{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T06:00:24Z","timestamp":1783576824700,"version":"3.55.0"},"reference-count":67,"publisher":"IOP Publishing","issue":"14","license":[{"start":{"date-parts":[[2025,7,17]],"date-time":"2025-07-17T00:00:00Z","timestamp":1752710400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2025,7,17]],"date-time":"2025-07-17T00:00:00Z","timestamp":1752710400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/iopscience.iop.org\/info\/page\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/100008363","name":"Kr\u00e6ftens Bek\u00e6mpelse","doi-asserted-by":"crossref","award":["R302-A17443"],"award-info":[{"award-number":["R302-A17443"]}],"id":[{"id":"10.13039\/100008363","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100019180","name":"HORIZON EUROPE European Research Council","doi-asserted-by":"crossref","award":["804746"],"award-info":[{"award-number":["804746"]}],"id":[{"id":"10.13039\/100019180","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["iopscience.iop.org"],"crossmark-restriction":false},"short-container-title":["Phys. Med. Biol."],"published-print":{"date-parts":[[2025,7,20]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>\n                  <jats:italic>Objective.<\/jats:italic> Tumor heterogeneity, including differences in cell density and hypoxic fraction (HF), can impact the efficacy of radiation therapy (RT). Quantitative imaging biomarkers (QIBs) are required to assess spatial tumor heterogeneity to allow personalization of RT with biologically guided adaptive RT. Time-dependent diffusion MRI (TDD-MRI) derived metrics are promising QIBs, as they are potentially able to characterize different aspects of tissue microstructure better than conventional diffusion-weighted MRI (DW-MRI). Time-dependent diffusion contrast (TDDC), a recently proposed TDD-MRI method, has shown promise in characterizing tissue microstructure by subtracting images acquired with different timing parameters. The current study aimed to biologically validate the TDDC in a small cohort of glioblastoma patients and determine the added value of TDDC compared to conventional diffusion metrics. <jats:italic>Approach.<\/jats:italic> 12 patients with glioblastoma underwent MRI scanning before surgery. A total of 27 image-guided biopsy specimens were collected during surgery to obtain the histological cell density and HF. TDDC and conventional diffusion metrics (apparent diffusion coefficient (ADC) from a monoexponential model, mean diffusivity (MD) and mean kurtosis (MK) from the diffusion kurtosis imaging model) were obtained from the TDD-MRI acquisition in locations corresponding to the biopsies to determine the associations with histology. <jats:italic>Main results.<\/jats:italic> TDDC correlated with cell density (<jats:italic>\u03c1<\/jats:italic> = 0.71, <jats:italic>p<\/jats:italic> = 0.003), whereas no significant correlation was found between cell density and ADC (<jats:italic>\u03c1<\/jats:italic> = \u22120.12, <jats:italic>p<\/jats:italic> = 0.6), MD (<jats:italic>\u03c1<\/jats:italic> =\u22120.11, <jats:italic>p<\/jats:italic> = 0.7), or MK (<jats:italic>\u03c1<\/jats:italic> =0.03, <jats:italic>p<\/jats:italic> = 0.9). Moreover, no significant correlation was found between HF and any of the diffusion metrics (<jats:italic>p<\/jats:italic> &gt; 0.1). <jats:italic>Significance.<\/jats:italic> For the first time, we related a clinically implementable TDD-MRI method to histology in glioblastoma and found that TDDC was a better cell density biomarker compared to conventional diffusion metrics. This positions TDDC as a potential QIB for biologically guided adaptive RT.<\/jats:p>","DOI":"10.1088\/1361-6560\/adece1","type":"journal-article","created":{"date-parts":[[2025,7,7]],"date-time":"2025-07-07T18:52:47Z","timestamp":1751914367000},"page":"145029","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Mapping cell density and hypoxia in glioblastoma using time-dependent diffusion MRI: improved cell density assessment compared to conventional diffusion metrics"],"prefix":"10.1088","volume":"70","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6209-4239","authenticated-orcid":true,"given":"Minea","family":"Jokivuolle","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7044-442X","authenticated-orcid":false,"given":"Henrik","family":"Lundell","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8606-7641","authenticated-orcid":true,"given":"Kristoffer Hougaard","family":"Madsen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5715-6901","authenticated-orcid":false,"given":"Frantz Rom","family":"Poulsen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5093-5985","authenticated-orcid":false,"given":"Jeanette Krogh","family":"Petersen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1473-9872","authenticated-orcid":false,"given":"Mads Hjortdal","family":"Gr\u00f8nh\u00f8j","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2644-8263","authenticated-orcid":true,"given":"Frederik Severin Gr\u00e5e","family":"Harbo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9047-5787","authenticated-orcid":false,"given":"Martin","family":"Wirenfeldt","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1538-4361","authenticated-orcid":true,"given":"Rikke Hedegaard","family":"Dahlrot","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3452-2291","authenticated-orcid":false,"given":"Jesper Dupont","family":"Ewald","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5402-0045","authenticated-orcid":true,"given":"Anne Louise H\u00f8jmark","family":"Bisgaard","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7270-7967","authenticated-orcid":true,"given":"Faisal","family":"Mahmood","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"266","published-online":{"date-parts":[[2025,7,17]]},"reference":[{"key":"pmbadece1bib1","doi-asserted-by":"publisher","first-page":"e3841","DOI":"10.1002\/nbm.3841","article-title":"Imaging brain microstructure with diffusion MRI: practicality and applications","volume":"32","author":"Alexander","year":"2019","journal-title":"NMR Biomed."},{"key":"pmbadece1bib2","doi-asserted-by":"publisher","first-page":"870","DOI":"10.1016\/S1053-8119(03)00336-7","article-title":"How to correct susceptibility distortions in spin-echo echo-planar images: application to diffusion tensor imaging","volume":"20","author":"Andersson","year":"2003","journal-title":"Neuroimage"},{"key":"pmbadece1bib3","doi-asserted-by":"publisher","first-page":"942","DOI":"10.1093\/neuonc\/nos128","article-title":"Regional variation in histopathologic features of tumor specimens from treatment-naive glioblastoma correlates with anatomic and physiologic MR Imaging","volume":"14","author":"Barajas","year":"2012","journal-title":"Neuro-oncology"},{"key":"pmbadece1bib4","doi-asserted-by":"publisher","first-page":"285","DOI":"10.1016\/S0360-3016(97)00101-6","article-title":"Tumor hypoxia adversely affects the prognosis of carcinoma of the head and neck","volume":"38","author":"Brizel","year":"1997","journal-title":"Int. J. Radiat. Oncol. Biol. Phys."},{"key":"pmbadece1bib5","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2023.120409","article-title":"Diffusion MRI with free gradient waveforms on a high-performance gradient system: probing restriction and exchange in the human brain","volume":"283","author":"Chakwizira","year":"2023","journal-title":"Neuroimage"},{"key":"pmbadece1bib6","first-page":"1904","article-title":"The correlation between MR diffusion-weighted imaging and pathological grades on glioma","volume":"18","author":"Chen","year":"2014","journal-title":"Eur. Rev. Med. Pharmacol. Sci."},{"key":"pmbadece1bib7","doi-asserted-by":"publisher","first-page":"852","DOI":"10.1002\/1522-2594(200012)44:6<852::AID-MRM5>3.0.CO;2-A","article-title":"Water diffusion compartmentation and anisotropy at high b values in the human brain","volume":"44","author":"Clark","year":"2000","journal-title":"Magn. Reson. Med."},{"key":"pmbadece1bib8","article-title":"Physics of diffusion weighted and diffusion tensor imaging","author":"Concepci\u00f3n","year":"2016"},{"key":"pmbadece1bib9","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0160250","article-title":"Automatic analysis of cellularity in glioblastoma and correlation with ADC using trajectory analysis and automatic nuclei counting","volume":"11","author":"Eidel","year":"2016","journal-title":"PLoS One"},{"key":"pmbadece1bib10","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0169292","article-title":"Tumor infiltration in enhancing and non-enhancing parts of glioblastoma: a correlation with histopathology","volume":"12","author":"Eidel","year":"2017","journal-title":"PLoS One"},{"key":"pmbadece1bib11","doi-asserted-by":"publisher","first-page":"538","DOI":"10.1002\/jmri.22068","article-title":"Validation of functional diffusion maps (fDMs) as a biomarker for human glioma cellularity","volume":"31","author":"Ellingson","year":"2010","journal-title":"J. Magn. Reson. Imaging"},{"key":"pmbadece1bib12","doi-asserted-by":"publisher","first-page":"1323","DOI":"10.1016\/j.mri.2012.05.001","article-title":"3D slicer as an image computing platform for the Quantitative Imaging Network","volume":"30","author":"Fedorov","year":"2012","journal-title":"Magn. Reson. Imaging"},{"key":"pmbadece1bib13","doi-asserted-by":"publisher","first-page":"546","DOI":"10.1016\/S1043-4666(05)80003-1","article-title":"Cell membrane permeabilization and cellular collapse, followed by loss of dehydrogenase activity: early events in tumour necrosis factor-induced cytotoxicity","volume":"5","author":"Grooten","year":"1993","journal-title":"Cytokine"},{"key":"pmbadece1bib14","doi-asserted-by":"publisher","first-page":"357","DOI":"10.1038\/s41586-020-2649-2","article-title":"Array programming with NumPy","volume":"585","author":"Harris","year":"2020","journal-title":"Nature"},{"key":"pmbadece1bib15","doi-asserted-by":"publisher","first-page":"513","DOI":"10.1002\/mrm.21178","article-title":"Multispectral tissue characterization in a RIF-1 tumor model: monitoring the ADC and T2 responses to single-dose radiotherapy. Part II","volume":"57","author":"Henning","year":"2007","journal-title":"Magn. Reson. Med."},{"key":"pmbadece1bib16","doi-asserted-by":"publisher","first-page":"428","DOI":"10.1038\/s41571-024-00891-1","article-title":"Multiparametric MRI for characterization of the tumour microenvironment","volume":"21","author":"Hoffmann","year":"2024","journal-title":"Nat. Rev. Clin. Oncol."},{"key":"pmbadece1bib17","doi-asserted-by":"publisher","first-page":"4774","DOI":"10.1158\/0008-5472.CAN-17-3806","article-title":"Combined MR imaging of oxygen consumption and supply reveals tumor hypoxia and aggressiveness in prostate cancer patients","volume":"78","author":"Hompland","year":"2018","journal-title":"Cancer Res."},{"key":"pmbadece1bib18","doi-asserted-by":"publisher","first-page":"674","DOI":"10.1038\/nrclinonc.2012.171","article-title":"Imaging hypoxia to improve radiotherapy outcome","volume":"9","author":"Horsman","year":"2012","journal-title":"Nat. Rev. Clin. Oncol."},{"key":"pmbadece1bib19","doi-asserted-by":"publisher","first-page":"1892","DOI":"10.1096\/fj.06-5930fje","article-title":"Increased migration and metastatic potential of tumor cells expressing aquaporin water channels","volume":"20","author":"Hu","year":"2006","journal-title":"FASEB J."},{"key":"pmbadece1bib20","doi-asserted-by":"publisher","first-page":"6066","DOI":"10.1038\/s41467-023-41559-1","article-title":"Integrated molecular and multiparametric MRI mapping of high-grade glioma identifies regional biologic signatures","volume":"14","author":"Hu","year":"2023","journal-title":"Nat. Commun."},{"key":"pmbadece1bib21","doi-asserted-by":"publisher","first-page":"2464","DOI":"10.1016\/j.ejrad.2015.09.013","article-title":"Correlations between ADC values and molecular markers of Ki-67 and HIF-1\u03b1 in hepatocellular carcinoma","volume":"84","author":"Huang","year":"2015","journal-title":"Eur. J. Radiol."},{"key":"pmbadece1bib22","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2022.119277","article-title":"Neurite Exchange Imaging (NEXI): a minimal model of diffusion in gray matter with inter-compartment water exchange","volume":"256","author":"Jelescu","year":"2022","journal-title":"Neuroimage"},{"key":"pmbadece1bib23","doi-asserted-by":"publisher","first-page":"1432","DOI":"10.1002\/mrm.20508","article-title":"Diffusional kurtosis imaging: the quantification of non-gaussian water diffusion by means of magnetic resonance imaging","volume":"53","author":"Jensen","year":"2005","journal-title":"Magn. Reson. Med."},{"key":"pmbadece1bib24","doi-asserted-by":"publisher","first-page":"1312","DOI":"10.1096\/fj.00-0732fje","article-title":"Induction of HIF\u20131\u03b1 in response to hypoxia is instantaneous","volume":"15","author":"Jewell","year":"2001","journal-title":"FASEB J."},{"key":"pmbadece1bib25","doi-asserted-by":"publisher","first-page":"e4799","DOI":"10.1002\/nbm.4799","article-title":"Improving MR cell size imaging by inclusion of transcytolemmal water exchange","volume":"35","author":"Jiang","year":"2022","journal-title":"NMR Biomed."},{"key":"pmbadece1bib26","doi-asserted-by":"publisher","first-page":"1076","DOI":"10.1002\/mrm.25684","article-title":"Quantification of cell size using temporal diffusion spectroscopy","volume":"75","author":"Jiang","year":"2016","journal-title":"Magn. Reson. Med."},{"key":"pmbadece1bib27","doi-asserted-by":"publisher","first-page":"346","DOI":"10.1002\/mp.17453","article-title":"Assessing tumor microstructure with time\u2010dependent diffusion imaging: considerations and feasibility on clinical MRI and MRI\u2010Linac","volume":"52","author":"Jokivuolle","year":"2025","journal-title":"Med. Phys."},{"key":"pmbadece1bib28","doi-asserted-by":"publisher","first-page":"196","DOI":"10.1109\/TMI.2009.2035616","article-title":"Elastix: a toolbox for intensity-based medical image registration","volume":"29","author":"Klein","year":"2009","journal-title":"IEEE Trans. Med. Imaging"},{"key":"pmbadece1bib29","doi-asserted-by":"publisher","first-page":"863","DOI":"10.1016\/j.ijrobp.2010.12.063","article-title":"Value of diffusion-weighted magnetic resonance imaging for prediction and early assessment of response to neoadjuvant radiochemotherapy in rectal cancer: preliminary results","volume":"82","author":"Lambrecht","year":"2012","journal-title":"Int. J. Radiat. Oncol. Biol. Phys."},{"key":"pmbadece1bib30","doi-asserted-by":"publisher","first-page":"1104","DOI":"10.1002\/mrm.26195","article-title":"Optimal experimental design for filter exchange imaging: apparent exchange rate measurements in the healthy brain and in intracranial tumors","volume":"77","author":"Lampinen","year":"2017","journal-title":"Magn. Reson. Med."},{"key":"pmbadece1bib31","doi-asserted-by":"publisher","first-page":"401","DOI":"10.1148\/radiology.161.2.3763909","article-title":"MR imaging of intravoxel incoherent motions: application to diffusion and perfusion in neurologic disorders","volume":"161","author":"Le Bihan","year":"1986","journal-title":"Radiology"},{"key":"pmbadece1bib32","doi-asserted-by":"publisher","first-page":"2239","DOI":"10.1002\/mrm.26309","article-title":"Impact of transcytolemmal water exchange on estimates of tissue microstructural properties derived from diffusion MRI","volume":"77","author":"Li","year":"2017","journal-title":"Magn. Reson. Med."},{"key":"pmbadece1bib33","doi-asserted-by":"publisher","first-page":"3961","DOI":"10.1007\/s00330-022-09296-z","article-title":"Whole-tumor histogram analysis of diffusion-weighted imaging and dynamic contrast-enhanced MRI for soft tissue sarcoma: correlation with HIF-1alpha expression","volume":"33","author":"Li","year":"2023","journal-title":"Eur. Radiol."},{"key":"pmbadece1bib34","doi-asserted-by":"publisher","first-page":"551","DOI":"10.1016\/S0360-3016(00)00467-3","article-title":"Towards multidimensional radiotherapy (MD-CRT): biological imaging and biological conformality","volume":"47","author":"Ling","year":"2000","journal-title":"Int. J. Radiat. Oncol. Biol. Phys."},{"key":"pmbadece1bib35","doi-asserted-by":"publisher","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":"Louis","year":"2021","journal-title":"Neuro-oncology"},{"key":"pmbadece1bib36","doi-asserted-by":"publisher","first-page":"941","DOI":"10.1016\/j.tranon.2018.05.005","article-title":"Relationship of in vivo MR parameters to histopathological and molecular characteristics of newly diagnosed, nonenhancing lower-grade gliomas","volume":"11","author":"Luks","year":"2018","journal-title":"Transl. Oncol."},{"key":"pmbadece1bib37","doi-asserted-by":"publisher","first-page":"918","DOI":"10.1002\/nbm.3137","article-title":"High angular resolution diffusion imaging with stimulated echoes: compensation and correction in experiment design and analysis","volume":"27","author":"Lundell","year":"2014","journal-title":"NMR Biomed."},{"key":"pmbadece1bib38","doi-asserted-by":"publisher","first-page":"e3884","DOI":"10.1002\/nbm.3884","article-title":"Apparent diffusion coefficients in prostate cancer: correlation with molecular markers Ki\u201067, HIF\u20101\u03b1 and VEGF","volume":"31","author":"Ma","year":"2018","journal-title":"NMR Biomed."},{"key":"pmbadece1bib39","doi-asserted-by":"publisher","first-page":"89","DOI":"10.3390\/cancers13010089","article-title":"Restricted water diffusion in diffusion-weighted magnetic resonance imaging in pancreatic cancer is associated with tumor hypoxia","volume":"13","author":"Mayer","year":"2020","journal-title":"Cancers"},{"key":"pmbadece1bib40","doi-asserted-by":"publisher","first-page":"1034","DOI":"10.1002\/glia.20524","article-title":"Expression and function of water channels (aquaporins) in migrating malignant astrocytes","volume":"55","author":"Mccoy","year":"2007","journal-title":"Glia"},{"key":"pmbadece1bib41","doi-asserted-by":"publisher","first-page":"233","DOI":"10.1002\/mrm.1910190208","article-title":"Diffusion imaging using stimulated echoes","volume":"19","author":"Merboldt","year":"1991","journal-title":"Magn. Reson. Med."},{"key":"pmbadece1bib42","doi-asserted-by":"publisher","DOI":"10.18632\/oncotarget.24905","article-title":"Histogram analysis of ADC in rectal cancer: associations with different histopathological findings including expression of EGFR, Hif1-alpha, VEGF, p53, PD1, and KI 67. A preliminary study","volume":"9","author":"Meyer","year":"2018","journal-title":"Oncotarget"},{"key":"pmbadece1bib43","doi-asserted-by":"publisher","first-page":"1573","DOI":"10.1002\/mrm.24395","article-title":"Noninvasive mapping of water diffusional exchange in the human brain using filter-exchange imaging","volume":"69","author":"Nilsson","year":"2013a","journal-title":"Magn. Reson. Med."},{"key":"pmbadece1bib44","first-page":"p 5355","article-title":"An open-source framework for analysis of multidimensional diffusion MRI data implemented in MATLAB","author":"Nilsson","year":"2018"},{"key":"pmbadece1bib45","doi-asserted-by":"publisher","first-page":"345","DOI":"10.1007\/s10334-013-0371-x","article-title":"The role of tissue microstructure and water exchange in biophysical modelling of diffusion in white matter","volume":"26","author":"Nilsson","year":"2013b","journal-title":"Magn. Reson. Mater. Phys. Biol. Med."},{"key":"pmbadece1bib46","doi-asserted-by":"publisher","first-page":"3172","DOI":"10.1002\/mrm.27101","article-title":"On modeling","volume":"79","author":"Novikov","year":"2018","journal-title":"Magn. Reson. Med."},{"key":"pmbadece1bib47","doi-asserted-by":"publisher","first-page":"518","DOI":"10.1016\/j.immuni.2014.09.008","article-title":"HIF transcription factors, inflammation, and immunity","volume":"41","author":"Palazon","year":"2014","journal-title":"Immunity"},{"key":"pmbadece1bib48","doi-asserted-by":"publisher","first-page":"1902","DOI":"10.1158\/0008-5472.CAN-13-2511","article-title":"Noninvasive quantification of solid tumor microstructure using VERDICT MRI","volume":"74","author":"Panagiotaki","year":"2014","journal-title":"Cancer Res."},{"key":"pmbadece1bib49","first-page":"2825","article-title":"Scikit-learn: machine learning in Python","volume":"12","author":"Pedregosa","year":"2011","journal-title":"J. Mach. Learn. Res."},{"key":"pmbadece1bib50","doi-asserted-by":"publisher","first-page":"2259","DOI":"10.1016\/S0006-3495(98)77935-4","article-title":"A model for diffusive transport through a spherical interface probed by pulsed-field gradient NMR","volume":"74","author":"Price","year":"1998","journal-title":"Biophys. J."},{"key":"pmbadece1bib51","doi-asserted-by":"publisher","first-page":"1347","DOI":"10.1177\/0300060517712654","article-title":"Evaluation of cerebral glioma using 3T diffusion kurtosis tensor imaging and the relationship between diffusion kurtosis metrics and tumor cellularity","volume":"45","author":"Qi","year":"2017","journal-title":"J. Int. Med. Res."},{"key":"pmbadece1bib52","doi-asserted-by":"publisher","first-page":"58","DOI":"10.3389\/fphy.2017.00058","article-title":"Time-dependent diffusion MRI in cancer: tissue modeling and applications","volume":"5","author":"Reynaud","year":"2017","journal-title":"Front. Phys."},{"key":"pmbadece1bib53","doi-asserted-by":"publisher","first-page":"1534","DOI":"10.1016\/j.mri.2012.04.020","article-title":"Assessment of hepatocellular carcinoma using apparent diffusion coefficient and diffusion kurtosis indices: preliminary experience in fresh liver explants","volume":"30","author":"Rosenkrantz","year":"2012","journal-title":"Magn. Reson. Imaging"},{"key":"pmbadece1bib54","doi-asserted-by":"publisher","first-page":"154","DOI":"10.1039\/9781788019910-00154","article-title":"Disentangling intercompartment exchange from restricted diffusion","author":"Schillmaier","year":"2020"},{"key":"pmbadece1bib55","doi-asserted-by":"publisher","first-page":"646","DOI":"10.1016\/j.coph.2013.04.009","article-title":"Targeting the HIF pathway in inflammation and immunity","volume":"13","author":"Scholz","year":"2013","journal-title":"Curr. Opin. Pharmacol."},{"key":"pmbadece1bib56","doi-asserted-by":"publisher","first-page":"1586","DOI":"10.3390\/ijms18071586","article-title":"The role of tumor microenvironment in chemoresistance: to survive, keep your enemies closer","volume":"18","author":"Senthebane","year":"2017","journal-title":"Int. J. Mol. Sci."},{"key":"pmbadece1bib57","doi-asserted-by":"publisher","first-page":"2046","DOI":"10.3174\/ajnr.A7270","article-title":"Grading of pediatric intracranial tumors: are intravoxel incoherent motion and diffusional kurtosis imaging superior to conventional DWI?","volume":"42","author":"She","year":"2021","journal-title":"Am. J. Neuroradiol."},{"key":"pmbadece1bib58","doi-asserted-by":"publisher","first-page":"S208","DOI":"10.1016\/j.neuroimage.2004.07.051","article-title":"Advances in functional and structural MR image analysis and implementation as FSL","volume":"23","author":"Smith","year":"2004","journal-title":"Neuroimage"},{"key":"pmbadece1bib59","doi-asserted-by":"publisher","first-page":"59492","DOI":"10.18632\/oncotarget.17752","article-title":"Correlation between apparent diffusion coefficient (ADC) and cellularity is different in several tumors: a meta-analysis","volume":"8","author":"Surov","year":"2017","journal-title":"Oncotarget"},{"key":"pmbadece1bib60","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1016\/j.oraloncology.2017.12.001","article-title":"Influence of tumor and microenvironment characteristics on diffusion-weighted imaging in oropharyngeal carcinoma: a pilot study","volume":"77","author":"Swartz","year":"2018","journal-title":"Oral Oncol."},{"key":"pmbadece1bib61","doi-asserted-by":"publisher","first-page":"2523","DOI":"10.1063\/1.1673336","article-title":"Use of the stimulated echo in NMR diffusion studies","volume":"52","author":"Tanner","year":"1970","journal-title":"J. Chem. Phys."},{"key":"pmbadece1bib62","doi-asserted-by":"publisher","first-page":"270","DOI":"10.1006\/gyno.1998.5163","article-title":"Pimonidazole: a novel hypoxia marker for complementary study of tumor hypoxia and cell proliferation in cervical carcinoma","volume":"71","author":"Varia","year":"1998","journal-title":"Gynecol. Oncol."},{"key":"pmbadece1bib63","doi-asserted-by":"publisher","first-page":"394","DOI":"10.1016\/j.neuroimage.2016.08.016","article-title":"Denoising of diffusion MRI using random matrix theory","volume":"142","author":"Veraart","year":"2016","journal-title":"Neuroimage"},{"key":"pmbadece1bib64","doi-asserted-by":"publisher","first-page":"653","DOI":"10.1088\/0031-9155\/38\/6\/001","article-title":"A model for calculating tumour control probability in radiotherapy including the effects of inhomogeneous distributions of dose and clonogenic cell density","volume":"38","author":"Webb","year":"1993","journal-title":"Phys. Med. Biol."},{"key":"pmbadece1bib65","doi-asserted-by":"publisher","first-page":"327","DOI":"10.1002\/hbm.21454","article-title":"Probing tissue microstructure with restriction spectrum imaging: histological and theoretical validation","volume":"34","author":"White","year":"2013","journal-title":"Hum. Brain Mapp."},{"key":"pmbadece1bib66","doi-asserted-by":"publisher","first-page":"871","DOI":"10.1002\/mrm.29250","article-title":"Correlations between DWI, IVIM, and HIF\u20101\u03b1 expression based on MRI and pathology in a murine model of rhabdomyosarcoma","volume":"88","author":"Yin","year":"2022","journal-title":"Magn. Reson. Med."},{"key":"pmbadece1bib67","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0087024","article-title":"Non-Gaussian analysis of diffusion weighted imaging in head and neck at 3T: a pilot study in patients with nasopharyngeal carcinoma","volume":"9","author":"Yuan","year":"2014","journal-title":"PLoS One"}],"container-title":["Physics in Medicine &amp; Biology"],"original-title":[],"link":[{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1361-6560\/adece1","content-type":"text\/html","content-version":"am","intended-application":"text-mining"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1361-6560\/adece1\/pdf","content-type":"application\/pdf","content-version":"am","intended-application":"text-mining"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1361-6560\/adece1","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1361-6560\/adece1\/pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1361-6560\/adece1\/pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1361-6560\/adece1\/pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1361-6560\/adece1\/pdf","content-type":"application\/pdf","content-version":"am","intended-application":"similarity-checking"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1361-6560\/adece1\/pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,17]],"date-time":"2025-07-17T07:20:09Z","timestamp":1752736809000},"score":1,"resource":{"primary":{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1361-6560\/adece1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,17]]},"references-count":67,"journal-issue":{"issue":"14","published-online":{"date-parts":[[2025,7,17]]},"published-print":{"date-parts":[[2025,7,20]]}},"URL":"https:\/\/doi.org\/10.1088\/1361-6560\/adece1","relation":{},"ISSN":["0031-9155","1361-6560"],"issn-type":[{"value":"0031-9155","type":"print"},{"value":"1361-6560","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,7,17]]},"assertion":[{"value":"Mapping cell density and hypoxia in glioblastoma using time-dependent diffusion MRI: improved cell density assessment compared to conventional diffusion metrics","name":"article_title","label":"Article Title"},{"value":"Physics in Medicine & Biology","name":"journal_title","label":"Journal Title"},{"value":"paper","name":"article_type","label":"Article Type"},{"value":"\u00a9 2025 The Author(s). Published on behalf of Institute of Physics and Engineering in Medicine by IOP Publishing Ltd","name":"copyright_information","label":"Copyright Information"},{"value":"2025-03-26","name":"date_received","label":"Date Received","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2025-07-07","name":"date_accepted","label":"Date Accepted","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2025-07-17","name":"date_epub","label":"Online publication date","group":{"name":"publication_dates","label":"Publication dates"}}]}}