Systematic imaging can be broadly defined as the systematic identification and characterization of biological processes at multiple scales and levels. In contrast to "classical" diagnostic imaging, systematic imaging emphasizes on detecting the overall abnormalities including molecular, functional, and structural alterations occurring during disease course in a systematic manner, rather than just one aspect in a partial manner. Concomitant efforts including improvement of imaging instruments, development of novel imaging agents, and advancement of artificial intelligence are warranted for achievement of systematic imaging. It is undeniable that scientists and radiologists will play a predominant role in directing this burgeoning field. This article introduces several recent developments in imaging modalities and nanoparticles-based imaging agents, and discusses how systematic imaging can be achieved. In the near future, systematic imaging which combines multiple imaging modalities with multimodal imaging agents will pave a new avenue for comprehensive characterization of diseases, successful achievement of image-guided therapy, precise evaluation of therapeutic effects, and rapid development of novel pharmaceuticals, with the final goal of improving human health-related outcomes.
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http://dx.doi.org/10.1007/s00259-020-05107-z | DOI Listing |
Biomed Phys Eng Express
January 2025
School of Engineering and Computing, University of the West of Scotland, University of the West of Scotland - Paisley Campus, Paisley PA1 2BE, UK, City, Paisley, PA1 2BE, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND.
Cancer grade classification is a challenging task identified from the cell structure of healthy and abnormal tissues. The partitioner learns about the malignant cell through the grading and plans the treatment strategy accordingly. A major portion of researchers used DL models for grade classification.
View Article and Find Full Text PDFBiomed Phys Eng Express
January 2025
Department of Ophthalmology, Hospital Universitario de Canarias, Carretera Ofra S/N, La Laguna, Santa Cruz de Tenerife, 38320, SPAIN.
This paper systematically evaluates saliency methods as explainability tools for convolutional neural networks trained to diagnose glaucoma using simplified eye fundus images that contain only disc and cup outlines. These simplified images, a methodological novelty, were used to relate features highlighted in the saliency maps to the geometrical clues that experts consider in glaucoma diagnosis. Despite their simplicity, these images retained sufficient information for accurate classification, with balanced accuracies ranging from 0.
View Article and Find Full Text PDFBiomed Phys Eng Express
January 2025
Shandong University of Traditional Chinese Medicine, Qingdao Academy of Chinese Medical Sciences, Jinan, Shandong, 250355, CHINA.
Mild cognitive impairment (MCI) is a significant predictor of the early progression of Alzheimer's disease, and it can be used as an important indicator of disease progression. However, many existing methods focus mainly on the image itself when processing brain imaging data, ignoring other non-imaging data (e.g.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
January 2025
Department of Immunology and Regenerative Biology, Weizmann Institute of Science, Rehovot 7610001, Israel.
Malignant gliomas are heterogeneous tumors, mostly incurable, arising in the central nervous system (CNS) driven by genetic, epigenetic, and metabolic aberrations. Mutations in isocitrate dehydrogenase (IDH1/2) enzymes are predominantly found in low-grade gliomas and secondary high-grade gliomas, with IDH1 mutations being more prevalent. Mutant-IDH1/2 confers a gain-of-function activity that favors the conversion of a-ketoglutarate (α-KG) to the oncometabolite 2-hydroxyglutarate (2-HG), resulting in an aberrant hypermethylation phenotype.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Neurology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
Purpose: A relative afferent pupillary defect (RAPD) is a characteristic clinical sign of optic neuritis (ON). Here, we systematically evaluated ultrasound pupillometry (UP) for the detection of an RAPD in patients with ON, including a comparison with infrared video pupillometry (IVP), the gold standard for objective pupillometry.
Materials And Methods: We enrolled 40 patients with acute (n = 9) or past (n = 31) ON (ON+), 31 patients with multiple sclerosis (MS) without prior ON, and 50 healthy controls (HC) in a cross-sectional observational study.
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