OBJECTIVE: Evaluate clinical outcome of early cyclic intravenous pamidronate treatment in children with moderate-to-severe osteogenesis imperfecta (OI), commenced before three years of age.METHODS: A retrospective review of 17 patients with moderate-to-severe OI. Development, anthropometry, fracture history, bone mineral density (BMD) and biochemistry were collected at baseline, 12 and 24 months.RESULTS: Four had OI type I, eleven had type III, one OI-FKBP10 type and one OI type V. Mean age at start of pamidronate was 14 ± 11 months. Pamidronate ranged from 6 to 12 mg/kg/year. No adverse reaction apart from fever and vomiting was noted. Long bone fracture decreased from a mean of 10.4/year to 1.2/year after 12 months and 1.4/year after 24 months (p = 0.02). Lumbar spine age- and height-matched BMD Z-scores increased (p < 0.005). Sixteen with vertebral compression fractures at baseline all showed improved vertebral shape (p < 0.001). Concavity index, likewise, improved (p < 0.005). Motor milestones compared to historical data show earlier attainment in rolling over, crawling, pulling to stand and walking independently but not sitting.CONCLUSION: Cyclic intravenous pamidronate, started under 3 years of age in children with moderate-to-severe OI, was well tolerated and associated with an increase in lumbar spine BMD, reduced fracture frequency, vertebral remodelling and attainment of motor milestones at an earlier age.
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Background: A new selective preventive spinal immobilization (PSI) protocol was introduced in the Netherlands. This may have led to an increase in non-immobilized spinal fractures (NISFs) and consequently adverse patient outcomes. Aim: A pilot study was conducted to describe the adverse patient outcomes in NISF of the PSI protocol change and assess the feasibility of a larger effect study. Methods: Retrospective comparative cohort pilot study including records of trauma patients with a presumed spinal injury who were presented at the emergency department of a level 2 trauma center by the emergency medical service (EMS). The pre-period 2013-2014 (strict PSI protocol), was compared to the post-period 2017-2018 (selective PSI protocol). Primary outcomes were the percentage of records with a NISF who had an adverse patient outcome such as neurological injuries and mortality before and after the protocol change. Secondary outcomes were the sample size calculation for a larger study and the feasibility of data collection. Results: 1,147 records were included; 442 pre-period, and 705 post-period. The NISF-prevalence was 10% (95% CI 7-16, n = 19) and 8% (95% CI 6-11, n = 33), respectively. In both periods, no neurological injuries or mortality due to NISF were found, by which calculating a sample size is impossible. Data collection showed to be feasible. Conclusions: No neurological injuries or mortality due to NISF were found in a strict and a selective PSI protocol. Therefore, a larger study is discouraged. Future studies should focus on which patients really profit from PSI and which patients do not.
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The childhood form of discitis was diagnosed in a 2-year-old girl and a 5-year-old boy. They presented with an antalgic posture, muscular defense and a positive Gowers sign. Characteristic symptoms of this childhood discitis form the triad: unexplained fever, increased erythrocyte sedimentation rate and symptomatic narrowing of an intervertebral space.
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We report on the calibration and testing of a fiber Bragg grating (FBG)-based 2D-shape sensing strip for real-time monitoring of the position and orientation of the human spine during gait. The strip is evaluated for its use as an input for control of an exoskeleton for patients with spinal cord injury. By measuring the torsion and bending of the back, walking movements can be reconstructed. The 3D-printed strip has nine embedded fiber Bragg gratings that are located at specific places with respect to the vertebral column. Three FBGs are placed opposite to the thoracic vertebrae T6–T9, these FBGs are sensitive for measuring the bending of the spine during the gait cycle. Torsion is measured at two locations: at thoracic vertebra, T3 and at lumbar vertebra, L3. At these locations, the width of the strip is reduced to have a larger sensitivity for torsion. The strain at each FBG is measured using an interrogator. This leads to the radius of curvature and torsion as a function of time. The Frenet-Serret formulae are used to calculate the shape of the strip during the gait cycle. We have calibrated this FBG strip for curvature by bending it at known radius of different curvatures. We found a linear dependence between the strain and curvature. For torsion calibration we have rotated the strip with a stepper motor at different angles and monitored the strain. We, again, found a linear dependence with a small hysteresis. We mounted the strip on a healthy test subject and monitored their gait cycle. The FBG strip shows similar results when compared to a motion capture system based on multiple cameras. Although the fixation of the strip to a garment or on the back directly strongly influences the measured response, it does show a periodic and reproducible signal during the gait cycle.
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INTRODUCTION: In patients with cancer, low muscle mass has been associated with a higher risk of fatigue, poorer treatment outcomes, and mortality. To determine body composition with computed tomography (CT), measuring the muscle quantity at the level of lumbar 3 (L3) is suggested. However, in patients with cancer, CT imaging of the L3 level is not always available. Thus far, little is known about the extent to which other vertebra levels could be useful for measuring muscle status. In this study, we aimed to assess the correlation of the muscle quantity and quality between any vertebra level and L3 level in patients with various tumor localizations.METHODS: Two hundred-twenty Positron Emission Tomography (PET)-CT images of patients with four different tumor localizations were included: 1. head and neck ( n = 34), 2. esophagus ( n = 45), 3. lung ( n = 54), and 4. melanoma ( n = 87). From the whole body scan, 24 slices were used, i.e., one for each vertebra level. Two examiners contoured the muscles independently. After contouring, muscle quantity was estimated by calculating skeletal muscle area (SMA) and skeletal muscle index (SMI). Muscle quality was assessed by calculating muscle radiation attenuation (MRA). Pearson correlation coefficient was used to determine whether the other vertebra levels correlate with L3 level. RESULTS: For SMA, strong correlations were found between C1-C3 and L3, and C7-L5 and L3 ( r = 0.72-0.95). For SMI, strong correlations were found between the levels C1-C2, C7-T5, T7-L5, and L3 ( r = 0.70-0.93), respectively. For MRA, strong correlations were found between T1-L5 and L3 ( r = 0.71-0.95). DISCUSSION: For muscle quantity, the correlations between the cervical, thoracic, and lumbar levels are good, except for the cervical levels in patients with esophageal cancer. For muscle quality, the correlations between the other levels and L3 are good, except for the cervical levels in patients with melanoma. If visualization of L3 on the CT scan is absent, the other thoracic and lumbar vertebra levels could serve as a proxy to measure muscle quantity and quality in patients with head and neck, esophageal, lung cancer, and melanoma, whereas the cervical levels may be less reliable as a proxy in some patient groups.
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Rationale: Patients with cancer of the upper gastrointestinal tract or lung are more likely to present with malnutrition at diagnosis than, for instance, patients with melanoma. Low muscle mass is an indicator of malnutrition and can be determined by computed tomography (CT) analysis of the skeletal muscle index (SMI) at the 3rd lumbar vertebra (L3) level. However, CT images at L3 are not always available. At each vertebra level, we determined if type of cancer, i.e., head and neck cancer (HNC), oesophageal cancer (OC) or lung cancer (LC) vs. melanoma (ME) was associated with lower SMI. Methods: CT images from adult patients with HNC, OC, LC or ME were included and analyzed. Scans were performed in the patient’s initial staging after diagnosis. MIM software version 7.0.1 was used to contour the muscle areas for all vertebra levels. Skeletal muscle area was corrected for stature to calculate SMI (cm2/m2). We tested for the association of HNC, OC, or LC diagnosis vs ME with SMI by univariate and multivariate linear regression analyses. In the multivariate analyses, age (years), sex, and body mass index (BMI; kg/m2) were included. Betas (B;95%CI) were calculated and statistical significance was set at p
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BACKGROUND: In critically ill patients, muscle loss is associated with adverse outcomes. Raw bioelectrical impedance analysis (BIA) parameters (eg, phase angle [PA] and impedance ratio [IR]) have received attention as potential markers of muscularity, nutrition status, and clinical outcomes. Our objective was to test whether PA and IR could be used to assess low muscularity and predict clinical outcomes.METHODS: Patients (≥18 years) having an abdominal computed tomography (CT) scan and admitted to intensive care underwent multifrequency BIA within 72 hours of scan. CT scans were landmarked at the third lumbar vertebra and analyzed for skeletal muscle cross-sectional area (CSA). CSA ≤170 cm(2) for males and ≤110 cm(2) for females defined low muscularity. The relationship between PA (and IR) and CT muscle CSA was evaluated using multivariate regression and included adjustments for age, sex, body mass index, Charlson Comorbidity Index, and admission type. PA and IR were also evaluated for predicting discharge status using dual-energy X-ray absorptiometry-derived cut-points for low fat-free mass index.RESULTS: Of 171 potentially eligible patients, 71 had BIA and CT scans within 72 hours. Area under the receiver operating characteristic (c-index) curve to predict CT-defined low muscularity was 0.67 (P ≤ .05) for both PA and IR. With covariates added to logistic regression models, PA and IR c-indexes were 0.78 and 0.76 (P < .05), respectively. Low PA and high IR predicted time to live ICU discharge.CONCLUSION: Our study highlights the potential utility of PA and IR as markers to identify patients with low muscularity who may benefit from early and rigorous intervention.
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Background: Manual muscle mass assessment based on Computed Tomography (CT) scans is recognized as a good marker for malnutrition, sarcopenia, and adverse outcomes. However, manual muscle mass analysis is cumbersome and time consuming. An accurate fully automated method is needed. In this study, we evaluate if manual psoas annotation can be substituted by a fully automatic deep learning-based method.Methods: This study included a cohort of 583 patients with severe aortic valve stenosis planned to undergo Transcatheter Aortic Valve Replacement (TAVR). Psoas muscle area was annotated manually on the CT scan at the height of lumbar vertebra 3 (L3). The deep learning-based method mimics this approach by first determining the L3 level and subsequently segmenting the psoas at that level. The fully automatic approach was evaluated as well as segmentation and slice selection, using average bias 95% limits of agreement, Intraclass Correlation Coefficient (ICC) and within-subject Coefficient of Variation (CV). To evaluate performance of the slice selection visual inspection was performed. To evaluate segmentation Dice index was computed between the manual and automatic segmentations (0 = no overlap, 1 = perfect overlap).Results: Included patients had a mean age of 81 ± 6 and 45% was female. The fully automatic method showed a bias and limits of agreement of -0.69 [-6.60 to 5.23] cm2, an ICC of 0.78 [95% CI: 0.74-0.82] and a within-subject CV of 11.2% [95% CI: 10.2-12.2]. For slice selection, 84% of the selections were on the same vertebra between methods, bias and limits of agreement was 3.4 [-24.5 to 31.4] mm. The Dice index for segmentation was 0.93 ± 0.04, bias and limits of agreement was -0.55 [1.71-2.80] cm2.Conclusion: Fully automatic assessment of psoas muscle area demonstrates accurate performance at the L3 level in CT images. It is a reliable tool that offers great opportunities for analysis in large scale studies and in clinical applications.
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OBJECTIVES: Assessment of malnutrition-related muscle depletion with computed tomography (CT) using skeletal muscle index (SMI) and muscle radiation attenuation (MRA) at the third lumbar vertebra is well validated. However, SMI and MRA values at other vertebral locations and interchangeability as parameters in different types of cancer are less known. We aimed to investigate whether adult patients with different types of cancer show differences in SMI and MRA at all vertebral levels.METHODS: We retrospectively analyzed CT images from 203 patients:120 with head and neck cancer, esophageal cancer, or lung cancer (HNC/EC/LC) and 83 with melanoma (ME). Univariate and multivariate linear regression analyses determined the association between SMI (cm²/m 2) and MRA (Hounsfield units) and cancer type at each vertebral level (significance corrected for multiple tests, P ≤ 0.002). The multivariate analyses included age, sex, cancer stage, comorbidity, CT protocol, and body mass index (BMI) (MRA analyses). RESULTS: SMI was lower in the HNC/EC/LC group versus the ME group at all vertebral levels, except C4 through C6 in the multivariate analyses. Female sex was associated with lower SMI at almost all levels. MRA was similar at most vertebral levels in both cancer groups but was lower at C1 through C4, T7, and L5 in the multivariate analyses. Use of contrast fluid and BMI were associated with higher MRA at all vertebral levels except T8 to T9 and C1 to C2, respectively.CONCLUSIONS: SMI, but not MRA, was lower in HNC/EC/LC patients than in ME patients at most vertebral levels. This indicates that low muscle mass presents itself across the various vertebral muscle areas. MRA may less consistently mark muscle depletion in malnourished patients.
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