savings, perfectly coregistered data and minor image quality differences.     

Temperature-controlled power modulation compensates for heterogeneous nanoparticle distributions: a computational optimization analysis for magnetic hyperthermia

Purpose: To study, with computational models, the utility of power modulation to reduce tissue temperature heterogeneity for variable nanoparticle distributions in magnetic nanoparticle hyperthermia.

Methods: Tumour and surrounding tissue were modeled by elliptical two- and three-dimensional computational phantoms having six different nanoparticle distributions. Nanoparticles were modeled as point heat sources having amplitude-dependent loss power. The total number of nanoparticles was fixed, and their spatial distribution and heat output were varied. Heat transfer was computed by solving the Pennes’ bioheat equation using finite element methods (FEM) with temperature-dependent blood perfusion. Local temperature was regulated using a proportional-integral-derivative (PID) controller. Tissue temperature, thermal dose and tissue damage were calculated. The required minimum thermal dose delivered to the tumor was kept constant, and heating power was adjusted for comparison of both the heating methods.

Results: Modulated power heating produced lower and more homogeneous temperature distributions than did constant power heating for all studied nanoparticle distributions. For a concentrated nanoparticle distribution, located off-center within the tumor, the maximum temperatures inside the tumor were 16% lower for modulated power heating when compared to constant power heating. This resulted in less damage to surrounding normal tissue. Modulated power heating reached target thermal doses up to nine-fold more rapidly when compared to constant power heating.

Conclusions: Controlling the temperature at the tumor-healthy tissue boundary by modulating the heating power of magnetic nanoparticles demonstrably compensates for a variable nanoparticle distribution to deliver effective treatment.