Original Article

Apparent diffusion coefficient (ADC) does not correlate with different serological parameters in myositis and myopathy

Acta Radiologica 0(0) 1–6 ! The Foundation Acta Radiologica 2017 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav DOI: 10.1177/0284185117731448 journals.sagepub.com/home/acr

Hans-Jonas Meyer1,2, Oliver Ziemann1, Malte Kornhuber3, Alexander Emmer3, Ulf Qua¨schling4, Stefan Schob4 and Alexey Surov2

Abstract Background: Magnetic resonance imaging (MRI) is widely used in several muscle disorders. Diffusion-weighted imaging (DWI) is an imaging modality, which can reflect microstructural tissue composition. The apparent diffusion coefficient (ADC) is used to quantify the random motion of water molecules in tissue. Purpose: To investigate ADC values in patients with myositis and non-inflammatory myopathy and to analyze possible associations between ADC and laboratory parameters in these patients. Material and Methods: Overall, 17 patients with several myositis entities, eight patients with non-inflammatory myopathies, and nine patients without muscle disorder as a control group were included in the study (mean age ¼ 55.3  14.3 years). The diagnosis was confirmed by histopathology in every case. DWI was obtained in a 1.5-T scanner using two b-values: 0 and 1000 s/mm2. In all patients, the blood sample was acquired within three days to the MRI. The following serological parameters were estimated: C-reactive protein, lactate dehydrogenase, alanine aminotransferase, aspartate aminotransferase, creatine kinase, and myoglobine. Results: The estimated mean ADC value for the myositis group was 1.89  0.37  10–3 mm2/s and for the non-inflammatory myopathy group was 1.79  0.33  10–3 mm2/s, respectively. The mean ADC values (1.15  0.37  10–3 mm2/s) were significantly higher to unaffected muscles (vs. myositis P ¼ 0.0002 and vs. myopathy P ¼ 0.0021). There were no significant correlations between serological parameters and ADC values. Conclusion: Affected muscles showed statistically significantly higher ADC values than normal muscles. No linear correlations between ADC and serological parameters were identified.

Keywords Diffusion-weighted imaging (DWI), apparent diffusion coefficient (ADC), myositis, myopathy, serological parameters, correlation Date received: 11 May 2017; accepted: 22 August 2017

Introduction Inflammatory myopathies are a heterogeneous group of diseases of unknown etiology and can be classified into the following groups: dermatomyositis; polymyositis; necrotizing autoimmune myositis; inclusion body myositis; and overlap myositis (1). The diagnostic workup is multimodal consisting of clinical history, pattern of muscle involvement, muscle enzyme levels, electromyographic findings muscle-histopathology, and certain autoantibodies (1). As an emergent imaging modality, magnetic resonance imaging (MRI) has been evaluated

1 Department of Diagnostic Radiology, Martin-Luther University HalleWittenberg, Halle, Germany 2 Department of Diagnostic and Interventional Radiology, University of Leipzig, Leipzig, Germany 3 Department of Neurology, Martin-Luther University Halle-Wittenberg, Halle, Germany 4 Department of Neuroradiology, University of Leipzig, Leipzig, Germany

Corresponding author: Hans-Jonas Meyer, Department of Diagnostic and Interventional Radiology, Universita¨tsklinikum Leipzig, Liebigstraße 20, 04103 Leipzig, Germany. Email: [email protected]

2 to be the best imaging method for screening and followup in these patients (2,3). It is clinically used to detect muscle edema, myofasciitis, or atrophy of affected muscles (1). However, beside morphological information magnetic resonance imaging (MRI) also can provide information about the microstructure of muscle tissue, for example by using diffusion-weighted imaging (DWI) (4). DWI measures the random motion of water molecules reflecting the microstructure of the underlying tissue and can be estimated quantitatively by the apparent diffusion coefficient (ADC) (5). Previously, it has been shown that DWI can be helpful to characterize muscle involvement in several disorders (6–10). Different serological parameters are also used to aid the diagnosis of muscle disorders and can indicate muscle alteration (1). The standard serological parameters for myopathy/myositis include C-reactive protein (CRP), lactate dehydrogenase (LDH), alanine aminotransferase (ALAT), aspartate aminotransferase (ASAT), creatine kinase (CK), and myoglobine, the most sensitive one being the CK (1). At last, the most important diagnostic tool is a muscle biopsy to confirm the final diagnosis, but it is an invasive procedure with possible complications (1). Previously, only few studies have investigated the associations between MRI and serological parameters in muscle diseases (11–13); however, only conventional MRI was used (11–13). There were no previous reports regarding associations between serological parameters and DWI. Therefore, the purpose of our study was to compare ADC values in different myopathies and

Fig. 1. Data acquisition in the study.

Acta Radiologica 0(0) myositis and to analyze possible associations between ADC and serological parameters.

Material and Methods This retrospective study was approved by the institutional ethic committee.

Patients In the time period from 2008 to 2015, 106 patients with different muscle disorders were investigated by MRI in our department. Patients were retrospectively included in the current study if they fulfilled the following inclusion criteria: if they had a muscle disorder (myositis or myopathy) confirmed by histopathology; MRI was performed with DWI; and affected muscles showed no artifacts on DWI. Cases that did not meet the inclusion criteria were excluded from the study. Patients with traumatic muscle injury, steroid induced myopathy, muscle abscess, and muscle subjected to ischemia or venous thrombosis were excluded (Fig. 1). Altogether, 25 patients fulfilled the inclusion criteria (13 women, 12 men; mean age ¼ 55.3  14.3 years; median age ¼ 55 years; age range ¼ 27–78 years). Different muscle disorders were diagnosed in these patients (Table 1). In addition, nine patients (6 women, 3 men) complained about muscle discomfort or pain. In these patients, no clinical signs of muscle disorders were found and also MRI showed no abnormalities. They were age-matched to our patient group.

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Table 1. Overview about the patient collective included in this study. n Myositis group Overlap syndrome Polymyositis Dermatomyositis Inclusion body myositis Non-inflammatory myopathy group Non-specific myopathy Limb girdle muscle dystrophy Matrin-3-related myopathy Total

17 8 6 2 1 8 4 3 1 25

Subgroup (%)

47.06 35.29 11.76 5.88 50.00 37.50 12.50 100

Overall patients (%) 68 32 24 8 4 32 16 12 4 100

Therefore, these patients were a control group in the present study.

MRI In all cases, MRI of the thigh and lower leg was performed using a 1.5-T scanner (Magnetom Vision Sonata Upgrade, Siemens, Erlangen, Germany). MRI sequences included turbo spin echo (TSE) images, T2weighted (T2W) fat-suppressed short tau inversion recovery (STIR) images, half-Fourier acquisition single-shot turbo spin-echo (HASTE) images, and T1weighted (T1W) spin-echo (SE) images before and after intravenous contrast medium. DW images were obtained with a multi-shot SE-EPI sequence (TR/TE ¼ 5800/68 ms, flip angle ¼ 90 , thickness ¼ 5 mm). DWI parameters included in all cases b-values of 0 and 1000 s/mm2.

ADC measurement ADC maps were automatically generated by the implemented software. In all cases, polygonal regions of interest (ROI) were manually drawn on the ADC maps along the contours of the affected muscles on each slice (whole muscle measure). A mean ADC value of each affected muscle was estimated. Furthermore, a mean ADC value of all affected muscles was calculated. In the control group, ROIs were drawn on the ADC maps within each investigated muscle and a mean ADC value of all muscles was calculated.

Serological parameters In all patients, the blood sample was taken within three days after the MRI. The following serological

parameters were measured: CRP, LDH, ALT, AST, CK, and myoglobine. The SI units were used for these parameters. Furthermore, the patients were screened for the autoantibodies Jo-1.

Statistical analysis Statistical analysis and graphics creation was performed using GraphPad Prism (GraphPad Software, La Jolla, CA, USA). Collected data were evaluated by means of descriptive statistics (absolute and relative frequencies). All values are presented as mean  standard deviation. Spearman’s correlation coefficient was used to analyze associations between investigated parameters. ADC and clinical subgroups were analyzed by Mann–Whitney test. In all instances, P values < 0.05 were taken to indicate statistical significance.

Results The estimated mean ADC values in the myositis group were 1.89  0.37  10–3 mm2/s (median ¼ 1.82  10–3 mm2/s, range ¼ 1.34–2.49  10–3 mm2/s) and in the myopathy group 1.79  0.33  10–3 mm2/s (median ¼ 1.77  10–3 mm2/s, range ¼ 1.29–2.35  10–3 mm2/s), respectively (Fig. 2). The control group had a mean ADC value of 1.15  0.37  10–3 mm2/s, median ¼ 1.18  10–3 mm2/s, range ¼ 0.58–1.72  10–3 mm2/s. The affected muscles displayed statistically significant higher ADC values than the unaffected muscles in the control group (vs. myositis P ¼ 0.0002 and vs. myopathy P ¼ 0.0021) (Fig. 3). ADC values did not significantly differ between the myositis group and the myopathy group (P ¼ 0.54). We divided the myositis group into two groups, overlapping myositis and the other entities. However, no statistically significant difference between those groups was found (P ¼ 0.96) (Table 2, Fig. 4). The Jo-1-positive polymyositis had a mean ADC of 1.54  0.18  10–3 mm2/s, which was lower than the Jo-1-negative polymyositis patients with 2.12  0.45  10–3 mm2/s. However, the difference did not reach statistical significance (P ¼ 0.25). Correlation analyses did not show significant associations between ADC values and different serological parameters (Table 3).

Discussion To the best of our knowledge, this is the first study in which associations between DWI and serological parameters in myositis and myopathy patients have been addressed. According to the literature, DWI is a sensitive modality for tissue characterization in several

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Acta Radiologica 0(0) disorders (4,6–10). For example, it can be used in different malignancies to assess tumor cellularity (14). Also, it is routinely used to detect intracellular edema in stroke patients (15). Recently, DWI was recognized to be a valuable modality in muscle imaging (7,8). It has been shown that several muscle tumors have different ADC values (8). For example, muscle lymphomas have significantly lower ADC values than other muscle tumors, such as sarcomas and muscle metastases (8,9).

Table 2. ADC values in different myositis groups.

Fig. 2. Imaging findings in a patient with a polymyositis. (a) T2W fat-suppressed short tau inversion recovery (STIR) image showing edema of the thigh musculature, especially of the biceps femoris muscles. (b) ADC map. A mean ADC value of all affected muscles is 1.5 mm2/s. Serological parameters for this case are as follows: CK ¼ 24.12 mmol/L, myoglobine ¼ 720 mmol/L, CRP ¼ 10 mg/dL, LDH ¼ 5.11 mmol/L, ASAT ¼ 0.96 nmol/L, ALAT ¼ 1.14 nmol/L.

Diagnosis

Mean ADC value  standard deviation (10–3 mm2/s)

Polymyositis Dermatomyositis Overlap syndrome Inclusion body myositis

1.90  0.46 2.22  0.37 1.86  0.30 1.78

Fig. 4. Comparison of ADC values between the overlap-syndrome and the other myositis entities. No statistically significant difference was identified (P ¼ 0.96).

Fig. 3. Comparison of ADC values between the groups with myositis, myopathy, and the control group.

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Table 3. Correlations between DWI and laboratory parameters in all patients Parameters CK Myoglobine CRP LDH AST ALT

ADCmean (10–3 mm2/s) r ¼ –0.13 P ¼ 0.53 r ¼ 0.07 P ¼ 0.75 r ¼ 0.12 P ¼ 0.53 r ¼ 0.15 P ¼ 0.51 r ¼ 0.03 P ¼ 0.88 r ¼ –0.02 P ¼ 0.89

Therefore, we hypothesize that DWI might be able to assess tissue alteration in inflammatory muscle diseases. Previously, only two studies investigated DWI in myositis (6,7). Qi et al. investigated eight patients with myositis and identified that mean ADC values of inflamed muscles were statistically significantly higher than those of controls (6). In another study, 46 myopathy patients were investigated by DWI (7). The authors also found statistically significant differences of ADC values between normal musculature, muscles with edema, and muscle dystrophy (7). However, the identified ADC values overlapped significantly and are not useful in clinical practice (7). So, the median ADC value of unaffected muscles was 1.69 mm2/s, inflamed muscles had a median ADC value of 1.66 mm2/s, and in muscle dystrophy the median ADC value was 1.60 mm2/s (7). In agreement with previous reports (6,16), we also found that affected muscles showed statistically significant higher ADC values than normal muscles. This finding may be related to muscle edema and alteration of cell membranes. The underlying tissue alterations in myositis are complex (17). Inflammatory T-cells, mainly located in the endomysium, surround the muscle fibers (17), leading theoretically to a decreased ADC value due to higher cellularity. This reaction, however, may precede the clinical manifestation and therefore need not be depicted by the clinical imaging studies. In another step, the muscle fibers are degraded by this inflammatory reaction, e.g. due to phagocytosis and necrosis (17). This reaction might lead to increasing ADC values. For example, in tumor patients with necrotic tumors the ADC value increases due to lower cellularity and more free diffusion space for the water molecules (18). Another factor is the resulting extracellular edema

caused by inflammation, resulting in increasing ADC values, like is known in brain vasogenic edema (19). The reproducibility of ADC values in muscle imaging is previously widely discussed (20–22). Ponratana et al. investigated lower extremity muscles in children and identified an excellent inter-reader agreement and test–retest repeatability (20). Therefore, ADC values can also be used as a biomarker in clinical routine. Despite the statistically significant difference of ADC values between the affected and unaffected muscles, there is notable overlap between the groups. Therefore, ADC values might aid the diagnosis but cannot make a diagnosis of myopathy alone. We hypothesize that ADC values might be more important as a biomarker to indicate therapeutic response or disease progression. However, longitudinal studies are needed to evaluate this possible use of ADC. Furthermore, there is inconsistency about different b-values in muscle imaging. For brain imaging, the standard b-values are 0 and 1000 s/mm2 (23). The higher the b value, the lower the ADC value becomes and the higher is the signal-to-noise ratio. Therefore, some authors acquired ADC values in muscles only with a low b-value of 500 s/mm2 (16) or 600 s/mm2 (10). However, other authors used higher b-values (6–8). Recently, it was identified that ADC values derived from even higher b-values might be better to reflect tumor histopathology than conventional ADC values (23). Several serological parameters are used to aid the diagnosis of muscle disorders (1). Except CRP, they all indicate unspecific cell lysis . CRP is an unspecific inflammation marker. Thereby, CK is the most important marker in myositis diagnosis (1). As a result, the ADC values might concordantly increase due to tissue alterations and should correlate with CK. However, in our study, no linear correlation was identified between ADC and CK. This finding may be due to complex biological changes in these multifactorial diseases. Furthermore, it should be considered that CK levels can be normal despite of active myositis (1). Previously reported data about muscle edema and CK levels were inconsistent. For example, in a recent study, a positive correlation between muscle edema identified on MRI and CK level expression was found in myositis (11). However, other authors did not show a significant correlation between T2 MRI and CK levels in patients with Duchenne myopathy (12). Similar results were also found in juvenile dermatomyositis (13). The authors found a positive correlation with T2 relaxation time on MRI and clinical scores but no correlation with CK level (13). We also did not find significant correlations between ADC and other serological parameters in our patients. The present study has several limitations. First, it has a retrospective design. Second, our patient sample

6 is relatively small, caused by the rarity of these disorders. Third, we acquired our DWI with only two b-values and therefore could not calculate other DWI parameters. In conclusion, affected muscles showed statistically significantly higher ADC values than normal muscles. No linear correlations between ADC and serological parameters were identified. Declaration of Conflicting Interests The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

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Funding The authors received no financial support for the research, authorship, and/or publication of this article.

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Apparent diffusion coefficient (ADC) does not correlate with different serological parameters in myositis and myopathy.

Background Magnetic resonance imaging (MRI) is widely used in several muscle disorders. Diffusion-weighted imaging (DWI) is an imaging modality, which...
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