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Predicting benefit from PARP inhibitors using deep learning on H&E-stained ovarian cancer slides.
Eur J Cancer
December 2024
Division of Digital Prevention, Diagnostics and Therapy Guidance, German Cancer Research Center (DKFZ), Heidelberg, Germany. Electronic address:
Article Synopsis
- Ovarian cancer patients with Homologous Recombination Deficiency (HRD) may benefit from PARP inhibitor therapy after platinum chemotherapy, and predicting this benefit through whole slide images (WSIs) could provide a quicker and less costly alternative to molecular tests.
- A Deep Learning (DL) model was trained on H&E stained WSIs using a specific HRD ground truth, and it was tested on a separate cohort to see how well it predicted HRD status and the benefit of olaparib treatment.
- Although the model showed potential, with a significant improvement in progression-free survival (PFS) for HRD positive patients treated with PARP inhibitors, its overall prediction accuracy was lower than desired, indicating that further
Is framing of treatment options misleading? Maybe, but not because of a lower-bound reading.
J Med Ethics
December 2024
Philosophy and Religious Studies, Utrecht University, Utrecht, The Netherlands
In a recent paper, Yeo argues that the framing of treatment options by physicians in the contexts of patient's decision-making conflicts with a physician's duty of disclosure. I argue that this conclusion is drawn too quickly, as it is questionable whether the empirical research on which Yeo relies is applicable to the framing of treatment options. This means that Yeo's main assumption is undermined, and we should hold off on concluding that the framing of treatment options is misleading.
View Article and Find Full Text PDFPortable head CT motion artifact correction via diffusion-based generative model.
Comput Med Imaging Graph
December 2024
Center for Advanced Medical Computing and Analysis, Massachusetts General Hospital and Harvard Medical School, Boston, United States. Electronic address:
Portable head CT images often suffer motion artifacts due to the prolonged scanning time and critically ill patients who are unable to hold still. Image-domain motion correction is attractive for this application as it does not require CT projection data. This paper describes and evaluates a generative model based on conditional diffusion to correct motion artifacts in portable head CT scans.
View Article and Find Full Text PDFDrone-Based Digital Phenotyping to Evaluating Relative Maturity, Stand Count, and Plant Height in Dry Beans ( L.).
Plant Phenomics
November 2024
Department of Plant, Soil, and Microbial Sciences, Michigan State University, East Lansing, MI 48824, USA.
Article Synopsis
- This study investigates the use of RGB drone imagery and deep learning techniques to assess plant maturity, stand count, and height, comparing these methods with traditional practices for improved efficiency and accuracy.
- A hybrid CNN-LSTM model was developed to predict relative maturity of dry beans, while the Faster R-CNN algorithm was utilized to detect early-stage plant counts, both demonstrating superior performance over conventional methods.
- The research indicates that combining drone data with environmental factors like growing degree days enhances model accuracy, and offers tools and software that could greatly benefit researchers in plant phenotyping.
Quantitative mapping of cerebrovascular reactivity amplitude and delay with breath-hold BOLD fMRI when end-tidal CO quality is low.
bioRxiv
November 2024
Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
Cerebrovascular reactivity (CVR), the ability of cerebral blood vessels to dilate or constrict in order to regulate blood flow, is a clinically useful measure of cerebrovascular health. CVR is often measured using a breath-hold task to modulate blood CO levels during an fMRI scan. Measuring end-tidal CO (PCO) with a nasal cannula during the task allows CVR amplitude to be calculated in standard units (vascular response per unit change in CO, or %BOLD/mmHg) and CVR delay to be calculated in seconds.
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