Evidence map›Paper›PMID 42159908›Full record

ArticleJapanese journal of radiology2026

Evaluation of 2D and 3D nnU-Net models with two-label and three-label strategies for automatic segmentation and total metabolic tumor volume estimation of metastatic differentiated thyroid carcinoma on FDG-PET/CT.

Yingtong Li, Hiroki Endo, Kenji Hirata, Junki Takenaka, Minghui Tang, Shiro Watanabe, Rina Kimura, Kohsuke Kudo

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Article in Japanese journal of radiology, 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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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Yingtong LiDepartment of Diagnostic Imaging, Graduate School of Medicine, Hokkaido University, Kita 14, Nishi 5, Kita-ku, Sapporo, 060-8648, Japan.
Hiroki EndoDepartment of Diagnostic Imaging, Graduate School of Medicine, Hokkaido University, Kita 14, Nishi 5, Kita-ku, Sapporo, 060-8648, Japan.
Kenji HirataDepartment of Diagnostic Imaging, Graduate School of Medicine, Hokkaido University, Kita 14, Nishi 5, Kita-ku, Sapporo, 060-8648, Japan. khirata@med.hokudai.ac.jp.ORCID http://orcid.org/0000-0003-0036-8975
Junki TakenakaDepartment of Diagnostic Imaging, Graduate School of Medicine, Hokkaido University, Kita 14, Nishi 5, Kita-ku, Sapporo, 060-8648, Japan.
Minghui TangDepartment of Diagnostic Imaging, Graduate School of Medicine, Hokkaido University, Kita 14, Nishi 5, Kita-ku, Sapporo, 060-8648, Japan.
Shiro WatanabeDepartment of Diagnostic Imaging, Graduate School of Medicine, Hokkaido University, Kita 14, Nishi 5, Kita-ku, Sapporo, 060-8648, Japan.
Rina KimuraDepartment of Diagnostic Imaging, Graduate School of Medicine, Hokkaido University, Kita 14, Nishi 5, Kita-ku, Sapporo, 060-8648, Japan.
Kohsuke KudoDepartment of Diagnostic Imaging, Graduate School of Medicine, Hokkaido University, Kita 14, Nishi 5, Kita-ku, Sapporo, 060-8648, Japan.

Funding

Cabinet Office BRIDGE (programs for bridging the gap between R&D and the ideal society (Society 5.0) and generating economic and social value) 23K07150 and JP20K08015JSPS KAKENHI 23K07150 and JP20K08015JST BOOST JPMJBS2426
6 · The paper itself

Abstract

purposeTo evaluate the segmentation performance and total metabolic tumor volume (TMTV) prediction accuracy of 2D and 3D nnU-Net models under two-label and three-label strategies for metastatic differentiated thyroid carcinoma (DTC) on FDG PET/CT images. MATERIALS AND

methodsA total of 194 patients with FDG-avid metastatic DTC who underwent PET/CT prior to iodine-131 treatment (2009-2022) were retrospectively analyzed. The dataset was divided into Cohort 1 (n = 160) for five-fold cross-validation and Cohort 2 (n = 34) for independent testing. Both 2D and 3D nnU-Net architectures were trained under two-label and three-label schemes. Segmentation performance was assessed using the Dice similarity coefficient (DSC). TMTV prediction was evaluated using the coefficient of determination (R

resultsUnder the two-label scheme, mean DSC values in Cohort 1 were 0.63 ± 0.28 (2D) and 0.60 ± 0.34 (3D), and in Cohort 2 were 0.60 ± 0.31 and 0.50 ± 0.32, respectively. Under the three-label scheme, mean DSC values in Cohort 1 were 0.66 ± 0.28 (2D) and 0.70 ± 0.30 (3D), and in Cohort 2 were 0.61 ± 0.33 and 0.61 ± 0.35, respectively. For TMTV prediction, R

conclusionThe 2D and 3D nnU-Net models demonstrated comparable performance for segmentation and TMTV prediction under both two-label and three-label strategies. While labeling strategy influenced segmentation metrics, systematic underestimation of TMTV was observed across architectures.

Indexed as

Imaging, Three-DimensionalPositron Emission Tomography Computed TomographyThyroid NeoplasmsAdultAgedFemaleFluorodeoxyglucose F18HumansMaleMiddle AgedRadiopharmaceuticalsRetrospective StudiesTumor BurdenFluorodeoxyglucose F18RadiopharmaceuticalsConvolutional neural networkDeep learningDifferentiated thyroid carcinomannU-netSegmentation

Identifiers

PMID42159908

What Socratic holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.