| Project/Area Number |
16K10275
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Radiation science
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| Research Institution | Nagoya University |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
二橋 尚志 名古屋大学, 医学部附属病院, 講師 (50464144)
上原 圭介 名古屋大学, 医学部附属病院, 病院講師 (50467320)
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| Project Period (FY) |
2016-04-01 – 2020-03-31
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| Project Status |
Completed (Fiscal Year 2019)
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| Budget Amount *help |
¥4,550,000 (Direct Cost: ¥3,500,000、Indirect Cost: ¥1,050,000)
Fiscal Year 2018: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2017: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2016: ¥2,860,000 (Direct Cost: ¥2,200,000、Indirect Cost: ¥660,000)
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| Keywords | perfusion CT / 治療効果予測 / 予後予測 / dual energy CT / テクスチャ解析 / 画像診断学 |
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| Outline of Final Research Achievements |
To analyze retrospectively the correlation between perfusion parameters and predicting pathologic response and prognosis to neoadjuvant chemotherapy (NAC) in locally advanced rectal cancer, we used perfusion CT before NAC. Blood flow (BF), blood volume (BV), mean transit time (MTT), and permeability (PMB) were quantified. The data were compared with the histological findings and clinical outcome.
Ten patients were pathological responders. BF and PMB were significantly higher in responders. MTT was significantly lower in responders. Four patients diagnosed with tumor recurrence after operation. One of four was pathological responders. Recurrence rate was significantly higher in non-responders. PMB was significantly higher and MTT was significantly lower in no recurrence.Using quantitative perfusion CT to quantify PMB and MTT can discriminate patients with a favorable response and prognosis.
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| Academic Significance and Societal Importance of the Research Achievements |
CTなどの画像検査は術前に一般的に行われる検査であり、患者負担の少ない侵襲性の低い検査である。術前化学療法や術前化学放射線療法で腫瘍細胞が消失した症例（CR）は予後が良いことが一般的に知られているが、一般的にこの評価ができるのは、手術後の病理組織標本での評価になり、治療開始前に治療効果や予後を予測することは難しい。術前の画像検査から得られるパラメータで、治療効果予測や予後予測ができれば、個々の症例に対し最適な治療方法を選択することが可能になり、患者さんへの大きな利益になると考える。
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