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Yusuke S Hori

Publications and source records attributed to Yusuke S Hori.

2 recordsLinked to original sources
PubMed2026

Outcomes of stereotactic radiosurgery for spine multiple myeloma-a systematic review.

Spinal involvement in multiple myeloma (MM) commonly results in pain, vertebral instability, epidural spinal cord compression, and neurological deficits. Although conventional external beam radiation therapy (EBRT) remains the standard radiation modality because of the radiosensitive nature of MM, stereotactic radiosurgery (SRS) has emerged as a highly conformal treatment option capable of delivering focal high-dose radiation while sparing adjacent spinal cord structures and uninvolved bone marrow. This systematic review evaluated the clinical outcomes and safety profile of SRS for spinal MM. A systematic review of the literature was performed to identify studies evaluating SRS for spinal MM. Extracted variables included patient demographics, tumor characteristics, treatment parameters, radiographic outcomes, pain response, neurological outcomes, local control, overall survival, and adverse events. Three retrospective studies comprising 133 patients and 181 treated spinal lesions met the inclusion criteria. Median patient age ranged from 59 to 65 years, with a slight male predominance across studies. Thoracic spine lesions represented the most treated region (55.5-67.7%). Median prescribed SRS dose was 14-16 Gy, predominantly delivered in a single fraction. Median follow-up ranged from 11.2 to 27.8 months. Local control rates ranged from 89.4 to 100%, with 6- and 12-month local control rates of 94% and 91%, respectively, in one study. Pain improvement was reported in 41-88% of treated patients/sites, with a median time to pain relief of 1.6 months in one cohort. Neurological improvement occurred in 56-71.4% of patients with preexisting deficits. Reported adverse events included vertebral compression fractures, fracture progression, pain flare, and tracheoesophageal fistula. De novo vertebral fractures ranged from 3.6 to 7%, while fracture progression ranged from 14 to 18%. SRS appears to provide excellent local control and meaningful pain and neurological improvement in patients with spinal MM, with acceptable toxicity profiles. The highly conformal nature of SRS may preserve uninvolved bone marrow and facilitate continuation of systemic therapy. However, the current evidence is limited to small retrospective studies with heterogeneous reporting, and further prospective comparative studies are needed to better define the role of SRS relative to conventional EBRT in spinal MM.

Humans↗
PubMed2026

Artificial intelligence (AI) uses in stereotactic radiosurgery (SRS): diagnosis with brain metastasis (BM) - A systematic review.

BACKGROUND: Brain metastases (BM) are the most common intracranial tumors in adults, and stereotactic radiosurgery (SRS) has become a mainstay of management. However, several diagnostic challenges persist in the SRS pathway, particularly the differentiation of radiation necrosis (RN) from true tumor progression, which conventional MRI and even advanced imaging techniques often cannot reliably resolve. Recent advances in artificial intelligence (AI) offer the potential to address these diagnostic limitations. This systematic review synthesizes current literature on AI applications for MRI-based diagnostic decision support in BM patients undergoing SRS, with a focus on radiomics and deep learning tools for distinguishing RN from progression, classifying molecular and histologic subtypes, and predicting treatment response. METHODS: A systematic review was performed in accordance with PRISMA guidelines. PubMed, Web of Science, and Scopus were searched using a targeted query combining terms related to AI, brain metastasis, diagnosis or imaging, and SRS. After screening 483 records and applying strict inclusion and exclusion criteria, 18 studies published between 2015 and 2025 were included. Data were extracted on study design, cohort characteristics, imaging modality, AI methodology, validation strategy, and reported diagnostic performance. RESULTS: Among the 18 included studies, AI models demonstrated strong performance across diagnostic tasks in the BM-SRS pathway. The differentiation of RN from true tumor progression was the most extensively studied application, addressed by 14 of 18 studies, with reported AUCs ranging from 0.71 to 0.94. Support vector machines, random-forest ensembles, convolutional neural networks, and transformer-based multimodal architectures were widely used. The literature evolved from single-sequence radiomic classifiers in 2018 to multimodal deep learning frameworks fusing imaging with clinical and genomic data in 2025. Contrast-enhanced T1-weighted MRI was the dominant imaging input, and texture-based radiomic features (GLCM, GLSZM, GLDM, and wavelet-derived features) were the most consistently predictive. The highest-performing models reached AUCs of 0.85-0.91 through multimodal integration of imaging with clinical and genomic features, and consistently outperformed expert neuroradiologist read on matched cases. Remaining studies addressed longitudinal segmentation-based detection of local failure and adverse radiation effects, BRAF mutation status in melanoma BM, early Gamma Knife treatment response, and primary tumor histology classification, with more variable performance. CONCLUSION: AI models, particularly those integrating MRI-derived radiomic features with clinical and genomic data, show high accuracy in supporting diagnostic decisions for BM patients treated with SRS. The post-SRS differentiation of radiation necrosis from true tumor progression has reached the greatest level of maturity and is closest to clinical translation, with potential to reduce unnecessary biopsies, personalize surveillance intervals, and rationalize treatment-pathway decisions. Other diagnostic applications, including molecular subtyping and primary tumor histology classification, remain exploratory and require further multicenter validation. Integration of AI tools into multidisciplinary tumor-board workflows, combined with prospective validation and standardized reporting, will be essential to realize the full clinical benefits of AI in SRS for brain metastases.

Humans↗