1. Chishiki Y, Hirano S, Li H, Kojima K, Nakano Y, Sakurai T, Mukai H, Sugiyama A, Kuwabara S. Different Patterns of Gray Matter Volume Reduction in Early-onset and Late-onset Alzheimer Disease. Cogn Behav Neurol 2020;33:253–258. doi: 10.1097/WNN.0000000000000245.
  2. Furukawa S, Hirano S, Yamamoto T, Asahina M, Uchiyama T, Yamanaka Y, Nakano Y, Ishikawa A, Kojima K, Abe M, Uji Y, Higuchi Y, Horikoshi T, Uno T, Kuwabara S. Decline in drawing ability and cerebral perfusion in Parkinson’s disease patients after subthalamic nucleus deep brain stimulation surgery. Parkinsonism Relat Disord 2020;70:60–66. doi: 10.1016/j.parkreldis.2019.12.002.
  3. Harada E, Morizono T, Kanno T, Saito M, Kawagishi H. Medicinal Mushroom, Grifola gargal (Agaricomycetes), Lowers Triglyceride in Animal Models of Obesity and Diabetes and in Adults with Prediabetes. Int J Med Mushrooms 2020;22:79–91. doi: 10.1615/IntJMedMushrooms.2019033285.
  4. Hoshino I, Yokota H, Ishige F, Iwatate Y, Takeshita N, Nagase H, Uno T, Matsubara H. Radiogenomics predicts the expression of microRNA-1246 in the serum of esophageal cancer patients. Sci Rep 2020;10:2532. doi: 10.1038/s41598-020-59500-7.
  5. Imaizumi A, Obata T, Kershaw J, Tachibana Y, Inubushi M, Koizumi M, Yoshikawa K, Zhang M-R, Tanimoto K, Harada R, Uno T, Saga T. Imaging of Hypoxic Tumor: Correlation between Diffusion-weighted MR Imaging and 18F-fluoroazomycin Arabinoside Positron Emission Tomography in Head and Neck Carcinoma. Magn Reson Med Sci 2020;19:276–281. doi: 10.2463/mrms.tn.2019-0007.
  6. Iwai Y, Nemoto MW, Horikoshi T, Kanazawa A, Kurokawa M, Saito M, Harada R, Kobayashi H, Uno T. Comparison of CT-based and MRI-based high-risk clinical target volumes in image guided-brachytherapy for cervical cancer, referencing recommendations from the Japanese Radiation Oncology Study Group (JROSG) and consensus statement guidelines from the Groupe Européen de Curiethérapie-European Society for Therapeutic Radiology and Oncology (GEC ESTRO). Jpn J Radiol 2020;38:899–905. doi: 10.1007/s11604-020-00980-y.
  7. Iwatate Y, Hoshino I, Ishige F, Itami M, Chiba S, Arimitsu H, Yanagibashi H, Nagase H, Yokota H, Takayama W. Prognostic significance of p16 protein in pancreatic ductal adenocarcinoma. Mol Clin Oncol 2020;13:83–91. doi: 10.3892/mco.2020.2047.
  8. Iwatate Y, Hoshino I, Yokota H, Ishige F, Itami M, Mori Y, Chiba S, Arimitsu H, Yanagibashi H, Nagase H, Takayama W. Radiogenomics for predicting p53 status, PD-L1 expression, and prognosis with machine learning in pancreatic cancer. Br J Cancer 2020;123:1253–1261. doi: 10.1038/s41416-020-0997-1.
  9. Kubota Y, Yokota H, Sakai T, Yoneyama M, Ohira K, Uno T. Clinical feasibility of single-shot fluid-attenuated inversion recovery with wide inversion recovery pulse designed to reduce cerebrospinal fluid and motion artifacts for evaluation of uncooperative patients in acute stroke protocol. J Magn Reson Imaging 2020. doi: 10.1002/jmri.27483.
  10. Kurokawa R, Gonoi W, Yokota H, Isshiki S, Ohira K, Mizuno H, Kiguchi T, Inui S, Kurokawa M, Kato S, Matsuki M, Takeda T, Yokoyama K, Ota Y, Nakai Y, Maeda E, Mori H, Abe O. Computed tomography findings of early-stage TAFRO syndrome and associated adrenal abnormalities. Eur Radiol 2020;30:5588–5598. doi: 10.1007/s00330-020-06919-1.
  11. Maki S, Furuya T, Horikoshi T, Yokota H, Mori Y, Ota J, Kawasaki Y, Miyamoto T, Norimoto M, Okimatsu S, Shiga Y, Inage K, Orita S, Takahashi H, Suyari H, Uno T, Ohtori S. A Deep Convolutional Neural Network With Performance Comparable to Radiologists for Differentiating Between Spinal Schwannoma and Meningioma. Spine 2020;45:694–700. doi: 10.1097/BRS.0000000000003353.
  12. Makino Y, Kojima M, Yoshida M, Motomura A, Inokuchi G, Chiba F, Torimitsu S, Hoshioka Y, Yamaguchi R, Saito N, Urabe S, Tsuneya S, Horikoshi T, Yajima D, Iwase H. Postmortem CT and MRI findings of massive fat embolism. Int J Legal Med 2020;134:669–678. doi: 10.1007/s00414-019-02128-8.
  13. Masuoka S, Nasu K, Takahashi H, Kitao A, Sakai M, Ishiguro T, Saida T, Minami M. Impaired lesion detectability on gadoxetic acid-enhanced MR imaging in indocyanine green excretory defect: case series of three patients. Jpn J Radiol 2020;38:997–1003. doi: 10.1007/s11604-020-00991-9.
  14. Matsuoka T, Oya N, Yokota H, Akazawa K, Yamada K, Narumoto J, Alzheimer’s Disease Neuroimaging Initiative. Pineal volume reduction in patients with mild cognitive impairment who converted to Alzheimer’s disease. Psychiatry Clin Neurosci 2020;74:587–593. doi: 10.1111/pcn.13103.
  15. Nagano H, Kono T, Saiga A, Kubota Y, Fujimoto M, Felizola SJA, Ishiwata K, Tamura A, Higuchi S, Sakuma I, Hashimoto N, Suzuki S, Koide H, Takeshita N, Sakamoto S, Ban T, Yokote K, Nakamura Y, Ichikawa T, Uno T, Tanaka T. Aldosterone Reduction Rate After Saline Infusion Test May Be a Novel Prediction in Patients With Primary Aldosteronism. J Clin Endocrinol Metab 2020;105. doi: 10.1210/clinem/dgz092.
  16. Nishiyama A, Kawata N, Yokota H, Sugiura T, Matsumura Y, Higashide T, Horikoshi T, Oda S, Tatsumi K, Uno T. A predictive factor for patients with acute respiratory distress syndrome: CT lung volumetry of the well-aerated region as an automated method. Eur J Radiol 2020;122:108748. doi: 10.1016/j.ejrad.2019.108748.
  17. Sugiyama A, Cooper G, Hirano S, Yokota H, Mori M, Shimizu K, Yakiyama M, Finke C, Brandt AU, Paul F, Kuwabara S. WITHDRAWN: Cognitive impairment in multiple system atrophy is related to white matter damage detected by the T1w/T2w ratio. Parkinsonism Relat Disord 2020. doi: 10.1016/j.parkreldis.2020.05.010.
  18. Sugiyama A, Yokota H, Hirano S, Cooper G, Mukai H, Koide K, Wang J, Ito S, Finke C, Brandt AU, Paul F, Kuwabara S. Magnetic resonance T1w/T2w ratio in the middle cerebellar peduncle might be a sensitive biomarker for multiple system atrophy. Eur Radiol 2020. doi: 10.1007/s00330-020-07521-1.
  19. Sugiyama A, Yokota H, Yamanaka Y, Mukai H, Yamamoto T, Hirano S, Koide K, Ito S, Kuwabara S. Vertical pons hyperintensity and hot cross bun sign in cerebellar-type multiple system atrophy and spinocerebellar ataxia type 3. BMC Neurol 2020;20:157. doi: 10.1186/s12883-020-01738-9.
  20. Tai H, Hirano S, Sakurai T, Nakano Y, Ishikawa A, Kojima K, Li H, Shimada H, Kashiwado K, Mukai H, Horikoshi T, Sugiyama A, Uno T, Kuwabara S. The Neuropsychological Correlates of Brain Perfusion and Gray Matter Volume in Alzheimer’s Disease. J Alzheimers Dis 2020;78:1639–1652. doi: 10.3233/JAD-200676.
  21. Takada A, Yokota H, Watanabe Nemoto M, Horikoshi T, Matsushima J, Uno T. A multi-scanner study of MRI radiomics in uterine cervical cancer: prediction of in-field tumor control after definitive radiotherapy based on a machine learning method including peritumoral regions. Jpn J Radiol 2020;38:265–273. doi: 10.1007/s11604-019-00917-0.
  22. Takahashi M, Nojima H, Kuboki S, Horikoshi T, Yokota T, Yoshitomi H, Furukawa K, Takayashiki T, Takano S, Ohtsuka M. Comparing prognostic factors of Glut-1 expression and maximum standardized uptake value by FDG-PET in patients with resectable pancreatic cancer. Pancreatology 2020;20:1205–1212. doi: 10.1016/j.pan.2020.07.407.
  23. Tamari K, Nagata Y, Nishiki S, Nakamura S, Ogawa K, Uno T. Nationwide survey of COVID-19 prevention measures in Japanese radiotherapy departments via online questionnaire for radiation oncologists. Radiother Oncol 2020;149:219–221. doi: 10.1016/j.radonc.2020.05.042.
  24. Toh Y, Numasaki H, Tachimori Y, Uno T, Jingu K, Nemoto K, Matsubara H. Current status of radiotherapy for patients with thoracic esophageal cancer in Japan, based on the Comprehensive Registry of Esophageal Cancer in Japan from 2009 to 2011 by the Japan Esophageal Society. Esophagus 2020;17:25–32. doi: 10.1007/s10388-019-00690-z.
  25. Wada T, Yokota H, Horikoshi T, Starkey J, Hattori S, Hashiba J, Uno T. Diagnostic performance and inter-operator variability of apparent diffusion coefficient analysis for differentiating pleomorphic adenoma and carcinoma ex pleomorphic adenoma: comparing one-point measurement and whole-tumor measurement including radiomics approach. Jpn J Radiol 2020;38:207–214. doi: 10.1007/s11604-019-00908-1.
  26. Yokota H, Uetani H, Tatekawa H, Hagiwara A, Morimoto E, Linetsky M, Yoo B, Ellingson BM, Salamon N. Focal cortical dysplasia imaging discrepancies between MRI and FDG-PET: Unique association with temporal lobe location. Seizure 2020;81:180–185. doi: 10.1016/j.seizure.2020.08.017.


  1. Saiga A, Yamamoto M, Kondo H, Kubota Y, Wada T, Akutsu A, Takeuchi T, Koizumi J, Uno T. Bowstring Phenomenon in Renal Artery Aneurysm Exclusion Using a Viabahn Stent Graft. Vasc Endovascular Surg 2020:1538574420975556. doi: 10.1177/1538574420975556.
  2. Yokoyama D, Horiguchi K, Higuchi Y, Hashiba J. Transnasal endoscopic resection of Epstein-Barr virus-associated cavernous sinus tumour. BMJ Case Rep 2020;13. doi: 10.1136/bcr-2020-236381.
  3. Yoshida M, Hoshioka Y, Makino Y, Kojima M, Horikoshi T, Mukai H, Hikosaka K, Norose K, Iwase H. Pseudo-“Pneumatosis intestinalis” sign: A case of parasite uniquely depicted on postmortem CT. Forensic Imaging 2020;20:200363. doi: 10.1016/j.fri.2020.200363.


  1. Watanabe M, Tachimori Y, Oyama T, Toh Y, Matsubara H, Ueno M, Kono K, Uno T, Ishihara R, Muro K, Numasaki H, Tanaka K, Ozawa S, Murakami K, Usune S, Takahashi A, Miyata H, Registration Committee for Esophageal Cancer of the Japan Esophageal Society. Comprehensive registry of esophageal cancer in Japan, 2013. Esophagus 2020. doi: 10.1007/s10388-020-00785-y.



  1. 大平健司, 横田元. 【サルコイドーシス】脳神経内科領域におけるサルコイドーシスの画像所見. BRAIN and NERVE: 神経研究の進歩 2020;72:0871–0882. doi: 10.11477/mf.1416201612.
  2. 横田元. 【頭部CT・MRIが読めるようになる 異常を見分けるためにまず押さえたい、解剖・撮像法・よく出会う疾患の読影法】頭部画像の基本的な事柄 各論を読む前に. レジデントノート 2020a;22:2203–2211.
  3. 横田元, 向井宏樹, 藤本肇. 【全身性疾患の窓としての臓器】脳神経. 臨床画像 2020;36:1340–1352. doi: 10.18885/CI.0000000491.
  4. 横田元, 堀越琢郎, 藤本肇. 【画像診断を取り巻く最近の話題】千葉大学における放射線科読影レポートに関する問題とその改善. 京都府立医科大学雑誌 2020;129:117–120.
  5. 雜賀厚至, 篠塚健. 【画像診断ドリル 救急医と放射線科医が伝授する適切なオーダーと読影法】(第6章)整形外科画像診断ドリル 症例4.発熱・腰背部痛を主訴とする70歳代男性. レジデントノート 2020;22:412–419.
  6. 雜賀厚至, 安念優. 【画像診断ドリル 救急医と放射線科医が伝授する適切なオーダーと読影法】(第5章)腹部画像診断ドリル 症例15.突然の腰背部痛を主訴に来院した30歳代男性. レジデントノート 2020a;22:386–390.
  7. 雜賀厚至, 安念優. 【画像診断ドリル 救急医と放射線科医が伝授する適切なオーダーと読影法】(第5章)腹部画像診断ドリル 症例16.腰痛・発熱を主訴とする70歳代男性. レジデントノート 2020b;22:391–396.
  8. 向井宏樹. 【頭部CT・MRIが読めるようになる 異常を見分けるためにまず押さえたい、解剖・撮像法・よく出会う疾患の読影法】病的意義の低い所見や偶発発見所見. レジデントノート 2020a;22:2247–2257.
  9. 西山晃, 横田元, 重田文子. 肺高血圧症におけるCTの読み方と活用法. 呼吸器内科 2020a;37:321–326.
  10. 高田章代, 堀越琢郎, 宇野隆. 【やさしくわかる 産科婦人科検査マスターブック】(第2章)婦人科腫瘍分野 PET. 産科と婦人科 2020a;87:113–117.
  11. 服部真也. 【頭部CT・MRIが読めるようになる 異常を見分けるためにまず押さえたい、解剖・撮像法・よく出会う疾患の読影法】頭部外傷の読影. レジデントノート 2020b;22:2239–2246.
  12. 前島拓馬. 【頭部CT・MRIが読めるようになる 異常を見分けるためにまず押さえたい、解剖・撮像法・よく出会う疾患の読影法】頭部の画像解剖. レジデントノート 2020a;22:2212–2220.
  13. 和田武, 坂本壮. 救急画像ただいま読影中![第6回] 保存版!胸部単純X線写真でわかる、うっ血・肺水腫所見のまとめ. J-COSMO 2020a;2:44–53.
  14. 和田武, 坂本壮. 救急画像ただいま読影中[第7回] 救急外来で遭遇するincidental findings. J-COSMO 2020e;2:330–337.
  15. 和田武, 坂本壮. 救急画像ただいま読影中(第8回) CTの基礎知識. J-COSMO 2020b;2:543–552.
  16. 和田武, 坂本壮. 救急画像ただいま読影中[第9回] 急性期脳梗塞の画像診断(1). J-COSMO 2020g;2:645–653.
  17. 和田武, 坂本壮. 救急画像ただいま読影中[第10回] 急性期脳梗塞の画像診断(2). J-COSMO 2020c;2:836–844.
  18. 和田武, 坂本壮. 救急画像ただいま読影中[第11回] 急性期脳梗塞の画像診断(3). J-COSMO 2020d;2:973–980.
  19. 牧聡, 古矢丈雄, 堀越琢郎, 横田元, 宮本卓弥, 沖松翔, 志賀康浩, 稲毛一秀, 折田純久, 江口和, 大鳥精司. 【整形外科におけるAIを用いた研究】畳み込みニューラルネットワーク(CNN)を用いた神経鞘腫と髄膜腫の鑑別. 関節外科 2020;39:1311–1316. doi: 10.18885/JJS.0000000476.


  1. 横田元. 頭部CT・MRIが読めるようになる 異常を見分けるためにまず押さえたい、解剖・撮像法・よく出会う疾患の読影法. レジデントノート 2020a;22.