Abstract:Introduction/Aims
Quantitative muscle ultrasound offers biomarkers that aid in the diagnosis, detection, and follow‐up of neuromuscular disorders. At present, quantitative muscle ultrasound methods are 2D and are often operator and device dependent. The aim of this study was to combine an existing device independent method with an automated ultrasound machine and perform 3D quantitative muscle ultrasound, providing new normative data of healthy controls.
Methods
In total, 123 healthy volunteers were included. … Show more
“…This difference is consistent with findings in healthy individuals. 5 Handgrip strength was lower in DM1 patients than in FSHD patients. This coincides with our expectations due to the known early involvement handgrip strength for DM1.…”
Section: Magnetic Resonance Imaging (Mri) Is Another Modality That Of...mentioning
confidence: 88%
“…The US volumes were processed according to our previously published method. 5 The postprocessing steps were automated except for the segmentation of muscle tissue. Segmentation was performed manually by the researcher and was performed such that the maximum amount of muscle tissue was included while excluding the fascia.…”
Introduction/AimsUltrasound imaging of muscle tissue conventionally results in two‐dimensional sampling of tissue. For heterogeneously affected muscles, a sampling error using two‐dimensional (2D) ultrasound can therefore be expected. In this study, we aimed to quantify and extend ultrasound imaging findings in neuromuscular disorders by using three‐dimensional quantitative muscle ultrasound (3D QMUS).MethodsPatients with facioscapulohumeral dystrophy (n = 31) and myotonic dystrophy type 1 (n = 16) were included in this study. After physical examination, including Medical Research Council (MRC) scores, the tibialis anterior muscle was scanned with automated ultrasound. QMUS parameters were calculated over 15 cm of the length of the tibialis anterior muscle and were compared with a healthy reference data set.ResultsWith 3D QMUS local deviations from the healthy reference could be detected. Significant Pearson correlations (P < .01) between MRC score and QMUS parameters in male patients (n = 23) included the mean echo intensity (EI) (0.684), the standard deviation of EI (0.737), and the residual attenuation (0.841). In 91% of all patients, mean EI deviated by more than 1 standard deviation from the healthy reference. In general, the proportion of muscle tissue with a Z score >1 was about 50%.DiscussionIn addition to mean EI, multiple QMUS parameters reported in this study are potential biomarkers for pathology. Besides a moderate correlation of mean EI with muscle weakness, two other parameters showed strong correlations: standard deviation of EI and residual attenuation. Local detection of abnormalities makes 3D QMUS a promising method that can be used in research and potentially for clinical evaluation.
“…This difference is consistent with findings in healthy individuals. 5 Handgrip strength was lower in DM1 patients than in FSHD patients. This coincides with our expectations due to the known early involvement handgrip strength for DM1.…”
Section: Magnetic Resonance Imaging (Mri) Is Another Modality That Of...mentioning
confidence: 88%
“…The US volumes were processed according to our previously published method. 5 The postprocessing steps were automated except for the segmentation of muscle tissue. Segmentation was performed manually by the researcher and was performed such that the maximum amount of muscle tissue was included while excluding the fascia.…”
Introduction/AimsUltrasound imaging of muscle tissue conventionally results in two‐dimensional sampling of tissue. For heterogeneously affected muscles, a sampling error using two‐dimensional (2D) ultrasound can therefore be expected. In this study, we aimed to quantify and extend ultrasound imaging findings in neuromuscular disorders by using three‐dimensional quantitative muscle ultrasound (3D QMUS).MethodsPatients with facioscapulohumeral dystrophy (n = 31) and myotonic dystrophy type 1 (n = 16) were included in this study. After physical examination, including Medical Research Council (MRC) scores, the tibialis anterior muscle was scanned with automated ultrasound. QMUS parameters were calculated over 15 cm of the length of the tibialis anterior muscle and were compared with a healthy reference data set.ResultsWith 3D QMUS local deviations from the healthy reference could be detected. Significant Pearson correlations (P < .01) between MRC score and QMUS parameters in male patients (n = 23) included the mean echo intensity (EI) (0.684), the standard deviation of EI (0.737), and the residual attenuation (0.841). In 91% of all patients, mean EI deviated by more than 1 standard deviation from the healthy reference. In general, the proportion of muscle tissue with a Z score >1 was about 50%.DiscussionIn addition to mean EI, multiple QMUS parameters reported in this study are potential biomarkers for pathology. Besides a moderate correlation of mean EI with muscle weakness, two other parameters showed strong correlations: standard deviation of EI and residual attenuation. Local detection of abnormalities makes 3D QMUS a promising method that can be used in research and potentially for clinical evaluation.
“…Fast FVUS might be suitable for quantitative muscle US (QMUS) which has been demonstrated to be a promising diagnostic and follow-up tool. In QMUS, the main measured parameter is echo intensity (EI) which depends on the image quality [1][2][3]. Acquisition with the fast FVUS can guarantee the image quality values are not impacted by the insufficient acquired data and might lead to more accurate and robust quantitative analysis.…”
Section: Discussionmentioning
confidence: 99%
“…In the past years, a variety of new applications have been developed for fast and on site stageing of disease. Quantitative US is one of them and has shown to be a promising tool for diagnosis and follow up in muscle diseases [1][2][3].…”
Free-hand volumetric ultrasound (FVUS) facilitates 3D US imaging of large anatomical areas. However, this method is user-dependent and image quality, especially in the scan direction (elevational direction), depends on the number of US images acquired per distance unit. This might affect clinical decision making for example in quantitative ultrasound muscle imaging. This study addresses three goals. First, to determine quantitatively below which number of acquisitions per cm (acq/cm) image quality is affected: the acquisition limit. Second, to determine the translation speed used naturally by sonographers. Third, to demonstrate in vivo possible benefits of utilizing plane wave imaging for FVUS, so-called fast FVUS in order to boost translation speed while maintaining quantitative image information. Fast FVUS enables imaging at much higher framerates and hence the acquisition limit is easier met which allows for much faster transducer translation. From an analysis of the contrast and elevational resolution in a phantom, the average acquisition limit was determined to be 33 acq/cm. Above this limit, the quantitative ultrasound information remained unchanged. This would imply that when imaging at 30 frames per second, a common frame-rate of current 2D ultrasound devices, suboptimal imaging quality is obtained above transducer translation speeds of 9.1 mm/s. The median and maximum transducer translation speed observed in 10 sonographers were 15.8 mm/s and 30.1 mm/s, thus above this limit. Finally, we presented a design of fast FVUS that enabled acquiring 200 fps, and hence, would allow imaging up to speeds of 60.6 mm/s. We demonstrated in vivo in tibialis anterior muscles that more anatomical details were visible with fast FVUS which were lost at the typical framerate. These observations support our hypothesis that fast FVUS would be an ideal method for 3D quantitative muscle ultrasound.
“…The Lamperti score 29 comprises a 0-15 severity scale evaluating degree of muscle weakness in 5 muscle regions separately. MVC of tibialis anterior was calculated as described by de Jong et al 49 . Finally, FSHD genetic characteristics (FSHD type and D4Z4 repeat length) and disease duration were obtained.…”
Facioscapulohumeral muscular dystrophy (FSHD) is incurable. DUX4 mis-expression is believed to underlie FSHD pathogenesis, alongside PAX7 target gene repression, yet clinical trials lack robust biomarkers of severity. FSHD entails fatty replacement of muscle, accelerated by inflammation, we thus performed RNA-sequencing on both an MRI guided inflamed (TIRM+) and non-inflamed (TIRM-) muscle biopsies from clinically-characterised FSHD patients, alongside peripheral blood mononucleated cells (PBMCs). PAX7 target gene repression in TIRM- muscle associates with severity. DUX4 target gene biomarkers associate with lower limb fat fraction and D4Z4 repeat length, but not severity. PAX7 target gene repression in muscle correlates with levels in matched PBMCs. A refined biomarker computed in PBMCs associates with severity in FSHD patients, and also validates as a classifier of severity in an independent set of 54 FSHD patient blood samples. In summary, we present a minimally-invasive, circulating, transcriptomic biomarker of FSHD clinical severity valid in muscle and blood.
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