Masahiro Kuroda

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About

Masahiro Kuroda is a Professor at the Graduate School of Health Sciences, Okayama University, Japan. His research focuses on the application of machine learning and advanced imaging techniques in oncology, particularly in improving diagnostic precision for head and neck tumors and breast cancer radiation therapy. Recent publications highlight his work on diffusion kurtosis imaging, modeling heart dose predictions, and assessing treatment outcomes for non-small cell lung cancer.

Recent Grants

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Development of clinical MRI software for quantitative analysis of intra-tumor apoptosis and its clinical trial

Open Date: 2019-04-01

Close Date: 2024-03-31

Grant: Close

Development of a new molecular image analysis method for quantitative evaluation of intratumoral apoptosis

Open Date: 2015-04-01

Close Date: 2019-03-31

Grant: Close

An establishment of the novel molecular imaging technique for the quantitative evaluation of the intra-tumoral apoptosis

Open Date: 2010-04-01

Close Date: 2014-03-31

Grant: Close

Development of No Induction Stent That Visualizes in Stent Lumen in MR Imaging

Open Date: 2007-01-01

Close Date: 2009-12-31

Grant: Close

ラジオ波焼灼療法と樹状細胞移植を併用する新しい悪性腫瘍の集学的治療法の開発

Open Date: 2003-01-01

Close Date: 2005-12-31

Articles (14)

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2025

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2025

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2024

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2023

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2023

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2023

We evaluated the usefulness of simple diffusion kurtosis (SD) imaging, which was developed to generate diffusion kurtosis images simultaneously with an apparent diffusion coefficient (ADC) map for 27 cystic disease lesions in the head and neck region. The mean kurtosis (MK) and ADC values were calculated for the cystic space. The MK values were dentigerous cyst (DC): 0.74, odontogenic keratocyst (OKC): 0.86, ranula (R): 0.13, and mucous cyst (M): 0, and the ADC values were DC: 1364 × 10−6 mm2/s, OKC: 925 × 10−6 mm2/s, R: 2718 × 10−6 mm2/s, and M: 2686 × 10−6 mm2/s. The MK values of DC and OKC were significantly higher than those of R and M, whereas their ADC values were significantly lower. One reason for the characteristic signal values in diffusion-weighted images of DC may be related to content components such as fibrous tissue and exudate cells. When imaging cystic disease in the head and neck region using SD imaging, the maximum b-value setting at the time of imaging should be limited to approximately 1200 s/mm2 for accurate MK value calculation. This study is the first to show that the MK values of DC are characteristically higher than those of other cysts.

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2023

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2021

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2021

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2021

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2021

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2021

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2020

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2020

Collaborators (7)

Kohei Sugimoto

Assistant Professor

Kawasaki University of Medical Welfare

JAPAN
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Yoshihide Nakamura

Okayama University

JAPAN
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Yoshinobu YANAGI

-

JAPAN
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yoshinori tanabe

Okayama University

JAPAN
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Miki Hisatomi

Okayama University Hospital

JAPAN
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Junichi Asaumi

Okayama University

JAPAN
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Masataka Oita

Associate Professor

Okayama University

JAPAN
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