Purpose Of Review: To highlight the recent literature on the use of hyperspectral imaging (HSI) for cancer margin evaluation ex vivo, for head and neck cancer pathology and in vivo during head and neck cancer surgery.
Recent Findings: HSI can be used ex vivo on unstained and stained tissue sections to analyze head and neck tissue and tumor cells in combination with machine learning approaches to analyze head and neck cancer cell characteristics and to discriminate the tumor border from normal tissue. Data on in vivo applications during head and neck cancer surgery are preliminary and limited. Even now an accuracy of 80% for tumor versus nonneoplastic tissue classification can be achieved for certain tasks, within the current in vivo settings.
Summary: Significant progress has been made to introduce HSI for ex vivo head and neck cancer pathology evaluation and for an intraoperative use to define the tumor margins. To optimize the accuracy for in vivo use, larger HSI databases with annotations for head and neck cancer are needed.
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http://dx.doi.org/10.1097/MOO.0000000000000957 | DOI Listing |
Mol Cancer
January 2025
Foshan Maternity and Child Healthcare Hospital; School of Pharmaceutical Sciences, Southern Medical University, Guangzhou, 515150, China.
Background: Intratumor-resident bacteria represent an integral component of the tumor microenvironment (TME). Microbial dysbiosis, which refers to an imbalance in the bacterial composition and bacterial metabolic activities, plays an important role in regulating breast cancer development and progression. However, the impact of specific intratumor-resident bacteria on tumor progression and their underlying mechanisms remain elusive.
View Article and Find Full Text PDFBMC Cancer
January 2025
Department of Tumor Biology and Genetics, Medical University of Warsaw, Warsaw, Poland.
Aim: The study was designed to evaluate molecular alterations, relevant to the prognosis and personalized therapy of salivary gland cancers (SGCs).
Materials And Methods: DNA was extracted from archival tissue of 40 patients with various SGCs subtypes. A targeted next-generation sequencing (NGS) panel was used for the identification of small-scale mutations, focal and chromosomal arm-level copy number changes.
Nat Med
January 2025
Department of Neurosurgery, NYU Langone Health, New York, NY, USA.
The adoption of large language models (LLMs) in healthcare demands a careful analysis of their potential to spread false medical knowledge. Because LLMs ingest massive volumes of data from the open Internet during training, they are potentially exposed to unverified medical knowledge that may include deliberately planted misinformation. Here, we perform a threat assessment that simulates a data-poisoning attack against The Pile, a popular dataset used for LLM development.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, MD, USA.
This study addresses the limited noninvasive tools for Head and Neck Squamous Cell Carcinoma (HNSCC) progression-free survival (PFS) prediction by identifying Computed Tomography (CT)-based biomarkers for predicting prognosis. A retrospective analysis was conducted on data from 203 HNSCC patients. An ensemble feature selection involving correlation analysis, univariate survival analysis, best-subset selection, and the LASSO-Cox algorithm was used to select functional features, which were then used to build final Cox Proportional Hazards models (CPH).
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