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349 results on '"Levin, Adam S"'

27. Screening for Asymptomatic Osteonecrosis of the Hip in Systemic Lupus Erythematous: A Systematic Review and Meta-Analysis of MRI-Based Prevalence.

Author

Ibad, Hamza A., Ghotbi, Elena, Kasaeian, Arta, Levin, Adam S., Jones, Lynne C., Anzai, Yoshimi, Soltanolkotabi, Maryam, Kapoor, Neena, Johnson, Pamela T., and Demehri, Shadpour

Subjects
OSTEONECROSIS, HIP joint, SYSTEMIC lupus erythematosus
Abstract

Objective. This paper aims to estimate asymptomatic hip osteonecrosis prevalence in SLE patients using MRI examination and to determine the prevalence among higher risk subpopulations. Materials and Methods. PubMed, Embase, Cochrane, and SCOPUS were searched from inception to May 9th, 2023. Studies on patients who were clinically diagnosed with systemic lupus erythematosus without reported symptoms attributable to hip osteonecrosis were included. Two independent reviewers extracted data and assessed the risk of bias. Data collected from each study include the study year, the number of hips screened, the number of hips with osteonecrosis, demographics, laboratory data, medications, follow-up time, radiological protocols, and MRI-based osteonecrosis detection and grading criteria. Results. Eleven eligible studies including 503 participants (15–35 years old; 74–100% female) with SLE were identified. Significant risk of bias was determined in one study. The overall prevalence of osteonecrosis of the hip was found to be 14% (184/1006 hip joints, 95% confidence interval: 7–22%, number needed to scan: 7.1). SLE patients who received corticosteroid treatment had a higher prevalence of asymptomatic hip osteonecrosis (18%) compared to non-corticosteroid users (0%, p-value < 0.01). Additionally, meta-regression results revealed that daily corticosteroid dose was associated with increased prevalence of asymptomatic osteonecrosis (0.5%/milligram, p-value < 0.01). Conclusions. The high prevalence of asymptomatic hip osteonecrosis in SLE patients raises concerns about the timeliness of interventions. The limitations of this study include a relatively low number of identified studies; and one study lacked full-text availability. [ABSTRACT FROM AUTHOR]

Published
2024
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29. The use of weakly supervised machine learning for necrosis assessment in patients with osteosarcoma: A pilot study.

Author

LiBrizzi, Christa L., Wang, Zhenzhen, Sulam, Jeremias, James, Aaron W., Levin, Adam S., and Morris, Carol D.

Subjects
SUPERVISED learning, MACHINE learning, PEARSON correlation (Statistics), OSTEOSARCOMA, PILOT projects
Abstract

Percent necrosis (PN) following chemotherapy is a prognostic factor for survival in osteosarcoma. Pathologists estimate PN by calculating tumor viability over an average of whole‐slide images (WSIs). This non‐standardized, labor‐intensive process requires specialized training and has high interobserver variability. Therefore, we aimed to develop a machine‐learning model capable of calculating PN in osteosarcoma with similar accuracy to that of a musculoskeletal pathologist. In this proof‐of‐concept study, we retrospectively obtained six WSIs from two patients with conventional osteosarcomas. A weakly supervised learning model was trained by using coarse and incomplete annotations of viable tumor, necrotic tumor, and nontumor tissue in WSIs. Weakly supervised learning refers to processes capable of creating predictive models on the basis of partially and imprecisely annotated data. Once "trained," the model segmented areas of tissue and determined PN of the same six WSIs. To assess model fidelity, the pathologist also estimated PN of each WSI, and we compared the estimates using Pearson's correlation and mean absolute error (MAE). MAE was 15% over the six samples, and 6.4% when an outlier was removed, for which the model inaccurately labeled cartilaginous tissue. The model and pathologist estimates were strongly, positively correlated (r = 0.85). Thus, we created and trained a weakly supervised machine learning model to segment viable tumor, necrotic tumor, and nontumor and to calculate PN with accuracy similar to that of a musculoskeletal pathologist. We expect improvement can be achieved by annotating cartilaginous and other mesenchymal tissue for better representation of the histological heterogeneity in osteosarcoma. [ABSTRACT FROM AUTHOR]

Published
2024
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31. Impact of Consolidative Radiation on Overall and Progression-Free Survival in Pediatric, Adolescent, and Young Adult Metastatic Bone and Soft Tissue Sarcoma

Author

Chang, Leslie, primary, D'Amiano, Anjali, additional, Bhatia, Rohini, additional, Yenokyan, Gayane, additional, Llosa, Nicolas J., additional, Ladle, Brian H., additional, Meyer, Christian F., additional, Levin, Adam S., additional, Pratilas, Christine A., additional, Ladra, Matthew, additional, and Acharya, Sahaja, additional

Published
2023
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32. Metastatic sarcomatoid carcinoma to bone

Author

Sabharwal, Samir, primary, LiBrizzi, Christa L., additional, Wangsiricharoen, Sintawat, additional, Gross, John M., additional, Strike, Sophia A., additional, Levin, Adam S., additional, and Morris, Carol D., additional

Published
2023
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39. Complex/cryptic EWSR1::FLI1/ERG Gene Fusions and 1q Jumping Translocation in Pediatric Ewing Sarcomas

Author

Zou, Ying S., primary, Morsberger, Laura, additional, Hardy, Melanie, additional, Ghabrial, Jen, additional, Stinnett, Victoria, additional, Murry, Jaclyn B., additional, Long, Patty, additional, Kim, Andrew, additional, Pratilas, Christine A., additional, Llosa, Nicolas J., additional, Ladle, Brian H., additional, Lemberg, Kathryn M., additional, Levin, Adam S., additional, Morris, Carol D., additional, Haley, Lisa, additional, Gocke, Christopher D., additional, and Gross, John M., additional

Published
2023
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