PET image nonuniformity texture features for metastasis risk prediction in osteosarcoma

Combining PET image texture nonuniformity with Ki-67 expression and clinical data can enhance the accuracy of metastasis prediction in osteosarcoma. This multimodal approach may support metastasis risk prediction in osteosarcoma and aid in personalized treatment planning.

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Publication Details

Journal
Nuclear Medicine Communications
Published
2025-05-06
DOI
https://doi.org/10.1097/mnm.0000000000001989
Citations
1
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
1.36
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PET image nonuniformity texture features for metastasis risk prediction in osteosarcoma

Muna Almaslamani, Byung-Hyun Byun, Kanghyon Song, Sang-Keun Woo et al.
1 citations
Nuclear Medicine Communications
Radiomics and Machine Learning in Medical Imaging
1.36
article

PET image nonuniformity texture features for metastasis risk prediction in osteosarcoma

Muna Almaslamani, Byung-Hyun Byun, Kanghyon Song, Sang-Keun Woo, Chang-Bae Kong
article en
1 citations

Abstract

Combining PET image texture nonuniformity with Ki-67 expression and clinical data can enhance the accuracy of metastasis prediction in osteosarcoma. This multimodal approach may support metastasis risk prediction in osteosarcoma and aid in personalized treatment planning.

Nuclear Medicine CommunicationsVol. 46(8)
Korea Institute of Radiological and Medical Sciences (KR), Korea University of Science and Technology (KR)
Life in Land
Openalex Percentile: Top 21%
Radiomics and Machine Learning in Medical Imaging
1.36
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