{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,26]],"date-time":"2026-10-26T18:44:01Z","timestamp":1793040241514,"version":"4.5.0"},"reference-count":48,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,12,22]],"date-time":"2025-12-22T00:00:00Z","timestamp":1766361600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2025,12,22]],"date-time":"2025-12-22T00:00:00Z","timestamp":1766361600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/100007316","name":"Division of Cancer Prevention, National Cancer Institute","doi-asserted-by":"publisher","award":["P30 CA022453"],"award-info":[{"award-number":["P30 CA022453"]}],"id":[{"id":"10.13039\/100007316","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Mol Imaging Biol"],"published-print":{"date-parts":[[2026,2]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>\n                      Increased amino acid transport in gliomas allows imaging of metabolically active tumor volume by PET. Tryptophan analog PET radiotracers can provide additional information by tracking tumoral metabolism via the upregulated immunosuppressive tryptophan-kynurenine pathway. We tested the recently developed tryptophan analog PET tracer [\n                      <jats:sup>18<\/jats:sup>\n                      F]-fluoro-ethyl-L-tryptophan ([\n                      <jats:sup>18<\/jats:sup>\n                      F]FETrp) for detecting post-treatment glioblastoma while using a non-invasive approach to generate parametric tryptophan metabolic maps and comparing them with static tracer uptake maps and contrast-enhanced MRI.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      Five patients (age: 22\u201367\u00a0years) with previously treated glioblastoma underwent [\n                      <jats:sup>18<\/jats:sup>\n                      F]FETrp PET\/CT imaging. A dynamic acquisition protocol sampled the brain and blood pool non-invasively using the FlowMotion Multiparametric PET software (Siemens Healthineers). Parametric brain images of the unidirectional uptake rate constant (K\n                      <jats:sub>i<\/jats:sub>\n                      ), characterizing irreversible tryptophan trapping and the volume of distribution (V\n                      <jats:sub>D<\/jats:sub>\n                      ) were fused with static uptake (SUV) maps and contrast-enhanced brain MRI. Voxels with elevated K\n                      <jats:sub>i<\/jats:sub>\n                      , V\n                      <jats:sub>D<\/jats:sub>\n                      , and SUV were defined, and their spatial associations with contrast-enhanced volumes were characterized by their % volume overlap and the distance between their centroids.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      A substantial spatial volume overlap was observed between MRI contrast-enhancing regions and elevated static [\n                      <jats:sup>18<\/jats:sup>\n                      F]FETrp uptake and V\n                      <jats:sub>D<\/jats:sub>\n                      . In contrast, the overlap between contrast-enhancing regions and elevated K\n                      <jats:sub>i<\/jats:sub>\n                      metabolic volumes was low (0\u201316%), with high K\n                      <jats:sub>i<\/jats:sub>\n                      areas extending deeper into non-enhancing brain (7\u201333\u00a0mm centroid distance). These non-enhancing high K\n                      <jats:sub>i<\/jats:sub>\n                      areas showed new contrast-enhancement on follow-up MRI, consistent with tumor progression.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>\n                      Areas of high tryptophan metabolism detected by [\n                      <jats:sup>18<\/jats:sup>\n                      F]FETrp PET-derived parametric (K\n                      <jats:sub>i<\/jats:sub>\n                      ) maps extend outside the contrast-enhancing glioblastoma mass in adjacent non-enhancing brain regions that can be missed or underestimated by static uptake images. Consequently, [\n                      <jats:sup>18<\/jats:sup>\n                      F]FETrp PET metabolic maps have the potential for enhanced detection of non-enhancing glioma infiltration for improved radiation or surgical treatment planning.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s11307-025-02075-4","type":"journal-article","created":{"date-parts":[[2025,12,22]],"date-time":"2025-12-22T19:51:49Z","timestamp":1766433109000},"page":"116-126","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Preliminary Results on the Added Value of Parametric Images Derived from 18F-fluoroethyl-L-tryptophan PET for Posttreatment Glioblastoma Assessment"],"prefix":"10.1007","volume":"28","author":[{"given":"Csaba","family":"Juh\u00e1sz","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Geoffrey R.","family":"Barger","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael","family":"Dominello","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Natasha L.","family":"Robinette","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Parthasarathi","family":"Chamiraju","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huailei","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5483-4452","authenticated-orcid":false,"given":"Otto","family":"Muzik","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,12,22]]},"reference":[{"issue":"12 Suppl 2","key":"2075_CR1","doi-asserted-by":"publisher","first-page":"iv1","DOI":"10.1093\/neuonc\/noad149","volume":"25","author":"QT Ostrom","year":"2023","unstructured":"Ostrom QT, Price M, Neff C, Cioffi G, Waite KA, Kruchko C, Barnholtz-Sloan JS (2023) CBTRUS statistical report: primary brain and other central nervous system tumors diagnosed in the United States in 2016-2020. Neuro Oncol 25(12 Suppl 2):iv1\u2013iv99","journal-title":"Neuro Oncol"},{"key":"2075_CR2","doi-asserted-by":"publisher","first-page":"170","DOI":"10.1038\/s41571-020-00447-z","volume":"18","author":"M Weller","year":"2021","unstructured":"Weller M, van den Bent M, Preusser M et al (2021) EANO guidelines on the diagnosis and treatment of diffuse gliomas of adulthood. Nat Rev Clin Oncol 18:170\u2013186","journal-title":"Nat Rev Clin Oncol"},{"key":"2075_CR3","doi-asserted-by":"publisher","first-page":"5187","DOI":"10.1200\/JCO.23.01059","volume":"41","author":"PY Wen","year":"2023","unstructured":"Wen PY, Van Den Bent MJ, Youssef G et al (2023) RANO 2.0: proposal for an update to the Response Assessment in Neuro-Oncology (RANO) criteria for high- and low-grade gliomas in adults. J Clin Oncol 41:5187\u20135199","journal-title":"J Clin Oncol"},{"key":"2075_CR4","doi-asserted-by":"publisher","first-page":"3160","DOI":"10.1200\/JCO.22.01579","volume":"41","author":"G Youssef","year":"2023","unstructured":"Youssef G, Rahman R, Bay C, Wang W, Lim-Fat MJ, Arnaout O, Bi WL, Cagney DN, Chang YS, Cloughesy TF, DeSalvo M, Ellingson BM, Flood TF, Gerstner ER, Gonzalez Castro LN, Guenette JP, Kim AE, Lee EQ, McFaline-Figueroa JR, Potter CA, Reardon DA, Huang RY, Wen PY (2023) Evaluation of standard response assessment in Neuro-Oncology, modified response assessment in Neuro-Oncology, and immunotherapy response assessment in Neuro-Oncology in newly diagnosed and recurrent glioblastoma. J Clin Oncol 41:3160\u20133171","journal-title":"J Clin Oncol"},{"key":"2075_CR5","doi-asserted-by":"publisher","first-page":"e29","DOI":"10.1016\/S1470-2045(23)00525-9","volume":"25","author":"NL Albert","year":"2024","unstructured":"Albert NL, Galldiks N, Ellingson BM, van den Bent MJ, Chang SM, Cicone F, de Groot J, Koh ES, Law I, Le Rhun E, Mair MJ, Minniti G, Rud\u00e0 R, Scott AM, Short SC, Smits M, Suchorska B, Tolboom N, Traub-Weidinger T, Tonn JC, Verger A, Weller M, Wen PY, Preusser M (2024) PET-based response assessment criteria for diffuse gliomas (PET RANO 1.0): a report of the RANO group. Lancet Oncol 25:e29\u2013e41","journal-title":"Lancet Oncol"},{"key":"2075_CR6","doi-asserted-by":"crossref","first-page":"1188","DOI":"10.1093\/neuonc\/nov225.24","volume":"17","author":"BM Ellingson","year":"2015","unstructured":"Ellingson BM, Bendszus M, Boxerman J et al (2015) Consensus recommendations for a standardized brain tumor imaging protocol in clinical trials. Neuro Oncol 17:1188\u20131198","journal-title":"Neuro Oncol"},{"key":"2075_CR7","doi-asserted-by":"publisher","first-page":"e062555","DOI":"10.1136\/bmjopen-2022-062555","volume":"13","author":"T Xiaoxue","year":"2023","unstructured":"Xiaoxue T, Yinzhong W, Meng Q, Lu X, Lei J (2023) Diagnostic value of PET with different radiotracers and MRI for recurrent glioma: a Bayesian network meta-analysis. BMJ Open 13:e062555","journal-title":"BMJ Open"},{"key":"2075_CR8","doi-asserted-by":"publisher","first-page":"758","DOI":"10.3174\/ajnr.A8565","volume":"46","author":"C Zhou","year":"2025","unstructured":"Zhou C, Kou Y, Zhou W, Zhao W, Fan Z, Jiao Y, Zhai Y, Liu J, Guo S, Ji P, Wang L (2025) Diagnostic value of PET tracers in differentiating glioma tumor recurrence from treatment-related changes: a systematic review and meta-analysis. AJNR Am J Neuroradiol 46:758\u2013765","journal-title":"AJNR Am J Neuroradiol"},{"key":"2075_CR9","doi-asserted-by":"publisher","first-page":"1199","DOI":"10.1093\/neuonc\/now058","volume":"18","author":"NL Albert","year":"2016","unstructured":"Albert NL, Weller M, Suchorska B et al (2016) Response assessment in Neuro-Oncology working group and European Association for Neuro-Oncology recommendations for the clinical use of PET imaging in gliomas. Neuro Oncol 18:1199\u20131208","journal-title":"Neuro Oncol"},{"key":"2075_CR10","doi-asserted-by":"publisher","first-page":"540","DOI":"10.1007\/s00259-018-4207-9","volume":"46","author":"I Law","year":"2019","unstructured":"Law I, Albert NL, Arbizu J et al (2019) Joint EANM\/EANO\/RANO practice guidelines\/SNMMI procedure standards for imaging of gliomas using PET with radiolabelled amino acids and [18F]FDG: version 1.0. Eur J Nucl Med Mol Imaging 46:540\u2013557","journal-title":"Eur J Nucl Med Mol Imaging"},{"key":"2075_CR11","doi-asserted-by":"publisher","first-page":"139","DOI":"10.1007\/s11060-021-03853-0","volume":"158","author":"DR Johnson","year":"2022","unstructured":"Johnson DR, Glenn CA, Javan R, Olson JJ (2022) Congress of Neurological Surgeons systematic review and evidence-based guidelines update on the role of imaging in the management of progressive glioblastoma in adults. J Neurooncol 158:139\u2013165","journal-title":"J Neurooncol"},{"key":"2075_CR12","doi-asserted-by":"publisher","first-page":"881","DOI":"10.1093\/neuonc\/noab013","volume":"23","author":"N Galldiks","year":"2021","unstructured":"Galldiks N, Niyazi M, Grosu AL, Kocher M, Langen KJ, Law I, Minniti G, Kim MM, Tsien C, Dhermain F, Soffietti R, Mehta MP, Weller M, Tonn JC (2021) Contribution of PET imaging to radiotherapy planning and monitoring in glioma patients - a report of the PET\/RANO group. Neuro Oncol 23:881\u2013893","journal-title":"Neuro Oncol"},{"key":"2075_CR13","doi-asserted-by":"publisher","first-page":"517","DOI":"10.1097\/RLU.0000000000004185","volume":"47","author":"F Fiz","year":"2022","unstructured":"Fiz F, Bini F, Gabriele E, Bottoni G, Garr\u00e8 ML, Marinozzi F, Milanaccio C, Verrico A, Massollo M, Bosio V, Lattuada M, Rossi A, Ramaglia A, Puntoni M, Morana G, Piccardo A (2022) Role of dynamic parameters of 18F-DOPA PET\/CT in pediatric gliomas. Clin Nucl Med 47:517\u2013524","journal-title":"Clin Nucl Med"},{"key":"2075_CR14","doi-asserted-by":"publisher","first-page":"2604","DOI":"10.3390\/diagnostics13152604","volume":"13","author":"R Hajri","year":"2023","unstructured":"Hajri R, Nicod-Lalonde M, Hottinger AF, Prior JO, Dunet V (2023) Prediction of glioma grade and IDH status using [18F]FET PET\/CT dynamic and multiparametric texture analysis. Diagnostics 13:2604","journal-title":"Diagnostics"},{"key":"2075_CR15","doi-asserted-by":"publisher","first-page":"345","DOI":"10.1038\/sj.jcbfm.9600199","volume":"26","author":"C Juh\u00e1sz","year":"2006","unstructured":"Juh\u00e1sz C, Chugani DC, Muzik O et al (2006) In vivo uptake and metabolism of alpha-[11C]methyl-L-tryptophan in human brain tumors. J Cereb Blood Flow Metab 26:345\u2013357","journal-title":"J Cereb Blood Flow Metab"},{"key":"2075_CR16","doi-asserted-by":"publisher","first-page":"409","DOI":"10.1007\/s11060-010-0327-1","volume":"102","author":"C Juh\u00e1sz","year":"2011","unstructured":"Juh\u00e1sz C, Muzik O, Chugani DC et al (2011) Differential kinetics of alpha-[11C]methyl-L-tryptophan on PET in low-grade brain tumors. J Neurooncol 102:409\u2013415","journal-title":"J Neurooncol"},{"key":"2075_CR17","doi-asserted-by":"publisher","first-page":"1058","DOI":"10.2967\/jnumed.111.097881","volume":"53","author":"B Alkonyi","year":"2012","unstructured":"Alkonyi B, Barger GR, Mittal S et al (2012) Accurate identification of recurrent gliomas from radiation injury by kinetic analysis of alpha-[11C]methyl-L-tryptophan PET. J Nucl Med 53:1058\u20131064","journal-title":"J Nucl Med"},{"key":"2075_CR18","doi-asserted-by":"publisher","first-page":"1373","DOI":"10.1093\/neuonc\/nou042","volume":"16","author":"DO Kamson","year":"2014","unstructured":"Kamson DO, Mittal S, Robinette NL, Muzik O, Kupsky WJ, Barger GR, Juh\u00e1sz C (2014) Increased tryptophan uptake on PET has strong independent prognostic value in patients with a previously treated high-grade glioma. Neuro Oncol 16:1373\u20131383","journal-title":"Neuro Oncol"},{"key":"2075_CR19","doi-asserted-by":"publisher","first-page":"1269","DOI":"10.1038\/nm934","volume":"9","author":"C Uyttenhove","year":"2003","unstructured":"Uyttenhove C, Pilotte L, Th\u00e9ate I, Stroobant V, Colau D, Parmentier N, Boon T, Van den Eynde BJ (2003) Evidence for a tumoral immune resistance mechanism based on tryptophan degradation by indoleamine 2,3-dioxygenase. Nat Med 9:1269\u20131274","journal-title":"Nat Med"},{"key":"2075_CR20","doi-asserted-by":"publisher","first-page":"460","DOI":"10.1007\/s11307-009-0225-0","volume":"11","author":"CEA Batista","year":"2009","unstructured":"Batista CEA, Juh\u00e1sz C, Muzik O et al (2009) Imaging correlates of differential expression of indoleamine 2,3-dioxygenase in human brain tumors. Mol Imaging Biol 11:460\u2013466","journal-title":"Mol Imaging Biol"},{"key":"2075_CR21","doi-asserted-by":"publisher","first-page":"230","DOI":"10.3171\/2008.10.JNS081141","volume":"111","author":"T Miyazaki","year":"2009","unstructured":"Miyazaki T, Moritake K, Yamada K, Hara N, Osago H, Shibata T, Akiyama Y, Tsuchiya M (2009) Indoleamine 2,3-dioxygenase as a new target for malignant glioma therapy. Laboratory investigation. J Neurosurg 111:230\u2013237","journal-title":"J Neurosurg"},{"key":"2075_CR22","doi-asserted-by":"crossref","unstructured":"Guastella AR, Michelhaugh SK, Klinger NV, Kupsky WJ, Polin LA, Muzik O, Juh\u00e1sz C, Mittal S (2016) Tryptophan PET Imaging of the Kynurenine Pathway in Patient-Derived Xenograft Models of Glioblastoma. Mol Imaging 15(pii): 1536012116644881","DOI":"10.1177\/1536012116644881"},{"key":"2075_CR23","doi-asserted-by":"publisher","first-page":"2159","DOI":"10.21873\/anticanres.11551","volume":"37","author":"PP Sordillo","year":"2017","unstructured":"Sordillo PP, Sordillo LA, Helson L (2017) The kynurenine pathway: a primary resistance mechanism in patients with glioblastoma. Anticancer Res 37:2159\u20132171","journal-title":"Anticancer Res"},{"key":"2075_CR24","doi-asserted-by":"publisher","first-page":"6650","DOI":"10.1158\/1078-0432.CCR-17-0120","volume":"23","author":"L Zhai","year":"2017","unstructured":"Zhai L, Ladomersky E, Lauing KL, Wu M, Genet M, Gritsina G et al (2017) Infiltrating T cells increase IDO1 expression in glioblastoma and contribute to decreased patient survival. Clin Cancer Res 23:6650\u20136660","journal-title":"Clin Cancer Res"},{"key":"2075_CR25","doi-asserted-by":"publisher","first-page":"14975","DOI":"10.1038\/s41598-024-65907-3","volume":"14","author":"A Jacquerie","year":"2024","unstructured":"Jacquerie A, Hoeben A, Eekers DBP, Postma AA, Vanmechelen M, de Smet F, Ackermans L, Anten M, Severens K, Zur Hausen A, Broen MPG, Beckervordersandforth J (2024) Prognostic relevance of high expression of kynurenine pathway markers in glioblastoma. Sci Rep 14:14975","journal-title":"Sci Rep"},{"key":"2075_CR26","doi-asserted-by":"publisher","DOI":"10.1016\/j.intimp.2024.113062","volume":"142","author":"Y Zhou","year":"2024","unstructured":"Zhou Y, Yao L, Ma T, Wang Z, Yin Y, Yang J, Zhang X, Zhang M, Qin G, Ma J, Zhao L, Liang J, Zhang J (2024) Indoleamine 2,3-dioxygenase-1 involves in CD8+T cell exhaustion in glioblastoma via regulating tryptophan levels. Int Immunopharmacol 142:113062. https:\/\/doi.org\/10.1016\/j.intimp.2024.113062","journal-title":"Int Immunopharmacol"},{"key":"2075_CR27","doi-asserted-by":"publisher","first-page":"805","DOI":"10.1007\/s11307-019-01430-6","volume":"22","author":"F John","year":"2020","unstructured":"John F, Muzik O, Mittal S, Juh\u00e1sz C (2020) Fluorine-18-labeled PET radiotracers for imaging tryptophan uptake and metabolism: a systematic review. Mol Imaging Biol 22:805\u2013819","journal-title":"Mol Imaging Biol"},{"key":"2075_CR28","doi-asserted-by":"publisher","first-page":"589","DOI":"10.1007\/s11307-016-1024-z","volume":"19","author":"Y Xin","year":"2017","unstructured":"Xin Y, Cai H (2017) Improved radiosynthesis and biological evaluations of L- and D-1-[18F]fluoroethyl-tryptophan for PET imaging of IDO-mediated kynurenine pathway of tryptophan metabolism. Mol Imaging Biol 19:589\u2013598","journal-title":"Mol Imaging Biol"},{"key":"2075_CR29","doi-asserted-by":"publisher","first-page":"1138","DOI":"10.1007\/s11307-019-01327-4","volume":"21","author":"Y Xin","year":"2019","unstructured":"Xin Y, Gao X, Liu L, Ge WP, Jain MK, Cai H (2019) Evaluation of L-1-[18F]fluoroethyl-tryptophan for PET imaging of cancer. Mol Imaging Biol 21:1138\u20131146","journal-title":"Mol Imaging Biol"},{"issue":"12","key":"2075_CR30","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1186\/s13550-022-00884-0","volume":"7","author":"AH Dias","year":"2022","unstructured":"Dias AH, Hansen AK, Munk OL, Gormsen LC (2022) Normal values for 18F-FDG uptake in organs and tissues measured by dynamic whole body multiparametric FDG PET in 126 patients. EJNMMI Res 7(12):15","journal-title":"EJNMMI Res"},{"key":"2075_CR31","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/jcbfm.1983.1","volume":"3","author":"C Patlak","year":"1983","unstructured":"Patlak C, Blasberg R, Fenstermacher J (1983) Graphical evaluation of blood-to-brain transfer constants from multiple-time uptake data. J Cereb Blood Flow Metab 3:1\u20137","journal-title":"J Cereb Blood Flow Metab"},{"key":"2075_CR32","doi-asserted-by":"publisher","first-page":"584","DOI":"10.1038\/jcbfm.1985.87","volume":"5","author":"C Patlak","year":"1985","unstructured":"Patlak C, Blasberg R (1985) Graphical evaluation of blood-to-brain transfer constants from multiple-time uptake data. Generalizations. J Cereb Blood Flow Metab 5:584\u2013590","journal-title":"J Cereb Blood Flow Metab"},{"key":"2075_CR33","doi-asserted-by":"publisher","first-page":"837","DOI":"10.1007\/s00259-020-05007-2","volume":"48","author":"AH Dias","year":"2021","unstructured":"Dias AH, Pedersen MF, Danielsen H, Munk OL, Gormsen LC (2021) Clinical feasibility and impact of fully automated multiparametric PET imaging using direct Patlak reconstruction: evaluation of 103 dynamic whole-body [18F]FDG PET\/CT scans. Eur J Nucl Med Mol Imaging 48:837\u2013850","journal-title":"Eur J Nucl Med Mol Imaging"},{"key":"2075_CR34","doi-asserted-by":"publisher","first-page":"4812","DOI":"10.1007\/s00330-018-5966-1","volume":"29","author":"G Fahrni","year":"2019","unstructured":"Fahrni G, Karakatsanis N, Di Domenicantonio G, Garibotto V, Zaidi H (2019) Does whole-body Patlak (18)F-FDG PET imaging improve lesion detectability in clinical oncology? Eur Radiol 29:4812\u20134821","journal-title":"Eur Radiol"},{"key":"2075_CR35","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1007\/s11307-023-01877-8","volume":"26","author":"O Muzik","year":"2024","unstructured":"Muzik O, Shields AF, Barger G, Jiang H, Chamiraju P, Juh\u00e1sz C (2024) The first human application of an F-18-labeled tryptophan analog for PET imaging of cancer. Mol Imaging Biol 26:29\u201335","journal-title":"Mol Imaging Biol"},{"key":"2075_CR36","doi-asserted-by":"publisher","first-page":"180","DOI":"10.1002\/jlcr.4027","volume":"66","author":"H Jiang","year":"2023","unstructured":"Jiang H, Guo Y, Cai H et al (2023) Automated radiosynthesis of 1-(2-[18F]fluoroethyl)-L-tryptophan ([18F]FETrp) for positron emission tomography (PET) imaging of cancer in humans. J Labelled Comp Radiopharm 66:180\u2013188","journal-title":"J Labelled Comp Radiopharm"},{"key":"2075_CR37","doi-asserted-by":"publisher","first-page":"648","DOI":"10.1007\/s00259-024-06926-0","volume":"52","author":"H Tang","year":"2025","unstructured":"Tang H, Wu Y, Cheng Z et al (2025) Assessment of image-derived input functions from small vessels for Patlak parametric imaging using total-body PET\/CT. Eur J Nucl Med Mol Imaging 52:648\u2013659","journal-title":"Eur J Nucl Med Mol Imaging"},{"issue":"6","key":"2075_CR38","doi-asserted-by":"publisher","first-page":"659","DOI":"10.1097\/00004647-199706000-00007","volume":"17","author":"O Muzik","year":"1997","unstructured":"Muzik O, Chugani DC, Chakraborty P, Mangner T, Chugani HT (1997) Analysis of [C-11]alpha-methyl-tryptophan kinetics for the estimation of serotonin synthesis rate in vivo. J Cereb Blood Flow Metab 17(6):659\u2013669","journal-title":"J Cereb Blood Flow Metab"},{"issue":"2","key":"2075_CR39","doi-asserted-by":"publisher","first-page":"208","DOI":"10.2967\/jnumed.116.179994","volume":"58","author":"SK Michelhaugh","year":"2017","unstructured":"Michelhaugh SK, Muzik O, Guastella AR, Klinger NV, Polin LA, Cai H, Xin Y, Mangner TJ, Zhang S, Juh\u00e1sz C, Mittal S (2017) Assessment of tryptophan uptake and kinetics using 1-(2\u201318F-fluoroethyl)-l-tryptophan and \u03b1-11C-methyl-l-tryptophan PET imaging in mice implanted with patient-derived brain tumor xenografts. J Nucl Med 58(2):208\u2013213","journal-title":"J Nucl Med"},{"key":"2075_CR40","doi-asserted-by":"publisher","first-page":"239","DOI":"10.1007\/s11060-018-2869-6","volume":"139","author":"AR Guastella","year":"2018","unstructured":"Guastella AR, Michelhaugh SK, Klinger NV, Fadel HA, Kiousis S, Ali-Fehmi R, Kupsky WJ, Juh\u00e1sz C, Mittal S (2018) Investigation of the aryl hydrocarbon receptor and the intrinsic tumoral component of the kynurenine pathway of tryptophan metabolism in primary brain tumors. J Neurooncol 139:239\u2013249","journal-title":"J Neurooncol"},{"key":"2075_CR41","doi-asserted-by":"publisher","first-page":"104657","DOI":"10.1016\/j.critrevonc.2025.104657","volume":"209","author":"F Gagliardi","year":"2025","unstructured":"Gagliardi F, De Domenico P, Snider S, Roncelli F, Comai S, Mortini P (2025) Immunomodulatory mechanisms driving tumor escape in glioblastoma: the central role of IDO and tryptophan metabolism in local and systemic immunotolerance. Crit Rev Oncol Hematol 209:104657","journal-title":"Crit Rev Oncol Hematol"},{"key":"2075_CR42","doi-asserted-by":"publisher","first-page":"321","DOI":"10.1038\/nbt0415-321","volume":"33","author":"C Sheridan","year":"2015","unstructured":"Sheridan C (2015) IDO inhibitors move center stage in immuno-oncology. Nat Biotechnol 33:321\u2013322","journal-title":"Nat Biotechnol"},{"key":"2075_CR43","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejphar.2021.173921","volume":"896","author":"M Ala","year":"2021","unstructured":"Ala M (2021) The footprint of kynurenine pathway in every cancer: a new target for chemotherapy. Eur J Pharmacol 896:173921","journal-title":"Eur J Pharmacol"},{"key":"2075_CR44","doi-asserted-by":"publisher","first-page":"111","DOI":"10.1007\/s11060-018-03013-x","volume":"141","author":"RV Lukas","year":"2019","unstructured":"Lukas RV, Juh\u00e1sz C, Wainwright DA, James CD, Kennedy E, Stupp R, Lesniak MS (2019) Imaging tryptophan uptake with positron emission tomography in glioblastoma patients treated with indoximod. J Neurooncol 141:111\u2013120","journal-title":"J Neurooncol"},{"key":"2075_CR45","doi-asserted-by":"publisher","first-page":"264","DOI":"10.1093\/neuonc\/noy169","volume":"21","author":"F John","year":"2019","unstructured":"John F, Bosny\u00e1k E, Robinette NL, Amit-Yousif AJ, Barger GR, Shah KD, Michelhaugh SK, Klinger NV, Mittal S, Juh\u00e1sz C (2019) Multimodal imaging-defined subregions in newly diagnosed glioblastoma: impact on overall survival. Neuro Oncol 21:264\u2013273","journal-title":"Neuro Oncol"},{"key":"2075_CR46","doi-asserted-by":"publisher","DOI":"10.1177\/1536012119885222","volume":"18","author":"F John","year":"2019","unstructured":"John F, Robinette NL, Amit-Yousif AJ, Bosny\u00e1k E, Barger GR, Shah KD, Mittal S, Juh\u00e1sz C (2019) Multimodal imaging of nonenhancing glioblastoma regions. Mol Imaging 18:1536012119885222","journal-title":"Mol Imaging"},{"key":"2075_CR47","doi-asserted-by":"publisher","first-page":"1505","DOI":"10.1088\/0031-9155\/55\/5\/016","volume":"55","author":"G Wang","year":"2010","unstructured":"Wang G, Qi J (2010) Acceleration of the direct reconstruction of linear parametric images using nested algorithms. Phys Med Biol 55:1505\u20131517","journal-title":"Phys Med Biol"},{"key":"2075_CR48","doi-asserted-by":"publisher","first-page":"501","DOI":"10.1007\/s00259-018-4153-6","volume":"46","author":"A Rahmim","year":"2019","unstructured":"Rahmim A, Lodge MA, Karakatsanis NA, Panin VY, Zhou Y, McMillan A et al (2019) Dynamic whole-body PET imaging: principles, potentials and applications. Eur J Nucl Med Mol Imaging 46:501\u2013518","journal-title":"Eur J Nucl Med Mol Imaging"}],"container-title":["Molecular Imaging and Biology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11307-025-02075-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11307-025-02075-4","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11307-025-02075-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T05:02:06Z","timestamp":1772859726000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11307-025-02075-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,22]]},"references-count":48,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2026,2]]}},"alternative-id":["2075"],"URL":"https:\/\/doi.org\/10.1007\/s11307-025-02075-4","relation":{},"ISSN":["1536-1632","1860-2002"],"issn-type":[{"value":"1536-1632","type":"print"},{"value":"1860-2002","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12,22]]},"assertion":[{"value":"18 July 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 November 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 December 2025","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 December 2025","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The study was supported by the Karmanos Cancer Institute SRIG and the National Cancer Institute (P30 CA022453). The Cyclotron and Radiochemistry Core is supported, in part, by NIH Center grant P30 CA022453 to the Karmanos Cancer Institute at Wayne State University. No other potential conflict of interest relevant to this article was reported.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure"}}]}}