Evidence map›Paper›PMID 41723750›Full record

ArticleEJNMMI physics2026

Advanced image reconstruction algorithms for high-resolution digital time-of-flight PET/CT enhance visualization of sub-clinical internal mammary lymph node metastases in breast cancer: a phantom and a clinical, retrospective cohort study.

Yoko Satoh, Kenta Miwa, Akinori Takenaka, Yoshitaka Inui, Masanori Watanabe, Tensho Yamao, Noriaki Miyaji, Seiichiro Ota, Edwin K Leung, Xibin Quan and 2 more

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Article in EJNMMI physics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

12 authors.

Yoko SatohImaging Center, Fujita Medical Innovation Center Tokyo, 1-1-4 Hanedakuko, Ota-ku, Tokyo, Japan. yoko.sato@fujita-hu.ac.jp.ORCID http://orcid.org/0000-0002-0188-0906
Kenta MiwaDepartment of Radiological Sciences, School of Health Sciences, Fukushima Medical University, Fukushima, Japan.
Akinori TakenakaDepartment of Radiology, Fujita Health University School of Medicine, Aichi, Japan.
Yoshitaka InuiDepartment of Radiology, Fujita Health University School of Medicine, Aichi, Japan.
Masanori WatanabeDepartment of Radiology, Fujita Health University Hospital, Aichi, Japan.
Tensho YamaoDepartment of Radiological Sciences, School of Health Sciences, Fukushima Medical University, Fukushima, Japan.
Noriaki MiyajiDepartment of Radiological Sciences, School of Health Sciences, Fukushima Medical University, Fukushima, Japan.
Seiichiro OtaDepartment of Radiology, Fujita Health University School of Medicine, Aichi, Japan.
Edwin K LeungUnited Imaging Healthcare North America, Inc., Houston, TX, USA.
Xibin QuanShanghai United Imaging Healthcare Co. Ltd., Shanghai, China.
Hiroshi ToyamaDepartment of Radiology, Fujita Health University School of Medicine, Aichi, Japan.
Masanori InoueDepartment of Radiology, Fujita Health University School of Medicine, Aichi, Japan.

Funding

United Imaging Halthcare Japan United Imaging Halthcare Japan
6 · The paper itself

Abstract

backgroundInternal mammary lymph node (IMLN) metastases play an important role in breast cancer staging and treatment planning but is often difficult to detect because of their small size and anatomical location. Recent advances in digital time-of-flight (TOF) positron emission tomography (PET)/CT and advanced image reconstruction techniques may improve the visualization of such small lesions. This study aimed to evaluate the performance of advanced reconstruction methods (HYPER Iterative and uAI HYPER DPR) for visualizing IMLN metastases in breast cancer using phantom and clinical data.

methodsA modified NEMA image quality phantom and a retrospective cohort of breast cancer patients with IMLN metastases were evaluated using a high-resolution digital TOF PET/CT system (uMI 550). Images were reconstructed using ordered subset expectation maximization (OSEM), HYPER Iterative, and uAI HYPER DPR with different reconstruction parameters, and quantitative metrics and visual scores were assessed.

resultsIn both phantom and clinical images, smaller RS-values for HYPER Iterative and larger Str-values for uAI HYPER DPR were associated with higher lesion conspicuity and contrast-related metrics, at the expense of increased noise. Images reconstructed with a 256 × 256 matrix showed lower background variability than those reconstructed with a 512 × 512 matrix. In the clinical study, these reconstruction settings resulted in higher SUV

Indexed as

Breast cancerDiagnostic performanceDigital PET/CTImage reconstructionIntramammary lymph node metastasis

Identifiers

PMID41723750
PMCPMC12963589

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