Radiomics analysis based on multiple parameters MR imaging in the spine: Predicting treatment response of osteolytic bone metastases to chemotherapy in breast cancer patients

Shi, Yan‐Jie; Zhu, Hai‐Tao; Li, Xiaoting; Zhang, Xiaoyan; Wei, Yi‐Yuan; Yan, Shuo; Sun, Ying‐Shi

doi:10.1016/j.mri.2022.05.012

Cited by 3 publications

(1 citation statement)

References 27 publications

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“…In patients with vertebral metastases, the ability to predict treatment response may help clinicians provide the most appropriate treatment with the best clinical outcome for the patient, avoid delayed transition to another treatment and prevent exposing patients to unnecessary treatment-related side effects. Shi YJ et al [ 101 ] studied the value of MRI-based radiomics in predicting the treatment response of chemotherapy in a small group of breast cancer patients with vertebral metastases. Their radiomics model was effective in predicting progressive vs non-progressive disease with an area under the curve (AUC) of up to 0.91.…”

Section: Discussionmentioning

confidence: 99%

Application of Artificial Intelligence Methods for Imaging of Spinal Metastasis

Ong

Zhu

Zhang

et al. 2022

Cancers

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Spinal metastasis is the most common malignant disease of the spine. Recently, major advances in machine learning and artificial intelligence technology have led to their increased use in oncological imaging. The purpose of this study is to review and summarise the present evidence for artificial intelligence applications in the detection, classification and management of spinal metastasis, along with their potential integration into clinical practice. A systematic, detailed search of the main electronic medical databases was undertaken in concordance with the PRISMA guidelines. A total of 30 articles were retrieved from the database and reviewed. Key findings of current AI applications were compiled and summarised. The main clinical applications of AI techniques include image processing, diagnosis, decision support, treatment assistance and prognostic outcomes. In the realm of spinal oncology, artificial intelligence technologies have achieved relatively good performance and hold immense potential to aid clinicians, including enhancing work efficiency and reducing adverse events. Further research is required to validate the clinical performance of the AI tools and facilitate their integration into routine clinical practice.

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Section: Discussionmentioning

confidence: 99%

Application of Artificial Intelligence Methods for Imaging of Spinal Metastasis

Ong

Zhu

Zhang

et al. 2022

Cancers

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Radiomics and radiogenomics of central nervous system metastatic lesions

Perillo,

Somma,

de Giorgi

et al. 2024

Radiomics and Radiogenomics in Neuro-Oncology

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A Multidisciplinary Update on Treatment Modalities for Metastatic Spinal Tumors with a Surgical Emphasis: A Literature Review and Evaluation of the Role of Artificial Intelligence

Houston,

Desai,

Takayanagi

et al. 2024

Cancers

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Spinal metastases occur in up to 40% of patients with cancer. Of these cases, 10% become symptomatic. The reported incidence of spinal metastases has increased in recent years due to innovations in imaging modalities and oncological treatments. As the incidence of spinal metastases rises, so does the demand for improved treatments and treatment algorithms, which now emphasize greater multidisciplinary collaboration and are increasingly customized per patient. Uniquely, we discuss the potential clinical applications of AI and NGS in the treatment of spinal metastases. Material and Methods: A PubMed search for articles published from 2000 to 2023 regarding spinal metastases and artificial intelligence in healthcare was completed. After screening for relevance, the key findings from each study were summarized in this update. Results: This review summarizes the evidence from studies reporting on treatment modalities for spinal metastases, including minimally invasive surgery (MIS), external beam radiation therapy (EBRT), stereotactic radiosurgery (SRS), CFR-PEEK instrumentation, radiofrequency ablation (RFA), next-generation sequencing (NGS), artificial intelligence, and predictive models.

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Radiomics analysis based on multiple parameters MR imaging in the spine: Predicting treatment response of osteolytic bone metastases to chemotherapy in breast cancer patients

Cited by 3 publications

References 27 publications

Application of Artificial Intelligence Methods for Imaging of Spinal Metastasis

Application of Artificial Intelligence Methods for Imaging of Spinal Metastasis

Radiomics and radiogenomics of central nervous system metastatic lesions

A Multidisciplinary Update on Treatment Modalities for Metastatic Spinal Tumors with a Surgical Emphasis: A Literature Review and Evaluation of the Role of Artificial Intelligence

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