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Yamashita Koji Last modified date:2022.06.19

Assistant Professor / Faculty of Medical Sciences

Graduate School

 Reseacher Profiling Tool Kyushu University Pure
Academic Degree
M.D., phD
Country of degree conferring institution (Overseas)
Field of Specialization
Diagnostic Radiology
Total Priod of education and research career in the foreign country
Research Interests
  • Predicting gene mutation status using MR imaging in gliomas
    keyword : Glioma, MR imaging, Radiogenomics
  • Diagnostic utility of the combination of intravoxel incoherent motion MR imaging in diagnosing brain tumors
    keyword : IVIM; MR; perfusion; GBM; PCNSL
  • MR imaging of brain tumors using arterial spin labeling
    keyword : ASL,MRI, brain tumor
  • Diagnosis of middle-ear cholesteatoma on diffusion-weighted imaing
    keyword : Cholesteatoma, temporal bone, MRI, Diffusion weighted imaging
Academic Activities
1. Koji Yamashita, Ryotaro Kamei, Hiroshi Sugimori, Takahiro Kuwashiro, So Tokunaga, Keisuke Kawamata, Kiyomi Furuya, Shino Harada, Junki Maehara, Yasushi Okada, Tomoyuki Noguchi, Interobserver reliability on intravoxel incoherent motion imaging in patients with acute ischemic stroke. , AJNR Am J Neuroradiol., 10.3174/ajnr.A7486 , 10.3174/ajnr.A7486 , 2022.05.
2. Yamashita Koji, Hiwatashi Akio, Osamu Togao, Kazufumi Kikuchi, Koji Yoshimoto, Satoshi O Suzuki, Hiroshi Honda, MR imaging Based Analysis of Glioblastoma multiforme: Estimation of IDH1 Mutation Status., AJNR Am J Neuroradiol., 37, 1, 58-65, 37(1):58-65, 2016.01, BACKGROUND AND PURPOSE: Glioblastoma multiforme is highly aggressive and the most common type of primary malignant brain tumor in adults. Imaging biomarkers may provide prognostic information for patients with this condition. Patients with glioma with isocitrate dehydrogenase 1 (IDH1) mutations have a better clinical outcome than those without such mutations. Our purpose was to investigate whether the IDH1 mutation status in glioblastoma multiforme can be predicted by using MR imaging.

MATERIALS AND METHODS: We retrospectively studied 55 patients with glioblastoma multiforme with wild type IDH1 and 11 patients with mutant IDH1. Absolute tumor blood flow and relative tumor blood flow within the enhancing portion of each tumor were measured by using arterial spin-labeling data. In addition, the maximum necrosis area, the percentage of cross-sectional necrosis area inside the enhancing lesions, and the minimum and mean apparent diffusion coefficients were obtained from contrast-enhanced T1-weighted images and diffusion-weighted imaging data. Each of the 6 parameters was compared between patients with wild type IDH1 and mutant IDH1 by using the Mann-Whitney U test. The performance in discriminating between the 2 entities was evaluated by using receiver operating characteristic analysis.

RESULTS: Absolute tumor blood flow, relative tumor blood flow, necrosis area, and percentage of cross-sectional necrosis area inside the enhancing lesion were significantly higher in patients with wild type IDH1 than in those with mutant IDH1 (P < .05 each). In contrast, no significant difference was found in the ADCminimum and ADCmean. The area under the curve for absolute tumor blood flow, relative tumor blood flow, percentage of cross-sectional necrosis area inside the enhancing lesion, and necrosis area were 0.850, 0.873, 0.739, and 0.772, respectively.

CONCLUSIONS: Tumor blood flow and necrosis area calculated from MR imaging are useful for predicting the IDH1 mutation status..
3. Yamashita Koji, Takashi Yoshiura, Hiwatashi Akio, Osamu Togao, Kazufumi Kikuchi, Makoto Obara, Nozomu Matsumoto, Hiroshi Honda, High-resolution Three-dimensional Diffusion-weighted Imaging of Middle Ear Cholesteatoma at 3.0 T MRI: Usefulness of 3D Turbo Field-echo with Diffusion-Sensitized Driven-equilibrium Preparation (TFE-DSDE) Compared to Single-shot Echo-planar Imaging., Eur J Radiol., pii: S0720-048X(13)00214-3. 10.1016/j.ejrad.2013.04.018. , 82, 9, 471-475, 2013.09, Objective: To prospectively evaluate the usefulness of a newly developed high-resolution three-dimensional diffusion-weighted imaging method, turbo field-echo with diffusion-sensitized driven-equilibrium (TFE–DSDE) in diagnosing middle-ear cholesteatoma by comparing it to conventionalsingle-shot echo-planar diffusion-weighted imaging (SS-EP DWI).Materials and methods: Institutional review board approval and informed consent from all participantswere obtained. We studied 30 patients with preoperatively suspected acquired cholesteatoma. Eachpatient underwent an MR examination including both SS-EP DWI and DSDE-TFE using a 3.0 T MR scan-ner. Images of the 30 patients (60 temporal bones including 30 with and 30 without cholesteatoma) werereviewed by two independent neuroradiologists. The confidence level for the presence of cholesteatomawas graded on a scale of 0–2 (0 = definite absence, 1 = equivocal, 2 = definite presence). Interobserveragreement as well as sensitivity, specificity, and accuracy for detection were assessed for the two review-ers.Results: Excellent interobserver agreement was shown for TFE–DSDE ( = 0.821) whereas fair agreementwas obtained for SS-EP DWI ( = 0.416). TFE–DSDE was associated with significantly higher sensitivity(83.3%) and accuracy (90.0%) compared to SS-EP DWI (sensitivity = 35.0%, accuracy = 66.7%; p < 0.05). Nosignificant difference was found in specificity (96.7% for TFE–DSDE, 98.3% for SS-EP DWI)Conclusion: With increased spatial resolution and reduced susceptibility artifacts, TFE–DSDE improvesthe accuracy in diagnosing acquired middle ear cholesteatomas compared to SS-EP DWI..
4. Yamashita K, Yoshiura T, Hiwatashi A, Togao O, Yoshimoto K, Suzuki SO, Abe K, Kikuchi K, Maruoka Y, Mizoguchi M, Iwaki T, Honda H, Differentiating primary central nervous system lymphoma from glioblastoma multiforme: assessment using arterial spin labeling, diffusion weighted imaging, and 18F-fluorodeoxyglucose positron emission tomography., Neuroradiology, 55, 2, 135-143, 2013.02, Introduction: Our purpose was to evaluate the diagnostic performance of arterial spin labeling (ASL) perfusion imaging, diffusion-weighted imaging (DWI), and 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) in differentiating primary central nervous system lymphomas (PCNSLs) from glioblastoma multiformes (GBMs). Methods: Fifty-six patients including 19 with PCNSL and 37 with GBM were retrospectively studied. From the ASL data, an absolute tumor blood flow (aTBF) and a relative tumor blood flow (rTBF) were obtained within the enhancing portion of each tumor. In addition, the minimum apparent diffusion coefficient (ADCmin) and the maximum standard uptake value (SUVmax) were obtained from DWI and FDG-PET data, respectively. Each of the four parameters was compared between PCNSLs and GBMs using Kruskal–Wallis test. The performance in discriminating between PCNSLs and GBMs was evaluated using the receiver-operating characteristics analysis. Area-under-the curve (AUC) values were compared among the four parameters using a nonparametric method.
Results: The aTBF, rTBF, and ADCmin were significantly higher in GBMs (mean aTBF ± SD = 91.6±56.0 mL/100 g/ min, mean rTBF ± SD = 2.61±1.61, mean ADCmin ± SD = 0.78±0.19×10^−3 mm^2/s) than in PCNSLs (mean aTBF ± SD = 37.3±10.5 mL/100 g/min, mean rTBF ± SD = 1.24±0.37, mean ADCmin ± SD = 0.61±0.13×10^−3 mm^2/s) (p< 0.005, respectively). In addition, SUVmax was significantly
lower in GBMs (mean ± SD = 13.1±6.34) than in PCNSLs (mean ± SD = 22.5±7.83) (p<0.005). The AUC for aTBF (0.888) was higher than those for rTBF (0.810), ADCmin (0.768), and SUVmax (0.848), although their difference was not statistically significant.
Conclusion: ASL perfusion imaging is useful for differentiating PCNSLs from GBMs as well as DWI and FDG-PET..
5. Yamashita K, Yoshiura T, Hiwatashi A, Kamano H, Dashjamts T, Shibata S, Tamae A, Honda H., Detection of Middle Ear Cholesteatoma by Diffusion-Weighted MR Imaging: Multishot Echo-Planar Imaging Compared with Single-Shot Echo-Planar Imaging., AJNR Am J Neuroradiol., 32, 10, 1915-1918, 2011.11.
6. Yamashita K, Yoshiura T, Arimura H, Mihara F, Noguchi T, Hiwatashi A, Togao O, Yamashita Y, Shono T, Kumazawa S, Higashida Y, Honda H, Performance evaluation of radiologists with artificial neural network for differential diagnosis of intra-axial cerebral tumors on MR images, Am J Neuroradiol., 2008.06.
1. Yamashita K, Wu Z, Zhang H, Yin W, Zhu Z, Luo T, Wen X, Jing B, Kam TE, Ksu LM, Yap PT, Wang L, Li G, Li T, Baluyot KR, Howell BR, Styner MA, Yacoub E, Chen G, Potts T, Gilmore JH, Piven J, Smith JK, Ugurbil K, Hazlett H, Zhu H, Elison JT, Shen D, Lin W, Prediction of Motor Function Development in Infants Using the Thickness of the Primary Motor Cortex, 25th Annual Meeting of the Organization for Human Brain Mapping, 2019.06.
2. Yamashita Koji, Predicting IDH1 and TERT Mutation Status in the patients with Glioblastoma, AIMS Neuro Imaging 2017, 2017.10.
3. Yamashita Koji, Hiwatashi Akio, Osamu Togao, Kazufumi Kikuchi, Ryusuke Hatae, Koji Yoshimoto, Masahiro Mizoguchi, Satoshi O Suzuki, Takashi Yoshiura, Hiroshi Honda, MR imaging Based Analysis of Glioblastoma multiforme: Estimation of IDH1 Mutation Status, ASNR 52th Annual Meeting & NER Foundation Symposium 2014, 2014.05.
Membership in Academic Society
  • The Japanese Society of Neuroradiology
  • Japan Radiological Society