MRI in multiple myeloma : a pictorial review of diagnostic and post-treatment findings

Magnetic resonance imaging (MRI) is increasingly being used in the diagnostic work-up of patients with multiple myeloma. Since 2014, MRI findings are included in the new diagnostic criteria proposed by the International Myeloma Working Group. Patients with smouldering myeloma presenting with more than one unequivocal focal lesion in the bone marrow on MRI are considered having symptomatic myeloma requiring treatment, regardless of the presence of lytic bone lesions. However, bone marrow evaluation with MRI offers more than only morphological information regarding the detection of focal lesions in patients with MM. The overall performance of MRI is enhanced by applying dynamic contrast-enhanced MRI and diffusion weighted imaging sequences, providing additional functional information on bone marrow vascularization and cellularity. This pictorial review provides an overview of the most important imaging findings in patients with monoclonal gammopathy of undetermined significance, smouldering myeloma and multiple myeloma, by performing a 'total' MRI investigation with implications for the diagnosis, staging and response assessment. Main message aEuro cent Conventional MRI diagnoses multiple myeloma by assessing the infiltration pattern. aEuro cent Dynamic contrast-enhanced MRI diagnoses multiple myeloma by assessing vascularization and perfusion. aEuro cent Diffusion weighted imaging evaluates bone marrow composition and cellularity in multiple myeloma. aEuro cent Combined morphological and functional MRI provides optimal bone marrow assessment for staging. aEuro cent Combined morphological and functional MRI is of considerable value in treatment follow-up

Proportional lumbar spine inter-vertebral motion patterns: a comparison of patients with chronic, non-specific low back pain and healthy controls

Introduction: Identifying biomechanical subgroups in chronic, non-specific low back pain (CNSLBP) populations from inter-vertebral displacements has proven elusive. Quantitative fluoroscopy (QF) has excellent repeatability and provides continuous standardised inter-vertebral kinematic data from fluoroscopic sequences allowing assessment of mid-range motion. The aim of this study was to determine whether proportional continuous IV rotational patterns were different in patients and controls. A secondary aim was to update the repeatability of QF measurement of range of motion (RoM) for inter-vertebral (IV) rotation

Large Asymmetric Hypertrophy of Rectus Abdominis Muscle in Professional Tennis Players

Purpose: To determine the volume and degree of asymmetry of the musculus rectus abdominis (RA) in professional tennis players. Methods: The volume of the RA was determined using magnetic resonance imaging (MRI) in 8 professional male tennis players and 6 non-active male control subjects. Results: Tennis players had 58 % greater RA volume than controls (P = 0.01), due to hypertrophy of both the dominant (34% greater volume, P = 0.02) and non-dominant (82 % greater volume, P = 0.01) sides, after accounting for age, the length of the RA muscle and body mass index (BMI) as covariates. In tennis players, there was a marked asymmetry in the development of the RA, which volume was 35 % greater in the non-dominant compared to the dominant side (P,0.001). In contrast, no sideto-side difference in RA volume was observed in the controls (P = 0.75). The degree of side-to-side asymmetry increased linearly from the first lumbar disc to the pubic symphysis (r = 0.97, P,0.001). Conclusions: Professional tennis is associated with marked hypertrophy of the musculus rectus abdominis, which achieves a volume that is 58 % greater than in non-active controls. Rectus abdominis hypertrophy is more marked in the non-dominant than in the dominant side, particularly in the more distal regions. Our study supports the concept that humans can differentially recruit both rectus abdominis but also the upper and lower regions of each muscle. It remains to b

Biomechanical evaluation of predictive parameters of progression in adolescent isthmic spondylolisthesis: a computer modeling and simulation study

<p>Abstract</p> <p>Background</p> <p>Pelvic incidence, sacral slope and slip percentage have been shown to be important predicting factors for assessing the risk of progression of low- and high-grade spondylolisthesis. Biomechanical factors, which affect the stress distribution and the mechanisms involved in the vertebral slippage, may also influence the risk of progression, but they are still not well known. The objective was to biomechanically evaluate how geometric sacral parameters influence shear and normal stress at the lumbosacral junction in spondylolisthesis.</p> <p>Methods</p> <p>A finite element model of a low-grade L5-S1 spondylolisthesis was constructed, including the morphology of the spine, pelvis and rib cage based on measurements from biplanar radiographs of a patient. Variations provided on this model aimed to study the effects on low grade spondylolisthesis as well as reproduce high grade spondylolisthesis. Normal and shear stresses at the lumbosacral junction were analyzed under various pelvic incidences, sacral slopes and slip percentages. Their influence on progression risk was statistically analyzed using a one-way analysis of variance.</p> <p>Results</p> <p>Stresses were mainly concentrated on the growth plate of S1, on the intervertebral disc of L5-S1, and ahead the sacral dome for low grade spondylolisthesis. For high grade spondylolisthesis, more important compression and shear stresses were seen in the anterior part of the growth plate and disc as compared to the lateral and posterior areas. Stress magnitudes over this area increased with slip percentage, sacral slope and pelvic incidence. Strong correlations were found between pelvic incidence and the resulting compression and shear stresses in the growth plate and intervertebral disc at the L5-S1 junction.</p> <p>Conclusions</p> <p>Progression of the slippage is mostly affected by a movement and an increase of stresses at the lumbosacral junction in accordance with spino-pelvic parameters. The statistical results provide evidence that pelvic incidence is a predictive parameter to determine progression in isthmic spondylolisthesis.</p

Convalescent plasma in patients admitted to hospital with COVID-19 (RECOVERY): a randomised controlled, open-label, platform trial

Background: Many patients with COVID-19 have been treated with plasma containing anti-SARS-CoV-2 antibodies. We aimed to evaluate the safety and efficacy of convalescent plasma therapy in patients admitted to hospital with COVID-19. Methods: This randomised, controlled, open-label, platform trial (Randomised Evaluation of COVID-19 Therapy [RECOVERY]) is assessing several possible treatments in patients hospitalised with COVID-19 in the UK. The trial is underway at 177 NHS hospitals from across the UK. Eligible and consenting patients were randomly assigned (1:1) to receive either usual care alone (usual care group) or usual care plus high-titre convalescent plasma (convalescent plasma group). The primary outcome was 28-day mortality, analysed on an intention-to-treat basis. The trial is registered with ISRCTN, 50189673, and ClinicalTrials.gov, NCT04381936. Findings: Between May 28, 2020, and Jan 15, 2021, 11558 (71%) of 16287 patients enrolled in RECOVERY were eligible to receive convalescent plasma and were assigned to either the convalescent plasma group or the usual care group. There was no significant difference in 28-day mortality between the two groups: 1399 (24%) of 5795 patients in the convalescent plasma group and 1408 (24%) of 5763 patients in the usual care group died within 28 days (rate ratio 1·00, 95% CI 0·93–1·07; p=0·95). The 28-day mortality rate ratio was similar in all prespecified subgroups of patients, including in those patients without detectable SARS-CoV-2 antibodies at randomisation. Allocation to convalescent plasma had no significant effect on the proportion of patients discharged from hospital within 28 days (3832 [66%] patients in the convalescent plasma group vs 3822 [66%] patients in the usual care group; rate ratio 0·99, 95% CI 0·94–1·03; p=0·57). Among those not on invasive mechanical ventilation at randomisation, there was no significant difference in the proportion of patients meeting the composite endpoint of progression to invasive mechanical ventilation or death (1568 [29%] of 5493 patients in the convalescent plasma group vs 1568 [29%] of 5448 patients in the usual care group; rate ratio 0·99, 95% CI 0·93–1·05; p=0·79). Interpretation: In patients hospitalised with COVID-19, high-titre convalescent plasma did not improve survival or other prespecified clinical outcomes. Funding: UK Research and Innovation (Medical Research Council) and National Institute of Health Research

Big data in public transportation: a review of sources and methods

The collection of big data, as an alternative to traditional resource-intensive manual data collection approaches, has become significantly more feasible over the past decade. The availability of such data, coupled with more sophisticated predictive statistical techniques, has contributed to an increase in attention towards the application of these data, particularly for transportation analysis. Within the transportation literature, there is a growing emphasis on developing sources of commonly collected public transportation data into more powerful analytical tools. A commonly held belief is that application of big data to transportation problems will yield new insights previously unattainable through traditional transportation data sets. However, there exist many ambiguities related to what constitutes big data, the ethical implications of big data collection and application, and how to best utilize the emerging data sets. The existing literature exploring big data provides no clear and consistent definition. While the collection of big data has grown and its application in both research and practice continues to expand, there is a significant disparity between methods of analysis applied to such data. This paper summarizes the recent literature on sources of big data and commonly applied methods used in its application to public transportation problems. We assess predominant big data sources, most frequently studied topics, and methodologies employed. The literature suggests smart card and automated data are the two big data sources most frequently used by researchers to conduct public transit analyses. The studies reviewed indicate that big data has largely been used to understand transit users’ travel behavior and to assess public transit service quality. The techniques reported in the literature largely mirror those used with smaller data sets. The application of more advanced statistical methods, commonly associated with big data, has been limited to a small number of studies. In order to fully capture the value of big data, new approaches to analysis will be necessary

Shared-use mobility competition: a trip-level analysis of taxi, bikeshare, and transit mode choice in Washington, DC

The emergence of new shared-use mobility options such as bikeshare and ride-hailing services render the traditional dichotomy between personal vehicles and public transit somewhat irrelevant. Transportation planners and policymakers have yet to conclude whether these mobility technologies are complementing or competing against existing public transit services. The understanding of this relationship is vital given the increasing uncertainty of funding sources for transit services, but limited by the scarcity of meaningful data provided by the private ride-hailing industry. This study applies big data analytic tools on a unique travel data set to uncover the predictors motivating a half-billion transit, taxi, and bikeshare trips in rail station walksheds across Washington, DC. Study findings indicate travel cost and natural environment factors as well as land use diversity and network connectivity metrics significantly impact the likelihood for an individual to travel via taxi or bikeshare rather than rail