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DOI 10.1007/s00432-021-03606-6

Медицинская библиотека · Journal of cancer research and clinical oncology · 2021

Radiomics MRI for lymph node status prediction in breast cancer patients: the state of art.

Calabrese Alessandro, Santucci Domiziana, Landi Roberta, Beomonte Zobel Bruno, Faiella Eliodoro, de Felice Carlo

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Аннотация

OBJECTIVES

To create a review of the existing literature on the radiomic approach in predicting the lymph node status of the axilla in breast cancer (BC).

MATERIALS AND

METHODS

Two reviewers conducted the literature search on MEDLINE databases independently. Ten articles on the prediction of sentinel lymph node metastasis in breast cancer with a radiomic approach were selected. The study characteristics and results were reported. The quality of the methodology was evaluated according to the Radiomics Quality Score (RQS).

RESULTS

All studies were retrospective in design and published between 2017 and 2020. The majority of studies used DCE-MRI sequences and two investigated only pre-contrast images. The sample size was lower than 200 patients for 7 studies. The pre-processing used software, feature extraction and selection methods and classifier development are heterogeneous and a standardization of results is not yet possible. The average RQS score was 11.1 (maximum possible value = 36). The criteria with the lowest scores were the type of study, validation, comparison with a gold standard, potential clinical utility, cost-effective analysis and open science data.

CONCLUSION

The field of radiomics is a diagnostic approach of relative recent development. The results in predicting axillary lymph node status are encouraging, but there are still weaknesses in the quality of studies that may limit the reproducibility of the results.

Для цитирования: Calabrese Alessandro, Santucci Domiziana, Landi Roberta, Beomonte Zobel Bruno, Faiella Eliodoro, de Felice Carlo. Radiomics MRI for lymph node status prediction in breast cancer patients: the state of art.. Journal of cancer research and clinical oncology. 2021. DOI: 10.1007/s00432-021-03606-6.

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