{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,16]],"date-time":"2026-10-16T18:46:56Z","timestamp":1792176416487,"version":"4.4.0"},"reference-count":35,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"5","license":[{"start":{"date-parts":[[2021,8,12]],"date-time":"2021-08-12T00:00:00Z","timestamp":1628726400000},"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":["Neurosurg.","NEUROS"],"published-print":{"date-parts":[[2021,11]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>BACKGROUND<\/jats:title>\n                    <jats:p>Preprocedure diffusion tensor magnetic resonance imaging (MRI) may predict the response of trigeminal neuralgia (TN) patients to Gamma Knife (Elekta AB) and microvascular decompression (MVD).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>OBJECTIVE<\/jats:title>\n                    <jats:p>To test this hypothesis using pontine-segment diffusion tensor MRI radial diffusivity (RD), a known biomarker for demyelination, to predict TN recurrence following MVD.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>METHODS<\/jats:title>\n                    <jats:p>\n                      RD from the pontine segment of the trigeminal tract was extracted in a semiautomated and blinded fashion and normalized to background pontine RD. Following validation against published results, the relationship of normalized RD to symptom duration (D\n                      <jats:sub>S<\/jats:sub>\n                      ) was measured. Both parameters were then introduced into machine-learning classifiers to group patient outcomes as TN remission or recurrence. Performance was evaluated in an observational study with leave-one-out cross-validation to calculate accuracy, sensitivity, specificity, and receiver operating characteristic curves.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>RESULTS<\/jats:title>\n                    <jats:p>\n                      The study population included 22 patients with TN type 1 (TN1). There was a negative correlation of normalized RD and preoperative symptom duration (\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      \u00a0=\u00a0.035, R\n                      <jats:sup>2<\/jats:sup>\n                      \u00a0=\u00a0.20). When pontine-segment RD and D\n                      <jats:sub>S<\/jats:sub>\n                      were included as input variables, 2 classifiers predicted pain-free remission versus eventual recurrence with 85% accuracy, 83% sensitivity, and 86% specificity (leave-one-out cross-validation;\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      \u00a0=\u00a0.029) in a cohort of 13 patients undergoing MVD.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>CONCLUSION<\/jats:title>\n                    <jats:p>\n                      Pontine-segment RD and D\n                      <jats:sub>S<\/jats:sub>\n                      accurately predict MVD outcomes in TN1 and provide further evidence that diffusion tensor MRI contains prognostic information. Use of a classifier may allow more accurate risk stratification for neurosurgeons and patients considering MVD as a treatment for TN1. These findings provide further insight into the relationship of pontine microstructure, represented by RD, and the pathophysiology of TN.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/neuros\/nyab292","type":"journal-article","created":{"date-parts":[[2021,7,13]],"date-time":"2021-07-13T23:12:56Z","timestamp":1626217976000},"page":"777-783","source":"Crossref","is-referenced-by-count":20,"title":["Classifier Using Pontine Radial Diffusivity and Symptom Duration Accurately Predicts Recurrence of Trigeminal Neuralgia After Microvascular Decompression: A Pilot Study and Algorithm Description"],"prefix":"10.1227","volume":"89","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2093-7733","authenticated-orcid":false,"given":"Matthew S","family":"Willsey","sequence":"first","affiliation":[{"name":"Department of Neurosurgery, University of Michigan, Ann Arbor, Michigan, USA"},{"name":"Department of Biomedical Engineering, University of Michigan, Ann Arbor, 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USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7506-105X","authenticated-orcid":false,"given":"Oren","family":"Sagher","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, University of Michigan, Ann Arbor, Michigan, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2300-6136","authenticated-orcid":false,"given":"Parag G","family":"Patil","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, University of Michigan, Ann Arbor, Michigan, USA"},{"name":"Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, USA"},{"name":"Department of Neurology, University of Michigan, Ann Arbor, Michigan, USA"},{"name":"Department of Anesthesiology, University of Michigan, Ann Arbor, Michigan, 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