Updated on 2025/03/06

写真a

 
KADOMATSU Yuka
 
Organization
Nagoya University Hospital Thoracic Surgery Assistant professor of hospital
Title
Assistant professor of hospital
Profile
2008年 名古屋大学医学部医学科卒業
    豊田厚生病院 臨床研修医
2010年 豊田厚生病院 外科医師
2012年 名古屋第一赤十字病院 呼吸器外科 医員
2017年 名古屋大学大学院 医学系研究科入学
    名古屋大学医学部附属病院 呼吸器外科 医員
2020年 名古屋大学医学部附属病院 呼吸器外科 病院助教
2021年 名古屋大学大学院医学系研究科 修了 医学博士取得
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Degree 1

  1. Doctor of Medical Science ( 2021.3   Nagoya University ) 

Research Areas 1

  1. Life Science / Respiratory surgery  / Primary spontaneous pneumothorax, lung cancer

Current Research Project and SDGs 1

  1. 超高齢化が進む本邦における、肺癌手術患者の周術期の就労状況やQOLの「見える化」を目指す実態調査

Research History 1

  1. Nagoya University   Assistant professor of hospital

    2020.4

Education 2

  1. Nagoya University

    2017.4 - 2021.3

  2. Nagoya University   Faculty of medicine   Department of Medicine

    2002.4 - 2008.3

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    Country: Japan

Committee Memberships 1

  1. 日本呼吸器外科学会   利益相反マネジメント委員会 委員  

    2023.5   

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    Committee type:Academic society

 

Papers 145

  1. Development of a machine learning-based risk model for postoperative complications of lung cancer surgery Reviewed

    Kadomatsu, Y; Emoto, R; Kubo, Y; Nakanishi, K; Ueno, H; Kato, T; Nakamura, S; Mizuno, T; Matsui, S; Chen-Yoshikawa, TF

    SURGERY TODAY     2024.6

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    Authorship:Lead author   Language:English   Publisher:Surgery Today  

    Purpose: To develop a comorbidity risk score specifically for lung resection surgeries. Methods: We reviewed the medical records of patients who underwent lung resections for lung cancer, and developed a risk model using data from 2014 to 2017 (training dataset), validated using data from 2018 to 2019 (validation dataset). Forty variables were analyzed, including 35 factors related to the patient’s overall condition and five factors related to surgical techniques and tumor-related factors. The risk model for postoperative complications was developed using an elastic net regularized generalized linear model. The performance of the risk model was evaluated using receiver operating characteristic curves and compared with the Charlson Comorbidity Index (CCI). Results: The rate of postoperative complications was 34.7% in the training dataset and 21.9% in the validation dataset. The final model consisted of 20 variables, including age, surgical-related factors, respiratory function tests, and comorbidities, such as chronic obstructive pulmonary disease, a history of ischemic heart disease, and 12 blood test results. The area under the curve (AUC) for the developed risk model was 0.734, whereas the AUC for the CCI was 0.521 in the validation dataset. Conclusions: The new machine learning model could predict postoperative complications with acceptable accuracy. Clinical registration number: 2020–0375.

    DOI: 10.1007/s00595-024-02878-y

    Web of Science

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    PubMed

  2. Clinical application of resection process map as a novel surgical guide in thoracic surgery Reviewed

    Kadomatsu, Y; Nakao, M; Ueno, H; Nakamura, S; Fukumoto, K; Chen-Yoshikawa, TF

    INTERDISCIPLINARY CARDIOVASCULAR AND THORACIC SURGERY   Vol. 36 ( 4 )   2023.4

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    Authorship:Lead author   Language:English   Publishing type:Research paper (scientific journal)   Publisher:Interdisciplinary cardiovascular and thoracic surgery  

    Resection Process Map (RPM) is a surgical simulation system that uses preoperative three-dimensional computed tomography. Unlike the usual static simulation, this system provides surgeons an individualized dynamic deformation of the lung parenchyma and vessels. RPM was first introduced in 2020. Although the intraoperative usefulness of this system has been evaluated experimentally, there have been no reports on its clinical use. Herein, we presented in detail the first experience on RPM during robot-assisted anatomical lung resection in the real clinical setting.

    DOI: 10.1093/icvts/ivad059

    Web of Science

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  3. Prognostic Value of Uncertain Resection for Overall Survival in Non-small Cell Lung Cancer Reviewed

    Kadomatsu, Y; Nakamura, S; Ueno, H; Goto, M; Ozeki, N; Fukumoto, K; Fukui, T; Suzuki, Y; Chen-Yoshikawa, TF

    ANNALS OF THORACIC SURGERY   Vol. 114 ( 4 ) page: 1262 - 1268   2022.10

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    Authorship:Lead author   Language:English   Publisher:Annals of Thoracic Surgery  

    Background: In this study we evaluated the R(un) category proposed by the International Association for the Study of Lung Cancer (IASLC) for non-small cell lung cancer (NSCLC). Methods: We retrospectively reviewed the medical records of patients with NSCLC who underwent segmentectomy or lobectomy between 2014 and 2015 at our institution. Residual tumor (R) status was reclassified from the Union for International Cancer Control designation to the IASLC-proposed R classification of R0 and R(un). The underlying reasons for the R(un) reclassification were analyzed according to pathologic stage, lymph node status, and resected lobe. A Cox proportional hazard model was used to evaluate the impacts of R(un) categorization on overall survival. Results: Of 355 patients, 44.5% were reclassified as R(un). The most common reason for the reclassification was insufficient number of harvested lymph nodes or no station 7 lymph nodes. When stratified by tumor location, the absence of station 7 lymph nodes was especially prominent in both the right and left upper lung resections. In the multivariate Cox regression model, the IASLC R classification was associated with poor overall survival in node-positive patients (hazard ratio, 2.657; P = .016). Conclusions: Various factors resulted in reclassification to R(un) because the R(un) group was highly heterogeneous. Careful consideration is required to determine whether the R(un) classification can be used as an indicator of lymph node dissection quality. For advanced cases, the R(un) definition may be useful in predicting poor prognosis.

    DOI: 10.1016/j.athoracsur.2021.07.087

    Web of Science

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  4. Relationship of smoking cessation period with the incidence of complications in lung cancer surgery Reviewed

    Kadomatsu, Y; Sugiyama, T; Sato, K; Nakanishi, K; Ueno, H; Goto, M; Ozeki, N; Nakamura, S; Fukumoto, K; Chen-Yoshikawa, TF

    EUROPEAN JOURNAL OF CARDIO-THORACIC SURGERY   Vol. 62 ( 3 )   2022.8

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    Authorship:Lead author   Language:English   Publisher:European Journal of Cardio-thoracic Surgery  

    OBJECTIVES: The incidence of postoperative complications is relatively high in smokers. Although 4-week smoking cessation before surgery is generally recommended, it has not been sufficiently studied in lung cancer surgery. This study investigated whether smoking cessation for a short period of time significantly reduced complications after lung cancer surgery. METHODS: This was a retrospective, observational study that investigated the relationship between the smoking cessation period and the incidence of complications in lung cancer surgery. Patients who underwent curative-intent surgery for lung cancer at our institution between January 2014 and December 2017 were included. The smokers were classified into the following 4 categories of smoking cessation period before surgery: current (<4 weeks), recent (4 weeks to 12 months), distant (12 months to 5 years) and ex-smokers (>5 years). RESULTS: A total of 911 patients were included in this study. The incidence of pulmonary complications was 5 times higher in the smoker group than in the never smoker group (12.9% vs 2.5%, P < 0.001). On multivariable analysis in both models, the odds ratio for complications was significantly higher in distant smokers than in recent smokers and never smokers. Across all models, low lung function significantly predicted the development of postoperative complications. CONCLUSIONS: The evidence-based smoking cessation duration that reduces the incidence of complications after thoracic surgery remains unclear. The incidence of postoperative complications was more strongly affected by low pulmonary function than by the duration of preoperative smoking cessation. For patients with marginal indications for surgery, postponing surgery to accommodate a smoking cessation period seemed unnecessary.

    DOI: 10.1093/ejcts/ezac163

    Web of Science

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  5. A novel system applying artificial intelligence in the identification of air leak sites Reviewed

    Kadomatsu, Y; Nakao, M; Ueno, H; Nakamura, S; Chen-Yoshikawa, TF

    JTCVS TECHNIQUES   Vol. 15   page: 181 - 191   2022.10

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    Authorship:Lead author   Language:English   Publisher:JTCVS Techniques  

    Objective: Prolonged air leak is the most common complication of thoracic surgery. Intraoperative leak site detection is the first step in decreasing the risk of leak-related postoperative complications. Methods: We retrospectively reviewed the surgical videos of patients who underwent lung resection at our institution. In the training phase, deep learning-based air leak detection software was developed using leak-positive endoscopic images. In the testing phase, a different data set was used to evaluate our proposed application for each predicted box. Results: A total of 110 originally captured and labeled images obtained from 70 surgeries were preprocessed for the training data set. The testing data set contained 64 leak-positive and 45 leak-negative sites. The testing data set was obtained from 93 operations, including 58 patients in whom an air leak was present and 35 patients in whom an air leak was absent. In the testing phase, our software detected leak sites with a sensitivity and specificity of 81.3% and 68.9%, respectively. Conclusions: We have successfully developed a deep learning-based leak site detection application, which can be used in deflated lungs. Although the current version is still a prototype with a limited training data set, it is a novel concept of leak detection based entirely on visual information.

    DOI: 10.1016/j.xjtc.2022.06.011

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MISC 10

  1. Immunosuppressive treatment for myasthenia gravis crises improve the taste disorder in patients with thymoma: two case reports.

    Fukumoto K, Ohara Y, Okado S, Watanabe H, Noritake O, Nakanishi K, Kadomatsu Y, Ueno H, Kato T, Nakamura S, Chen-Yoshikawa TF

    Mediastinum (Hong Kong, China)   Vol. 7   page: 40   2023

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    Language:English   Publisher:Mediastinum  

    Background: Taste disorders in patients with thymoma accompanied by myasthenia gravis (MG) is rare. Case Description: The first case was a male in his 50s who underwent surgery for Masaoka stage III type B3 thymoma. He experienced a loss of taste before surgery, which showed no improvement after surgery. Due to a MG crisis 44 days after surgery, the patient underwent intensive treatment with mechanical ventilation, steroid pulse therapy, and intravenous immunoglobulin (IVIG) therapy. The patient recovered taste when he started oral food intake after the treatment for the MG crisis (about 3 months after surgery). Despite the recovery of taste after steroid pulse therapy and IVIG therapy, taste disorder gradually worsened about 1 year and 9 months after surgery, resulting in an almost complete loss of sweet taste 2 years after surgery. The second case was a male in his 60s who underwent surgery for Masaoka stage II type B1 thymoma. He experienced loss of taste before surgery, which showed no improvement after surgery. Five years and two months after surgery, the patient was diagnosed with a MG crisis and underwent steroid pulse therapy. Along with improvements in MG symptoms, taste disorders gradually improved. After 6 years and 10 months of surgery, the patient is still alive without MG symptoms (only pyridostigmine, 180 mg/body/day), taste disorder, and thymoma recurrence. Conclusions: The autoimmune mechanism may contribute to taste disorders in patients with thymoma, which can be recovered by immunosuppressive treatment in our cases.

    DOI: 10.21037/med-23-8

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  2. 合併症軽減に効果的な術前禁煙期間の検討

    門松 由佳, 矢澤 まり, 坪内 秀樹, 仲西 慶太, 杉山 燈人, 上野 陽史, 後藤 真輝, 尾関 直樹, 中村 彰太, 福井 高幸, 芳川 豊史

    気管支学   Vol. 43 ( Suppl. ) page: S183 - S183   2021.6

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    Language:Japanese   Publisher:(NPO)日本呼吸器内視鏡学会  

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  3. 実臨床におけるR0(un)の意義と再発への影響

    門松 由佳, 矢澤 まり, 坪内 秀樹, 仲西 慶太, 杉山 燈人, 上野 陽史, 後藤 真輝, 尾関 直樹, 中村 彰太, 福井 高幸, 芳川 豊史

    日本呼吸器外科学会雑誌   Vol. 35 ( 3 ) page: O7 - 1   2021.5

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    Language:Japanese   Publisher:(NPO)日本呼吸器外科学会  

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  4. 術後合併症が非小細胞肺癌切除後の予後に与える影響

    門松 由佳, 矢澤 まり, 坪内 秀樹, 仲西 慶太, 杉山 燈人, 上野 陽史, 後藤 真輝, 尾関 直樹, 中村 彰太, 福井 高幸, 芳川 豊史

    日本外科学会定期学術集会抄録集   Vol. 121回   page: PS - 7   2021.4

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    Language:Japanese   Publisher:(一社)日本外科学会  

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  5. 原発性自然気胸手術におけるポリグリコール酸シートの断端被覆の再発予防効果 メタアナリシス

    門松 由佳, 福井 高幸, 若井 建志, 森 正一, 川口 晃司, 中村 彰太, 羽切 周平, 尾関 直樹, 森 俊輔, 後藤 真輝, 杉山 燈人, 坪内 秀樹, 芳川 豊史

    日本外科学会定期学術集会抄録集   Vol. 120回   page: DP - 7   2020.8

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    Language:Japanese   Publisher:(一社)日本外科学会  

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Presentations 7

  1. 肺癌患者の就労および術後の休職・就労復帰に関する前向き調査の取り組み

    第64回日本肺癌学会学術集会 

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    Event date: 2023.11

    Presentation type:Oral presentation (general)  

  2. 約500例のロボット支援下手術から見る術中トラブル事例の傾向とその対策

    第40回日本呼吸器外科学会 

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    Event date: 2023.7

    Presentation type:Oral presentation (general)  

  3. 肺癌患者における術後合併症リスクを予測する新しい併存疾患スコアの開発と検証

    第123回日本外科学会  2023.4.27 

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    Event date: 2023.4

    Language:Japanese   Presentation type:Oral presentation (general)  

  4. CO2送気により脚ブロックと血圧低下を生じたロボット支援下手術の一例

    門松由佳

    第15回日本ロボット外科学会学術集会  2023.2.2 

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    Event date: 2023.2

    Language:Japanese   Presentation type:Oral presentation (general)  

  5. Resection Process Mapの術中使用経験

    門松 由佳1、中尾  恵2、勝谷亮太郎1、岡戸 翔嗣1、伊藤 俊成1、佐藤 惠雄1、仲西 慶太1、上野 陽史1、加藤 毅人1、尾関 直樹1、中村 彰太1、福本 紘一1、芳川 豊史1

    第65回関西胸部外科学会学術集会  2022.6.17 

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    Event date: 2022.6

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:浜松  

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Research Project for Joint Research, Competitive Funding, etc. 1

  1. 超高齢化が進む本邦における、肺癌手術の周術期の就労状況やQOLの「見える化」を目指す実態調査

    2023.12

    若手胸部外科医研究助成 

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    Authorship:Principal investigator  Grant type:Competitive

KAKENHI (Grants-in-Aid for Scientific Research) 3

  1. Creation of intraoperative marker-less marking and novel surgical guide following variable lungs by deaeration and surgical procedure and d

    Grant number:24K02534  2024.4 - 2027.3

    Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (B)

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    Authorship:Coinvestigator(s) 

  2. オリガミ理論に基づいた正確な肺部分切除法の創出

    Grant number:22K16565  2022.4 - 2025.3

    科学研究費助成事業  若手研究

    門松 由佳

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    Authorship:Principal investigator 

    Grant amount:\4550000 ( Direct Cost: \3500000 、 Indirect Cost:\1050000 )

    CT機器の精度向上と普及に伴い微小肺結節の切除手術は増加している。部分切除時の肺は肺の虚脱(脱気変形)のみならず、肺の折りたたみ(Folding)による修飾をうける。様々な微小結節位置の同定法が考案されているが、いずれも微小結節の表面位置の指標のみであり、深部断端の特定法はいまだ確立されていない。今なお、非触知結節の深部断端は外科医の経験にもとづいて予測し、切除している現状がある。本研究が目指すのは術前CTのみから肺部分切除時(脱気変形+Folding変形後)の位置同定アルゴリズムを確立することである。
    CT検査の普及により微小な肺結節の手術症例が増加している。術前の拡張肺における結節の局在を3次元的に示す機能は市販の3D医用画像処理ワークステーションで可能である。しかし、術中の分離肺換気による肺虚脱変形により結節の局在はかなり変化するため、不十分である。
    本研究では蝕知不能な微小結節の同定とエビデンスに基づく肺部分切除実施にむけて①3D医用画像処理ワークステーション (Synapse Vincent、zaiostation) ②術中コーンビームCT(Cone Beam CT: CBCT) ③VAL-MAP(気管支鏡バーチャル3D肺マッピング) ④superDimension ナビゲーションシステム ⑤肺脱気変形モデルを利用して取り組んでいる。
    本研究の目的は脱気変形に対応した微小結節の位置変化を術前CTからのみ予測し、非侵襲的な追加処置のみでエビデンスに基づいた部分切除アルゴリズムを作成することである。
    2022年度は部分切除部位の可視化を目的にターゲットとする結節周囲に金属製クリップを4か所置き、脱気時と拡張時の術中コーンビームCTを撮影した。クリップの位置を目安に術後、Synapse Vincentを使用して切除範囲に伴う肺実質領域について検討した。同側で複数回の肺部分切除が計画される場合があるが、2度目以降の手術の場合には既に肺の変形をきたしていること、またアルゴリズム作成段階では完全な非触知結節は対象とならないため、対象症例が想定より少ないという問題点も明らかとなった。
    本研究の遂行には、これまでに肺切除歴のない初回肺部分切除例での検討が必要である。しかし、コロナ禍の回復をうけて、肺癌手術症例数が増加したため、比較的難易度の低い部分切除症例の当院での施行が減少した。
    このため、2022年度遂行予定であった必要症例数が集積できなかった。
    研究の進捗が遅れているため、2023年度は2022年度の症例集積を引き続き行う。
    最終年度で使用する予定であったSuperDimensionの返却時期が早まったため、Super Dimensionを使用しないValidation方法について検討中である。

  3. Challenge in developing a guide for surface identification of the lungs using deformation algorithm by deflation and bird-view function

    Grant number:21H03020  2021.4 - 2024.3

    Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (B)

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    Authorship:Coinvestigator(s) 

 

Teaching Experience (On-campus) 2

  1. PBLチュートリアルまとめセッション

    2024

  2. 4年生臨床医学総論PBLチュートリアル

    2022

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    4年生臨床医学総論PBLチュートリアル