Purpose: MR temperature monitoring of mild radiofrequency hyperthermia (RF-HT) of cancer exploits the linear resonance frequency shift of water with temperature. Motion-induced susceptibility distribution changes cause artifacts that we correct here using the total field inversion (TFI) approach.
Methods: The performance of TFI was compared to two background field removal (BFR) methods: Laplacian boundary value (LBV) and projection onto dipole fields (PDF). Data sets with spatial susceptibility change and -drift were simulated, phantom heating experiments were performed, four volunteer data sets at thermoneutral conditions as well as data from one cervical cancer, two sarcoma, and one seroma patients undergoing mild RF-HT were corrected using the proposed methods.
Results: Simulations and phantom heating experiments revealed that using BFR or TFI preserves temperature-induced phase change, while removing susceptibility artifacts and -drift. TFI resulted in the least cumulative error for all four volunteers. Temperature probe information from four patient data sets were best depicted by TFI-corrected data in terms of accuracy and precision. TFI also performed best in case of the sarcoma treatment without temperature probe.
Conclusion: TFI outperforms previously suggested BFR methods in terms of accuracy and robustness. While PDF consistently overestimates susceptibility contribution, and LBV removes valuable pixel information, TFI is more robust and leads to more accurate temperature estimations.
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http://dx.doi.org/10.1002/mrm.29191 | DOI Listing |
Cancer Genet
December 2024
Department of Otolaryngology, University of Minnesota, MMC396, 420 Delaware St SE, Minneapolis, MN 55455, USA.
Objective: Studies of squamous cell carcinoma of the head and neck (HNSCC) have demonstrated the importance of nuclear receptors and their associated coregulators in the development and treatment of HNSCC. We sought to characterize members of the nuclear receptor super family through interrogation of RNA-Seq and microarray data.
Materials And Methods: TCGA RNA-Seq data within the cBioportal platform comparing HNSCC samples (n = 515 patients with RNA-Seq data) to normal tissue (n = 82 patients) was interrogated for significant differences in nuclear receptor expression.
Curr Opin Plant Biol
January 2025
Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA.
Plant diseases constantly threaten crops and food systems, while global connectivity further increases the risks of spreading existing and exotic pathogens. Here, we first explore how an integrative approach involving plant pathway knowledgegraphs, differential gene expression data, and biochemical data informing Raman spectroscopy could be used to detect plant pathways responding to pathogen attacks. The Plant Reactome (https://plantreactome.
View Article and Find Full Text PDFLifetime Data Anal
January 2025
Institut Camille Jordan, UMR 5208, Université Claude Bernard Lyon 1, Bat. Braconnier, 43, blvd du 11 novembre 1918, F - 69622, Villeurbanne Cedex, France.
Based on the expectile loss function and the adaptive LASSO penalty, the paper proposes and studies the estimation methods for the accelerated failure time (AFT) model. In this approach, we need to estimate the survival function of the censoring variable by the Kaplan-Meier estimator. The AFT model parameters are first estimated by the expectile method and afterwards, when the number of explanatory variables can be large, by the adaptive LASSO expectile method which directly carries out the automatic selection of variables.
View Article and Find Full Text PDFJ Chem Inf Model
January 2025
Department of Urology, Ji'an Third People's Hospital, Ji'an 343000, Jiangxi, China.
As combination therapy becomes more common in clinical applications, predicting adverse effects of combination medications is a challenging task. However, there are three limitations of the existing prediction models. First, they rely on a single view of the drug and cannot fully utilize multiview information, resulting in limited performance when capturing complex structures.
View Article and Find Full Text PDFMol Ecol Resour
January 2025
Section for Molecular Ecology and Evolution, Globe Institute, University of Copenhagen, Copenhagen, Denmark.
Reduced representation sequencing (RRS) has proven to be a cost-effective solution for sequencing subsets of the genome in non-model species for large-scale studies. However, the targeted nature of RRS approaches commonly introduces large amounts of missing data, leading to reduced statistical power and biased estimates in downstream analyses. Genotype imputation, the statistical inference of missing sites across the genome, is a powerful alternative to overcome the caveats associated with missing sites.
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