Publications by authors named "M Y O Misawa"

Background: Artificial intelligence (AI) has significantly impacted medical imaging, particularly in gastrointestinal endoscopy. Computer-aided detection and diagnosis systems (CADe and CADx) are thought to enhance the quality of colonoscopy procedures.

Summary: Colonoscopy is essential for colorectal cancer screening, but often misses a significant percentage of adenomas.

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Background: Brain tumor in children can induce hemianopia, a loss of conscious vision, profoundly impacting their development and quality of life, yet no effective intervention exists for this pediatric population. This study aimed to explore the feasibility, safety, and potential effectiveness of a home-based audiovisual stimulation in immersive virtual-reality (3D-MOT-IVR) to improve visual function and functional vision.

Methods: In a phase 2a, open-labeled, nonrandomized, single-arm study, conducted from July 2022 to October 2023 (NCT05065268), 10 children and adolescents with stable hemianopia were enrolled to perform 20-min sessions of 3D-MOT-IVR every other day for six weeks from home.

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Objectives: This study evaluates risk factors for lymph node metastasis (LNM) in T2 colorectal cancer to refine patient selection for endoscopic resection.

Methods: We reviewed records from consecutive patients who had undergone curative surgical resection of T2 colorectal cancer at our institution in Japan between April 2001 and December 2021. Data on conventional clinicopathologic variables were retrieved from the pathology reports at the time of surgery.

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Article Synopsis
  • The study focuses on the need for an objective method to evaluate and compare different computer-aided detection (CADe) algorithms used in colorectal cancer screening, as their performance varies and no standard exists.
  • A modified Delphi approach was employed, where 25 experts generated and prioritized scoring criteria over eight months, ultimately identifying six key metrics, including sensitivity and adenoma detection rate.
  • The resulting criteria aim to guide the development and improvement of CADe software, with future research suggested to validate these metrics on benchmark video datasets.
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