Takahito Nakajima
ORCID: 0000-0001-6704-2297
· 10 papers in corpus
review
2026
Cervical cancer remains a major cause of mortality among women worldwide, highlighting the need for advances in diagnostic and therapeutic strategies. This review provides a comprehensive overview of recent developments in histopathological…
observational
2025
PURPOSE: This study aimed to compare MRI findings among benign, borderline, and malignant ovarian seromucinous neoplasms. METHODS: We retrospectively analyzed MRI data from 24 patients with ovarian seromucinous neoplasms-seven benign, thir…
observational
2025
OBJECTIVES: To investigate the frequency and patterns of calcification in ovarian tumours and evaluate their association with various histological types and malignancy grades. METHODS: This retrospective study included patients who underwe…
diagnostic-accuracy
2025
PURPOSE: To assess the utility of apparent diffusion coefficient maps (ADC) for diagnosing myometrial invasion (MI) in endometrial cancer (EC). METHODS: This retrospective study included 164 patients (mean age, 56 years; range, 25-89 years…
diagnostic-accuracy
2024
PURPOSE: To compare the diagnostic performance of virtual monoenergetic imaging (VMI), computed tomography (CT), and magnetic resonance imaging (MRI) in patients with endometrial cancer (EC). MATERIAL AND METHODS: This retrospective study …
case-report
2024
Arterioportal fistula (APF) combined with a visceral artery pseudoaneurysm is an exceptionally rare and critical vascular disorder of the abdominal viscera, with pseudoaneurysm rupture being potentially fatal and severe APF leading to porta…
review
2024
This review focuses on inflammatory diseases of female and male genital organs and discusses their epidemiology, pathogenesis, clinical presentation, and imaging findings. The female section covers pelvic inflammatory disease (PID) primaril…
observational
2023
BACKGROUND: Preoperative assessment of the histological type of ovarian cancer is essential to determine the appropriate treatment strategy. Tumor location may be helpful in this regard. The purpose of this study was to compare the position…
diagnostic-accuracy
2022
BACKGROUND: This study aimed to compare deep learning with radiologists' assessments for diagnosing ovarian carcinoma using MRI. METHODS: This retrospective study included 194 patients with pathologically confirmed ovarian carcinomas or bo…
diagnostic-accuracy
2022
PURPOSE: To verify whether deep learning can be used to differentiate between carcinosarcomas (CSs) and endometrial carcinomas (ECs) using several magnetic resonance imaging (MRI) sequences. MATERIAL AND METHODS: This retrospective study i…