KEIO RESEARCHERS INFORMATION SYSTEM

Profile 【 Display / hide 】

Profile 【 Display / hide 】

• 日本医学放射線学会 放射線診断専門医
  日本乳がん検診精度管理中央機構 検診マンモグラフィ読影認定医(B-1)

Career 【 Display / hide 】

Career 【 Display / hide 】

• 2008.04

  -

  2009.03

  Saitama City Hospital, 初期研修医

• 2009.04

  -

  2010.03

  Keio university hospital, 初期研修医

• 2010.04

  -

  2012.03

  Keio university hospital, 放射線科

• 2012.04

  -

  2014.03

  Eiju general hospital, 放射線診断科

• 2014.04

  -

  Present

  Keio university hospital, 放射線診断科

Academic Background 【 Display / hide 】

Academic Background 【 Display / hide 】

• 2002.04

  -

  2008.03

  Keio University, 医学部

  University, Graduated

Licenses and Qualifications 【 Display / hide 】

Licenses and Qualifications 【 Display / hide 】

• 医師免許, 2008.04

• 日本乳がん検診精度管理中央機構 検診マンモグラフィ読影認定医(B-1), 2012.06

• 放射線診断専門医, 2015.09

Research Areas 【 Display / hide 】

Research Areas 【 Display / hide 】

• Life Science / Radiological sciences

Research Keywords 【 Display / hide 】

Research Keywords 【 Display / hide 】

• CT

• MRI

• 放射線診断学

• 消化管造影

Papers 【 Display / hide 】

Papers 【 Display / hide 】

• Radiologic features of mixed epithelial and stromal tumors of the kidney: Hyperattenuating on unenhanced computed tomography and T2-hypointensity on magnetic resonance imaging

  Tatsuya S., Hirotaka A., Yuki A., Akiko T., Masahiro H., Shigeo O., Shuji M., Ryuichi M., Mototsugu O., Masahiro J.

  Radiology Case Reports (Radiology Case Reports)  16 ( 4 ) 858 - 862 2021.04

  　View Summary

  In the 2016 World Health Organization renal tumor classification, the mixed epithelial and stromal tumor family was introduced as a new entity. This family encompasses a spectrum of tumors, ranging from predominantly cystic tumors (adult cystic nephromas) to tumors that are variably solid (mixed epithelial and stromal tumors). The majority of previous studies incorporating “mixed epithelial and stromal tumor” in the titles were actually reports of imaging findings of adult cystic nephroma. Thus, the solid component of mixed epithelial and stromal tumors has not been well evaluated. In this study, we present 2 cases of mixed epithelial and stromal tumors, as defined by the 2016 World Health Organization classification, showing a predominantly solid component. The characteristic findings of the solid component of these tumors were T2-hypointensity on magnetic resonance imaging and hyperattenuation on unenhanced computed tomography. Angiomyolipoma with epithelial cysts and epithelioid angiomyolipoma should be considered in the differential diagnosis of mixed epithelial and stromal tumors.

  • Access to Document (DOI)

• mixed epithelial and stromal tumor ; MEST of the kidney

  鈴木達也，有田祐起，秋田大宇，陣崎雅弘

  Japanese Journal of Imaging Diagnosis (秀潤社)  41 ( 5 ) 464 - 465 2021.03

  Research paper (scientific journal), Joint Work

• Clinical utility of the Vesical Imaging-Reporting and Data System for muscle-invasive bladder cancer between radiologists and urologists based on multiparametric MRI including 3D FSE T2-weighted acquisitions

  Arita Y., Shigeta K., Akita H., Suzuki T., Kufukihara R., Kwee T.C., Ishii R., Mikami S., Okuda S., Kikuchi E., Oya M., Jinzaki M.

  European Radiology (European Radiology)  31 ( 2 ) 875 - 883 2021.02

  ISSN  09387994

  　View Summary

  Objectives: To investigate the clinical utility of the Vesical Imaging-Reporting and Data System (VI-RADS) by comparing its diagnostic performance for muscle-invasive bladder cancer (MIBC) between radiologists and urologists based on multiparametric MRI, including three-dimensional (3D) fast spin-echo (FSE) T2-weighted acquisitions. Methods: This study included 66 treatment-naïve patients (60 men, 6 women; mean age 74.0 years) with pathologically proven bladder cancer who underwent multiparametric MRI, including 3D FSE T2-weighted imaging, before transurethral bladder tumour resection between January 2010 and November 2018. The MRI scans were categorised according to the five-point VI-RADS score by four independent readers (two board-certified radiologists and board-certified urologists each), blinded to the histopathological findings. The VI-RADS scores were compared with the postoperative histopathological diagnosis. Interobserver agreement was assessed using weighted kappa coefficients. ROC analysis and generalised estimating equations were used to evaluate the diagnostic performance. Results: Forty-nine (74.2%) and 17 (25.8%) tumours were confirmed to be non-MIBC and MIBC, respectively, based on pathological examination. The interobserver agreement was good-to-excellent between all pairs of readers (range, 0.73–0.91). The urologists’ sensitivity/specificity values for DCE-MRI VI-RADS scores were significantly lower than those of radiologists. No significant differences were observed for the overall VI-RADS score. The AUC for the overall VI-RADS score was 0.94, 0.92, 0.89, and 0.87 for radiologists 1 and 2 and urologists 1 and 2, respectively. Conclusions: The VI-RADS score, based on multiparametric MRI including 3D FSE T2-weighted acquisitions, can be useful for radiologists and urologists to determine the bladder cancer muscle invasion status preoperatively. Key Points: • VI-RADS (using multiparametric MRI including 3D FSE T2-weighted acquisitions) achieves good to excellent interobserver agreement and has similar diagnostic performance for detecting muscle invasion by both radiologists and urologists. • The diagnostic performance of the overall VI-RADS score is high for both radiologists and urologists, particularly due to the dominant effect of diffusion-weighted imaging on the overall VI-RADS score. • The sensitivity and specificity values of the T2WI VI-RADS scores for four readers in our study (using 3D FSE T2-weighted acquisitions) were similar (with slightly higher specificity values) to previously published results (using 2D FSE T2-weighted acquisitions).

  • Access to Document (DOI)

• Performance of a deep learning-based identification system for esophageal cancer from CT images

  Takeuchi M., Seto T., Hashimoto M., Ichihara N., Morimoto Y., Kawakubo H., Suzuki T., Jinzaki M., Kitagawa Y., Miyata H., Sakakibara Y.

  Esophagus (Esophagus)   2021

  ISSN  16129059

  　View Summary

  Background: Because cancers of hollow organs such as the esophagus are hard to detect even by the expert physician, it is important to establish diagnostic systems to support physicians and increase the accuracy of diagnosis. In recent years, deep learning-based artificial intelligence (AI) technology has been employed for medical image recognition. However, no optimal CT diagnostic system employing deep learning technology has been attempted and established for esophageal cancer so far. Purpose: To establish an AI-based diagnostic system for esophageal cancer from CT images. Materials and methods: In this single-center, retrospective cohort study, 457 patients with primary esophageal cancer referred to our division between 2005 and 2018 were enrolled. We fine-tuned VGG16, an image recognition model of deep learning convolutional neural network (CNN), for the detection of esophageal cancer. We evaluated the diagnostic accuracy of the CNN using a test data set including 46 cancerous CT images and 100 non-cancerous images and compared it to that of two radiologists. Results: Pre-treatment esophageal cancer stages of the patients included in the test data set were clinical T1 (12 patients), clinical T2 (9 patients), clinical T3 (20 patients), and clinical T4 (5 patients). The CNN-based system showed a diagnostic accuracy of 84.2%, F value of 0.742, sensitivity of 71.7%, and specificity of 90.0%. Conclusions: Our AI-based diagnostic system succeeded in detecting esophageal cancer with high accuracy. More training with vast datasets collected from multiples centers would lead to even higher diagnostic accuracy and aid better decision making.

  • Access to Document (DOI)

• Evaluation of preoperative prediction of intestinal invasion in patients with ovarian cancer

  Takeda T., Hayashi S., Kobayashi Y., Tsuji K., Nagai S., Tominaga E., Suzuki T., Okuda S., Banno K., Aoki D.

  International Journal of Gynecology and Obstetrics (International Journal of Gynecology and Obstetrics)   2020

  ISSN  00207292

  　View Summary

  Objective: To optimize prediction for intestinal invasion of epithelial ovarian cancer. It is important to achieve debulking surgery to improve prognosis in ovarian cancer; intestinal resection is adopted if the cancer is invaded and resectable, but the preoperative evaluation method of intestinal invasion is still controversial. Methods: Patients (n = 174) who underwent primary debulking surgery for epithelial ovarian cancer were recruited for retrospective study; 28 and 146 patients were classified into the invasion and non-invasion groups, whether they needed intestinal resection or not. We collected clinical data including evaluation of computed tomography (CT), magnetic resonance imaging (MRI), and barium contrast radiography, and analyzed their accuracy. Results: The sensitivity and specificity for intestinal invasion were 33.3% and 98.6%, 42.9% and 98.6%, and 66.7% and 93.9% in CT, MRI, and barium contrast radiography, respectively. CT and MRI combined showed a sensitivity of 58.3% and specificity of 96.9%; all three methods combined was the most sensitive combination, showing a sensitivity of 79.2% and specificity of 90.8%. Conclusion: Combination of CT, MRI, and barium contrast radiography predicts intestinal invasion with the highest sensitivity. These three modalities, however, could not predict all intestinal invasion. Patients should be informed of the possibility of unexpected extensive resection.

  • Access to Document (DOI)

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Papers, etc., Registered in KOARA 【 Display / hide 】

Papers, etc., Registered in KOARA 【 Display / hide 】

• Elucidation of undetermined pathological mechanism and quantification of the diseases that demonstrate more relevant symptoms in the standing position than in the supine position by using upright CT

  Suzuki, Tatsuya

  科学研究費補助金研究成果報告書 2022

Presentations 【 Display / hide 】

Presentations 【 Display / hide 】

• 320列面検出器型立位CTを用いた内視鏡的Flap valve評価法の妥当性の検討

  正岡建洋, 山田祥岳, 水野達人, 山田稔, 横山陽一, 山本悠太, 亀山尚子, 鈴木達也, 金井隆典, 陣崎雅弘

  第61回日本消化器病学会大会 (神戸) , 

  2019.11

• 3T-MRIにおける自由呼吸下・上腹部脂肪抑制3DT1強調像の実用性：Stack-of-stars法と圧縮センシング法の比較

  Suzuki Tatsuya, Okuda Shigeo, Matsusaka Yohji, Toyama Kenji, Watanabe Toshio, Nunokawa Yoshinobu, Motomatsu Sari, Anayama Hirochika, Kamitaki Yasuko, Murakami Mikoto, Nozaki Atsushi, Jinzaki Masahiro

  第47回日本磁気共鳴医学会大会 (熊本) , 

  2019.09

• Clinical value of free-breathing Stack-Of-Stars LAVA for liver MRI

  Suzuki T, Okuda S, Matsusaka Y, Toyama K, Jinzaki M.

  ECR 2019 (European Congress of Radiology) (Vienna) , 

  2019.02

  , 

  Poster presentation

• Clinical value of free-breathing LAVA-Star in the upper abdomen

  Suzuki Tatsuya , Okuda Shigeo , Matsusaka Yohji , Toyama Kenji , Jinzaki Masahiro , Fujishiro Rikiya , Motomatsu Sari , Nunokawa Yoshinobu , Watanabe Toshio , Nozaki Atsushi

  第46回日本磁気共鳴医学会大会 (金沢) , 

  2018.09

  , 

  Poster presentation

• MRエンテログラフィー：DISCO法を用いた造影効果の経時的観察

  鈴木達也, 奥田茂男, 松本俊亮, 陣崎雅弘, 藤代力也, 本松沙里, 布川嘉喜, 渡部敏男

  第45回日本磁気共鳴医学会大会 (宇都宮) , 

  2017.09

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Courses Taught 【 Display / hide 】

Courses Taught 【 Display / hide 】

• PHYSICAL ASSESSMENT AND DIAGNOSTIC IMAGING

  2024

• PHYSICAL ASSESSMENT AND DIAGNOSTIC IMAGING

  2023

• PHYSICAL ASSESSMENT AND DIAGNOSTIC IMAGING

  2022

• PHYSICAL ASSESSMENT AND DIAGNOSTIC IMAGING

  2021