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Medical Application of Hydrogen in Hematological Diseases.

ABSTRACT: Hydrogen gas has been reported to have medical efficacy since the 1880s. Still, medical researchers did not pay much attention to hydrogen gas until the 20th century. Recent research, both basic and clinical, has proven that hydrogen is an important physiological regulatory factor with antioxidative, anti-inflammatory, and antiapoptotic effects. In the past two decades, more than 1000 papers have been published on the topic, including organ ischemia-reperfusion injury, radiation injury, diabetes, atherosclerosis, hypertension, or cancer. We have previously hypothesized and proven the therapeutic effects of hydrogen gas in graft-versus-host disease following stem cell transplantation. In the current manuscript, we present the clinical advances of hydrogen gas in hematological disorders.

SUBMITTER: Qian L

PROVIDER: S-EPMC6906850 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Medical Application of Hydrogen in Hematological Diseases.

Qian Liren L Wu Zhengcheng Z Cen Jian J Pasca Sergiu S Tomuleasa Ciprian C

Oxidative medicine and cellular longevity 20191128

Hydrogen gas has been reported to have medical efficacy since the 1880s. Still, medical researchers did not pay much attention to hydrogen gas until the 20th century. Recent research, both basic and clinical, has proven that hydrogen is an important physiological regulatory factor with antioxidative, anti-inflammatory, and antiapoptotic effects. In the past two decades, more than 1000 papers have been published on the topic, including organ ischemia-reperfusion injury, radiation injury, diabetes ...[more]

PMID: 31871547

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Project description:BackgroundHere, we conducted a scoping review to (i) establish which machine learning (ML) methods have been applied to hematological malignancy imaging; (ii) establish how ML is being applied to hematological cancer radiology; and (iii) identify addressable research gaps.MethodsThe review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Extension for Scoping Reviews guidelines. The inclusion criteria were (i) pediatric and adult patients with suspected or confirmed hematological malignancy undergoing imaging (population); (ii) any study using ML techniques to derive models using radiological images to apply to the clinical management of these patients (concept); and (iii) original research articles conducted in any setting globally (context). Quality Assessment of Diagnostic Accuracy Studies 2 criteria were used to assess diagnostic and segmentation studies, while the Newcastle-Ottawa scale was used to assess the quality of observational studies.ResultsOf 53 eligible studies, 33 applied diverse ML techniques to diagnose hematological malignancies or to differentiate them from other diseases, especially discriminating gliomas from primary central nervous system lymphomas (n=18); 11 applied ML to segmentation tasks, while 9 applied ML to prognostication or predicting therapeutic responses, especially for diffuse large B-cell lymphoma. All studies reported discrimination statistics, but no study calculated calibration statistics. Every diagnostic/segmentation study had a high risk of bias due to their case-control design; many studies failed to provide adequate details of the reference standard; and only a few studies used independent validation.ConclusionTo deliver validated ML-based models to radiologists managing hematological malignancies, future studies should (i) adhere to standardized, high-quality reporting guidelines such as the Checklist for Artificial Intelligence in Medical Imaging; (ii) validate models in independent cohorts; (ii) standardize volume segmentation methods for segmentation tasks; (iv) establish comprehensive prospective studies that include different tumor grades, comparisons with radiologists, optimal imaging modalities, sequences, and planes; (v) include side-by-side comparisons of different methods; and (vi) include low- and middle-income countries in multicentric studies to enhance generalizability and reduce inequity.

Dataset Information

Medical Application of Hydrogen in Hematological Diseases.

Publications

Medical Application of Hydrogen in Hematological Diseases.

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