{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T03:02:20Z","timestamp":1787022140078,"version":"build-2736575974"},"reference-count":18,"publisher":"Public Library of Science (PLoS)","issue":"4","license":[{"start":{"date-parts":[[2024,4,1]],"date-time":"2024-04-01T00:00:00Z","timestamp":1711929600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS ONE"],"abstract":"<jats:p>\n                    In pre-clinical models of brain gliomas, Relaxation Along a Fictitious Field in second rotating frame (T\n                    <jats:sub>RAFF2<\/jats:sub>\n                    ), continues wave T\n                    <jats:sub>1rho<\/jats:sub>\n                    (T\n                    <jats:sub>1\u03c1cw<\/jats:sub>\n                    ), adiabatic T\n                    <jats:sub>1rho<\/jats:sub>\n                    (T\n                    <jats:sub>1\u03c1adiab<\/jats:sub>\n                    ), and adiabatic T\n                    <jats:sub>2rho<\/jats:sub>\n                    (T\n                    <jats:sub>2\u03c1adiab<\/jats:sub>\n                    ) relaxation time mappings have demonstrated potential to non-invasively characterize brain gliomas. Our aim was to evaluate the feasibility and potential of 4 different spin lock methods at 3T to characterize primary brain glioma. 22 patients (26\u201372 years) with suspected primary glioma. T\n                    <jats:sub>1\u03c1cw<\/jats:sub>\n                    was performed using pulse peak amplitude of 500Hz and pulse train durations of 40 and 80 ms while the corresponding values for T\n                    <jats:sub>1\u03c1adiab<\/jats:sub>\n                    , T\n                    <jats:sub>2\u03c1adiab<\/jats:sub>\n                    , T\n                    <jats:sub>RAFF2<\/jats:sub>\n                    were 500\/500\/500Hz and 48 and 96, 64 and 112, 45 and 90 ms, respectively. The parametric maps were calculated using a monoexponential model. Molecular profiles were evaluated from tissue specimens obtained during the resection. The lesion regions-of-interest were segmented from high intensity FLAIR using automatic segmentation with manual refinement. Statistical descriptors from the voxel intensity values inside each lesion and radiomic features (Pyrad MRC package) were calculated. From extracted radiomics, mRMRe R package version 2.1.0 was used to select 3 features in each modality for statistical comparisons. Of the 22 patients, 10 were found to have IDH-mutant gliomas and of those 5 patients had 1p\/19q codeletion group comparisons. Following correction for effects of age and gender, at least one statistical descriptor was able to differentiate between IDH and 1p\/19q codeletion status for all the parametric maps. In the radiomic analysis, corner-edge detector features with Harris-Stephens filtered signal showed significant group differences in IDH and 1p\/19q codeletion groups. Spin lock imaging at 3T of human glioma was feasible and various qualitative parameters derived from the parametric maps were found to have potential to differentiate IDH and 1p19q codeletion status. Future larger prospective clinical trials are warranted to evaluate these methods further.\n                  <\/jats:p>","DOI":"10.1371\/journal.pone.0296958","type":"journal-article","created":{"date-parts":[[2024,4,1]],"date-time":"2024-04-01T13:37:22Z","timestamp":1711978642000},"page":"e0296958","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":3,"title":["Relaxation Along a Fictitious Field, continuous wave T1rho, adiabatic T1rho and adiabatic T2rho imaging of human gliomas at 3T: A feasibility study"],"prefix":"10.1371","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6305-3570","authenticated-orcid":true,"given":"Ivan","family":"Jambor","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aida","family":"Steiner","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marko","family":"Pesola","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maria","family":"Gardberg","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Janek","family":"Frantz\u00e9n","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pekka","family":"Jokinen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Timo","family":"Liimatainen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5878-4333","authenticated-orcid":true,"given":"Heikki","family":"Minn","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hannu","family":"Aronen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Harri","family":"Merisaari","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2024,4,1]]},"reference":[{"key":"pone.0296958.ref001","doi-asserted-by":"crossref","first-page":"1231","DOI":"10.1093\/neuonc\/noab106","article-title":"The 2021 WHO Classification of Tumors of the Central Nervous System: a summary.","volume":"23","author":"DN Louis","year":"2021","journal-title":"Neuro Oncol"},{"key":"pone.0296958.ref002","first-page":"1989","article-title":"Glioma grading: sensitivity, specificity, and predictive values of perfusion MR imaging and proton MR spectroscopic imaging compared with conventional MR imaging.","author":"M Law","journal-title":"AJNR AmJNeuroradiol:"},{"key":"pone.0296958.ref003","doi-asserted-by":"crossref","first-page":"269","DOI":"10.1016\/j.jmr.2011.01.022","article-title":"Relaxation dispersion in MRI induced by fictitious magnetic fields","volume":"209","author":"T Liimatainen","year":"2011","journal-title":"J Magn Reson"},{"key":"pone.0296958.ref004","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1371\/journal.pone.0069157","article-title":"Relaxation Along a Fictitious Field (RAFF) and Z-spectroscopy using Alternating-Phase Irradiation (ZAPI) in Permanent Focal Cerebral Ischemia in Rat","volume":"8","author":"KT Jokivarsi","year":"2013","journal-title":"PLoS One"},{"key":"pone.0296958.ref005","first-page":"268","article-title":"Quantitative magnetic resonance imaging assessment of cerebral ischemia in rat using on-resonance T(1) in the rotating frame.","author":"OH Grohn","journal-title":"Magn Reson"},{"key":"pone.0296958.ref006","doi-asserted-by":"crossref","first-page":"269","DOI":"10.1002\/mrm.22997","article-title":"Glioma cell density in a rat gene therapy model gauged by water relaxation rate along a fictitious magnetic field","volume":"67","author":"T Liimatainen","year":"2012","journal-title":"Magn Reson Med"},{"key":"pone.0296958.ref007","doi-asserted-by":"crossref","first-page":"61892","DOI":"10.1371\/journal.pone.0061892","article-title":"Accelerating Fibre Orientation Estimation from Diffusion Weighted Magnetic Resonance Imaging Using GPUs","volume":"8","author":"M Hern\u00e1ndez","year":"2013","journal-title":"PLoS One"},{"key":"pone.0296958.ref008","doi-asserted-by":"crossref","first-page":"1512","DOI":"10.1016\/j.ejrad.2013.05.029","article-title":"FLAIR lesion segmentation: Application in patients with brain tumors and acute ischemic stroke","volume":"82","author":"M Artzi","year":"2013","journal-title":"Eur J Radiol"},{"key":"pone.0296958.ref009","doi-asserted-by":"crossref","first-page":"e104","DOI":"10.1158\/0008-5472.CAN-17-0339","article-title":"Computational radiomics system to decode the radiographic phenotype","volume":"77","author":"JJM Van Griethuysen","year":"2017","journal-title":"Cancer Res"},{"key":"pone.0296958.ref010","first-page":"mrm.28058","article-title":"Repeatability of radiomics and machine learning for DWI: Short-term repeatability study of 112 patients with prostate cancer","author":"H Merisaari","year":"2019","journal-title":"Magn Reson Med"},{"key":"pone.0296958.ref011","doi-asserted-by":"crossref","first-page":"2365","DOI":"10.1093\/bioinformatics\/btt383","article-title":"MRMRe: An R package for parallelized mRMR ensemble feature selection","volume":"29","author":"N De Jay","year":"2013","journal-title":"Bioinformatics"},{"key":"pone.0296958.ref012","doi-asserted-by":"crossref","first-page":"7455","DOI":"10.1158\/1078-0432.CCR-19-1127","article-title":"Predicting the 1p\/19q codeletion status of presumed low-grade glioma with an externally validated machine learning algorithm","volume":"25","author":"SR van der Voort","year":"2019","journal-title":"Clin Cancer Res"},{"key":"pone.0296958.ref013","first-page":"0869","article-title":"MRI Contrasts Generated Using Fictitious Fields in High-Rank Rotating Frames Correlate With Myelin Content in Normal Rat Brain ex vivo","volume":"21","author":"T Liimatainen","year":"2013","journal-title":"Proc 21st Sci Meet Int Soc Magn Reson Med"},{"key":"pone.0296958.ref014","first-page":"269","article-title":"Relaxation dispersion in MRI induced by fictitious magnetic fields","author":"T Liimatainen","journal-title":"JMagn Reson"},{"key":"pone.0296958.ref015","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1002\/mrm.25647","article-title":"Rotating frame relaxation imaging of prostate cancer: Repeatability, cancer detection, and Gleason score prediction","volume":"75","author":"I Jambor","year":"2016","journal-title":"Magn Reson Med"},{"key":"pone.0296958.ref016","doi-asserted-by":"crossref","first-page":"911","DOI":"10.1007\/s10278-023-00778-0","article-title":"Development and Validation of CT-Based Radiomics Signature for Overall Survival Prediction in Multi-organ Cancer.","volume":"36","author":"VH Le","year":"2023","journal-title":"J Digit Imaging"},{"key":"pone.0296958.ref017","first-page":"S1076","article-title":"Predicting EGFR Mutation Status in Non-Small Cell Lung Cancer Using Artificial Intelligence: A Systematic Review and Meta-Analysis.","volume":"27","author":"HS Nguyen","year":"2023","journal-title":"Acad Radiol"},{"issue":"89","key":"pone.0296958.ref018","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1093\/neuros\/nyab124","article-title":"State of Radiomics in Glioblastoma.","volume":"15","author":"B Taha","year":"2021","journal-title":"Neurosurgery"}],"container-title":["PLOS ONE"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pone.0296958","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,4,1]],"date-time":"2024-04-01T13:37:41Z","timestamp":1711978661000},"score":1,"resource":{"primary":{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pone.0296958"}},"subtitle":[],"editor":[{"given":"Syed M.","family":"Faisal","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]}],"short-title":[],"issued":{"date-parts":[[2024,4,1]]},"references-count":18,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2024,4,1]]}},"URL":"https:\/\/doi.org\/10.1371\/journal.pone.0296958","relation":{},"ISSN":["1932-6203"],"issn-type":[{"value":"1932-6203","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,4,1]]}}}