Yutaka Midorikawa

Summary

Affiliation: University of Tokyo
Country: Japan

Publications

  1. Kajiwara T, Midorikawa Y, Yamazaki S, Higaki T, Nakayama H, Moriguchi M, et al. Clinical score to predict the risk of bile leakage after liver resection. BMC Surg. 2016;16:30 pubmed publisher
    ..6 %) patients in low-, middle, and high-risk groups were given a diagnosis of bile leakage after operation, respectively (P?=?0.144). Our risk score model can be used to predict the risk of bile leakage after liver resection. ..
  2. Yagi R, Midorikawa Y, Moriguchi M, Nakayama H, Aramaki O, Yamazaki S, et al. Liver resection for recurrent hepatocellular carcinoma to improve survivability: a proposal of indication criteria. Surgery. 2018;163:1250-1256 pubmed publisher
    ..176). Liver resection is recommended as first-line therapy for recurrent hepatocellular carcinoma in patients with a score of 0, while those with score 2/3 should be considered candidates for transcatheter arterial chemoembolization. ..
  3. Tsuji S, Midorikawa Y, Seki M, Takayama T, Sugiyama Y, Aburatani H. Network-based analysis for identification of candidate genes for colorectal cancer progression. Biochem Biophys Res Commun. 2016;476:534-540 pubmed publisher
  4. Ebisawa K, Midorikawa Y, Higaki T, Nakayama H, Tsuji S, Nishimaki H, et al. Natural history of nonenhancing lesions incidentally detected during the diagnosis of hepatocellular carcinoma. Surgery. 2016;160:654-60 pubmed publisher
    ..This should be considered a risk factor for the appearance of new hepatocellular carcinoma. ..
  5. Abe H, Midorikawa Y, Mitsuka Y, Aramaki O, Higaki T, Matsumoto N, et al. Predicting postoperative outcomes of liver resection by magnetic resonance elastography. Surgery. 2017;162:248-255 pubmed publisher
    ..003). The liver stiffness measurement by magnetic resonance elastography could be used as a predictive marker for the risk of major complications due to blood loss during liver resection. ..
  6. Mitsuka Y, Midorikawa Y, Abe H, Matsumoto N, Moriyama M, Haradome H, et al. A prediction model for the grade of liver fibrosis using magnetic resonance elastography. BMC Gastroenterol. 2017;17:133 pubmed publisher
    ..5%) Grade III (F4) patients in the test group, with a total accuracy of 83.8%. The prediction model based on LSM, ICGR15, and platelet count can accurately and reproducibly predict liver fibrosis grade. ..