We present a non-invasive (albeit contact) method based on Optical Coherence Elastography (OCE) enabling the in vivo segmentation of morphological tissue constituents, in particular, monitoring of morphological alterations during both tumor development and its response to therapies. The method uses compressional OCE to reconstruct tissue stiffness map as the first step. Then the OCE-image is divided into regions, for which the Young's modulus (stiffness) falls in specific ranges corresponding to the morphological constituents to be discriminated. These stiffness ranges (characteristic "stiffness spectra") are initially determined by careful comparison of the "gold-standard" histological data and the OCE-based stiffness map for the corresponding tissue regions. After such pre-calibration, the results of morphological segmentation of OCE-images demonstrate a striking similarity with the histological results in terms of percentage of the segmented zones. To validate the sensitivity of the OCE-method and demonstrate its high correlation with conventional histological segmentation we present results obtained in vivo on a murine model of breast cancer in comparative experimental study of the efficacy of two antitumor chemotherapeutic drugs with different mechanisms of action. The new technique allowed in vivo monitoring and quantitative segmentation of (1) viable, (2) dystrophic, (3) necrotic tumor cells and (4) edema zones very similar to morphological segmentation of histological images. Numerous applications in other experimental/clinical areas requiring rapid, nearly real-time, quantitative assessment of tissue structure can be foreseen.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7366713 | PMC |
http://dx.doi.org/10.1038/s41598-020-68631-w | DOI Listing |
Cancers (Basel)
December 2024
Department of Urology, Korea University Guro Hospital, Korea University College of Medicine, Seoul 08308, Republic of Korea.
Background/objectives: Cystoscopy is necessary for diagnosing bladder cancer, but it has limitations in identifying ambiguous lesions, such as carcinoma in situ (CIS), which leads to a high recurrence rate of bladder cancer. With the significant advancements in deep learning in the medical field, several studies have explored its application in cystoscopy. This study aimed to utilize the VGG19 and Deeplab v3+ deep learning models to classify and segment cystoscope images, respectively.
View Article and Find Full Text PDFDiagnostics (Basel)
December 2024
Department of Anatomy, School of Medicine, Faculty of Health Sciences, National and Kapodistrian University of Athens, Goudi, 11 527 Athens, Greece.
: The caroticoclinoid bar (CCB) or caroticoclinoid foramen (CCF) represents a well-described ossified variant of the skull base. It corresponds to an osseous bridge (resulting after homonymous ligament ossification) between the anterior and middle clinoid processes (ACPs and MCPs) surrounding the internal carotid artery (ICA)'s cavernous segment. Although extensive research has been performed on this clinically significant entity, only a few studies have been conducted on its effect on the ICA.
View Article and Find Full Text PDFPlants (Basel)
January 2025
Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China.
The Tianshan wild fruit forest region is a vital repository of plant biodiversity, particularly rich in the unique genetic resources of endemic medicinal plants in this ecological niche. However, human activities such as unregulated mining and excessive grazing have led to a significant reduction in the diversity of these medicinal plants. This study represents the first application of DNA barcoding to 101 medicinal plants found in the Tianshan wild fruit forests, using three genetic loci along with morphological identification methods.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Orthopaedic Surgery and Traumatology, Bern University Hospital, Inselspital, University of Bern, Bern, Switzerland.
Scapular morphological attributes show promise as prognostic indicators of retear following rotator cuff repair. Current evaluation techniques using single-slice magnetic-resonance imaging (MRI) are, however, prone to error, while more accurate computed tomography (CT)-based three-dimensional techniques, are limited by cost and radiation exposure. In this study we propose deep learning-based methods that enable automatic scapular morphological analysis from diagnostic MRI despite the anisotropic resolution and reduced field of view, compared to CT.
View Article and Find Full Text PDFJ Magn Reson Imaging
January 2025
Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Osteoarthritis (OA) is heterogeneous and involves structural changes in the whole joint, such as cartilage, meniscus/labrum, ligaments, and tendons, mainly with short T2 relaxation times. Detecting OA before the onset of irreversible changes is crucial for early proactive management and limit growing disease burden. The more recent advanced quantitative imaging techniques and deep learning (DL) algorithms in musculoskeletal imaging have shown great potential for visualizing "pre-OA.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!