The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.
Fractional anisotropy and tumor cell density of the tumor core show positive correlation in diffusion tensor magnetic resonance imaging of malignant brain tumors
Abstract
A noninvasive technique for assessing tumor tissue characteristics is required to assist preoperative surgical planning for malignant brain tumors. Preoperative information on tumor cell density within a tumor would help better define the target for tumor biopsy, resulting in more accurate diagnosis and grading of malignant brain tumors. One possible source of this information is diffusion tensor imaging (DTI), although to date studies have focused on its ability to delineate white matter fiber tracks by fiber-tracking and to detect tumor infiltration around the tumor and normal white matter interface. However, the use of DTI for providing information on cell density has also been examined, although with the controversial results. In addition the exact relationships between cell density and the two key values that DTI provides, namely fractional anisotropy (FA) and mean diffusivity (MD), still need to be investigated. In the present study we performed a retrospective investigation of tumor cell density and FA and MD values in biopsy cases. We found that FA has a good positive correlation (R=0.75) and MD has a good negative correlation (R=0.70) with tumor cell density within the tumor core. Similar correlation was observed between the Ki-67 labeling index and FA (R=0.71) and MD (R=0.62). Thus, measurement of both FA and MD within the tumor core has a potential to provide detailed information on tumor cell density within the tumor. Although data obtained from DTI should be interpreted carefully and comprehensively with other imaging modalities such as positron emission tomography, DTI seems to be informative for planning the best biopsy target containing the highest cell density.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Some studies showed that FA can predict cell number and tissue density (60,61) and that higher FA could indicate greater tissue integrity.”
From Neuroanatomic differences associated with stress susceptibility and resilience (2016) · cites this paper as [61]
Citations
Cites
MR diffusion tensor spectroscopy and imaging
Basser, P. J., Mattiello, J., & LeBihan, D. (1994) · Biophysical Journal · doi:10.1016/s0006-3495(94)80775-1 · Cited by 5,970
Estimation of the Effective Self-Diffusion Tensor from the NMR Spin Echo
Basser, P. J., Mattiello, J., & Bihan, D. L. (1994) · Journal of Magnetic Resonance Series B · doi:10.1006/jmrb.1994.1037 · Cited by 3,656
Sugahara, T., Korogi, Y., Kochi, M., Ikushima, I., Shigematu, Y., Hirai, T., Okuda, T., Liang, L., Ge, Y., Komohara, Y., et al. (1999) · Journal of Magnetic Resonance Imaging · doi:10.1002/(sici)1522-2586(199901)9:1 · Cited by 1,151
Preoperative and Intraoperative Diffusion Tensor Imaging-based Fiber Tracking in Glioma Surgery
Nimsky, C., Ganslandt, O., Hastreiter, P., Wang, R., Benner, T., Sorensen, A. G., & Fahlbusch, R. (2005) · Neurosurgery · doi:10.1227/01.neu.0000144842.18771.30 · Cited by 442
Bello, L., Gambini, A., Castellano, A., Carrabba, G. G., Acerbi, F., Fava, E., Giussani, C. G., Cadioli, M., Blasi, V., Casarotti, A., et al. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.08.031 · Cited by 416
Brain white matter anatomy of tumor patients evaluated with diffusion tensor imaging
Mori, S., Frederiksen, K., van Zijl, P. C. M., Stieltjes, B., Kraut, M. A., Solaiyappan, M., & Pomper, M. G. (2002) · Annals of Neurology · doi:10.1002/ana.10137 · Cited by 281
Gupta, R. K., Cloughesy, T. F., Sinha, U. S., Garakian, J., Lazareff, J. A., Rubino, G. J., Rubino, L., Becker, D. P., Vinters, H. V., & Alger, J. R. (2000) · Journal of Neuro-Oncology · doi:10.1023/a:1006431120031 · Cited by 278
Provenzale, J. M., McGraw, P., Mhatre, P., Guo, A. C., & DeLong, D. M. (2004) · Radiology · doi:10.1148/radiol.2322030959 · Cited by 269
Kinoshita, M., Yamada, K., Hashimoto, N., Kato, A., Izumoto, S., Baba, T., Maruno, M., Nishimura, T., & Yoshimine, T. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2004.07.076 · Cited by 265
Self-citationTievsky, A. L., Ptak, T., & Farkas, J. (1999) · PubMed Central · Cited by 248
Cited by
Sorted by citations
Gliomas: diffusion kurtosis MR imaging in grading
Van Cauter, S., Veraart, J., Sijbers, J., Peeters, R. R., Himmelreich, U., De Keyzer, F., Van Gool, S. W., Van Calenbergh, F., De Vleeschouwer, S., Van Hecke, W., et al. (2012) · Radiology · doi:10.1148/radiol.12110927 · Cited by 340
Validation of functional diffusion maps (fDMs) as a biomarker for human glioma cellularity
Ellingson, B. M., Malkin, M. G., Rand, S. D., Connelly, J., Quinsey, C. S., LaViolette, P. S., Bedekar, D. P., & Schmainda, K. M. (2010) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.22068 · Cited by 278
Wang, S., Kim, S. J., Chawla, S., Wolf, R. L., Knipp, D., Vossough, A., O’Rourke, D. M., Judy, K. D., Poptani, H., & Melhem, E. R. (2011) · American Journal of Neuroradiology · doi:10.3174/ajnr.a2333 · Cited by 196
Neuroanatomic differences associated with stress susceptibility and resilience
Anacker, C., Scholz, J., O’Donnell, K. J., Allemang-Grand, R., Diorio, J., Bagot, R. C., Nestler, E. J., Hen, R., Lerch, J. P., & Meaney, M. J. (2016) · Biological Psychiatry · doi:10.1016/j.biopsych.2015.08.009 · Cited by 167
Szczepankiewicz, F., van Westen, D., Englund, E. M., Westin, C., Ståhlberg, F., Lätt, J., Sundgren, P. C., & Nilsson, M. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.07.038 · Cited by 169
Tsougos, I., Svolos, P., Kousi, E., Fountas, K. N., Theodorou, K., Fezoulidis, I. V., & Kapsalaki, E. Z. (2012) · Cancer Imaging · doi:10.1102/1470-7330.2012.0038 · Cited by 160
Differentiation between glioblastomas and solitary brain metastases using diffusion tensor imaging
Wang, S., Kim, S., Chawla, S., Wolf, R. L., Zhang, W., O’Rourke, D. M., Judy, K. D., Melhem, E. R., & Poptani, H. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.09.027 · Cited by 155
Ellingson, B. M. (2015) · Current Neurology and Neuroscience Reports · doi:10.1007/s11910-014-0506-0 · Cited by 132
Guo, J., Zhou, H.-Y., Zeng, J., Wang, K.-J., Lai, J., & Liu, Y.-X. (2020) · Petroleum Science · doi:10.1007/s12182-020-00488-0 · Cited by 126
Assessment of diffusion tensor imaging metrics in differentiating low-grade from high-grade gliomas
El-Serougy, L. G., Razek, A. A. K. A., Ezzat, A., Eldawoody, H. A. F., & El-Morsy, A. (2016) · The Neuroradiology Journal · doi:10.1177/1971400916665382 · Cited by 114
Svolos, P., Kousi, E., Kapsalaki, E. Z., Theodorou, K., Fezoulidis, I. V., Kappas, C., & Tsougos, I. (2014) · Cancer Imaging · doi:10.1186/1470-7330-14-20 · Cited by 115
Liu, X., Tian, W., Kolar, B. S., Yeaney, G. A., Qiu, X., Johnson, M. D., & EKHOLM, S. E. (2011) · Neuro-Oncology · doi:10.1093/neuonc/noq197 · Cited by 101
Bauer, A., Erly, W. K., Moser, F. G., Maya, M. M., & Nael, K. (2015) · Neuroradiology · doi:10.1007/s00234-015-1524-6 · Cited by 98
Yan, J., Zhao, Y., Chen, Y., Wang, W., Duan, W., Wang, L., Zhang, S., Ding, T., Liu, L., Sun, Q., et al. (2021) · EBioMedicine · doi:10.1016/j.ebiom.2021.103583 · Cited by 89
Verhoeven, J. S., Sage, C. A., Leemans, A., Hecke, W. V., Callaert, D. V., Peeters, R. R., Cock, P. D., Lagae, L. G., & Sunaert, S. G. (2009) · Human Brain Mapping · doi:10.1002/hbm.20880 · Cited by 86
LaViolette, P. S., Mickevicius, N. J., Cochran, E. J., Rand, S. D., Connelly, J., Bovi, J. A., Malkin, M. G., Mueller, W. M., & Schmainda, K. M. (2014) · Neuro-Oncology · doi:10.1093/neuonc/nou142 · Cited by 83
In vivo MRI signatures of hippocampal subfield pathology in intractable epilepsy
Goubran, M., Bernhardt, B. C., Cantor‐Rivera, D., Lau, J. C., Blinston, C. A., Hammond, R. R., de Ribaupierre, S., Burneo, J. G., Mirsattari, S. M., Steven, D. A., et al. (2015) · Human Brain Mapping · doi:10.1002/hbm.23090 · Cited by 79
Okita, Y., Kinoshita, M., Goto, T., Kagawa, N., Kishima, H., Shimosegawa, E., Hatazawa, J., Hashimoto, N., & Yoshimine, T. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.11.024 · Cited by 76
Self-citationLundemann, M. J., af Rosenschöld, P. M., Muhic, A., Larsen, V. A., Poulsen, H. S., Engelholm, S., Andersen, F. L., Kjær, A., Larsson, H. B. W., Law, I. G., et al. (2018) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-018-4180-3 · Cited by 75
Predicting survival in glioblastomas using diffusion tensor imaging metrics
Saksena, S., Jain, R., Narang, J., Scarpace, L. M., Schultz, L. R., Lehman, N. L., Hearshen, D., Patel, S. C., & Mikkelsen, T. (2010) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.22304 · Cited by 71
Park, Y. W., Han, K., Ahn, S. S., Choi, Y. S., Chang, J. H., Kim, S. H., Kang, S., Kim, E. H., & Lee, S. (2018) · American Journal of Neuroradiology · doi:10.3174/ajnr.a5569 · Cited by 69
Ellingson, B. M., Malkin, M. G., Rand, S. D., LaViolette, P. S., Connelly, J., Mueller, W. M., & Schmainda, K. M. (2010) · Journal of Neuro-Oncology · doi:10.1007/s11060-010-0293-7 · Cited by 65
Wang, S., Kim, S. J., Poptani, H., Woo, J. H., Mohan, S., Jin, R., Voluck, M. R., O’Rourke, D. M., Wolf, R. L., Melhem, E. R., et al. (2014) · American Journal of Neuroradiology · doi:10.3174/ajnr.a3871 · Cited by 61
Kinoshita, M., Goto, T., Okita, Y., Kagawa, N., Kishima, H., Hashimoto, N., & Yoshimine, T. (2009) · Journal of Neuro-Oncology · doi:10.1007/s11060-009-9979-0 · Cited by 58
Self-citationAnalysis of diffusion tensor imaging metrics for gliomas grading at 3T
Server, A., Graff, B. A., Josefsen, R., Orheim, T. E. D., Schellhorn, T., Nordhøy, W., & Nakstad, P. (2014) · European Journal of Radiology · doi:10.1016/j.ejrad.2013.12.023 · Cited by 59
White matter tract involvement in brain tumors: a diffusion tensor imaging analysis
Yen, P. S., Teo, B. T., Chiu, C., Chen, S. C., Chiu, T. L., & Su, C. F. (2009) · Surgical Neurology · doi:10.1016/j.surneu.2009.05.008 · Cited by 56
Imaging of Brain Tumors: Functional Magnetic Resonance Imaging and Diffusion Tensor Imaging
Gupta, A. K., Shah, A. D., Young, R. J., & Holodny, A. I. (2010) · Neuroimaging Clinics of North America · doi:10.1016/j.nic.2010.04.004 · Cited by 54
Structural correlates of memory performance with diffusion tensor imaging
Sasson, E., Doniger, G. M., Pasternak, O., & Assaf, Y. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.12.079 · Cited by 53
Jiang, R., Du, F., He, C., Gu, M., Zhenwu, K., & Li, J. (2014) · PLoS ONE · doi:10.1371/journal.pone.0112550 · Cited by 51
Jiang, R., Ma, Z., Dong, H., Sun, S., Zeng, X., & Li, X. (2016) · British Journal of Radiology · doi:10.1259/bjr.20160076 · Cited by 50
Li, L., Margolis, D., Deng, M., Cai, J., Yuan, L., Feng, Z., Min, X., Hu, Z., Hu, D., Liu, J., et al. (2014) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.24813 · Cited by 50
Mao, J., Zeng, W., Zhang, Q., Yang, Z., Yan, X., Zhang, H., Wang, M., Yang, G., Zhou, M., & Shen, J. (2020) · BMC Medical Imaging · doi:10.1186/s12880-020-00524-w · Cited by 49
Ceschin, R. C., Kurland, B. F., Abberbock, S. R., Ellingson, B. M., Okada, H., Jakacki, R. I., Pollack, I. F., & Panigrahy, A. (2015) · American Journal of Neuroradiology · doi:10.3174/ajnr.a4428 · Cited by 48
Onaygil, C., Kaya, H., Uğurlu, M. Ü., & Arıbal, E. (2016) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.25481 · Cited by 47
Arita, H., Kinoshita, M., Kagawa, N., Fujimoto, Y., Kishima, H., Hashimoto, N., & Yoshimine, T. (2011) · Cancer · doi:10.1002/cncr.26445 · Cited by 48
Self-citationDiagnostic and Prognostic Value of11C-Methionine PET for Nonenhancing Gliomas
Takano, K., Kinoshita, M., Arita, H., Okita, Y., Chiba, Y., Kagawa, N., Fujimoto, Y., Kishima, H., Kanemura, Y., Nonaka, M., et al. (2015) · American Journal of Neuroradiology · doi:10.3174/ajnr.a4460 · Cited by 46
Self-citationEllingson, B. M., LaViolette, P. S., Rand, S. D., Malkin, M. G., Connelly, J., Mueller, W. M., Prost, R. W., & Schmainda, K. M. (2010) · Magnetic Resonance in Medicine · doi:10.1002/mrm.22688 · Cited by 44
Value of diffusion tensor imaging in differentiating malignant from benign parotid gland tumors
Takumi, K., Fukukura, Y., Hakamada, H., Ideue, J., Kumagae, Y., & Yoshiura, T. (2017) · European Journal of Radiology · doi:10.1016/j.ejrad.2017.08.013 · Cited by 42
Zou, Q.-G., Xu, H.-B., Liu, F., Guo, W., Kong, X., & Wu, Y. (2011) · Clinical Radiology · doi:10.1016/j.crad.2011.05.001 · Cited by 41
Zhao, J., Li, J.-B., Wang, J.-Y., Wang, Y.-L., Liu, D.-W., Li, X.-B., Song, Y.-K., Tian, Y.-S., Yan, X., Li, Z.-H., et al. (2018) · NeuroImage: Clinical · doi:10.1016/j.nicl.2018.04.011 · Cited by 41
MR molecular imaging of HER‐2 in a murine tumor xenograft by SPIO labeling of anti‐HER‐2 affibody
Kinoshita, M., Yoshioka, Y., Okita, Y., Hashimoto, N., & Yoshimine, T. (2010) · Contrast Media & Molecular Imaging · doi:10.1002/cmmi.363 · Cited by 37
Self-citationGuo, L., Wang, G., Feng, Y., Yu, T., Guo, Y. F., Bai, X., & Ye, Z. (2016) · Radiation Oncology · doi:10.1186/s13014-016-0702-y · Cited by 37
Personalized fMRI Delineates Functional Regions Preserved within Brain Tumors
Cui, W., Wang, Y., Ren, J., Hubbard, C. S., Fu, X., Fang, S., Wang, D., Zhang, H., Li, Y., Li, L., et al. (2022) · Annals of Neurology · doi:10.1002/ana.26303 · Cited by 36
Liu, X., Tian, W., Kolar, B. S., Hu, R. M., Huang, Y., Huang, J. H., & EKHOLM, S. E. (2013) · Journal of Neuro-Oncology · doi:10.1007/s11060-013-1323-z · Cited by 36
Ma, L., & Song, Z. J. (2013) · Clinical Neurology and Neurosurgery · doi:10.1016/j.clineuro.2013.10.003 · Cited by 36
Spatial Organization and Correlations of Cell Nuclei in Brain Tumors
Jiao, Y., Berman, H. K., Kiehl, T.-R., & Salvatore Torquato, A. (2011) · PLoS ONE · doi:10.1371/journal.pone.0027323 · Cited by 36
Ellingson, B. M., Cloughesy, T. F., Lai, A., Nghiemphu, P. L., & Pope, W. B. (2011) · Journal of Neuro-Oncology · doi:10.1007/s11060-011-0567-8 · Cited by 35
Karavaeva, E., Harris, R. J., Leu, K., Shabihkhani, M., Yong, W. H., Pope, W. B., Lai, A., Nghiemphu, P. L., Liau, L. M., Chen, W., et al. (2014) · Molecular Imaging and Biology · doi:10.1007/s11307-014-0807-3 · Cited by 35
Xiong, J., Tan, W., Pan, J., Wang, Y., Yin, B., Zhang, J., & Geng, D. (2015) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.24958 · Cited by 36
Romano, A., Palizzi, S., Romano, A., Moltoni, G., Napoli, A. D., Maccioni, F., & Bozzao, A. (2023) · Cancers · doi:10.3390/cancers15030618 · Cited by 35
Malinsky, M., Peter, R., Hodneland, E., Lundervold, A. J., Lundervold, A., & Jan, J. (2013) · Journal of Digital Imaging · doi:10.1007/s10278-012-9561-8 · Cited by 33
Diffusion-Weighted MRI for Assessment of Early Cancer Treatment Response
Galbán, S., Brisset, J., Rehemtulla, A., Chenevert, T. L., Ross, B. D., & Galbán, C. J. (2010) · Current Pharmaceutical Biotechnology · doi:10.2174/138920110792246627 · Cited by 31
Diffusion Tensor Magnetic Resonance Imaging of Rat Glioma Models
Wang, S., & Zhou, J. (2012) · Journal of Computer Assisted Tomography · doi:10.1097/rct.0b013e3182685436 · Cited by 30
Kinoshita, M., Hashimoto, N., Goto, T., Yanagisawa, T., Okita, Y., Kagawa, N., Kishima, H., Tanaka, H., Fujita, N., Shimosegawa, E., et al. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.11.034 · Cited by 29
Self-citationWang, S., Chen, Y., Lal, B., Ford, E., Tryggestad, E. J., Armour, M., Yan, K., Laterra, J., & Zhou, J. (2011) · Journal of Neuro-Oncology · doi:10.1007/s11060-011-0719-x · Cited by 28
Toh, C., Wei, K., Ng, S.-H., Wan, Y., Castillo, M., & Lin, C. (2011) · American Journal of Neuroradiology · doi:10.3174/ajnr.a2871 · Cited by 27
Quantitative evaluation of diffusion tensor imaging for clinical management of glioma
Li, Y., & Zhang, W. (2018) · Neurosurgical Review · doi:10.1007/s10143-018-1050-1 · Cited by 27
Qu, J., Qin, L., Cheng, S., Leung, K. J., Li, X., Li, H., Dai, J., Jiang, T., Akgöz, A., Seethamraju, R. T., et al. (2015) · European Journal of Radiology · doi:10.1016/j.ejrad.2015.12.026 · Cited by 26
Li, F., Shi, W., Wang, D., Xu, Y., Li, H., He, J., & Zeng, Q. (2016) · Clinical Neurology and Neurosurgery · doi:10.1016/j.clineuro.2016.10.018 · Cited by 26
Liu, X., Yuan, J., Guang, Y., Wang, X., & Feng, Z. (2018) · Frontiers in Neuroscience · doi:10.3389/fnins.2018.00613 · Cited by 25
Kinoshita, M., Arita, H., Okita, Y., Kagawa, N., Kishima, H., Hashimoto, N., Tanaka, H., Watanabe, Y., Shimosegawa, E., Hatazawa, J., et al. (2016) · Journal of neurosurgery · doi:10.3171/2015.11.jns151848 · Cited by 25
Self-citationMagnetic resonance diffusion tensor imaging of the testis: Preliminary observations
Tsili, A. C., Ntorkou, A. A., Astrakas, L. G., Boukali, E., Giannakis, D., Maliakas, V., Sofikitis, N., & Argyropoulou, M. I. (2017) · European Journal of Radiology · doi:10.1016/j.ejrad.2017.08.037 · Cited by 24
Alterations in fiber pathways reveal brain tumor typology: a diffusion tractography study
Campanella, M., Ius, T., Škrap, M., & Fadiga, L. (2014) · PeerJ · doi:10.7717/peerj.497 · Cited by 24
Diffusion tensor imaging of cysts, hemangiomas, and metastases of the liver
Ertürk, Ş. M., Ichikawa, T., Kaya, E., Yapıcı, Ö., Özel, A., Mahmutoğlu, A. S., & Başak, M. (2013) · Acta Radiologica · doi:10.1177/0284185113504916 · Cited by 24
Chen, L., Hu, H., Chen, W., Wu, Q., Zhou, J., Chen, H., Xu, X., Shi, H., & Wu, F.-Y. (2021) · BMC Ophthalmology · doi:10.1186/s12886-021-02044-9 · Cited by 23
Clinical Impact of Integrated Physiologic Brain Tumor Imaging
Pillai, J. J., Zacà, D., & Choudhri, A. F. (2010) · Technology in Cancer Research & Treatment · doi:10.1177/153303461000900406 · Cited by 23
Zhang, P., & Liu, B. (2020) · ACS Chemical Neuroscience · doi:10.1021/acschemneuro.9b00698 · Cited by 22
Lin, Y., Wang, C., Wai, Y. Y., Wan, Y., Ng, S.-H., Chen, Y.-L., Liu, H., & Wang, J. (2009) · American Journal of Neuroradiology · doi:10.3174/ajnr.a1799 · Cited by 22
Multi-modal imaging of tumor cellularity and Tryptophan metabolism in human Gliomas
Jeong, J., Juhász, C., Mittal, S., Bosnyák, E., Kamson, D. O., Barger, G. R., Robinette, N. L., Kupsky, W. J., & Chugani, D. C. (2015) · Cancer Imaging · doi:10.1186/s40644-015-0045-1 · Cited by 21
Application of DTI and ARFI imaging in differential diagnosis of parotid tumours
Yu, J., Du, Y., Lü, Y., Zhang, W., Zhang, D., Wang, G., & Li, C. (2016) · Dentomaxillofacial Radiology · doi:10.1259/dmfr.20160100 · Cited by 20
Bilkey, J., Tata, A., McKee, T. D., Porcari, A. M., Bluemke, E., Woolman, M., Ventura, M., Eberlin, M. N., & Zarrine‐Afsar, A. (2016) · Analytical Chemistry · doi:10.1021/acs.analchem.6b02767 · Cited by 20
Münnich, T., Klein, J., Hattingen, E., Noack, A., Herrmann, E. M., Seifert, V., Senft, C., & Forster, M.-T. (2018) · Operative Neurosurgery · doi:10.1093/ons/opy062 · Cited by 19
El-Serougy, L. G., Razek, A. A. K. A., Mousa, A. E., Eldawoody, H. A. F., & El-Morsy, A. (2015) · The Egyptian Journal of Radiology and Nuclear Medicine · doi:10.1016/j.ejrnm.2015.08.005 · Cited by 19
Imaging biomarkers for antiangiogenic therapy in malignant gliomas
Leu, K., Pope, W. B., Cloughesy, T. F., Lai, A., Nghiemphu, P. L., Chen, W., Liau, L. M., & Ellingson, B. M. (2012) · CNS Oncology · doi:10.2217/cns.12.29 · Cited by 19
Mohan, S., Chawla, S., Wang, S., Verma, G., Skolnik, A. D., Brem, S. S., Peters, K. B., & Poptani, H. (2016) · CNS Oncology · doi:10.2217/cns-2016-0003 · Cited by 19
Li, X., Liang, Q., Zhuang, L., Zhang, X. M., Chen, T., Li, L., Liu, J., Calimente, H., Wei, Y., & Hu, J. (2015) · PLoS ONE · doi:10.1371/journal.pone.0135568 · Cited by 19
Advances in the Radiological Evaluation of and Theranostics for Glioblastoma
Hooper, G. W., Ansari, S. M. S., Johnson, J. M., & Ginat, D. T. (2023) · Cancers · doi:10.3390/cancers15164162 · Cited by 18
Brandão, L. A., & Castillo, M. (2016) · Neuroimaging Clinics of North America · doi:10.1016/j.nic.2016.06.004 · Cited by 18
Kinoshita, M., Uchikoshi, M., Tateishi, S., Miyazaki, S., Sakai, M., Ozaki, T., Asai, K., Fujita, Y., Matsuhashi, T., Kanemura, Y., et al. (2021) · Cancers · doi:10.3390/cancers13164067 · Cited by 17
Self-citationSvolos, P., Tsolaki, E. C., Theodorou, K., Fountas, K. N., Kapsalaki, E. Z., Fezoulidis, I. V., & Tsougos, I. (2013) · Clinical Imaging · doi:10.1016/j.clinimag.2013.03.006 · Cited by 17
Spalice, A., Nicita, F., Papetti, L., Ursitti, F., Biasi, C. D., Parisi, P., Ruggieri, M., & Iannetti, P. (2010) · Child s Nervous System · doi:10.1007/s00381-010-1192-0 · Cited by 17
Abd‐El‐Barr, M. M., Saleh, E., Huang, R. Y., & Golby, A. J. (2013) · Imaging in Medicine · doi:10.2217/iim.13.40 · Cited by 15
Determining mean fractional anisotropy using DDCOSY: preliminary results in biological tissues
Zong, F., Ancelet, L. R., Hermans, I. F., & Galvosas, P. (2016) · Magnetic Resonance in Chemistry · doi:10.1002/mrc.4492 · Cited by 15
Shams, B., Wang, Z., Roine, T., Aydogan, D. B., Vajkoczy, P., Lippert, C., Picht, T., & Fekonja, L. S. (2022) · Brain Communications · doi:10.1093/braincomms/fcac141 · Cited by 14
Yadav, V. K., Mohan, S., Agarwal, S., de Godoy, L. L., Rajan, A., Nasrallah, M. P., Bagley, S. J., Brem, S. S., Loevner, L. A., Poptani, H., et al. (2024) · Neuro-Oncology Advances · doi:10.1093/noajnl/vdae159 · Cited by 12
Diffusion-weighted and diffusion-tensor imaging of normal and diseased uterus
Bozkurt, D. K. (2015) · World Journal of Radiology · doi:10.4329/wjr.v7.i7.149 · Cited by 12
Huang, Z., Lu, C., Li, G., Li, Z., Sun, S., Zhang, Y., Hou, Z., & Xie, J. (2021) · Frontiers in Oncology · doi:10.3389/fonc.2021.627202 · Cited by 12
Wang, Z., Guan, F., Duan, W., Guo, Y. F., Pei, D., Qiu, Y., Wang, M., Xing, A., Liu, Z., Yu, B., et al. (2023) · CNS Neuroscience & Therapeutics · doi:10.1111/cns.14263 · Cited by 11
Marzi, S., Minosse, S., Vidiri, A., Piludu, F., & Giannelli, M. (2018) · Medical Physics · doi:10.1002/mp.13238 · Cited by 12
Woodworth, D. C., Pope, W. B., Liau, L. M., Kim, H. J., Lai, A., Nghiemphu, P. L., Cloughesy, T. F., & Ellingson, B. M. (2013) · Journal of Neuro-Oncology · doi:10.1007/s11060-013-1320-2 · Cited by 12
Wang, Y., Zhang, X., Cao, K., Li, Y., Li, X.-T., Qi, L., Tang, L., Wang, Z., & Gao, S. (2015) · Europe PMC (PubMed Central) · doi:10.3978/j.issn.1000-9604.2015.03.04 · Cited by 11
Pretreatment Evaluation of Glioma
Mohammadzadeh, A., Mohammadzadeh, V., Kooraki, S., Sotoudeh, H., Kadivar, S., Shakiba, M., Rasuli, B., Borhani, A., & Mohammadzadeh, M. (2016) · Neuroimaging Clinics of North America · doi:10.1016/j.nic.2016.06.006 · Cited by 11
Cepeda, S., García-García, S., Velasco-Casares, M., Fernández-Pérez, G. C., Zamora, T., Arrese, I., & Sarabia, R. (2021) · Brain Sciences · doi:10.3390/brainsci11020271 · Cited by 11
Hou, Z., Xu, C., Li, H., Zeng, C., Wang, J., Gao, Z., Zhang, M., Dou, W., Zhang, N., Zhang, L., et al. (2018) · World Neurosurgery · doi:10.1016/j.wneu.2018.02.095 · Cited by 10
Analysis of the pyramidal tract in tumor patients using diffusion tensor imaging
Cárdenes, R., Muñoz‐Moreno, E., Sarabia-Herrero, R., Rodríguez‐Velasco, M., Fuertes-Alija, J. J., & Martín‐Fernández, M. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.12.032 · Cited by 10
Vidyadharan, S., Rao, B. V. V. S. N. P., Yogeeswari, P., Kesavadas, C., & Rajagopalan, V. (2024) · Scientific Reports · doi:10.1038/s41598-024-70627-9 · Cited by 9
Diffusion MR Imaging of the Brain in Patients with Cancer
Debnam, J. M., & Schellingerhout, D. (2011) · International Journal of Molecular Imaging · doi:10.1155/2011/714021 · Cited by 9
Diffusion Tensor Imaging: Introduction and Applications to Brain Tumor Characterization
Wang, S., Kim, S., & Melhem, E. R. (2013) · Springer eBooks · doi:10.1007/978-1-4419-5858-7_2 · Cited by 9
Augelli, R., Ciceri, E. F. M., Ghimenton, C., Zoccatelli, G., Bucci, A., Nicolato, A., Beltramello, A., Pinna, G., & Ricciardi, G. K. (2019) · European Journal of Radiology · doi:10.1016/j.ejrad.2019.04.020 · Cited by 9
Batalov, A. I., Afandiev, R. M., Zakharova, N. E., Pogosbekyan, E. L., Shulgina, A. A., Kobyakov, G. L., Aa, P., & Pronin, I. (2022) · Neuroradiology · doi:10.1007/s00234-021-02888-4 · Cited by 8
Metadata
- Authors
- Kinoshita, M., Hashimoto, N., Goto, T., Kagawa, N., Kishima, H., Izumoto, S., Tanaka, H., Fujita, N., & Yoshimine, T.
- Affiliations
- The University of Osaka (JP)
- Corresponding author
- Kinoshita, Manabu
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2008-10
- Volume
- 43
- Issue
- 1
- Pages
- 29-35
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W2057822953
- Cited by
- 176
- References
- 28
- Citations by year
- 2026: 7 · 2025: 6 · 2024: 11 · 2023: 10 · 2022: 5 · 2021: 10 · 2020: 3 · 2019: 4 · 2018: 11 · 2017: 6 · 2016: 17 · 2015: 17 · 2014: 15 · 2013: 9 · 2012: 7
- FWCI
- 9.73
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Ministry of Education, Culture, Sports, Science and Technology (18591589, 19790997)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › MRI in cancer diagnosis
- Health Sciences › Medicine › Oncology › Glioma Diagnosis and Treatment
- Keywords
- fractional anisotropy, mean diffusivity, tumor cell density, malignant brain tumors, tumor core, diffusion tensor imaging, Ki-67 proliferation index, tumor grading, surgical planning
- MeSH terms
- Adult, Aged, Algorithms, Brain Neoplasms, Cell Count, Child, Child, Preschool, Female, Humans, Image Enhancement, Image Interpretation, Computer-Assisted, Male, Middle Aged, Sensitivity and Specificity, Statistics as Topic, Reproducibility of Results, Anisotropy, Diffusion Magnetic Resonance Imaging
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review