Conversion of MR signals into units of metabolite concentration requires a very high level of diligence to account for the numerous parameters and transformations that affect the proportionality between the quantity of excited nuclei in the acquisition volume and the integrated area of the corresponding peak in the spectrum. We describe a method that eases this burden with respect to the transformations that occur during and following data acquisition. The conceptual approach is similar to the ERETIC method, which uses a pre-calibrated, artificial reference signal as a calibration factor to accomplish the conversion. The distinguishing feature of our method is that the artificial signal is introduced strictly via induction, rather than radiation. We tested a prototype probe that includes a second RF coil rigidly positioned close to the receive coil so that there was constant mutual inductance between them. The artificial signal was transmitted through the second RF coil and acquired by the receive coil in parallel with the real signal. Our results demonstrate that the calibration factor is immune to changes in sample resistance. This is a key advantage because it removes the cumbersome requirement that coil loading conditions be the same for the calibration sample as for experimental samples. The method should be adaptable to human studies and could allow more practical and accurate quantification of metabolite content.
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http://dx.doi.org/10.1016/j.jmr.2008.05.022 | DOI Listing |
Arthritis Res Ther
December 2024
Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, National Clinical Research Center for Dermatologic and Immunologic Diseases (NCRC-DID), Ministry of Science & Technology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Key Laboratory of Rheumatology and Clinical Immunology, Ministry of Education, Beijing, China.
Background: Thrombocytopenia (TP) is a hematological manifestation of systemic lupus erythematosus (SLE) and is associated with unfavorable prognostic outcomes. This study aimed to develop a risk prediction model for new-onset TP in SLE patients.
Methods: Based on the multicenter prospective Chinese SLE Treatment and Research Group (CSTAR) registry, newly diagnosed SLE patients without TP at registration were enrolled.
BMC Health Serv Res
December 2024
Western Sydney University, School of Computer, Data and Mathematical Sciences, Sydney, Australia.
Background: China is currently at a turning point as its total population has started to decline, and therefore faces issues related to caring for an ageing population, which will require an increase in Total Health Expenditure (THE). Therefore, the ability to forecast China's future THE is essential.
Methods: We developed two THE System Dynamics (SD) models using Stella Architect 3.
World J Surg Oncol
December 2024
Department of Hospital Infection Management and Preventive Health Care, Zhejiang Provincial People's Hospital Bijie Hospital, Bijie, 551799, China.
Introduction: Although the Tumor-Node-Metastasis (TNM) staging system is widely used for staging lung squamous cell carcinoma (LSCC), the TNM system primarily emphasizes tumor size and metastasis, without adequately considering lymph node involvement. Consequently, incorporating lymph node metastasis as an additional prognostic factor is essential for predicting outcomes in LSCC patients.
Methods: This retrospective study included patients diagnosed with LSCC between 2004 and 2018 and was based on data from the Surveillance, Epidemiology, and End Results (SEER) database of the National Cancer Institute.
BMC Pulm Med
December 2024
Department of Infectious Diseases, Fujian Shengli Medical College, Fujian Medical University, Fuzhou University Affiliated Provincial Hospital, Fuzhou, China.
Purpose: Available research indicates that the mammalian target of rapamycin complex 1 (mTORC1) signaling pathway is significantly correlated with lung cancer brain metastasis (BM). This study established a clinical predictive model for assessing the risk of BM based on the mTORC1-related single nucleotide polymorphisms (SNPs).
Methods: In this single-center retrospective study, 395 patients with non-small cell lung cancer were included.
J Racial Ethn Health Disparities
December 2024
Department of Biostatistics and Epidemiology, College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
Background: The Charlson Comorbidity Index (CCI) is a frequently used mortality predictor based on a scoring system for the number and type of patient comorbidities health researchers have used since the late 1980s. The initial purpose of the CCI was to classify comorbid conditions, which could alter the risk of patient mortality within a 1-year time frame. However, the CCI may not accurately reflect risk among American Indians because they are a small proportion of the US population and possibly lack representation in the original patient cohort.
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