Korhan Buyukturkoglu, Lin Lu, Levi Davis, Renan E. Orellana, Charles C. White, Rongyi Sun, Sinem Ozcelik, Nina M. Isenstein, Kaho B. Onomichi, Rifat Iqbal, Binsheng Zhao, Yaakov Stern, Burcu Zeydan, Orhun H. Kantarci, Claire S. Riley, Philip L. De Jager
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Radiomic features (RF) and volumes were extracted from the whole thalamus, five thalamic nuclei, and the putamen segmented on three-dimensional T1-weighted images. Cognitive performance was assessed using the Symbol Digit Modalities Test (SDMT) and Paced Auditory Serial Addition Test (PASAT) in PwMS and the Digit Symbol Substitution Test (DSST) in HC. In the first MS cohort, multivariate linear regression in a discovery set (<i>N</i> = 103) identified thalamus-derived RF associated with SDMT, which were retested in a replication set (<i>N</i> = 63). Their associations with PASAT in a second MS cohort (<i>N</i> = 176) and DSST in HC were also evaluated. We then tested whether the same RFs, when extracted from the putamen, was associated with SDMT. Least Absolute Shrinkage and Selection Operator (LASSO) models assessed the combined predictive value of RF and volumes.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>Twenty-eight RF–region of interest (ROI) pairs were associated with SDMT in the replication set (false discovery rate [FDR] < 0.05). Of these, 24 were also associated with PASAT (FDR ≤ 0.03), and 2 with DSST. Only ventral nuclei volume showed replicated associations among volumetrics. Only four putamen-derived pairs were associated with SDMT (FDR = 0.04). LASSO results confirmed RF outperformed volumes.</p>\n </section>\n \n <section>\n \n <h3> Conclusion</h3>\n \n <p>RF extracted from the thalamus is strongly associated with cognitive performance in PwMS, outperforming volumetric measures and supporting their potential as sensitive imaging biomarkers.</p>\n </section>\n </div>","PeriodicalId":16399,"journal":{"name":"Journal of Neuroimaging","volume":"35 4","pages":""},"PeriodicalIF":2.3000,"publicationDate":"2025-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Radiomic Approach to Clinical MRI Refines the Thalamus-Cognition Link in Multiple Sclerosis\",\"authors\":\"Korhan Buyukturkoglu, Lin Lu, Levi Davis, Renan E. Orellana, Charles C. White, Rongyi Sun, Sinem Ozcelik, Nina M. Isenstein, Kaho B. Onomichi, Rifat Iqbal, Binsheng Zhao, Yaakov Stern, Burcu Zeydan, Orhun H. Kantarci, Claire S. Riley, Philip L. 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In the first MS cohort, multivariate linear regression in a discovery set (<i>N</i> = 103) identified thalamus-derived RF associated with SDMT, which were retested in a replication set (<i>N</i> = 63). Their associations with PASAT in a second MS cohort (<i>N</i> = 176) and DSST in HC were also evaluated. We then tested whether the same RFs, when extracted from the putamen, was associated with SDMT. Least Absolute Shrinkage and Selection Operator (LASSO) models assessed the combined predictive value of RF and volumes.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Results</h3>\\n \\n <p>Twenty-eight RF–region of interest (ROI) pairs were associated with SDMT in the replication set (false discovery rate [FDR] < 0.05). Of these, 24 were also associated with PASAT (FDR ≤ 0.03), and 2 with DSST. Only ventral nuclei volume showed replicated associations among volumetrics. Only four putamen-derived pairs were associated with SDMT (FDR = 0.04). 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A Radiomic Approach to Clinical MRI Refines the Thalamus-Cognition Link in Multiple Sclerosis
Background and Purpose
Radiomics extracts imaging features that may not be detectable through conventional volumetric analyses. Given their role in multiple sclerosis (MS), we applied radiomics to thalamic nuclei and examined their associations with cognitive performance.
Methods
A total of 601 individuals were included (342 people with MS [PwMS] from two cohorts and 259 healthy controls [HC]). Radiomic features (RF) and volumes were extracted from the whole thalamus, five thalamic nuclei, and the putamen segmented on three-dimensional T1-weighted images. Cognitive performance was assessed using the Symbol Digit Modalities Test (SDMT) and Paced Auditory Serial Addition Test (PASAT) in PwMS and the Digit Symbol Substitution Test (DSST) in HC. In the first MS cohort, multivariate linear regression in a discovery set (N = 103) identified thalamus-derived RF associated with SDMT, which were retested in a replication set (N = 63). Their associations with PASAT in a second MS cohort (N = 176) and DSST in HC were also evaluated. We then tested whether the same RFs, when extracted from the putamen, was associated with SDMT. Least Absolute Shrinkage and Selection Operator (LASSO) models assessed the combined predictive value of RF and volumes.
Results
Twenty-eight RF–region of interest (ROI) pairs were associated with SDMT in the replication set (false discovery rate [FDR] < 0.05). Of these, 24 were also associated with PASAT (FDR ≤ 0.03), and 2 with DSST. Only ventral nuclei volume showed replicated associations among volumetrics. Only four putamen-derived pairs were associated with SDMT (FDR = 0.04). LASSO results confirmed RF outperformed volumes.
Conclusion
RF extracted from the thalamus is strongly associated with cognitive performance in PwMS, outperforming volumetric measures and supporting their potential as sensitive imaging biomarkers.
期刊介绍:
Start reading the Journal of Neuroimaging to learn the latest neurological imaging techniques. The peer-reviewed research is written in a practical clinical context, giving you the information you need on:
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and other new and upcoming neuroscientific modalities.The Journal of Neuroimaging addresses the full spectrum of human nervous system disease, including stroke, neoplasia, degenerating and demyelinating disease, epilepsy, tumors, lesions, infectious disease, cerebral vascular arterial diseases, toxic-metabolic disease, psychoses, dementias, heredo-familial disease, and trauma.Offering original research, review articles, case reports, neuroimaging CPCs, and evaluations of instruments and technology relevant to the nervous system, the Journal of Neuroimaging focuses on useful clinical developments and applications, tested techniques and interpretations, patient care, diagnostics, and therapeutics. Start reading today!