{"id":3875,"date":"2018-01-26T14:05:41","date_gmt":"2018-01-26T05:05:41","guid":{"rendered":"https:\/\/www.m.ehime-u.ac.jp\/school\/radiology\/contents\/?p=3875"},"modified":"2018-01-26T14:05:41","modified_gmt":"2018-01-26T05:05:41","slug":"2017%e5%b9%b4%e6%a5%ad%e7%b8%be%e3%80%80%e3%81%9d%e3%81%ae1","status":"publish","type":"post","link":"https:\/\/www.m.ehime-u.ac.jp\/school\/radiology\/%e7%a0%94%e7%a9%b6%e7%b4%b9%e4%bb%8b\/3875\/","title":{"rendered":"2017\u5e74\u696d\u7e3e\u3000\u305d\u306e1"},"content":{"rendered":"

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\n\u539f\u8457\u8ad6\u6587<\/a>
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\n\u25a0<\/span> \u8ad6\u6587\u30fb\u8457\u66f8<\/strong>
\n<\/a>\u25cf<\/span> \u539f\u8457\u8ad6\u6587<\/p>\n

    \n
  1. Fukuyama N, KidoT, Kurata A, Tanabe Y, Kido T, Yokoi T, Ogawa R, Nishiyama H, Uetani T, Mochizuki T.\u00a0Myocardial Segmentation of Area at Risk Based on Coronary Computed Tomography Angiography and Voronoi Diagram in Comparison with Magnetic Resonance Perfusion Imaging. Open Journal of Radiology, 2017,7,9-22<\/li>\n
  2. Fukuyama N, Kurata A, Kawaguchi N, Tashiro R, Higaki T, Yokoi T, Tanabe Y, Nishiyama H, Itoh T, Kido T, Miyagawa M, Mochizuki T.\u00a0Phase Contrast Injection Protocol for Pediatric Cardiac Computed Tomography in Children with Congenital Heart Disease. 2017 Dec 6. doi: 10.1007\/s00246-017-1782-7.<\/li>\n
  3. Hyodo T, Yada N, Hori M, Maenishi O, Lamb P, Sasaki K, Onoda M, Kudo M, Mochizuki T, Murakami T. Multimaterial Decomposition Algorithm for the Quantification of Liver Fat Content by Using Fast-Kilovolt-Peak Switching Dual-Energy CT: Clinical Evaluation. Radiology. 2017;283(1):108-18.<\/li>\n
  4. Hyodo T, Hori M, Lamb P, Sasaki K, Wakayama T, Chiba Y, Mochizuki T, Murakami T. Multimaterial Decomposition Algorithm for the Quantification of Liver Fat Content by Using Fast-Kilovolt-Peak Switching Dual-Energy CT: Experimental Validation. Radiology. 2017;282(2):381-9.<\/li>\n
  5. Kawaguchi N, Okayama H, Kawamura G, Shigematsu T, Takahashi T, Kawada Y, Hiasa G, Yamada T, Matsuoka H, Kazatani Y, Miyagawa M, Mochizuki T. Clinical usefulness of coronary flow reserve ratio for the detection of significant coronary artery disease on\u00a013<\/sup>N-ammonia positron emission tomography. Circ J. 2017 Sep 26. doi: 10.1253\/circj. CJ-17-0745.<\/li>\n
  6. Kawaguchi N, Miyagawa M, Mochizuki T, et al.\u3000Clinical usefulness of coronary flow reserve ratio for the detection of significant coronary artery disease on\u00a013<\/sup>N-Ammonia positron emission tomography. Circ J, 2017 (in press)<\/li>\n
  7. Kido To, Kido Te, Nakamura M, Watanabe K, Schmidt M, Forman C, Mochizuki T.Assessment of Left Ventricular Function and Mass on Free-Breathing Compressed Sensing Real-Time Cine Imaging. Circ J. 2017; 81: 1463-1468.<\/li>\n
  8. Kurata A, Coenen A, Lubbers MM, Nieman K, Kido T, Kido T, Yamashita N, Watanabe K, Krestin GP, Mochizuki T. The effect of blood pressure on non-invasive fractional flow reserve derived from coronary computed tomography angiography. Eur Radiol. 2017; 27: 1416-1423.<\/li>\n
  9. Coenen A, Lubbers MM, Kurata A, Kono A, Dedic A, Chelu RG, Dijkshoorn ML, Rossi A, van Geuns RM, Nieman K. Diagnostic value of transmural perfusion ratio derived from dynamic CT-based myocardial perfusion imaging for the detection of haemodynamically relevant coronary artery stenosis. Eur Radiol. 2017; 27: 2309-2316.<\/li>\n
  10. Coenen A, Rossi A, Lubbers MM, Kurata A, Kono AK, Chelu RG, Segreto S, Dijkshoorn ML, Wragg A, van Geuns RM, Pugliese F, Nieman K.\u3000Integrating CT Myocardial Perfusion and CT-FFR in the Work-Up of Coronary Artery Disease. JACC Cardiovasc Imaging. 2017; 10:760-770.<\/li>\n
  11. Lubbers MM, Dedic A, Kurata A, Dijkshoorn M, Schaap J, Lammers J, Lamfers EJ, Rensing BJ, Braam RL, Nathoe HM, Post JC, Rood PP, Schultz CJ, Moelker A, Ouhlous M, van Dalen BM, Boersma E, Nieman K. Round-the-clock performance of coronary CT angiography for suspected acute coronary syndrome: Results from the BEACON trial. Eur Radiol. 2017 Dec 15. doi: 10.1007\/s00330-017-5082-7.<\/li>\n
  12. Miyagawa M, Nishiyama Y, Uetani T, Ogimoto A, Ikeda S, Ishimura H, Watanabe E, Tashiro R, Tanabe Y, Kido T, Kurata A, Mochizuki T. Estimation of myocardial flow reserve utilizing an ultrafast cardiac SPECT: Comparison with coronary angiography, fractional flow reserve, and the SYNTAX score. Int J Cardiol. 2017 Oct 1;244:347-353.<\/li>\n
  13. Chikamori T, Goto K, Hida S, Miyagawa M, Ishimura H, Uchida K, Fukuyama T, Mochizuki T, Yamashina A. Diagnostic performance of a semiconductor gamma-camera system as studied by multicenter registry. J Cardiol. 2017 Feb;69(2):449-455.<\/li>\n
  14. Oshida T, Mori T, Shimizu H, Yoshino Y, Sonobe N, Matsumoto T, Kikuchi K, Miyagawa M, Iga J, Mochizuki T, Ueno SI. Neural basis of visual perception and reasoning ability in Alzheimer\u2019s disease: correlation between Raven\u2019s Colored Progressive Matrices test and 123 I-IMP SPECT imaging results. Int J Geriatr Psychiatry. 2017 Apr;32(4):407-413.<\/li>\n
  15. Ogawa R, Kido T, Nakamura M, Kido T, Kurata A, Uetani T, Ogimoto A, Miyagawa M, Mochizuki T. T1 mapping using saturation recovery single-shot acquisition at 3-tesla magnetic resonance imaging in hypertrophic cardiomyopathy: comparison to late gadolinium enhancement. Jpn J Radiol. 2017 Mar;35(3):116-125.<\/li>\n
  16. Ogawa, T. Kido, M. Nakamura, T. Kido, A. Kurata, M. Miyagawa, T. Mochizuki. Diagnostic capability of feature-tracking cardiovascular magnetic resonance to detect infarcted segments: a comparison with tagged magnetic resonance and wall thickening analysis. Clin Radiol. 2017; Oct;72(10): 828-834.<\/li>\n
  17. Tanabe Y, Kido T, Kurata A, Yokoi T, Fukuyama N, Uetani T, Nishiyama H, Kawaguchi N, Tahir E, Miyagawa M, Mochizuki T. Peak enhancement ratio of myocardium to aorta for identification of myocardial ischemia using dynamic myocardial computed tomography perfusion imaging. J Cardiol. 2017 Dec;70(6):565-570.<\/li>\n
  18. Tanabe Y, Kido T, Kurata A, Sawada S, Suekuni H, Kido T, Yokoi T, Uetani T, Inoue K, Miyagawa M, Mochizuki T. Three-dimensional maximum principal strain using cardiac computed tomography for identification of myocardial infarction. Eur Radiol. 2017 Apr;27(4):1667-1675.<\/li>\n
  19. Tanabe Y, Kido T, Kurata A, Fukuyama N, Yokoi T, Kido T, Uetani T, Vembar M, Dhanantwari A, Tokuyasu S, Yamashita N, Mochizuki T. Impact of knowledge-based iterative model reconstruction on myocardial late iodine enhancement in computed tomography and comparison with cardiac magnetic resonance. Int J Cardiovasc Imaging. 2017 Oct;33(10):1609-1618.<\/li>\n
  20. Tanabe Y, Kido T, Kurata A, Kouchi T, Fukuyama N, Yokoi T, Uetani T, Yamashita N, Miyagawa M, Mochizuki T. Late iodine enhancement computed tomography with image subtraction for assessment of myocardial infarction. Eur Radiol. 2017 Sep 19.<\/li>\n
  21. Halliburton S, Tanabe Y, Partovi S, Rajiah P. The role of advanced reconstruction algorithms in cardiac CT. Cardiovasc Diagn Ther 2017;7(5):527-538.<\/li>\n
  22. Izumoto H, Hiraoka A, Ishimaru Y, Murakami T, Kitahata S, Ueki H, Aibiki T, Okudaira T, Miyamoto Y, Yamago H, Iwasaki R, Tomida H, Mori K, Kishida M, Tsubouchi E, Miyata H, Ninomiya T, Kawasaki H, Hirooka M, Matsuura B, Abe M, Hiasa Y, Michitaka K, Kudo M. Validation of Newly Proposed Time to Transarterial Chemoembolization Progression in Intermediate-Stage Hepatocellular Carcinoma Cases. Oncology 2017;93(suppl 1):120-126<\/li>\n
  23. Ohta K, Tanada M, Sugawara Y, Teramoto N, Iguchi H. Usefulness of positron emission tomography (PET)\/contrast-enhanced computed tomography (CE-CT) in discriminating between malignant and benign intraductal papillary mucinous neoplasms (IPMNs). Pancreatology 17:911-919, 2017.<\/li>\n
  24. Hirata M, Watanabe R, Koyano Y, Sugata S, Takeda Y, Nakamura S, Akamune A, Tsuda T, Mochizuki T. Using a Motion Sensor-Equipped Smartphone to Facilitate CT-Guided Puncture. Cardiovasc Intervent Radiol. 2017 Apr;40(4):609-615.<\/li>\n<\/ol>\n

    <\/a>\u25cf<\/span>\u00a0\u7dcf\u8aac\u3001\u4ed6<\/p>\n

      \n
    1. \u9752\u91ce\u7965\u53f8, \u4ed6. \u5730\u65b9\u4e2d\u898f\u6a21\u7dcf\u5408\u75c5\u9662\u306b\u304a\u3051\u308b\u9ad8\u6027\u80fd3T MRI\u5c0e\u5165\u306e\u7d4c\u7def\u3068\u52b9\u679c. \u65b0\u533b\u7642\u3000510:36-40, 2017<\/li>\n
    2. \u4e95\u624b\u9999\u5948\uff0e\u57fa\u672c\u304b\u3089\u8eab\u306b\u3064\u304f\u7e26\u9694\u30fb\u80f8\u819c\u306e\u753b\u50cf\u8a3a\u65ad\u300c\u56a2\u80de\u6027\u816b\u7624\u300d\uff0e\u753b\u50cf\u8a3a\u65ad 37(12): 1175-1186, 2017<\/li>\n
    3. \u5ca9\u6751\u5353\u660e, \u798f\u4e95\u8061, \u4e95\u4e0a\u7950\u99ac, \u7af9\u53e3\u5d07, \u5bae\u5185\u7701\u8535, \u5bae\ufa11\u4e07\u7d14. \u5e02\u7acb\u5b87\u548c\u5cf6\u75c5\u9662\u653e\u5c04\u7dda\u79d1\u306b\u304a\u3051\u308b\u526f\u814e\u9759\u8108\u30b5\u30f3\u30d7\u30ea\u30f3\u30b0\u306e\u73fe\u72b6. \u5357\u4e88\u533b\u5b66\u96d1\u8a8c 17: 25-32, 2016<\/li>\n
    4. \u5c0f\u5ddd\u907c.\u3000World On-Line News\u5fc3\u81d3MRI\u306b\u95a2\u3059\u308b\u30c8\u30d4\u30c3\u30af\u30b9<\/li>\n
    5. \u57ce\u6238\u502b\u4e4b. \u5fc3\u81d3MRI\u306b\u304a\u3051\u308b\u753b\u50cf\u8a3a\u65ad\u306e\u4eca. Rad Fan Vol.15 N0.3. (2017.3\u6708\u53f7)<\/li>\n
    6. \u57ce\u6238\u502b\u4e4b.\u3000MRI\u306b\u304a\u3051\u308b\u5fc3\u81d3\u306e\u5305\u62ec\u691c\u67fb\u306e\u5b9f\u969b. INNERVISION Vol.32 N0.5. (2017.5\u6708\u53f7)<\/li>\n
    7. \u6d25\u7530\u5b5d\u6cbb, \u677e\u7530\u6075, \u7530\u4e2d\u5b8f\u660e, \u5009\u7530\u8056, \u671b\u6708\u8f1d\u4e00. \u611b\u5a9b\u5927\u5b66\u533b\u5b66\u90e8\u306b\u304a\u3051\u308bCT\u88ab\u66dd\u4f4e\u6e1b\u306e\u53d6\u308a\u7d44\u307f. \u611b\u5a9b\u533b\u5b66 36\uff1a184-188,2017<\/li>\n
    8. \u6d25\u7530\u5b5d\u6cbb, \u677e\u7530\u6075, \u7530\u4e2d\u5b8f\u660e, \u57ce\u6238\u8f1d\u4ec1, \u671b\u6708\u8f1d\u4e00, \u83c5\u539f\u656c\u6587. \u767a\u898b\u6642\u70b9\u4ee5\u524d\u306e\u8179\u90e8CT\u306b,\u81b5\u764c\u767a\u898b\u306e\u624b\u304c\u304b\u308a\u3068\u306a\u308b\u6240\u898b\u306f\u3042\u308b\u304b? \u81e8\u5e8a\u653e\u5c04\u7dda\u300062\uff1a1151-1156,2017<\/li>\n
    9. \u00a0\u4e2d\u7530\u82f1\u4e8c\uff0c\u6749\u539f\u9032\u4ecb\uff0c\u83c5\u539f\u656c\u6587\uff0c\u5c3e\u5d0e\u654f\u6587\uff0e\u810a\u690e\u8ee2\u79fb\u306e\u65e9\u671f\u8a3a\u65ad\u30fb\u65e9\u671f\u6cbb\u7642\u306b\u3088\u308b\u9ebb\u75fa\u4e88\u9632\u3068RT\u306e\u6cbb\u7642\u6210\u7e3e\uff0eJ MIOS 84:29-41, 2017<\/li>\n
    10. \u6771\u91ce \u535a. \u7b2c57\u56de\u65e5\u672c\u6838\u533b\u5b66\u4f1a\u5b66\u8853\u7dcf\u4f1a\u306b\u53c2\u52a0\u3057\u3066. Rad Fan 15: 87-89, 2017<\/li>\n
    11. Miyagawa M, Tashiro R, Watanabe E, Kawaguchi N, Ishimura H, Kido T, Kido T, Kurata A, Mochizuki T. Focus issue: cardiac sarcoidodis\u2212from the CME session at 63rd<\/sup> SNMMI annual meeting\u2212review article: Optimal patient preparation for detection and assessment of cardiac sarcoidosis by FDG-PET. Ann Nucl Cardiol 2017; 3(1): 113-116.<\/li>\n
    12. \u5bae\u5ddd\u6b63\u7537, \u6e21\u90e8\u7b11\u9e97, \u77f3\u6751\u96bc\u4eba, \u671b\u6708\u8f1d\u4e00. \u2163 PET\/CT\u3068SPECT\/CT\u306e\u30b9\u30c8\u30e9\u30c6\u30b8\u30fc&\u30a2\u30a6\u30c8\u30ab\u30e0 \u5fc3\u7b4bSPECT\u691c\u67fb\u306b\u3088\u308b\u5fc3\u6a5f\u80fd\u306e\u5b9a\u91cf\u89e3\u6790.INNERVISION 32(5): 73-75, 2017.<\/li>\n
    13. \u5bae\u5ddd\u6b63\u7537, \u6e21\u90e8\u7b11\u9e97, \u77f3\u6751\u96bc\u4eba, \u671b\u6708\u8f1d\u4e00. \u534a\u5c0e\u4f53SPECT\u3092\u7528\u3044\u305fTc-99m\u5fc3\u7b4b\u8840\u6d41\u4e88\u5099\u80fd\u306e\u5b9a\u91cf\u8a55\u4fa1. \u5fc3\u81d3\u6838\u533b\u5b66 19(1) : in press, 2017.<\/li>\n
    14. \u5bae\u5ddd\u6b63\u7537. \u77f3\u4e38\u8ad6\u6587\u306b\u5bfe\u3059\u308bEditorial Comment.–\u30b9\u30c6\u30ed\u30a4\u30c9\u6cbb\u7642\u306b\u3066FDG-PET\u3067\u306e\u5fc3\u7b4b\u96c6\u7a4d\u304c\u6d88\u5931\u3057\u305f\u5fc3\u30b5\u30eb\u30b3\u30a4\u30c9\u30fc\u30b7\u30b9\u306e3\u4f8b. \u5fc3\u81d3 49(5): 475, 2017.<\/li>\n
    15. \u6a6b\u5c71\u3000\u9686,\u3000\u85e4\u672c\u60a6\u5b50\u3001\u6a6b\u5c71\u3000\u8cb4\u7d00\u3001\u9152\u4e95\u7f8e\u4f73\u3001\u5927\u4e80\u771f\u4e00\u3001\u767d\u5c71\u88d5\u5b50\u3001\u7af9\u539f\u548c\u5b8f\u3002\u7247\u5ca1\u6b63\u660e. \u5b50\u5bae\u9838\u764c\u2162B\u671f\u306e\u6cbb\u7642\u6210\u7e3e\u3068\u5316\u5b66\u653e\u5c04\u7dda\u6cbb\u7642\u4f8b\u306e\u518d\u767a\u30ea\u30b9\u30af\u56e0\u5b50\u3000\u73fe\u4ee3\u7523\u5a66\u4eba\u79d166:39-43, 2017<\/li>\n
    16. \u4e2d\u7530\u82f1\u4e8c\uff0c\u6749\u539f\u9032\u4ecb\uff0c\u83c5\u539f\u656c\u6587\uff0c\u5c3e\u5d0e\u654f\u6587\uff0e\u810a\u690e\u8ee2\u79fb\u306e\u65e9\u671f\u8a3a\u65ad\u30fb\u65e9\u671f\u6cbb\u7642\u306b\u3088\u308b\u9ebb\u75fa\u4e88\u9632\u3068RT\u306e\u6cbb\u7642\u6210\u7e3e\uff0eJ MIOS 84:29-41, 2017<\/li>\n<\/ol>\n

      <\/a>\u25cf<\/span> \u75c7\u4f8b\u5831\u544a<\/p>\n

        \n
      1. \u5ddd\u53e3\u76f4\u4eba\u3001\u77f3\u4e38\u826f\u5e83\u3001\u6751\u4e0a\u5fe0\u53f8\u3001\u4e09\u6728\u5747\u3001\u4ed6. \u7279\u767a\u6027\u98df\u9053\u80c3\u7c98\u819c\u4e0b\u8840\u816b\u306b\u5bfe\u3057\u3066\u52d5\u8108\u585e\u6813\u8853\u3092\u65bd\u884c\u3057\u305f\uff11\u4f8b. \u81e8\u5e8a\u653e\u5c04\u7dda 9, 2017<\/li>\n
      2. \u53ea\u4fe1\u7f8e\u7d00\uff0c\u83c5\u539f\u656c\u6587\uff0c\u7247\u5ca1\u6b63\u660e\uff0c\u9ad8\u7551\u656c\u4e4b\uff0c\u5c0f\u677e\u6b63\u660e\uff0c\u7af9\u539f\u548c\u5b8f\uff0c\u9ad8\u7551\u6d69\u4e4b\uff0c\u5bfa\u672c\u5178\u5f18\uff0e\u5b50\u5bae\u9838\u764c\u540c\u6642\u5316\u5b66\u653e\u5c04\u7dda\u7642\u6cd5\u5f8c\u306b\u767a\u75c7\u3057\uff0c\u8a3a\u65ad\u306b\u82e6\u616e\u3057\u305f\u8179\u819c\u60aa\u6027\u4e2d\u76ae\u816b\u306e1\u4f8b\uff0e\u81e8\u5e8a\u653e\u5c04\u7dda62:759-763, 20173.<\/li>\n
      3. \u5fb3\u6c38\u4f38\u5b50\uff0c\u5fb3\u5897\u660e\u6587\uff0c\u53ea\u4fe1\u7f8e\u7d00\uff0c\u83c5\u539f\u656c\u6587\uff0c\u5927\u4e80\u771f\u4e00\uff0c\u5c0f\u677e\u6b63\u660e\uff0c\u7af9\u539f\u548c\u5b8f\uff0c\u5bfa\u672c\u5178\u5f18\uff0e\u5375\u5de3serous borderline tumor-micropapillary variant\u306e1\u4f8b\uff0e\u81e8\u5e8a\u653e\u5c04\u7dda62:997-1000, 2017<\/li>\n
      4. \u5fb3\u5897\u660e\u6587, \u83c5\u539f\u656c\u6587, \u5c71\u672c\u96c4\u592a, \u7d30\u5ddd\u6d69\u5e73, \u6749\u672c\u9f8d\u58eb\u90ce, \u5c71\u4e0b\u7d20\u5f18, \u897f\u6751\u7406\u6075\u5b50. \u4f4e\u60aa\u6027\u5ea6\u80ce\u5150\u578b\u817a\u764c\u306e1\u4f8b. \u81e8\u5e8a\u653e\u5c04\u7dda 62: 1699-1702, 2017.<\/li>\n<\/ol>\n

        <\/a>\u25cf<\/span> \u8457\u66f8<\/p>\n

          \n
        1. \u5009\u7530\u3000\u8056\u3001\u5009\u7530\u3000\u7f8e\u6075\u3001\u5317\u6fa4\u3000\u7406\u5b50\u3001\u671b\u6708\u8f1d\u4e00. \u5fc3\u81d3\u8840\u7ba1\u75c5\u7406\u5b66\u3068\u753b\u50cf\u8a3a\u65ad. \u81e8\u5e8a\u753b\u50cf\uff08\u30e1\u30b8\u30ab\u30eb\u30d3\u30e5\u30fc\u793e\u3001\u677e\u6c38\u5c1a\u6587 \u7de8\u8457\u30012017 p400-403\uff09<\/li>\n<\/ol>\n

          \u25a0<\/span> \u5b66\u4f1a\u30fb\u7814\u7a76\u4f1a\u767a\u8868<\/strong>
          \n          <\/a>\u25cf<\/span> \u56fd\u969b\u5b66\u4f1a<\/p>\n

            \n
          1. Hamamoto Y, Manabe T, Takeda H, Kanzaki H, Nagasaki K, Takata N, Mochizuk T. Prognostic factor in palliative radiation therapy for patients with good performance status. ESTRO 36 (2017. 5, Vienna)<\/li>\n
          2. Hyodo T, Yada N, Maenishi O, Sasaki K, Kono Y, Murakami T. Virtual Unenhanced Algorithms for Fast-Kilovolt Switching Dual-Energy CT: Comparison Between Dedicated and Non-dedicated Softwares for Assessment of Liver Fat Content.\u00a0 The RSNA 103rd Scientific Assembly and Annual Meeting (2017. Nov, Chicago)<\/li>\n
          3. Hyodo T, Yagyu Y, Kono Y, Oda T, Saitou T, Murakami T, Numoto I, Sasaki K, Ueshima K. Iodine Density Imaging using Dual-energy CT in Patients with Hepatocellular Carcinoma After Transcatheter Arterial Chemoembolization: Quantitative Assessment of Ethiodized Oil Retention for Predicting Tumor Recurrence.\u00a0 The RSNA 103rd Scientific Assembly and Annual Meeting (2017. Nov, Chicago)<\/li>\n
          4. Kawaguchi N, Hirai K, Nakamura M, Kido To, Kido Te, Kurata A, Miyagawa M, Mochizuki T. Usefulness of Hybrid Imaging on Cardiac CT and 13N-ammonia PET for Assessment of Significant Coronary Artery Disease. RSNA2017 (2017.11 Chicago)<\/li>\n
          5. Kurata A. Session 3. CT for myocardial ischemia; CT perfusion update. Cardiovascular Imaging in Computed Tomography Summit. (2017, May, Seoul, Korea)<\/li>\n
          6. Kurata A. Session 5. SCCT IRC: Clinical role of CT based myocardial segmentation. Cardiovascular Imaging in Computed Tomography Summit. (2017, May, Seoul, Korea)<\/li>\n
          7. Kurata A, Nishimura K, Uetani T, Ikeda S, Hirai K, Yokoi T, Kido T, Miygawa M, Mochizuki T. Analytical Coronary Sinus Imaging on Computed Tomography for Guiding Left Ventricular Lead Placement in Cardiac Resynchronization Therapy. Rapid Fire Session. The 12th Annual Scientific Meeting of the Society of Cardiovascular Computed Tomography. (2017, July, Washington DC, USA)<\/li>\n
          8. M Matsuda, T Tsuda, K Kikuchi, Y Sugawara, M Mochizuki. Imaging features of gastrointestinal stromal tumors of small bowel. RSNA 2017 Educational Exhibit 2017.11 (Chicago)<\/li>\n
          9. Matsuda M, Tsuda T, Kikuchi K, Sugawara Y, Mochizuki T. Imaging features of gastrointestinal stromal tumors of small bowel. The 103th Radiological Society of North America 2017 Annual meeting. (2017. 11, Chicago, USA)<\/li>\n
          10. Matsuda M, Tsuda T, Tanaka H, Mochizuki T. Dual-energy CT in patients with small\u3000HCC: utility of noise reduced monoenergetic images on detection of washout and image quality in delayed phase. The 103th Radiological Society of North America 2017 Annual meeting. (2017. 11, Chicago, USA)<\/li>\n
          11. Miyagawa M, Tashiro R, Watanabe E, Ogawa R, Kawaguchi N, Nakamura M, Kido T, Kurata A, Mochizuki T. Quantitative Assessment of Cardiac FDG Uptake During a Long-term follow-up of steroid therapy in patients with cardiac sarcoidosis. RSNA 103th Annual Meeting 2017 (2017.11.27, Chicago, USA)<\/li>\n
          12. Nakamura M, Kido To, Watanabe K, Mochizuki T et al. Non-contrast compressed sensing whole-heart coronary MRA at 3T:\u00a0First results in twenty healthy volunteers. Euro CMR (2017.5, Prague, Czech)<\/li>\n
          13. Nakamura M, Kido To, Watanabe K, Mochizuki T et al. Non-contrast compressed sensing whole-heart coronary MRA at 3T:\u00a0First results in twenty healthy volunteers. RSNA 2017 (2017.11, Chicago, USA)<\/li>\n
          14. Noriko Takata, Yasushi Hamamoto, Hiroshi Ishikawa, Shintaro Tsuruoka, Kei Nagasaki, Hiromitsu Kanzaki, Masaaki Kataoka, Teruhito Mochizuki. Pericardial effusion after chemoradiotherapy for esophageal cancer -Comparison of four-field technique and traditional two opposed field technique \u2013 The 102th Radiological Society of North America 2016 Annual meeting. (2016. 11, Chicago, USA)<\/li>\n
          15. Ogawa Ryo, Kido Tomoyuki, Nakamura Masashi,\u2028Emiri miyauch, Yokoi Takahiro, Naoki Fukuyama, Teruhito Kido, Akira Kurata, Masao Miyagawa, Teruhito Mochizuki. Evaluation of pulmonary perfusion in Tetralogy of Fallot after repair. (ASCI 2017. 6, Kyoto)<\/li>\n
          16. Ryo Ogawa, Tomoyuki Kido, Masashi Nakamura, Teruhito Kido, Akira Kurata, Masao Miyagawa, Teruhito Mochizuki. RIGHT VENTRICULAR STRAIN ANALYSIS BY FEATURE TRACKING IN TETRALOGY OF FALLOT AFTER REPAIR. (EURO CMR 2017. 5, Prague)<\/li>\n
          17. Shintaro Tsuruoka, Masaaki Kataoka, Kotaro Uwatsu, Atsushi Nishikawa, Teruhito Mochizuki. Prognostic Value of HER2 Status in Breast Cancer Patients With Brain Metastases. American Society for Radiation Oncology 59th Annual Meeting. (2017. 9, San Diego, USA)<\/li>\n
          18. Shintaro Tsuruoka, Masaaki Kataoka, Akifumi Tokumasu, Kotaro Uwatsu, Atsushi Nishikawa, Teruhito Mochizuki. Tumor Growth Patterns on Magnetic Resonance Imaging is Correlated With Prognosis in Patients With Locally Advanced Cervical Cancer Treated with Radiotherapy. American Society for Radiation Oncology 59th Annual Meeting. (2017. 9, San Diego, USA)<\/li>\n
          19. Tanabe Y, Kido T, Yokoi T, Fukuyama N, Kurta A, Kido T, Mochizuki T. Impact of Knowledge-based Model Reconstruction on Image Quality and Hemodynamic Parameters in Dynamic Myocardial Computed Tomography Perfusion Imaging. The 11th The Annual Scientific Meeting of the Society of Cardiovascular Computed Tomography (2017. 7, Washington)<\/li>\n
          20. Tanabe Y, Rajiah P. Dual Energy CT in Evaluation of Pulmonary Embolism: Opportunities, Challenges, Pitfalls and Solutions. RSNA 103th Scientific Assembly and Annual Meeting. (2017.12, Chicago)<\/li>\n
          21. Ball C, Tanabe Y, Gilkeson R, Rajiah P. Dynamic Cardiac CT with Functional Evaluation. RSNA 103th Scientific Assembly and Annual Meeting. (2017.12, Chicago)<\/li>\n
          22. Watanabe E\uff0cMiyagawa M\uff0cHirai K\uff0cYokoi T\uff0cOgawa R\uff0cNakamura M\uff0cKawaguchi N\uff0cKido To\uff0cKido Te\uff0cKurata A\uff0cMochizuki T\uff0eIncremental value of myocardial perfusion reserve for detection of multi-vessel coronary artery disease with use of a cadmium-zinc-telluride SPECT\uff0eAmerican Roentgen Ray Society 2017 Annual Meeting(2017\uff0e4\uff0c New Orleans)<\/li>\n
          23. Watanabe E\uff0cMiyagawa M\uff0cHirai K\uff0cYokoi T\uff0cOgawa R\uff0cNakamura M\uff0cKawaguchi N\uff0cKido To\uff0cKido Te\uff0cKurata A\uff0cMochizuki T\uff0eCharacteristics of cardiac FDG accumulation on PET\/CT in patients with chronic and paroxysmal atrial fibrillation\uff0eThe 11th<\/sup> Congress of Asian Society of Cardiovascular Imaging(2017\uff0e6\uff0cKyoto)<\/li>\n
          24. Watanabe E\uff0cMiyagawa M\uff0cHirai K\uff0cYokoi T\uff0cOgawa R\uff0cNakamura M\uff0cKawaguchi N\uff0cKido To\uff0cKido Te\uff0cKurata A\uff0cMochizuki T\uff0eDetection of increased FDG uptake in the atria by PET\/CT in patients with atrial fibrillation\uff0e104th<\/sup> Radiological Society of North America Scientific Assembly and Annual Meeting(2017\uff0e11\uff0cChicago)<\/li>\n
          25. Yokoi T, Itoh T, Nishiyama H, Kido T, Mochizuki T. Evaluation of Coronary Artery with High-Pitch Spiral Scan on Third Generation Dual-Source CT : A Phantom Study. ARRS 2017 (2017. 5, New Orleans)<\/li>\n
          26. Yokoi T, Kido T, Kurata A, Kawaguchi N, Watanabe E, Ogawa R, Nakamura M, Kido T, Miyagawa M, Mochizuki T. Stenosis-related Regional CT Perfusion Derived Myocardial Blood Flow Based on Volornoi Algorithm Myocardial Segmentation. The 11th<\/sup> Congress of Asian Society of Cardiovascular Imaging (2017. 6, Kyoto)<\/li>\n
          27. Yokoi T, Kido T, Kurata A, Kawaguchi N, Watanabe E, Ogawa R, Nakamura M, Kido T, Nishiyama H, Nakao K, Itoh T, Miyagawa M, Mochizuki T. Diagnostic Performance of the Stenosis-related Regional Myocardial Blood Flow Using Stress Dynamic CT Myocardial Perfusion Imaging. 12th<\/sup> Annual Scientific meeting of the Society of Cardiovascular Computed Tomography (2017. 7, Wahington, D.C.)<\/li>\n
          28. Matsumoto T, Nishina T, Niibe Y, Yamashita H, Katsui K, Kataoka M, Terahara A, Shimada H, Jingu K.\u3000Severe toxicity risk factor analysis of salvage radiotherapy for oligo-recurrence in the lymph nodes (LN) of esophagus carcinoma: From multi-institutional retrospective study. 2017 Gastrointestinal Cancers Symposium (2017, 1, San Francisco)<\/li>\n
          29. Nozaki M, Kagami Y, Shibata T, Nakamura K, Ito Y, Nishimura Y, Kawaguchi Y, Saito Y, Nagata Y, Matsumoto Y, Akimoto T, Nishimura T, Uno T, Tsujino K, Kataoka M,<\/u>Kodaira T, Shiraishi K, Inoue K, Isohashi F, Hiraoka M, Karasawa K, Izumi S, Sakurai H. A Clinical Trial on Hypofractionated Whole-breast Irradiation after Breast-conserving Surgery. European Society for Radiotherapy and Oncology: 36th<\/sup>Annual Congress (2017, 5, Vienna) EUROPEAN<\/li>\n
          30. Maki Y, Ueno T, Sugimoto R, Harada D, Uwatsu K, Kozuki T, Nishikawa A, Nogami N, Kataoka M,<\/u>Yamashita M. Outcome of stereotactic body radiotherapy for clinical Stage I non small cell lung cancer and CT findings: comparison with surgical resection.18th World Conference on Lung Cancer (2017, 10, Tokyo)<\/li>\n
          31. Aogi K, Sugawara Y, Kadoya T, Okada M. 18F FDG-PET\/CT on prognosis prediction for breast cancer patients. BIT\u2019s 10th Annual Meeting World Cancer Congress-2017 (2017 May 21, Barcelona)<\/li>\n<\/ol>\n

            ————\u56fd\u5185\u5b66\u4f1a\u3001\u8b1b\u6f14\u3001\u7814\u7a76\u52a9\u6210\u3001\u53d7\u8cde\u306f 2017\u5e74\u696d\u7e3e\u3000\u305d\u306e2<\/a>\u3092\u3054\u89a7\u304f\u3060\u3055\u3044\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"

            \u25a0\u8ad6\u6587 \u539f\u8457\u8ad6\u6587 \u7dcf\u8aac, \u4ed6 \u75c7\u4f8b\u5831\u544a \u8457\u66f8 \u25a0\u3000\u5b66\u4f1a\u30fb\u7814\u7a76\u4f1a\u767a\u8868 \u56fd\u969b\u5b66\u4f1a \u56fd\u5185\u5b66\u4f1a\uff08\u5168\u56fd\uff09 \u56fd\u5185\u5b66\u4f1a\uff08\u5730\u65b9\u4f1a\uff09 \u25a0 \u8b1b\u6f14 \u25a0 \u7814\u7a76\u52a9\u6210 \u25a0 \u53d7\u8cde ————— […]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[20],"tags":[],"class_list":["post-3875","post","type-post","status-publish","format-standard","hentry","category-20"],"acf":[],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/www.m.ehime-u.ac.jp\/school\/radiology\/wp-json\/wp\/v2\/posts\/3875","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.m.ehime-u.ac.jp\/school\/radiology\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.m.ehime-u.ac.jp\/school\/radiology\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.m.ehime-u.ac.jp\/school\/radiology\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.m.ehime-u.ac.jp\/school\/radiology\/wp-json\/wp\/v2\/comments?post=3875"}],"version-history":[{"count":0,"href":"https:\/\/www.m.ehime-u.ac.jp\/school\/radiology\/wp-json\/wp\/v2\/posts\/3875\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.m.ehime-u.ac.jp\/school\/radiology\/wp-json\/wp\/v2\/media?parent=3875"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.m.ehime-u.ac.jp\/school\/radiology\/wp-json\/wp\/v2\/categories?post=3875"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.m.ehime-u.ac.jp\/school\/radiology\/wp-json\/wp\/v2\/tags?post=3875"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}