{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T14:05:11Z","timestamp":1753884311647,"version":"3.41.2"},"reference-count":24,"publisher":"Oxford University Press (OUP)","issue":"1085","license":[{"start":{"date-parts":[[2018,2,20]],"date-time":"2018-02-20T00:00:00Z","timestamp":1519084800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,5,1]]},"abstract":"<jats:sec>\n                  <jats:title>Objective:<\/jats:title>\n                  <jats:p>Diffusion-weighted imaging (DWI) has the potential of being able to reflect histopathology architecture. A novel imaging approach, namely histogram analysis, is used to further characterize tissues on MRI. The aim of this study was to correlate histogram parameters derived from apparent diffusion coefficient (ADC) maps with serological parameters in myositis.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Methods:<\/jats:title>\n                  <jats:p>16 patients with autoimmune myositis were included in this retrospective study. DWI was obtained on a 1.5 T scanner by using the b \u00a0-values of 0 and 1000\u2009s mm\u2013 \u00a02. Histogram analysis was performed as a whole muscle measurement by using a custom-made Matlab-based application. The following ADC histogram parameters were estimated: ADCmean, ADCmax, ADCmin, ADCmedian, ADCmode, and the following percentiles ADCp10, ADCp25, ADCp75, ADCp90, as well histogram parameters kurtosis, skewness, and entropy. In all patients, the blood sample was acquired within 3 days to the MRI. The following serological parameters were estimated: alanine aminotransferase, aspartate aminotransferase, creatine kinase, lactate dehydrogenase, C-reactive protein (CRP) and myoglobin. All patients were screened for Jo1-autobodies.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results:<\/jats:title>\n                  <jats:p>Kurtosis correlated inversely with CRP (p = \u20130.55 and 0.03). Furthermore, ADCp10 and ADCp90 values tended to correlate with creatine kinase (p = \u20130.43, 0.11, and p = \u20130.42, = 0.12 respectively). In addition, ADCmean, p10, p25, median, mode, and entropy were different between Jo1-positive and Jo1-negative patients.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusion:<\/jats:title>\n                  <jats:p>ADC histogram parameters are sensitive for detection of muscle alterations in myositis patients.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Advances in knowledge:<\/jats:title>\n                  <jats:p>This study identified that kurtosis derived from ADC maps is associated with CRP in myositis patients. Furthermore, several ADC histogram parameters are statistically different between Jo1-positive and Jo1-negative patients.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1259\/bjr.20170900","type":"journal-article","created":{"date-parts":[[2018,2,13]],"date-time":"2018-02-13T16:44:24Z","timestamp":1518540264000},"source":"Crossref","is-referenced-by-count":6,"title":["Histogram analysis derived from apparent diffusion coefficient (ADC) is more sensitive to reflect serological parameters in myositis than conventional ADC analysis"],"prefix":"10.1093","volume":"91","author":[{"given":"Hans Jonas","family":"Meyer","sequence":"first","affiliation":[{"name":"Department of Diagnostic and Interventional Radiology, University of Leipzig , Leipzig , Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alexander","family":"Emmer","sequence":"additional","affiliation":[{"name":"Department of Neurology, Martin-Luther University Halle-Wittenberg , Halle (Saale) , Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Malte","family":"Kornhuber","sequence":"additional","affiliation":[{"name":"Department of Neurology, Martin-Luther University Halle-Wittenberg , Halle (Saale) , Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alexey","family":"Surov","sequence":"additional","affiliation":[{"name":"Department of Diagnostic and Interventional Radiology, University of Leipzig , Leipzig , Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2018,2,20]]},"reference":[{"key":"2024050214300959300_b1","doi-asserted-by":"crossref","first-page":"967","DOI":"10.2214\/ajr.179.4.1790967","article-title":"Whole-body MR imaging in the diagnosis of polymyositis","volume":"179","author":"O'Connell","year":"2002","journal-title":"AJR Am J Roentgenol"},{"key":"2024050214300959300_b2","doi-asserted-by":"crossref","first-page":"1320","DOI":"10.1007\/s00415-016-8350-6","article-title":"Magnetic resonance imaging patterns of muscle involvement in genetic muscle diseases: a systematic review","volume":"264","author":"Leung","year":"2017","journal-title":"J Neurol"},{"key":"2024050214300959300_b3","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1593\/neo.81328","article-title":"Diffusion-weighted magnetic resonance imaging as a cancer biomarker: consensus and recommendations","volume":"11","author":"Padhani","year":"2009","journal-title":"Neoplasia"},{"key":"2024050214300959300_b4","doi-asserted-by":"crossref","first-page":"59492","DOI":"10.18632\/oncotarget.17752","article-title":"Correlation between apparent diffusion coefficient (ADC) and cellularity is different in several tumors: a meta-analysis","volume":"8","author":"Surov","year":"2017","journal-title":"Oncotarget"},{"key":"2024050214300959300_b5","doi-asserted-by":"crossref","first-page":"75434","DOI":"10.18632\/oncotarget.20406","article-title":"Associations between apparent diffusion coefficient (ADC) and KI 67 in different tumors: a meta-analysis. 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