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Routine clinical magnetic resonance imaging (MRI) sequences are frequently employed to quantify IMAT\/IMF due to their broad availability and non-invasive nature. However, methodological standardization and comprehensive validation against quantitative MRI (qMRI) reference standards remain sparse. The lack of standardization and validation presents a significant barrier to clinical adoption. Furthermore, automation of IMAT\/IMF quantification methods remains underexplored, which limits reproducibility and large-scale application in clinical settings. Addressing these gaps, which is the objective of this systematic review, is essential for ensuring seamless integration of IMAT\/IMF quantification into clinical routine assessments.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, we systematically reviewed 65 studies that assessed IMAT or IMF using conventional MRI. The selected studies were categorized based on their methodological approaches, anatomical regions analyzed, and validation against qMRI reference standards. Additionally, we classified the level of automation of these methods and identified the necessary steps to be implemented in order to reach full automation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Our findings reveal a high methodological diversity in the literature, with substantial variations based on the anatomical region studied. Very few studies validated their findings against qMRI reference standards, a crucial step for establishing these methods in clinical practice. The automation potential of the reviewed methods varied significantly, with only a limited number of studies addressing full automation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>This systematic review highlights gaps in validation and automation of IMAT\/IMF quantification methods using conventional MRI sequences. We provide guidance for researchers and clinicians aiming to implement these techniques in routine assessments. Transitioning from qualitative to quantitative MRI assessments requires standardization and automation to improve reproducibility and clinical applicability. Automation plays a key role in integrating these methods into clinical workflows, reducing manual effort, and increasing efficiency. By fostering the development of computer-aided solutions, this review supports the advancement of reliable and accessible IMAT\/IMF quantification methods that have the potential to transform musculoskeletal imaging and patient care.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s12880-025-02037-w","type":"journal-article","created":{"date-parts":[[2025,11,21]],"date-time":"2025-11-21T09:36:14Z","timestamp":1763717774000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Automatability and validity of methods for the quantification of intra-\/Intermuscular adipose tissue in conventional MRI: a systematic review"],"prefix":"10.1186","volume":"25","author":[{"given":"Alicia","family":"Pirwass","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Birte","family":"Glimm","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michael","family":"Munz","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hans-Joachim","family":"Wilke","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,11,21]]},"reference":[{"key":"2037_CR1","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1016\/j.jot.2023.07.005","volume-title":"Journal of orthopaedic translation","author":"K Engelke","year":"2023","unstructured":"Engelke K, Chaudry O, Gast L, Eldib MA, Wang L, Laredo JD, et al. 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