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One common shortcoming for the abdominal subcutaneous adipose tissue (ASAT) of obese subjects is the technically restricted imaging field of view (FOV). This work derives equations for the conversion between six surrogate measures and fully segmented ASAT volume and discusses the predictive power of these image-based quantities. Clinical (gender, age, anthropometry) and MRI data (1.5\u00a0T, two-point Dixon sequence) of 193 overweight and obese patients (116 female, 77 male) from a single research center for obesity were analyzed retrospectively. Six surrogate measures of fully segmented ASAT volume (<jats:italic>V<\/jats:italic><jats:sub>ASAT<\/jats:sub>) were considered: two simple ASAT lengths, two partial areas (<jats:italic>A<\/jats:italic><jats:sub>p-FH<\/jats:sub>, <jats:italic>A<\/jats:italic><jats:sub>p-ASIS<\/jats:sub>) and two partial volumes (<jats:italic>V<\/jats:italic><jats:sub>p-FH<\/jats:sub>, <jats:italic>V<\/jats:italic><jats:sub>p-ASIS<\/jats:sub>) limited by either the femoral heads (FH) or the anterior superior iliac spine (ASIS). Least-squares regression between each measure and <jats:italic>V<\/jats:italic><jats:sub>ASAT<\/jats:sub> provided slope and intercept for the computation of estimated ASAT volumes (<jats:italic>V<\/jats:italic><jats:sup>~<\/jats:sup><jats:sub>ASAT<\/jats:sub>). Goodness of fit was evaluated by coefficient of determination (<jats:italic>R<\/jats:italic><jats:sup>2<\/jats:sup>) and standard deviation of percent differences (<jats:italic>s<\/jats:italic><jats:sub>d%<\/jats:sub>) between <jats:italic>V<\/jats:italic><jats:sup>~<\/jats:sup><jats:sub>ASAT<\/jats:sub> and <jats:italic>V<\/jats:italic><jats:sub>ASAT<\/jats:sub>. Best agreement was observed for partial volume <jats:italic>V<\/jats:italic><jats:sub>p-FH<\/jats:sub> (<jats:italic>s<\/jats:italic><jats:sub>d%<\/jats:sub>\u2009=\u200914.4% and <jats:italic>R<\/jats:italic><jats:sup>2<\/jats:sup>\u2009=\u20090.78), followed by <jats:italic>V<\/jats:italic><jats:sub>p-ASIS<\/jats:sub> (<jats:italic>s<\/jats:italic><jats:sub>d%<\/jats:sub>\u2009=\u200918.1% and <jats:italic>R<\/jats:italic><jats:sup>2<\/jats:sup>\u2009=\u20090.69) and AWF<jats:sub>ASIS<\/jats:sub> (<jats:italic>s<\/jats:italic><jats:sub>d%<\/jats:sub>\u2009=\u200923.9% and <jats:italic>R<\/jats:italic><jats:sup>2<\/jats:sup>\u2009=\u20090.54), with minor gender differences only. Other estimates from simple lengths and partial areas were moderate only (<jats:italic>s<\/jats:italic><jats:sub>d%<\/jats:sub>\u2009&gt;\u200923.0% and <jats:italic>R<\/jats:italic><jats:sup>2<\/jats:sup>\u2009&lt;\u20090.50). Gender differences in <jats:italic>R<\/jats:italic><jats:sup>2<\/jats:sup> generally ranged between 0.02 (<jats:italic>d<\/jats:italic><jats:sub>ven<\/jats:sub>) and 0.29 (<jats:italic>A<\/jats:italic><jats:sub>p-FH<\/jats:sub>). The common FOV restriction for MRI volumetry of ASAT in obese subjects can best be overcome by estimating <jats:italic>V<\/jats:italic><jats:sub>ASAT<\/jats:sub> from <jats:italic>V<\/jats:italic><jats:sub>p-FH<\/jats:sub> using the equation derived here. The very simple AWF<jats:sub>ASIS<\/jats:sub> can be used with reservation.<\/jats:p>","DOI":"10.1038\/s41598-020-75985-8","type":"journal-article","created":{"date-parts":[[2020,11,4]],"date-time":"2020-11-04T11:03:36Z","timestamp":1604487816000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Abdominal subcutaneous fat quantification in obese patients from limited field-of-view MRI data"],"prefix":"10.1038","volume":"10","author":[{"given":"Sophia","family":"Michel","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nicolas","family":"Linder","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tobias","family":"Eggebrecht","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alexander","family":"Schaudinn","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Matthias","family":"Bl\u00fcher","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Arne","family":"Dietrich","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Timm","family":"Denecke","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Harald","family":"Busse","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2020,11,4]]},"reference":[{"key":"75985_CR1","volume-title":"The SuRF Report 2: Surveillance of Chronic Disease Risk Factors: Country-Level Data and Comparable Estimates","author":"World Health Organization","year":"2005","unstructured":"World Health Organization. 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