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Filename: controllers/Detail.php
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File: /var/www/html/application/controllers/Detail.php
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File: /var/www/html/index.php
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Filename: controllers/Detail.php
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Filename: controllers/Detail.php
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Despite sharing the same histologic classification, individual tumors in multi metastatic patients may present with different characteristics and varying sensitivities to anticancer therapies. In this study, we investigate the utility of radiomic biomarkers for prediction of lesion-specific treatment resistance in multi metastatic leiomyosarcoma patients. Using a dataset of n=202 lung metastases (LM) from n=80 patients with 1648 pre-treatment computed tomography (CT) radiomics features and LM progression determined from follow-up CT, we developed a radiomic model to predict the progression of each lesion. Repeat experiments assessed the relative predictive performance across LM volume groups. Lesion-specific radiomic models indicate up to a 4.5-fold increase in predictive capacity compared with a no-skill classifier, with an area under the precision-recall curve of 0.70 for the most precise model (FDR = 0.05). Precision varied by administered drug and LM volume. The effect of LM volume was controlled by removing radiomic features at a volume-correlation coefficient threshold of 0.20. Predicting lesion-specific responses using radiomic features represents a novel strategy by which to assess treatment response that acknowledges biological diversity within metastatic subclones, which could facilitate management strategies involving selective ablation of resistant clones in the setting of systemic therapy.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10593058 | PMC |
http://dx.doi.org/10.1101/2023.09.22.23294942 | DOI Listing |
Heart Lung Circ
December 2024
National Heart Center Singapore, Singapore, Singapore; Duke-NUS Medical School, Singapore, Singapore; Department of Biomedical Engineering, National University of Singapore, Singapore, Singapore. Electronic address:
Aim: Physician visual assessment (PVA) in invasive coronary angiography (ICA) is clinically used to determine stenosis severity and guide coronary intervention. However, PVA provides limited information regarding the haemodynamic significance of stenosis. This prospective study aimed to develop a model combining visual diameter stenosis (DS) and quantitative coronary angiography (QCA)-derived parameters to diagnose ischaemic lesions using invasive fractional flow reserve (FFR) with pharmacologically induced maximal hyperaemia as the gold standard.
View Article and Find Full Text PDFJ Cardiovasc Comput Tomogr
October 2024
Klinik für Herz- und Kreislauferkrankungen, Deutsches Herzzentrum München, Klinik an der Technischen Universität München, Lazarettstrasse 36, 80636 Munich, Germany. Electronic address:
Purpose: To characterize preprocedural coronary atherosclerotic lesions derived from CCTA and assess their association with in-stent restenosis (ISR) after percutaneous coronary intervention (PCI).
Materials And Methods: This retrospective cohort-study included patients who underwent CCTA for suspected coronary artery disease, subsequent index angiography including PCI and surveillance angiography within 6-8 months after the index procedure. We performed a plaque analysis of culprit lesions on CCTA using a dedicated plaque analysis software including assessment of the surrounding pericoronary fat attenuation index (FAI) and compared findings between lesions with and without ISR at surveillance angiography after stenting.
Eur Heart J
October 2024
Department of Cardiology, Boston Children's Hospital, Boston, MA, USA.
Comput Methods Programs Biomed
December 2024
Department of Electronics Information and Bioengineering, Politecnico di Milano, Milan, Italy.
Background And Objective: Invasive fractional flow reserve (FFR) measurement is the gold standard method for coronary artery disease (CAD) diagnosis. FFR-CT exploits computational fluid dynamics (CFD) for non-invasive evaluation of FFR, simulating coronary flow in virtual geometries reconstructed from computed tomography (CT), but suffers from cost-intensive computing process and uncertainties in the definition of patient specific boundary conditions (BCs). In this work, we investigated the use of time-averaged steady BCs, compared to pulsatile to reduce the computational time and deployed a self-adjusting method for the tuning of BCs to patient-specific clinical data.
View Article and Find Full Text PDFJACC Cardiovasc Interv
September 2024
Department of Cardiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China. Electronic address:
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