{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,19]],"date-time":"2026-03-19T04:17:46Z","timestamp":1773893866054,"version":"3.50.1"},"reference-count":45,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2025,12,27]],"date-time":"2025-12-27T00:00:00Z","timestamp":1766793600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2025,12,27]],"date-time":"2025-12-27T00:00:00Z","timestamp":1766793600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["aapm.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Medical Physics"],"published-print":{"date-parts":[[2026,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Sacral chordoma (SC) is a rare and locally aggressive tumor, characterized by a high risk of local recurrence (LR). Advanced imaging biomarkers capturing tumor heterogeneity and treatment response may help refine patient stratification and improve outcomes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>This study aims to explore the potential of microstructural parameters and habitat analysis derived from diffusion\u2010weighted MRI (DW\u2010MRI) to characterize intratumoral heterogeneity, assess treatment\u2010induced changes, following carbon ion radiotherapy (CIRT), and investigate their association with recurrence patterns in SC patients.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      A retrospective analysis was performed on 40 SC patients treated with CIRT. Microstructural parameters\u2014cell radius (\n                      <jats:italic>R<\/jats:italic>\n                      ), eccentricity (ecc), diffusion coefficient (\n                      <jats:italic>D<\/jats:italic>\n                      ), cell volume fraction (vf), and apparent cellularity (\u03c1\u2010app)\u2014were estimated from DW\u2010MRI using a computational model based on Monte Carlo simulations. Longitudinal changes were assessed from DW\u2010MRI scans acquired at baseline, first follow\u2010up (3 months after CIRT), and, for LR patients, at the time of recurrence. Habitat imaging analysis was performed by applying\n                      <jats:italic>K<\/jats:italic>\n                      \u2010means clustering (\n                      <jats:italic>k<\/jats:italic>\n                      \u00a0=\u00a02) independently to each map of the six microstructural parameters. A joint clustering approach was then used to combine these binary maps, resulting in 64 unique microstructural configurations (2\n                      <jats:sup>6<\/jats:sup>\n                      habitats). The spatial distribution of these habitats was quantified within the gross tumor volume (GTV) and recurrence regions. Associations with clinical outcomes were explored by analyzing habitat fractions in patients with early (early\u2010LR) vs. late recurrence (late\u2010LR), and by comparing recurrences predominantly located within the high\u2010dose clinical target volume irradiated during CIRT (in\u2010field\u2010LR) vs. those partially outside the target (marginal\u2010LR). Statistical tests, multiregional spatial interaction (MSI) matrix analysis, Cox regression, Spearman correlation and Kaplan\u2013Meier survival analyses were performed.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Treatment\u2010induced changes in microstructural parameters were statistically significant in both local control (LC) and LR patients, characterized by an increase in cell radius, eccentricity, ADC, and diffusion, and a concomitant reduction in cell volume fraction and apparent cellularity. This pattern suggested a reduction in cell density and increased tissue disorganization, likely reflecting CIRT\u2010induced cell damage and extracellular matrix remodeling. Habitat analysis revealed distinct microstructural configurations associated with clinical outcome. A favorable microstructural pattern\u2014high diffusivity and low cellularity\u2014was predominantly found in LC patients (HABITAT47_212221), whereas more aggressive configurations (low diffusivity and high cellularity) were enriched in LR patients (HABITAT26_122112 and HABITAT28_122122). Univariate Cox regression identified these high\u2010risk habitats as significantly associated with recurrence (hazard ratio\u00a0&gt;\u00a01,\n                      <jats:italic>p<\/jats:italic>\n                      \u2010value\u00a0&lt;\u00a00.05). Moreover, habitat fractions showed a progressive trend across recurrence risk subgroups (LC, late\u2010LR, early\u2010LR; LC, in\u2010field\u2010LR, marginal\u2010LR), while spatial analyses revealed increased co\u2010localization of high\u2010risk habitats in LR patients based on MSI matrix analysis. Finally, Kaplan\u2013Meier analysis based on hazard ratios predicted at first follow\u2010up using Cox models trained on baseline habitat fractions revealed significant differences in progression\u2010free survival.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>This study demonstrates the potential of DW\u2010MRI\u2010derived microstructural parameters and habitat imaging to capture intratumoral heterogeneity, assess treatment\u2010induced microstructural changes, and identify high\u2010risk patterns associated with LR in SC patients treated with CIRT. These findings support the integration of microstructural and habitat\u2010based imaging as a non\u2010invasive tool for risk stratification and personalized treatment planning in CIRT for SC.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/mp.70208","type":"journal-article","created":{"date-parts":[[2025,12,27]],"date-time":"2025-12-27T17:31:10Z","timestamp":1766856670000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Microstructural profiling and habitat analysis to characterize treatment outcome patterns in Sacral Chordomas treated with carbon ions"],"prefix":"10.1002","volume":"53","author":[{"given":"Letizia","family":"Morelli","sequence":"first","affiliation":[{"name":"Department of Electronics, Information and Bioengineering Politecnico di Milano  Milan 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