2025/04/22 更新

写真a

フジクラ マミコ
藤倉 満美子
FUJIKURA Mamiko
所属
学術研究院医療開発領域 助教
職名
助教
外部リンク

学位

  • 博士(歯学) ( 2017年9月   昭和大学 )

学歴

  • 昭和大学大学院歯学研究科    

    2013年10月 - 2017年9月

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経歴

  • 岡山大学病院   歯科 歯科放射線科部門   助教

    2020年4月 - 現在

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  • 東京医科歯科大学歯学部附属病院   歯科放射線科   医員

    2015年4月 - 2020年3月

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所属学協会

 

論文

  • Robustness of Machine Learning Predictions for Determining Whether Deep Inspiration Breath-Hold Is Required in Breast Cancer Radiation Therapy 査読

    Wlla E. Al-Hammad, Masahiro Kuroda, Ghaida Al Jamal, Mamiko Fujikura, Ryo Kamizaki, Kazuhiro Kuroda, Suzuka Yoshida, Yoshihide Nakamura, Masataka Oita, Yoshinori Tanabe, Kohei Sugimoto, Irfan Sugianto, Majd Barham, Nouha Tekiki, Miki Hisatomi, Junichi Asaumi

    Diagnostics   15 ( 6 )   668 - 668   2025年3月

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    記述言語:英語   掲載種別:研究論文(学術雑誌)   出版者・発行元:MDPI AG  

    Background/Objectives: Deep inspiration breath-hold (DIBH) is a commonly used technique to reduce the mean heart dose (MHD), which is critical for minimizing late cardiac side effects in breast cancer patients undergoing radiation therapy (RT). Although previous studies have explored the potential of machine learning (ML) to predict which patients might benefit from DIBH, none have rigorously assessed ML model performance across various MHD thresholds and parameter settings. This study aims to evaluate the robustness of ML models in predicting the need for DIBH across different clinical scenarios. Methods: Using data from 207 breast cancer patients treated with RT, we developed and tested ML models at three MHD cut-off values (240, 270, and 300 cGy), considering variations in the number of independent variables (three vs. six) and folds in the cross-validation (three, four, and five). Robustness was defined as achieving high F2 scores and low instability in predictive performance. Results: Our findings indicate that the decision tree (DT) model demonstrated consistently high robustness at 240 and 270 cGy, while the random forest model performed optimally at 300 cGy. At 240 cGy, a threshold critical to minimize late cardiac risks, the DT model exhibited stable predictive power, reducing the risk of overestimating DIBH necessity. Conclusions: These results suggest that the DT model, particularly at lower MHD thresholds, may be the most reliable for clinical applications. By providing a tool for targeted DIBH implementation, this model has the potential to enhance patient-specific treatment planning and improve clinical outcomes in RT.

    DOI: 10.3390/diagnostics15060668

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  • Evaluation of CT Findings in Squamous and Non-Squamous Cell Carcinomas of the Maxillary Sinus 査読

    Yuka Asaumi, Mamiko Fujikura, Miki Hisatomi, Wlla E. Al-Hammad, Yohei Takeshita, Shunsuke Okada, Toshiyuki Kawazu, Yoshinobu Yanagi, Junichi Asaumi

    Journal of Hard Tissue Biology   34 ( 1 )   35 - 40   2025年

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    担当区分:責任著者   記述言語:英語   掲載種別:研究論文(学術雑誌)   出版者・発行元:Society for Hard Tissue Regenerative Biology  

    DOI: 10.2485/jhtb.34.35

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  • Central dentinogenic ghost cell tumor of the maxilla: a case report with new imaging findings and review of the literature 査読

    Suzuka Yoshida, Yohei Takeshita, Toshiyuki Kawazu, Miki Hisatomi, Shunsuke Okada, Mamiko Fujikura, Kyoichi Obata, Kiyofumi Takabatake, Saori Yoshida, Junichi Asaumi

    Oral Radiology   2024年7月

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    掲載種別:研究論文(学術雑誌)   出版者・発行元:Springer Science and Business Media LLC  

    Abstract

    A dentinogenic ghost cell tumor (DGCT) is a rare benign odontogenic tumor that commonly shows characteristics of solid proliferation and has a relatively high risk of recurrence after surgical treatment. We herein report a case of a central DGCT that occurred in the maxilla and resulted in bone expansion. This study highlights new imaging findings (particularly magnetic resonance imaging) along with histopathological observations. In addition, we conducted a review of the existing literature on this rare tumor. A 37-year-old man developed swelling around the right cheek. A benign odontogenic tumor such as ameloblastoma was suspected based on the imaging examination findings (including bone expansion and the internal characteristics of the tumor) on panoramic imaging, computed tomography, and magnetic resonance imaging. The lesion was surgically excised from the right maxilla. Postoperative histopathological examination led to a definitive diagnosis of central DGCT. The tumor comprised epithelial neoplastic islands, resembling ameloblastoma, inside tight fibroconnective tissue; masses of ghost cells and formation of dentin were also observed. We had suspected that the minute high-density region around the molars on the imaging examinations represented alveolar bone change; however, it represented dentin formation. This led to difficulty diagnosing the lesion. Although DGCT may present characteristic findings on imaging examinations, its occurrence is infrequent, and in some cases, the findings may include the presence or absence of an impacted tooth without obvious calcification. The present case suggests that we should consider the possibility of an odontogenic tumor with calcification when high-density structures are observed inside the lesion.

    DOI: 10.1007/s11282-024-00764-4

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    その他リンク: https://link.springer.com/article/10.1007/s11282-024-00764-4/fulltext.html

  • Preliminary Study of Dental Caries Detection by Deep Neural Network Applying Domain-Specific Transfer Learning 査読

    Toshiyuki Kawazu, Yohei Takeshita, Mamiko Fujikura, Shunsuke Okada, Miki Hisatomi, Junichi Asaumi

    Journal of Medical and Biological Engineering   44 ( 1 )   43 - 48   2024年2月

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    掲載種別:研究論文(学術雑誌)  

    Purpose: The purpose of this study is to confirm whether it is possible to acquire a certain degree of diagnostic ability even with a small dataset using domain-specific transfer learning. In this study, we constructed a simulated caries detection model on panoramic tomography using transfer learning. Methods: A simulated caries model was trained and validated using 1094 trimmed intraoral images. A convolutional neural network (CNN) with three convolution and three max pooling layers was developed. We applied this caries detection model to 50 panoramic images and evaluated its diagnostic performance. Results: The diagnostic performance of the CNN model on the intraoral film was as follows: C0 84.6%; C1 90.6%; C2 88.6%. Finally, we tested 50 panoramic images with simulated caries insertion. The diagnostic performance of the CNN model on the panoramic image was as follows: C0 75.0%, C1 80.0%, C2 80.0%, and overall diagnostic accuracy was 78.0%. The diagnostic performance of the caries detection model constructed only with panoramic images was much lower than that of the intraoral film. Conclusion: Domain-specific transfer learning methods may be useful for saving datasets and training time (179/250).

    DOI: 10.1007/s40846-024-00848-w

    Scopus

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  • Imaging characteristics of incidentally detected cosmetic surgery-derived foreign bodies on CT images in the maxillofacial region 査読

    Miki Hisatomi, Yohei Takeshita, Yoshinobu Yanagi, Shunsuke Okada, Mamiko Fujikura, Suzuka Yoshida, Toshiyuki Kawazu, Junichi Asaumi

    Oral Radiology   40 ( 2 )   277 - 284   2024年1月

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    記述言語:英語   掲載種別:研究論文(学術雑誌)   出版者・発行元:Springer Science and Business Media LLC  

    Abstract

    Objectives

    This study examined the imaging characteristics of cosmetic surgery-derived foreign bodies in the maxillofacial region through a retrospective review of cosmetic material foreign bodies incidentally detected on computed tomography (CT) images in routine clinical practice.

    Methods

    We retrospectively investigated cases of cosmetic surgery-derived foreign bodies other than dental materials in the maxillofacial region, using 5 years of CT image data stored on an imaging server. The imaging findings of these foreign bodies were investigated, along with patient age, patient sex, whether the foreign bodies were associated with the disease targeted by the CT scan, and the availability of cosmetic surgery information prior to examination.

    Results

    Foreign bodies were more common in women (19/21 cases), and affected patients displayed a wide age range (20–84 years). Four types of cosmetic surgery-derived foreign bodies in the maxillofacial region were detected by CT examination: nasal prostheses (nasal region), lifting sutures and injectable facial fillers (both in the buccal region), and silicone chin implants (chin region).

    Conclusions

    A cosmetic surgery-derived foreign body should be suspected when a foreign body is identified without a dental source of infection. In addition, cosmetic surgery-derived foreign bodies may be present in numerous patients, regardless of age or sex.

    DOI: 10.1007/s11282-023-00734-2

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    その他リンク: https://link.springer.com/article/10.1007/s11282-023-00734-2/fulltext.html

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MISC

  • 分化度が異なるOSCCにおけるCXCR4阻害剤の有用性

    吉田 沙織, 河合 穂高, 竹下 洋平, 岡田 俊輔, 藤倉 満美子, 久富 美紀, 河津 俊幸, 長塚 仁, 浅海 淳一, 柳 文修

    日本病理学会会誌   112 ( 1 )   290 - 290   2023年3月

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    記述言語:日本語   出版者・発行元:(一社)日本病理学会  

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  • 分化度の異なる口腔扁平上皮癌におけるシスプラチンとCXCR4阻害剤併用の効果

    吉田 沙織, 河合 穂高, 竹下 洋平, 岡田 俊輔, 藤倉 満美子, 久富 美紀, 河津 俊幸, 長塚 仁, 浅海 淳一, 柳 文修

    日本口腔診断学会雑誌   36 ( 1 )   82 - 82   2023年2月

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    記述言語:日本語   出版者・発行元:(一社)日本口腔診断学会  

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  • OSCCにおけるCXCR4阻害剤-シスプラチン併用療法の可能性

    吉田沙織, 河合穂高, 佐能彰, 竹下洋平, 岡田俊輔, 藤倉満美子, 久富美紀, 長塚仁, 浅海淳一, 浅海淳一, 浅海淳一, 柳文修, 柳文修, 柳文修

    日本口腔腫瘍学会総会・学術大会プログラム・抄録集   41st   2023年

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  • 頬粘膜神経鞘腫を契機に発見された多発神経原性腫瘍の1例

    久富美紀, 竹下洋平, 河合穂高, 岡田俊輔, 藤倉満美子, 吉田沙織, 河津俊幸, 長塚仁, 柳文修, 柳文修, 浅海淳一, 浅海淳一

    日本口腔腫瘍学会総会・学術大会プログラム・抄録集   41st   2023年

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  • 口腔顎顔面領域の臨床解剖と画像診断

    竹下洋平, 河津俊幸, 久富美紀, 岡田俊輔, 藤倉満美子, 伊原木聰一郎, 岩永譲, 岩永譲, 影山幾男, 松下祐樹, TUBBS R. Shane, 浅海淳一, 浅海淳一, 浅海淳一

    日本解剖学会総会・全国学術集会講演プログラム・抄録集   127th (CD-ROM)   2022年

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講演・口頭発表等

  • Two cases of de novo myoepithelial carcinoma -focusing on MRI findings-

    Fujikura M., Hisatomi M., Al-hammad WE, Takeshita Y., Okada S., Kawazu T., Fujita M., Yanagi Y., Asaumi J.

    The 14th Asian Congress of Oral and Maxillofacial Radiology  2024年6月14日 

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    開催年月日: 2024年6月11日 - 2024年6月15日

    記述言語:英語   会議種別:ポスター発表  

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  • Evaluation of CT findings in squamous and non-squamous carcinomas of the maxillary sinus

    Asaumi Y., Fujikura M., Hisatomi M., Al-hammad WE, Takeshita Y., Okada S., Fujita M., Kawazu T., Yanagi Y., Asaumi J.

    The 14th Asian Congress of Oral and Maxillofacial Radiology  2024年6月13日 

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    開催年月日: 2024年6月11日 - 2024年6月15日

    記述言語:英語   会議種別:ポスター発表  

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  • CT画像から偶発的に発見された顎口腔領域に認める美容整形由来の異物の画像的検討

    久富美紀, 竹下洋平, 岡田俊輔, 藤倉満美子, 藤田麻里子, 吉田沙織, 難波友里, 吉田鈴加, 河津俊幸, 柳 文修

    日本歯科放射線学会第64回学術大会  2024年5月25日 

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    開催年月日: 2024年5月24日 - 2024年5月26日

    記述言語:日本語   会議種別:ポスター発表  

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  • 含歯性嚢胞のSimple Diffusion Kurtosis Imagingにおける特徴的なMK値

    福村優華, 吉田鈴加, 中村吉秀, 竹下洋平, 岡田俊輔, 藤倉満美子, 久富美紀, 柳文修, 黒田昌宏, 河津俊幸

    日本歯科放射線学会第64回学術大会  2024年5月25日 

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    開催年月日: 2024年5月24日 - 2024年5月26日

    記述言語:日本語   会議種別:口頭発表(一般)  

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  • ChatGPTは日本歯科放射線学会専門医試験対策に有用か

    竹下洋平, 河津俊幸, 久富美紀, 岡田俊輔, 藤倉満美子, 吉田鈴加, 福村優華, 中村吉秀, 柳文修, 浅海淳一

    日本歯科放射線学会第42回関西・九州合同地方会(第65回関西・第61回九州地方会)  2023年12月2日 

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    開催年月日: 2023年12月2日

    記述言語:日本語   会議種別:口頭発表(一般)  

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共同研究・競争的資金等の研究

  • 顎関節症と筋バランスの関連性の解析ーMRIを用いた定量評価ー

    研究課題/領域番号:25K20348  2025年04月 - 2029年03月

    日本学術振興会  科学研究費助成事業  若手研究

    藤倉 満美子

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    配分額:1690000円 ( 直接経費:1300000円 、 間接経費:390000円 )

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担当授業科目

  • 病態エックス線像実習 (2024年度) 第1学期  - 火5,火6,火7

  • 病態エックス線像実習 (2023年度) 第1学期  - 火5,火6,火7

  • 病態エックス線像実習 (2022年度) 第1学期  - 火5,火6,火7