医学部 内科学(ばんたね病院)

祖父江 嘉洋

ソブエ ヨシヒロ  (Yoshihiro Sobue)

基本情報

所属
藤田医科大学 医学部・内科学 准教授

通称等の別名
祖父江嘉洋
J-GLOBAL ID
202001007459916653
researchmap会員ID
R000007464

論文

 37
  • Yoshihiro Sobue, Eiichi Watanabe, Yusuke Funato, Masanobu Yanase, Hideo Izawa
    ESC heart failure 2024年6月10日  
    AIMS: Sudden cardiac death (SCD) is a common mode of death in patients with congestive heart failure (CHF). Implantable cardioverter defibrillator (ICD) implantation is established treatment for SCD prevention, but current eligibility criteria based on left ventricular ejection fraction (LVEF) and New York Heart Association (NYHA) functional class may be due for reconsideration given the increasing effectiveness of pharmacological therapy. We sought to reconsider the risk stratification of SCD in patients with symptomatic CHF. METHODS: In total, 1,676 consecutive patients (74 ± 13 years old; 56% male) with NYHA class II or III CHF between 2008 and 2015 were enrolled for this prospective study. The endpoint was SCD. RESULTS: During a median (interquartile range) follow-up period of 25 (4-70) months, 198 (11.8%) patients suffered SCD. Of those events, 23% occurred within 3 months of discharge. In the adjusted analyses, estimated glomerular filtration rate (eGFR) < 30 ml/min/1.73 m2 [hazard ratio (HR) 1.73, 95% confidence interval (CI) 1.11-2.70, P = 0.01] and LVEF ≤ 35% (HR 2.31, 95% CI 1.47-3.66, P < 0.01) were independent risk predictors of SCD. Addition of eGFR to LVEF significantly improved prediction of SCD in the C-index (P = 0.04), and in two metrics, net reclassification improvement (P = 0.01) and integrated discrimination improvement (P = 0.03). The predictive power of eGFR declined time-dependently over 2 years. CONCLUSIONS: The addition of eGFR to current eligibility criteria may be useful for risk assessment of SCD, although its predictive power wanes over time. Roughly a quarter of the SCD occurred within 3 months after discharge in patients with CHF.
  • Bon-Kwon Koo, Seokhun Yang, Jae Wook Jung, Jinlong Zhang, Keehwan Lee, Doyeon Hwang, Kyu-Sun Lee, Joon-Hyung Doh, Chang-Wook Nam, Tae Hyun Kim, Eun-Seok Shin, Eun Ju Chun, Su-Yeon Choi, Hyun Kuk Kim, Young Joon Hong, Hun-Jun Park, Song-Yi Kim, Mirza Husic, Jess Lambrechtsen, Jesper M Jensen, Bjarne L Nørgaard, Daniele Andreini, Pal Maurovich-Horvat, Bela Merkely, Martin Penicka, Bernard de Bruyne, Abdul Ihdayhid, Brian Ko, Georgios Tzimas, Jonathon Leipsic, Javier Sanz, Mark G Rabbat, Farhan Katchi, Moneal Shah, Nobuhiro Tanaka, Ryo Nakazato, Taku Asano, Mitsuyasu Terashima, Hiroaki Takashima, Tetsuya Amano, Yoshihiro Sobue, Hitoshi Matsuo, Hiromasa Otake, Takashi Kubo, Masahiro Takahata, Takashi Akasaka, Teruhito Kido, Teruhito Mochizuki, Hiroyoshi Yokoi, Taichi Okonogi, Tomohiro Kawasaki, Koichi Nakao, Tomohiro Sakamoto, Taishi Yonetsu, Tsunekazu Kakuta, Yohei Yamauchi, Jeroen J Bax, Leslee J Shaw, Peter H Stone, Jagat Narula
    JACC. Cardiovascular imaging 2024年5月15日  
    BACKGROUND: A lesion-level risk prediction for acute coronary syndrome (ACS) needs better characterization. OBJECTIVES: This study sought to investigate the additive value of artificial intelligence-enabled quantitative coronary plaque and hemodynamic analysis (AI-QCPHA). METHODS: Among ACS patients who underwent coronary computed tomography angiography (CTA) from 1 month to 3 years before the ACS event, culprit and nonculprit lesions on coronary CTA were adjudicated based on invasive coronary angiography. The primary endpoint was the predictability of the risk models for ACS culprit lesions. The reference model included the Coronary Artery Disease Reporting and Data System, a standardized classification for stenosis severity, and high-risk plaque, defined as lesions with ≥2 adverse plaque characteristics. The new prediction model was the reference model plus AI-QCPHA features, selected by hierarchical clustering and information gain in the derivation cohort. The model performance was assessed in the validation cohort. RESULTS: Among 351 patients (age: 65.9 ± 11.7 years) with 2,088 nonculprit and 363 culprit lesions, the median interval from coronary CTA to ACS event was 375 days (Q1-Q3: 95-645 days), and 223 patients (63.5%) presented with myocardial infarction. In the derivation cohort (n = 243), the best AI-QCPHA features were fractional flow reserve across the lesion, plaque burden, total plaque volume, low-attenuation plaque volume, and averaged percent total myocardial blood flow. The addition of AI-QCPHA features showed higher predictability than the reference model in the validation cohort (n = 108) (AUC: 0.84 vs 0.78; P < 0.001). The additive value of AI-QCPHA features was consistent across different timepoints from coronary CTA. CONCLUSIONS: AI-enabled plaque and hemodynamic quantification enhanced the predictability for ACS culprit lesions over the conventional coronary CTA analysis. (Exploring the Mechanism of Plaque Rupture in Acute Coronary Syndrome Using Coronary Computed Tomography Angiography and Computational Fluid Dynamics II [EMERALD-II]; NCT03591328).
  • Hiroyuki Omori, Hitoshi Matsuo, Shinichiro Fujimoto, Yoshihiro Sobue, Yui Nozaki, Gaku Nakazawa, Kuniaki Takahashi, Kazuhiro Osawa, Ryo Okubo, Umihiko Kaneko, Hideyuki Sato, Takashi Kajiya, Toru Miyoshi, Keishi Ichikawa, Mitsunori Abe, Toshiro Kitagawa, Hiroki Ikenaga, Mike Saji, Nobuo Iguchi, Takeshi Ijichi, Hiroshi Mikamo, Akira Kurata, Masao Moroi, Raisuke Iijima, Shant Malkasian, Tami Crabtree, James K Min, James P Earls, Rine Nakanishi
    Atherosclerosis 386 117363-117363 2023年12月  
    BACKGROUND AND AIMS: Artificial intelligence quantitative CT (AI-QCT) determines coronary plaque morphology with high efficiency and accuracy. Yet, its performance to quantify lipid-rich plaque remains unclear. This study investigated the performance of AI-QCT for the detection of low-density noncalcified plaque (LD-NCP) using near-infrared spectroscopy-intravascular ultrasound (NIRS-IVUS). METHODS: The INVICTUS Registry is a multi-center registry enrolling patients undergoing clinically indicated coronary CT angiography and IVUS, NIRS-IVUS, or optical coherence tomography. We assessed the performance of various Hounsfield unit (HU) and volume thresholds of LD-NCP using maxLCBI4mm ≥ 400 as the reference standard and the correlation of the vessel area, lumen area, plaque burden, and lesion length between AI-QCT and IVUS. RESULTS: This study included 133 atherosclerotic plaques from 47 patients who underwent coronary CT angiography and NIRS-IVUS The area under the curve of LD-NCP<30HU was 0.97 (95% confidence interval [CI]: 0.93-1.00] with an optimal volume threshold of 2.30 mm3. Accuracy, sensitivity, and specificity were 94% (95% CI: 88-96%], 93% (95% CI: 76-98%), and 94% (95% CI: 88-98%), respectively, using <30 HU and 2.3 mm3, versus 42%, 100%, and 27% using <30 HU and >0 mm3 volume of LD-NCP (p < 0.001 for accuracy and specificity). AI-QCT strongly correlated with IVUS measurements; vessel area (r2 = 0.87), lumen area (r2 = 0.87), plaque burden (r2 = 0.78) and lesion length (r2 = 0.88), respectively. CONCLUSIONS: AI-QCT demonstrated excellent diagnostic performance in detecting significant LD-NCP using maxLCBI4mm ≥ 400 as the reference standard. Additionally, vessel area, lumen area, plaque burden, and lesion length derived from AI-QCT strongly correlated with respective IVUS measurements.
  • Taro Makino, Tomohide Ichikawa, Mari Amino, Mari Nakamura, Masayuki Koshikawa, Yuji Motoike, Yoshihiro Nomura, Masahide Harada, Yoshihiro Sobue, Eiichi Watanabe, Ken Kiyono, Koichiro Yoshioka, Yuji Ikari, Yukio Ozaki, Hideo Izawa
    Annals of noninvasive electrocardiology : the official journal of the International Society for Holter and Noninvasive Electrocardiology, Inc 28(6) e13069 2023年11月  
    BACKGROUND: We aimed to investigate the association between ventricular repolarization instability and sustained ventricular tachycardia and ventricular fibrillation (VT/VF) occurring within 48 h (acute-phase VT/VF) after the onset of acute coronary syndrome (ACS) and the prognostic role of repolarization instability and heart rate variability (HRV) after discharge from the hospital. METHODS: We studied 572 ACS patients with a left ventricular ejection fraction >35%. The ventricular repolarization instability was assessed by the beat-to-beat T-wave amplitude variability (TAV) using high-resolution 24-h Holter ECGs recorded at a median of 11 days from the date of admission. We calculated the HRV parameters including the deceleration capacity (DC) and non-Gaussian index calculated on a 25 s timescale (λ25s). The DC and λ25s were dichotomized based on previous studies' thresholds. RESULTS: Acute-phase VT/VF developed in 43 (7.5%) patients. In-hospital mortality was significantly higher among VT/VF patients (4.7% vs. 0.9%, p = .03). An adjusted logistic model showed that the maximum TAV (odds ratio 1.02, 95% confidence interval [CI] 1.00-1.29, p = .04) was associated with acute-phase VT/VF. During a median follow-up period of 2.1 years, 19 (3.3%) patients had cardiac deaths or resuscitated cardiac arrest. Acute-phase VT/VF (p = .12) and TAV (p = .72) were not significant predictors of survival. An age and sex-adjusted Cox model showed that the DC (p < .01), λ25s (p < .01), and emergency coronary intervention (p < .01) were independent predictors. CONCLUSION: T-wave amplitude variability was associated with acute-phase VT/VF, but the TAV was not predictive of survival post-discharge. The DC, λ25s, and emergency coronary intervention were independent predictors of survival.
  • Terumasa Kondo, Atsushi Teramoto, Eiichi Watanabe, Yoshihiro Sobue, Hideo Izawa, Kuniaki Saito, Hiroshi Fujita
    IEEE journal of translational engineering in health and medicine 11 191-198 2023年  
    OBJECTIVE: The early detection of cardiac disease is important because the disease can lead to sudden death and poor prognosis. Electrocardiograms (ECG) are used to screen for cardiac diseases and are useful for the early detection and determination of treatment strategies. However, the ECG waveforms of cardiac care unit (CCU) patients with severe cardiac disease are often complicated by comorbidities and patient conditions, making it difficult to predict the severity of further cardiac disease. Therefore, this study predicts the short-term prognosis of CCU patients to detect further deterioration in CCU patients at an early stage. METHODS: The ECG data (II, V3, V5, aVR induction) of CCU patients were converted to image data. The transformed ECG images were used to predict short-term prognosis with a two-dimensional convolutional neural network (CNN). RESULTS: The prediction accuracy was 77.3%. Visualization by GradCAM showed that the CNN tended to focus on the shape and regularity of waveforms, such as heart failure and myocardial infarction. CONCLUSION: These results suggest that the proposed method may be useful for short-term prognosis prediction using the ECG waveforms of CCU patients. CLINICAL IMPACT: The proposed method could be used to determine the treatment strategy and choose the intensity of treatment after admission to the CCU.

共同研究・競争的資金等の研究課題

 1

その他

 1
  • ①Three vessels-FFR(3V-FFR)による心血管イベント予測 冠動脈CTは、冠動脈の解剖学的走行、冠動脈狭窄の診断、冠動脈壁評価などに関する有益な情報を提供するすることができ、現在、その適応はガイドラインにより運動負荷心電図所見にと基づきリスクの層別化を行い、中等度リスク群が対象となる。高い陰性的中率を有することで、安全に非侵襲的に虚血性心疾患を除外できることが可能である。しかしその一方で、①不整脈や高心拍の場合にmotion artifactのため画質不良になること、②重度石灰化病変では血管内腔評価が困難なことが多い、③機能的評価が行えないことが課題として挙げられる。③に関しては現行のガイドラインでは機能的評価としてシンチグラフィー等の負荷心筋血流イメージングにて評価することを推奨している。 CTによる解剖学的狭窄評価と負荷心筋血流イメージングによる機能的虚血評価が陽性となれば、侵襲的冠動脈造影検査(CAG)による精査となるが、その際、CAGによる解剖学的狭窄に加え、冠血流予備量比(Fractional Flow Reserve; FFR)による機能的評価を行うことが推奨されている。FFRは薬物投与による最大充血下に狭窄前後の圧格差を圧センサーを有するワイヤー(pressure wire)を用いて評価する方法である。FFRに基づく血行再建術はその後の患者の転帰および費用対効果が、CAGに比べて優れていることが無作為化臨床試験で明らかにされている。しかしその一方でCAGに加え、pressure wireを冠動脈内へ挿入するため、侵襲的であることが課題として挙げられる。近年、数値流体力学を応用し、冠動脈CTによる得られた画像所見を基に仮想の最大充血下における狭窄前後のFFR(FFR-CT)を算出されることが可能となった。これまでにwireを用いたinvasive FFRと比較し、FFR-CTの有意な正相関が報告されているが、FFR-CT値による予後評価の報告は少ない。FFR-CT値を用いた予後評価を検討する。 関連論文 1)日本循環器学会/日本心臓血管外科学会合同ガイドライン安定冠動脈疾患の血行再建ガイドライン(2018年改定版) 2)Min JK et al. Diagnostic Accuracy of Fractional Flow Reserve From Anatomic CT Angiography. JAMA, 2012; 308: 1237-45