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Objectives To assess the ability of quantitative T2, diffusion tensor imaging (DTI) and radiologist’s scores to detect muscle changes following acute muscle tear in soccer and rugby players. To assess the ability of these parameters to predict return to play times. Methods In this prospective, longitudinal study, 13 male athletes (age 19 to 34 years; mean 25 years) underwent MRI within 1 week of suffering acute muscle tear. Imaging included measurements of T2 and DTI parameters. Images were also assessed using modified Peetrons and British athletics muscle injury classification (BAMIC) scores. Participants returned for a second scan within 1 week of being determined fit to return to play. MRI measurements were compared between visits. Pearson’s correlation between visit 1 measurements and return to play times was assessed. Results There were significant differences between visits in BAMIC scores (Z = − 2.088; p = 0.037), modified Peetrons (Z = − 2.530; p = 0.011) and quantitative MRI measurements; T2, 13.12 ms (95% CI, 4.82 ms, 21.42 ms; p = 0.01); mean diffusivity (0.22 (0.04, 0.39); p = 0.02) and fractional anisotropy (0.07 (0.01, 0.14); p = 0.03). BAMIC scores showed a significant correlation with return to play time (Rs = 0.64; p = 0.02), but modified Peetrons scores and quantitative parameters did not. Conclusions T2 and DTI measurements in muscle can detect changes due to healing following muscle tear. Although BAMIC scores correlated well with return to play times, in this small study, quantitative MRI values did not, suggesting that T2 and DTI measurements are inferior predictors of return to play time compared with visual scoring. Key Points • Muscle changes following acute muscle tear can be measured using T2 and diffusion measurements on MRI. • Measurements of T2 and diffusion using MRI are not as good as a radiologist’s visual report at predicting return to play time after acute muscle tear.

Background The aim of this study was to explore the feasibility of using a non-absorbable biocompatible polyester patch to augment open repair of massive rotator cuff tears (Patch group) and compare outcomes with other treatment options (Non-patch group). Methods Participants referred to orthopaedic clinics for rotator cuff surgery were recruited. Choice of intervention (Patch or Non-patch) was based on patient preference and intra-operative findings. Oxford Shoulder Score (OSS), Shoulder Pain and Disability Index (SPADI), and Constant score were completed at baseline and 6 months. Shoulder MRI was performed at baseline and 6 months to assess fat fraction and Goutallier classification pre- and post- treatment. Feasibility outcomes (including retention, consent and missing data) were assessed. Results Sixty-eight participants (29 in the Patch group, 39 in Non-patch group) were included (mean age 65.3 years). Conversion to consent (92.6%), missing data (0% at baseline), and attrition rate (16%) were deemed successful feasibility endpoints. There was significant improvement in the Patch group compared to Non-patch at 6 months in OSS (difference in medians 9.76 (95% CI 2.25, 17.29) and SPADI: 22.97 (95% CI 3.02, 42.92), with no substantive differences in Constant score. The patch group had a higher proportion of participants improving greater than MCID for OSS (78% vs 62%) and SPADI (63% vs 50%) respectively. Analysis of the 48 paired MRIs demonstrated a slight increase in the fat fraction for supraspinatus (53 to 55%), and infraspinatus (26 to 29%) at 6 months. These differences were similar and in the same direction when the participants were analysed by treatment group. The Goutallier score remained the same or worsened one grade in both groups equally. Conclusions This study indicates that a definitive clinical trial investigating the use of a non-absorbable patch to augment repair of massive rotator cuff tears is feasible. In such patients, the patch has the potential to improve shoulder symptoms at 6 months. Trial registration ISRCTN, ISRCTN79844053, Registered 15th October 2014 (retrospectively registered).

OBJECTIVE To confirm the presence of subclinical cardiovascular dysfunction in working-age adults with type 2 diabetes (T2D) and determine whether this is improved by a low-energy meal replacement diet (MRP) or exercise training. RESEARCH DESIGN AND METHODS This article reports on a prospective, randomized, open-label, blinded end point trial with nested case-control study. Asymptomatic younger adults with T2D were randomized 1:1:1 to a 12-week intervention of 1) routine care, 2) supervised aerobic exercise training, or 3) a low-energy (∼810 kcal/day) MRP. Participants underwent echocardiography, cardiopulmonary exercise testing, and cardiac magnetic resonance (CMR) at baseline and 12 weeks. The primary outcome was change in left ventricular (LV) peak early diastolic strain rate (PEDSR) as measured by CMR. Healthy volunteers were enrolled for baseline case-control comparison. RESULTS Eighty-seven participants with T2D (age 51 ± 7 years, HbA1c 7.3 ± 1.1%) and 36 matched control participants were included. At baseline, those with T2D had evidence of diastolic dysfunction (PEDSR 1.01 ± 0.19 vs. 1.10 ± 0.16 s−1, P = 0.02) compared with control participants. Seventy-six participants with T2D completed the trial (30 routine care, 22 exercise, and 24 MRP). The MRP arm lost 13 kg in weight and had improved blood pressure, glycemia, LV mass/volume, and aortic stiffness. The exercise arm had negligible weight loss but increased exercise capacity. PEDSR increased in the exercise arm versus routine care (β = 0.132, P = 0.002) but did not improve with the MRP (β = 0.016, P = 0.731). CONCLUSIONS In asymptomatic working-age adults with T2D, exercise training improved diastolic function. Despite beneficial effects of weight loss on glycemic control, concentric LV remodeling, and aortic stiffness, a low-energy MRP did not improve diastolic function.

Background Skeletal muscles undergo changes with ageing which can cause sarcopenia that can result in frailty. Quantitative MRI may detect the muscle-deficit component of frailty which could help improve the understanding of ageing muscles. Aims To investigate whether quantitative MRI measures of T2, fat fraction (FF), diffusion tensor imaging and muscle volume can detect differences within the muscles between three age groups, and to assess how these measures compare with frailty index, gait speed and muscle power. Methods 18 ‘young’ (18–30 years), 18 ‘middle-aged’ (31–68 years) and 18 ‘older’ (> 69 years) healthy participants were recruited. Participants had an MRI of their dominant thigh. Knee extension and flexion power and handgrip strength were measured. Frailty (English Longitudinal Study of Ageing frailty index) and gait speed were measured in the older participants. Results Young participants had a lower muscle MRI T2, FF and mean diffusivity than middle-aged and older participants; middle-aged participants had lower values than older participants. Young participants had greater muscle flexion and extension power, muscle volume and stronger hand grip than middle-aged and older participants; middle-aged participants had greater values than the older participants. Quantitative MRI measurements correlated with frailty index, gait speed, grip strength and muscle power. Discussion Quantitative MRI and strength measurements can detect muscle differences due to ageing. Older participants had raised T2, FF and mean diffusivity and lower muscle volume, grip strength and muscle power. Conclusions Quantitative MRI measurements correlate with frailty and muscle function and could be used for identifying differences across age groups within muscle.

Background: There is a high prevalence of asymptomatic (American Heart Association Stage B) heart failure (SBHF) in people with type 2 diabetes (T2D). We aimed to identify associations between clinical characteristics and markers of SBHF in adults with T2D, which may allow therapeutic interventions prior to symptom onset. Methods: Adults with T2D from a multi-ethnic population with no prevalent cardiovascular disease [ n = 247, age 52 ± 12 years, glycated haemoglobin A1c (HbA1c) 7.4 ± 1.1% (57 ± 12 mmol/mol), duration of diabetes 61 (32, 120) months] underwent echocardiography and adenosine stress perfusion cardiovascular magnetic resonance imaging. Multivariable linear regression analyses were performed to identify independent associations between clinical characteristics and markers of SBHF. Results: In a series of multivariable linear regression models containing age, sex, ethnicity, smoking history, number of glucose-lowering agents, systolic blood pressure (BP) duration of diabetes, body mass index (BMI), HbA1c, serum creatinine, and low-density lipoprotein (LDL)-cholesterol, independent associations with: left ventricular mass:volume were age (β = 0.024), number of glucose-lowering agents (β = 0.022) and systolic BP (β = 0.027); global longitudinal strain were never smoking (β = −1.196), systolic BP (β = 0.328), and BMI (β = −0.348); myocardial perfusion reserve were age (β = −0.364) and male sex (β = 0.458); and aortic distensibility were age (β = −0.629) and systolic BP (β = −0.348). HbA1c was not independently associated with any marker of SBHF. Conclusions: In asymptomatic adults with T2D, age, systolic BP, BMI, and smoking history, but not glycaemic control, are the major determinants of SBHF. Given BP and BMI are modifiable, these may be important targets to reduce the development of symptomatic heart failure.

Background The determinants of exercise capacity in people with type 2 diabetes (T2D), a group at high risk of heart failure, are unknown. Purpose To assess the relationship between subclinical cardiovascular dysfunction and peak VO2 in adults with T2D. Methods We enrolled asymptomatic adults with T2D and no prevalent cardiovascular disease. Matched controls were recruited for comparison. Subjects underwent echocardiography, cardiopulmonary exercise testing and adenosine stress cardiac MRI. Multivariable linear regression analysis was undertaken to identify independent associations between measures of cardiovascular structure and function and peak VO2 (Figure 1). Results 247 adults with T2D (age 52±12y, 55% males, A1c 7.4±1.1%) and 78 controls were included. Subjects with T2D had increased concentric LV remodelling (LV mass/volume 0.84±0.14 vs. 0.76±0.11g/mL, p Conclusions In asymptomatic people with T2D, aortic stiffening, diastolic filling, and myocardial perfusion reserve are key determinants of peak VO2, independent of age, sex, ethnicity, smoking status, or blood pressure. Figure 1 Funding Acknowledgement Type of funding source: Public Institution(s). Main funding source(s): National Institute for Health Research - Career Development Fellowship (G P McCann, CDF-2014-07-045). British Heart Foundation - Clinical Research Training Fellowship (G S Gulsin)

OBJECTIVE To assess the relationship between subclinical cardiac dysfunction and aerobic exercise capacity (peak VO2) in adults with type 2 diabetes (T2D), a group at high risk of developing heart failure. RESEARCH DESIGN AND METHODS Cross-sectional study. We prospectively enrolled a multiethnic cohort of asymptomatic adults with T2D and no history, signs, or symptoms of cardiovascular disease. Age-, sex-, and ethnicity-matched control subjects were recruited for comparison. Participants underwent bioanthropometric profiling, cardiopulmonary exercise testing, and cardiovascular magnetic resonance with adenosine stress perfusion imaging. Multivariable linear regression analysis was undertaken to identify independent associations between measures of cardiovascular structure and function and peak VO2. RESULTS A total of 247 adults with T2D (aged 51.8 ± 11.9 years, 55% males, 37% black or south Asian ethnicity, HbA1c 7.4 ± 1.1% [57 ± 12 mmol/mol], and duration of diabetes 61 [32–120] months) and 78 control subjects were included. Subjects with T2D had increased concentric left ventricular remodeling, reduced myocardial perfusion reserve (MPR), and markedly lower aerobic exercise capacity (peak VO2 18.0 ± 6.6 vs. 27.8 ± 9.0 mL/kg/min; P < 0.001) compared with control subjects. In a multivariable linear regression model containing age, sex, ethnicity, smoking status, and systolic blood pressure, only MPR (β = 0.822; P = 0.006) and left ventricular diastolic filling pressure (E/e′) (β = −0.388; P = 0.001) were independently associated with peak VO2 in subjects with T2D. CONCLUSIONS In a multiethnic cohort of asymptomatic people with T2D, MPR and diastolic function are key determinants of aerobic exercise capacity, independent of age, sex, ethnicity, smoking status, or blood pressure.

Objective: This study aimed to assess the feasibility of extracellular volume-fraction (ECV) measurement, and time to achieve contrast equilibrium (CE), in healthy muscles, and to determine whether in-flow and partial-volume errors in the femoral artery affect measurements, and if there are differences in the partition coefficient (λ) between muscles. Methods: T1 was measured in the biceps femoris, vastus intermedius, femoral artery and aorta of 10 healthy participants. This was repeated alternately between the thigh and aorta for ≥25 min following a bolus of gadoterate meglumine. λ was calculated for each muscle/blood measurement. Time to CE was assessed semi-quantitatively. Results: 8/10 participants achieved CE. Time to CE = 19±2 min (mean ± 95% confidence interval). Measured λ: biceps femoris/aorta = 0.210±0.034, vastus intermedius/aorta = 0.165±0.015, biceps femoris/femoral artery = 0.265±0.054, vastus intermedius/femoral artery = 0.211±0.026. There were significant differences in λ between the muscles when using the same vessel (p < 0.05), and between λ calculated in the same muscle when using different vessels (p < 0.05). Conclusion: ECV measurements in the thigh are clinically feasible. The use of the femoral artery for the blood measurement is associated with small but significant differences in λ. ECV measurements are sensitive to differences between muscles within the healthy thigh. Advances in knowledge: This paper determines the time to contrast equilibrium in the healthy thigh and describes a method for measuring accurately ECV in skeletal muscle. This can aid in the diagnosis and understanding of inflammatory auto-immune diseases.

Background Myositis is an autoimmune disease which can cause a decrease in quality of life and increased mortality, presenting with muscle weakness, raised muscle enzymes and myalgia. Diagnosis is reliant on subjective clinical examinations, blood tests, conventional MRI and invasive muscle biopsies. Quantitative T2 MRI offers a non-invasive measurement of muscle oedema which could help improve the understanding of muscle pathology and potentially inform diagnosis. The aim of this study was to evaluate whether quantitative T2 MRI of muscles is sensitive enough to detect differences in myositis patients compared to healthy controls, and how it compares with current radiologist scoring methods. Methods 16 myositis patients were recruited (10/16 female, 10 polymyositis, 6 dermatomyositis, mean age 50 ± 26), median CK 1000IU/L ± 3100IU/L, and 16 age and gender matched healthy controls were recruited. MRI of the dominant thigh were performed. Imaging was performed using a fat-suppressed turbo-spin echo sequence. Quantitative T2 measurements were obtained from regions of interest (ROI) drawn manually within the individual muscles that make up the quadriceps and hamstrings with no distinction made between affected and unaffected muscles. A mono-exponential fit was used to obtain an estimate of the T2 from each ROI. Two radiologists blinded to the diagnosis, semi-quantitatively scored by consensus the muscles on a 4-point visual scale as either no oedema (0), mild oedema (1), moderate oedema (2) or severe oedema (3). Muscle strength was assessed using an isokinetic dynamometer. Results T2 values were higher in myositis patients compared to healthy controls [mean (SD) hamstring myositis 47.8ms (7.7ms), healthy 39.9ms (1.5ms), p < 0.001; quadriceps myositis 53.8ms (12.1ms), healthy 42.1ms (2.1ms), p < 0.001]. Quantitative T2 correlated with the radiologists’ oedema scores with rs=0.7 in the hamstrings (p < 0.001) and rs=0.6 in the quadriceps (p < 0.001), with an upward trend in T2 as radiologist scored visible oedema increased. Patients who had been classified as normal by the radiologists were compared with matched healthy controls (n = 8), T2 values for patients with ‘normal muscle’ were still higher than those for healthy controls: mean T2 in the hamstrings (myositis 42.2ms, healthy controls 38.7ms, p = 0.004); mean T2 in the quadriceps (myositis 43.9ms, healthy controls 40.1ms, p = 0.001). T2 was inversely correlated with muscle strength in all participants. Conclusion Quantitative T2 measurements can detect muscle differences between myositis patients and healthy control groups, which suggests that this measurement could be used as an objective method to monitor muscles. They are also sensitive to differences that may not be detected by radiologists. This suggests that subtle systemic changes in muscle in myositis patients, which go undetected in semi-quantitative visual scoring, can be detected using quantitative T2 measurements. This shows the potential for T2 measurements to be a diagnostic measure in the diagnosis and management of myositis. Disclosures M. Farrow None. J. Biglands None. A. Grainger None. E. Hensor None. P. O'Connor None. A. Ladas None. S. Tanner None. A. Aslam None. P. Emery None. A. Tan None.

Background Rheumatoid arthritis (RA) can present with the loss of muscle mass and a decrease in strength and functional capability. Quantitative MRI offers a non-invasive measurement of muscle status which could improve the understanding of muscle pathology in RA. The purpose of this study was to assess whether MRI-based measurements of T2, fat fraction (FF), diffusion tensor imaging and muscle volume can detect differences between the muscles of RA patients and healthy controls in the thigh; and to assess how different stages of the disease present differently. Methods 39 RA patients were recruited, comprised of 3 groups: 13 newly diagnosed treatment naïve (Group 1 - New RA: 10/13 female, mean age 63 years, mean CRP 31.5, mean EMS 71 minutes), 13 in clinical remission DAS28 3.2 ± raised CRP/ESR ± DMARD/targeted therapy escalation ± requiring steroid therapy (Group 3 - Resistant RA: 10/13 female, mean age 65, mean CRP 17.4, mean disease 123 months, mean EMS 63 minutes). 13 healthy controls were also recruited. All 4 groups were age and gender matched. MRI of the dominant thigh was performed using a STEAM-EPI imaging sequence to assess diffusion: mean diffusivity (MD) and fractional anisotropy (FA), 2-point Dixon imaging to assess FF and a fat-suppressed turbo-spin echo sequence to measure T2. All participants had knee extension/flexion and grip strength torque measured using isokinetic dynamometer. Results A one-way ANOVA analysis demonstrated significant differences in T2, FF and muscle volume between RA patients and healthy controls, but no difference in MD or FA. There was no significant difference between the RA groups. T2 and FF were higher in RA patients whilst muscle volume was lower. Muscle volume was significantly correlated with early morning stiffness (rs = 0.4, p = 0.001), DAS28 (rs = 0.4, p = 0.001) and grip strength (rs = 0.5, p < 0.001). All RA patients showed weaker strength compared to the healthy controls. Although the patients in remission (group 2) had better results compared to New (group 1) and Resistant RA patients (group 3), they performed worse than the healthy controls in all strength assessments. Conclusion Quantitative MRI can detect changes in the muscles of RA patients, whether they are newly diagnosed, in remission or with persistently active disease. Difference in T2, FF and muscle volume were apparent even at diagnosis, suggesting muscle changes in RA occur early. Despite effective RA therapy, patients in remission show worse MRI parameters and strength compared to healthy individuals. These warrant attention in improving the muscle strength and quality throughout the spectrum of the RA continuum. Disclosures M. Farrow: None. J. Biglands: None. S. Tanner: None. E. Hensor: None. M. Buch: None. P. Emery: None. A. Tan: None.

Objectives RA patients often present with low muscle mass and decreased strength. Quantitative MRI offers a non-invasive measurement of muscle status. This study assessed whether MRI-based measurements of T2, fat fraction, diffusion tensor imaging and muscle volume can detect differences between the thigh muscles of RA patients and healthy controls, and assessed the muscle phenotype of different disease stages. Methods Thirty-nine RA patients (13 ‘new RA’—newly diagnosed, treatment naïve, 13 ‘active RA’—persistent DAS28 >3.2 for >1 year, 13 ‘remission RA’—persistent DAS28 1 year) and 13 age and gender directly matched healthy controls had an MRI scan of their dominant thigh. All participants had knee extension and flexion torque and grip strength measured. Results MRI T2 and fat fraction were higher in the three groups of RA patients compared with healthy controls in the thigh muscles. There were no clinically meaningful differences in the mean diffusivity. The muscle volume, handgrip strength, knee extension and flexion were lower in all three groups of RA patients compared with healthy controls. Conclusion Quantitative MRI and muscle strength measurements can potentially detect differences within the muscles between RA patients and healthy controls. These differences may be seen in RA patients who are yet to start treatment, those with persistent active disease, and those who were in clinical remission. This suggests that the muscles in RA patients are affected in the early stages of the disease and that signs of muscle pathology and muscle weakness are still observed in clinical remission.

Objectives: To assess the test–retest variability of both diffusion parameters and fat fraction (FF) estimates in normal muscle, and to assess differences in normal values between muscles in the thigh. Methods: 29 healthy volunteers (mean age 37 years, range 20–60 years, 17/29 males) completed the study. Magnetic resonance images of the mid-thigh were acquired using a stimulated echo acquisition mode-echoplanar imaging (STEAM-EPI) imaging sequence, to assess diffusion, and 2-point Dixon imaging, to assess FF. Imaging was repeated in 19 participants after a 30 min interval in order to assess test–retest variability of the measurements. Results: Intraclass correlation coefficients (ICCs) for test–retest variability were 0.99 [95% confidence interval, (CI): 0.98, 1] for FF, 0.94 (95% CI: 0.84, 0.97) for mean diffusivity and 0.89 (95% CI: 0.74, 0.96) for fractional anisotropy (FA). FF was higher in the hamstrings than the quadriceps by a mean difference of 1.81% (95% CI:1.63, 2.00)%, p < 0.001. Mean diffusivity was significantly lower in the hamstrings than the quadriceps (0.26 (0.13, 0.39) x10-3 mm2s−1, p < 0.001) whereas fractional anisotropy was significantly higher in the hamstrings relative to the quadriceps with a mean difference of 0.063 (0.05, 0.07), p < 0.001. Conclusions: This study has shown excellent test-retest, variability in MR-based FF and diffusion measurements and demonstrated significant differences in these measures between hamstrings and quadriceps in the healthy thigh. Advances in knowledge: Test–retest variability is excellent for STEAM-EPI diffusion and 2-point Dixon-based FF measurements in the healthy muscle. Inter- and intraobserver variability were excellent for region of interest placement for STEAM-EPI diffusion and 2-point Dixon-based FF measurements in the healthy muscle. There are significant differences in FF and diffusion measurements between the hamstrings and quadriceps in the normal muscle.

Purpose To compare methods designed to minimize or correct signal nonlinearity in quantitative myocardial dynamic contrast-enhanced (DCE) MRI. Methods DCE-MRI studies were simulated and data acquired in eight volunteers. Signal nonlinearity was corrected using either a dual-bolus approach or model-based correction using proton-density weighted imaging (conventional or dual-sequence acquisition) or T1 data (native or bookend). Scanning of healthy and infarcted myocardium at 3 T was simulated, including noise, saturation imperfection and T1 measurement error. Data were analyzed using model-based deconvolution with a one-compartment (mono-exponential) model. Results Substantial variation between methods was demonstrated in volunteers. In simulations the dual-bolus method proved stable for realistic levels of saturation efficiency but demonstrated bias due to residual nonlinearity. Model-based methods performed ideally in the absence of confounding error sources and were generally robust to noise or saturation imperfection, except for native T1 based correction which was highly sensitive to the latter. All methods demonstrated large variation in accuracy above an over-saturation level where baseline signal was nulled. For the dual-sequence approach this caused substantial bias at the saturation efficiencies observed in volunteers. Conclusion The choice of nonlinearity correction method in myocardial DCE-MRI impacts on accuracy and precision of estimated parameters, particularly in the presence of nonideal saturation

AIM To assess whether magnetic resonance imaging (MRI)-based measurements of T2, fat fraction, diffusion tensor imaging, and muscle volume can detect differences between the muscles of myositis patients and healthy controls, and to identify how they compare with semi-quantitative MRI diagnosis. MATERIALS AND METHODS Sixteen myositis patients and 16 age- and gender-matched healthy controls underwent MRI of their thigh. Quantitative MRI measurements and radiologists' semi-quantitative scores were assessed. Strength was assessed using an isokinetic dynamometer. RESULTS: Fat fraction and T2 values were higher in myositis patients whereas muscle volume was lower compared to healthy controls. There was no difference in diffusion. Muscle strength was lower in myositis patients compared to healthy controls. In a subgroup of eight patients, scored as unaffected by radiologists, T2 values were still significantly higher in myositis patients. CONCLUSIONS Quantitative MRI measurements can detect differences between myositis patients and healthy controls. Changes in the muscles of myositis patients, undetected by visual, semi-quantitative scoring, can be detected using quantitative T2 measurements. This suggests that MRI T2 values may be useful for the management of myositis patients.

Background:Peripheral myositis in systemic sclerosis (SSc) is associated with poor prognosis and myocarditis1but non-inflammatory myopathy, which also represents a significant cause of disability in SSc remains poorly understood. Cardiovascular magnetic resonance (CMR) T1 mapping studies in asymptomatic SSc patients show increased extracellular volume (ECV), suggestive of diffuse fibrosis in both the myocardium and thoracic muscle2.Objectives:To evaluate the feasibility of T1 mapping MRI and determine ECV in peripheral muscle of SSc patients with and without myopathy and explore the association between cardiac and peripheral muscle T1 mapping in SSc.Methods:This was a hypothesis-generating pilot and feasibility study. SSc patients, fulfilling the 2013 ACR/EULAR criteria, with no cardiovascular disease or myositis but either minimal muscle symptoms (non-inflammatory myopathy) or no muscle involvement and healthy volunteers (HV) underwent peripheral muscle T1 mapping-MRI for native T1 and extracellular volume (ECV) quantification of the dominant thigh. Patients also had T1 mapping CMR, and creatine-kinase (CK) measured. Non-inflammatory myopathy was defined as current/history of minimally raised CK (Results:12 SSc patients and 10 HV were recruited. SSc patients had a median (IQR) age of 52 (41,65) years, 9/12 had limited cutaneous SSc, 4/12 interstitial lung disease, 7/12 non-inflammatory myopathy. Higher skeletal muscle ECV was recorded in SSc patients compared to HV [mean (SD) 23(11)%, vs 11(4)% p=0.04]. Skeletal muscle native T1 values were comparable between the 2 groups although modestly higher in SSc patients [mean (SD) 1396ms (56) vs 1387ms (42)] (Figure 1A).Peripheral muscle ECV associated with CK (R2=0.307, rho=0.554, p=0.061) and was higher in SSc patients with evidence of myopathy compared to those with no myopathy [28 (10)% vs 15 (5)%, p=0.023] (Figure 1B). An ECV of 22% was determined to best identify myopathy with a sensitivity of 71% and a specificity of 80%.SSc patients had raised myocardial ECV and native T1 with means (SD) of 31 (3) % and 1287 (54) ms respectively (normal reference range ECV ≤29%, native T1 ≤1240ms). No clear association between myocardial and peripheral muscle ECV (rho=-0.485) or between myocardial ECV and peripheral muscle native T1 (rho=0.470) of SSc patients was observed.Conclusion:This pilot study to determine ECV-MRI of the peripheral muscle showed higher ECV in SSc patients compared to HV, suggesting the presence of diffuse fibrosis in the peripheral muscle of SSc patients. These data support further investigation to understand the pathophysiological involvement and relationship of peripheral and cardiac muscle in SSc.References:[1]Follansbee WP et al, Am Heart J. 1993[2]Barison A et al, Eur Heart J Cardiovasc Imaging. 2015Disclosure of Interests:Raluca-Bianca Dumitru: None declared, Alex Goodall: None declared, David Broadbent: None declared, Ananth Kidambi: None declared, Sven Plein: None declared, Francesco Del Galdo: None declared, Ai Lyn Tan: None declared, John Biglands: None declared, Maya H Buch Grant/research support from: Pfizer, Roche, and UCB, Consultant of: Pfizer; AbbVie; Eli Lilly; Gilead Sciences, Inc.; Merck-Serono; Sandoz; and Sanofi

Background:As well as joint damage, rheumatoid arthritis (RA) is also associated with altered body composition known as rheumatoid cachexia (RC). RC is characterised by reduced skeletal muscle and increased (white) fat mass and decreased strength. RC is associated with increased disease severity and disability (1). It is unknown at what stage muscle involvement begins in RA, and if the muscle damage is modifiable when patients achieve disease control.Quantitative MRI (qMRI) can measure the biomarkers associated with RC. MRI T2 is sensitive to fluid related to physiological changes at the molecular level, and is regarded as an indirect measure of muscle inflammation (2). MRI muscle fat fraction (FF) measurements are useful for identifying myosteatosis (3).Objectives:To obtain preliminary estimates of the extent to which muscle imaging phenotype differs between RA and healthy controls (HC); and to describe the RA phenotype at different levels of disease activity.Methods:39 RA patients (comprising three groups) and 13 age and gender directly matched HC had a MRI scan of their dominant thigh. The RA groups were:[1]13 ‘New RA’ - newly diagnosed, treatment naïve[2]13 ‘Active RA’ - diagnosed >1 year, persistent DAS28 >3.2 for >1 year[3]13 ‘Remission RA’ - diagnosed >1 year, persistent DAS28 1 yearMR images of the mid-thigh were acquired using Dixon imaging to assess FF and a fat-suppressed multi-echo spin-echo to measure T2. Regions of interest were drawn around the quadriceps and hamstrings. All participants had knee extension and flexion torque measured on an isokinetic dynamometer, and isometric dynamometer to measure grip strength. One-Way ANOVA with Dunnett’s post-hoc analysis provided preliminary indication of potential differences between T2, FF, muscle volume and strength measurements between the disease stages.Results:39 RA patients were recruited: 13 new RA (mean age [years] 63 ± 15, DAS28 5.2 ± 3), 13 active RA (mean age [years] 65 ± 10, DAS28 4.8 ± 3), 13 remission RA (mean age [years] 67 ± 19, DAS28 1.7 ± 0.7) and also 13 HC. T2 and FF were higher in RA patients compared to HC (fig. 1). Within the hamstrings for T2, the mean differences between HC versus new, active and remission patients were 4.5ms (95% CI 2.5, 6.4; p3(95% CI -751, -283; p3(95% CI -605, -136; p=0.001), and -312.3cm3(95% CI -546. -77; p=0.006) respectively (fig. 2). Knee flexion/extension and handgrip strength were lower in all 3 groups of RA patients compared to HC. For knee flexion, the mean differences between HC versus new, active and remission patients were 18.4Nm (95% CI -35, -1; p=0.03), 10.1Nm (95% CI -27, 7; p=0.3), and 13.3Nm (95% CI -33, 0; p=0.1) respectively.Figure 1.Quantitative T2 and FF MRI of RA patients and healthy controlsConclusion:This pilot study suggests muscle health may be adversely affected in RA patients compared to matched HC. Our results suggest that muscle changes occur in the earliest stages of RA and persist throughout the disease duration, even in clinical remission. If confirmed, these data imply the need for adjunctive muscle intervention to current RA treatment strategies in order to improve patient outcomes.References:[1]Giles JT, et al. Arthritis Care & Research. 2008[2]Maillard SM, et al. Rheumatology (Oxford, England). 2004[3]Grimm A, et al. The Journal of Frailty & Aging. 2018.Figure 2.MRI muscle volume in RA patients and healthy controlsDisclosure of Interests:Matt Farrow: None declared, John Biglands: None declared, Steven Tanner: None declared, Elizabeth Hensor: None declared, Maya H Buch Grant/research support from: Pfizer, Roche, and UCB, Consultant of: Pfizer; AbbVie; Eli Lilly; Gilead Sciences, Inc.; Merck-Serono; Sandoz; and Sanofi, Paul Emery Grant/research support from: AbbVie, Bristol-Myers Squibb, Merck Sharp & Dohme, Pfizer, Roche (all paid to employer), Consultant of: AbbVie (consultant, clinical trials, advisor), Bristol-Myers Squibb (consultant, clinical trials, advisor), Lilly (clinical trials, advisor), Merck Sharp & Dohme (consultant, clinical trials, advisor), Novartis (consultant, clinical trials, advisor), Pfizer (consultant, clinical trials, advisor), Roche (consultant, clinical trials, advisor), Samsung (clinical trials, advisor), Sandoz (clinical trials, advisor), UCB (consultant, clinical trials, advisor), Ai Lyn Tan: None declared

OBJECTIVES: To screen for significant arrhythmias with an implantable loop recorder (ILR) in patients with SSc and no known cardiovascular disease, and identify associated disease phenotype, blood and cardiovascular magnetic resonance (CMR) biomarkers.METHODS: Twenty patients with SSc with no history of primary SSc heart disease, traditional cardiovascular disease, diabetes or maximum one traditional cardiovascular risk factor underwent clinical assessment, contrast-enhanced CMR and ILR insertion.RESULTS: ILR data were available for 19 patients: 63% female, mean (s.d.) age of 53 (12) years, 32% diffuse SSc. Eight patients had significant arrhythmias over 3 years: one complete heart block, two non-sustained ventricular tachycardia [all three dcSSc, two anti-topoisomerase antibodies (Scl70) positive, three interstitial lung disease and two previous digital ulceration] and five atrial arrhythmias of which four were with limited SSc. These required interventions with one permanent pacemaker implantation, four anti-arrhythmic pharmacotherapy, one anticoagulation.Patients with significant arrhythmia had higher baseline high-sensitivity troponin I and N-terminal pro-brain natriuretic peptide [mean difference (95% CI) 117 (-11, 245) and 92 (-30, 215) ng/l, respectively], and CMR-extracellular volume [mean (s.d.) 32 (2) vs 29 (4)%]. Late gadolinium enhancement was observed in five patients, only one with significant arrhythmia.CONCLUSION: This first ILR study identified potentially life-threatening arrhythmias in asymptomatic SSc patients attributable to a primary SSc heart disease. Disease phenotype, CMR-extracellular volume (indicating diffuse fibrosis) and cardiac biomarkers may identify at-risk patients that would benefit from ILR screening. Future studies can inform a risk model and provide insights into SSc-associated arrhythmia pathogenesis.

Objectives This study sought to compare the diagnostic accuracy of visual and quantitative analyses of myocardial perfusion cardiovascular magnetic resonance against a reference standard of quantitative coronary angiography. Background Visual analysis of perfusion cardiovascular magnetic resonance studies for assessing myocardial perfusion has been shown to have high diagnostic accuracy for coronary artery disease. However, only a few small studies have assessed the diagnostic accuracy of quantitative myocardial perfusion. Methods This retrospective study included 128 patients randomly selected from the CE-MARC (Clinical Evaluation of Magnetic Resonance Imaging in Coronary Heart Disease) study population such that the distribution of risk factors and disease status was proportionate to the full population. Visual analysis results of cardiovascular magnetic resonance perfusion images, by consensus of 2 expert readers, were taken from the original study reports. Quantitative myocardial blood flow estimates were obtained using Fermi-constrained deconvolution. The reference standard for myocardial ischemia was a quantitative coronary x-ray angiogram stenosis severity of ≥70% diameter in any coronary artery of >2 mm diameter, or ≥50% in the left main stem. Diagnostic performance was calculated using receiver-operating characteristic curve analysis. Results The area under the curve for visual analysis was 0.88 (95% confidence interval: 0.81 to 0.95) with a sensitivity of 81.0% (95% confidence interval: 69.1% to 92.8%) and specificity of 86.0% (95% confidence interval: 78.7% to 93.4%). For quantitative stress myocardial blood flow the area under the curve was 0.89 (95% confidence interval: 0.83 to 0.96) with a sensitivity of 87.5% (95% confidence interval: 77.3% to 97.7%) and specificity of 84.5% (95% confidence interval: 76.8% to 92.3%). There was no statistically significant difference between the diagnostic performance of quantitative and visual analyses (p = 0.72). Incorporating rest myocardial blood flow values to generate a myocardial perfusion reserve did not significantly increase the quantitative analysis area under the curve (p = 0.79). Conclusions Quantitative perfusion has a high diagnostic accuracy for detecting coronary artery disease but is not superior to visual analysis. The incorporation of rest perfusion imaging does not improve diagnostic accuracy in quantitative perfusion analysis.

To compare the diagnostic performance of four tracer kinetic analysis methods to quantify myocardial perfusion from magnetic resonance (MR) imaging cardiac perfusion data sets in terms of their ability to lead to the diagnosis of myocardial ischemia.The study was approved by the regional ethics committee, and all patients gave written consent. A representative sample of 50 patients with suspected ischemic heart disease was retrospectively selected from the Clinical Evaluation of Magnetic Resonance Imaging in Coronary Heart Disease trial data set. Quantitative myocardial blood flow (MBF) was estimated from rest and adenosine stress MR imaging perfusion data sets by using four established methods. A matching diagnosis of both an inducible defect as assessed with single photon emission computed tomography and a luminal stenosis of 70% or more as assessed with quantitative x-ray angiography was used as the reference standard for the presence of myocardial ischemia. Diagnostic performance was evaluated with receiver operating characteristic (ROC) curve analysis for each method, with stress MBF and myocardial perfusion reserve (MPR) serving as continuous measures.Area under the ROC curve with stress MBF and MPR as the outcome measures, respectively, was 0.86 and 0.92 for the Fermi model, 0.85 and 0.87 for the uptake model, 0.85 and 0.80 for the one-compartment model, and 0.87 and 0.87 for model-independent deconvolution. There was no significant difference between any of the models or between MBF and MPR, except that the Fermi model outperformed the one-compartment model if MPR was used as the outcome measure (P = .02).Diagnostic performance of quantitative myocardial perfusion estimates is not affected by the tracer kinetic analysis method used.

To determine if myocardial perfusion cardiac magnetic resonance (MR) imaging can show changes in myocardial blood flow (MBF) during the cold pressor test (CPT) and can allow identification of the differing endothelial function of smokers and nonsmokers when compared during adenosine stress.The study was approved by the institutional ethics review board and all participants gave informed written consent. Twenty-nine healthy volunteers (19 nonsmokers, 10 smokers; mean age ± standard deviation, 22 years ± 4) underwent 1.5-T MR imaging and analysis. Myocardial perfusion was assessed during rest, peak CPT, and adenosine hyperemia with a saturation-recovery gradient-echo pulse sequence (spatial resolution, 2.4 × 2.4 × 10 mm). Global, endocardial, and epicardial MBF were calculated by using Fermi-constrained deconvolution. Paired and independent t test statistical analyses were used to compare the responses between tests and groups. Regression analysis was performed to identify predictors of MBF change.MBF at rest was similar between the nonsmoking and smoking groups (0.97 mL/g/min ± 0.4 vs 0.96 mL/g/min ± 0.3, respectively; P = .96). Nonsmokers responded to CPT with a 47% increase in MBF (1.43 mL/g/min ± 0.5) and smokers responded with a 27% increase (1.22 mL/g/min ± 0.4; P.001). An endocardial-to-epicardial gradient existed at rest (nonsmokers, 1.10 [P = .002]; smokers, 1.30 [P = .01]) and CPT (nonsmokers, 1.19 [P.001] smokers, 1.28 [P = .04]) but reversed during adenosine stress (nonsmokers, 0.89 [P = .03]; smokers, 0.92 [P = .42]).Myocardial perfusion cardiac MR imaging during CPT can allow assessment of changes in MBF globally and in the separate myocardial layers in healthy smokers and nonsmokers. This allows the combined assessment of endothelium-dependent (CPT) and endothelium-independent (adenosine stress test) MBF reserve in a single study.

This study sought to compare the diagnostic accuracy of visual and quantitative analyses of myocardial perfusion cardiovascular magnetic resonance against a reference standard of quantitative coronary angiography.Visual analysis of perfusion cardiovascular magnetic resonance studies for assessing myocardial perfusion has been shown to have high diagnostic accuracy for coronary artery disease. However, only a few small studies have assessed the diagnostic accuracy of quantitative myocardial perfusion.This retrospective study included 128 patients randomly selected from the CE-MARC (Clinical Evaluation of Magnetic Resonance Imaging in Coronary Heart Disease) study population such that the distribution of risk factors and disease status was proportionate to the full population. Visual analysis results of cardiovascular magnetic resonance perfusion images, by consensus of 2 expert readers, were taken from the original study reports. Quantitative myocardial blood flow estimates were obtained using Fermi-constrained deconvolution. The reference standard for myocardial ischemia was a quantitative coronary x-ray angiogram stenosis severity of ≥70% diameter in any coronary artery of2 mm diameter, or ≥50% in the left main stem. Diagnostic performance was calculated using receiver-operating characteristic curve analysis.The area under the curve for visual analysis was 0.88 (95% confidence interval: 0.81 to 0.95) with a sensitivity of 81.0% (95% confidence interval: 69.1% to 92.8%) and specificity of 86.0% (95% confidence interval: 78.7% to 93.4%). For quantitative stress myocardial blood flow the area under the curve was 0.89 (95% confidence interval: 0.83 to 0.96) with a sensitivity of 87.5% (95% confidence interval: 77.3% to 97.7%) and specificity of 84.5% (95% confidence interval: 76.8% to 92.3%). There was no statistically significant difference between the diagnostic performance of quantitative and visual analyses (p = 0.72). Incorporating rest myocardial blood flow values to generate a myocardial perfusion reserve did not significantly increase the quantitative analysis area under the curve (p = 0.79).Quantitative perfusion has a high diagnostic accuracy for detecting coronary artery disease but is not superior to visual analysis. The incorporation of rest perfusion imaging does not improve diagnostic accuracy in quantitative perfusion analysis.

Purpose: To assess the reproducibility of semiquantitative and quantitative analysis of first-pass myocardial perfusion cardiovascular magnetic resonance (CMR) in healthy volunteers. Materials and Methods: Eleven volunteers underwent myocardial perfusion CMR during adenosine stress and rest on 2 separate days. Perfusion data were acquired in a single mid-ventricular section in two cardiac phases to permit cardiac phase reproducibility comparisons. Semiquantitative analysis was performed to derive normalized upslopes of myocardial signal intensity profiles (myocardial perfusion index, MPI). The quantitative analysis estimated absolute myocardial blood flow (MBF) using Fermi-constrained deconvolution. The perfusion reserve index was calculated by dividing stress by rest data. Two observers performed all the measurements independently. One observer repeated all first scan measurements 4 weeks later. Results: The reproducibility of perfusion CMR was highest for semiquantitative analysis with an intraobserver coefficient of variability (CoV) of 3%–7% and interobserver CoV of 4%–10%. Semiquantitative interstudy comparison was less reproducible (CoV of 13%–27%). Quantitative intraobserver CoV of 10%–18%, interobserver CoV of 8%–15% and interstudy CoV of 20%–41%. Reproducibility of systolic and diastolic phases and the endocardial and epicardial myocardial layer showed similar reproducibility on both semiquantitative and quantitative analysis. Conclusion: The reproducibility of CMR myocardial perfusion estimates is good, but varies between intraobserver, interobserver, and interstudy comparisons. In this study semiquantitative analysis was more reproducible than quantitative analysis. J. Magn. Reson. Imaging 2013;37:865–874. © 2013 Wiley Periodicals, Inc.

Respiratory motion is a significant obstacle to the use of quantitative perfusion in clinical practice. Increasingly complex motion correction algorithms are being developed to correct for respiratory motion. However, the impact of these improvements on the final diagnosis of ischemic heart disease has not been evaluated. The aim of this study was to compare the performance of four automated correction methods in terms of their impact on diagnostic accuracy. Three strategies for motion correction were used: (1) independent translation correction for all slices, (2) translation correction for the basal slice with transform propagation to the remaining two slices assuming identical motion in the remaining slices, and (3) rigid correction (translation and rotation) for the basal slice. There were no significant differences in diagnostic accuracy between the manual and automatic motion-corrected datasets ([Formula: see text]). The area under the curve values for manual motion correction and automatic motion correction were 0.93 and 0.92, respectively. All of the automated motion correction methods achieved a comparable diagnostic accuracy to manual correction. This suggests that the simplest automated motion correction method (method 2 with translation transform for basal location and transform propagation to the remaining slices) is a sufficiently complex motion correction method for use in quantitative myocardial perfusion.

This study aims to quantify subendocardial and subepicardial myocardial blood flow (MBF) from dynamic contrast-enhanced MRI and to compare semi-quantitative and quantitative analysis methods. 17 healthy volunteers (9 males, mean age 34 ± 8) were scanned during adenosine stress and at rest. A “semi-quantitative” myocardial perfusion index (MPI) was calculated based on maximal upslopes of signal intensity-time profiles for a mid-ventricular myocardial slice. In addition, absolute MBF (ml/g/min) was estimated using Fermi-constrained deconvolution. On semi-quantitative analysis, the ratio of subendocardial to subepicardial MPI was 0.98 ± 0.1 at stress and 1.16 ± 0.09 at rest, P < 0.0001. The MPRI (i.e. the ratio of stress over rest MPI) for the subendocardium was 1.54 ± 0.3 versus 1.81 ± 0.35 for the subepicardium, P = 0.03. For quantitative analysis, the ratio of subendocardial to subepicardial MBF was 0.91 ± 0.11 at stress versus 1.17 ± 0.16 at rest, P < 0.0001. The subendocardial MBF reserve was also lower than in the subepicardium (2.6 ± 0.75 vs. 3.32 ± 0.93, P = 0.027). In conclusion, semi-quantitative and quantitative analysis of dynamic contrast-enhanced MRI shows higher subendocardial blood flow at rest and reduced subendocardial perfusion reserve compared to the subepicardium.

Quantitative analysis of cardiac dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) perfusion datasets is dependent on the drawing (manually or automatically) of myocardial contours. The required accuracy of these contours for myocardial blood flow (MBF) estimation is not well understood. This study investigates the relationship between myocardial contour errors and MBF errors. Myocardial contours were manually drawn on DCE-MRI perfusion datasets of healthy volunteers imaged in systole. Systematic and random contour errors were simulated using spline curves and the resulting errors in MBF were calculated. The degree of contour error was also evaluated by two recognized segmentation metrics. We derived contour error tolerances in terms of the maximum deviation (MD) a contour could deviate radially from the 'true' contour expressed as a fraction of each volunteer's mean myocardial width (MW). Significant MBF errors were avoided by setting tolerances of MD ≤ 0.4 MW, when considering the whole myocardium, MD ≤ 0.3 MW, when considering six radial segments, and MD ≤ 0.2 MW for further subdivision into endo- and epicardial regions, with the exception of the anteroseptal region, which required greater accuracy. None of the considered segmentation metrics correlated with MBF error; thus, both segmentation metrics and MBF errors should be used to evaluate contouring algorithms.

Myocardial blood flow varies during the cardiac cycle in response to pulsatile changes in epicardial circulation and cyclical variation in myocardial tension. First-pass assessment of myocardial perfusion by dynamic contrast-enhanced MRI is one of the most challenging applications of MRI because of the spatial and temporal constraints imposed by the cardiac physiology and the nature of dynamic contrast-enhanced MRI signal collection. Here, we describe a dynamic contrast-enhanced MRI method for simultaneous assessment of systolic and diastolic myocardial blood flow. The feasibility of this method was demonstrated in a study of 17 healthy volunteers at rest and under adenosine-induced vasodilatory stress. We found that myocardial blood flow was independent of the cardiac phase at rest. However, under adenosine-induced hyperemia, myocardial blood flow and myocardial perfusion reserve were significantly higher in diastole than in systole. Furthermore, the transmural distribution of myocardial blood flow and myocardial perfusion reserve was cardiac phase dependent, with a reversal of the typical subendocardial to subepicardial myocardial blood flow gradient in systole, but not diastole, under stress. The observed difference between systolic and diastolic myocardial blood flow must be taken into account when assessing myocardial blood flow using dynamic contrast-enhanced MRI. Furthermore, targeted assessment of systolic or diastolic perfusion using dynamic contrast-enhanced MRI may provide novel insights into the pathophysiology of ischemic and microvascular heart disease.

Background Quantification of physiological parameters, including myocardial blood flow (MBF), by perfusion MRI relies on analysis of data that describes temporal variation of relative contrast agent concentration following bolus administration. At doses required for sufficient SNR, signal enhancement cannot be used directly as the relationship between signal intensity (SI) and the resulting concentrations in blood and myocardium is non-linear. Proposed solutions to this include separation of the AIF and myocardial data acquisition, or model based non-linearity correction.

Methods This was a retrospective study using a 128 patient subsample of patients, selected from the CE-MARC study such that the distribution of risk factors and disease status within the sample was representative of the full study population. Both visual and quantitative analysis were carried out using the AHA standardised 16 segment model. Visual analysis was part of the original CE-MARC study and was performed by 2 expert reviewers in consensus. To obtain qMBF estimates, manual contouring of the myocardium was carried out and individual qMBF estimates were obtained for each AHA segment using Fermi-constrained deconvolution. The arterial input function was taken from the left ventricular blood pool of the basal slice. Myocardial perfusion reserve values were calculated on a segment by segment basis by dividing the stress by the rest qMBF. The reference standard for myocardial ischaemia was a quantitative coronary X-ray angiogram (QCA) score of ≥70% in any of the coronary territories, or ≥50% in the left main stem. Diagnostic performance was calculated using receiver operator characteristic (ROC) curve analysis. For visual analysis the summed score from all AHA segments was used as the diagnostic measure. For quantitative analysis the minimum MPR value from the AHA segments was used. A DeLong, DeLong, ClarkePearson analysis was performed to test for a statistically significant difference in the area under the curve (AUC) values between visual and quantitative analysis.

Aims Type 2 diabetes mellitus is an independent risk factor for the development of heart failure. To better understand the mechanism by which this occurs, we investigated cardiac structure, function, and perfusion in patients with and without diabetes. Methods and results Sixty-five patients with no stenosis >30% on invasive coronary angiography were categorized into diabetes (19) and non-diabetes (46) which was further categorized into prediabetes (30) and controls (16) according to the American Diabetes Association guidelines. Each patient underwent comprehensive cardiovascular magnetic resonance assessment. Left-ventricular (LV) mass, relative wall mass (RWM), Lagrangian circumferential strain, LV torsion, and myocardial perfusion reserve (MPR) were calculated. LV mass was higher in diabetics than non-diabetics (112.8 ± 39.7 vs. 91.5 ± 21.3 g, P = 0.01) and in diabetics than prediabetics (112.8 ± 39.7 vs. 90.3 ± 18.7 g, P = 0.02). LV torsion angle was higher in diabetics than non-diabetics (9.65 ± 1.90 vs. 8.59 ± 1.91°, P = 0.047), and MPR was lower in diabetics than non-diabetics (2.10 ± 0.76 vs. 2.84 ± 1.25 mL/g/min, P = 0.01). There was significant correlation between MPR and early diastolic strain rate (r = −0.310, P = 0.01) and LV torsion (r = −0.306, P = 0.01). In multivariable linear regression analysis, non-diabetics waist–hip ratio, but not body mass index, had a significant association with RWM (Beta = 0.34, P = 0.02). Conclusion Patients with diabetes have increased LV mass, LV torsion, and decreased MPR. There is a significant association between decreased MPR and increased LV torsion suggesting a possible mechanistic link between microvascular disease and cardiac dysfunction in diabetes.

Background Intramyocardial hemorrhage (IMH) identified by cardiovascular magnetic resonance (CMR) is an established prognostic marker following acute myocardial infarction (AMI). Detection of IMH by T2-weighted or T2 star CMR can be limited by long breath hold times and sensitivity to artefacts, especially at 3T. We compared the image quality and diagnostic ability of susceptibility-weighted magnetic resonance imaging (SW MRI) with T2-weighted and T2 star CMR to detect IMH at 3T. Methods Forty-nine patients (42 males; mean age 58 years, range 35–76) underwent 3T cardiovascular magnetic resonance (CMR) 2 days following re-perfused AMI. T2-weighted, T2 star and SW MRI images were obtained. Signal and contrast measurements were compared between the three methods and diagnostic accuracy of SW MRI was assessed against T2w images by 2 independent, blinded observers. Image quality was rated on a 4-point scale from 1 (unusable) to 4 (excellent). Results Of 49 patients, IMH was detected in 20 (41%) by SW MRI, 21 (43%) by T2-weighted and 17 (34%) by T2 star imaging (p = ns). Compared to T2-weighted imaging, SW MRI had sensitivity of 93% and specificity of 86%. SW MRI had similar inter-observer reliability to T2-weighted imaging (κ = 0.90 and κ = 0.88 respectively); both had higher reliability than T2 star (κ = 0.53). Breath hold times were shorter for SW MRI (4 seconds vs. 16 seconds) with improved image quality rating (3.8 ± 0.4, 3.3 ± 1.0, 2.8 ± 1.1 respectively; p

Background The human interaction required for manual motion correction/contouring of cardiac perfusion series remains a significant obstacle to quantitative perfusion gaining a wider acceptance in clinical practice. The use of image registration for motion correction in perfusion data offers a considerable time saving. Numerous registration methods have been proposed, with evaluation limited to the image registration accuracy. However, the important clinical question is how do these methods affect diagnosis? The aim of this study is to evaluate perfusion series registration in terms of its affect on the diagnostic accuracy of myocardial ischaemia.

Background Type 2 Diabetes Mellitus (T2DM) and prediabetes are associated with an increased cardiovascular risk and heart failure independent of the presence of obstructive coronary artery disease, caused in part by myocardial microvascular dysfunction. Recent studies have reported contractile dysfunction and increased rotation with the onset of diabetic cardiomyopathy in uncomplicated T2DM patients. Independently, higher resting myocardial blood flow (MBF) has been reported in T2DM. The objective of this study was to determine whether there is a correlation between LV Epicardial Rotation (LV ER) and resting MBF in T2DM patients with angiographically normal coronaries, measured by tissue tagging and perfusion cardiovascular Magnetic Resonance (CMR). Methods Sixty five patients with no coronary stenosis >30% on invasive angiography were recruited and categorized into T2DM, prediabetes and normal controls groups according to American Diabetes Association guidelines. All patients underwent rest and adenosine stress myocardial perfusion CMR at a single mid-LV location, cine imaging covering the entire heart and myocardial tissue tagging in three LV short axis locations (apical, mid LV and basal). LV volumes and mass were calculated from cine images. LV rotation in three myocardial layers (endocardial, midmyocardial and epicardial) was calculated from CSPAMM tissue images using Tag Track (Gyrotools, Zurich). For this study, only rest MBF was calculated using Fermi-constrained deconvolution for the entire myocardium. Results Patient characteristics and results are shown in Table 1. Patients with T2DM had significantly higher resting MBF than the two other groups. Corresponding mid LV ER was higher in T2DM patients compared to patients with prediabetes and normal controls (Figure 1) (not statistically significant). Univariate analysis showed a significant positive correlation between MBF and LV ER in the entire study population (Pearson coefficient (r) of 0.25, p = 0.05). In the individual groups, the linear determination coefficient (R2) showed that LV ER in T2DM patients had stronger positive correlation (R2 = 0.31) with resting MBF than in patients with prediabetes (R2 = 0.16) and controls (R2 = 0.29), Figure 1. Conclusions T2DM patients when compared to age-matched patients with prediabetes and normal controls have higher peak LV ER. Resting MBF correlates with LV ER. These results suggest that LV ER analysis in uncomplicated T2DM patients may be useful for non-invasive screening of early subtle contractile dysfunction associated with microvascular dysfunction in diabetes patients.

To assess the feasibility of simultaneously measuring blood flow (Fb ), Gd-DTPA extraction fraction (E), and distribution volume (vd ) in healthy myocardium at rest and under adenosine stress using dynamic contrast-enhanced MRI.Sixteen volunteers were examined at 1.5 T and 11 returned for a repeat study. The data were analyzed using a distributed parameter (DP) 2-region model to arrive at estimates of Fb , E, blood volume, and interstitial volume. For comparison, estimates of Fb were also obtained using a Fermi function model.DP model fits were successful in 49 of the 54 data sets. Estimates obtained using DP and Fermi models did not differ for either rest Fb or myocardial perfusion reserve though DP estimates of stress Fb were lower than Fermi estimates. The repeatability of the DP parameters Fb , E, and vd was better than or equal to the repeatability of Fermi-Fb . E at rest and under stress was estimated to be 66% and 57%, respectively.The results suggest that characteristics of the microvasculature of healthy myocardium can be reliably determined using dynamic contrast-enhanced MRI at rest and under stress and that delivery of Gd-DTPA to the myocardium is not flow-limited.

To compare myocardial blood flow (MBF) at systole and diastole and determine the diagnostic accuracy of both phases in patients suspected of having coronary artery disease (CAD).The study was approved by the regional ethics committee, and all patients gave written informed consent. After coronary angiography, 40 patients (27 men; mean age, 64 years ± 8) underwent stress-rest perfusion magnetic resonance (MR) imaging at 1.5 T, with images aquired simultaneously at end systole and middiastole. Patients were classified as having CAD (stenosis .70%) or no significant CAD. In patients with CAD, myocardial segments were classified as stenosis-dependent (downstream of significant stenosis) or remote. MBF and myocardial perfusion reserve (MPR) were calculated for each segment, and mean values in each phase were compared with paired t tests. The diagnostic accuracy of each phase was determined with receiver operating characteristic (ROC) analysis.Twenty-one of the 40 patients (53%) had CAD. Resting MBF was similar in both phases for patients with and patients without CAD (P.05). Stress MBF was greater in diastole than systole in normal, remote, and stenosis-dependent segments (3.75 mL/g/min ± 1.50 vs 3.15 mL/g/min ± 1.10, respectively, for normal segments; 2.75 mL/g/min ± 1.20 vs 2.38 mL/g/min ± 0.99, respectively, for remote segments; 2.49 mL/g/min ± 1.07 vs 2.23 mL/g/min ± 0.90, respectively, for stenosis-dependent segments; P.01). MPR was greater in diastole than systole in all segment groups (P.05). The diagnostic accuracies at diastole and systole were similar (area under the ROC curve = 0.79 and 0.82, respectively; P = .30).Myocardial perfusion MR estimates of stress MBF and MPR were greater in diastole than systole in patients with and patients without CAD. However, both phases had similar diagnostic accuracy. These observations may be relevant to other dynamic perfusion methods, including computed tomography and echocardiography.

This study has shown that in patients with suspected and confirmed CAD, estimates of MBF by perfusion-CMR are significantly higher in diastole than systole during maximal hyperemic stress.

Myocardial blood flow varies during the cardiac cycle in response to pulsatile changes in epicardial circulation and cyclical variation in myocardial tension. First-pass assessment of myocardial perfusion by dynamic contrast-enhanced MRI is one of the most challenging applications of MRI because of the spatial and temporal constraints imposed by the cardiac physiology and the nature of dynamic contrast-enhanced MRI signal collection. Here, we describe a dynamic contrast-enhanced MRI method for simultaneous assessment of systolic and diastolic myocardial blood flow. The feasibility of this method was demonstrated in a study of 17 healthy volunteers at rest and under adenosine-induced vasodilatory stress. We found that myocardial blood flow was independent of the cardiac phase at rest. However, under adenosine-induced hyperemia, myocardial blood flow and myocardial perfusion reserve were significantly higher in diastole than in systole. Furthermore, the transmural distribution of myocardial blood flow and myocardial perfusion reserve was cardiac phase dependent, with a reversal of the typical subendocardial to subepicardial myocardial blood flow gradient in systole, but not diastole, under stress. The observed difference between systolic and diastolic myocardial blood flow must be taken into account when assessing myocardial blood flow using dynamic contrast-enhanced MRI. Furthermore, targeted assessment of systolic or diastolic perfusion using dynamic contrast-enhanced MRI may provide novel insights into the pathophysiology of ischemic and microvascular heart disease.

Introduction Dynamic contrast enhanced myocardial perfusion MRI (DCE-MRI) has the potential to be superior to other currently available imaging techniques for the assessment of myocardial ischaemia. Quantitative analysis of cardiac perfusion is currently not routinely carried out because of the time consuming process of manually segmenting the myocardium from large DCE-MRI datasets. A range of automated segmentation algorithms have been proposed which quote results in terms of distance error or estimated myocardial blood flow (MBF). However, the relationship between these two evaluation measures is not clear, making objective comparisons of algorithm performance difficult.

Introduction Left bundle branch block is often associated with underlying coronary artery disease (CAD) but its presence can limit the diagnostic accuracy of non-invasive imaging tests. In particular, there is a high incidence of false-positive results with exercise single-photon emission CT (SPECT) due to apparent septal perfusion defects. The use of vasodilator stress has reduced but not eliminated this problem. Several hypotheses have been postulated to explain the cause of such perfusion defects, and these include: early activation of the septum leading to shortened diastole and reduced blood flow, partial volume effects caused by impaired septal thickening, and increased septal intra-myocardial pressure during diastole resulting in reduced flow reserve. A number of small studies using positron emission tomography (PET) or early quantitative SPECT techniques have evaluated regional differences in myocardial blood flow (MBF) in patients with LBBB, but the results have been conflicting and have shown either no regional differences or a relative but not absolute reduction in septal perfusion. This study re-evaluates the unresolved question of septal perfusion in LBBB by using quantitative perfusion CMR. Methods 9 patients with LBBB and no significant CAD underwent adenosine stress/rest perfusion CMR at 1.5 T and X-ray angiography. Absence of CAD was defined as luminal stenosis Results Resting MBF was similar in both septal and lateral regions in all patients (1.27±0.26 vs 1.27±0.23 ml/g/min; p=0.95) (table 1). Stress MBF was significantly lower in septal regions compared to lateral regions in all patients (septal/lateral ratio=0.86±0.07) (table 1, figure 1). Accordingly, the mean stress MBF and mean MPR were significantly lower in the septal regions compared to lateral regions (MBF 3.99±1.03 vs 4.62±0.96 ml/g/min, p Conclusions This study is the first to use quantitative perfusion CMR to evaluate regional differences in MBF in patients with LBBB. The results suggest that although septal perfusion remains normal in LBBB, there is a genuine relative reduction in MBF during stress compared to the lateral wall. This phenomenon may account for the false positive results seen with myocardial perfusion imaging techniques and highlights a potential clinical utility of quantitative perfusion CMR.

Introduction Although differences in systolic and diastolic myocardial blood flow (MBF) estimates have been shown in healthy volunteers, the impact of cardiac phase on detecting coronary artery disease (CAD) using cardiovascular magnetic resonance (CMR) myocardial perfusion imaging is unknown. The aim of this study was to compare MBF estimates in systole and diastole in patients with suspected CAD and determine if either phase has greater diagnostic accuracy. Methods Following invasive coronary angiography, 40 patients (68% men, 64±8 yrs) underwent stress/rest perfusion-CMR (1.5T Philips) which was acquired at mid-systole and end-diastole simultaneously. Based on angiographic stenosis >70% (quantitative coronary angiography), patients were grouped as having “CAD” or “no CAD.” In patients with CAD, myocardial segments were classified as “stenosis-dependent” (downstream of a significant stenosis) or “remote.” For each segment, MBF (Fermi-constrained deconvolution) and myocardial perfusion reserve (MPR) were calculated. The diagnostic accuracy of each phase was determined with receiver operator characteristic analysis. Results 21 patients (53%) had CAD. A typical example of a patient with ischaemia is shown in Abstract 085 figure 1. Resting MBF was similar in the two cardiac phases for both normal and CAD patients (all p values >0.05). MBF at stress was greater in diastole than systole in normal, remote and stenosis-dependent segments (3.75±1.5 vs 3.15±1.1 ml/g/min; 2.75±1.20 vs 2.38±0.99 ml/g/min; 2.49±1.07 vs 2.23±0.90 ml/g/min; all p values Conclusion Estimates of stress MBF and MPR by perfusion-CMR in this study were greater in diastole than systole in normal and CAD patients. Although the diagnostic accuracy of both phases was similar, the MPR cut-off values were different. These observations are relevant to any form of dynamic myocardial perfusion assessment and are of particular importance to promising developments in 3D perfusion-CMR and CT perfusion imaging where the acquisition phase may be specifically chosen. Different estimates of MBF and different MPR cut-off values between phases mean a universal standard needs to be agreed for 3D acquisitions.

Background Diagnostic studies using dynamic contrast enhanced (DCE) MRI perfusion imaging typically evaluate perfusion in terms of the myocardial perfusion reserve (MPR), which is the ratio of stress to rest myocardial blood flow (MBF) measurements. The aim of this study was to establish whether or not, in the case of absolute MBF quantitation, the MPR exhibits a diagnostic advantage over the stress MBF measurements alone.