Azama Kimei

写真a

Title

Assistant Professor

Researcher Number(JSPS Kakenhi)

30724752
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Current Affiliation Organization 【 display / non-display 】

  • Duty   University of the Ryukyus   Graduate School of Medicine   Assistant Professor  

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Academic degree 【 display / non-display 】

  • University of the Ryukyus -  Doctor

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Published Papers 【 display / non-display 】

  • Selective Transarterial Embolization for Refractory Bleeding in Advanced Scalp Angiosarcoma: Two Cases

    Sakumoto, M; Toyosato, S; Kayo, A; Azama, K; Oshiro, Y; Miyake, R; Komiyama, S; Kaneshima, A; Uehara, H; Miyagi, T; Yamaguchi, S; Yanagi, T

    JOURNAL OF DERMATOLOGY ( Journal of Dermatology )    2026.08 [ Peer Review Accepted ]

    Type of publication: Research paper (scientific journal)

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    Cutaneous angiosarcoma of the scalp is a highly aggressive vascular malignancy that predominantly affects elderly individuals and may cause severe tumor bleeding during disease progression. Hemorrhage from ulcerated tumors is often difficult to control, particularly in patients previously treated with chemoradiotherapy. We report two cases of advanced scalp angiosarcoma in which refractory tumor bleeding was successfully controlled by selective transarterial embolization. The first patient, a 75-year-old man with recurrent angiosarcoma of the frontal scalp region after multiple systemic therapies and radiotherapy, developed repeated arterial bleeding from ulcerated lesions requiring transfusion support. Angiography identified tumor-feeding branches of the superficial temporal artery and angular artery, and embolization achieved immediate hemostasis. A second embolization procedure was required for recurrent bleeding. The second patient, a 75-year-old woman, also developed persistent bleeding from a progressive scalp tumor despite chemoradiotherapy. Selective arterial embolization resulted in rapid and sustained bleeding control without major complications. These cases suggest that selective transarterial embolization may provide rapid control of refractory arterial tumor bleeding and reduce local treatment burden in selected patients with advanced scalp angiosarcoma.

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  • A case of ruptured gastric varices successfully treated with embolization via the paraumbilical vein approach

    SUGIMURA Tomoko, SHIROMA Keisuke, AZAMA Kimei, ITO Junji, NISHIE Akihiro, UMEMURA Takehiro

    Journal of Japanese Society for Emergency Medicine ( Japanese Society for Emergency Medicine )  29 ( 2 ) 153 - 158   2026.04 [ Peer Review Accepted ]

    Type of publication: Research paper (scientific journal)

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    <p>Ruptured varices are life-threatening, and rapid hemostatic intervention directly affects survival. Endoscopic hemostasis is generally considered the first-line treatment; however, it can be difficult when visualization is poor or when the patient presents with respiratory or circulatory failure. Here, we report a case of gastric variceal rupture in which endoscopic hemostasis was not feasible and was successfully managed with variceal embolization via a paraumbilical vein. The patient was a female aged 77 years who developed hemorrhagic shock and hypoxemia due to gastric variceal rupture associated with liver cirrhosis. Endoscopic hemostasis was attempted; however, it could not be completed because of poor visualization caused by continuous hematemesis and the patient's worsening condition. Transhepatic variceal embolization via intrahepatic portal puncture was considered unsuitable due to massive ascites. Therefore, percutaneous puncture of a dilated paraumbilical vein was performed, and varices from the posterior gastric vein were embolized using n-butyl cyanoacrylate. The postoperative course was uneventful, without rebleeding, and the patient was discharged home. Variceal embolization via a paraumbilical vein can be an effective and safe life-saving option for patients in whom endoscopic hemostasis or a transhepatic approach is not feasible.</p>

  • Artificial intelligence-based lung nodule detection for pulmonary arteriovenous fistulas on chest computed tomography

    Azama Kimei, Tsuchiya Nanae, Toyosato Shun, Yonemoto Koji, Nishie Akihiro

    World Journal of Radiology ( Baishideng Publishing Group Inc. )  18 ( 4 ) 1 - 9   2026.04 [ Peer Review Accepted ]

    Type of publication: Research paper (scientific journal)

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    BACKGROUND Pulmonary arteriovenous fistulas (PAVFs) are abnormal vascular communications between pulmonary arteries and veins that may cause hypoxemia and paradoxical embolism. Because many patients are asymptomatic, PAVFs are often detected incidentally on chest computed tomography (CT). Accurate identification of PAVFs is clinically important for appropriate management; however, small or atypical lesions may be overlooked during routine interpretation. Computer-aided detection (CAD) systems for pulmonary nodules are widely used in clinical practice, but their ability to detect PAVFs has not been systematically evaluated. We hypothesized that a lung nodule-based artificial intelligence (AI)- CAD system could detect PAVFs on chest CT. AIM To evaluate the detectability of PAVFs on chest CT using an AI-based CAD system for lung nodules. METHODS This retrospective observational study included 21 patients with 26 PAVFs identified at University of the Ryukyus Hospital between 2009 and 2021. Chest CT images, including non-contrast and contrast-enhanced scans, were analyzed using a commercially available AI-based lung nodule CAD system. Detection performance was classified as consistent, conditional, or failed detection, and lesion characteristics associated with successful detection were analyzed. Correlations between CAD-derived measurements and manual measurements were assessed using Pearson’s correlation coefficient RESULTS Among the 26 PAVFs, 15 lesions (58%) were consistently detected, 2 lesions (8%) were detected under certain imaging conditions, and 9 lesions (35%) were not detected, yielding an overall detection success rate of 65% (17/26). Detection rates did not differ significantly according to contrast phase (58% for non-contrast, 71% for pulmonary arterial phase, and 47% for parenchymal phase) or window setting (61% for lung window vs 58% for mediastinal window). Detection success was higher for complex-type lesions than for simple-type lesions (100% vs 59%, P = 0.26). CAD-derived maximum lesion length correlated strongly with manual measurements (r = 0.90, P < 0.001), as did CAD-derived lesion volume (r = 0.92, P < 0.001). CONCLUSION A lung nodule-based AI-CAD system detected a substantial proportion of PAVFs on chest CT and provided reliable quantitative measurements, supporting its potential adjunctive role in PAVF detection and follow-up.

  • Artificial intelligence-based lung nodule detection for pulmonary arteriovenous fistulas on chest computed tomography.

    Azama K, Tsuchiya N, Toyosato S, Yonemoto K, Nishie A

    World journal of radiology   18 ( 4 ) 119851 - 119851   2026.04 [ Peer Review Accepted ]

    Type of publication: Research paper (scientific journal)

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    BACKGROUND: Pulmonary arteriovenous fistulas (PAVFs) are abnormal vascular communications between pulmonary arteries and veins that may cause hypoxemia and paradoxical embolism. Because many patients are asymptomatic, PAVFs are often detected incidentally on chest computed tomography (CT). Accurate identification of PAVFs is clinically important for appropriate management; however, small or atypical lesions may be overlooked during routine interpretation. Computer-aided detection (CAD) systems for pulmonary nodules are widely used in clinical practice, but their ability to detect PAVFs has not been systematically evaluated. We hypothesized that a lung nodule-based artificial intelligence (AI)-CAD system could detect PAVFs on chest CT. AIM: To evaluate the detectability of PAVFs on chest CT using an AI-based CAD system for lung nodules. METHODS: This retrospective observational study included 21 patients with 26 PAVFs identified at University of the Ryukyus Hospital between 2009 and 2021. Chest CT images, including non-contrast and contrast-enhanced scans, were analyzed using a commercially available AI-based lung nodule CAD system. Detection performance was classified as consistent, conditional, or failed detection, and lesion characteristics associated with successful detection were analyzed. Correlations between CAD-derived measurements and manual measurements were assessed using Pearson's correlation coefficient. RESULTS: Among the 26 PAVFs, 15 lesions (58%) were consistently detected, 2 lesions (8%) were detected under certain imaging conditions, and 9 lesions (35%) were not detected, yielding an overall detection success rate of 65% (17/26). Detection rates did not differ significantly according to contrast phase (58% for non-contrast, 71% for pulmonary arterial phase, and 47% for parenchymal phase) or window setting (61% for lung window vs 58% for mediastinal window). Detection success was higher for complex-type lesions than for simple-type lesions (100% vs 59%, P = 0.26). CAD-derived maximum lesion length correlated strongly with manual measurements (r = 0.90, P < 0.001), as did CAD-derived lesion volume (r = 0.92, P < 0.001). CONCLUSION: A lung nodule-based AI-CAD system detected a substantial proportion of PAVFs on chest CT and provided reliable quantitative measurements, supporting its potential adjunctive role in PAVF detection and follow-up.

  • Non-thrombotic pulmonary emboli: imaging findings and differential diagnoses

    Tsuchiya, N; Chinen, Y; Yumoto, K; Uechi, M; Ito, J; Azama, K; Makino, W; Koga, T; Nishie, A

    JAPANESE JOURNAL OF RADIOLOGY ( Japanese Journal of Radiology )  43 ( 11 ) 1746 - 1760   2025.11 [ Peer Review Accepted ]

    Type of publication: Research paper (scientific journal)

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    OBJECTIVE: Nonthrombotic pulmonary embolism (NTPE) encompasses a diverse group of rare but clinically significant conditions that involve fat, tumor, air, amniotic fluid, septic, parasitic, and iatrogenic emboli. This review summarizes the pathophysiology, imaging findings, and differential diagnoses of NTPE toward the goal of facilitating its accurate radiologic diagnosis. CONTENT: In NTPE, the use of computed tomography pulmonary angiography (CTPA) may reveal filling defects in the pulmonary arteries; however, the embolus is often not directly visualized, especially in cases of microscopic emboli. NTPE-related pulmonary lesions arise from two mechanisms: mechanical obstruction and chemical injury. Clarifying the link between these mechanisms and imaging features is crucial for achieving the accurate diagnosis of NTPEs. Tools such as dual-energy CT and ventilation-perfusion scintigraphy contribute to the detection of microvascular involvement. We present the characteristic imaging patterns and diagnostic pitfalls for each NTPE subtype, illustrated with representative cases. CONCLUSION: The awareness of NTPE entities and their imaging features is essential for the timely diagnosis and management of these emboli. Radiologists should consider the possible presence of an NTPE in patients with unexplained respiratory symptoms, especially when conventional imaging fails to demonstrate thrombotic emboli.

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