{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,24]],"date-time":"2026-08-24T06:19:15Z","timestamp":1787552355377,"version":"build-2736575974"},"reference-count":32,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,8,24]],"date-time":"2026-08-24T00:00:00Z","timestamp":1787529600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Oncol."],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Diffuse large B-cell lymphoma (DLBCL) is the most common and highly heterogeneous subtype of non-Hodgkin lymphoma, and accurate staging is essential for treatment planning and prognosis. This study explored the value of 2-[18F]fluoro-2-deoxy-D-glucose positron emission tomography\/computed tomography (18F-FDG PET\/CT) metabolic network connectivity for the clinical staging of DLBCL.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      Forty-two previously untreated patients (23 males, 19 females; aged 30-82 years) diagnosed as\n                      <jats:italic>de novo<\/jats:italic>\n                      DLBCL, not otherwise specified, were retrospectively analyzed (stage I, n=3; II, n=5; III, n=9; IV, n=25). Lesions were automatically delineated using a 41% SUVmax threshold. Four metabolic and four diffusion parameters were computed, and a radiomics-based lesion metabolic network was constructed for each patient with stage II-IV disease.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The degree Pearson correlation coefficient (DPCC) of the metabolic network differed significantly among stages II-IV (n=39, p&amp;lt;0.001) and between stage II (n=5) and stages III+IV (n=34) (p&amp;lt;0.001), whereas conventional metabolic, diffusion, and other network parameters showed no significant differences. DPCC decreased with increasing stage, indicating rising inter-lesion metabolic heterogeneity.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>The DPCC of 18F-FDG PET\/CT metabolic network connectivity is associated with clinical stage in DLBCL patients with multiple measurable lesions and may provide complementary network-level information. These exploratory findings require external validation in larger, multicenter cohorts.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fonc.2026.1856758","type":"journal-article","created":{"date-parts":[[2026,8,24]],"date-time":"2026-08-24T05:27:55Z","timestamp":1787549275000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["18F-FDG PET\/CT metabolic network connectivity in clinical staging of diffuse large B-cell lymphoma"],"prefix":"10.3389","volume":"16","author":[{"given":"Jinhai","family":"Zou","sequence":"first","affiliation":[{"name":"Department of Nuclear Medicine, Cangzhou Central Hospital","place":["Cangzhou, Hebei, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Han","family":"Zou","sequence":"additional","affiliation":[{"name":"Second Clinical Medical College of Lanzhou University","place":["Lanzhou, Gansu, 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